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.



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    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!





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    Chicken Crust Pizza (Keto & Gluten-Free)

    By electricdiet / July 19, 2021


    Ditch the high-carb pizza crust and indulge in this protein-packed, gluten-free, keto chicken crust pizza instead! It’s so easy — just mix, bake, add your favorite toppings, and enjoy.

    Closeup of pizza on a wooden cutting board with one slice cut out

    From cauliflower crusts to fathead dough to pizza casseroles, there are plenty of ways to enjoy pizza on a low-carb or keto diet. But I think I may have found my new favorite: keto chicken crust pizza!

    As the name suggests, the bulk of this crust is actually made from shredded chicken. It’s extremely low in carbs, gluten-free, and packed with protein. Win-win-win! Best of all, it couldn’t be easier to make.

    How to make keto chicken crust pizza

    This quick recipe comes together in just a few simple steps. Your pizza will be ready in less than 45 minutes!

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

    Step 1: Preheat the oven to 375°F. Line a baking sheet with parchment paper.

    Step 2: In a large bowl, combine 1 cup of mozzarella with the chicken, cream cheese, parmesan, egg, oregano, garlic powder, onion, and salt.

    Crust ingredients in a large glass bowl, about to be mixed

    Step 3: Use your hands to mix until well-incorporated.

    Crust batter in a large glass bowl, as seen from above

    Step 4: Press the mixture down onto the prepared baking sheet as uniformly as possible, about ¼ inch thick.

    Crust dough flattened onto a baking sheet lined with parchment paper, as seen from above

    Step 5: Bake the crust for 20 minutes or until just starting to brown.

    Baked crust on a baking sheet lined with parchment paper, as seen from above

    Step 6: Top with sauce and the remaining mozzarella cheese.

    Baked crust topped with sauce and mozzarella, ready to go back in the oven

    Step 7: Bake for 10 more minutes until the cheese is melted, then top with fresh basil after the bake.

    Finished pizza topped with fresh basil, sitting on a baking sheet lined with parchment paper, ready to be cut into slices

    Want your cheese extra bubbly? Turn your oven to broil for the last 1-2 minutes of the bake. Then, slice your pizza into 6 pieces and enjoy!

    Full pizza on a baking sheet lined with parchment paper, ready to be sliced

    Additional toppings for your pizza

    Want to add a few more of your favorite toppings? That’s the beauty of pizza — you can make it totally your own!

    I love adding low-carb veggies like mushrooms, spinach, or olives. For even more protein, throw on some pepperoni, bacon, or even cooked sausage.

    One thing to keep in mind is that the crust definitely has a mild chicken taste. After all, it’s just chicken, cheese, and an egg. That’s why I like to choose toppings that go well with chicken… which, thankfully, is most toppings out there!

    For example, if you love barbeque chicken pizza, try drizzling keto-friendly BBQ sauce over your slices. Or maybe you want to add a little keto ranch with some bacon.

    You could also replace the tomato sauce with a white sauce, pesto spread, or even olive oil. Top with arugula and roasted garlic for a delicious combination.

    There are truly endless ways you could make your pizza. Just be sure to choose low-carb toppings to keep your pizza keto-friendly!

    Three slices of Keto Chicken Crust Pizza on separate white plates

    Is tomato sauce okay for keto?

    Tomatoes have a decent amount of carbs, so they’re best enjoyed in moderation on a keto diet. But what about tomato sauce?

    The trick is to find a sauce with little or no sugar added. Be sure to read your labels if you’re buying sauce at the grocery store, or you could always make your own keto tomato sauce right at home.

    Once you have a low-sugar sauce picked out, just be sure to pay attention to your portion size. That’s all it takes to enjoy tomato sauce on a keto diet!

    Storage

    Have leftover pizza? Lucky you! Any extra slices can be stored in an airtight container in the refrigerator for 2-3 days. To reheat, bake at 350°F for about 5-10 minutes or until heated through.

    You can also store your slices in an airtight container in the freezer for up to 3 months. When you’re ready to eat, bake the frozen slices at 350°F for 10-15 minutes until nice and hot.

    Closeup of pizza on a wooden cutting board with one slice cut out

    Other tasty keto-friendly recipes

    Following a low-carb way of eating doesn’t mean you have to give up your favorite comfort foods! With a few simple ingredient swaps, many recipes can be adapted to be keto-friendly. If you’re looking for some inspiration, here are a few of my favorite options:

    Craving a sweet treat to round out your delicious meal? Check out this roundup of my favorite keto-friendly dessert recipes for some yummy options!

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

    Recipe Card

    Keto Chicken Crust Pizza

    Ditch the high-carb pizza crust and indulge in this protein-packed, gluten-free, keto chicken crust pizza instead! It’s so easy — just mix, bake, add your favorite toppings, and enjoy.

    Prep Time:10 minutes

    Cook Time:30 minutes

    Total Time:40 minutes

    Servings:2

    A slice of keto chicken crust pizza on a white plate next to basil leaves

    Instructions

    • Preheat the oven to 375°F. Line a baking sheet with parchment paper.

    • In a large bowl, combine 1 cup of mozzarella with the chicken, cream cheese, parmesan, egg, oregano, garlic powder, onion, and salt.

    • Use your hands to mix until well-incorporated.

    • Press the mixture down onto the prepared baking sheet as uniformly as possible, about ¼ inch thick.

    • Bake the crust for 20 minutes or until just starting to brown.

    • Top with sauce and the remaining mozzarella cheese.

    • Bake for 10 more minutes until the cheese is melted, then top with fresh basil after the bake.

    • (optional) Broil for 1-2 minutes until the cheese is bubbly and golden.

    Recipe Notes

    This recipe is for 2 servings. If you cut the pizza into 6 slices, each serving will be 3 slices.
    Leftovers can be stored in an airtight container in the refrigerator for 2-3 days. To reheat, bake at 350°F for 5-10 minutes until heated through.
    Pizza can also be stored in the freezer for up to 3 months. To reheat, bake frozen slices at 350°F for 10-15 minutes until hot.

    Nutrition Info Per Serving

    Nutrition Facts

    Keto Chicken Crust Pizza

    Amount Per Serving (3 slices)

    Calories 784
    Calories from Fat 434

    % Daily Value*

    Fat 48.2g74%

    Saturated Fat 26.5g133%

    Trans Fat 0.1g

    Polyunsaturated Fat 1.8g

    Monounsaturated Fat 7.2g

    Cholesterol 349mg116%

    Sodium 1319.7mg55%

    Potassium 746.4mg21%

    Carbohydrates 14.9g5%

    Fiber 1.6g6%

    Sugar 4.8g5%

    Protein 71.3g143%

    Net carbs 13.3g

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

    Course: Main Course

    Cuisine: American

    Diet: Diabetic, Gluten Free

    Keyword: chicken crust, gluten-free, keto pizza crust, low-carb pizza



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    One Grocery Shopping List: 3 Delicious Diabetic Meals

    By electricdiet / July 17, 2021


    Delicious Diabetic Meals for the Whole Family

    If you or someone you love has been diagnosed with diabetes, you may feel as though you have to give up your favorite dishes all together. Not so! There’s no need to completely change your menu, just how you prepare it. With a healthy meal plan and a few simple adjustments to the menu, anyone, even those with diabetes, can enjoy a delicious and fun party. With over 10% of the American population having diabetes, it is important to understand that there is no magical diabetes diet. Portion control, moderate sugar, and healthy fat choices are not just guidelines for diabetics to keep in mind, but for everyone’s health, as it really is the healthiest way to eat!

    3 Diabetic Dinners Grocery Shopping List

    3 Diabetic Dinners Shopping List 2

    Get the printable shopping list here!

    Protein Rich Full Flavor Hacienda Chicken

    Easy and effortless, Hacienda Chicken with a smoky cumin seasoning in a simple salsa sauce makes a quick full-flavored nightly dinner. Serve over brown rice to add blood sugar stabilizing whole grain fiber to your meal.

    Beef Stew in Slow Cooker

    Crock Pot Beef Stew & Veggies Basically Cooks Itself

    Diabetic and gluten free, Beef Stew in the Slow Cooker basically cooks itself. The secret ingredient of barbecue sauce combined with meat and a whole lot of veggies makes for a super satisfying home-cooked hearty classic dish. Try serving over low carb cauliflower rice to soak up all the super sauce.

    Roasted Summer Vegetables and Pasta

    Eat the Rainbow is this Delectable Roasted Summer Vegetables and Pasta

    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. You are eating the rainbow in this hearty veggie dish. Look for pre-chopped veggies in your supermarket and it’s basically a one-step recipe! Keep an eye out for healthier options of available high protein, whole wheat pasta varieties.

    Stock Your Kitchen to Get Cooking

    Banza Chickpea Pasta, Variety Pack (Rigatoni/Cavatappi/Ziti/Wheels) - Gluten Free Healthy Pasta, High Protein, Lower Carb and Non-GMOBanza Chickpea Pasta, Variety Pack (Rigatoni/Cavatappi/Ziti/Wheels) – Gluten Free Healthy Pasta, High Protein, Lower Carb and Non-GMOBanza Chickpea Pasta, Variety Pack (Rigatoni/Cavatappi/Ziti/Wheels) - Gluten Free Healthy Pasta, High Protein, Lower Carb and Non-GMORightRice - Variety Pack (7oz. Pack of 6) - Made from Vegetables - High Protein, Vegan, non GMO, Gluten FreeRightRice – Variety Pack (7oz. Pack of 6) – Made from Vegetables – High Protein, Vegan, non GMO, Gluten FreeRightRice - Variety Pack (7oz. Pack of 6) - Made from Vegetables - High Protein, Vegan, non GMO, Gluten FreeBARILLA Protein+ (Plus) Spaghetti Pasta - Protein from Lentils, Chickpeas & Peas - Good Source of Plant-Based Protein - Protein PastaBARILLA Protein+ (Plus) Spaghetti Pasta – Protein from Lentils, Chickpeas & Peas – Good Source of Plant-Based Protein – Protein PastaBARILLA Protein+ (Plus) Spaghetti Pasta - Protein from Lentils, Chickpeas & Peas - Good Source of Plant-Based Protein - Protein Pasta

    Want More? Simplify Weekly Meal Planning with Holly’s Diabetic Meal Plan Downloadable

    diabetic meal plan

    Can you eat delicious food that is also good for you? Of course! Diabetic friendly meals definitely do not have to be boring and tasteless. This Diabetic Meal Plan & Recipes Downloadable is your easy go-to guide to meal planning diabetic meals the whole family will love. This comprehensive guide includes 13 weekly recipes, from dinners, lunch, snacks and dessert.

