Blueberry Cobbler – My Bizzy Kitchen

By electricdiet / August 8, 2021


This blueberry cobbler was requested by so many people when I asked for blueberry recipes that you wanted lightened up.  So happy because this is delicious!

this is a photo of blueberry cobbler

What is a cobbler?

Cobblers can vary depending on where you live.  Some cobblers have a biscuit like topping, but I made my cobbler with a cake like base.  Actually I used an old pancake recipe on my blog to make the cake and it is so light and delicious.  Note, the cake is not overly sweet, so feel free to add additional no calorie sweetener to your taste.  With the sweet blueberry topping though, I think this is the perfect combination.

What ingredients do you need to make a cobbler?

You may already have many of the ingredients in your pantry to make this cobbler:

  • flour
  • no calorie sweetener (I used Truvia)
  • baking powder
  • salt
  • lemon juice
  • unsweetened almond milk
  • light butter
  • blueberries
  • sugar
  • cornstarch

How do you make a cobbler?

Simply mix the batter together and place in a 1.5 quart baking dish.  Mix the berry topping and place on top of the batter.  This literally comes together in five minutes.  Then bake and enjoy!

Ingredients

  • For the batter:
  • 1.25 cups flour
  • 1/4 cup no calorie sweetener (I used Truvia)
  • 2 teaspoons baking powder
  • 1/2 teaspoon salt
  • 1 teaspoon lemon juice
  • 1 cup unsweetened almond milk (any milk works)
  • 2 tablespoons melted light butter (I used I Can’t Believe It’s Not Butter Light)
  • 1 tablespoon decorative sugar (or coarse sugar)
  • For the berries:
  • 3 cups blueberries, rinsed and patted dry
  • 1 tablespoon sugar
  • 1 teaspoon lemon juice
  • 1 tablespoon cornstarch

Instructions

  1. Mix the flour through melted butter for the batter. Place in a 1.5 quart casserole dish. Sprinkle with the one tablespoon sugar.
  2. Mix the blueberries through cornstarch together. Place on top of the batter.
  3. Bake at 375 for 45 minutes.

Notes

On all WW plans, each serving is 4 points.

Nutrition Information:

Yield: 6

Serving Size: 1

Amount Per Serving:

Calories: 191Total Fat: 4gSaturated Fat: 2gTrans Fat: 0gUnsaturated Fat: 1gCholesterol: 5mgSodium: 362mgCarbohydrates: 38gFiber: 3gSugar: 12gProtein: 4g


Did you make this recipe?

Please leave a comment on the blog or share a photo on Instagram

Don’t like blueberries?  Use your favorite fruit:  peaches, raspberries, strawberries would all be delicious.

Let me know if you try this.  If you love blueberries, check out my blueberry cottage cheese pancakes – so good!

Biz

I am a widowed 52 year old trying to figure out my life after losing my husband after a long illness.

Cooking and being in the kitchen feeds my soul!





Sell Unused Diabetic Strips Today!

Dutch Oven Chicken | Diabetes Strong

By electricdiet / August 6, 2021


This Dutch oven chicken recipe is one of the best ways to roast an entire bird. You’ll get crispy, seasoned skin on the outside and tender, juicy meat on the inside every time.

Dutch oven chicken on a white plate next to thyme sprigs and garnished with two lemon slices

When done properly, a whole roast chicken can be a show-stealer. Of course, the key is to avoid letting the meat dry out while also making sure that the skin has enough time to crisp up.

That’s why I love making this Dutch oven chicken recipe! It’s so simple, and you get juicy, tender chicken with crispy skin every time. Prep only takes a few minutes, and then the Dutch oven does all the hard work for you.

How to make Dutch oven chicken

This recipe comes together in just a few easy steps. Let’s see how it’s done!

Step 1: Preheat the oven to 400°F.

Step 2: In a small bowl, mix together the butter, salt, dried thyme, garlic powder, paprika, and pepper until a paste forms.

Butter, salt, dried thyme, garlic powder, paprika, and pepper combined into a paste in a ramekin

Step 3: Spread the butter mixture over the outside of the whole chicken and in the body cavity.

Butter and spice mixture rubbed over the whole chicken, as seen from above

Step 4: Stuff the chicken cavity with thyme, onion, lemon, and garlic cloves.

Step 5: Spread the rest of the garlic, lemons, onion, and fresh thyme in the bottom of a Dutch oven. Add the water, then place the chicken on top.

Buttered chicken placed on top of onions, lemons, and herbs in a dutch oven, as seen from above

Step 6: Cover the Dutch oven with the lid, then bake for 40 minutes.

Step 7: Remove the lid and continue baking for an additional 45 minutes to an hour, or until a thermometer inserted into the thickest part of the chicken breast reads at least 165°F.

Step 8: Remove the chicken from the oven and allow it to rest for at least 10 minutes.

Whole chicken finished baking and resting in the dutch oven, as seen from above

As the meat rests, the muscle fibers will relax and reabsorb some of the juices they released while cooking. This ensures your chicken won’t turn out dry, so always make sure you give it time to rest!

Whole chicken finished cooking and resting in the dutch oven on top of a decorative striped napkin

What to serve with this chicken recipe

While your chicken is roasting, that’s a great time to prepare some phenomenal sides to complement your meal. If you’re looking for inspiration, I have a few ideas for you.

For something simple yet flavorful, you can never go wrong with eggplant caprese salad. The balsamic drizzle really takes the presentation to the next level.

I also love these low-carb stuffed mushrooms. They’re packed with melted cheesy goodness and always a crowd pleaser!

For a heartier side, you can’t go wrong with keto broccoli casserole. And a batch of low-carb cornbread to soak up any extra sauce is always a good idea!

Whole chicken on a white plate next to sprigs of thyme and garnished with two lemon slices, as seen from above

Storage

If you find yourself with leftovers, you can store them in an airtight container in the refrigerator for up to three days. I recommend reheating in the microwave or in a covered dish in the oven until heated through.

Looking for longer storage? The chicken will stay fresh in an airtight container in the freezer for up to three months!

Whole chicken on a white plate next to sprigs of thyme and garnished with two lemon slices, as seen from above

Other delicious chicken recipes

From quick weeknight dinners to special celebrations to holiday feasts, there’s truly a chicken recipe for every occasion. Want to shake up your routine? Here are a few of my favorite healthy chicken recipes I know you’ll love:

If you’re looking for even more ideas, check out this roundup of my favorite Healthy Diabetic Chicken Recipes!

When you’ve tried this dish, don’t forget to let me know how you liked it and rate the recipe in the comments below!

Recipe Card

Dutch Oven Chicken

This Dutch oven chicken recipe is one of the best ways to roast an entire bird. You’ll get crispy, seasoned skin on the outside and tender, juicy meat on the inside every time.

Prep Time:10 minutes

Cook Time:1 hour 30 minutes

Rest Time:10 minutes

Total Time:1 hour 50 minutes

Dutch oven chicken on a white plate next to thyme sprigs and garnished with two lemon slices

Instructions

  • Preheat the oven to 400°F.

  • In a small bowl, mix together the butter, salt, dried thyme, garlic powder, paprika, and pepper until a paste forms.

  • Spread the butter mixture over the outside of the whole chicken and in the body cavity.

  • Stuff the chicken cavity with thyme, onion, lemon, and garlic cloves.

  • Spread the rest of the garlic, lemons, onion, and fresh thyme in the bottom of a Dutch oven. Add the water, then place the chicken on top.

  • Cover the Dutch oven with the lid, then bake for 40 minutes.

  • Remove the lid and continue baking for an additional 45 minutes to an hour, or until a thermometer inserted into the thickest part of the chicken breast reads at least 165°F.

  • Remove the chicken from the oven and allow it to rest for at least 10 minutes.

Recipe Notes

This recipe is for 1 whole chicken. Each serving is roughly ¼ of the chicken.
Leftovers can be stored in an airtight container in the refrigerator for up to 3 days or in the freezer for up to 3 months.

Nutrition Info Per Serving

Nutrition Facts

Dutch Oven Chicken

Amount Per Serving (0.25 chicken)

Calories 469
Calories from Fat 83

% Daily Value*

Fat 9.2g14%

Saturated Fat 3.6g18%

Trans Fat 0g

Polyunsaturated Fat 0.3g

Monounsaturated Fat 1.7g

Cholesterol 223.3mg74%

Sodium 535.7mg22%

Potassium 154.7mg4%

Carbohydrates 11g4%

Fiber 3.4g14%

Sugar 1.2g1%

Protein 84.8g170%

Net carbs 7.6g

* Percent Daily Values are based on a 2000 calorie diet.

Course: Main Course

Cuisine: American

Diet: Diabetic, Gluten Free

Keyword: dairy-free, Dutch oven chicken, gluten-free, low carb, roast chicken, whole chicken



Sell Unused Diabetic Strips Today!

Fresh Fig Cake Moist & Amazing+Fresh Fig Recipes! When is Fig Season?

By electricdiet / August 4, 2021


Moist and delicious, Fresh Fig Cake is an all-time favorite fresh fig recipe in Holly’s cookbook, Eating Well to Fight Arthritis.  Who doesn’t like fresh easy fig recipes? You might be wondering when is fig season? The season is really from late summer to fall which is August until October, however you will find some fresh figs in early summer. Give Holly’s popular fresh fig cake moist recipe a try because her whole cookbook has a focus on anti inflammatory recipes.  This mouth-watering cake even has nutritious benefits as it is diabetic-friendly and high in potassium and fiber.

fresh fig bundt cake

Fresh Fig Cake
Now, if you are one of those that turn up your nose to fresh figs, this Fresh Fig Cake will instantly change your mind.  The recipe is from Eating Well to Fight Arthritis.  I honestly couldn’t wait to include this recipe in one of my cookbooks. Actually, lots of people have asked me for fresh fig recipes.

    Servings20 servings

    Ingredients

    • 1/3cup


      canola oil

    • 1 1/2cups


      sugar

    • 1teaspoon


      vanilla extract

    • 2


      eggs

    • 1


      egg white

    • 2cups


      all-purpose flour

    • 1teaspoon


      baking soda

    • 1 1/2teaspoons


      ground cinnamon

    • 1cup


      buttermilk

    • 1cup


      coarsely chopped fresh figsstems removed

    • 1/2cup


      chopped pecans



    • Glaze

    Instructions
    1. Preheat oven 350°F. Coat Bundt pan with nonstick cooking spray.


    2. In mixing bowl, cream oil, sugar, and vanilla. Add eggs and egg white, one at a time, beating well after each addition until creamy.


    3. In small bowl, combine flour, baking soda, and cinnamon. Add flour mixture to sugar mixture, alternating with buttermilk and ending with flour. Beat after each addition.


    4. Stir in figs and pecans. Bake 40-45 minutes, until top springs back when touched. Then, let cake cool 10 minutes and then invert onto serving plate. Next, pour Glaze (recipe follows) over hot cake.

    Recipe Notes

    Calories 194, Calories from Fat 32%, Fat 7g, Saturated Fat 1g, Cholesterol 21g, Sodium 11mg, Carbohydrates 30g, Dietary Fiber 1g, Total Sugars 20g, Protein 3g, Diabetic Exchanges: 2 other carbohydrate, 1 1/2 fat

    Terrific Tip: Fresh dates may be used for figs. If using dried figs, it might not be quite as moist, but I am sure as good.

    Glaze

      Ingredients

      • 1/4cup


        sugar

      • 2teaspoons


        light corn syrup

      • 1tablespoon


        butter

      • 1/4cup


        buttermilk

      • 1/4teaspoon


        baking soda

      • 1/2teaspoon


        vanilla extract

      Instructions
      1. In small nonstick pot, combine all ingredients except vanilla and bring to boil 4 minutes over medium heat, stirring constantly. Add vanilla and pour over hot cake.

      Recipe Notes

      Per Serving: Calories 194, Protein (g) 3, Carbohydrate (g) 30, Fat (g) 7, Calories from Fat (%) 32, Saturated Fat (g) 1, Dietary Fiber (g) 1, Sugar (g) 20, Cholesterol (mg) 21, Sodium (mg) 111 Diabetic Exchanges: 2 other carbohydrates, 1 ½ fat

      Terrific Tidbit: Fresh dates may be substituted or dried fruit.

      Fresh Fig Cake
      Now, if you are one of those that turn up your nose to fresh figs, this Fresh Fig Cake will instantly change your mind.  The recipe is from Eating Well to Fight Arthritis.  I honestly couldn’t wait to include this recipe in one of my cookbooks. Actually, lots of people have asked me for fresh fig recipes.

        Servings20 servings

        Ingredients

        • 1/3cup


          canola oil

        • 1 1/2cups


          sugar

        • 1teaspoon


          vanilla extract

        • 2


          eggs

        • 1


          egg white

        • 2cups


          all-purpose flour

        • 1teaspoon


          baking soda

        • 1 1/2teaspoons


          ground cinnamon

        • 1cup


          buttermilk

        • 1cup


          coarsely chopped fresh figsstems removed

        • 1/2cup


          chopped pecans



        • Glaze

        Instructions
        1. Preheat oven 350°F. Coat Bundt pan with nonstick cooking spray.


        2. In mixing bowl, cream oil, sugar, and vanilla. Add eggs and egg white, one at a time, beating well after each addition until creamy.


        3. In small bowl, combine flour, baking soda, and cinnamon. Add flour mixture to sugar mixture, alternating with buttermilk and ending with flour. Beat after each addition.


        4. Stir in figs and pecans. Bake 40-45 minutes, until top springs back when touched. Then, let cake cool 10 minutes and then invert onto serving plate. Next, pour Glaze (recipe follows) over hot cake.

        Recipe Notes

        Calories 194, Calories from Fat 32%, Fat 7g, Saturated Fat 1g, Cholesterol 21g, Sodium 11mg, Carbohydrates 30g, Dietary Fiber 1g, Total Sugars 20g, Protein 3g, Diabetic Exchanges: 2 other carbohydrate, 1 1/2 fat

        Terrific Tip: Fresh dates may be used for figs. If using dried figs, it might not be quite as moist, but I am sure as good.

        fresh fig cake

        Stock Your Kitchen to Whip Up this Recipe

        KitchenAid Limited Edition Queen of Hearts Stand Mixer, Passion RedKitchenAid Limited Edition Queen of Hearts Stand Mixer, Passion RedKitchenAid Limited Edition Queen of Hearts Stand Mixer, Passion RedKitchenAid Classic Mixing Bowls, Set of 3, PistachioKitchenAid Classic Mixing Bowls, Set of 3, PistachioKitchenAid Classic Mixing Bowls, Set of 3, PistachioNordic Ware Platinum Collection Anniversary Bundt PanNordic Ware Platinum Collection Anniversary Bundt PanNordic Ware Platinum Collection Anniversary Bundt Pan

        Fig Facts To Know To Take Advantage of Fig Season:

        • A fresh fig is lusciously sweet with a slight crunch making them unique and delicious.
        • You may use dried figs or dates, however, this is one of those recipes that fresh is best.
        • They are high in potassium and fiber
        • Fresh figs are perishable so they say 90% are made into dried figs.

        Fresh Fig Recipes Make Healthy Easy Recipe

        Not only is this cake absolutely delicious but this Fig Bundt Cake recipe is a spectacular easy diabetic recipe. Remember, there’s no magical diabetic diet but it is the healthiest way to eat! Holly appeared with arthritis diet recipes on The 700 Club and everyone said these were their favorite to eat.

        Eating Well to Fight Arthritis cookbook, has a “D” that highlights diabetic-friendly recipes throughout the book. You will be surprised by how many of your favorite recipes will also be easy diabetic recipes too.  With Team Holly’s recipes, eating healthy is made easy and fun for you! So, if you are looking for a diabetic diet, this book makes a great choice besides giving you great recipes for an anti inflammatory diet!

        fresh fig cake for fig season with fresh fig recipes for Fig Bundt Cake

        Does Your Bundt Cake Stick in the Pan? Nonstick Bundt Cake Pans Make A Difference

        With a new nonstick Bundt pan it will make such a difference in making sure your cake comes out of the pan without sticking. If you use an old pan and get aggravated when your cake gets stuck it is time for an upgrade! However, Holly always said those were the pieces of cake she got to taste and eat ahead of time – ha!

        You will like this pan but any nonstick Bundt pan works. Also, check out the different shaped holiday Bundt pans.  You’ll make quite the dessert statement.

        More Easy Fig Recipes: Incredible and Delicious Fig Pizza

        Do you like pizza? You may be thinking pizza and figs don’t go together.  Yes, they do and especially during fig season! You will look forward to making this Fig, Caramelized Onion, Prosciutto and Goat Cheese Pizza in Holly’s cookbook, Too Hot in the KitchenThis is another one of those absolutely delicious fresh fig recipes.  Honestly, you must give this delicious fig pizza a try and especially if you enjoy the savory and sweet combination. We are familiar with a fresh fig appetizer with prosciutto and goat cheese however, this pizza has the same fabulous flavors and then you have a healthy fig pizza recipe.

        Where To Find Fresh Figs  for Fresh Fig Recipes

        Fresh make a difference in this cake recipe.  If you have a Trader Joe’s in your area you’ll love these black mission figs if you can’t find fresh at your store. Take advantage of fresh figs in your local store during the season.

        Also, did you know that figs are considered an aphrodisiac? Considered a symbol of fertility and revered as an aphrodisiac, turn pizza into an alluring palate pleasing masterpiece. Just saying!  Maybe another good reason to eat figs!

        How To Can Whole Figs? Get Fresh Fig Recipes During Fig Season

        If you are interested in canning whole figs, check out this blog. According to this great blog on canning whole figs, it is an easy process of water bath canning the fruit in syrup.  Find out how to can whole figs and what to do with them after they are canned. This modern homestead site also features Holly’s famous Fresh Fig Cake on their blog so they know about delicious and easy fig recipes.

        Get All of Holly’s Healthy Easy Cookbooks

        The post Fresh Fig Cake Moist & Amazing+Fresh Fig Recipes! When is Fig Season? appeared first on The Healthy Cooking Blog.



        Sell Unused Diabetic Strips Today!

        Changes in Gut Microbiota Control Metabolic Endotoxemia-Induced Inflammation in High-Fat Diet–Induced Obesity and Diabetes in Mice

        By electricdiet / August 2, 2021


        Abstract

        OBJECTIVE—Diabetes and obesity are characterized by a low-grade inflammation whose molecular origin is unknown. We previously determined, first, that metabolic endotoxemia controls the inflammatory tone, body weight gain, and diabetes, and second, that high-fat feeding modulates gut microbiota and the plasma concentration of lipopolysaccharide (LPS), i.e., metabolic endotoxemia. Therefore, it remained to demonstrate whether changes in gut microbiota control the occurrence of metabolic diseases.

        RESEARCH DESIGN AND METHODS—We changed gut microbiota by means of antibiotic treatment to demonstrate, first, that changes in gut microbiota could be responsible for the control of metabolic endotoxemia, the low-grade inflammation, obesity, and type 2 diabetes and, second, to provide some mechanisms responsible for such effect.

        RESULTS—We found that changes of gut microbiota induced by an antibiotic treatment reduced metabolic endotoxemia and the cecal content of LPS in both high-fat–fed and ob/ob mice. This effect was correlated with reduced glucose intolerance, body weight gain, fat mass development, lower inflammation, oxidative stress, and macrophage infiltration marker mRNA expression in visceral adipose tissue. Importantly, high-fat feeding strongly increased intestinal permeability and reduced the expression of genes coding for proteins of the tight junctions. Furthermore, the absence of CD14 in ob/ob CD14/ mutant mice mimicked the metabolic and inflammatory effects of antibiotics.

        CONCLUSIONS—This new finding demonstrates that changes in gut microbiota controls metabolic endotoxemia, inflammation, and associated disorders by a mechanism that could increase intestinal permeability. It would thus be useful to develop strategies for changing gut microbiota to control, intestinal permeability, metabolic endotoxemia, and associated disorders.

