The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes.

articles epidemiologyWe summed AS soda, coffee, and tea intakes to estimate AS beverage (ASB) consumption, and-among consumers-identified ASB consumption quartiles. Participants using AS sweeteners and/or cereals-but not ASBs-were included in ASB consumption quartile 1. Participants reporting no AS use were categorized "nonusers. "Dieting status and exercise frequency (2) were recorded at baseline and follow-up. In cohort 1 only, baseline 24-h dietary recalls were performed (2). In cohort 2 only, follow-up AS use (present or absent) was ascertained.Physical measurements and demographic data Standard anthropometric measurements were performed (2). A BMI <25 kg/m 2 was categorized normal weight (NW); ≥ 25 and <30 kg/m 2 , overweight (OW); and ≥ 30 kg/m 2 , obese (OB). The latter categories were combined as OW/OB (BMI ≥ 25 kg/m 2 ). Baseline education and occupation were recorded, and occupation-based Duncan socioeconomic index scores (range: 0-96) assigned. Of 3,682 follow-up participants, 3371 (91.6%) had complete data for all variables reported. statistical analysesIncidence of OW/OB (OW/OB inc ) was defined as the percent of baseline NW participants who had become OW/OB by follow-up. Incidence of obesity (OB inc ) was defined as the percent of baseline NWor-OW participants (BMI < 30 kg/m 2 ) who had become OB by follow-up. Change in BMI (ΔBMI) was calculated as BMI at follow-up minus BMI at baseline. Change in exercise frequency (Δexercise) was calculated as the number of exercise sessions per week at follow-up minus the number of sessions per week at baseline. Participants with Δexercise ≥1/week were categorized as "exercising more"; those ≤−1/ week, as "exercising less"; and all others, as "exercising same. " Excess BMI gains in AS users ("users") were calculated as ΔBMI among users minus ΔBMI among nonusers, divided by ΔBMI among nonusers.Means of continuous variables and percentages of categorical variables are presented by baseline AS consumption status. We used logistic regression to adjust odds ratios (ORs) for baseline BMI, as well as gender and ethnicity; baseline age, education, socioeconomic index, exercise frequency, and smoking status; interim change in exercise level; and interim smoking cessation ("demographic/behavioral covariates"), with ordinal categories of AS doses/day as a predictor variable. Analysis of covariance was used to assess associations between ASB consumption category and ΔBMI. In logistic regression and analysis of covariance models, linear trend was assessed by models using the ordinal category of ASB doses/ day as a continuous measure. All statistical calculations were performed using SAS version 9.1 (SAS Institute, Cary, NC).Analyses of ΔBMI-with adjustment for baseline BMI and demographic/behavioral covariates-were performed for the entire sample. Within cohort 2, they were repeated separately by baseline AS use status (present or absent), with additional adjustment for follow-up AS status. Within cohort 2, these analyses were also repeated among participants whose AS use st...

Genetic Analysis Workshop 18 (GAW18) focused on identification of genes and functional variants that influence complex phenotypes in human sequence data. Data for the workshop were donated by the T2D-GENES Consortium and included whole genome sequences for odd-numbered autosomes in 464 key individuals selected from 20 Mexican American families, a dense set of single-nucleotide polymorphisms in 959 individuals in these families, and longitudinal data on systolic and diastolic blood pressure measured at 1-4 examinations over a period of 20 years. Simulated phenotypes were generated based on the real sequence data and pedigree structures. In the design of the simulation model, gene expression measures from the San Antonio Family Heart Study (not distributed as part of the GAW18 data) were used to identify genes whose mRNA levels were correlated with blood pressure. Observed variants within these genes were designated as functional in the GAW18 simulation if they were nonsynonymous and predicted to have deleterious effects on protein function or if they were noncoding and associated with mRNA levels. Two simulated longitudinal phenotypes were modeled to have the same trait distributions as the real systolic and diastolic blood pressure data, with effects of age, sex, and medication use, including a genotype-medication interaction. For each phenotype, more than 1000 sequence variants in more than 200 genes present on the odd-numbered autosomes individually explained less than 0.01-2.78% of phenotypic variance. Cumulatively, variants in the most influential gene explained 7.79% of trait variance. An additional simulated phenotype, Q1, was designed to be correlated among family members but to not be associated with any sequence variants. Two hundred replicates of the phenotypes were simulated, with each including data for 849 individuals.