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    The post One Grocery Shopping List: 3 Delicious Diabetic Meals appeared first on The Healthy Cooking Blog.



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    Butyrate Improves Insulin Sensitivity and Increases Energy Expenditure in Mice

    By electricdiet / July 15, 2021


    Abstract

    OBJECTIVE We examined the role of butyric acid, a short-chain fatty acid formed by fermentation in the large intestine, in the regulation of insulin sensitivity in mice fed a high-fat diet.

    RESEARCH DESIGN AND METHODS In dietary-obese C57BL/6J mice, sodium butyrate was administrated through diet supplementation at 5% wt/wt in the high-fat diet. Insulin sensitivity was examined with insulin tolerance testing and homeostasis model assessment for insulin resistance. Energy metabolism was monitored in a metabolic chamber. Mitochondrial function was investigated in brown adipocytes and skeletal muscle in the mice.

    RESULTS On the high-fat diet, supplementation of butyrate prevented development of insulin resistance and obesity in C57BL/6 mice. Fasting blood glucose, fasting insulin, and insulin tolerance were all preserved in the treated mice. Body fat content was maintained at 10% without a reduction in food intake. Adaptive thermogenesis and fatty acid oxidation were enhanced. An increase in mitochondrial function and biogenesis was observed in skeletal muscle and brown fat. The type I fiber was enriched in skeletal muscle. Peroxisome proliferator–activated receptor-γ coactivator-1α expression was elevated at mRNA and protein levels. AMP kinase and p38 activities were elevated. In the obese mice, supplementation of butyrate led to an increase in insulin sensitivity and a reduction in adiposity.

    CONCLUSIONS Dietary supplementation of butyrate can prevent and treat diet-induced insulin resistance in mouse. The mechanism of butyrate action is related to promotion of energy expenditure and induction of mitochondria function.

    Recent studies suggest that natural compounds represent a rich source for small thermogenic molecules, which hold potential in the prevention and treatment of obesity and insulin resistance. Several natural products, such as resveratrol (1,2), bile acid (3), and genipin (4), have been reported to increase thermogenic activities in animal or cellular models. In the current study, we provide evidence for the thermogenic activity and therapeutic value of a short-chain fatty acid, butyric acid, in a mouse model of metabolic syndrome. Butyric acid has four carbons in the molecule (CH3CH2CH2-COOH) and becomes sodium butyrate after receiving sodium. Sodium butyrate is a dietary component found in foods such as cheese and butter. It is also produced in large amounts from dietary fiber after fermentation in the large intestine, where butyric acid is generated together with other short-chain fatty acids from nondigestible carbohydrates, such as nonstarch polysaccharides, resistant starch, and miscellaneous low-digestible saccharides (5,6). The bioactivities of sodium butyrate are related to inhibition of class I and class II histone deacetylases (7). Histone deacetylases regulate gene transcription through modification of chromatin structure by deacetylation of proteins, including histone proteins and transcription factors. To our knowledge, there is no report about butyrate in the regulation of insulin sensitivity or energy metabolism.

    Dietary intervention is a potential strategy in the prevention and treatment of metabolic syndrome. Peroxisome proliferator–activated receptor (PPAR)-γ coactivator (PGC)-1α, a transcription coactivator, is a promising molecular target in dietary intervention (1,2). PGC-1α controls energy metabolism by interaction with several transcription factors, e.g., estrogen-related receptor-α, nuclear respiratory factor-1 and -2, PPAR-α and -δ, and thyroid hormone receptor, that direct gene transcription for mitochondrial biogenesis and respiration (8). In the muscle, PGC-1α increases oxidative (type I) fiber differentiation and enhances fatty acid metabolism (9). In brown fat, PGC-1α stimulates adaptive thermogenesis through upregulation of uncoupling protein (UCP)-1 expression (10). A reduction in PGC-1α function is associated with mitochondrial dysfunction, reduction in fatty acid oxidation, and risk for insulin resistance or type 2 diabetes (1114). Dietary intervention of PGC-1α activity holds promise in the prevention and treatment of metabolic syndrome. However, our knowledge is limited in the dietary components or derivatives that are able to regulate the PGC-1 activity. In the current report, we provide evidence that sodium butyrate induced PGC-1 activity in skeletal muscle and brown fat in mice.

    RESEARCH DESIGN AND METHODS

    Male C57BL/6J (4 weeks old) mice were purchased from the Jackson Laboratory (Bar Harbor, ME). After 1 week quarantine, the C57BL/6J mice were fed a high-fat diet (D12331; Research Diets, New Brunswick, NJ), in which 58% of calories is from fat. All of the mice were housed in the animal facility with a 12-h light/dark cycle and constant temperature (22–24°C). The mice had free access to water and diet. All procedures were performed in accordance with National Institutes of Health guidelines for the care and use of animals and were approved by the institutional animal care and use committee at the Pennington Biomedical Research Center.

    Sodium butyrate administration.

    Sodium butyrate (303410; Sigma) was incorporated into the high-fat diet at 5% wt/wt. Sodium butyrate was blended into the diet using a food processor at 400 rpm. The sodium butyrate–containing diet was pelleted and stored in a –20°C freezer until usage. On the supplemented diet, mice could receive sodium butyrate at 5 g · kg−1 · day−1 at the normal daily rate of calorie intake.

    Intraperitoneal insulin tolerance.

    Intraperitoneal insulin tolerance testing was conducted by intraperitoneal injection of insulin (I9278; Sigma) at 0.75 units/kg body wt in mice after a 4-h fast, as described previously (15).

    Nuclear magnetic resonance.

    Body composition was measured for the fat content using quantitative nuclear magnetic resonance as previously described (15).

    Quantitative real-time RT-PCR.

    Total RNA was extracted from frozen tissues (kept at −80°C) using Tri-Reagent (T9424; Sigma), as described previously (16). TaqMan RT-PCR primer and probe were used to determine mRNA for PGC-1α (Mm00447183_m1), UCP-1 (Mm00494069_m1), PPAR-δ (Mm01305434_m1), and carnitine palmitoyltransferase-1b (CPT1b; Mm00487200_m1). The reagents were purchased from Applied Biosystems (Foster City, CA). Mouse ribosomal 18S rRNA_s1 (without intron-exon junction) was used as an internal control. The reaction was conducted with a 7900 HT Fast real-time PCR system (Applied Biosystems).

    Metabolic chamber.

    Energy expenditure, respiratory exchange ratio, spontaneous physical movement, and food intake were measured simultaneously for each mouse with a comprehensive laboratory animal monitoring system (Columbus Instruments, Columbus, OH) as described previously (15).

    Body temperature in cold response.

    Body temperature was measured in the cold room with ambient temperature at 4°C. Animals were sedated and restrained for <30 s during the measurement. A Thermalert model TH-8 temperature monitor (Physitemp, Clifton, NJ) was used with the probe placed in the rectum at 2.5 cm in depth.

    Western blotting.

    Fresh fat and muscles were collected and frozen immediately in liquid nitrogen. The whole-cell lysate was prepared in a lysis buffer with sonication as described previously (16). Antibodies and their sources are myoglobin (sc-25607; Santa Cruz Biotechnology), phosphorylated Akt (threonine 308 [Thr308], no. 9275; Cell Signaling), tubulin (ab7291; Abcam), phosphorylated insulin receptor substrate-1 (tyrosine 632 [Tyr632], no. sc-17196; Santa Cruz Biotechnology), myosin (M8421; Sigma), phosphorylated AMP kinase (AMPK; Thr172, no. 2531; Cell Signaling), and pP38 (sc-7975; Santa Cruz Biotechnology). The antibodies to PGC-1α and UCP-1 were from Dr. Thomas Gettys at our institute (Pennington Biomedical Research Center).

    Muscle fiber type.

    The fiber types in skeletal muscle were examined using two methods: succinate dehydrogenase staining for ATPase and immunostaining of type I myosin heavy chain. In the succinate dehydrogenase staining, midbelly cross-sections of muscle were cut at 8 μm in a cryostat (–20°C). After drying for 5 min at room temperature, the sections were incubated at 37°C for 60 min in incubation solution containing 6.5 mmol/l sodium phosphate monobasic, 43.5 mmol/l sodium phosphate biphasic, 0.6 mmol/l nitroblue tetrazolium (74032; Sigma), and 50 mmol/l sodium succinate (14160; Sigma). The sections were rinsed three times (30 s each time) in 0.9% saline, 5 min in 15% ethanol, and then mounted with aqueous mounting medium (DakoCytomation).

    Immunohistostaining.

    Fresh skeletal muscle was collected, embedded in gum tragacanth mixed with OCT freezing matrix, and quickly frozen in liquid nitrogen. The tissue slides were obtained through serial cross-section cutting at 8 μm thickness. The slide was blotted with type I myosin heavy-chain antibody (M8421; Sigma) at 1:200 dilution. After being washed, the slide was incubated with a biotinylated secondary antibody (BA-2000), and the color reaction was performed using ABC elite reagent (PK-6101). A 3,3′-diaminobenzidine substrate kit (SK-4100) was used to obtain signal for myosin I.

    Hematoxylin and eosin staining.

    Fresh tissues (brown adipose tissue [BAT]) were collected at 16 weeks of age after 12 weeks on the sodium butyrate–containing diet. Tissue was fixed in 10% formalin solution (HT50–1-2; Sigma). Tissue slides were obtained through serial cross-section cutting 8 μm in thickness and processed with standard procedure.

    Histone deacetylase assay and nuclear extract preparation.

    Histone deacetylase assay was conducted using a histone deacetylase assay kit (17-320; Upstate). Briefly, the muscle nuclear extract (10 μg) was incubated with [3H]acetyl CoA (TRK688; Amersham) radio-labeled histone H4 peptide (25,000 cpm, as a substrate) at 37°C for 12 h by shaking. Released [3H]acetate was measured using a scintillation counter. The nuclear extract was prepared according to a protocol described previously (17).

    Lipids in serum and feces.

