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OBJECTIVE: Obesity is a key predictor of type 2 diabetes (T2D). However, metabolic complications are not solely due to increased BMI. We hypothesized that differences between genetically predicted BMI and observed BMI (BMI-diff) could reflect deviation from individual set point and may predict incident T2D. RESEARCH DESIGN AND METHODS: From the UK Biobank cohort, we selected participants of European ancestry without T2D (n = 332,154). The polygenic risk score for BMI was calculated via Bayesian regression and continuous shrinkage priors (PRS-CS). According to the BMI-diff, the 10-year risk of T2D was assessed using multivariable Cox proportional hazards model. Independent data from the Korean Genome and Epidemiology Study (KoGES) cohort from South Korea (n = 7,430) were used for replication. RESULTS: Participants from the UK Biobank were divided into train (n = 268,041) and test set (n = 115,119) to establish genetically predicted BMI. In the test set, the genetically predicted BMI explained 7.1% of the variance of BMI, and there were 3,599 T2D cases (3.1%) during a 10-year follow-up. Participants in the higher quintiles of BMI-diff (more obese than genetically predicted) had significantly higher risk of T2D than those in the lowest quintile after adjusting for observed BMI: the adjusted hazard ratio of the 1st quintile (vs. 5th quintile) was 1.61 (95% CI 1.26–2.05, P < 0.001). Results were consistent among individuals in the KoGES study. Moreover, higher BMI than predicted was associated with impaired insulin sensitivity. CONCLUSIONS: Having a higher BMI than genetically predicted is associated with an increased risk of T2D. These findings underscore the potential to reassess T2D risk based on individual levels of obesity using genetic thresholds for BMI. [ABSTRACT FROM AUTHOR]

Partitioned polygenic scores (pPS) have been developed to capture pathophysiologic processes underlying type 2 diabetes (T2D). We investigated the association of T2D pPS with diabetes-related traits and T2D incidence in the Diabetes Prevention Program. We generated five T2D pPS (β-cell, proinsulin, liver/lipid, obesity, lipodystrophy) in 2,647 participants randomized to intensive lifestyle, metformin, or placebo arms. Associations were tested with general linear models and Cox regression with adjustment for age, sex, and principal components. Sensitivity analyses included adjustment for BMI. Higher β-cell pPS was associated with lower insulinogenic index and corrected insulin response at 1-year follow-up with adjustment for baseline measures (effect per pPS SD −0.04, P = 9.6 × 10−7, and −8.45 μU/mg, P = 5.6 × 10−6, respectively) and with increased diabetes incidence with adjustment for BMI at nominal significance (hazard ratio 1.10 per SD, P = 0.035). The liver/lipid pPS was associated with reduced 1-year baseline-adjusted triglyceride levels (effect per SD −4.37, P = 0.001). There was no significant interaction between T2D pPS and randomized groups. The remaining pPS were associated with baseline measures only. We conclude that despite interventions for diabetes prevention, participants with a high genetic burden of the β-cell cluster pPS had worsening in measures of β-cell function. Article Highlights: Process-specific genetic scores (partitioned polygenic scores [pPS]) help explain clinical heterogeneity in type 2 diabetes, but whether they inform differential response to diabetes prevention strategies is unknown. In the Diabetes Prevention Program clinical trial, we examined pPS for associations with longitudinal glycemic measures and type 2 diabetes development. Higher β-cell pPS was associated with reduced baseline and even further reduced 1-year β-cell function despite diabetes prevention interventions. Diabetes prevention interventions may not optimally prevent β-cell function decline in people with genetic susceptibility for β-cell dysfunction, which may contribute to the heterogeneity seen in progression of diabetes development. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To identify genetic risk factors for incident cardiovascular disease (CVD) among people with type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: We conducted a multiancestry time-to-event genome-wide association study for incident CVD among people with T2D. We also tested 204 known coronary artery disease (CAD) variants for association with incident CVD. RESULTS: Among 49,230 participants with T2D, 8,956 had incident CVD events (event rate 18.2%). We identified three novel genetic loci for incident CVD: rs147138607 (near CACNA1E/ZNF648 , hazard ratio [HR] 1.23, P = 3.6 × 10−9), rs77142250 (near HS3ST1 , HR 1.89, P = 9.9 × 10−9), and rs335407 (near TFB1M/NOX3 , HR 1.25, P = 1.5 × 10−8). Among 204 known CAD loci, 5 were associated with incident CVD in T2D (multiple comparison–adjusted P < 0.00024, 0.05/204). A standardized polygenic score of these 204 variants was associated with incident CVD with HR 1.14 (P = 1.0 × 10−16). CONCLUSIONS: The data point to novel and known genomic regions associated with incident CVD among individuals with T2D. [ABSTRACT FROM AUTHOR]

Objectives: Experimental and genetic studies suggest that fibroblast growth factor 21 (FGF21) modulates macronutrient and alcohol preferences, but evidence of such regulation in humans remains scarce. To address this gap in translation, we aimed to map the relationships between plasma FGF21 levels, FGF21 genetic variation and habitual macronutrient intake in a large human population., Methods: We fine-mapped and performed colocalization of the FGF21 genetic region in GWAS summary statistics of plasma FGF21 levels and macronutrient intake. UK Biobank data were used to investigate the associations between FGF21 genetic variants, plasma FGF21 protein levels, and macronutrient intake (including alcohol) assessed with repeated 24-hour recalls. One- and two-sample mendelian randomization were performed to estimate the effects of plasma FGF21 on macronutrient intake., Results: We show that the main macronutrient-associated variant rs838133 and the FGF21 cis-pQTL rs838131, both in the FGF21 gene, are distinct genetic signals. Effect directions also suggest that the influence of FGF21 variation on macronutrient intake appear more complex than by direct mediation through plasma FGF21. Only when considering this complexity at FGF21, is plasma FGF21 estimated to reduce alcohol and increase protein and fat intake using mendelian randomization. Importantly, plasma FGF21 levels also appear markedly elevated by primarily high alcohol and low protein intake., Conclusions: These findings support the feedback diet-regulatory mechanism of FGF21 in humans, but highlights the need for mechanistic characterization of the complex FGF21 genetic region., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Niels Grarup reports a relationship with Novo Nordisk that includes: employment. Matthew P Gillum reports a relationship with Novo Nordisk that includes: employment. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier GmbH.. All rights reserved.)