For more than a decade, pioneering animal studies conducted by investigators at Purdue University have provided evidence to support a central thesis: that the uncoupling of sweet taste and caloric intake by low-calorie sweeteners (LCS) can disrupt an animal's ability to predict the metabolic consequences of sweet taste, and thereby impair the animal's ability to respond appropriately to sweet-tasting foods. These investigators’ work has been replicated and extended internationally. There now exists a body of evidence, from a number of investigators, that animals chronically exposed to any of a range of LCSs – including saccharin, sucralose, acesulfame potassium, aspartame, or the combination of erythritol + aspartame – have exhibited one or more of the following conditions: increased food consumption, lower post-prandial thermogenesis, increased weight gain, greater percent body fat, decreased GLP-1 release during glucose tolerance testing, and significantly greater fasting glucose, glucose area under the curve during glucose tolerance testing, and hyperinsulinemia, compared with animals exposed to plain water or – in many cases – even to calorically-sweetened foods or liquids. Adverse impacts of LCS have appeared diminished in animals on dietary restriction, but were pronounced among males, animals genetically predisposed to obesity, and animals with diet-induced obesity. Impacts have been especially striking in animals on high-energy diets: diets high in fats and sugars, and diets which resemble a highly-processed ‘Western’ diet, including trans-fatty acids and monosodium glutamate. These studies have offered both support for, and biologically plausible mechanisms to explain, the results from a series of large-scale, long-term prospective observational studies conducted in humans, in which longitudinal increases in weight, abdominal adiposity, and incidence of overweight and obesity have been observed among study participants who reported using diet sodas and other LCS-sweetened beverages daily or more often at baseline. Furthermore, frequent use of diet beverages has been associated prospectively with increased long-term risk and/or hazard of a number of cardiometabolic conditions usually considered to be among the sequelae of obesity: hypertension, metabolic syndrome, diabetes, depression, kidney dysfunction, heart attack, stroke, and even cardiovascular and total mortality. Reverse causality does not appear to explain fully the increased risk observed across all of these studies, the majority of which have included key potential confounders as covariates. These have included body mass index or waist circumference at baseline; total caloric intake and specific macronutrient intake; physical activity; smoking; demographic and other relevant risk factors; and/or family history of disease. Whether non-LCS ingredients in diet beverages might have independently increased the weight gain and/or cardiometabolic risk observed among frequent consumers of LCS-sweetened beverages deserves further exploration. In the me...

BACKGROUND/OBJECTIVES Diet soda (DS) intake (DSI) has been associated with increased cardiometabolic risk, but its specific impact in older adults has not been addressed. Because central obesity increases cardiovascular risk, we examined the relationship between DSI and long-term waist circumference (WC) change (ΔWC) in the bi-ethnic San Antonio Longitudinal Study of Aging (SALSA). DESIGN Prospective cohort study. SETTING San Antonio, Texas, neighborhoods PARTICIPANTS SALSA examined 749 Mexican-American and European-American individuals ≥ 65 years old at baseline (BL: 1992-1996); 79.1% of survivors completed follow-up 1 (FU1) (2000-2001, n=474); 73.4%, FU2 (2001-2003, n=413); and 71.0%, FU3 (2003-2004, n=375). Participants completed a mean of 2.64 follow-up intervals, for 9.41 total follow-up years. MEASUREMENTS DSI, WC, height and weight were measured at outset and conclusion of each interval: BL-FU1, FU1-FU2, and FU2-FU3. RESULTS Adjusted for initial WC, demographics, physical activity, diabetes, and smoking, mean interval ΔWC (95% confidence interval) for all DS users was almost triple that among non-users: 2.11 (1.45-2.76) vs. 0.77 (0.29-1.23) cm, respectively (p < 0.001). For non-, occasional, and daily DS users, adjusted interval ΔWCs were 0.77 (0.29-1.23), 1.76 (0.96-2.57), and 3.04 (1.82-4.26) cm, respectively (p=0.002 for trend). This translates to ΔWCs of 0.80, 1.83, and 3.16 inches, respectively, for these groups, over the total SALSA follow-up. In sub-analyses stratified separately by key covariates, ΔWC point estimates were consistently higher among DS users. CONCLUSION In a striking dose-response relationship, increasing diet soda intake was associated with escalating abdominal obesity, a potential pathway for heightened cardiometabolic risk in this aging population.