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Richa Saxena and colleagues report genome-wide association analyses of sleep disturbance traits in the UK Biobank cohort. They discover loci associated with insomnia symptoms and excessive daytime sleepiness and identify genetic correlations with several neuropsychiatric and metabolic traits. Chronic sleep disturbances, associated with cardiometabolic diseases, psychiatric disorders and all-cause mortality 1 , 2 , affect 25–30% of adults worldwide 3 . Although environmental factors contribute substantially to self-reported habitual sleep duration and disruption, these traits are heritable 4 , 5 , 6 , 7 , 8 , 9 and identification of the genes involved should improve understanding of sleep, mechanisms linking sleep to disease and development of new therapies. We report single- and multiple-trait genome-wide association analyses of self-reported sleep duration, insomnia symptoms and excessive daytime sleepiness in the UK Biobank ( n = 112,586). We discover loci associated with insomnia symptoms (near MEIS1 , TMEM132E , CYCL1 and TGFBI in females and WDR27 in males), excessive daytime sleepiness (near AR – OPHN1 ) and a composite sleep trait (near PATJ ( INADL ) and HCRTR2 ) and replicate a locus associated with sleep duration (at PAX8 ). We also observe genetic correlation between longer sleep duration and schizophrenia risk ( r g = 0.29, P = 1.90 × 10 −13 ) and between increased levels of excessive daytime sleepiness and increased measures for adiposity traits (body mass index (BMI): r g = 0.20, P = 3.12 × 10 −9 ; waist circumference: r g = 0.20, P = 2.12 × 10 −7 ).

Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10(-8)), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution. Genome-wide association studies (GWAS) have become a key tool to discover genetic markers for complex traits; however, environmental factors that interact with genes are rarely considered. Here, the authors conduct a GWAS of obesity traits, and find that smoking may alter genetic susceptibilities.

DNA sequencing identifies common and rare genetic variants for association studies, but studies typically focus on variants in nuclear DNA and ignore the mitochondrial genome. In fact, analyzing variants in mitochondrial DNA (mtDNA) sequences presents special problems, which we resolve here with a general solution for the analysis of mtDNA in next-generation sequencing studies. The new program package comprises 1) an algorithm designed to identify mtDNA variants (i.e., homoplasmies and heteroplasmies), incorporating sequencing error rates at each base in a likelihood calculation and allowing allele fractions at a variant site to differ across individuals; and 2) an estimation of mtDNA copy number in a cell directly from whole-genome sequencing data. We also apply the methods to DNA sequence from lymphocytes of ~2,000 SardiNIA Project participants. As expected, mothers and offspring share all homoplasmies but a lesser proportion of heteroplasmies. Both homoplasmies and heteroplasmies show 5-fold higher transition/transversion ratios than variants in nuclear DNA. Also, heteroplasmy increases with age, though on average only ~1 heteroplasmy reaches the 4% level between ages 20 and 90. In addition, we find that mtDNA copy number averages ~110 copies/lymphocyte and is ~54% heritable, implying substantial genetic regulation of the level of mtDNA. Copy numbers also decrease modestly but significantly with age, and females on average have significantly more copies than males. The mtDNA copy numbers are significantly associated with waist circumference (p-value = 0.0031) and waist-hip ratio (p-value = 2.4×10-5), but not with body mass index, indicating an association with central fat distribution. To our knowledge, this is the largest population analysis to date of mtDNA dynamics, revealing the age-imposed increase in heteroplasmy, the relatively high heritability of copy number, and the association of copy number with metabolic traits.

