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 the heritability of this disease. Here, 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 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the 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 the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.

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Excessive alcohol consumption is a major public health problem worldwide. Although drinking habits are known to be inherited, few genes have been identified that are robustly linked to alcohol drinking. We conducted a genome-wide association metaanalysis and replication study among >105,000 individuals of European ancestry and identified β-Klotho (KLB) as a locus associated with alcohol consumption (rs11940694; P = 9.2 × 10⁻¹²). β-Klotho is an obligate coreceptor for the hormone FGF21, which is secreted from the liver and implicated in macronutrient preference in humans. We show that brain-specific β-Klotho KO mice have an increased alcohol preference and that FGF21 inhibits alcohol drinking by acting on the brain. These data suggest that a liver–brain endocrine axis may play an important role in the regulation of alcohol drinking behavior and provide a unique pharmacologic target for reducing alcohol consumption. Significance Alcohol is a widely consumed drug in western societies that can lead to addiction. A small shift in consumption can have dramatic consequences on public health. We performed the largest genome-wide association metaanalysis and replication study to date (>105,000 individuals) and identified a genetic basis for alcohol consumption during nonaddictive drinking. We found that a locus in the gene encoding β-Klotho is associated with alcohol consumption. β-Klotho is an essential receptor component for the endocrine FGFs, FGF19 and FGF21. Using mouse models and pharmacologic administration of FGF21, we show that β-Klotho in the brain controls alcohol drinking. These findings reveal a mechanism regulating alcohol consumption in humans that may be pharmacologically tractable for reducing alcohol intake.

The present study evaluated the ability of the visceral adiposity index (VAI), the lipid accumulation product (LAP), and product of triglycerides and glucose (TyG), three novel, insulin resistance-related markers, to discriminate prediabetes/diabetes in the general German population. Altogether 2,045 Germans (31–72 years, 53.3% women) without known diabetes and a history of Myocardial Infarction (MI)/stroke from the Cooperative Health Research in the Region of Augsburg (KORA) F4 Study were eligible. The discriminatory accuracy of the markers for oral glucose tolerance test (OGTT)-defined prediabetes/diabetes according to the American Diabetes Association (ADA) criteria was assessed by the area under the receiver operating characteristic (ROC) curve (AUC). The Youden Index (YI) was used to determine optimal cut-off values, and a non-parametric ROC regression was used to examine whether the discriminatory accuracy varied by sex and age. 365 men (38.2%) and 257 women (23.6%) were newly diagnosed with prediabetes/diabetes. AUCs for TyG, LAP and VAI were 0.762 (95% CI 0.740–0.784), 0.743 (95% CI 0.720–0.765), and 0.687 (95% CI 0.662–0.712), respectively. The optimal cut-off values for the LAP and TyG were 56.70 and 8.75 in men, and 30.40 and 8.53 in women. In conclusion, TyG and LAP provide good discrimination of persons with prediabetes/diabetes.

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery. Decline in daily physical activity is thought to be a key contributor to the global obesity epidemic. However, the impact of sedentariness on adiposity may be in part determined by a person’s genetic constitution. The specific genetic variants that are sensitive to physical activity and regulate adiposity remain largely unknown. Here, we aimed to identify genetic variants whose effects on adiposity are modified by physical activity by examining ~2.5 million genetic variants in up to 200,452 individuals. We also tested whether adjusting for physical activity as a covariate could lead to the identification of novel adiposity variants. We find robust evidence of interaction with physical activity for the strongest known obesity risk-locus in the FTO gene, of which the body mass index-increasing effect is attenuated by ~30% in physically active individuals compared to inactive individuals. Our analyses indicate that other similar gene-physical activity interactions may exist, but better measurement of physical activity, larger sample sizes, and/or improved analytical methods will be required to identify them. Adjusting for physical activity, we identify 11 novel adiposity variants, suggesting that accounting for physical activity or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.