    The serum fatty acids, including butyrate, were examined using a protocol described elsewhere (18). The detail is presented in Supplement 1, available in an online appendix at http://diabetes.diabetesjournals.org/cgi/content/full/db08-1637/DC1. Fatty acids in feces were determined using the protocol from a study by Schwarz et al. (19). Triglyceride and cholesterol were measured in whole blood with a Cardiochek portable test system.

    Statistical analysis.

    Data are the means ± SE from multiple samples. All of the in vitro experiments were conducted at least three times. Student’s t test or two-way ANOVA was used in the statistical analysis with significance set at P ≤ 0.05.

    RESULTS

    Energy metabolism.

    We first tested butyrate in prevention of dietary obesity. In the diet-induced obesity model, butyrate supplementation started at the beginning of high-fat diet feeding. Plain high-fat diet was used in the control group. Calorie intake was monitored four times in the first 10 weeks. After normalization with body weight, calorie intake was reduced with the increase in age. In the butyrate group, it was significantly higher at all of the time points (Fig. 1A). Energy expenditure, oxygen consumption, and substrate utilization were monitored using a metabolic chamber. In the butyrate group, energy expenditure and oxygen consumption were elevated at night (Fig. 1B and C). The respiratory exchange ratio was reduced during the day and night (Fig. 1D), suggesting an increase in fatty acid oxidation in response to butyrate. These data suggest that sodium butyrate may increase energy expenditure in the diet-induced obesity model.

    FIG. 1.
    FIG. 1.

    Energy metabolism in response to sodium butyrate. Butyrate increased energy expenditure in C57BL/B6 mice. Energy expenditure was examined using the metabolic chamber at the 1st week and the 10th week on high-fat diet (16 weeks in age). In this study, sodium butyrate was used at 5% wt/wt in high-fat diet. A: Food intake. Food intake was monitored daily for 5 days at each time point. Average daily food intake (g) was converted into kilocalories and normalized with body weight (kg) and 24 h. B: Energy expenditure measured as kilocalories per kilogram lean mass per hour. C: Oxygen consumption measured as milliliters volume oxygen per kilogram lean mass per hour. D: Substrate utilization. This is expressed by respiratory exchange ratio (RER), which is the volume ratio of oxygen consumed versus CO2 exhaled. E: Body weight (BW). F: Body fat content in percentage of body weight. This was determined by nuclear magnetic resonance. G: Body muscle content in percentage of body weight. H: Lipid in feces. Feces were collected in the cages during a 24-h period on high-fat diet at 12 weeks. Total lipids were extracted and quantified (P > 0.05, n = 5). I: Spontaneous physical activity. The frequency of horizontal movement (X) was shown for day and night at 10 weeks on a high-fat diet. For AD, and I, n = 8 in the control or butyrate group. For EG, n = 10 in the control or butyrate group. Values are the means ± SE. *P < 0.05, **P < 0.001 by Student’s t test. □, Control; ■, butyrate.

    Body weight and fat content were monitored in this study. In the control mice, body weight increased from 23 to 40 g after 16 weeks on high-fat diet (Fig. 1E), and fat content (adiposity) increased from 10 to 35% of body weight (Fig. 1F). Accordingly, lean mass was reduced from 80 to 65% (Fig. 1G). In the butyrate group, these parameters were not significantly changed during the 16 weeks on high-fat diet (Fig. 1E, F, and G), suggesting that butyrate prevented diet-induced obesity. Mouse growth was not influenced by butyrate because body length was identical between the two groups. Dietary fat digestion and absorption in the gastrointestinal tract was examined by measuring fatty acid content in feces. Fat content was identical in the feces of the two groups (Fig. 1H), suggesting that butyrate does not influence fat absorption by the gastrointestinal tract. Spontaneous physical activity was monitored during the day and night in the mice. The data suggest that physical activity was not reduced by butyrate (Fig. 1I). Increased activity was observed in the butyrate group at night. These data suggest that dietary supplementation with butyrate protected the mice from diet-induced obesity. This effect is associated with an increase in energy expenditure and fatty acid oxidation. The food intake and physical activity suggests that no toxicity was observed for butyrate in the mice.

    Insulin sensitivity.

    The increase in energy metabolism suggests that butyrate may protect mice from high-fat diet–induced insulin resistance. To test this possibility, systemic insulin sensitivity was analyzed by fasting glucose, fasting insulin, and insulin tolerance. In the control group, fasting glucose was increased significantly after 10 weeks on high-fat diet (Fig. 2A). In the butyrate group, this increase was not observed (Fig. 2A). Fasting insulin was 50% lower in the butyrate group at 16 weeks on high-fat diet (Fig. 2B). In the intraperitoneal insulin tolerance test, the butyrate group exhibited much better response to insulin at all time points (30, 60, 120, and 180 min) (Fig. 2C). Homeostasis model assessment for insulin resistance (HOMA-IR) was 60% lower in the butyrate group (Fig. 2D). These data suggest that insulin resistance was prevented in the butyrate group. Insulin signaling was examined in the skeletal muscle lysate with Tyr632 (Y632) phosphorylation of insulin receptor substrate-1 protein and Thr308 phosphorylation of Akt (Fig. 2E). Both signals were increased in the butyrate-treated mice (Fig. 2E and F), suggesting a molecular mechanism of insulin sensitization.

    FIG. 2.
    FIG. 2.

    Insulin sensitivity in butyrate-treated mice. A: Fasting glucose. Tail vein blood was used for glucose assay after 16 h fasting during the period of high-fat diet feeding. B: Fasting insulin. The insulin level was determined at 16 weeks on high-fat diet in fasting condition with a Lincoplex kit (MADPK model). C: Intraperitoneal insulin tolerance in butyrate-treated mice. Intraperitoneal insulin tolerance testing was performed at 12 weeks on high-fat diet (at 16 weeks of age). In AC, data are the means ± SE (n = 9). *P < 0.05, **P < 0.001 by Student’s t test. D: HOMA-IR. After an overnight fast, blood glucose and insulin were measured and used to determine insulin sensitivity through HOMA-IR (IR = fasting insulin mU/ml × fasting glucose mg/dl ÷ 405). Values are the means ± SE (n = 8 mice). **P < 0.001. E: Insulin signaling. The gastrocnemius muscle was isolated after insulin (0.75 units/kg) injection in mice for 30 min and used to prepare the whole-cell lysate for immunoblot. The mice on high-fat diet for 13 weeks were used in the signaling assay. F: Signal quantification. The blot signal in E was quantified and presented after normalization with protein loading. **P < 0.001 (n = 2). IRS, insulin receptor substrate.

    BAT.

    The association of increased food intake with elevated energy expenditure led us to study BAT, which is responsible for adaptive thermogenesis in response to diet or cold (2022). Diet-induced thermogenesis reduces obesity in both humans and animals (23). In the butyrate group, the increase in energy expenditure was observed at night when mice actively took food (Fig. 1A and B). This result suggests an increase in thermogenesis. To determine the thermogenic function, we conducted a cold-response experiment. Mice were exposed to a cold environment with an ambient temperature of 4°C for 90 min. Core body temperature was monitored three times by measuring the rectal temperature. In control mice, body temperature decreased with time and was 34.5°C after 90 min in the cold (Fig. 3A). In butyrate-treated mice, body temperature dropped to 35°C transiently at 30 min and then returned to 36°C for the remainder of the time. These data suggest that thermogenic function is enhanced in the butyrate group.

    FIG. 3.
    FIG. 3.

    Brown adipose tissue response to sodium butyrate. A: Adaptive thermogenesis in cold environment. Rectum temperature was measured when the mice were exposed to 4°C ambient temperature in a cold room at 10 weeks on high-fat diet. Details of the procedure are described in research design and methods. B: Hematoxylin and eosin staining in BAT. The staining was conducted in BAT collected at 13 weeks on high-fat diet. Photograph was taken at ×100 magnification. C: mRNA expression in BAT. BAT was collected at 13 weeks on high-fat diet. Gene expression was examined by qRT-PCR. mRNA of PGC-1α and UCP-1 in brown fat of mice treated with butyrate was measured. D: Immunoblot of protein in BAT. BAT was collected at 13 weeks of butyrate treatment. The whole-cell lysate (100 μg) was resolved in SDS-PAGE and blotted with PGC-1α and UCP-1 antibodies. Data are the means ± SE (n = 9 mice). *P < 0.05. (A high-quality digital representation of this figure is available in the online issue.)

    Brown fat is critical for adaptive thermogenesis in mice. Morphology and gene expression were examined in brown fat. Compared with the control mice, the size of brown adipocytes was much smaller in the butyrate group (Fig. 3B), suggesting higher thermogenic activity that leads to the reduction in fat accumulation. Mitochondrial function is regulated by gene expression (24). To understand the molecular basis of the increased thermogenesis, we examined the expression of two thermogenesis-related genes, PGC-1α and UCP-1, in BAT. mRNA of both genes was increased in the butyrate-treated mice (Fig. 3C). The increase was observed in their proteins in the brown fat (Fig. 3D). The increased gene expression provides a molecular basis for enhanced thermogenesis by butyrate treatment.

    Skeletal muscle.

    To understand the cellular basis of enhanced fatty acid utilization in the butyrate group, we assessed muscle fiber types. PGC-1α was reported to induce transformation of skeletal muscle fiber from glycolytic type (type II) into oxidative type (type I) in transgenic mice (9). Type I fibers are distinct from type II fibers in several properties (25). Type I fibers (oxidative and slow-twitch fibers) are rich in mitochondria, red in color, and active in fat oxidation for ATP biosynthesis. Type II fibers (glycolytic and fast-twitch fibers) are relatively poor in mitochondrial activity, lighter in color, and dependent on glycolysis in ATP production. The butyrate effect on PGC-1α in BAT suggests that skeletal muscle fibers may be changed by butyrate.

    Compared with the control group, the butyrate group exhibited a deep red color (Fig. 4A). Fiber type analysis was conducted in the vastus lateralis, gastrocnemius (rich in glycolytic fibers), and soleus (rich in oxidative fiber). Type I fiber was determined with type I myosin heavy-chain immunohistostaining. The ratio of type I fibers were increased in all of the skeletal muscles of butyrate-treated mice (Fig. 4B). The increase was confirmed with a metachromatic dye–ATPase assay, in which the type I fibers were blue in color (Fig. 4C). To support the change in muscle morphology, the proteins of type 1 myosin heavy chain and PGC-1α were quantified in muscle lysate in an immunoblot. A significant increase was observed in both proteins in butyrate-treated mice (Fig. 4D). Myoglobin (another marker of oxidative type I fiber) was also increased by butyrate (Fig. 4D). A mean value of each protein is presented in Fig. 4D. These data suggest that the ratio of type I fiber was increased by butyrate in skeletal muscle.