Aims/hypothesis We previously reported that obese individuals with the metabolic syndrome (at risk), compared with obese individuals without the metabolic syndrome (healthy obese), have elevated serum AGEs that strongly correlate with insulin resistance, oxidative stress and inflammation. We hypothesised that a diet low in AGEs (L-AGE) would improve components of the metabolic syndrome in obese individuals, confirming high AGEs as a new risk factor for the metabolic syndrome. Methods A randomised 1 year trial was conducted in obese individuals with the metabolic syndrome in two parallel groups: L-AGE diet vs a regular diet, habitually high in AGEs (Reg-AGE). Participants were allocated to each group by randomisation using random permuted blocks. At baseline and at the end of the trial, we obtained anthropometric variables, blood and urine samples, and performed OGTTs and MRI measurements of visceral and subcutaneous abdominal tissue and carotid artery. Only investigators involved in laboratory determinations were blinded to dietary assignment. Effects on insulin resistance (HOMA-IR) were the primary outcome. Results Sixty-one individuals were randomised to a Reg-AGE diet and 77 to an L-AGE diet; the data of 49 and 51, respectively, were analysed at the study end in 2014. The L-AGE diet markedly improved insulin resistance; modestly decreased body weight; lowered AGEs, oxidative stress and inflammation; and enhanced the protective factors sirtuin 1, AGE receptor 1 and glyoxalase I. The Reg-AGE diet raised AGEs and markers of insulin resistance, oxidative stress and inflammation. There were no effects on MRI-assessed measurements. No side effects from the intervention were identified. HOMA-IR came down from 3.1 ± 1.8 to 1.9 ± 1.3 ( p  < 0.001) in the L-AGE group, while it increased from 2.9 ± 1.2 to 3.6 ± 1.7 ( p  < 0.002) in the Reg-AGE group. Conclusions / interpretation L-AGE ameliorates insulin resistance in obese people with the metabolic syndrome, and may reduce the risk of type 2 diabetes, without necessitating a major reduction in adiposity. Elevated serum AGEs may be used to diagnose and treat ‘at-risk’ obesity. Trial registration ClinicalTrials.gov NCT01363141 Funding The study was funded by the National Institute of Diabetes and Digestive and Kidney Diseases (DK091231)

Understanding of the genetic basis of type 2 diabetes (T2D) has progressed rapidly, but the interactions between common genetic variants and lifestyle risk factors have not been systematically investigated in studies with adequate statistical power. Therefore, we aimed to quantify the combined effects of genetic and lifestyle factors on risk of T2D in order to inform strategies for prevention. The InterAct study includes 12,403 incident T2D cases and a representative sub-cohort of 16,154 individuals from a cohort of 340,234 European participants with 3.99 million person-years of follow-up. We studied the combined effects of an additive genetic T2D risk score and modifiable and non-modifiable risk factors using Prentice-weighted Cox regression and random effects meta-analysis methods. The effect of the genetic score was significantly greater in younger individuals (p for interaction  = 1.20×10-4). Relative genetic risk (per standard deviation [4.4 risk alleles]) was also larger in participants who were leaner, both in terms of body mass index (p for interaction  = 1.50×10-3) and waist circumference (p for interaction  = 7.49×10-9). Examination of absolute risks by strata showed the importance of obesity for T2D risk. The 10-y cumulative incidence of T2D rose from 0.25% to 0.89% across extreme quartiles of the genetic score in normal weight individuals, compared to 4.22% to 7.99% in obese individuals. We detected no significant interactions between the genetic score and sex, diabetes family history, physical activity, or dietary habits assessed by a Mediterranean diet score. The relative effect of a T2D genetic risk score is greater in younger and leaner participants. However, this sub-group is at low absolute risk and would not be a logical target for preventive interventions. The high absolute risk associated with obesity at any level of genetic risk highlights the importance of universal rather than targeted approaches to lifestyle intervention.

Abstract Context Atrial fibrillation (AF), cardiac arrhythmias, and related risk factors are common in patients with Cushing’s syndrome, or clinical chronic hypercortisolism. While hypercortisolism may be associated with AF, this association has not yet been ascertained causally. Objective To determine whether plasma cortisol is causally associated with AF using a 2-sample Mendelian randomization (MR) design. Methods Three genetic variants in the SERPINA1/SERPINA6 locus and functionally associated with plasma cortisol were identified in the CORtisol NETwork consortium (12 597 participants). Summary-level genome-wide association study (GWAS) data for the associations between the cortisol-associated variants and AF were obtained from a GWAS meta-analysis of 6 studies (60 620 AF cases and 970 216 noncases) and the FinnGen consortium (17 325 AF cases and 97 214 noncases). The fixed-effects inverse-variance weighted approach accounting for genetic correlations between variants was used for analysis. Multivariable MR analyses were conducted to assess potential mediating effects of systolic blood pressure (SBP) and waist circumference (WC). Summary-level GWAS data for SBP and WC were obtained respectively from the International Consortium of Blood Pressure (757 601 participants) and the Genetic Investigation of ANthropometric Traits consortium (232 101 participants). Results One standard deviation increase in genetically predicted plasma cortisol was associated with greater risk of AF (odds ratio [OR] 1.20, 95% CI 1.06-1.35). The association attenuated when adjusting for genetically predicted SBP and WC (OR 0.99, 95% CI 0.72-1.38). Conclusion Evidence derived from the MR study suggests a positive association between plasma cortisol and risk of AF, likely mediated through SBP and WC.