        Environmental factors, such as a fat-enriched diet and a sedentary lifestyle, are the causes of the great prevalence of obesity and type 2 diabetes in the population (1). Diabetes and obesity are characterized by a low-grade inflammation whose molecular origin is unknown (2,3). However, we have recently reported that moderate increase of plasma concentration of the inflammatory reagent, the bacterial lipopolysaccharide (LPS), increased during a fat-enriched diet, and defined metabolic endotoxemia (4). We demonstrated that LPS was responsible for the onset of metabolic diseases (4), because a continuous subcutaneous low-rate infusion of LPS induced most, if not all, of the features of metabolic diseases. Most importantly, the corresponding LPS receptor CD14 knockout mouse resisted the occurrence of the diseases. LPS is a major component of the outer membrane in Gram-negative bacteria. Although the reasons for its increase in plasma during high-fat feeding were undetermined, its levels were closely correlated but not causatively demonstrated, with changes in intestinal microbiota where the Gram negative–to–Gram positive ratio increased during high-fat feeding (4). Furthermore, dietary fibers, which reduce the impact of high-fat diet on the occurrence of the metabolic diseases (5), normalized the Gram negative–to–Gram positive ratio and plasma endotoxemia (6). These data strongly suggested that intestinal microbiota could be responsible for changes of metabolic endotoxemia and for the onset of the corresponding diseases, although the causative link between intestinal bacteria, endotoxemia, and metabolic disease was not shown. Gut microbiota has recently been proposed as an environmental factor involved in the control of body weight and energy homeostasis (712). Germ-free mice of the same age and genetic background as conventional mice fed with a normal chow diet had a 40% lower weight (11), whereas germ-free mice colonized with the gut microbiota derived from the conventional mice increased their fat mass and developed insulin resistance within 2 weeks. In addition, germ-free mice resisted high-fat diet–induced body weight gain and fat mass development and had lower glycemia and insulinemia (9). Strikingly, these data did not provide any result with regard to the impact of the microflora on endotoxemia and inflammation. Altogether, this evidence suggests that changes in intestinal microbial composition could be responsible for increased endotoxemia in response to a high-fat diet, which in turn would trigger the development of obesity and diabetes. Therefore, we aimed at changing the intestinal microbiota by means of an antibiotic treatment to reduce the elevated concentration of plasma LPS in high-fat diet–fed mice and in ob/ob mice. We further studied some mechanisms through which intestinal microbiota changes metabolic endotoxemia and the corresponding metabolic consequences.

        RESEARCH DESIGN AND METHODS

        Twelve-week-old male C57bl6/J mice (Charles River, Lyon, France) and 6-week-old ob/ob (n = 13) mice (C57bl6 background; The Jackson Laboratories, Bar Harbor, ME) were housed in a controlled environment (inverted 12-h daylight cycle, lights-off at 10:00 a.m.) with free access to food and water. The mice were fed a control (n = 13) (A04, Villemoisson sur Orge, France) or a high-fat, carbohydrate-free diet (high fat, n = 17) for 4 weeks. The role of the microflora was investigated by treating control (control antibiotic, n = 13), high-fat–fed (high-fat antibiotic, n = 17), or ob/ob (ob/ob antibiotic, n = 8) mice with antibiotics (1.0 g/l ampicillin [Sigma, St. Louis, MO] and 0.5 g/l neomycin [Sigma] in drinking water) during the experimental period. Ampicillin and neomycin are broad-spectrum antibiotics that are poorly absorbed (or unabsorbed as in the case of neomycin) and thus without any systemic effects (13). The high-fat diet contained 72% fat (corn oil and lard), 28% protein, and <1% carbohydrate, as energy content (5). To generate the ob/ob CD14−/− mice, CD14−/− mice (C57bl6 background) were intercrossed with ob+/−, and F1 double heterozygotes were then used to generate the ob/ob CD14−/− and ob/ob genotypes. All of the following animal experimental procedures were validated by the local ethics committee, by the Rangueil Hospital animal ethics committee, and by the Université catholique de Louvain.

        RNA extraction from cecal contents.

        Bacterial RNAs were extracted from cecal contents using BioRobot-EZ1 (Qiagen, Hilden, Germany), according to the manufacturer’s instructions. In a nutshell, cecal contents were homogenized in a bead beater for 2 min in a sterile microcentrifuge tube containing 0.3 g glass beads and 750 μl QIAzol lysis reagent. After the addition of 150 μl chloroform:isoamylalcohol (24:1), the samples were vortexed for 15 s and left to stand for 2–3 min at room temperature. Finally, the samples were centrifuged at 12,000g for 15 min at 4°C, and 300 μl supernatant was loaded into the BioRobot equipment.

        Denaturing gradient gel electrophoresis profiles of cecal bacteria.

        Bacterial RNA was amplified by RT-PCR targeting the V3 region of the 16S rRNA gene and using the universal bacterial primers HDA1-GC and HDA2 and a previously described program (14) (HDA1-GC, 5′-CGCCCGGGGCGCGCCCCGTGGCGGGGCGGGGGCGCGGGGGGACTCCTACGGGAGGCAGCAGT; and HDA2, 5′-GTATTACCGCGGCTGCTGGCAC-3′). RT-PCR was performed using a Qiagen One-Step RT-PCR kit. Electrophoresis was performed with a DCode apparatus (Bio-Rad) and 6% polyacrylamide gels with a 30–55% gradient of 7 mol/l urea and 40% (vol/vol) formamide, which increased in the direction of electrophoresis. Electrophoretic runs were in a Tris-acetate-EDTA buffer (40 mmol/l Tris, 20 mmol/l acetic acid, and 1 mmol/l EDTA) at 130 V and 60°C for 270 min. Gels were stained with SYBR Safe 1× (Invitrogen) for 30 min, rinsed with deionized water, and viewed by UV transillumination. Denaturing gradient gel electrophoresis (DGGE) profiles were compared by determining the Dice similarity coefficient and using the Bionumerics software package (version 4.01, Applied Maths) at a sensitivity of 1–2%.

        Fecal analyses.

        The content of the cecum was vacuum dried. The remainder of the nondigested carbohydrates, proteins, and lipids were quantified as described previously (15,16). The total LPS content was extracted and measured as described previously (17,18).

        Quantitative RT-PCR quantification of microbial cecal content.

        The cecal contents collected postmortem from mice were stored at −80°C. The QIAamp DNA Stool Minikit (Qiagen) was used to extract DNA from stool sample according to the manufacturer’s instructions. The primers and probes used to detect Bifidobacterium spp. and Lactobacillus spp. were based on 16S rRNA gene sequences. The PCR amplification reactions were carried out as follows: 2 min at 50°C, 10 min at 95°C, followed by 45 cycles of 15 s at 95°C and 1 min at 60°C. Detection was carried out on an ABI Prism 7900 sequence detection system (Applied Biosystems, Foster City, CA). Each assay was performed in duplicate in the same run. The cycle threshold of each sample was then compared with a standard curve made by diluting genomic DNA (10-fold serial dilution) from cultures. Cell counts before DNA extraction were determined with the Neubauer hemocytometer. To determine the sensitivity and specificity of the assays, the PCR assays were confirmed using a set of intestinal bacterial species as controls. Group-specific primers based on 16 S rDNA sequences PCR assay are forward Bifidobacterium, CGCGTCYGGTGTGAAAG; reverse Bifidobacterium, CCCCACATCCAGCATCCA; BHQ-1-bifido, AACAGGATTAGATACCC; forward Lactobacillus, GAGGCAGCAGTAGGGAATCTTC; reverse Lactobacillus, GGCCAGTTACTACCTCTATCCTTCTTC; BHQ-1-lacto, ATGGAGCAACGCCGC; forward Bacteroides-Prevotella, GAGAGGAAGGTCCCCCAC; reverse Bacteroides-Prevotella, CGCTACTTGGCTGGTTCAG; and VIC-CCATTGACCAATATTCCTCACTGCTGCCT-TAMRA.

        Glucose tolerance tests.

        Oral glucose tolerance tests were performed as follows: 6-h–fasted mice were injected with glucose by gavage (1 g/kg glucose, 20% glucose solution). Blood glucose was determined with a glucose meter (Roche Diagnostics, Meylan, France) on 3.5 μl blood collected from the tip of the tail vein. In addition, to assess plasma insulin concentration, 20 μl blood was sampled 30 min before and 15 min after the glucose challenge. The plasma was separated and frozen at −80°C.

        Real-time quantitative PCR.

        Total RNAs from each individual adipose tissues were prepared using the TriPure reagent (Roche, Basel, Switzerland) as described previously (5). cDNA was synthesized using a reverse transcription kit (Promega, Madison, WI) from 1 μg total RNA. PCRs were performed with an ABIPrism 7000 Sequence Detection System instrument and software (Applied Biosystems) as described previously (5). Primer sequences for the targeted mouse genes are the following: forward tumor necrosis factor-α (TNF-α), TGGGACAGTGACCTGGACTGT; reverse TNF-α, TTCGGAAAGCCCATTTGAGT; forward interleukin (IL)-1, TCGCTCAGGGTCACAAGAAA; reverse IL-1, CATCAGAGGCAAGGAGGAAAAC; forward plasminogen activator inhibitor 1 (PAI-1), ACAGCCTTTGTCATCTCAGCC; reverse PAI-1, CCGAACCACAAAGAGAAAGGA; forward ribosomal protein L19 (RPL19), GAAGGTCAAAGGGAATGTGTTCA; reverse RPL19, CCTTGTCTGCCTTCAGCTTGT; forward monocyte chemotactic protein (MCP)-1, GCAGTTAACGCCCCACTCA; reverse MCP-1, CCCAGCCTACTCATTGGGATCA; forward F4/80, TGACAACCAGACGGCTTGTG; reverse F4/80, GCAGGCGAGGAAAAGATAGTGT; forward NADPHox, GGTTGGGGCTGAACATTTTTC; reverse NADPHox, TCGACACACAGGAATCAGGAT; forward six-transmembrane protein of prostate 2 (STAMP2), GCATCTAGTGTTCCTGACTGGA; reverse STAMP2, TCAAATGCGGAATACCTTGCT; forward zonula occludens-1 (ZO-1), ACCCGAAACTGATGCTGTGGATAG; reverse ZO-1, AAATGGCCGGGCAGAACTTGTGTA; forward occludin, ATGTCCGGCCGATGCTCTC; and reverse occludin, TTTGGCTGCTCTTGGGTCTGTAT. The PCR conditions were 2 min at 50°C, 10 min at 95°C followed by 40 cycles of two-step PCR denaturation at 95°C for 15 s and annealing extension at 60°C for 60 s. Each sample contained 0.5–5 ng cDNA in 1× SYBRGreen PCR Master Mix (Applied Biosystems) and 200 or 300 nmol/l of each primer (Eurogentec, Verviers, Belgium) in a final volume of 25 μl. The relative amount of each studied mRNA was normalized to RPL19 rRNA levels as housekeeping gene, and the data were analyzed according to the 2−ΔΔCT method.

        Adipose tissue morphometry and staining.

        The mean relative proportion and mean surface area of the adipocytes was estimated by a point-counting technique on paraffin-embedded tissue as described previously (4).

        Intestinal permeability in vivo.

        This measure is based on the intestinal permeability to 4,000-Da fluorescent-dextran (Sigma-Aldrich, St. Louis, MO) as described previously (19). Briefly, 6-h–fasted mice were injected with fluorescein isothiocyanate (FITC)-dextran by gavage (600 mg/kg body wt, 125 mg/ml). After 1 h, 120 μl blood was collected from the tip of the tail vein. The blood was centrifuged at 4°C, 12,000g, for 3 min. Plasma was diluted in an equal volume of PBS (pH 7.4) and analyzed for FITC-dextran concentration with a fluorescence spectrophotometer (HTS-7000 Plus-plate-reader; Perkin Elmer, Wellesley, MA) at the excitation wavelength of 485 nm and the emission wavelength of 535 nm. Standard curves for calculating the FITC-dextran concentration in the samples were obtained by diluting FITC-dextran in nontreated plasma diluted with PBS (1:2 [vol/vol]).

        Biochemical analyses.

        Plasma LPS concentration was determined using a kit based on a Limulus amebocyte extract (LAL kit endpoint-QCL1000; Cambrex BioScience, Walkersville, MD), where samples were diluted 1/40 to 1/100 and heated for 10 min at 70°C. Internal control of recovery calculation was included in the assessment. Plasma insulin concentration was determined in 5 μl plasma using an ELISA kit (Mercodia, Uppsala, Sweden) and following the manufacturer’s instructions. Visceral adipose tissue oxidative stress level was evaluated by measuring lipid peroxidation and reactive compounds such as malondialdehyde (MDA) and 4-hydroxynonenal, natural byproducts of lipid peroxidation. The aldehydic secondary products of lipid peroxidation are accepted markers of oxidative stress. Thiobarbituric acid reactive substances (TBARS) constitute a well-established assay for screening and monitoring lipid peroxidation. The adducts formed in samples, due to the reaction between MDA with thiobarbituric acid, were measured spectrophotometrically. TBARS levels were determined from a MDA equivalence standard.

        Statistical analysis.

        Results are presented as means ± SE. The statistical significance of differences was analyzed by one-way ANOVA followed by post hoc (Bonferroni’s multiple comparison test) or Pearson’s correlation using GraphPad Prism version 4.00 for Windows (GraphPad Software, San Diego, CA; www.graphpad.com). Data with different superscript letters are significantly different (P < 0.05) according to the post hoc ANOVA statistical analysis.

        RESULTS

        Antibiotic treatment–associated changes in gut microbiota and endotoxemia during high-fat feeding.

        We previously showed that high-fat feeding changed gut microbiota and increased plasma LPS levels, as defined by metabolic endotoxemia (4). This was confirmed as assessed by the DGGE analysis (Fig. 1A). Therefore, to establish a cause and effect relationship according to which changes in gut microbiota initiated metabolic endotoxemia, we used large-spectrum antibiotics to modify the intestinal microbial community in mice and assessed the main features of high-fat diet–induced metabolic disorders. A 4-week antibiotic treatment strongly changed gut microbiota mRNA and bacterial content profile in both control and high-fat–treated mice (Fig. 1A; Table 1). DGGE profiles clearly showed that cecal bacterial composition and/or metabolic activity were strongly affected after a 4-week antibiotic treatment regardless of the diet (Fig. 1A). Similarity analysis of DGGE profiles of cecal bacterial communities showed that the profiles of chow-fed animals and those of chow-fed animals treated with antibiotics were only 44% similar. This difference was even more dramatic between the high-fat–fed and high-fat–fed, antibiotic-treated mice (high-fat antibiotic), where the profiles were only 22% similar. After antibiotic treatment, each individual animal showed identical bacterial profiles (Dice’s coefficient 100%). Moreover, we showed that high-fat diet dramatically changed the gut microbiota content. This was characterized by a strong reduction of some Gram-positive and -negative bacteria (Lactobacillus spp., Bifidobacterium spp., and Bacteroides-Prevotella spp.) (Table 1). The reduced cecal microbiota content of high-fat antibiotic–treated mice only was associated with reduced metabolic endotoxemia to be similar to that of the control mice (Fig. 1B). Similarly, the cecal endotoxin content per gram of cecal content was significantly decreased after antibiotic treatment (cecal endotoxin content: control, 2.00a ± 0.04 log μg/g; control antibiotic, 1.30b ± 0.26 log μg/g; high fat, 0.93c ± 0.07 log μg/g; high-fat antibiotic, 0.02d ± 0.2 log μg/g). Moreover, we found that high-fat diet–induced metabolic endotoxemia depended on a mechanism involved in the control of gut permeability. We demonstrated that high-fat feeding dramatically increased intestinal permeability (Fig. 1C) by a mechanism associated with a reduced expression of epithelial tight junction proteins such as ZO-1 and Occludin (Fig. 1DG), although only a tendency was observed for occludin. This effect was completely restored by the antibiotic treatment. These data suggest that gut bacteria are involved in the control intestinal permeability and furthermore in the occurrence of metabolic endotoxemia.

        Antibiotic treatment reduced the occurrence of adipose tissue inflammation, oxidative stress, and macrophage infiltration markers in high-fat diet–fed mice.

        To causally link changes of gut microbiota to high-fat diet–induced markers of metabolic disorders, we quantified the mRNA concentrations of PAI-1, IL-1, and TNF-α in visceral (mesenteric) adipose tissue. All mRNA concentrations were increased in high-fat diet–fed mice when compared with control-fed mice. This increase was totally blunted in the high-fat diet–fed, antibiotic-treated mice (Fig. 2A, D, and G). Inflammation and metabolic disorders are frequently associated with oxidative stress in adipose depots (2022). We found that high-fat feeding increased STAMP2 (21) and NADPHox mRNA concentrations and lipid peroxidation, which were totally normalized by the antibiotic treatment (Fig. 2B, E, and H). Similarly, the mRNA concentrations of chemokine MCP-1 and a marker specific of mature macrophages, F4/80, were increased in high-fat mice and totally normalized by the antibiotic treatment (Fig. 2C and F). The microflora therefore appears to be a key link between high-fat feeding, plasma LPS, and visceral adipose tissue inflammation. As reported for the visceral adipose depots, the mRNA concentrations of PAI-1, IL-1, TNF-α, and F4/80 were increased in the subcutaneous adipose depots of high-fat diet–fed mice as well (Fig. 3A, D, G, and F), whereas this increase was totally blunted in the high-fat diet–fed, antibiotic-treated mice. However, no significant change was observed for STAMP2, NADPHox, and MCP-1 mRNA (Fig. 3B, C, and E).

        Metabolic endotoxemia positively correlated with inflammation, oxidative stress, and macrophage infiltration markers.

        To identify whether the changes of gut microbiota and metabolic endotoxemia controlled visceral adipose tissue inflammation, oxidative stress, and macrophage infiltration, we performed multiple correlation analyses between these parameters. Metabolic endotoxemia positively and significantly correlated with PAI-1, IL-1, TNF-α, STAMP2, NADPHox, MCP-1, and F4/80 mRNA (Fig. 4AC; Supplemental Fig. 1, which is detailed in the online appendix [available at http://dx.doi.org/10.2337/db07-1403]). With the same aim in view, we performed other correlations and found that all inflammatory markers, oxidative stress, and macrophage infiltration markers positively and significantly correlated with one another (Fig. 4DI), Altogether, these multiple correlations support a strong relationship between gut microbiota, endotoxemia, inflammation, and oxidative stress during high-fat diet feeding.

        Antibiotic treatment prevented high-fat diet–induced adipocyte hypertrophy.

        We previously reported that a high-fat diet increased the adipocyte cell size (4), and here, we confirmed these data (Fig. 5A, B, and D). Furthermore, we also assumed that it could be due to a LPS-dependent mechanism (4). Therefore, we wondered whether reduced metabolic endotoxemia, induced by the antibiotic treatment, was associated with changes in adipocyte cell size. The mean adipocyte size was reduced in high-fat antibiotic–treated mice when compared with high-fat untreated mice (Fig. 5A, B, and D). These changes were accompanied with a lower cell density when compared with all of the groups (Fig. 5C).

        Antibiotic treatment improved metabolic parameters of diabetes and obesity in high-fat diet–fed mice.