    FIG. 4.
    FIG. 4.

    Oxidative fiber in skeletal muscle. A: Vastus lateralis muscle. The tissue was isolated from mice that were fed high-fat diet for 13 weeks. B: Oxidative fiber (type I fibers) in serial cryostat sections of muscle. The muscle tissue slides were made from vastus lateralis, gastrocnemius (gastr.), and soleus muscle. They were stained with antibody against type I myosin heavy chain for oxidative fibers, as indicated by the brown color. The photograph was taken at ×20 magnification. C: Succinate dehydrogenase staining of oxidative fibers. The oxidative fibers were stained in serial cryostat sections of the vastus lateralis and gastrocnemius (gastr.) muscle as indicated by dark blue color in the photomicrograph. D and E: Quantification of proteins in immunoblot. The whole-cell lysate was prepared from muscle tissues and analyzed in an immunoblot. Signals for PGC-1α, type I myosin heavy chain, myoglobin, phosphorylated AMPK (pAMPK), and phosphorylated p38 (pP38) were blotted with specific antibodies. A representative blot is shown. Relative signal strength was quantified for each band and expressed in the bar figure. Results are the means ± SE (n = 8 mice). *P < 0.01, **P < 0.001 (vs. control). (A high-quality digital representation of this figure is available in the online issue.)

    AMPK and p38 activities were examined by their phosphorylation status. Their activities may contribute to elevation of PGC-1α protein through enhanced protein stability (2628). It was not clear whether this mechanism was activated by butyrate. To test this possibility, we examined activity of AMPK and p38 in skeletal muscle. An increase in their phosphorylation was observed in muscle lysate of butyrate-treated mice (Fig. 4D), suggesting increased activation of the two kinases by butyrate. In the L6 cell line, AMPK and p38 phosphorylation was increased by butyrate in the cell culture (Fig. 5A), suggesting butyrate is able to activate AMPK directly. In the same culture, PGC-1α protein was increased (Fig. 5A). In the liver of butyrate-treated mice, a similar pattern of changes was observed in AMPK, p38, and PGC-1α (Fig. 5B). These data consistently suggest that AMPK and p38 were activated by butyrate and that their activation may contribute to the increase in PGC-1α activity.

    FIG. 5.
    FIG. 5.

    Effect of butyrate on L6 muscle cells and liver tissues. A: AMPK and PGC-1α in L6 cells. Differentiated L6 myotubes were starved in 0.25% BSA and Dulbecco’s modified Eagle’s medium overnight. The cells were treated with 500 μmol/l of sodium butyrate for 4 h and analyzed in an immunoblot. A mean value of triplicate experiments is shown in the bar figure. B: AMPK and PGC-1α in liver. The whole-cell lysate was prepared from liver tissues collected from mice on high-fat diet (HFD) for 13 weeks and analyzed in an immunoblot. In the experiments, phosphorylated AMP kinase (pAMPK), phosphorylated p38 (pP38), and PGC-1α were blotted with the specific antibodies. A representative blot is shown. A mean value of five mice is shown in the bar figure (n = 5). *P < 0.05; **P < 0.001.

    Mitochondrial function.

    Mitochondrial function was examined in skeletal muscle tissue and L6 muscle cells under butyrate treatment. Fatty acid oxidation was monitored in gastrocnemius muscle with 14C-labeled palmitic acid. A 200% increase in 14C-labeled CO2 was observed in butyrate-treated mice (Fig. 6A). Fatty acid oxidation was associated with expression of PGC-1α target genes, such as CPT1b and COX-I (cytochrome c oxidase I) (9). Expression of these two genes was increased in skeletal muscle of butyrate-treated mice (Fig. 6B and C). The nuclear receptor PPAR-δ promotes fatty acid oxidation in skeletal muscle (29). PPAR-δ expression was also increased in butyrate-treated mice (Fig. 6B). In cultured L6 cells, a similar increase was observed in fatty acid oxidation and gene expression after butyrate treatment (Fig. 6D and E). These data consistently support the role of butyrate activity in the promotion of mitochondrial function.

    FIG. 6.
    FIG. 6.

    Mitochondrial function and blood lipids. Vastus lateralis muscle and blood samples were collected from mice at 13 weeks on high-fat diet (18 weeks in age) and examined for fatty acid oxidation, gene expression, and blood lipids. A: Fatty acid oxidation in muscle. The y-axis represents fold change in 14C-labled CO2. B: Gene expression in muscle. Relative fold change in mRNA was used to indicate gene expression. C: Mitochondrial DNA COX-I (cytochrome c oxidase I) determined by SYBR Green RT-PCR. D: Fatty acid oxidation in L6 cells. Fully differentiated L6 cells were treated with 500 μmol/l butyrate for 16 h, and fatty acid oxidation was measured. E: Gene expression in L6 cells. Relative fold change in mRNA was used to indicate gene expression. F: Butyrate in serum. G: Histone deacetylase activity in muscle. H: Triglyceride in blood. I: Total cholesterol in blood. Data are the means ± SE (n = 6). *P < 0.05; **P < 0.001.

    Histone deacetylase activity in muscle.

    The butyrate concentration was analyzed in serum collected from the butyrate and control groups. In the fasted condition (overnight fast), the butyrate concentration was 7.23 ± 0.93 μg/ml in the butyrate group and 5.71 ± 0.38 μg/ml in the control animals. In the fed condition, the butyrate concentration was 9.40 ± 1.36 μg/ml in the butyrate group versus 5.48 ± 0.60 μg/ml in the control mice (P < 0.05, n = 5) (Fig. 6F). The data suggest that dietary supplementation increased butyrate levels in the blood. It is likely that the metabolic activity of butyrate is related to inhibition of histone deacetylase. Sodium butyrate inhibits the class I and class II histone deacetylases. To test this possibility, histone deacetylase activity was examined in skeletal muscle of mice at 16 weeks on high-fat diet (Fig. 6F). The assay was conducted with nuclear extracts of muscle samples. Histone deacetylase activity was reduced by 50% in the butyrate group (Fig. 6G). Trichostatin A (TSA), a typical histone deacetylase inhibitor, was used as a positive control in the parallel treatment. Histone deacetylase activity was decreased in the skeletal muscle of TSA-treated mice (Supplement 2). These data suggested that dietary supplementation of butyrate leads to suppression of histone deacetylase activity in the body. Total triglyceride and cholesterol were examined in the blood. These lipids were reduced in the butyrate group (Fig. 6H and I).

    Treatment of obesity with butyrate.

    In the prevention studies, butyrate was administrated together with high-fat diet during the induction of obesity. To test butyrate in the treatment of obesity and insulin resistance, we administrated butyrate to obese mice that had been on a high-fat diet for 16 weeks. After a 5-week treatment with butyrate, the obese mice lost 10.2% of their original body weight, which dropped from 37.6 to 34.4 g (Fig. 7A). In the control group, body weight increased by 15.8% (from 35.9 to 41.6 g) during the same time period. Consistent with the change in body weight, fat content was reduced by 10% in the butyrate group (Fig. 7B). Furthermore, fasting glucose was reduced by 30% from 131 to 98.6 mg/dl (P < 0.016), HOMA-IR was reduced by 50%, and intraperitoneal insulin tolerance was improved significantly in the butyrate group (Fig. 7C and D). These data suggest that butyrate is effective in the treatment of obesity and insulin resistance in the dietary obese model.

    FIG. 7.
    FIG. 7.

    Treatment of obesity with butyrate. Obesity was induced in C57BL/6J mice fed a high-fat diet for 16 weeks (21 weeks in age). The obese mice were then treated with butyrate through food supplementation for 5 weeks. A: Body weight (BW). Body weight was shown at the beginning and end of the 5-week butyrate treatment. B: Fat content. Fat content was determined in the body using nuclear magnetic resonance at the end of the 5-week treatment with butyrate. C: Intraperitoneal insulin tolerance. At the end of 5 weeks, intraperitoneal insulin tolerance testing was performed after a 4-h fast. D: HOMA-IR. Values are the means ± SE (n = 8 in each group). *P < 0.05.

    DISCUSSION

    Metabolic activities of butyric acid were examined in this study in diet-induced obese mice. The most important observation is that butyrate supplementation at 5% wt/wt in high-fat diet prevented development of dietary obesity and insulin resistance. It also reduced obesity and insulin resistance in obese mice. In butyrate-treated mice, the plasma butyrate concentration was increased, and blood lipids (triglycerides, cholesterol, and total fatty acids) were decreased (Fig. 6H–I and Supplement 1). The change in insulin sensitivity may be a consequence of a reduction in adiposity in our model. The increase in energy expenditure and fatty acid oxidation may be responsible for the antiobesity effect of butyrate. Butyrate supplementation did not reduce food intake, fat absorption, or locomotor activity, suggesting that there was no toxicity from butyrate. Butyrate was tested at 5 and 2.5% wt/wt in the high-fat diet in this study. At the lower (2.5% wt/wt) dosage, similar metabolic activity was observed (Supplement 3). At 5% in the high-fat diet, butyrate increased the calorie content from 58 to 64.4% in the fat. The increase in fat calories may not contribute to our observation of the antiobesity activity for butyrate. A recent study of weight-loss diets suggests that total calorie intake, not diet composition, is responsible for weight reduction in humans (30). At the cellular level, butyrate increased mitochondrial respiration, as indicated by the increase in oxygen consumption and CO2 production. At the molecular level, increased expression of PGC-1α, PPAR-δ, and CPT1b may be involved in the stimulation of mitochondrial function by butyrate.

