Risk Factors and Etiology of Obesity and Type 2 Diabetes

National Institute Of Diabetes And Digestive And Kidney Diseases

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Abstract

Decreased insulin action, impaired insulin secretion, reduced insulin clearance and increased adiposity are important risk factors for development of type 2 diabetes (T2D) Greater insulin resistance and lower insulin secretion are risk factors for T2D t even in individuals with both normal fasting and two-hour glucose concentrations. Thus, we have investigated factors which may further explain the physiology of these phenotypes. We found that the greater anion gap, a marker of acid accumulation, was associated with insulin resistance as measured by the euglycemic-hyperinsulinemic clamp. While higher acid accumulation (greater anion gap) predicted T2D this was not independent of insulin resistance. Thus, relative greater acid accumulation which may reflect consumption of greater animal protein and/or renal acid handling may be directly etiologic in insulin resistance. This may occur via effects on interstitial pH where glucose disposal occurs. Measurement of insulin resistance and secretion requires lengthy time intensive procedures. Plasma metabolomics and proteomics measures can be used to create surrogate signatures for these more time-consuming measures. We have performed both measures in individuals with gold standard measures of insulin resistance. We have identified both metabolomic and proteomic signatures that correlate with clamp derived measures of insulin resistance and replicate in insulin resistance measures in other populations. Furthermore, these metabolomic and proteomic signatures both separately predict T2D in our studies and in other larger populations (CARDIA, UK BIOBANK). This indicates that a metabolomic or proteomic signature from a single fasting plasma sample can provide risk information equivalent to that of more time intensive testing. We will plan to investigate metabolomic and proteomic signatures of energy expenditure and weight gain. We will link these profiles with analyzed genome wide association data. There has been increased interest in insulin resistance as a cause of other metabolic diseases. We have found that insulin resistance measured prior to onset of diabetes predicts early signs of diabetes related kidney disease. Thus, insulin resistance independent of hyperglycemia may affect renal function. We have also found that greater hepatic insulin resistance predicts risk of gallstone disease. Thus, we have expanded the metabolic effect of this key risk factor for type 2 diabetes. Given the identified metabolic risks for gallbladder disease and its high prevalence in those also at risk for T2D, we examined the metabolic and genetic profile of those who developed gallbladder disease. Individuals who underwent previous cholecystectomy had lower respiratory quotients, higher lipid oxidation rates and higher energy expenditure during sleep. Plasma bile acid concentrations did not explain these differences. We did identify several genetic variants associated with gallbladder disease including in the fucosyltransferase 3 (FUT3) gene and in the ABCG5 and ABCG8 sterol transporter genes. With the increased interest in the mixed meal tolerance test (MMTT) as a marker of dietary response, we also investigate the reproducibility, determinants and how well the MMTT predicted diabetes and related endpoints. We found moderate reproducibility for total glucose and insulin area under the curve (AUC) measures, but poor when the incremental AUC was used. Measures of insulin resistance and insulin secretion were limited determinants of the glucose and insulin MMTT response. Glucose and insulin responses to the MMTT predicted development of type 2 diabetes (with similar strength to oral glucose tolerance tests), diabetic retinopathy and nephropathy. Because the optimal dosing of the MMTT is uncertain, we have started an outpatient study to compare metabolic responses to MMTT dosing based on fixed dose versus one adjusted for metabolic body size. The study is currently enrolling eligible participants. Participants undergo screening, an oral glucose tolerance test to rule out diabetes and are then are given a fixed or adjusted dose liquid meal in random order. Previous predictors of weight gain based on this study have included, higher respiratory quotient, higher insulin mediated glucose uptake, lower free T3, and relatively lower energy expenditure. Variability in energy expenditure is a mediator of weight change, and we have continued to evaluate factors related to metabolic rate. We had previously confirmed that lower energy expenditure relative to body size predicted weight and fat mass gain in a larger cohort with longer follow-up. Using resting energy expenditure measured at 5 and 10 years of age, we demonstrated that relatively lower resting energy expenditure at age 10 (but not at age 5) predicted greater increase in body mass index indicating an effect of metabolic rate on weight in late childhood. We have recently demonstrated that spontaneous physical activity (SPA) or “fidgeting” behavior as measured in our metabolic chambers declined from 1985 to 2005 indicating an effect of increasing sedentary lifestyle even on unprompted movement. There is also a seasonal effect on SPA; in the southwest, SPA declines during the summer compared to winter. Given that energy expenditure and substrate oxidation continue to play an important role in maintaining energy balance, we have continued to investigate factors which explain the inter-individual variance in these measurements. On a cellular level, in adipocytes we found that higher in vitro lipolysis is associated with higher whole-body lipid oxidation and less weight gain. We have also found that sphingolipid (which are cell membrane components important in cellular signaling) and endocannabinoid concentrations in skeletal muscle are associated with lower energy expenditure and weight gain. In mediation analysis, sphingomyelins’ effect on energy expenditure was mediated by the endocannabinoid anandamide. We demonstrated that a genetic variant in ceramide synthase 2 (CERS2), which catalyzes synthesis of very long acyl chain ceramides, a component of sphingomyelin is associated with higher sleeping energy expenditure and greater hepatic insulin resistance (as measured during the euglycemic-hyperinsulinemic clamp). Another variant near the gene cluster CELSR2-PRSC1-SORT1 gene cluster which is involved in lipoprotein metabolism was associated with low density lipoprotein (LDL) and lower resting metabolic rate. There are additional genetic factors that we have identified that underlie adiposity and its risk factors. Mutations in the melanocortin 4 receptor gene are associated with increased body mass index and lower 24-hour energy expenditure in humans. Individuals with MC4R mutations have accelerated weight gain in childhood but not in adulthood indicating a more potent effect of this mutation in early life. Furthermore, we found that presence of MC4R mutations predicted development of diabetes in childhood independent of body weight. The mechanism by which MC4R leads to hyperphagia and weight gain is not clear. One possible mediator is brain derived neurotrophic factor (BDNF) a downstream effector of MC4R signaling which has been implicated in childhood hyperphagia and weight gain. However, serum BDNF did not differ between individuals with and without MC4R mutations. Recently a more common single nucleotide polymorphism (SNP) in MC4R has been identified that is associated with increased BMI in Native Americans of southwestern heritage. This common SNP is near the promoter region and is also associated with lower energy expenditure and increased ad libitum food intake.