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Obesity is a major risk factor for metabolic and cardiovascular disease in adults. The Framingham Heart Study was established to follow the development of cardiovascular disease (CVD) over a long period of time and to identify major risk factors for premature death. The study was one of the first to show that obesity is a major risk factor for CVD in adults.

Introduction: Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes.

Methods: A two-stage genome-wide meta-analysis of low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglyceride (TG) levels was performed while accounting for gene-educational attainment interactions in up to 226,315 individuals from five population groups. We considered two educational attainment variables: “Some College” (yes/no, for any education beyond high school) and “Graduated College” (yes/no, for completing a 4-year college degree). Genome-wide significant (p < 5 × 10−8) and suggestive (p < 1 × 10−6) variants were identified in Stage 1 (in up to 108,784 individuals) through genome-wide analysis, and those variants were followed up in Stage 2 studies (in up to 117,531 individuals).

Results: In combined analysis of Stages 1 and 2, we identified 18 novel lipid loci (nine for LDL, seven for HDL, and two for TG) by two degree-of-freedom (2 DF) joint tests of main and interaction effects. Four loci showed significant interaction with educational attainment. Two loci were significant only in cross-population analyses. Several loci include genes with known or suggested roles in adipose (FOXP1, MBOAT4, SKP2, STIM1, STX4), brain (BRI3, FILIP1, FOXP1, LINC00290, LMTK2, MBOAT4, MYO6, SENP6, SRGAP3, STIM1, TMEM167A, TMEM30A), and liver (BRI3, FOXP1) biology, highlighting the potential importance of brain-adipose-liver communication in the regulation of lipid metabolism. An investigation of the potential druggability of genes in identified loci resulted in five gene targets shown to interact with drugs approved by the Food and Drug Administration, including genes with roles in adipose and brain tissue.

Discussion: Genome-wide interaction analysis of educational attainment identified novel lipid loci not previously detected by analyses limited to main genetic effects.

Aims/hypothesis: Islet autoimmunity may progress to adult-onset diabetes. We investigated whether circulating odd-chain fatty acids (OCFA) 15:0 and 17:0, which are inversely associated with type 2 diabetes, interact with autoantibodies against GAD65 (GAD65Ab) on the incidence of adult-onset diabetes.

Methods: We used the European EPIC-InterAct case–cohort study including 11,124 incident adult-onset diabetes cases and a subcohort of 14,866 randomly selected individuals. Adjusted Prentice-weighted Cox regression estimated HRs and 95% CIs of diabetes in relation to 1 SD lower plasma phospholipid 15:0 and/or 17:0 concentrations or their main contributor, dairy intake, among GAD65Ab-negative and -positive individuals. Interactions between tertiles of OCFA and GAD65Ab status were estimated by proportion attributable to interaction (AP).

Results: Low concentrations of OCFA, particularly 17:0, were associated with a higher incidence of adult-onset diabetes in both GAD65Ab-negative (HR 1.55 [95% CI 1.48, 1.64]) and GAD65Ab-positive (HR 1.69 [95% CI 1.34, 2.13]) individuals. The combination of low 17:0 and high GAD65Ab positivity vs high 17:0 and GAD65Ab negativity conferred an HR of 7.51 (95% CI 4.83, 11.69), with evidence of additive interaction (AP 0.25 [95% CI 0.05, 0.45]). Low dairy intake was not associated with diabetes incidence in either GAD65Ab-negative (HR 0.98 [95% CI 0.94, 1.02]) or GAD65Ab-positive individuals (HR 0.97 [95% CI 0.79, 1.18]).

Conclusions/interpretation: Low plasma phospholipid 17:0 concentrations may promote the progression from GAD65Ab positivity to adult-onset diabetes. Graphical Abstract: [Figure not available: see fulltext.]

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40–50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10–20% (14–24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

Assessing the causal effects of individual dietary macronutrients and cardiometabolic disease is challenging owing to the complexity to distinguish direct effects from those mediated or confounded by other factors. To estimate these effects, intake of protein, carbohydrate, sugar, fat, and its subtypes were obtained using food frequency data derived from a Swedish population-based cohort (n~60,000). Data on clinical outcomes (i.e., type 2 diabetes (T2D) and cardiovascular disease (CVD) incidence) were obtained by linking health registry data. We assessed the magnitude of direct and mediated effects of diet, adiposity and physical activity on T2D and CVD using structural equation modelling (SEM). To strengthen causal inference, we used Mendelian randomization (MR) to model macronutrient intake exposures against clinical outcomes. We identified likely causal effects of genetically predicted carbohydrate intake (including sugar intake) and T2D, independent of adiposity and physical activity. Pairwise, serial-and parallel-mediational configurations yielded similar results. In the integrative genomic analyses, the candidate causal variant localized to the established type 2 diabetes gene TCF7L2. These findings may be informative when considering which dietary modifications included in nutritional guidelines are most likely to elicit health-promoting effects.

The present study assessed the temporal associations of ~ 300 lifestyle exposures with nine cardiometabolic traits to identify exposures/exposure groups that might inform lifestyle interventions for the reduction of cardiometabolic disease risk. The analyses were undertaken in a longitudinal sample comprising > 31,000 adults living in northern Sweden. Linear mixed models were used to assess the average associations of lifestyle exposures and linear regression models were used to test associations with 10-year change in the cardiometabolic traits. ‘Physical activity’ and ‘General Health’ were the exposure categories containing the highest number of ‘tentative signals’ in analyses assessing the average association of lifestyle variables, while ‘Tobacco use’ was the top category for the 10-year change association analyses. Eleven modifiable variables showed a consistent average association among the majority of cardiometabolic traits. These variables belonged to the domains: (i) Smoking, (ii) Beverage (filtered coffee), (iii) physical activity, (iv) alcohol intake, and (v) specific variables related to Nordic lifestyle (hunting/fishing during leisure time and boiled coffee consumption). We used an agnostic, data-driven approach to assess a wide range of established and novel risk factors for cardiometabolic disease. Our findings highlight key variables, along with their respective effect estimates, that might be prioritised for subsequent prediction models and lifestyle interventions.