    The current study indicates that in vivo butyrate is a novel activator of PGC-1α. PGC-1α activity may be regulated by butyrate at three levels. PGC-1α expression was increased in both mRNA and protein. The protein elevation was observed in brown fat, skeletal muscle, and liver in butyrate-treated mice. It may be a result of increased mRNA expression or extended half-life of the PGC-1α protein. The change in protein stability is supported by the activities of AMPK and p38 in tissues and cells after butyrate treatment. These kinases phosphorylate the PGC-1α protein and inhibit its degradation (27,28,3134). As a transcriptional coactivator, PGC-1α transcription activity may be induced by phosphorylation, which leads to removal of a suppressor protein (p160 myb) that is associated with PGC-1α in the basal condition (35). P38 acts downstream of AMPK in the phosphorylation of PGC-1α (36). Therefore, AMPK may increase PGC-1α phosphorylation through direct and indirect (p38) mechanisms. It is not clear how AMPK is activated by butyrate. Butyrate may act through induction of AMP levels in cells from increased consumption of ATP. It was reported that butyrate increases ATP consumption (37). Induction of PGC-1α activity may be a molecular mechanism by which butyrate stimulates mitochondrial function.

    Inhibition of histone deacetylase may contribute to increased mRNA expression of PGC-1α, PPAR-δ, and CPT1b. Histone deacetylase inhibition promotes gene expression through transcriptional activation, which is determined by gene promoter activity. Promoter activation requires histone acetylation, which opens chromatin DNA to the general transcription factors for transcription initiation and mRNA elongation. Histone deacetylase inhibits gene promoter activity through deacetylation of histone proteins. In the presence of butyrate, promoter inhibition is prevented by butyrate suppression of histone deacetylase. Histone deacetylase suppression will enhance histone acetylation. This chromatin modification may occur in the gene promoters for PGC-1α, PPAR-δ, and CPT1b for the upregulation of gene transcription.

    Butyrate induces type I fiber differentiation in skeletal muscle. In skeletal muscle cells, inhibition of histone deacetylase enhances myotube differentiation in vitro (2830) and protects muscle from dystrophy in vivo (2931). In transgenic mice, knockout of class II histone deacetylases was shown to promote differentiation of type I (oxidative) fibers in skeletal muscle (32). This is consistent with our data that type I fiber was increased by butyrate, which inhibits histone deacetylase activities in the skeletal muscle of butyrate-treated mice. TSA, a typical histone deacetylase inhibitor, was tested in parallel treatment with butyrate. TSA exhibited activity similar to that of butyrate in mice (Supplement 2). TSA prevented dietary obesity, insulin resistance, and increased the type I fiber in the skeletal muscle. The activity was associated with elevation of PGC-1α protein. The current study suggests that the metabolic activities of butyrate may be dependent on the inhibition of histone deacetylase.

    In summary, dietary supplementation of butyrate can prevent and treat diet-induced obesity and insulin resistance in mouse models of obesity. These activities of butyrate are similar to those of resveratrol (1,2). The mechanism of butyrate action is related to promotion of energy expenditure and induction of mitochondrial function. Stimulation of PGC-1α activity may be a molecular mechanism of butyrate activity. Activation of AMPK and inhibition of histone deacetylases may contribute to the PGC-1α regulation. Butyrate and its derivatives may have potential application in the prevention and treatment of metabolic syndrome in humans.

    Acknowledgments

    This study was supported by National Institutes of Health grants DK68036 and P50AT02776-020002 (to J.Y.), American Diabetes Association (ADA) Research Award 7-07-RA-189 (to J.Y.), a pilot grant from the Functional Food Division at the Pennington Biomedical Research Center, ADA Junior Faculty Award 1-09-JF-17 (to Z.G.), and CNRU Grant 1P30 DK072476 sponsored by the NIDDK.

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

    We thank Zhong Wang, Can Pang, Jong-Seop Rim, Qing He, Ms. Xin Ye, and Wei Tseng for their excellent technical support. We thank Thomas Gettys for the antibodies to PGC-1α and UCP-1.

    Footnotes

    • 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.

      • Received November 24, 2008.
      • Accepted March 24, 2009.
    • 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.



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    Raising Cane’s Sauce Recipe – My Bizzy Kitchen

    By electricdiet / July 13, 2021






    Raising Cane’s Sauce Recipe – My Bizzy Kitchen




































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    Keto Coconut Macaroons | Diabetes Strong

    By electricdiet / July 11, 2021


    Crispy on the outside, soft on the inside, and packed with wonderful flavor, these keto coconut macaroons are such a treat! Less than 1 net carb each and ready in under 30 minutes.

    Stack of Keto Coconut Macaroons on a white plate, topped with shredded coconut

    When you’re in the mood for a sweet treat, these keto coconut macaroons are sure to hit the spot! Not to be confused with French macarons, these wonderful cookies are crispy on the outside, soft on the inside, and oh-so-delicious.

    They’re also dairy free, gluten free, and less than 1 net carb each. Best of all, they can be ready in under 30 minutes!

    How to make keto coconut macaroons

    These delicious cookies come together in just eight easy steps. Let’s see how it’s done!

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

    Step 1: Preheat the oven to 375°F. Line a baking sheet with parchment paper.

    Step 2: In a large bowl, beat the egg whites until slightly foamy.

    Slightly frothed egg whites in a glass bowl with an electric mixer

    Step 3: Add the swerve, then whip on high speed until stiff peaks form.

    Stiff egg whites in a glass bowl with an electric mixer, as seen from above

    Step 4: Add the coconut flour and vanilla. Mix until just combined, working gently so the egg whites don’t deflate.

    Step 5: Carefully fold in the shredded coconut and mix until incorporated.

    Macaroon dough with shredded coconut, mixed until just incorporated in a glass bowl with a wooden spoon

    Step 6: Drop the mixture by heaping tablespoons onto the prepared baking sheet. You should have 15 total cookies.

    Heaps of dough on a baking sheet lined with parchment paper, as seen from above

    Step 7: Bake for 12-15 minutes, or until browned along the edges.

    Finished macaroons cooling on a baking sheet lined with parchment paper, as seen from above

    Step 8: Remove from the oven and allow to cool on the pan for 5 minutes, then transfer to a wire rack to finish cooling.

    How simple was that? The hardest part is waiting for them to fully cool before you dive in!

    Three macaroons on a white plate with a bite taken out of one

    Is coconut good for keto?

    Shredded coconut is great for a low-carb or keto diet. Just make sure you’re buying the unsweetened version to avoid any added sugar.

    Coconut is a very nutritious fruit — it’s a great source of minerals, B vitamins, and antioxidants. Best of all, this fruit is low in carbs and high in fat, which makes it a great ingredient to incorporate into your keto baking!

    Stack of macaroons on a white plate topped with shredded coconut, as seen from above

    Making keto chocolate macaroons

    Who doesn’t love adding a little chocolate to their keto treats? Good news: it’s very easy to do!

    The easiest option is to drizzle your macaroons. Once they’ve finished baking, allow them to cool completely while you melt sugar-free chocolate chips. Then, simply drizzle your macaroons to your liking and set them in the refrigerator to allow the chocolate to set.

    You could also dip the bottom of your cooled macaroons into the melted chocolate for a chocolate layer. Once you’ve dipped all the cookies, drizzle any remaining chocolate on top, then set in the refrigerator until the chocolate solidifies.

    Storage

    Any leftover coconut macaroons can be stored in an airtight container at room temperature for 2-3 days or in the refrigerator for 5-6 days. If you added chocolate, make sure to store them in the refrigerator so it doesn’t melt.

    You can also freeze your cookies for up to 3 months. To enjoy, allow them to thaw either at room temperature for 1-2 hours or in the refrigerator for 4-5 hours.

    Close-up of a macaroon with a bite taken out; stack of macaroons in the background

    Other keto cookie recipes

    Are you always looking for more low-carb ways to indulge your sweet tooth? Personally, I can never get enough of keto-friendly cookies! Here are a few of my favorite recipes I know you’ll love:

    For even more ways to indulge your dessert cravings and stay in ketosis, make sure to check out my roundup of 10 Keto-Friendly Dessert Recipes!

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

    Recipe Card

    Keto Coconut Macaroons

    Crispy on the outside, soft on the inside, and packed with wonderful flavor, these keto coconut macaroons are such a treat! Less than 1 net carb each and ready in under 30 minutes.

    Prep Time:10 minutes

    Cook Time:15 minutes

    Cooling Time:5 minutes

    Total Time:30 minutes

    Servings:15

    A stack of Keto Coconut Macaroons on a white plate with shredded coconut

    Instructions

    • Preheat the oven to 375°F. Line a baking sheet with parchment paper.

    • In a large bowl, beat the egg whites until slightly foamy.

    • Add the Swerve, then whip on high speed until stiff peaks form.

    • Add the coconut flour and vanilla. Mix until just combined, working gently so the egg whites don’t deflate.

    • Carefully fold in the shredded coconut and mix until incorporated.

    • Drop the mixture by heaping tablespoons onto the prepared baking sheet. You should have 15 total cookies.

    • Bake for 12-15 minutes, or until browned along the edges.

    • Remove from the oven and allow to cool on the pan for 5 minutes, then transfer to a wire rack to finish cooling.

    Recipe Notes

    This recipe is for 15 servings. If you make 15 cookies from the batter, each serving will be 1 cookie.
    For chocolate macaroons, melt sugar-free chocolate chips, then either drizzle the macaroons or dip the bottoms to coat.
    Cookies can be stored in an airtight container at room temperature for 2-3 days, in the refrigerator for 5-6 days, or in the freezer for 3 months. Thaw in the refrigerator for 4-5 hours or at room temperature for 1-2 hours.

    Nutrition Info Per Serving

    Nutrition Facts

    Keto Coconut Macaroons

    Amount Per Serving (1 maccaroon)

    Calories 58
    Calories from Fat 46

    % Daily Value*

    Fat 5.1g8%

    Saturated Fat 4.5g23%

    Trans Fat 0g

    Polyunsaturated Fat 0g

    Monounsaturated Fat 0g

    Cholesterol 0mg0%

    Sodium 15mg1%

    Potassium 11.2mg0%

    Carbohydrates 2.4g1%

    Fiber 1.6g6%

    Sugar 0.7g1%

    Protein 1.4g3%

    Net carbs 0.8g

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

    Course: Dessert, Snack

    Cuisine: American

    Diet: Diabetic, Gluten Free

    Keyword: dairy-free, gluten-free, Keto macaroons, low carb, macaroons



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    Calzones – Easy Italian Dinner Favorites

    By electricdiet / July 9, 2021


    Fantastic Family Friendly Italian Style Meal

    Rich and robust in flavor, Italian style dishes make a family friendly satisfying meal. Through the years, Holly set out to create her own homemade recipes to satisfy her craving and of course always keeping them trim and terrific! Classic marinara sauce mixed with sirloin, garlic, mushrooms and mozzarella all rolled into a dough makes for an outstanding all-in-one meal, the Calzone from Holly’s KITCHEN 101 cookbook.