Objectives Central obesity poses significant health risks because it increases susceptibility to multiple chronic diseases. Epigenetic features such as DNA methylation may be associated with specific obesity traits, which could help us understand how genetic and environmental factors interact to influence the development of obesity. This study aims to identify DNA methylation sites associated with the waist circumference (WC) in Northern Han Chinese population, and to elucidate potential causal relationships. Methods A total of 59 pairs of WC discordant monozygotic twins (ΔWC >0) were selected from the Qingdao Twin Registry in China. Generalized estimated equation model was employed to estimate the methylation levels of CpG sites on WC. Causal relationships between methylation and WC were assessed through the examination of family confounding factors using FAmiliaL CONfounding (ICE FALCON). Additionally, the findings of the epigenome-wide analysis were corroborated in the validation stage. Results We identified 26 CpG sites with differential methylation reached false discovery rate (FDR) < 0.05 and 22 differentially methylated regions (slk-corrected p  < 0.05) strongly linked to WC. These findings provided annotations for 26 genes, with notable emphasis on MMP17 , ITGA11 , COL23A1 , TFPI , A2ML1-AS1 , MRGPRE , C2orf82 , and NINJ2 . ICE FALCON analysis indicated the DNA methylation of ITGA11 and TFPI had a causal effect on WC and vice versa ( p  < 0.05). Subsequent validation analysis successfully replicated 10 ( p  < 0.05) out of the 26 identified sites. Conclusions Our research has ascertained an association between specific epigenetic variations and WC in the Northern Han Chinese population. These DNA methylation features can offer fresh insights into the epigenetic regulation of obesity and WC as well as hints to plausible biological mechanisms.

We analyzed the contribution of genetic factors on the association between puberty timing and body mass index (BMI) using longitudinal data and two approaches: (i) genetic twin design and (ii) polygenic scores (PGS) of obesity indices. Our data were derived from Finnish cohorts: 9080 twins had information on puberty timing and BMI and 2468 twins also had genetic data. Early puberty timing was moderately associated with higher BMI in childhood in both boys and girls; in adulthood these correlations were weaker and largely disappeared after adjusting for childhood BMI. The largest proportion of these correlations was attributable to genetic factors. The higher PGSs of BMI and waist circumference were associated with earlier timing of puberty in girls, whereas weaker associations were found in boys. Early puberty is not an independent risk factor for adult obesity but rather reflects the association between puberty timing and childhood BMI contributed by genetic predisposition.

Obesity is a worldwide health problem that is closely linked to many metabolic disorders. Regular physical exercise has been found to attenuate the genetic predisposition to obesity. However, it remains unknown what kinds of exercise can modify the genetic risk of obesity. This study included 18,424 unrelated Han Chinese adults aged 30-70 years who participated in the Taiwan Biobank (TWB). A total of 5 obesity measures were investigated here, including body mass index (BMI), body fat percentage (BFP), waist circumference (WC), hip circumference (HC), and waist-to-hip ratio (WHR). Because there have been no large genome-wide association studies on obesity for Han Chinese, we used the TWB internal weights to construct genetic risk scores (GRSs) for each obesity measure, and then test the significance of GRS-by-exercise interactions. The significance level throughout this work was set at 0.05/550 = 9.1x10-5 because a total of 550 tests were performed. Performing regular exercise was found to attenuate the genetic effects on 4 obesity measures, including BMI, BFP, WC, and HC. Among the 18 kinds of self-reported regular exercise, 6 mitigated the genetic effects on at least one obesity measure. Regular jogging blunted the genetic effects on BMI, BFP, and HC. Mountain climbing, walking, exercise walking, international standard dancing, and a longer practice of yoga also attenuated the genetic effects on BMI. Exercises such as cycling, stretching exercise, swimming, dance dance revolution, and qigong were not found to modify the genetic effects on any obesity measure. Across all 5 obesity measures, regular jogging consistently presented the most significant interactions with GRSs. Our findings show that the genetic effects on obesity measures can be decreased to various extents by performing different kinds of exercise. The benefits of regular physical exercise are more impactful in subjects who are more predisposed to obesity.