People appear to vary in their susceptibility to lifestyle risk factors for cardiometabolic disease; determining a priori who is most sensitive may help optimize the timing, design, and delivery of preventative interventions. We aimed to ascertain a person’s degree of resilience or sensitivity to adverse lifestyle exposures and determine whether these classifications help predict cardiometabolic disease later in life; we pooled data from two population-based Swedish prospective cohort studies (n = 53,507), and we contrasted an individual’s cardiometabolic biomarker profile with the profile predicted for them given their lifestyle exposure characteristics using a quantile random forest approach. People who were classed as ‘sensitive’ to hypertension- and dyslipidemia-related lifestyle exposures were at higher risk of developing cardiovascular disease (CVD, hazards ratio 1.6 (95% CI: 1.3, 1.91)), compared with the general population. No differences were observed for type 2 diabetes (T2D) risk. Here, we report a novel approach to identify individuals who are especially sensitive to adverse lifestyle exposures and who are at higher risk of subsequent cardiovascular events. Early preventive interventions may be needed in this subgroup.

Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, “Some College” (yes/no) and “Graduated College” (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P < 5 × 10-8). Two novel loci were identified based on the 1DF test of interaction with educational attainment, while the remaining 16 loci were identified through the 2DF joint test of genetic and interaction effects. Ten novel loci were identified in individuals of African ancestry. Several novel loci show strong biological plausibility since they involve physiologic systems implicated in BP regulation. They include genes involved in the central nervous system-adrenal signaling axis (ZDHHC17, CADPS, PIK3C2G), vascular structure and function (GNB3, CDON), and renal function (HAS2 and HAS2-AS1, SLIT3). Collectively, these findings suggest a role of educational attainment or SES in further dissection of the genetic architecture of BP.

Context: Pancreatic beta-cell glucose sensitivity is the slope of the plasma glucose-insulin secretion relationship and is a key predictor of deteriorating glucose tolerance and development of type 2 diabetes. However, there are no large-scale studies looking at the genetic determinants of beta-cell glucose sensitivity.

Objective: To understand the genetic determinants of pancreatic beta-cell glucose sensitivity using genome-wide meta-analysis and candidate gene studies.

Design: We performed a genome-wide meta-analysis for beta-cell glucose sensitivity in subjects with type 2 diabetes and nondiabetic subjects from 6 independent cohorts (n = 5706). Beta-cell glucose sensitivity was calculated from mixed meal and oral glucose tolerance tests, and its associations between known glycemia-related single nucleotide polymorphisms (SNPs) and genome-wide association study (GWAS) SNPs were estimated using linear regression models.

Results: Beta-cell glucose sensitivity was moderately heritable (h2 ranged from 34% to 55%) using SNP and family-based analyses. GWAS meta-analysis identified multiple correlated SNPs in the CDKAL1 gene and GIPR-QPCTL gene loci that reached genome-wide significance, with SNP rs2238691 in GIPR-QPCTL (P value = 2.64 × 10−9) and rs9368219 in the CDKAL1 (P value = 3.15 × 10−9) showing the strongest association with beta-cell glucose sensitivity. These loci surpassed genome-wide significance when the GWAS meta-analysis was repeated after exclusion of the diabetic subjects. After correction for multiple testing, glycemia-associated SNPs in or near the HHEX and IGF2B2 loci were also associated with beta-cell glucose sensitivity.

Conclusion: We show that, variation at the GIPR-QPCTL and CDKAL1 loci are key determinants of pancreatic beta-cell glucose sensitivity.

Aims: Brisk walking and a greater muscle strength have been associated with a longer life; whether these associations are influenced by other lifestyle behaviours, however, is less well known.

Methods: Information on usual walking pace (self-defined as slow, steady/average, or brisk), dynamometer-assessed handgrip strength, lifestyle behaviours (physical activity, TV viewing, diet, alcohol intake, sleep and smoking) and body mass index was collected at baseline in 450,888 UK Biobank study participants. We estimated 10-year standardised survival for individual and combined lifestyle behaviours and body mass index across levels of walking pace and handgrip strength.

Results: Over a median follow-up of 7.0 years, 3808 (1.6%) deaths in women and 6783 (3.2%) in men occurred. Brisk walkers had a survival advantage over slow walkers, irrespective of the degree of engagement in other lifestyle behaviours, except for smoking. Estimated 10-year survival was higher in brisk walkers who otherwise engaged in an unhealthy lifestyle compared to slow walkers who engaged in an otherwise healthy lifestyle: 97.1% (95% confidence interval: 96.9–97.3) vs 95.0% (94.6–95.4) in women; 94.8% (94.7–95.0) vs 93.7% (93.3–94.2) in men. Body mass index modified the association between walking pace and survival in men, with the largest survival benefits of brisk walking observed in underweight participants. Compared to walking pace, for handgrip strength there was more overlap in 10-year survival across lifestyle behaviours.

Conclusion: Except for smoking, brisk walkers with an otherwise unhealthy lifestyle have a lower mortality risk than slow walkers with an otherwise healthy lifestyle.