    Calzones
    My calzones might not look picture perfect but when it comes to taste, this easy-to-make scrumptious recipe gets a thumbs up!

      Servings8 calzones

      Ingredients

      • 1/2pound


        ground sirloin

      • 1/2cup


        chopped onion

      • 1cup


        sliced mushrooms

      • 1teaspoon


        minced garlic

      • 1teaspoon


        dried basil leaves

      • 1/2teaspoon


        dried oregano leaves



      • salt and pepper to taste

      • 1


        can refrigerated pizza crust10-13.8-ounce

      • 1/2cup


        shredded part-skim mozzarella cheese

      • 1cup


        marinara sauce

      Instructions
      1. Preheat oven 425°F. Coat baking sheet with nonstick cooking spray.

      2. In large nonstick skillet, cook meat, onion, mushrooms and garlic until meat is done; drain excess fat. Add basil, oregano and season to taste. Set aside.

      3. Unroll dough; pat and stretch into rectangle on floured surface. Cut dough into eight squares. Spoon about 1/4 cup meat mixture on each square. Sprinkle evenly with cheese.

      4. Fold dough over filling forming into a semi-circle mashing edges to form rim. Press fork along edges to seal dough. Prick tops of calzones with fork to allow steam to escape. Place on baking sheet.

      5. Bake 10-12 minutes or until lightly browned. Serve with marinara sauce.

      Recipe Notes

      Calories 190, Calories from Fat 23%, Fat 5g, Saturated Fat 1g, Cholesterol 20mg, Sodium 433mg, Carbohydrates 24g, Dietary Fiber 2g, Total Sugars 5g, Protein 12g, Dietary Exchanges: 1 starch, 1 vegetable, 1 lean meat

      Terrific Tip: Be creative and add your favorite vegetables to the calzone filling.

      Calzone Recipe from KITCHEN 101 cookbook

      KITCHEN 101 cookbook is perfect for the new kitchen or the busy person. Unroll refrigerated pizza crust, stuff with Italian style ingredients and try adding your favorite veggies for an unbeatable dish your family will ask for time and again. Get your kids in on the action, as they will enjoy folding the dough and helping mash the edges. No picture perfection needed for this tasty meaty masterpiece.

      Be creative and add your favorite vegetables to the calzone filling. Hard to believe but this comfort-food Calzone is diabetic friendly! They are also easy to freeze so feel free to make plenty and keep in the freezer to pull out on a busy night.

      What Your Kitchen Needs for this Recipe

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      Get All of Holly’s Healthy Easy Cookbooks

      The post Calzones – Easy Italian Dinner Favorites appeared first on The Healthy Cooking Blog.



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      Tauroursodeoxycholic Acid May Improve Liver and Muscle but Not Adipose Tissue Insulin Sensitivity in Obese Men and Women

      By electricdiet / July 7, 2021


      Abstract

      OBJECTIVE Insulin resistance is commonly associated with obesity. Studies conducted in obese mouse models found that endoplasmic reticulum (ER) stress contributes to insulin resistance, and treatment with tauroursodeoxycholic acid (TUDCA), a bile acid derivative that acts as a chemical chaperone to enhance protein folding and ameliorate ER stress, increases insulin sensitivity. The purpose of this study was to determine the effect of TUDCA therapy on multiorgan insulin action and metabolic factors associated with insulin resistance in obese men and women.

      RESEARCH DESIGN AND METHODS Twenty obese subjects ([means ± SD] aged 48 ± 11 years, BMI 37 ± 4 kg/m2) were randomized to 4 weeks of treatment with TUDCA (1,750 mg/day) or placebo. A two-stage hyperinsulinemic-euglycemic clamp procedure in conjunction with stable isotopically labeled tracer infusions and muscle and adipose tissue biopsies were used to evaluate in vivo insulin sensitivity, cellular factors involved in insulin signaling, and cellular markers of ER stress.

      RESULTS Hepatic and muscle insulin sensitivity increased by ∼30% (P < 0.05) after treatment with TUDCA but did not change after placebo therapy. In addition, therapy with TUDCA, but not placebo, increased muscle insulin signaling (phosphorylated insulin receptor substrateTyr and AktSer473 levels) (P < 0.05). Markers of ER stress in muscle or adipose tissue did not change after treatment with either TUDCA or placebo.

      CONCLUSIONS These data demonstrate that TUDCA might be an effective pharmacological approach for treating insulin resistance. Additional studies are needed to evaluate the target cells and mechanisms responsible for this effect.

      The ability of insulin to decrease hepatic glucose production, suppress adipose tissue lipolytic rate, and stimulate skeletal muscle glucose uptake is critical for normal metabolic function. Obesity is an important cause of multiorgan insulin resistance (13), and insulin sensitivity decreases linearly with increasing BMI (4,5). Insulin resistance has important clinical implications because it is involved in the pathogenesis of many of the metabolic complications associated with obesity. The precise mechanisms responsible for the link between obesity and insulin resistance are not known but likely involve alterations in fatty acid metabolism, excess triglyceride accumulation in the liver and muscle (611), and systemic low-grade inflammation (1214).

      Recently, endoplasmic reticulum (ER) stress has been identified as a contributor to insulin resistance associated with obesity in experimental models (15,16). The ER is responsible for the synthesis, folding, and trafficking of secretory and membrane proteins. Disruption of ER homeostasis results in an adaptive unfolded protein response (UPR), which aims to restore ER folding capacity and mitigate stress. ER stress can also inhibit insulin signaling, at least in part, by activating the c-Jun NH2-terminal kinase (JNK) pathway through inositol-requiring enzyme (IRE)-1 (15,1720) or RNA-dependent protein kinase (PKR)-mediated mechanisms (21). Increased ER stress is associated with impaired insulin action in obese mice (15), and chemical or genetic amelioration of this stress improves insulin sensitivity and glucose homeostasis (18). Increased ER stress in liver and adipose tissue and insulin resistance are also associated with obesity in humans (22,23), whereas weight loss decreases ER stress and improves insulin sensitivity (22).

      Tauroursodeoxycholic acid (TUDCA) is a bile acid derivative that has been used in Europe to treat cholelithiasis and cholestatic liver disease. TUDCA can also act as a chemical chaperone to enhance protein folding and protect cells against ER stress (18). In obese mice, parenteral TUDCA treatment reduces ER stress, improves systemic insulin resistance, and decreases intrahepatic triglyceride (IHTG) content (18). Although data from studies conducted in animal models and cell systems demonstrate beneficial metabolic effects, the effect of TUDCA on insulin action has not been studied in human subjects.

      The purpose of the present study was to determine whether chemical interventions targeting the ER stress pathway results in metabolic benefits in people. Accordingly, we conducted a randomized controlled trial in insulin-resistant, obese subjects to evaluate the effect of treatment with TUDCA on insulin sensitivity in the liver (glucose production), muscle (glucose uptake), and adipose tissue (lipolysis). We hypothesized that treatment with TUDCA would improve multiorgan insulin signaling and sensitivity and other metabolic factors associated with insulin resistance. The hyperinsulinemic-euglycemic clamp procedure, in conjunction with stable isotopically labeled tracer infusions, was used to determine in vivo insulin sensitivity, and adipose tissue and skeletal muscle biopsies were obtained to assess ER stress markers, phosphorylation of JNK, and components of the insulin-signaling pathway before and after 4 weeks of treatment with TUDCA or placebo.

      RESEARCH DESIGN AND METHODS

      Twenty obese adults ([means ± SD] 8 men and 12 women, aged 48 ± 11 years, BMI 37 ± 4 kg/m2) participated in this single-blinded, randomized, placebo-controlled trial. All subjects were insulin resistant, defined as a homeostasis model assessment of insulin resistance (HOMA-IR) value of ≥3.0 at the time of screening (24). Subjects completed a comprehensive medical evaluation, including a detailed history, physical examination, blood tests, and a 2-h oral glucose tolerance test. Those who had diabetes, chronic liver disease other than nonalcoholic fatty liver disease (NAFLD), severe hypertriglyceridemia (fasting serum triglyceride concentrations >400 mg/dl), and those who smoked cigarettes or were taking medications known to alter glucose or lipid metabolism were excluded. We purposely studied obese subjects who were insulin resistant but did not have diabetes to provide the best chance for detecting an improvement in insulin sensitivity by TUDCA therapy, without the potential confounding influences of treatment with diabetes medications and differences in glucose control among study subjects. All subjects were sedentary (regular exercise <1 h/week and ≤1 time/week) and weight stable (<2% weight change) for at least 3 months before the study. Subjects provided written informed consent before participating in this study, which was approved by human research protection office of Washington University School of Medicine in St. Louis, Missouri.

      Body composition.

      Body composition analyses were performed ∼1 week before the hyperinsulinemic-euglycemic clamp procedure was performed. Body fat mass and fat-free mass were determined by using dual-energy X-ray absorptiometry (QDR 4500; Hologic, Waltman, MA). Abdominal subcutaneous adipose tissue and intra-abdominal adipose tissue volumes were determined by using magnetic resonance imaging; the sum of 10 axial images of 1-cm thickness, beginning at the L4–L5 interspace and extending proximally, was used to determine each fat depot volume. Intrahepatic triglyceride content was determined by using magnetic resonance spectroscopy (3T Siemens Magnetom Trio scanner; Siemens, Erlanger, Germany); three 15 × 15 × 15–mm voxels were examined in each subject, and the values were averaged to provide an estimate of the percent of total liver volume comprised of triglycerides (25).

      Hyperinsulinemic-euglycemic clamp procedure.