        High-fat feeding induced glucose intolerance because the blood glucose concentrations were all higher than those of the control mice during the glucose challenge (Fig. 6A). High-fat mice treated with antibiotics exhibited improved glucose tolerance when compared with untreated mice (Fig. 6A). However, the blood glucose profiles and the calculated area under curve were still significantly different from the control-fed mice. Furthermore, glucose-induced insulin secretion, insulin resistance index, body weight gain, total energy intake, and visceral and subcutaneous adipose weight were significantly higher in high-fat diet–fed mice when compared with all of the other groups (Fig. 6BH). All of the parameters were corrected by the antibiotic treatment, except for the energy intake after high-fat diet feeding, which was worsened during antibiotic treatment (Fig. 6F). This increased energy intake could be related to an impaired energy harvesting. Fecal energy content per gram cecum content was similar between groups. It was 3.16a ± 0.5, 3.28a ± 0.04, 3.11a ± 0.05, and 3.23a ± 0.08 kcal/g, in control, control antibiotic, high fat, and high-fat antibiotic, respectively. However, the total cecal content was decreased after high-fat feeding (control 0.45a ± 0.02 vs. high fat 0.19c ± 0.01 g) and significantly increased after antibiotic treatment (control antibiotic 1.36b ± 0.08 and high-fat antibiotic 0.82d ± 0.03 g). Consequently, the total cecal energy content was increased fourfold in high-fat antibiotic (2.85d ± 0.05 kcal) when compared with high-fat mice (0.68c ± 0.08 kcal). A similar trend was observed in control (1.42a ± 0.38 kcal) versus control antibiotic (4.63b ± 0.31 kcal). The total cecal lipid content was sixfold increased in high-fat antibiotic (34.38c ± 5.52 mg) when compared with high-fat mice (5.54a ± 0.44 mg). This increase was more moderate in control (8.81a ± 0.11 mg) versus control antibiotic (18.36b ± 1.84 mg).

        Antibiotic treatment of ob/ob mice reduced endotoxemia.

        To assess the contribution of gut microbiota to the development of metabolic endotoxemia and inflammation regardless of the high-fat feeding, we turned to ob/ob mice. These animals are characterized by higher inflammatory tone and plasma LPS concentration, whereas they are consuming a normal chow (23). Almost no bacterial RNAs were detected in any of the cecal contents of ob/ob mice treated with antibiotics, thus suggesting that similar to high-fat mice, the antibiotic treatment had a dramatic effect on the ob/ob intestinal microbial population. This could be due to the increased food intake and therefore antibiotic intake as well. Bacterial quantification confirms the DGGE profile and shows significant decrease in Lactobacillus spp., Bifidobacterium spp., and Bacteroides-Prevotella spp. (Table 1). Furthermore, our data showed that the treatment of ob/ob mice reduced metabolic endotoxemia (Fig. 7A and B). However, endotoxemia still remained higher than control values.

        Antibiotic treatment of ob/ob mice lowered the mRNA concentration of adipose tissue inflammatory markers and metabolic parameters of diabetes and obesity.

        The mRNA concentrations of PAI-1 and F4/80 were significantly reduced in the visceral adipose depots and to a lower extent in the subcutaneous adipose depots of ob/ob antibiotic-treated mice (Fig. 7H, I, L, and M). Similarly, visceral adipose depot lipid peroxides, markers of oxidative stress, were twofold lower in antibiotic-treated mice (Fig. 7N). Moreover, glucose intolerance (Fig. 7C), insulin resistance index (Fig. 7F), glucose-induced insulin secretion (Fig. 7E), and visceral and subcutaneous adipose tissue weights (Fig. 7J and K) were reduced by the antibiotic treatment. However, no significant change of body weight was detected (Fig. 7G).

        The lack of the LPS receptor CD14 partially reverted inflammatory markers and metabolic parameters in ob/ob mice.

        We and others previously demonstrated that the lack of LPS receptor protects against the high-fat diet–induced adipose tissue inflammation and metabolic disorders (4,2428). To demonstrate that the LPS receptor might be involved in the inflammatory phenotype of ob/ob mice, we generated ob/ob CD14−/− mice. We showed here that in ob/ob CD14−/− mice, PAI-1 and F4/80 mRNA concentrations were reduced in the visceral adipose depots (Fig. 7H and L). This was accompanied by a reduction of oxidative stress markers (Fig. 7N). All of these parameters remained unchanged in the subcutaneous adipose depot when compared with ob/ob mice showing that CD14-mediated inflammation targeted visceral fat. Furthermore, blood glucose profiles, insulin resistance index, glucose-induced insulin secretion, visceral and subcutaneous adipose tissue weights, and lipid peroxidation were reduced in ob/ob CD14−/− when compared with ob/ob mice (Fig. 7CN).

        DISCUSSION

        We reported here that gut bacteria are involved in high-fat diet and ob/ob-induced metabolic endotoxemia, adipose tissue inflammation, and metabolic disorders. This effect could be mediated by a mechanism that could increase gut permeability and enhance LPS absorption. Antibiotic treatment significantly lowers plasma LPS levels, gut permeability, and the occurrence of visceral adipose tissue inflammation, oxidative stress, macrophage infiltration, and metabolic disorders. We therefore conclude that gut microbiota could control intestinal permeability, which determines the threshold at which metabolic endotoxemia-induced metabolic disorders occur.

        We and others have recently demonstrated that the mechanisms of high-fat diet–induced inflammation and metabolic disorders were clearly linked to LPS (4,2428). We here confirm these data and further demonstrate that this mechanism was linked to endotoxemia. We identified here that metabolic endotoxemia was due to changes in intestinal microbiota, because the antibiotic treatment, which dramatically reduced the local intestinal microbiota, restored normal plasma LPS values in high-fat diet–fed mice. High plasma LPS levels could result from an increased production of endotoxin by a change in gut microbiota (4,6). Evidently, the intestinal epithelium acts as a continuous barrier to avoid LPS translocation, but some endogenous or exogenous factors may alter this function. Among the factors promoting a leaky gut and increasing plasma LPS levels, alcohol consumption (29,30,31,32,33), immobilization stress (33,34), and radiation (35) have been put forward. Most importantly, in most of these studies, antibiotic treatments were also administered and resulted in reduced plasma and cecal LPS levels. In addition to these factors, we further showed that reduced endotoxemia was due to a change in the microflora profile. High-fat feeding decreased the number of bifidobacteria (4,6). This group of bacteria has been shown to reduce intestinal LPS levels in mice and to improve the mucosal barrier function (3638). Furthermore, we have shown that prebiotics increased the number of bifidobacteria and reduced the impact of high-fat diet–induced metabolic disorders (6). Interestingly, bifidobacteria do not degrade intestinal mucous glycoproteins like other pathogenic bacteria do. This effect promotes a healthier microvillus environment by preventing permeability and bacterial translocation (39,40). In the present study, we further provide evidence that the mechanisms involved in the development of metabolic endotoxemia and the corresponding metabolic disorders in response to high-fat feeding are associated with an increased intestinal permeability. The modulation of gut bacteria after high-fat diet strongly increased intestinal permeability by reducing the expression of genes coding for tight junction proteins ZO-1 and occludin. Moreover, our data demonstrate that gut bacteria are clearly involved in the present mechanism because antibiotic-treated mice exhibited normal intestinal integrity, although the mice were still eating a high-fat diet. We therefore, suggest that high-fat feeding changes gut microflora, which then increase intestinal LPS permeability (Fig. 1C). It is noteworthy that the antibiotic treatment reduced the intestinal content in LPS, which could contribute as well to the reduced metabolic endotoxemia. We report here that changes in feeding habits or the antibiotic treatment profoundly affect the fecal content in energy. The lipid content was dramatically increased in mice treated with antibiotics, suggesting that intestinal flora contributes to energy harvesting or absorption. This observation is also supported by data from literature (712). Together, these data emphasize the role of gut microbiota in the development of high-fat diet–induced metabolic disorders.

        These results demonstrate that the gut bacteria determines the threshold at which metabolic endotoxemia occurs during high-fat diet feeding. However, the role of gut microbiota on the development of metabolic endotoxemia-induced inflammation and metabolic disorders is poorly defined. Therefore, we characterized several inflammatory markers and found that the increase in PAI-1, IL-1, and TNF-α mRNA concentrations after high-fat feeding was completely abolished by the antibiotic treatment. This mechanism does not depend on the amount of fat ingested because it was even increased by the antibiotic treatment. Oxidative stress is frequently associated with inflammation and metabolic dysfunction in adipose depots (2021,22). We similarly found that the antibiotic treatment totally normalized lipid peroxidation in the visceral adipose depots and normalized the inflammatory/oxidative stress factor STAMP2 (21) and NADPHox mRNA concentration in the visceral and subcutaneous adipose depots. Furthermore, we found that antibiotic-treated mice exhibited normal F4/80 and MCP-1 mRNA concentrations in the visceral adipose depot. Our result are in agreement with data from the literature, because we and others have previously shown that high-fat feeding is associated with adipose tissue macrophage infiltration (F4/80-positive cells) and chemokine MCP-1 (4,41,42). Moreover, our multiple correlation analyses strongly suggest that inflammation, macrophage infiltration, and oxidative stress markers are induced by LPS-dependent mechanisms and controlled by the antibiotic treatment. We here also further demonstrated that the modulation of gut microbiota improved high-fat diet–induced glucose intolerance, body weight gain, and fat mass development. These results are in line with our and other previous data showing that in the absence of metabolic endotoxemia or LPS receptor, dietary lipids are not sufficient to induce metabolic disorders (4,6,25,28).

        To assess the contribution of gut microbiota to the development of metabolic endotoxemia and inflammation regardless of the high-fat feeding, we focused on ob/ob mice. These animals are characterized by different gut microbiota (8,12), higher inflammatory tone, and endotoxemia when compared with wild-type mice (23). Antibiotic treatment dramatically changed the ob/ob mice gut microbiota; reduced Lactobacillus spp., Bifidobacterium spp., and Bacteroides-Prevotella spp.; and lowered metabolic endotoxemia. Furthermore, these parameters were associated with a significantly lower inflammatory tone in ob/ob antibiotic-treated mice. To demonstrate that the LPS receptor is involved in the regulation of inflammation and metabolic disorders in response to changes of gut microbiota, we therefore generated ob/ob mice lacking the LPS receptor CD14 (ob/ob CD14−/−). Inflammation and macrophage infiltration markers were reduced in the visceral adipose depots and to a lower extent in the subcutaneous adipose depots of ob/ob CD14−/− mice. The latter set of data demonstrates that metabolic endotoxemia measured in ob/ob mice is, at least in part, involved in the inflammatory phenotype. In ob/ob mice, the lowering of metabolic endotoxemia, by means of the antibiotic treatment, and of LPS action in the ob/ob CD14−/− mice are associated with a significantly increased glucose tolerance and reduced visceral and subcutaneous adipose depots weight. Interestingly, we also found that ob/ob mice treated for 4 weeks with an endotoxin inhibitor (43) administered via osmotic mini-pumps improved glucose tolerance and lowered adipose tissue fat mass (Supplemental Fig. 2). This pattern is similar to that observed in antibiotic-treated mice. This confirms that the gut microflora and the consequent increased bacteria-derived factor LPS exert a key role in the development of adipose depots and inflammation in ob/ob mice. Altogether, these data demonstrate that changes in gut microbiota and metabolic endotoxemia play a role in the ob/ob phenotype.

        In the quest for non–gut-dependent sources of endotoxemia, periodontitis could also be linked to the development of metabolic disorders (44). Several studies reported that the treatment of periodontitis with antibiotics was associated with improved metabolic parameters (45). Nevertheless, the impact of such antibiotic treatment on gut microbiota has not been investigated but could play a part in the improved metabolic phenotype.

        In summary, first, we have demonstrated that in high-fat diet–fed mice, the modulation of gut microbiota is associated with an increased intestinal permeability that precedes the development of metabolic endotoxemia, inflammation, and associated disorders (Fig. 8). Second, we found that in ob/ob mice, gut microbiota determines the concentration of plasma LPS and is a mechanism involved in metabolic disorders. Altogether, we demonstrate that gut microbiota sets the threshold for metabolic endotoxemia.

        FIG. 1.
        FIG. 1.

        Antibiotic treatment–associated changes in gut microbiota, intestinal permeability, and endotoxemia during high-fat feeding. A: DGGE profiles generated from the cecal microbiota in mice fed normal diet (CT), normal diet and antibiotics (CT-Ab), high-fat diet (HF), or high-fat diet and antibiotics (HF-Ab) for 4 weeks. Each number and profile corresponds to a different animal. Bar = Dice’s similarity coefficient. B: Plasma endotoxin (LPS) concentration (EU/ml). Data are means ± SE. Data with different superscript letters are significantly different (P < 0.05), according to the post hoc ANOVA statistical analysis. C: Intestinal permeability assay: Plasma DX-4000-FITC (μg/ml). n.d., not detectable concentration. D and F: Epithelial tight junction proteins markers (ZO-1 and occludin mRNA concentrations). E and G: Correlations between intestinal permeability markers: plasma DX-4000-FITC and epithelial tight junction ZO-1 and occludin mRNA concentrations (P < 0.05). Inset corresponds to Pearson’s r correlation and corresponding P value. Data are means ± SE. Data with different superscript letters are significantly different (P < 0.05) according to the post hoc ANOVA statistical analysis.

        FIG. 2.
        FIG. 2.

        Antibiotic treatment reduced the occurrence of visceral adipose tissue inflammation, oxidative stress, and macrophage infiltration markers in high-fat diet–fed mice. Inflammation: PAI-1, IL-1, and TNF-α mRNA concentrations (A, D, and G); oxidative stress: STAMP-2 and NADPHox mRNA concentrations (B and E); macrophage infiltration markers: MCP-1 and F4/80 mRNA concentrations (C and F), visceral adipose tissue oxidative stress levels (lipid peroxides concentrations) (H) in mice fed normal diet (CT), normal diet and antibiotics (CT-Ab), high-fat diet (HF), or high-fat diet and antibiotics (HF-Ab) for 4 weeks. Data are means ± SE. Data with different superscript letters are significantly different (P < 0.05) according to the post hoc ANOVA statistical analysis.

        FIG. 3.
        FIG. 3.

        Antibiotic treatment reduced the occurrence of subcutaneous adipose tissue inflammation and macrophage infiltration markers in high-fat diet–fed mice. Inflammation: PAI-1, IL-1, and TNF-α mRNA concentrations (A, D and G); oxidative stress: STAMP-2 and NADPHox mRNA concentrations (B and E); macrophage infiltration markers: MCP-1 and F4/80 mRNA concentrations (C and F) in mice fed normal diet (CT), normal diet and antibiotics (CT-Ab), high-fat diet (HF), or high-fat diet and antibiotics (HF-Ab) for 4 weeks. Data are means ± SE. Data with different superscript letters are significantly different (P < 0.05) according to the post hoc ANOVA statistical analysis.

        FIG. 4.
        FIG. 4.

        Metabolic endotoxemia positively correlated with inflammation, oxidative stress, and macrophage infiltration markers. Correlations between plasma endotoxin (LPS, EU/ml) and PAI-1 (A), STAMP2 (B), and F4/80 (C) mRNA concentrations; correlations between PAI-1 mRNA concentrations and IL-1 (D), STAMP2 (E), and F4/80 mRNA (F) concentrations; correlations between NADPHox mRNA concentrations and PAI-1 (G), STAMP2 (H), and F4/80 mRNA (I) concentrations in the visceral adipose depots of mice fed normal diet (CT), normal diet and antibiotic (CT-Ab), high-fat diet (HF), or high-fat diet and antibiotics (HF-Ab) for 4 weeks. P < 0.05, inset corresponds to Pearson’s r correlation and corresponding P value.

        FIG. 5.
        FIG. 5.

        Antibiotic treatment prevented high-fat diet–induced adipocyte hypertrophy. A: Adipocyte size distribution (%). B: Adipocyte mean area (μm2). C: Cell density (arbitrary unit). D: Representative adipose tissue staining in mice fed normal diet (CT), normal diet and antibiotics (CT-Ab), high-fat diet (HF), or high-fat diet and antibiotics (HF-Ab) for 4 weeks. Data are means ± SE. Data with different superscript letters are significantly different (P < 0.05) according to the post hoc ANOVA statistical analysis.

        FIG. 6.
        FIG. 6.

        Antibiotic treatment improved metabolic parameters of diabetes and obesity in high-fat diet–fed mice. A: Plasma glucose (mmol/l) after an oral glucose load (1 g/kg) in mice fed normal diet (CT), normal diet and antibiotics (CT-Ab), high-fat diet (HF), or high-fat diet and antibiotics (HF-Ab) for 4 weeks. The inset represents the area under curve (AUC) of the same groups. B: Plasma insulin concentration (pmol/l) 30 min before (−30) and 15 min after (15) oral glucose administration of the same groups. C: Insulin resistance index. D: Glucose-induced insulin secretion after oral glucose administration. E: Body weight gain. F: Total energy intake. G: Subcutaneous adipose tissue weight (percent body weight). H: Visceral adipose tissue weight (percent body weight) in mice fed normal diet (CT), normal diet and antibiotics (CT-Ab), high-fat diet (HF), or high-fat diet and antibiotics (HF-Ab) for 4 weeks. Data are means ± SE. Data with different superscript letters are significantly different (P < 0.05) according to the post hoc ANOVA statistical analysis.

        FIG. 7.
        FIG. 7.

        Antibiotic treatment of ob/ob mice reduced endotoxemia. ob/ob mice treated with antibiotic and ob/ob CD14−/− mice exhibited lower mRNA concentration of adipose tissue inflammatory markers and improved metabolic parameters. A: DGGE profiles generated from the cecal microbiota in ob/ob mice (Ob) or ob/ob mice treated with antibiotic (Ob-Ab) for 4 weeks. Each number and profile correspond to a different animal. B: Plasma endotoxin (LPS) concentration (EU/ml). C: Plasma glucose (mmol/l) after an oral glucose load (1 g/kg) in ob/ob mice (Ob), ob/ob mice treated with antibiotics (Ob-Ab) for 4 weeks, or ob/ob 14−/− mice. The inset represents the area under curve (AUC) of the same groups. D: Plasma insulin concentration (pmol/l) 30 min before (−30) and 15 min after (15) oral glucose administration of the same groups. E: Glucose-induced insulin secretion after oral glucose administration. F: Insulin resistance index. G: Body weight gain. J: Subcutaneous adipose tissue weight (percent body weight). K: Visceral adipose tissue weight (percent body weight). H and L: Visceral adipose tissue PAI-1 and F4/80 mRNA concentrations. I and M: Subcutaneous adipose tissue PAI-1 and F4/80 mRNA concentrations in ob/ob mice (Ob), ob/ob mice treated with antibiotics (Ob-Ab) for 4 weeks, or ob/ob 14−/− mice. N: Visceral adipose tissue oxidative stress levels (lipid peroxides concentrations) in the same groups. Data are means ± SE. Data with different superscript letters are significantly different (P < 0.05) according to the post hoc ANOVA statistical analysis.

        FIG. 8.
        FIG. 8.

        Hypothesis for bacteria-induced metabolic disease. On excessive high-fat feeding, intestinal microflora changes. This is associated with an increased intestinal permeability. Consequently, endotoxemia increases and triggers inflammation and metabolic disorders.

        TABLE 1

        Bacterial quantification

        Acknowledgments

        P.D.C. is a postdoctoral researcher from the Fonds de la Recherche Scientifique (Belgium) and recipient of subsides from Fonds speciaux de recherché, Université Catholique de Louvain (UCL) (Belgium). N.M.D. is the recipient of subsides from Fonds speciaux de recherché, UCL (Belgium). R.B. is the recipient of subsides from the Nutritia Foundation, the Association Française Etude et de Recherche sur les obésités, l’Agence National de la Recherche (Programme ANR-05-PNRA-004 Nutrisens, PNRA-005.13 MitHyCal, PNRA-30032006-01-03 Metaprofile), the Institut National de la Santé et de la Recherche Médicale, the Université Paul Sabatier, and the Club d’étude du système nerveux autonome.

        We thank Dr. C. Feyt and Dr. G. Muccioli for helpful criticisms and F. De Backer, A. Stroobants, A. Colom, and C. Chabo for excellent technical assistance.

        Footnotes

        • Published ahead of print at http://diabetes.diabetesjournals.org on 27 February 2008. DOI: 10.2337/db07-1403.

          Additional information for this article can be found in an online appendix at http://dx.doi.org/10.2337/db07-1403.