      Subjects were admitted to the clinical research unit at Washington University School of Medicine in the afternoon on the day before the clamp procedure. At 1800 h, they consumed a standard meal containing 12 kcal/kg fat-free mass, with 55% of total energy provided as carbohydrates, 30% as fat, and 15% as protein. Subjects then fasted, except for water, until completion of the clamp procedure the next day. At 0500 h the following morning, a catheter was inserted into a forearm vein to infuse stable isotopically labeled tracers (purchased from Cambridge Isotope Laboratories, Andover, MA), dextrose and insulin. A second catheter was inserted into the contralateral radial artery to obtain blood samples. Radial artery cannulation was not successful in four subjects, so a catheter was inserted into a hand vein, which was heated to 55°C by using a thermostatically controlled box to obtain arterialized blood samples (26). At 0600 h, a primed-continuous infusion of [6,6-2H2]glucose (priming dose 22.5 μmol/kg body wt; infusion rate 0.25 μmol/kg body wt/min) was started and maintained for 9.5 h. At 0800 h, a continuous infusion of [2,2-2H2]palmitate (infusion rate 0.035 μmol/kg body wt/min) bound to 25% human albumin was started and maintained for 7.5 h. At 0930 h, 3.5 h after starting the glucose tracer infusion, a two-stage hyperinsulinemic-euglycemic clamp procedure was started and continued for 6 h. During stage 1 of the clamp procedure (3.5–6.5 h), insulin was infused at a rate of 7 mU/m2 body surface area [BSA]/min (initiated with a priming dose of 28 mU/m2 BSA/min for 5 min and then 14 mU/m2 BSA/min for another 5 min) for 3 h. During stage 2 of the clamp procedure (6.5–9.5 h), the rate of insulin infusion was increased to 50 mU/m2 BSA/min (initiated with a priming dose of 200 mU/m2 BSA/min for 5 min and then 100 mU/m2 BSA/min for another 5 min). These insulin infusion rates were chosen to evaluate adipose tissue insulin sensitivity (low-dose insulin infusion to submaximally suppress lipolysis of adipose tissue triglycerides) and skeletal muscle insulin sensitivity (high-dose insulin infusion to stimulate muscle glucose uptake) (27). Euglycemia was maintained at a blood concentration of ∼5.6 mmol/l (100 mg/dl) by infusing 20% dextrose enriched to 2.5% with [6,6-2H2]glucose. The infusion rate of [6,6-2H2]glucose was reduced by 50% of basal during stage 1 and by 75% of basal during stage 2 of the clamp procedure to account for the expected decline in endogenous glucose production. The infusion rate of [2,2-2H2]palmitate was reduced by 50% of basal during stage 1 to account for the expected decline in lipolytic rate.

      Blood samples were obtained before the start of the tracer infusions to determine background plasma tracer-to-tracee ratios of glucose and palmitate and every 10 min during the final 30 min of the basal period and stages 1 and 2 of the clamp procedure to determine glucose, free fatty acid (FFA), and insulin concentrations and substrate kinetics. Blood samples were collected in chilled heparinized tubes to determine glucose and insulin concentration. All other blood samples were collected in chilled tubes containing EDTA. Samples were placed on ice, and plasma was separated by centrifugation within 30 min of collection. Plasma samples were stored at −80°C until final analyses were performed.

      Subcutaneous abdominal adipose tissue and muscle tissue (vastus lateralis portion of the quadriceps femoris) were obtained during the basal period to determine the expression and regulation of ER stress markers. Additional muscle tissue was obtained at ∼30 min after starting stage 2 of the clamp procedure to determine the levels and the extent of phosphorylation of JNK and elements of the insulin-signaling pathway. The biopsy sites were cleaned and draped, and the skin and underlying tissues were anesthetized with lidocaine. A small (∼0.5 cm) skin incision was made with a scalpel; adipose tissue was aspirated through a 4-mm liposuction cannula, and muscle tissue was obtained by using Tilley-Henkel forceps (Sontec Instruments, Centennial, CO). Muscle and adipose tissue samples were immediately rinsed in ice-cold saline, frozen in liquid nitrogen, and stored at −80°C until final analyses were performed.

      Intervention.

      After the baseline clamp procedure was completed, each subject was randomized to 4 weeks of oral treatment with either TUDCA (1,750 mg/day) or placebo. Both TUDCA and placebo were kindly provided by Bruschettini S.r.l (Genova, Italy). During the 4-week intervention period, subjects were seen every week to review any study-related issues, reinforce treatment compliance, check body weight, and assess vital signs. After 4 weeks of treatment, the body composition analyses and clamp procedure performed at baseline were repeated. Stage 2 of the clamp procedure was not completed in 2 of 10 subjects who received TUDCA treatment because of technical difficulties in obtaining blood samples. Treatment with drug or placebo was continued until all evaluations were finished.

      Sample processing and analyses.

      Plasma glucose concentration was determined by using an automated glucose analyzer (YSI 2300 STAT Plus; Yellow Springs Instruments, Yellow Springs, OH). Plasma FFA concentrations were quantified by using gas chromatography (HP 5890 Series II GC; Hewlett-Packard, Palo Alto, CA) (28). Plasma insulin concentration was measured by using a chemiluminescent immunometric assay (Immulite 1000; Diagnostic Products, Los Angeles, CA). Plasma C-reactive protein and interleukin-6 concentrations were measured by using commercially available high-sensitivity immunoassays (R&D Systems, Minneapolis, MN). Total and high–molecular weight adiponectin concentrations were determined by using fast protein liquid chromatography (AKTA FPLC system; GE Healthcare) and fluorescent Western blotting (LI-COR Biotechnology, Lincoln, NE), as previously described (29). Plasma glucose and palmitate tracer-to-tracee ratios were determined by using gas chromatography/mass spectroscopy (MSD 5973 system with capillary column; Hewlett-Packard), as previously described (30).

      To determine the activation of the insulin signaling and the JNK pathways in muscle and adipose tissue, we measured the site-specific phosphorylation of insulin receptor substrate (IRS)-1, Akt, and JNK. Tissue samples were cryopulverized, and the powdered tissue transferred to a tube containing cell lysis solution (Cell Signaling, Beverly, MA) and homogenized using a polytron (PowerGen 125; Fisher, Pittsburgh, PA). Homogenates were spun for 15 min at 2000g at 4°C to pellet insoluble material. The total protein concentration in the supernatant was measured (DC Protein Assay; Bio-Rad, Hercules, CA), and 25–50 μg protein were electrophoresed by SDS-PAGE and transferred to nitrocellulose membranes. Blots were probed with polyclonal antibodies directed against total Akt, AktSer473, total JNK, and JNKThr183/Tyr185 (all Cell Signaling, Beverly, MA) in Western analyses. To evaluate IRS-1 tyrosine phosphorylation, blots were concurrently probed with a rabbit polyclonal antibody against IRS-1 (gift of Mike Mueckler, Washington University School of Medicine, St. Louis, MO) and a mouse monoclonal phospho-tyrosine antibody (Cell Signaling, Danvers, MA) and then incubated with secondary antibodies tagged with red (anti-mouse) or green (anti-rabbit) fluorophores. Detection was performed with the LiCor dual-color system (Li-Cor Biosciences, Lincoln, NE). All band intensities were visualized and quantified by using the LiCor system and Odyssey 3.0 software, and phosphorylation levels were expressed as a function of total protein levels.

      Real-time quantitative PCR was performed as previously described to determine the mRNA expression of ER stress markers (glucose-regulated protein 78 [Grp78], spliced X-box binding protein-1 [XBP-1], and C/EBP homologous protein [CHOP]) in adipose tissue (22). Frozen adipose tissue samples were homogenized in TRIzol reagent (Invitrogen, Carlsbad, CA), and cDNA synthesis was performed by using 1 μg of sample RNA reverse transcribed with high-capacity cDNA archive system (Applied Biosystems, Foster City, CA); quantitative RT-PCR was performed by using SybrGreen reagent in an ABI 7300 real-time PCR system (Applied Biosystems). The mRNA expression of ER stress markers were normalized to 18S rRNA. The protein expression of homocysteine-induced ER protein (HERP) and the concentrations of eukaryotic elongation initiation factor 2α (eIF2α) phosphorylated at serine 52 and JNK phosphorylated at threonine 183 and tyrosine 185 in adipose tissue were determined by Western analyses using rabbit polyclonal anti–p-eIF2α (Invitrogen) and mouse monoclonal anti–p-JNK (Cell Signaling, Danvers, MA) antibodies as previously described (22). Anti-HERP antibody was a gift from Dr. Yasuhiko Hirabayashi of Tohoku University (Sendai Japan). The band intensities of p-(eIF2α), p-JNK, and HERP were normalized to actin.

      Calculations.

      Isotopic steady-state conditions were achieved during the final 30 min of the basal period and stages 1 and 2 of the clamp procedure, so the Steele equation for steady-state conditions was used to calculate glucose rate of appearance (Ra), glucose rate of disappearance (Rd), and palmitate Ra (31). The hepatic insulin sensitivity index was determined as the reciprocal of the hepatic insulin resistance index, which was calculated as the product of the basal hepatic glucose production rate (in μmol/min) and basal plasma insulin concentration (in μU/ml) (32). Adipose tissue insulin sensitivity was assessed by calculating the relative decrease from basal in palmitate Ra into plasma during stage 1 of the clamp procedure. Skeletal muscle insulin sensitivity was assessed by calculating the relative increase from basal in glucose Rd from plasma during stage 2 of the clamp procedure. The HOMA-IR score was calculated as the product of fasting plasma insulin (in mU/l) and glucose (in mmol/l) concentrations divided by 22.5 (24).

      Statistical analyses.

      Statistical analyses were performed by using SPSS for Windows (version 16.0; SPSS, Chicago, IL). Results are reported as means ± SD (normally distributed datasets) or medians and quartiles (skewed datasets). Two-way repeated-measures ANOVA was used to determine whether the changes in outcomes (normally distributed datasets) in response to either TUDCA or placebo treatment were different. Skewed data sets were evaluated by using nonparametric analyses. A P value ≤0.05 was considered statistically significant. Results are reported as means ± SD (normally distributed datasets) or medians and quartiles (skewed datasets).

      Based on data on glucose kinetics we obtained in obese subjects previously (33), we estimated that a sample size of 10 participants per group would allow us to detect a 25% difference in insulin sensitivity after treatment between groups, with an α value of 0.05 and power of 80% (β = 0.2). A difference in insulin sensitivity of this magnitude is clinically meaningful because it represents the lower end of the observed effect of current treatment strategies for insulin resistance, such as moderate weight loss (33) or pharmacotherapy (e.g., metformin and thiazolidinediones) (3441).

      RESULTS

      Subject characteristics, metabolic variables, and body composition.

      Subjects randomized to receive TUDCA and placebo were similar in age, sex, BMI, and body composition (Table 1). Body weight, total body fat, and fat distribution (intra-abdominal fat volume and IHTG content) did not change after 4 weeks of treatment with either TUDCA or placebo (Table 1). Baseline (before treatment) plasma concentrations of glucose, insulin, FFAs, triglycerides, aspartate aminotransferase, alanine aminotransferase, total adiponectin, high–molecular weight adiponectin, and markers of inflammation were not different between groups and did not change after either TUDCA or placebo treatment (Table 1). The HOMA-IR score did not change after placebo treatment but was ∼20% lower after TUDCA treatment (Table 1); however, the decrease in HOMA-IR after TUDCA therapy was not statistically significant.

      TABLE 1

      Subjects’ characteristics, metabolic variables, and body composition

      Insulin sensitivity assessed by using the hyperinsulinemic-euglycemic clamp technique.

      During the hyperinsulinemic-euglycemic clamp procedure, euglycemia was maintained at ∼100 mg/dl in all subjects (average plasma glucose concentration: 100.0 ± 2.1 mg/dl during stage 1 and 102.0 ± 2.7 mg/dl during stage 2 of the clamp procedure) and plasma insulin concentration increased to 29 ± 17 μU/ml during stage 1 and to 81 ± 19 μU/ml during stage 2.

      The hepatic insulin sensitivity index increased by ∼30% after TUDCA treatment but was not affected by placebo therapy (Fig. 1A). Glucose Rd increased by ∼150% (P < 0.001) from basal values during stage 2 of the clamp procedure in both the TUDCA and placebo groups before treatment. Compared with baseline (pretreatment) values, the increase in glucose Rd above basal values during stage 2 was 34 ± 23% greater after treatment with TUDCA (P < 0.05) but did not change after treatment with placebo (Fig. 1B). Insulin infusion suppressed palmitate Ra by ∼50% in both TUDCA and placebo groups before treatment, and this remained the same after treatment with either TUDCA or placebo (Fig. 1C).

      FIG. 1.
      FIG. 1.

      Liver, muscle, and adipose tissue insulin sensitivity before (□) and after (Embedded Image) 4 weeks of placebo or TUDCA treatment. A: Hepatic insulin sensitivity index. B: Glucose rate of disappearance (Rd); data represent only 8 of 10 subjects who received TUDCA treatment because of technical difficulties in obtaining blood samples in two subjects. C: Palmitate rate of appearance. Values are means ± SD. *Value significantly different from corresponding value before treatment, P < 0.05. †Main effect of insulin, P < 0.0001.

      Consistent with our kinetic data, TUDCA therapy increased insulin signaling in muscle but not adipose tissue. Compared with placebo treatment, TUDCA treatment increased insulin-stimulated phosphorylation of IRSTyr and AktSer473 in muscle (both P < 0.05) (Fig. 2). In contrast, TUDCA therapy did not alter insulin-stimulated phosphorylation of IRSTyr and AktSer473 in adipose tissue (data not shown). No difference in skeletal muscle phosphorylation of JNKThr183/Tyr185 was detected between subjects treated with placebo or TUDCA (Fig. 2).

      FIG. 2.
      FIG. 2.

      Effect of placebo (□) or TUDCA (Embedded Image) treatment on skeletal muscle IRSTyr, AktSer473, and JNKThr183/Tyr185 levels. Values are means ± SD and expressed relative to values before treatment, which were set to one for each person. *Value significantly different from corresponding placebo value, P < 0.05.

      ER stress markers in muscle and adipose tissue.

      Adipose tissue mRNA expression of spliced XBP-1, Grp78, and CHOP (Fig. 3A) and protein levels of HERP, eIF2αSer52, and JNKThr183/Tyr185 (Fig. 3B) were not affected by either placebo or TUDCA treatment. Spliced XBP-1, Grp78, and CHOP mRNA expression in skeletal muscle were very low (below the limit of reliable detection for spliced XBP-1) and did not change after TUDCA treatment (data not shown).

      FIG. 3.
      FIG. 3.

      Endoplasmic reticulum stress markers before (□) and after (Embedded Image) placebo or TUDCA therapy. A: Gene expression (relative to 18S rRNA). B: Protein content (relative to actin). Values are medians and quartiles.

      DISCUSSION

      Data from recent studies (15,18,22,23) conducted in both rodent models and human subjects have demonstrated that obesity is associated with liver and adipose tissue but not muscle ER stress. Treating obese mice with TUDCA, which acts as a chemical chaperone that reduces ER stress in liver and adipose tissue, results in improved insulin sensitivity in liver, muscle, and adipose tissue (18). However, the use of agents that can decrease ER stress to treat obesity-associated insulin resistance has not been evaluated in people. Accordingly, we conducted a randomized controlled trial to determine the effect of 4 weeks of treatment with TUDCA on multiorgan insulin sensitivity and factors involved in regulating insulin action in obese subjects with insulin resistance. Our data demonstrate that TUDCA therapy increases hepatic and muscle insulin action in vivo with a concomitant increase in the phosphorylation of components of the muscle insulin-signaling pathway. Moreover, the magnitude of the improvement in hepatic and muscle insulin sensitivity (both ∼30%) is similar to the insulin-sensitizing effects of currently available diabetes medications, such as thiazolinediones and metformin (3541). However, we did not detect an effect of TUDCA on adipose tissue insulin sensitivity or ER stress, making it unlikely that a reduction in adipocyte ER stress was responsible for the effect on insulin action in this trial. These data suggest that TUDCA therapy might provide a novel pharmacological approach for improving glucose homeostasis in insulin-resistant obese people.

      The precise cellular mechanisms responsible for the improvement in hepatic insulin sensitivity after TUDCA therapy are not clear. Data from studies conducted in human hepatocyte cultures have shown that TUDCA activates Akt and its downstream targets via a G-protein–coupled receptor–dependent mechanism (42,43). In addition, activation of the nuclear farnesoid X receptor (FXR) by bile acids or FXR agonists improves insulin sensitivity in vitro in cell systems and in vivo in animal models (44,45). However, TUDCA, unlike some other bile acids, is a relatively poor substrate for FXR (46). In animal models and cultured liver cells, TUDCA treatment can suppress ER stress and increase insulin signaling (18). Therefore, it is possible that TUDCA therapy affected hepatic ER stress in our subjects, but we did not obtain liver tissue in our subjects to directly evaluate this possibility.

      The mechanisms responsible for the TUDCA-induced improvement in skeletal muscle insulin sensitivity and insulin signaling in our subjects and in the previous study (18) conducted in mice are also not clear. In contrast with adipose tissue and liver, ER stress indicators are not increased in skeletal muscle from obese mice (15,18) or obese people (23), and TUDCA treatment did not affect muscle ER stress markers in our study. In addition, muscle does not express the FXR (46), which precludes the possibility of an FXR-mediated improvement in muscle insulin action. However, G-protein receptors are expressed ubiquitously, so some of the effects of TUDCA in muscle might be mediated by G-protein receptor activation of Akt.

      Although we found that TUDCA therapy improved hepatic and muscle insulin sensitivity, we did not find a significant effect of TUDCA therapy on HOMA-IR and many of the metabolic variables associated with insulin resistance, such as plasma glucose, insulin, and FFA concentrations. It is likely that these measures were not adequate to detect an effect of TUDCA, which required a more sensitive assessment of insulin action by using stable isotopically labeled tracers and the hyperinsulinenmic-euglycemic clamp procedure.

      Unlike data obtained from mouse models (18), we did not detect an effect of TUDCA therapy on adipose tissue insulin sensitivity or signaling or the expression of adipose tissue ER stress markers. Several factors might be responsible for the apparent difference observed after TUDCA therapy in mice and our study in human subjects. First, it is possible that the amount of TUDCA we gave our subjects, which is the maximum dose used to treat biliary disease, was insufficient to generate changes in adipose tissue ER stress; in the previous study, ∼30 times more TUDCA relative to body weight was given to mice than to our subjects. Second, TUDCA was given intraperitoneally in the mice but orally to our subjects. It is likely this difference in route of administration further limited the systemic availability of TUDCA in our subjects, because TUDCA is effectively metabolized by the liver and there is minimal splanchnic escape of bile acid conjugates into the systemic circulation (47). Finally, the expression of transporters responsible for TUDCA tissue uptake is very low in most extrahepatic tissues (48,49), so large plasma concentrations might be needed to achieve adequate tissue uptake to affect intracellular function. These pharmacokinetic factors raise the possibility that adipose tissue did not get sufficient exposure to orally administered TUDCA to affect ER stress in our subjects. Future studies with different dosing regimens are needed to address this issue.

      In summary, insulin resistance is involved in the pathogenesis of the key metabolic disorders associated with obesity (13,614). The results from the present study demonstrate that TUDCA therapy increases liver and muscle insulin sensitivity in obese, insulin-resistant subjects. Additional studies are needed to determine the specific cellular mechanisms responsible for this effect and to determine the therapeutic potential of this class of compounds for obese people with insulin resistance.

      ACKNOWLEDGMENTS

      This study was supported by National Institutes of Health Grants DK 37948, DK52539, DK 56341 (Nutrition Obesity Research Center), RR 00954 (Biomedical Mass Spectrometry Resource), UL1 RR024992 (Institute for Clinical and Translational Science), and T32 ES007155-24 (Environmental Health Training grant). This study also received support from the Nutricia Research Foundation (2009-26), Syndexa Pharmaceuticals, a mentor-based postdoctoral fellowship from the American Diabetes Association, and a Donald and Sue Pritzker Scholar award.

      G.S.H. is a shareholder and member of the scientific advisory board at Syndexa Pharmaceuticals. No other potential conflicts of interest relevant to this article were reported.

      M.K., B.M., G.S.H., and S.K. were involved in designing and conducting the infusion studies, processing the study samples, collecting data, performing the final data analyses, and writing the manuscript. B.S.M. was involved in conducting the infusion studies. M.F.G., L.Y., T.A.P., B.N.F., B.W.P., and J.D.H. were involved in sample processing and sample analyses.

      The authors thank Adewole Okunade, Freida Custodio, and Jennifer Shew for their technical assistance, Ken Schechtman for assistance with statistical analyses, Melisa Moore and the staff of the Clinical Research Unit for their help in performing the studies, and the study subjects for their participation.

      Footnotes

      • Clinical Trials reg. no. NCT00771901, clinicaltrials.gov.

      • 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.

      • Received March 2, 2010.
      • Accepted May 21, 2010.



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