          The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

          • Accepted February 25, 2008.
          • Received October 3, 2007.

        REFERENCES

        1. Kahn SE, Hull RL, Utzschneider KM: Mechanisms linking obesity to insulin resistance and type 2 diabetes.
          Nature444
          :840
          –846,2006

        2. Hotamisligil GS: Inflammation and metabolic disorders.
          Nature444
          :860
          –867,2006

        3. Wellen KE, Hotamisligil GS: Inflammation, stress, and diabetes.
          J Clin Invest115
          :1111
          –1119,2005

        4. Cani PD, Amar J, Iglesias MA, Poggi M, Knauf C, Bastelica D, Neyrinck AM, Fava F, Tuohy KM, Chabo C, Waget A, Delmee E, Cousin B, Sulpice T, Chamontin B, Ferrieres J, Tanti JF, Gibson GR, Casteilla L, Delzenne NM, Alessi MC, Burcelin R: Metabolic endotoxemia initiates obesity and insulin resistance.
          Diabetes56
          :1761
          –1772,2007

        5. Cani PD, Knauf C, Iglesias MA, Drucker DJ, Delzenne NM, Burcelin R: Improvement of glucose tolerance and hepatic insulin sensitivity by oligofructose requires a functional glucagon-like peptide 1 receptor.
          Diabetes55
          :1484
          –1490,2006

        6. Cani PD, Neyrinck AM, Fava F, Knauf C, Burcelin RG, Tuohy KM, Gibson GR, Delzenne NM: Selective increases of bifidobacteria in gut microflora improve high-fat-diet-induced diabetes in mice through a mechanism associated with endotoxaemia.
          Diabetologia50
          :2374
          –2383,2007

        7. Ley RE, Turnbaugh PJ, Klein S, Gordon JI: Microbial ecology: human gut microbes associated with obesity.
          Nature444
          :1022
          –1023,2006

        8. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI: An obesity-associated gut microbiome with increased capacity for energy harvest.
          Nature444
          :1027
          –1031,2006

        9. Backhed F, Manchester JK, Semenkovich CF, Gordon JI: Mechanisms underlying the resistance to diet-induced obesity in germ-free mice.
          Proc Natl Acad Sci U S A104
          :979
          –984,2007

        10. Backhed F, Ley RE, Sonnenburg JL, Peterson DA, Gordon JI: Host-bacterial mutualism in the human intestine.
          Science307
          :1915
          –1920,2005

        11. Backhed F, Ding H, Wang T, Hooper LV, Koh GY, Nagy A, Semenkovich CF, Gordon JI: The gut microbiota as an environmental factor that regulates fat storage.
          Proc Natl Acad Sci U S A101
          :15718
          –15723,2004

        12. Ley RE, Backhed F, Turnbaugh P, Lozupone CA, Knight RD, Gordon JI: Obesity alters gut microbial ecology.
          Proc Natl Acad Sci U S A102
          :11070
          –11075,2005

        13. Ferrier L, Berard F, Debrauwer L, Chabo C, Langella P, Bueno L, Fioramonti J: Impairment of the intestinal barrier by ethanol involves enteric microflora and mast cell activation in rodents.
          Am J Pathol168
          :1148
          –1154,2006

        14. Tannock GW, Munro K, Harmsen HJ, Welling GW, Smart J, Gopal PK: Analysis of the fecal microflora of human subjects consuming a probiotic product containing Lactobacillus rhamnosus DR20.
          Appl Environ Microbiol66
          :2578
          –2588,2000

        15. Futatsugi A, Nakamura T, Yamada MK, Ebisui E, Nakamura K, Uchida K, Kitaguchi T, Takahashi-Iwanaga H, Noda T, Aruga J, Mikoshiba K: IP3 receptor types 2 and 3 mediate exocrine secretion underlying energy metabolism.
          Science309
          :2232
          –2234,2005

        16. Jeejeebhoy KN, Ahmad S, Kozak G: Determination of fecal fats containing both medium and long chain triglycerides and fatty acids.
          Clin Biochem3
          :157
          –163,1970

        17. Goossens D, Jonkers D, Russel M, Stobberingh E, van den BA, Stockbrugger R: The effect of Lactobacillus plantarum 299v on the bacterial composition and metabolic activity in faeces of healthy volunteers: a placebo-controlled study on the onset and duration of effects.
          Aliment Pharmacol Ther18
          :495
          –505,2003

        18. Goris H, de Boer F, van der Waaij D: Oral administration of antibiotics and intestinal flora associated endotoxin in mice.
          Scand J Infect Dis18
          :55
          –63,1986

        19. Wang Q, Fang CH, Hasselgren PO: Intestinal permeability is reduced and IL-10 levels are increased in septic IL-6 knockout mice.
          Am J Physiol Regul Integr Comp Physiol281
          :R1013
          –R1023,2001

        20. Furukawa S, Fujita T, Shimabukuro M, Iwaki M, Yamada Y, Nakajima Y, Nakayama O, Makishima M, Matsuda M, Shimomura I: Increased oxidative stress in obesity and its impact on metabolic syndrome.
          J Clin Invest114
          :1752
          –1761,2004

        21. Wellen KE, Fucho R, Gregor MF, Furuhashi M, Morgan C, Lindstad T, Vaillancourt E, Gorgun CZ, Saatcioglu F, Hotamisligil GS: Coordinated regulation of nutrient and inflammatory responses by STAMP2 is essential for metabolic homeostasis.
          Cell129
          :537
          –548,2007

        22. Houstis N, Rosen ED, Lander ES: Reactive oxygen species have a causal role in multiple forms of insulin resistance.
          Nature440
          :944
          –948,2006

        23. Brun P, Castagliuolo I, Leo VD, Buda A, Pinzani M, Palu G, Martines D: Increased intestinal permeability in obese mice: new evidence in the pathogenesis of nonalcoholic steatohepatitis.
          Am J Physiol Gastrointest Liver Physiol292
          :G518
          –G525,2007

        24. Poggi M, Bastelica D, Gual P, Iglesias MA, Gremeaux T, Knauf C, Peiretti F, Verdier M, Juhan-Vague I, Tanti JF, Burcelin R, Alessi MC: C3H/HeJ mice carrying a toll-like receptor 4 mutation are protected against the development of insulin resistance in white adipose tissue in response to a high-fat diet.
          Diabetologia50
          :1267
          –1276,2007

        25. Shi H, Kokoeva MV, Inouye K, Tzameli I, Yin H, Flier JS: TLR4 links innate immunity and fatty acid-induced insulin resistance.
          J Clin Invest116
          :3015
          –3025,2006

        26. Song MJ, Kim KH, Yoon JM, Kim JB: Activation of Toll-like receptor 4 is associated with insulin resistance in adipocytes.
          Biochem Biophys Res Commun346
          :739
          –745,2006

        27. Suganami T, Mieda T, Itoh M, Shimoda Y, Kamei Y, Ogawa Y: Attenuation of obesity-induced adipose tissue inflammation in C3H/HeJ mice carrying a Toll-like receptor 4 mutation.
          Biochem Biophys Res Commun354
          :45
          –49,2007

        28. Tsukumo DM, Carvalho-Filho MA, Carvalheira JB, Prada PO, Hirabara SM, Schenka AA, Araujo EP, Vassallo J, Curi R, Velloso LA, Saad MJ: Loss-of-function mutation in Toll-like receptor 4 prevents diet-induced obesity and insulin resistance.
          Diabetes56
          :1986
          –1998,2007

        29. Nishida J, Ekataksin W, McDonnell D, Urbaschek R, Urbaschek B, McCuskey RS: Ethanol exacerbates hepatic microvascular dysfunction, endotoxemia, and lethality in septic mice.
          Shock1
          :413
          –418,1994

        30. Adachi Y, Moore LE, Bradford BU, Gao W, Thurman RG: Antibiotics prevent liver injury in rats following long-term exposure to ethanol.
          Gastroenterology108
          :218
          –224,1995

        31. Enomoto N, Ikejima K, Yamashina S, Hirose M, Shimizu H, Kitamura T, Takei Y, Sato AN, Thurman RG: Kupffer cell sensitization by alcohol involves increased permeability to gut-derived endotoxin.
          Alcohol Clin Exp Res25
          :51S
          –54S,2001

        32. Enomoto N, Ikejima K, Bradford B, Rivera C, Kono H, Brenner DA, Thurman RG: Alcohol causes both tolerance and sensitization of rat Kupffer cells via mechanisms dependent on endotoxin.
          Gastroenterology115
          :443
          –451,1998

        33. Rivera CA, Bradford BU, Seabra V, Thurman RG: Role of endotoxin in the hypermetabolic state after acute ethanol exposure.
          Am J Physiol275
          :G1252
          –G1258,1998

        34. Rivera CA, Tcharmtchi MH, Mendoza L, Smith CW: Endotoxemia and hepatic injury in a rodent model of hindlimb unloading.
          J Appl Physiol95
          :1656
          –1663,2003

        35. Paulos CM, Wrzesinski C, Kaiser A, Hinrichs CS, Chieppa M, Cassard L, Palmer DC, Boni A, Muranski P, Yu Z, Gattinoni L, Antony PA, Rosenberg SA, Restifo NP: Microbial translocation augments the function of adoptively transferred self/tumor-specific CD8 T cells via TLR4 signaling.
          J Clin Invest117
          :2197
          –2204,2007

        36. Wang Z, Xiao G, Yao Y, Guo S, Lu K, Sheng Z: The role of bifidobacteria in gut barrier function after thermal injury in rats.
          J Trauma61
          :650
          –657,2006

        37. Griffiths EA, Duffy LC, Schanbacher FL, Qiao H, Dryja D, Leavens A, Rossman J, Rich G, Dirienzo D, Ogra PL: In vivo effects of bifidobacteria and lactoferrin on gut endotoxin concentration and mucosal immunity in Balb/c mice.
          Dig Dis Sci49
          :579
          –589,2004

        38. Wang ZT, Yao YM, Xiao GX, Sheng ZY: Risk factors of development of gut-derived bacterial translocation in thermally injured rats.
          World J Gastroenterol10
          :1619
          –1624,2004

        39. Caplan MS, Miller-Catchpole R, Kaup S, Russell T, Lickerman M, Am M, Xiao Y, Thomson R Jr: Bifidobacterial supplementation reduces the incidence of necrotizing enterocolitis in a neonatal rat model.
          Gastroenterology117
          :577
          –583,1999

        40. Ruseler-van Embden JG, van Lieshout LM, Gosselink MJ, Marteau P: Inability of Lactobacillus casei strain GG, L. acidophilus, and Bifidobacterium bifidum to degrade intestinal mucus glycoproteins.
          Scand J Gastroenterol30
          :675
          –680,1995

        41. Weisberg SP, McCann D, Desai M, Rosenbaum M, Leibel RL, Ferrante AW Jr: Obesity is associated with macrophage accumulation in adipose tissue.
          J Clin Invest112
          :1796
          –1808,2003

        42. Kanda H, Tateya S, Tamori Y, Kotani K, Hiasa K, Kitazawa R, Kitazawa S, Miyachi H, Maeda S, Egashira K, Kasuga M: MCP-1 contributes to macrophage infiltration into adipose tissue, insulin resistance, and hepatic steatosis in obesity.
          J Clin Invest116
          :1494
          –1505,2006

        43. Rustici A, Velucchi M, Faggioni R, Sironi M, Ghezzi P, Quataert S, Green B, Porro M: Molecular mapping and detoxification of the lipid A binding site by synthetic peptides.
          Science259
          :361
          –365,1993

        44. Saito T, Hayashida H, Furugen R: Comment on: Cani et al: (2007) Metabolic endotoxemia initiates obesity and insulin resistance:
          Diabetes 56:1761–1772. Diabetes56
          :e20
          ,2007

        45. Janket SJ, Wightman A, Baird AE, Van Dyke TE, Jones JA: Does periodontal treatment improve glycemic control in diabetic patients? A meta-analysis of intervention studies.
          J Dent Res84
          :1154
          –1159,2005



        Sell Unused Diabetic Strips Today!

        Avocado Brownies (Low-Carb) – Diabetic Foodie

        By electricdiet / July 31, 2021


        Rich, chewy, fudgy avocado brownies are the healthy way to satisfy your chocolate cravings! They’re gluten-free, keto-friendly, and super easy to throw together.

        Two brownies on a white plate with a bite taken out of the first one

        When I’m craving something chocolatey and decadent, I always think of brownies. From crispy edge pieces to those ooey-gooey center pieces, there’s a reason this treat is such a classic.

        Of course, I don’t always love the sugar and carbs you find in traditional recipes. That’s why I prefer to make these avocado brownies instead!

        If you’ve never baked with avocado before, rest assured: your dessert will NOT turn out tasting like guacamole. In fact, the rich chocolate flavor completely masks the avocado, leaving you with decadent, fudgy goodness.

        Even though you don’t taste it, avocado is really the powerhouse ingredient of this recipe. It keeps the brownies super moist while also adding some healthy fat and fiber to each slice!

        If you haven’t tried baking with avocado yet, these brownies are the perfect place to start. They’re so delicious, it’s hard to believe they’re gluten-free and keto-friendly! And best of all, prep only takes about 10 minutes.

        How to make avocado brownies

        This decadent dessert comes together in just six easy steps.

        Ingredients for recipe in separate bowls and ramekins, as seen from above

        Step 1: Preheat the oven to 350°F. Grease or line a 9×9 baking dish and set aside.

        Step 2: Combine all the ingredients in the blender.

        Ingredients for brownies in the blender, ready to be mixed

        Step 3: Blend until a smooth, thick batter starts to form. Stop the blender, stir the batter, then blend again, repeating as necessary until the batter is completely incorporated.

        Brownie batter mixed together in the blender, as seen from above

        Step 4: Spread the batter into the prepared baking dish.

        Brownie batter in a square baking dish over parchment paper, ready to bake

        Step 5: Bake for 22-25 minutes or until a toothpick inserted into the center comes out clean, then remove from the oven.

        Step 6: Allow the brownies to cool in the pan for at least 30 minutes before slicing.

        Finished brownies in the baking tin as they cool

        Waiting for your brownies to cool is the hardest part, but trust me, your patience will pay off! Cooling is what gives the brownies that ultra-fudgy texture that makes them so irresistible. Believe me, it’s well worth the wait.

        Closeup of sliced brownies on a wooden cutting board with one slice pulled slightly away from the rest

        Tips for making your perfect brownies

        When it comes to mashing up the avocado and making sure it’s fully incorporated into the brownie batter, I highly recommend using a blender. If you don’t have one, you could use a fork or even a potato masher. Just make sure to REALLY mash the avocado well.

        Not following a keto way of eating? The low-carb sweeteners can be replaced 1:1 with regular sugar if you like.

        Prefer your brownie texture firmer and more cake-like? Try baking your batch for a little longer, around 25-27 minutes. If you prefer them extra gooey, bake for 22-23 minutes.

        Overhead view of brownie slices with one brownie turned on it's side to show the texture

        Storage

        The good news about this recipe is that it keeps very well! You can have a rich, chocolatey, healthy dessert ready to enjoy all week long.

        Simply store the brownies in an airtight container in the refrigerator for up to 5 days… if they last that long! You can eat them cold straight from the fridge or heat them in the microwave for a few seconds to enjoy warm.

        Close-up of two avocado brownies on a small white plate

        Other healthy dessert recipes

        Eating healthy and regulating your blood sugar doesn’t mean you can’t indulge your sweet tooth! If you’re looking for more dessert recipes that you can enjoy in a diabetic-friendly diet, here are a few of my favorites I know you’ll enjoy:

        When you’ve tried these brownies, please don’t forget to let me know how you liked them and rate the recipe in the comments below!

        Recipe Card

        Close-up of two avocado brownies on a small white plate

        Avocado Brownies

        Rich, chewy, fudgy avocado brownies are the healthy way to satisfy your chocolate cravings! They’re gluten-free, keto-friendly, and super easy to throw together.

        Prep Time:10 minutes

        Cook Time:25 minutes

        Cooling Time:30 minutes

        Total Time:1 hour 5 minutes

        Author:Diabetic Foodie

        Servings:9

        Instructions

        • Preheat the oven to 350°F. Grease or line a 9×9 baking dish and set aside.

        • Combine all the ingredients in the blender.

        • Blend until a smooth, thick batter starts to form. Stop the blender, stir the batter, then blend again, repeating as necessary until the batter is completely incorporated.

        • Spread the batter into the prepared baking dish.

        • Bake for 22-25 minutes or until a toothpick inserted into the center comes out clean, then remove from the oven.

        • Allow the brownies to cool in the pan for at least 30 minutes before slicing.

        Recipe Notes

        This recipe is for 9 servings. If you slice into 9 brownies, each brownie will be 1 serving.
        If not following a keto diet, the low-carb sweeteners can be replaced 1:1 with regular sugar.
        Leftovers can be stored in an airtight container in the refrigerator for up to 5 days.

        Nutrition Info Per Serving

        Nutrition Facts

        Avocado Brownies

        Amount Per Serving

        Calories 269
        Calories from Fat 221

        % Daily Value*

        Fat 24.6g38%

        Saturated Fat 8.3g52%

        Trans Fat 0g

        Polyunsaturated Fat 0.7g

        Monounsaturated Fat 4.5g

        Cholesterol 88.8mg30%

        Sodium 259.4mg11%

        Potassium 153.2mg4%

        Carbohydrates 7.8g3%

        Fiber 5.4g23%

        Sugar 1.1g1%

        Protein 7.5g15%

        Net carbs 2.4g

        * Percent Daily Values are based on a 2000 calorie diet.

        Course: Dessert

        Cuisine: American

        Diet: Diabetic, Gluten Free

        Keyword: Avocado brownies, gluten-free, Keto brownies



        Sell Unused Diabetic Strips Today!

        Chicken Souvlaki Pita Sandwiches – My Bizzy Kitchen

        By electricdiet / July 29, 2021


        These chicken souvlaki pita sandwiches are my new favorite sandwich.  One reason is that after marinating the chicken, this comes together in less than 15 minutes!

        Is this a traditional chicken souvlaki?  I am not sure, all I know is that it’s delicious.

        The star of the show?  The pan fried lemon!

        this is a photo of chicken souvlaki in a pita

        this is a photo of a pan fried lemon

        Once cooked for about 2-3 minutes per side, the lemon rind becomes super soft and edible and adds just enough citrus notes to the sandwich that if you didn’t know it was in there, you would wonder where the punch of acid was coming from.  #love

        Ingredients

        • For the chicken:
        • 1 pound chicken breast, cut into bite sized pieces
        • 1 tablespoon grapeseed oil (or any oil)
        • 1 teaspoon dried rosemary
        • 1 teaspoon dried oregano
        • 1 teaspoon garlic powder
        • 3 tablespoons lemon juice
        • For the pitas:
        • 12 ounces skinny pizza dough (divided into 3 ounce portions)
        • avocado oil spray
        • seasoning of choice (I used chopped dried rosemary and a pinch of garlic powder)
        • For the sandwich:
        • 4 tablespoons hummus
        • diced cucumber and tomatoes
        • Ed’s ranch dressing (see notes below)
        • pan fried lemon slices

        Instructions

        1. Mix the chicken and all the ingredients through to the lemon juice. Let marinate for at least an hour.
        2. Heat skillet over medium heat. Add avocado oil spray and cook the chicken for about 10 minutes, or until it reaches an internal temperature of 160. Set aside.
        3. Roll out the pizza dough into a 5 inch circle. Cook in a skillet with avocado oil spray, and season with your favorite dry herbs. Cook each side for about 2-3 minutes.
        4. To assemble: one tablespoon hummus, add chicken and top with the cucumbers and tomatoes and drizzle a tablespoon of Ed’s ranch dressing.
        5. To make this sandwich EXTRA. After the pitas are cooked, cook two slices of lemon for 2-3 minutes, or until the rind starts to soften. Chop and add 1/2 lemon slice to each sandwich.
        6. To make this sandwich EXTRA EXTRA: spray a skillet with avocado oil spray and fold the sandwich like a taco, and pan fry each side for 2-3 minutes. The outside will be a bit crispy, but chewy in the center.

        Notes

        On #teampurple and #teamblue this sandwich is 5 points. On #teamgreen it’s 7 points.

        Nutrition Information:

        Yield: 4

        Serving Size: 1

        Amount Per Serving:

        Calories: 542Total Fat: 20gSaturated Fat: 3gTrans Fat: 0gUnsaturated Fat: 15gCholesterol: 98mgSodium: 615mgCarbohydrates: 47gFiber: 4gSugar: 4gProtein: 43g


        Did you make this recipe?

        Please leave a comment on the blog or share a photo on Instagram

        Let me know if you make this sandwich – I loved it so much it’s going on one of our cooking classes in August!

        Do you know about our cooking class?

        My daughter Hannah and I host four zoom classes a month.  Each class by itself is $20 for an hour class which includes printable recipes.  You can choose to sit back with a glass of wine and watch and the video will be recorded and emailed to you after class.  Or you can cook along with us!  You’ll get the full recipes 7 days before the next class.

        Become a member for $40 and save 50% and it’s only $10 a class.  We have 96 FIVE STAR REVIEWS!  Here are just a few recent ones:

        It’s so fun to see how many things you can make in just one hour. The recipes are always easy and flavorful, and Hannah and Biz are such a joy to watch. I love the cooking classes because there are so many recipes that I would never have thought to try on my own.

         

        Susan V.

        July 25th, 2021

        I learned more great recipes!! Radishes used as a replacement for potatoes! Yes, please! And it’s always so fun with Biz & Hannah!

         

        Kathy S.

        July 25th, 2021

        Biz and Hannah were amazing as always! They are fun to learn with and share SO much extra info!

         

        Kathleen F.

        July 25th, 2021

        Loved it can’t wait to try all the recipes.

         

        Wendy M.

        July 21st, 2021

        As usual, it was a joy to spend time with these ladies!! These recipes were fabulous, and I can’t wait to try them!

         

        If you ever have any questions about the cooking class, or a recipe I’ve posted, you can always reach me at [email protected] 

        Biz

        I am a widowed 52 year old trying to figure out my life after losing my husband after a long illness.

        Cooking and being in the kitchen feeds my soul!





        Sell Unused Diabetic Strips Today!

        Diabetes & Erectile Dysfunction: Causes & Treatment Options

        By electricdiet / July 27, 2021


        High blood sugars can impact the nerves, blood vessels, and blood flow in every part of your body — including your penis. For men with type 1 or type 2 diabetes, erectile dysfunction is a common complication of high blood sugar levels.

        Fortunately, erectile dysfunction is also something you can often prevent, manage, and treat.

        Let’s take a closer look at how diabetes can increase your risk of erectile dysfunction, the causes and symptoms, and today’s best treatment options.

        Diabetes & Erectile Dysfunction: Causes & Treatment Options

        What is erectile dysfunction?

        Erectile dysfunction (ED) is the inability to get or maintain an erection firm enough to participate in sexual intercourse, according to the Diabetes Research & Wellness Foundation (DRWF). 

        Approximately 18 million men across the United States struggle with ED.

        What happens during a healthy erection

        In a healthy man, an erection begins when his brain and/or nerve-endings in his penis are signaled. This signal (and arousal) triggers the smooth muscle along the shaft of the penis to relax, which increases blood flow in the spongy tissue that also runs along the shaft of the penis. 

        To ensure adequate blood flow to the penis, the blood vessels release nitric oxide into the bloodstream. This chemical tells the smooth muscles in your penis to relax which is what enables plenty of blood flow.

        This means there is then significantly more blood within the penis compared to when it is not being aroused.

        “As the blood flow increases, the pressure within the spongy tissue increases and the penis expands,” explains the DRWF. “As the pressure in the penis increases, the veins that drain blood out of the penis are compressed—trapping the blood within the penis—and an erection is achieved.”

        And then when a man ejaculates or you are no longer aroused, the pressure decreases, the excess blood flows out of the penis, and it returns to its softer, non-erect shape. 

        What happens during erectile dysfunction

        In a man struggling with erectile dysfunction, there are several things that can interfere with the function of the smooth muscles, the release of nitric oxide, and the restriction of blood flow.

        Erectile dysfunction can actually be the result of either a problem in your vascular system, endocrine system, or nervous system.

        It can also be related to a medication you’re taking or another health issue entirely.

        Pinpointing the exact cause of your erectile dysfunction can take some time. Your healthcare team will most likely examine the following aspects of your health to better determine the cause of your ED so it can be effectively treated:

        • Your sexual activity
        • Your sexual history 
        • Physical exam  
        • Signs of nerve damage throughout your body
        • Signs of circulation/blood flow issues throughout your body
        • Urinalysis
        • Cholesterol levels
        • Liver function 
        • Kidney function
        • Testosterone levels
        • Psychological issues

        Let’s take a look at the most common causes.

        Causes of erectile dysfunction

        Here are the most common and likely causes of ED according to the National Institute of Diabetes and Digestive and Kidney Diseases.

        Health conditions that can cause ED

        • Type 2 diabetes
        • Alcoholism
        • Obesity 
        • Smoking cigarettes
        • Lack of exercise
        • Illegal drug use
        • Heart and blood vessel disease 
        • Atherosclerosis
        • High blood pressure
        • Chronic kidney disease
        • Multiple sclerosis 
        • Peyronie’s disease
        • Parkinson’s disease
        • Injury from treatments for prostate cancer, including radiation therapy and prostate surgery
        • Injury to the penis, spinal cord, prostate, bladder, or pelvis
        • Surgery for bladder cancer 

        Psychological conditions that can cause ED

        • Fear of sexual failure
        • Anxiety 
        • Depression 
        • Guilt related to sexual activity or performance
        • Low self-esteem
        • Stress about sexual performance or stress in general

        Medications that can cause ED

        • Blood pressure medicines 
        • Antiandrogens—medicines used for prostate cancer therapy 
        • Antidepressants 
        • Tranquilizers, or prescription sedatives—medicines that make you calmer or sleepy
        • Appetite suppressants, or medicines that make you less hungry
        • Ulcer medicines
        • And more…

        Why diabetes causes erectile dysfunction

        “Fifty percent of men with diabetes will suffer from erectile dysfunction,” explains the DRWF. 

        Additionally, ED may actually develop 10 to 15 years earlier in a man with diabetes than a non-diabetic man because of the toll high blood sugars can take on the nerves and blood vessels in the penis.

        Damaged blood vessels

        As explained earlier, nitric oxide plays a critical role in increasing blood flow in the penis during arousal in order to become erect. 

        In a man with persistently high blood sugar levels, the blood vessels experience ongoing damage which significantly interferes with their ability to release nitric oxide. This means the smooth muscles don’t properly relax and blood cannot flow fully into the penis to create an erection.

        Damaged nerve endings

        Just like high blood sugar levels can damage the nerve endings in your fingers and toes, it can damage the nerves in your penis that enable you to feel the pleasure of sex. (The same is true for nerve endings in a woman’s clitoris.)

        This means you have two things working against your ability to enjoy sex: difficulty getting and sustaining an erection, and difficulty feeling the physical pleasure of sex which could hamper your ability to ejaculate.

        Treating erectile dysfunction

        If your erectile dysfunction can’t be treated by improving another issue in your overall health, more erection-focused treatment options are available.

        Improve your blood sugars

        First and foremost, improving your blood sugar levels is critical. No amount of Viagra is going to truly help if your body continues to endure damage from persistently high blood sugars.

        Work with your healthcare team to make adjustments in your diabetes medications, nutrition, and exercise to bring your blood sugars down into a healthier range. 

        You don’t have to achieve perfection — but simply bringing your average blood sugar down can have a big impact on your ED and every other aspect of your health.

        Medications to enhance erections

        You’ve likely heard of some or all of these medications that treat erectile dysfunction. They work by increasing blood flow to the penis when a man is sexually aroused. 

        Talk to your doctor about the best option for you because while they all work similarly, there are different choices within each drug based on the time of increased blood flow and the duration of the drug in your system.

        You absolutely should not take these drugs if:

        • You take a nitrate medication for chest pain
        • You take an alpha-blocker for high blood pressure or prostate problems
        • You have high or low blood pressure
        • You have a history of stroke or heart attack within the previous 6 months
        • You have kidney or liver disease
        • You have retinitis pigmentosa

        Penile suppository 

        This treatment involves a medication being inserted directly into your urethra (the tube within the shaft of your penis that expels both urine and semen). 

        The medication is absorbed into the lining of the urethra and increases your ability to maintain an erection without the risk of unwanted prolonged erections. 

        While it can be uncomfortable during and shortly after the insertion process of the pellet-shaped medication, it’s generally painless. 

        Penile Injections 

        This treatment involves an at-home injection of one of the following medications: alprostadil, phentolamine, or papaverine. 

        These drugs all work by increasing the size of the blood vessels within the penis which increases blood flow. They are generally expected to help you maintain an erection for up to one hour.

        While a doctor would teach you how to administer this injection the first time, it is something you would do on your own for ongoing use of this treatment.

        Unwanted prolonged erections are considered rare with this treatment.

        Vacuum Devices

        A less invasive and non-medication approach is a vacuum device that creates a suction around the shaft of the penis, encouraging the flow of blood. 

        A restrictive band is also used after the vacuum device has produced an erection. The band helps to ensure the blood supply stays in the penis during intercourse and is safe to leave on for about 30 minutes. 

        While you don’t need a doctor’s appointment or a prescription, it’s still important to purchase a higher-quality penile vacuum to ensure safety, comfort, and efficacy. Some doctors may even have vacuum devices you can borrow to try at home and determine if it’s an effective option for you.

        Surgery

        Lastly, and least likely something you’ll need, is a surgical treatment option for “impotence.” This surgery involves the implanting of a “rigid but flexible” rod that can be manually bent upward (for intercourse) or downward for day-to-day life.

        The second surgical option is an implant that can be inflated. A reservoir of fluid is placed under the skin in your scrotum or abdomen. Using the inflation device, the pressure is applied and fluid is pumped into the implanted cylinders located at the base of your penis.

        After intercourse is complete, the fluid drains from the penis so you are no longer erect. 

        Work with your healthcare to first pinpoint the cause of your ED

        Erectile dysfunction is a very common issue, but rushing to your doctor for a prescription of Viagra isn’t necessarily the answer. Work with your healthcare team to fully understand the cause of your ED before determining the best treatment plan for you! 

        And of course, work to improve your blood sugar levels, too.



        Sell Unused Diabetic Strips Today!

        Easy Vegetarian Gourmet – Roasted Summer Vegetables and Pasta Recipe

        By electricdiet / July 25, 2021


        Try Roasting as Vegetable Cooking Method for Healthy Flavor

        Looking for an easy, fresh and delicious way to get in those nutritious veggies? Try roasting as it brings out the explosion of flavor in this delectable vegetarian dish, Roasted Summer Vegetables and Pasta from Gulf Coast Favorites cookbook. You will not believe how simple this gourmet-style meal is to create. Get yourself a sous chef or look for pre-chopped veggies in your supermarket and it’s basically a one-step recipe!

        Eat the Rainbow for Nutrition!

        You are eating the rainbow in this hearty veggie dish. Squash alone provides vitamins A, B and C plus fiber, calcium, iron and folate. Grape tomatoes also have vitamins A and C – both powerful antioxidants – vitamin A is needed for eye, bone and skin health while vitamin C promotes immunity and healing. Not to mention, tomatoes are rich in lycopene the valuable antioxidant found to reduce the risk of cancer.

        Roasted Summer Vegetables and Pasta
        This easy recipe captures the essence of summer. Fresh basil is a key ingredient, while roasted garlic adds a truly intensive flavor.

          Servings8 (1-cup) servings

          Ingredients

          • 1


            package small tubular pasta8-ounce

          • 3


            large yellow squashabout 4 cups, halved and sliced 1-inch thick crosswise

          • 1pint


            grape or cherry tomatoes

          • 1


            red onionhalved and sliced 1/2-inch thick

          • 6cloves


            garlicsliced

          • 3tablespoons


            olive oil



          • salt and pepper to taste

          • 3tablespoons


            grated Parmesan cheese

          • 1/2cup


            torn fresh basil leaves

          Instructions
          1. Preheat oven to 450°F. Line a baking sheet with foil. Cook pasta according to package directions, omitting any salt or oil. Drain and set aside.

          2. Spread squash, tomatoes, onion, and garlic on prepared baking sheet. Toss with oil and season to taste. Roast in oven for 35–40 minutes.

          3. Add pasta to pan, mixing with vegetables. Sprinkle with Parmesan cheese, add basil, and toss well.

          Recipe Notes

          Calories 189 | Calories from fat 29% | Fat 6 g, Saturated Fat 1 g | Cholesterol 2 mg | Sodium 38 mg, Carbohydrate 28 g | Dietary Fiber 2 g | Sugars 5 g | Protein 6 g, Diabetic Exchanges1 1/2 starch | 1 vegetable | 1 fat

          What You Will Need to Make this Recipe

          Barilla Whole Grain Pasta, Elbows, 16 OunceBarilla Whole Grain Pasta, Elbows, 16 OunceBarilla Whole Grain Pasta, Elbows, 16 OunceReynolds Aluminum Foil Sheets - 12 x 10.75 Inches, 500 SheetsReynolds Aluminum Foil Sheets – 12 x 10.75 Inches, 500 SheetsReynolds Aluminum Foil Sheets - 12 x 10.75 Inches, 500 SheetsOXO Good Grips Wooden Spoon Set, 3-Piece,BrownOXO Good Grips Wooden Spoon Set, 3-Piece,BrownOXO Good Grips Wooden Spoon Set, 3-Piece,Brown

          Choose Whole Grain Pasta

          While you are at it, choose whole grain pasta over regular pasta for more vitamins, minerals and fiber per serving. They are both interchangeable in recipes as they are prepared the same way; however whole wheat pasta provides 6 grams of fiber per serving versus only 2.5 grams from regular. This will help weight maintenance as fiber helps you feel satisfied and full longer, contributes to a healthy digestive system and may also help lower cholesterol and regulate blood sugar.

          Louisiana Cookbook Offers Best Healthy Recipes

          These vegetables are in season in the summer, you can find them year round.  Make this using your favorite veggies and whatever you find in season. Roasting is always a delicious healthy cooking method!

          If you want healthy southern recipes, turn to Gulf Coast Favorites cookbook.  All of Holly’s cookbooks have a ‘Pantry Stocking Guide’ to help stock your pantry and help you whip up healthy meals in a hurry! “A well-stocked pantry is like a permanent shopping list!” Then, you can cook any meal in 30 minutes.

          3 Diabetic Dinners Grocery Shopping List

          Want More Delicious Diabetic Dinners with Grocery Shopping List?!

          If you are looking for more super satisfying diabetic meals the whole family will love, check this 3 Diabetic Dinners Meal Plan out! This recipe plus 2 more favorite diabetic friendly dinners are ready for you to cook this week, complete with your own printable shopping list!

          Get All of Holly’s Healthy Easy Cookbooks

          The post Easy Vegetarian Gourmet – Roasted Summer Vegetables and Pasta Recipe appeared first on The Healthy Cooking Blog.



          Sell Unused Diabetic Strips Today!

          From the Triumvirate to the Ominous Octet: A New Paradigm for the Treatment of Type 2 Diabetes Mellitus

          By electricdiet / July 23, 2021


          Insulin resistance in muscle and liver and β-cell failure represent the core pathophysiologic defects in type 2 diabetes. It now is recognized that the β-cell failure occurs much earlier and is more severe than previously thought. Subjects in the upper tertile of impaired glucose tolerance (IGT) are maximally/near-maximally insulin resistant and have lost over 80% of their β-cell function. In addition to the muscle, liver, and β-cell (triumvirate), the fat cell (accelerated lipolysis), gastrointestinal tract (incretin deficiency/resistance), α-cell (hyperglucagonemia), kidney (increased glucose reabsorption), and brain (insulin resistance) all play important roles in the development of glucose intolerance in type 2 diabetic individuals. Collectively, these eight players comprise the ominous octet and dictate that: 1) multiple drugs used in combination will be required to correct the multiple pathophysiological defects, 2) treatment should be based upon reversal of known pathogenic abnormalities and not simply on reducing the A1C, and 3) therapy must be started early to prevent/slow the progressive β-cell failure that already is well established in IGT subjects. A treatment paradigm shift is recommended in which combination therapy is initiated with diet/exercise, metformin (which improves insulin sensitivity and has antiatherogenic effects), a thiazolidinedione (TZD) (which improves insulin sensitivity, preserves β-cell function, and exerts antiatherogenic effects), and exenatide (which preserves β-cell function and promotes weight loss). Sulfonylureas are not recommended because, after an initial improvement in glycemic control, they are associated with a progressive rise in A1C and progressive loss of β-cell function.

          NATURAL HISTORY OF TYPE 2 DIABETES

          The natural history of type 2 diabetes has been well described in multiple populations (116) (rev. in (17,18). Individuals destined to develop type 2 diabetes inherit a set of genes from their parents that make their tissues resistant to insulin (1,16,1924). In liver, the insulin resistance is manifested by an overproduction of glucose during the basal state despite the presence of fasting hyperinsulinemia (25) and an impaired suppression of hepatic glucose production (HGP) in response to insulin (26), as occurs following a meal (27). In muscle (19,26,28,29), the insulin resistance is manifest by impaired glucose uptake following ingestion of a carbohydrate meal and results in postprandial hyperglycemia (27). Although the origins of the insulin resistance can be traced to their genetic background (17,20), the epidemic of diabetes that has enveloped westernized countries is related to the epidemic of obesity and physical inactivity (30). Both obesity (31) and decreased physical activity (32) are insulin-resistant states and, when added to the genetic burden of the insulin resistance, place a major stress on the pancreatic β-cells to augment their secretion of insulin to offset the defect in insulin action (1,17). As long as the β-cells are able to augment their secretion of insulin sufficiently to offset the insulin resistance, glucose tolerance remains normal (33). However, with time the β-cells begin to fail and initially the postprandial plasma glucose levels and subsequently the fasting plasma glucose concentration begin to rise, leading to the onset of overt diabetes (14,12,17,18,34). Collectively, the insulin resistance in muscle and liver and β-cell failure have been referred to as the triumvirate (1) (Fig. 1). The resultant hyperglycemia and poor metabolic control may cause a further decline in insulin sensitivity, but it is the progressive β-cell failure that determines the rate of disease progression.

          FIG. 1.
          FIG. 1.

          Pathogenesis of type 2 diabetes: the triumvirate. Insulin resistance in muscle and liver and impaired insulin secretion represent the core defects in type 2 diabetes (1). See text for a more detailed explanation.

          The natural history of type 2 diabetes described above (1) is depicted by a prospective study carried out by Felber and colleagues in Lausanne, Switzerland (35) (Fig. 2). Although the study was originally cross-sectional in nature, subjects were followed up for 6 years and shown to progress from one category of glucose intolerance to the next. All subjects had a euglycemic insulin clamp to measure tissue sensitivity to insulin and an oral glucose tolerance test (OGTT) to provide an overall measure of glucose homeostasis and β-cell function. In lean subjects with normal glucose tolerance (NGT), the mean plasma glucose and insulin concentrations during the OGTT were 115 mg/dl and 62 μU/ml, while the mean rate of insulin-stimulated glucose disposal (measured with a 40 mU/m2 per min euglycemic insulin clamp) was 265 mg/m2 per min. Obesity was associated with a 29% decline in insulin sensitivity, but glucose tolerance remained perfectly normal because of the compensatory increase in insulin secretion. With time the obese NGT individuals progressed to IGT in association with a further 28% reduction in insulin sensitivity (total decrease = 57% from NGT to IGT). However, the rise in plasma glucose concentration was quite modest because of a further compensatory increase in insulin secretion. However, people with IGT are in a very precarious position. They are maximally or near-maximally insulin resistant, and their β-cells are functioning at less than maximum capacity. With time the β-cells cannot continue to produce these very large amounts of insulin and the obese IGT individual progresses to overt diabetes. The decline in glucose tolerance is associated with a marked decrease in insulin secretion without further change in insulin sensitivity (Fig. 2). This characteristic rise in insulin response to insulin resistance and hyperglycemia, followed by a subsequent decline, has been referred to as Starling’s curve of the pancreas (1). This natural history of type 2 diabetes has been demonstrated in many prospective studies carried out in many diverse ethnic populations (118,36,37). Although the relative contributions of insulin resistance and β-cell failure to the development of type 2 diabetes may differ in different ethnic groups (38), the onset and pace of β-cell failure determines the rate of progression of hyperglycemia.

          FIG. 2.
          FIG. 2.

          Natural history of type 2 diabetes. The plasma insulin response (○) depicts the classic Starling’s curve of the pancreas (1). See text for a more detailed explanation. ●, insulin-mediated glucose uptake (top panel).

          β-CELL FUNCTION

          Although the plasma insulin response to the development of insulin resistance typically is increased during the natural history of type 2 diabetes (Fig. 2), this does not mean that the β-cell is functioning normally. To the contrary, recent studies from our group have demonstrated that the onset of β-cell failure occurs much earlier and is more severe than previously appreciated. In the San Antonio Metabolism (SAM) study and the Veterans Administration Genetic Epidemiology Study (VAGES), we examined a large number of subjects with NGT (n = 318), IGT (n = 259), and type 2 diabetes (n = 201) (3942). All subjects had an OGTT with plasma glucose and insulin concentrations measured every 15 min to evaluate overall glucose tolerance and β-cell function and a euglycemic insulin clamp to measure insulin sensitivity. It now is recognized that simply measuring the plasma insulin response to a glucose challenge does not provide a valid index of β-cell function (43). The β-cell responds to an increment in glucose (ΔG) with an increment in insulin (ΔI) (43). Thus, a better measure of β-cell function is ΔI/ΔG. However, the β-cell also is keenly aware of the body’s sensitivity to insulin and adjusts its secretion of insulin to maintain normoglycemia (33,4345). Thus, the gold standard for measuring β-cell function is the insulin secretion/insulin resistance (ΔI/ΔG ÷ IR), or so called disposition, index. Note that insulin resistance is the inverse of insulin sensitivity. Supplemental Fig. A1 (available in an online appendix at http://diabetes.diabetesjournals.org/cgi/content/full/db09-9028/DC1) displays the glucose area under the curve (AUC) and insulin AUC in NGT, IGT, and type 2 diabetic subjects who participated in VAGES and SAM. In the right panel, the typical inverted U-shaped or Starling’s curve of the pancreas for the plasma insulin response is evident. Although subjects with IGT have an increase in the absolute plasma insulin concentration, this should not be interpreted to mean that the β-cells in these individuals are functioning normally.

          Figure 3 depicts the insulin secretion/insulin resistance index (ΔI/ΔG ÷ IR) in NGT, IGT, and type 2 diabetic subjects as a function of the 2-h plasma glucose concentration during the OGTT. If a 2-h plasma glucose <140 mg/dl is considered to represent “normal” glucose tolerance, subjects in the upper tertile (2-h PG = 120–139 mg/dl) have lost two-thirds of their β-cell function (see arrow in Fig. 3). Most disturbingly, subjects in the upper tertile of IGT (2-h PG = 180–199 mg/dl) have lost 80–85% of their β-cell function (see second arrow in Fig. 3). Although not commented upon, similar conclusions can be reached from data in previous publications (2,3,7,15). The therapeutic implications of these findings are readily evident. By the time that the diagnosis of diabetes is made, the patient has lost over 80% of his/her β-cell function, and it is essential that the physician intervene aggressively with therapies known to correct known pathophysiological disturbances in β-cell function.

          FIG. 3.
          FIG. 3.

          Insulin secretion/insulin resistance (disposition) index (ΔI/ΔG ÷ IR) in individuals with NGT, IGT, and type 2 diabetes (T2DM) as a function of the 2-h plasma glucose (PG) concentration in lean and obese subjects (3942).

          In biomedical phenomena, most reactions take place as a log function. Figure 4 depicts the natural log of the 2-h plasma glucose concentration during the OGTT as a function of the natural log of the insulin secretion/insulin resistance (β-cell function) index. These two variables are strongly and linearly related with an r value of 0.91 (P < 0.00001). There are no cut points that distinguish NGT from IGT from type 2 diabetes. Rather, glucose intolerance is a continuum, and subjects simply move up and down this curve as a function of the insulin secretion/insulin resistance index. Therefore, the current diagnostic criteria (46) for IGT and type 2 diabetes are quite arbitrary and, like plasma cholesterol, glucose tolerance should be viewed as a continuum of risk. The higher the 2-h plasma glucose concentration, even within the range of IGT, the greater is the risk for microvascular complications (see subsequent discussion).

          FIG. 4.
          FIG. 4.

          Natural log of the 2-h plasma glucose (PG) concentration versus natural log of the insulin secretion/insulin resistance index (measure of β-cell function) (3942). T2DM, type 2 diabetes.

          Even more ominous are the observations of Butler et al. (47). In a postmortem analysis, these investigators quantitated relative β-cell volume and related it to the fasting plasma glucose concentration. As individuals progressed from NGT to impaired fasting glucose (IFG), there was a 50% decline in β-cell volume, suggesting a significant loss of β-cell mass long before the onset of type 2 diabetes. With the progression to overt diabetes, there was a further and significant loss of β-cell volume. Although β-cell volume should not be viewed to be synonymous with β-cell mass, these results suggest that significant loss of β-cell mass occurs long before the onset of type 2 diabetes, according to current diagnostic criteria (46).

          In summary, our findings (4042) demonstrate that, at the stage of IGT, individuals have lost over 80% of their β-cell function, while the results of Butler et al. (47) suggest that subjects with “pre-diabetes” have lost approximately half of their β-cell volume.

          “PRE-DIABETES”

          The recently published results of the Diabetes Prevention Program (DPP) (48) have raised further concern about the clinical implications of the term “pre-diabetes.” In the DPP, individuals who entered with a diagnosis of IGT and still had IGT 3 years later had a 7.9% incidence of background diabetic retinopathy at the time of study end. Individuals who entered the DPP with IGT but who progressed to diabetes after 3 years had a 12.6% incidence of diabetic retinopathy at the time of study end. Moreover, these IGT individuals developed diabetic retinopathy with an A1C of 5.9 and 6.1%, respectively, values much less than the current American Diabetes Association (ADA) treatment goal of 7% (49). Peripheral neuropathy also is a common finding in IGT, occurring in as many as 5–10% individuals (50,51).

          In summary, individuals with IGT are maximally or near- maximally insulin resistant, they have lost 80% of their β-cell function, and they have an approximate 10% incidence of diabetic retinopathy. By both pathophysiological and clinical standpoints, these pre-diabetic individuals with IGT should be considered to have type 2 diabetes.

          The clinical implications of these findings for the treatment of type 2 diabetes are that the physician must intervene early, at the stage of IGT or IFG, with interventions that target pathogenic mechanisms known to promote β-cell failure.

          PATHOGENESIS OF β-CELL FAILURE (supplemental Fig. A2)

          Age.

          Advancing age plays an important role in the progressive β-cell failure that characterizes type 2 diabetes. Numerous studies (5254) have demonstrated a progressive age-related decline in β-cell function. This is consistent with the well-established observation that the incidence of diabetes increases progressively with advancing age.

          Genes.

          β-Cell failure also clusters in families, and studies in first-degree relatives of type 2 diabetic parents and in twins have provided strong evidence for the genetic basis of the β-cell dysfunction (5558). Impaired insulin secretion has been shown to be an inherited trait in Finnish families with type 2 diabetes with evidence for a susceptibility locus on chromosome 12 (59). Most recently, a number of genes associated with β-cell dysfunction in type 2 diabetic individuals have been described (20,6062). Of these genes, the transcription factor TCF7L2 is best established (60,61). Studies by Groop and colleagues (63) have shown that the T-allele of single nucleotide polymorphism rs7903146 of the TCF7L2 gene is associated with impaired insulin secretion in vivo and reduced responsiveness to glucagon-like peptide 1 (GLP-1). Both the CT and TT genotypes predict type 2 diabetes in multiple ethnic groups (64). In both the Malmo and Botnia studies, presence of either the CT or TT genotype was associated with a significant reduction in the diabetes-free survival time, with odds ratios of 1.58 and 1.61, respectively (63). TCF7L2 encodes for a transcription factor involved in Wnt signaling, which plays a central role in the regulation of β-cell proliferation and insulin secretion (65).

          Unfortunately, at present there are no known therapeutic interventions that can reverse either the age-related decline or genetic-related factors responsible for impaired insulin secretion. However, there are a number of causes of β-cell failure that can be reversed or ameliorated.

          Insulin resistance.

          Insulin resistance, by placing an increased demand on the β-cell to hypersecrete insulin, also plays an important role in the progressive β-cell failure of type 2 diabetes. Therefore, interventions aimed at enhancing insulin sensitivity are of paramount importance. The precise mechanism(s) via which insulin resistance leads to β-cell failure remain(s) unknown. It commonly is stated that the β-cell, by being forced to continuously hypersecrete insulin, eventually wears out. Although simplistic in nature, this explanation lacks a mechanistic cause. An alternate hypothesis, for which considerable evidence exists, is that the cause of the insulin resistance is also directly responsible for the β-cell failure. Thus, just as excess deposition of fat (LC-fatty acyl CoAs, diacylglycerol, and ceramide) in liver and muscle has been shown to cause insulin resistance in these organs, i.e., lipotoxicity, deposition of fat in the β-cell leads to impaired insulin secretion and β-cell failure (see subsequent discussion). Similarly, hypersecretion of islet amyloid polypeptide (IAPP), which is co-secreted in a one-to-one ratio with insulin, can lead to progressive β-cell failure (see subsequent discussion).

          Lipotoxicity.

          Elevated plasma free fatty acid (FFA) levels impair insulin secretion, and this has been referred to as lipotoxicity (66,67). Studies from our laboratory (24) have shown that a physiological elevation of the plasma FFA concentration for as little as 48 h markedly impairs insulin secretion in genetically predisposed individuals (Fig. 5). In this study, the normal glucose tolerant offspring of two type 2 diabetic parents received a 48-h infusion of saline or Intralipid to approximately double the plasma FFA concentration and then received a 2-h hyperglycemic (125 mg/dl) clamp. Compared with saline infusion, lipid infusion markedly impaired both the first and second phases of C-peptide release and reduced the insulin secretory rate, calculated by deconvolution of the plasma C-peptide curve. Conversely, a sustained reduction in plasma FFA concentration with acipimox in nondiabetic subjects with a strong family history of type 2 diabetes improved insulin secretion (68). In vivo studies in rodents (6971) and in humans (72), as well as in vitro studies (73), also support an important role for lipotoxicity. Thus, when human pancreatic islets were incubated for 48 h in presence of 2 mmol/l FFA (oleate-to-palmitate ratio 2:1), insulin secretion, especially the acute insulin response, was markedly reduced. Exposure to FFA caused a marked inhibition of insulin mRNA expression, decreased glucose-stimulated insulin release, and reduction of islet insulin content (69). Rosiglitazone, a peroxisome proliferator–activated receptor (PPAR)γ agonist, prevented all of these deleterious effects of FFA (74). Consistent with these in vitro observations, we have shown that both rosiglitazone and pioglitazone markedly improve the insulin secretion/insulin resistance index in vivo in type 2 diabetic humans (75).

          FIG. 5.
          FIG. 5.

          Effect of physiological elevation (48 h) in the plasma FFA concentration (brought about by lipid infusion) on plasma C-peptide concentration (left) and insulin secretory response (deconvolution of the palsma C-peptide curve) (right) in offspring of two type 2 diabetic parents (24).

          In summary, interventions—such as weight loss and TZDs—that mobilize fat out of the β-cell would be expected to reverse lipotoxicity and preserve β-cell function.

          Glucotoxicity.

          Chronically elevated plasma glucose levels also impair β-cell function, and this has been referred to as glucotoxicity (76). Studies by Rossetti et al. (77) have provided definitive proof of this concept (Fig. 6). Partially pancreatectomized diabetic rats are characterized by severe defects in both first- and second-phase insulin secretion compared with control rats. Following treatment with phlorizin, an inhibitor of renal glucose transport, the plasma glucose profile was normalized without changes in any other circulating metabolites. Normalization of the plasma glucose profile was associated with restoration of both the first and second phases of insulin secretion. In vitro studies with isolated human islets also have demonstrated that chronic exposure to elevated plasma glucose levels impairs insulin secretion (78,79). In rats, Leahy et al. (80) showed that elevation of the mean day-long plasma glucose concentration in vivo by as little as 16 mg/dl leads to a marked inhibition of glucose-stimulated insulin secretion in the isolated perfused pancreas.

          FIG. 6.
          FIG. 6.

          First-phase (0–10 min) and second-phase (10–120 min) plasma insulin response during hyperglycemic clamp in partially pancreatectomized diabetic (DIAB) and control (CON) rats (77). PHLOR, phlorizin.

          Thus, strict glycemic control is essential not only to prevent the microvascular complications of diabetes but also to reverse the glucotoxic effect of chronic hyperglycemia on the β-cells (8084), as well as on hepatic and muscle insulin resistance.

          IAPP.

          Hypersecretion of IAPP and amyloid deposition within the pancreas have also been implicated in the progressive β-cell failure of type 2 diabetes (85,86). Although convincing evidence for a pathogenic role of IAPP exists in rodents (87,88), the natural history of pancreatic amylin deposition in humans has yet to be defined (89).

          To address this issue, Chavez and colleagues (90,91) examined the relationship between pancreatic amylin deposition and β-cell function in 150 baboons spanning a wide range of glucose tolerance. Since the baboon genome shares more than 98% homology with the human genome, results in baboons are likely to be pertinent to those in humans (92). As the relative amyloid area of the pancreatic islets increased from <5.5% to >51%, there was a progressive decline in the log of HOMA-β. The decline in β-cell function was strongly correlated with the increase in fasting plasma glucose concentration. Studies by Butler and colleagues (93,94) have also provided additional evidence for a β-cell toxic effect for the soluble IAPP fibrils.

          Because amylin is secreted in a one-to-one ratio with insulin (95,96) and IAPP oligomers are toxic (89,93,94), interventions that improve insulin sensitivity, i.e., TZDs/metformin/weight loss, by leading to a reduction in insulin secretion, would be expected to preserve β-cell function on a long-term basis. Of note, rosiglitazone has been shown to protect human islets against human IAPP toxicity by a phosphatidylinositol (PI) 3-kinase–dependent pathway (97).

          Incretins.

          Abnormalities in the incretin axis have been shown to play an important role in the progressive β-cell failure of type 2 diabetes. GLP-1 and glucose-dependent insulinotrophic polypeptide (also called gastric inhibitory polypeptide [GIP]) account for ∼90% of the incretin effect (98100). In type 2 diabetes, there is a deficiency of GLP-1 (98100) and resistance to the action of GIP (102105). The deficiency of GLP-1 can be observed in individuals with IGT and worsens progressively with progression to type 2 diabetes (101). In addition to deficiency of GLP-1, there is resistance to the stimulatory effect of GLP-1 on insulin secretion (106,107). In contrast to GLP-1, plasma levels of GIP are elevated in type 2 diabetes, yet circulating plasma insulin levels are reduced (108). This suggests that there is β-cell resistance to the stimulatory effect of GIP on insulin secretion, and this, in fact, has been demonstrated (105). Of note, recent studies have shown that tight glycemic control can restore the β-cells’ insulin secretory response to GIP (109). Thus, β-cell resistance to GIP is another manifestation of glucotoxicity.

          Because GLP-1 deficiency occurs early in the natural history of type 2 diabetes, it follows that GLP-1 replacement therapy is a logical choice to restore the deficient insulin response that is characteristic of the diabetic condition.

          Summary: β-cell dysfunction and development of type 2 diabetes.

          In summary, although insulin resistance in liver and muscle are well established early in the natural history of the disease, type 2 diabetes does not occur in the absence of progressive β-cell failure.

          INSULIN RESISTANCE

          Both the liver and muscle are severely resistant to insulin in individuals with type 2 diabetes (rev. in (1,17,18). However, when discussing insulin resistance, it is important to distinguish what is responsible for the insulin resistance in the basal or fasting state and what is responsible for the insulin resistance in the insulin-stimulated state.

          Liver.

          The brain has an obligate need for glucose and is responsible for ∼50% of glucose utilization under basal or fasting conditions (110). This glucose demand is met primarily by glucose production by the liver and to a smaller extent the kidneys (110). Following an overnight fast, the liver of nondiabetic individuals produces glucose at the rate of ∼2 mg/kg per min (1,25) (Fig. 7). In type 2 diabetic individuals, the rate of basal HGP is increased, averaging ∼2.5 mg/kg per min (1,25) (Fig. 7). In an average 80-kg person, this amounts to the addition of an extra 25–30 g of glucose to the systemic circulation every night. As shown in Fig. 7, control subjects cluster with a fasting plasma glucose concentration of ∼85–90 mg/dl, and their rate of HGP averages ∼2 mg/kg per min. In type 2 diabetic subjects, as the rate of basal HGP rises, so also does the fasting plasma glucose concentration, and these two variables are strongly correlated with an R value of 0.847 (P < 0.001). This overproduction of glucose by the liver occurs in the presence of fasting plasma insulin levels that are increased 2.5- to 3-fold, indicating severe resistance to the suppressive effect of insulin on HGP. Similar observations have been made by others (27,110116). The increase in basal HGP is explained entirely by an increase in hepatic gluconeogenesis (117119). In addition to hepatic insulin resistance, multiple other factors contribute to accelerated rate of HGP including: 1) increased circulating glucagon levels and enhanced hepatic sensitivity to glucagon (120122); 2) lipotoxicity leading to increased expression and activity of phosphoenolpyruvate carboxykinase and pyruvate carboxylase (123), the rate-limiting enzymes for gluconeogenesis; and 3) glucotoxicity, leading to increased expression and activity of glucose-6-phosphatase, the rate-limiting enzyme for glucose escape from the liver (124).

          FIG. 7.
          FIG. 7.

          Basal HGP (left) in control and type 2 diabetic (T2DM) subjects. The relationship between basal HGP and fasting plasma glucose (FPG) concentration is shown on the right (1,25).

          Muscle.

          Using the euglycemic insulin clamp technique (125) in combination with tritiated glucose to measure total body glucose disposal, we (1,18,19,26,28,29,40,111,126) and others (12,16,44,45,116,127130) conclusively have demonstrated that lean type 2 diabetic individuals are severely resistant to insulin compared with age-, weight-, and sex-matched control subjects (Fig. 8). Employing femoral arterial and venous catheterization in combination with the insulin clamp, we further demonstrated that muscle insulin resistance could account for over 85–90% of the impairment in total body glucose disposal in type 2 diabetic subjects (19,28) (Fig. 8). Even though the insulin clamp was extended for an additional hour in diabetic subjects to account for the delay in onset of insulin action, the rate of insulin-stimulated glucose disposal remained 50% less than in control subjects. A similar defect in insulin-stimulated muscle glucose uptake in type 2 diabetic subjects has been demonstrated by others (131133).

          FIG. 8.
          FIG. 8.

          Insulin-stimulated total body glucose uptake (left) and insulin-stimulated leg glucose uptake (right) in control (CON) and type 2 diabetic (T2DM) subjects (28,29).

          In type 2 diabetic subjects we, as well as others, have documented the presence of multiple intramyocellular defects in insulin action (rev. in (17,18,126), including impaired glucose transport and phosphorylation (19,133137), reduced glycogen synthesis (111,138,139), and decreased glucose oxidation (26,140142). However, more proximal defects in the insulin signal transduction system play a paramount role in the muscle insulin resistance (126,143).

          Insulin signal transduction.

          For insulin to work, it must first bind to and then activate the insulin receptor by phosphorylating key tyrosine residues on the β chain (126,144146) (supplemental Fig. A3). This results in the translocation of insulin receptor substrate (IRS)-1 to the plasma membrane, where it interacts with the insulin receptor and also undergoes tyrosine phosphorylation. This leads to the activation of PI 3-kinase and Akt, resulting in glucose transport into the cell, activation of nitric oxide synthase with arterial vasodilation (147149), and stimulation of multiple intracellular metabolic processes.

          Studies from our laboratory were the first to demonstrate in humans that the ability of insulin to tyrosine phosphorylate IRS-1 was severely impaired in lean type 2 diabetic individuals (126,143,150), in obese normal glucose tolerant individuals (143), and in the insulin-resistant, normal glucose tolerant offspring of two type 2 diabetic parents (151,152) (Fig. 9). Similar defects have been demonstrated by others in human muscle (21,23,153156). This defect in insulin signaling leads to decreased glucose transport, impaired release of nitric oxide with endothelial dysfunction, and multiple defects in intramyocellular glucose metabolism.

          FIG. 9.
          FIG. 9.

          Relationship between impaired insulin signal transduction and accelerated atherogenesis in insulin-resistant subjects, i.e., type 2 diabetes and obesity (126,143).

          In contrast to the severe defect in IRS-1 activation, we have shown that the mitogen-activated protein (MAP) kinase pathway, which can be activated by Shc, is normally responsive to insulin (143) (Fig. 9). The MAP kinase pathway, when stimulated, leads to the activation of a number of intracellular pathways involved in inflammation, cellular proliferation, and atherosclerosis (157159). Thus, the block at the level of IRS-1 impairs glucose transport into the cell and the resultant hyperglycemia stimulates insulin secretion. Because the MAP kinase pathway retains its sensitivity to insulin (143,159,160), this causes excessive stimulation of this pathway and activation of multiple intracellular pathways involved in inflammation and atherogenesis. This, in part, explains the strong association between insulin resistance and atherosclerotic cardiovascular disease in nondiabetic, as well as in type 2 diabetic, individuals (161166).

          As shown by Miyazaki et al. (150) in our laboratory, there is only one class of oral antidiabetic drugs—the TZDs—that simultaneously augment insulin signaling through IRS-1 and inhibit the MAP kinase pathways. These molecular observations help to explain the recent results from the CHICAGO (Carotid Intima-Media Thickness in Atherosclerosis Using Pioglitazone) (167) and PERISCOPE (Pioglitazone Effect on Regression of Intravascular Sonographic Coronary Obstruction Prospective Evaluation) (168) studies, in which pioglitazone was shown to halt the progression of carotid intima-media thickness and coronary atherosclerosis, respectively, in type 2 diabetic patients. Consistent with these anatomical studies, pioglitazone in the PROactive study (169) was shown to decrease (P = 0.027) the second principal end point of death, myocardial infarction, and stroke by 16%. The primary composite end point was reduced by 10% but did not reach statistical significance because of an increase in leg revascularization, which is not an end point in most cardiovascular studies. This is not surprising since gravity, not lipids or blood pressure, is the most important risk for peripheral vascular disease.

          Route of glucose administration: oral vs. intravenous.

          The euglycemic insulin clamp, by maintaining plasma glucose and insulin levels constant, has become the gold standard for quantitating insulin sensitivity. However, the normal route of glucose administration in every day life is via the gastrointestinal tract. Using a double tracer technique (1-14C-glucose orally and 3-3H-glucose intravenously) in combination with hepatic vein catheterization, we set out to examine the disposal of oral versus intravenous glucose in healthy, normal glucose tolerant and type 2 diabetic subjects (170174).

          Under basal conditions, with fasting plasma glucose and insulin concentrations of 90 mg/dl and 11 mU/ml, respectively, the splanchnic tissues, which primarily reflect the liver, take up glucose at the rate of 0.5 mg/kg per min (Fig. 10). When insulin was administered intravenously to raise the plasma insulin concentration to 1,189 μU/ml, while maintaining euglycemia, in subjects with NGT, no stimulation of hepatic glucose uptake was observed. When insulin was infused with glucose to elevate both glucose and insulin levels, hepatic glucose uptake increased, but only in proportion to the increase in plasma glucose concentration, despite plasma insulin concentrations in excess of 1,000 μU/ml. In contrast, when glucose was administered orally, hepatic glucose uptake increased 4.5-fold, despite plasma insulin and glucose concentrations that were much lower than with intravenous glucose plus insulin administration (Fig. 10). When the same oral glucose load was administered to type 2 diabetic individuals, despite higher plasma glucose and insulin concentrations than in nondiabetic subjects, hepatic glucose uptake was reduced by >50%. Thus, individuals with type 2 diabetes lack the gut factor that is responsible for augmenting hepatic glucose uptake following glucose ingestion.

          FIG. 10.
          FIG. 10.

          Hepatic glucose uptake in nondiabetic and diabetic (DIAB) subjects as a function of plasma glucose and insulin concentrations and route of glucose administration (170174).

          Summary: pathogenesis.

          In summary, impaired insulin secretion, decreased muscle glucose uptake, increased HGP, and decreased hepatic glucose uptake all contribute to the glucose intolerance in type 2 diabetic individuals.

          DYSHARMONIOUS QUARTET (SUPPLEMENTAL FIG. A4)

          The last decade has taught us that the fat cell also plays a pivotal role in the pathogenesis of type 2 diabetes. Collectively, the fat cell and his three friends—the muscle, liver, and β-cell—comprise the harmonious quartet, or perhaps more appropriately, the dysharmonious quartet, since together they sing a very bad tune for the diabetic patient. Considerable evidence implicates deranged adipocyte metabolism and altered fat topography in the pathogenesis of glucose intolerance in type 2 diabetes (17,26,68,127,175178): 1) Fat cells are resistant to insulin’s antilipolytic effect, leading to day-long elevation in the plasma FFA concentration (26,140,175179). 2) Chronically increased plasma FFA levels stimulate gluconeogenesis (180182), induce hepatic/muscle insulin resistance (142,183185), and impair insulin secretion (24,186). These FFA-induced disturbances are referred to as lipotoxicity. 3) Dysfunctional fat cells produce excessive amounts of insulin resistance–inducing, inflammatory, and atherosclerotic-provoking adipocytokines and fail to secrete normal amounts of insulin-sensitizing adipocytokines such as adiponectin (175,176). 4) Enlarged fat cells are insulin resistant and have diminished capacity to store fat (187,188). When adipocyte storage capacity is exceeded, lipid “overflows” into muscle, liver, and β-cells, causing muscle/hepatic insulin resistance and impaired insulin secretion (rev. in (175,176). Lipid can also overflow into arterial vascular smooth cells, leading to the acceleration of atherosclerosis.

          Using 14C-palmitate in combination with the insulin clamp technique, Groop et al. (26) demonstrated that the antilipolytic effect of insulin was markedly impaired in lean type 2 diabetic subjects, as well as in obese nondiabetic subjects (140). In both type 2 diabetic (supplemental Fig. A5) and obese nondiabetic subjects, the ability of insulin to suppress the plasma FFA concentration and inhibit FFA turnover is significantly impaired compared with lean normal glucose tolerant control subjects at all plasma insulin concentrations spanning the physiological and pharmacological range.

          Many investigators, including Boden, Shulman, and ourselves (181,182,185,189), have shown that a physiological elevation in the plasma FFA concentration stimulates HGP and impairs insulin-stimulated glucose uptake in liver (190) and muscle (151,182185,189194). As discussed earlier, we and others (24,186) have also shown that elevated plasma FFA levels inhibit insulin secretion.

          Many years ago, Professor Philip Randle (195) described his now famous cycle of substrate competition, whereby elevated FFA oxidation in muscle reciprocally impaired glucose oxidation. Although there clearly is substrate competition between FFA and glucose with respect to oxidative metabolism (196,197), FFAs have been shown to have independent effects to inhibit glycogen synthase (198,199) and both glucose transport and glucose phosphorylation (192,200).

          More recently, we have examined the effect of a 4-h lipid versus saline infusion on the insulin signal transduction system in healthy lean normal glucose tolerant subjects (201). Lipid was infused at three rates (30, 60, and 90 ml/h) to cause a physiological and pharmacological elevation in the plasma FFA concentration. During the saline control study, insulin increased whole-body glucose metabolism from 2.7 to 10.8 mg · kg−1 · min−1. Lipid infusion caused a dose-response decline in insulin-stimulated whole-body glucose disposal (by 22, 30, and 34%, respectively), which primarily reflects muscle. Compared with the saline control study, lipid infusion caused a dose-response inhibition of muscle insulin receptor tyrosine phosphorylation, IRS-1 tyrosine phosphorylation, PI 3-kinase activity, and Akt serine phosphorylation (Fig. 11).

          FIG. 11.
          FIG. 11.

          Effect of lipid infusion to cause a physiological-pharmacological elevation in plasma FFA concentration on insulin signal transduction in healthy nondiabetic subjects (201). PY, phosphorylation.

          After fatty acids enter the cell, they can be converted to triglycerides, which are inert, or to toxic lipid metabolites such as fatty acyl CoAs, diacylglycerol, and ceramide. Using magnetic resonance spectroscopy, we quantitated intramyocellular triglyceride content in healthy normal glucose tolerant and type 2 diabetic subjects and demonstrated that muscle lipid content was significantly increased in the diabetic group (R.A.D., unpublished data). Similar results have been reported by Petersen et al. (202). Fatty acyl CoAs, which are known to inhibit insulin signaling (203,204), were also significantly increased in muscle in diabetic subjects (205,206). Diabetic subjects were treated with pioglitazone, which increases the expression of peroxisome proliferator–activated γ coactivator 1 (PGC-1) (207). PGC-1 is the master regulator of mitochondrial biogenesis and augments the expression of multiple genes involved in mitochondrial oxidative phosphorylation (208210). Pioglitazone reduced the intramyocellular lipid and fatty acyl CoA concentrations, and the decrement in muscle fatty acyl CoA content was closely related to the improvement in insulin-stimulated muscle glucose disposal (205). When we reduced the intramyocellular fatty acyl CoA content with acipimox, a potent inhibitor of lipolysis, a similar improvement in insulin-mediated glucose disposal was noted (206). Increased intramyocellular levels of diacylglycerol (194,211) and ceramides (212,213) have also been demonstrated in type 2 diabetic and obese nondiabetic subjects and shown to be related to the insulin resistance and impaired insulin signaling in muscle. Most recently, we demonstrated that a 48-h lipid infusion, designed to increase the plasma FFA concentration ∼1.5- to 2.0-fold, inhibited the expression of PGC1α, PGC1β, PDHA1, and multiple mitochondrial genes involved in oxidative phosphorylation in muscle (214), thus mimicking the pattern of gene expression observed in type 2 diabetic subjects and in the normal glucose tolerant, insulin-resistant offspring of two type 2 diabetic parents (215,216). Most recently, we examined the effect of palmitoyl carnitine on ATP synthesis in mitochondria isolated from muscle of normal glucose tolerant subjects (217). Low concentrations of palmitoyl carnitine (1–4 μmol/l) augmented ATP synthesis. However, palmitoyl carnitine concentrations >4 μmol/l were associated with marked inhibition of ATP synthesis and a decrease in the inner mitochondrial membrane potential, which provides the electromotive driving force for electron transport. Collectively, these findings provide strong support for lipotoxicity and adipocyte insulin resistance in the pathogenesis of type 2 diabetes.

          QUINTESSENTIAL QUINTET

          Although the fat cell is a worthy member of the dysharmonious quartet, the time has arrived to expand the playing field to include the gastrointestinal tissues as the fifth member of the quintessential quintet.

          Glucose ingestion elicits a much greater insulin response than an intravenous glucose infusion that mimics the plasma glucose concentration profile observed with oral glucose (98100). The great majority (>99%) of this incretin effect can be explained by two hormones: GLP-1 and GIP (98100). As discussed earlier, GLP-1 secretion by the L-cells of the distal small intestine is deficient (98100), while GIP secretion by the K-cells of the more proximal small intestine is increased, but there is resistance to the stimulatory effect of GIP on insulin secretion (102105). GLP-1 also is a potent inhibitor of glucagon secretion (98100), and the deficient GLP-1 response contributes to the paradoxical rise in plasma glucagon secretion and impaired suppression of HGP that occurs after ingestion of a mixed meal (218). Clearly, the gut is a major endocrine organ and contributes to the pathogenesis of type 2 diabetes.

          Studies from our laboratory have demonstrated that in healthy normal glucose tolerant subjects, approximately one-half of the suppression of HGP following a mixed meal is secondary to inhibition of glucagon secretion, the other one-half is secondary to the increase in insulin secretion, and the insulin-to-glucagon ratio correlated strongly with the suppression of HGP during the meal (218). These studies also demonstrated that a large amount of the ingested glucose load did not appear in the systemic circulation, consistent with previous studies from our laboratory (28,170172). This could have been the result of delayed gastric emptying, a known effect of exenatide, or an increase in splanchnic (primarily reflects liver) glucose uptake. To examine this question more directly, type 2 diabetic subjects received a 6-h meal tolerance test with the double tracer technique (1-14C-glucose orally and 3-3H-glucose intravenously) before and after 2 weeks of exenatide treatment (219). Exenatide was not given on the day of the study. The ingested glucose load was labeled with acetaminophen to follow gastric empting. Exenatide significantly reduced both the fasting and postprandial plasma glucose levels following ingestion of the meal compared with the baseline study performed prior to exenatide. The increment in insulin secretory rate divided by the increment in plasma glucose concentration increased more than twofold, demonstrating a potent stimulatory effect of exenatide on β-cell function. The increase in insulin secretion, in concert with a decline in glucagon release, led to a significant reduction in HGP following ingestion of the mixed meal. Gastric emptying was unaltered by exenatide, since the last dose of exenatide was administered more than ∼16 h prior to the meal. Neither splanchnic nor peripheral tissue glucose uptake was significantly altered. Thus, the primary effect of exenatide to improve glucose tolerance is related to the incretin’s suppressive effect on HGP. Most recently, Cherrington (220) and Bergman (221) and colleagues have presented evidence in support of an effect of GLP-1 to enhance hepatic glucose uptake of ingested glucose in dogs.

          SETACEOUS SEXTET

          The sixth member, who establishes the setaceous sextet, is the pancreatic α-cell. Many groups, dating back to the 1970s, have demonstrated that the basal plasma glucagon concentration is elevated in type 2 diabetic individuals (119121,222224). The important contribution of elevated fasting plasma glucagon levels to the increased basal rate of HGP in type 2 diabetic individuals was provided by Baron et al. (122). Compared with control subjects, diabetic individuals had a markedly elevated rate of basal HGP, which correlated closely with the increase in fasting plasma glucagon concentration. Following somatostatin infusion, plasma glucagon levels declined by 44% in association with a 58% decrease in basal HGP. These results conclusively demonstrate the pivotal role of hyperglucagonemia in the pathogenesis of fasting hyperglycemia in type 2 diabetes. There also is evidence that the liver may be hypersensitive to the stimulatory effect of glucagon in hepatic gluconeogenesis (120).

          In summary, drugs that inhibit glucagon secretion or block the glucagon receptor are likely to be effective in treating patients with type 2 diabetes. One such example is exenatide (225), but glucagon receptor antagonists also have been shown to be effective (226).

          SEPTICIDAL SEPTET

          The next, and most recent member, implicated in the pathogenesis of type 2 diabetes is the kidney who along with the muscle, liver, α-cell, β-cell, adipocyte, and gut, forms the septicidal septet.

          The kidney filters ∼162 g ([glomerular filtration rate = 180 l/day] × [fasting plasma glucose = 900 mg/l]) of glucose every day. Ninty percent of the filtered glucose is reabsorbed by the high capacity SGLT2 transporter in the convoluted segment of the proximal tubule, and the remaining 10% of the filtered glucose is reabsorbed by the SGLT1 transporter in the straight segment of the descending proximal tubule (227). The result is that no glucose appears in the urine.

          In animal models of both type 1 and type 2 diabetes, the maximal renal tubular reabsorptive capacity, or Tm, for glucose is increased (228230). In humans with type 1 diabetes, Mogensen et al. (231) have shown that the Tm for glucose is increased. In human type 2 diabetes, the Tm for glucose has not been systematically examined. No studies in either type 1 or type 2 diabetic individuals have examined the splay in the glucose titration curve in humans. However, cultured human proximal renal tubular cells from type 2 diabetic patients demonstrate markedly increased levels of SGLT2 mRNA and protein and a fourfold increase in the uptake of α-methyl-d-glucopyranoside (AMG), a nonmetabolizeable glucose analog (232) (Fig. 12).

          FIG. 12.
          FIG. 12.

          SGLT 2 transporter mRNA (left) and protein (middle) and glucose transport (α-methyl-d-glucopyranoside) (right) are increased in cultured renal proximal tubular epithelial cells of individuals with type 2 diabetes (T2DM) versus nondiabetic subjects (CON) (232).

          These observations have important clinical implications. Thus, an adaptive response by the kidney to conserve glucose, which is essential to meet the energy demands of the body, especially the brain and other neural tissues, which have an obligate need for glucose, becomes maladaptive in the diabetic patient. Instead of dumping glucose in the urine to correct the hyperglycemia, the kidney chooses to hold on to the glucose. Even worse, the ability of the diabetic kidney to reabsorb glucose appears to be augmented by an absolute increase in the renal reabsorptive capacity for glucose.

          In summary, the development of medications that inhibit renal proximal tubular glucose reabsorption provides a rational approach to the treatment of type 2 diabetes (227).

          OMINOUS OCTET (FIG. 13)

          The last, and perhaps most important, player to be implicated in the pathogenesis of type 2 diabetes is the brain, which, along with his seven companions, forms the ominous octet. It is abundantly clear that the current epidemic of diabetes is being driven by the epidemic of obesity (207,233). Porte and colleagues (234237) were among the first to demonstrate that, in rodents, insulin was a powerful appetite suppressant. Obese individuals, both diabetic and nondiabetic, are characterized by insulin resistance and compensatory hyperinsulinemia. Nonetheless, food intake is increased in obese subjects despite the presence of hyperinsulinemia, and one could postulate that the insulin resistance in peripheral tissues also extends to the brain.

          FIG. 13.
          FIG. 13.

          The ominous octet. See text for a more detailed explanation.

          Our laboratory has attempted to address the issue of impaired appetite regulation by insulin in obese subjects using functional magnetic resonance imaging (MRI) to examine the cerebral response to an ingested glucose load (238). After glucose ingestion, two hypothalamic areas with consistent inhibition were noted: the lower posterior hypothalamus, which contains the ventromedial nuclei, and the upper posterior hypothalamus, which contains the paraventricular nuclei. In both of these hypothalamic areas, which are key centers for appetite regulation, the magnitude of the inhibitory response following glucose ingestion was reduced in obese, insulin-resistant, normal glucose tolerant subjects, and there was a delay in the time taken to reach the maximum inhibitory response, even though the plasma insulin response was markedly increased in the obese group. Whether the impaired functional MRI response in obese subjects contributes to or is a consequence of the insulin resistance and weight gain remains to be determined. Nonetheless, these results suggest that the brain, like other organs (liver, muscle, and fat) in the body, may be resistant to insulin. Studies by Obici et al. (239,240) in rodents have also provided evidence for cerebral insulin resistance leading to increased HGP and reduced muscle glucose uptake.

          IMPLICATIONS FOR THERAPY

          The preceding review of the pathophysiology of type 2 diabetes has important therapeutic implications (Table 1). First, effective treatment of type 2 diabetes will require multiple drugs used in combination to correct the multiple pathophysiological defects. Second, the treatment should be based upon known pathogenic abnormalities and NOT simply on the reduction in A1C. Third, therapy must be started early in the natural history of type 2 diabetes, if progressive β-cell failure is to be prevented.

          TABLE 1

          Pathogenesis of type 2 diabetes: implications for therapy

          Let us now examine the current therapeutic options as they relate to four of the key pathophysiological derangements present in type 2 diabetes (Fig. 14). At the level of the liver, we have shown that both metformin (241243) and the TZDs (175,244252) are potent insulin sensitizers and inhibit the increased rate of hepatic gluconeogenesis (220,221) that is characteristic of type 2 diabetic patients. In muscle, TZDs are potent insulin sensitizers (244252), whereas metformin is a very weak insulin sensitizer (241,243,253). Since the TZDs work through the classic insulin signaling pathway (150,254), whereas metformin works through the AMP kinase pathway (255,256), combination therapy with a TZD plus metformin gives a completely additive effect to reduce the A1C (257265), and hypoglycemia is not encountered because these drugs are insulin sensitizers and do not augment insulin secretion. In adipose tissue, the TZDs are also excellent insulin sensitizers and are potent inhibitors of lipolysis (263). TZDs also effectively mobilize fat out of muscle, liver, and β-cell, thereby ameliorating lipotoxicity (175,176,205,264267).

          FIG. 14.
          FIG. 14.

          Treatment of type 2 diabetes: a therapeutic approach based upon pathophysiology. See text for a more detailed explanation.

          At the level of the β-cell, only the TZDs conclusively have been shown to improve and preserve β-cell function (75,268) and demonstrate durability of control (167,168,260, 268272). There is also evidence that the GLP-1 analogs can preserve β-cell function on a long-term basis (273275). Nonetheless, the two most commonly prescribed drugs in the U.S. and throughout the world are the sulfonylureas and metformin, and neither of these drugs exerts any significant protective effect on the β-cell. This is a major concern, since progressive β-cell failure is the primary pathogenic abnormality responsible for the development of overt diabetes and the progressive rise in A1C (Fig. 2 and supplemental Fig. A1).

          Sulfonylureas and metformin.

          Professor Robert Turner, in the UK Prospective Diabetes Study (UKPDS), was the first to conclusively show that sulfonylureas had no protective effect on the β-cell in newly diagnosed type 2 diabetic patients over the 15-year study duration (36). After an initial drop in the A1C, sulfonylurea-treated patients experienced a progressive deterioration in glycemic control that paralleled the rise in A1C in the conventionally treated group (Fig. 15). Moreover, in the UKPDS sulfonylureas were shown not to have a significant protective effect against atherosclerotic cardiovascular complications (34), and some studies even have suggested that sulfonylureas may accelerate the atherogenic process (276,277). Similarly, metformin-treated patients in the UKPDS, after an initial decline in A1C, secondary to the biguanide’s inhibitory effect on HGP, also experienced a progressive deterioration in glycemic control (Fig. 15) (278). Using HOMA-β, Professors Holman and Turner showed that the relentless rise in A1C observed with both sulfonylureas and metformin resulted from a progressive decline in β-cell function and that by 3 years ∼50% of diabetic patients required an additional pharmacological agent to maintain the A1C <7.0% (279284). Although there is some in vitro evidence that metformin may improve β-cell function and prevent β-cell apoptosis (285,286), the in vivo data from the UKPDS fail to support any role for metformin in the preservation of β-cell function. However, metformin was shown to reduce macrovascular events in UKPDS (278), although by today’s standards the number of diabetic subjects in the metformin arm (n = 342) would be considered inadequate to justify any conclusions about cardiovascular protection.

          FIG. 15.
          FIG. 15.

          The effect of sulfonylurea (glibenclamide = glyburide) and metformin therapy on the plasma A1C concentration in newly diagnosed type 2 diabetic subjects. Conventionally treated diabetic subjects received diet plus exercise therapy (36,279).

          It is especially noteworthy that UKPDS was originally designed as a monotherapy study. However, after 3 years it became evident that neither monotherapy with metformin nor sulfonylureas was capable of preventing progressive β-cell failure and stabilizing the A1C at its starting level (279283). Therefore, the investigators altered the study protocol to allow metformin to be added to the sulfonylurea arm, sulfonylureas to be added to the metformin arm, and/or insulin to be added to the sulfonylurea arm (279283). Although the addition of a second oral antidiabetic agent improved glycemic control, after the initial decline in A1C progressive β-cell failure continued and the A1C rose progressively.

          ADOPT (A Diabetes Outcome Progression Trial) (268) has provided results similar to those obtained in the UKPDS. In newly diagnosed type 2 diabetic patients treated with glyburide, after an initial decline, the A1C rose continuously due to the progressive loss of β-cell function (Fig. 16). In contrast, rosiglitazone caused an initial reduction in A1C that was largely sustained over the 5-year study duration because of a durable effect to preserve β-cell function (Fig. 17). The rate of decline in β-cell function was 3.5-fold greater in glyburide-treated patients versus rosiglitazone-treated patients. Although metformin produced a more sustained effect to lower the A1C than the sulfonylureas in ADOPT, it also was associated with a progressive rise in A1C and progressive decline in β-cell function after the first year (268).

          FIG. 16.
          FIG. 16.

          Summary of studies examining the effect of sulfonylurea (SU) treatment versus placebo or versus active-comparator on A1C in type 2 diabetic subjects (36,166,167,260,269273,279285). See text for a more detailed discussion. GLY, glyburide.

          A number of long-term (>1.5 years), active-comparator, or placebo-controlled studies have examined the ability of sulfonylureas to produce a durable reduction in A1C in type 2 diabetic patients. All of these studies (36,166,167, 260,268272) showed that, after an initial decline in A1C, a variety of sulfonylureas, including glyburide, glimepiride, and gliclazide, were associated with a progressive decline in β-cell function with an accompanying loss of glycemic control (Fig. 16). There are no exceptions to this consistent loss of glycemic control with the sulfonylureas after the initial 18 months of therapy. Thus, evidence-based medicine conclusively demonstrates that the glucose-lowering effect of the sulfonylureas is not durable and that the loss of glycemic control is associated with progressive β-cell failure (36,37,166,167,268272,279283).

          TZDs.

          In contrast to the sulfonylureas, eight long-term (>1.5 years) active-comparator or double-blind placebo-controlled studies with the TZDs present a very different picture (Fig. 17) (167,168,268272). Thus, after an initial decline in A1C, durability of glycemic control is maintained because of the preservation of β-cell function in type 2 diabetic patients. In addition to these studies performed in type 2 diabetic patients, there are five studies in subjects with IGT demonstrating that TZDs prevent the progression of IGT to type 2 diabetes (286290). The DREAM (Diabetes Reduction Assessment with Ramipril and Rosiglitazone Medication) study showed a 62% decrease in the development of type 2 diabetes with rosiglitazone (287), while the ACT NOW (Actos Now for Prevention of Diabetes) study (290) showed a 81% reduction in the conversion of IGT to type 2 diabetes with pioglitazone. All five of these studies showed that, in addition to their insulin sensitizing effect, the TZDs had a major action to preserve β-cell function. In ACT NOW, the improvement in the insulin secretion/insulin resistance (disposition) index (measure of β-cell function) was shown both with the OGTT and the frequently sampled intravenous glucose tolerance test. Similar results have been demonstrated in the TRIPOD (Troglitazone In Prevention Of Diabetes) and PIPOD (Pioglitazone In Prevention Of Diabetes) studies (286,289) in which the development of diabetes in Hispanic women with a history of gestational diabetes was decreased by 52 and 62%, respectively. Many in vivo and in vitro studies with human and rodent islets have shown that TZDs exert a protective effect on β-cell function (291295).

          FIG. 17.
          FIG. 17.

          Summary of studies examining the effect of TZDs versus placebo or versus active-comparator on A1C in type 2 diabetic subjects (167,168,260,268273). See text for a more detailed discussion. PIO, pioglitazone; ROSI, rosiglitazone.

          GLP-1 analogs.

          Incretins also have been shown to improve β-cell function and maintain durability of glycemic control. Bunck et al. (273) studied 69 metformin-treated type 2 diabetic patients with a mean age of 58 years and BMI of 30.5 kg/m2. Subjects received glargine insulin or exenatide to similarly reduce the A1C to 6.8%. Before and after 1 year, C-peptide secretion was evaluated with an 80-min hyperglycemic clamp. During the repeat hyperglycemic clamp performed after 1 year, both the first (0–10 min) and second (10–80 min) phases of insulin secretion were increased 1.5- and 2.9-fold, respectively, in the group treated with exenatide versus the group treated with glargine. Glargine increased by 31% the ratio of the C-peptide response during the hyperglycemic clamp performed after 1 year compared with the hyperglycemic clamp performed at baseline. In contrast, exenatide increased the ratio more than threefold, demonstrating a potent effect of this GLP-1 analog to augment β-cell function.

          In a 32-week double-blind, placebo-controlled study, exenatide (10 μg b.i.d.) reduced A1C by ∼1.0–1.2% and markedly decreased the postprandial rise in plasma glucose concentration while maintaining the plasma insulin response at pre-exenatide treatment levels (274). Consequently, the ΔI/ΔG ratio increased dramatically, indicating a robust effect on β-cell function. A subset of these subjects were followed-up for 3.5 years, and the decline in A1C was shown to persist (275). However, it is not known whether the subjects who did not continue in this long-term extension study had the same characteristics, i.e., level of glycemic control, etc., as those who continued to be followed for 3.5 years. In vivo studies in rodents (296,297) and in vitro studies with cultured human islets (298) have shown that exenatide can expand β-cell mass and prevent apoptosis of islets, respectively. Whether these effects to augment β-cell mass will be observed in diabetic humans remains to be determined. Irrespective of changes in β-cell mass, the studies of Bunck et al. (273) clearly document a major effect of exenatide to augment β-cell function.

          In addition to their effect on the β-cell, exenatide and other GLP-1 beneficially impact four other members of the ominous octet: liver (reduced HGP), α-cell (reduced glucagon secretion), gut (replacement of deficient GLP-1 response), and brain (reduced appetite with weight loss). Importantly, the stimulatory effect of exenatide on insulin secretion dissipates when normoglycemia is achieved, thereby minimizing the adverse effect of hypoglycemia.

          Dipeptidyl peptidase-IV inhibitors.

          There are no long-term studies examining the effect of the dipeptidyl peptidase-IV (DPP-IV) inhibitors on β-cell function. However, in short-term studies, from several months to 1 year, both sitagliptin and vildagliptin (98,99,299,300) reduce the postprandial plasma glucose concentration while maintaining the plasma insulin response, indicating a positive effect on β-cell function. Whether this enhancement in insulin secretion will be translated into preservation of β-cell function on a long-term basis remains to be determined. The DPP-IV inhibitors also decrease glucagon secretion, and in concert with the rise in plasma insulin, this leads to a reduction in basal HGP (301). Hypoglycemia does not occur with the DPP-IV inhibitors, but they do not suppress appetite or cause weight loss.

          Summary.

          The introduction of the TZDs and GLP-1 analogs into the diabetes market place and their potential to preserve β-cell function offer a new therapeutic approach to the treatment of type 2 diabetes.

          ADA ALGORITHM FOR TREATMENT OF TYPE 2 DIABETES

          The ADA algorithm for the treatment of type 2 diabetes advocates a stepwise therapeutic approach that is based upon reduction in the plasma glucose concentration and NOT upon known pathophysiological disturbances (49). It dictates the initiation of therapy with lifestyle modification plus metformin to achieve an A1C < 7.0% (Fig. 18). If the goal is not reached or if secondary failure occurs, the ADA algorithm suggests one of three options: 1) First is the addition of basal insulin, an option unlikely to be chosen by primary care physicians or most endocrinologists in the U.S. and unlikely to achieve the desired level of glycemic control based upon well-designed studies by experts in the field of insulin therapy (302308). Moreover, all of these insulin-based add-on studies have been associated with a high incidence of hypoglycemia and major weight gain (range 4.2–19.2 lbs, mean 8.5 lbs within 6–12 months or less) (Fig. 19). 2) Second is the addition of a TZD, but this option is unlikely to be chosen because of the concerns raised in the ADA algorithm about this class of drugs. Thus, the ADA algorithm basically guides the physician to select a sulfonylurea as the choice for a second antidiabetic agent. Moreover, third party reimbursers like this option because sulfonylureas are inexpensive. Neither the GLP-1 analogs nor the DPP-4 inhibitors are included as an option in the ADA algorithm (49). Since neither the sulfonylureas nor metformin exerts any effect to preserve β-cell function (see previous discussion and Fig. 16), the 20% of β-cell function that was present at the time of diagnosis of diabetes (4042) will largely have been lost by the time that combined sulfonylurea/metformin therapy has failed, and the majority of these patients will require insulin treatment. Insulin therapy is difficult for most primary care physicians, and even in the hands of experienced endocrinologists it is not easy to achieve and maintain an A1C <7%—let alone <6.5%—without significant hypoglycemia and weight gain (302308). Moreover, it is unclear why one would initiate insulin before exenatide, since insulin rarely decreases the A1C to <7.0% and is associated with significant weight gain and hypoglycemia (302308) (Fig. 19). Most recently, an ADA Consensus Statement has significantly revised the ADA therapeutic algorithm (309). A two-tier approach is advocated, and sulfonylureas have been elevated into the first tier and are to be used if diet/exercise plus metformin fail to reduce the A1C to <7.0% (Fig. 20). From the pathophysiological standpoint, this represents a major step backward, since an overwhelming body of evidence-based medicine (Fig. 16) conclusively demonstrates that sulfonylureas do not preserve β-cell function and do not achieve durability of glycemic control. Although this algorithm is not the official policy statement of ADA, it is likely to be interpreted as such by most third-party payers.

          FIG. 18.
          FIG. 18.

          ADA algorithm for the treatment of type 2 diabetes (49). See text for a more detailed explanation. SU, sulfonylurea.

          FIG. 19.
          FIG. 19.

          Effect of insulin (Ins) and exenatide on A1C and body weight in type 2 diabetic subjects (302308).

          FIG. 20.
          FIG. 20.

          ADA consensus statement algorithm on the treatment of type 2 diabetes. As indicated, this does not represent the official statement of ADA (49). See text for a detailed discussion (309). Exen, exenatide; PIO, pioglitazone; SU, sulfonylurea.

          PATHOPHYSIOLOGICAL-BASED ALGORITHM

          An alternate therapeutic algorithm is based upon known pathophysiological disturbances in type 2 diabetes (Fig. 21). This algorithm provides a more rational approach and is more likely to produce a durable long-term effect. This algorithm initiates treatment with lifestyle modification plus triple combination therapy with drugs known to improve insulin sensitivity (TZDs and metformin) and, most importantly, with drugs that have been shown to preserve β-cell function (TZDs and exenatide) (Fig. 21). Further, a more rational goal of therapy should be an A1C <6.0%, since the DPP has taught us that as many as 12% of individuals with IGT and an A1C of 6.0% already have background diabetic retinopathy.

          FIG. 21.
          FIG. 21.

          Pathophysiological-based algorithm: treatment of type 2 diabetes based upon pathophysiology. See text for a detailed discussion.

          Comparison of the stepwise ADA algorithm with the combination pathophysiological-based algorithm is shown in Fig. 22. Many studies, including the UKPDS, have shown that stepped metformin/sulfonylurea therapy does not achieve durable glycemic control. Conversely, the TZDs and the GLP-1 analogs, when used as monotherapy, each have been shown to have a more durable effect. When used in combination, if anything, one would hypothesize an even more durable effect on β-cell function and reduction in A1C, although this remains to be proven. Neither the sulfonylureas nor metformin has been shown to preserve β-cell function. In contrast, both the TZDs and exenatide have been shown to preserve β-cell function. Hypoglycemia is common with the sulfonylureas and insulin, and this prohibits the achievement of the optimal A1C goal of 6.0%, let alone an A1C <7.0% (the ADA-recommended goal). In contrast, hypoglycemia is uncommon with the insulin sensitizers and GLP-1 analogs, allowing the physician to titrate these drugs to maximum doses to reduce the A1C <6.0%. Lastly, weight gain is common with sulfonylurea and insulin therapy, whereas weight loss is the norm with exenatide, and exenatide blocks the weight gain that is associated with the TZDs.

          FIG. 22.
          FIG. 22.

          Comparison of the ADA and pathophysiological-based algorithms. See text for a detailed discussion.

          Summary: Treatment.

          Although this paradigm shift, which is based upon pathophysiology, represents a novel approach to the treatment of type 2 diabetes, it is substantiated by a vast body of basic scientific and clinical investigational studies. Because this algorithm is based upon the reversal of known pathophysiological defects, it has a high probability of achieving durable glycemic control. If the plasma glucose concentration can be maintained within the normal nondiabetic range, the microvascular complications of the disease, which are costly to treat and associated with major morbidity and mortality, can be prevented. Most importantly, this will enhance the quality of life for all diabetic patients.

          Acknowledgments

          No potential conflicts of interest relevant to this article were reported.

          Footnotes

          • Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.



          Sell Unused Diabetic Strips Today!

          Goat Cheese Pasta with Meatballs

          By electricdiet / July 21, 2021


          Am I the only one that can never cook the right amount of pasta without having five cups leftover?  That’s how this goat cheese pasta with meatballs came about.

          I am the leftover queen!  A quick search in my fridge and I found an unopened goat cheese.  Then I pulled out the leftover pasta, some flour, and almond milk.

          One way I save on groceries each week is only buying exactly what I need that week.  So I purchased one single Italian sausage link at Mariano’s for $1.26 and only used half of it.  The rest will go on pizza later this week.

          this is a photo of Italian sausage in the meat case at Marianos

          This is a photo of ingredients used to make goat cheese pasta with meatballs

          Ingredients

          • 1 cup cooked pasta (I used leftover pasta)
          • 1 tablespoon I Can’t Believe It’s Not Butter
          • 2 cloves garlic, sliced thin
          • 1 tablespoon flour
          • 1/2 cup unsweetened almond milk
          • 1 teaspoon dried parsley
          • 1 ounce goat cheese
          • 2 ounces of Italian sausage, removed from casing

          Instructions

          1. Heat skillet with avocado oil spray. Form tiny meatballs with the Italian sausage, about the size of marbles, and cook for 3-4 minutes. Set aside.
          2. In the same pan, melt the butter. Add the garlic and cook for one minute. Add the flour and cook for one minute. Add in the almond milk and cook for 3-4 minutes, until the sauce thickens, then add in the goat cheese, parsley, salt and pepper. Cook for one minute, coating the pasta, then add back in the meatballs and cook for one more minute.
          3. Garnish with fresh parsley if you are feeling fancy.

          Nutrition Information:

          Yield: 1

          Serving Size: 1

          Amount Per Serving:

          Calories: 567Total Fat: 31gSaturated Fat: 11gTrans Fat: 1gUnsaturated Fat: 20gCholesterol: 46mgSodium: 647mgCarbohydrates: 47gFiber: 3gSugar: 2gProtein: 25g


          Did you make this recipe?

          Please leave a comment on the blog or share a photo on Instagram

          This goat cheese pasta with meatballs tastes like it should be 2000 calories.  It’s creamy, rich and I love how every strand of pasta is coated in the goat cheese sauce.

          this is a photo of goat cheese pasta with meatballs

          What is a good substitute cheese if I don’t like goat cheese?

          You would want a good melty cheese, like white cheddar, gruyere or swiss cheese.  Cream cheese could even be substituted in a pinch!

          Let me know if you make this – totally worth the points and calories to me!

          Biz

          I am a widowed 52 year old trying to figure out my life after losing my husband after a long illness.

          Cooking and being in the kitchen feeds my soul!





          Sell Unused Diabetic Strips Today!

          Page 3 of 33
          >