Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, we conducted genome-wide association meta-analyses of waist and hip circumference-related traits in up to 224,459 individuals. We identified 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (WHRadjBMI) and an additional 19 loci newly associated with related waist and hip circumference measures (P<5×10−8). Twenty of the 49 WHRadjBMI loci showed significant sexual dimorphism, 19 of which displayed a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation, and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.

SummaryOverweight and obesity affect ~1.5 billion people worldwide, and are major risk factors for type-2 diabetes (T2D), cardiovascular disease and related metabolic and inflammatory disturbances.1,2 Although the mechanisms linking adiposity to its clinical sequelae are poorly understood, recent studies suggest that adiposity may influence DNA methylation,3–6 a key regulator of gene expression and molecular phenotype.7 Here we use epigenome-wide association to show that body mass index (BMI, a key measure of adiposity) is associated with widespread changes in DNA methylation (187 genetic loci at P<1x10-7, range P=9.2x10-8 to 6.0x10-46; N=10,261 samples). Genetic association analyses demonstrate that the alterations in DNA methylation are predominantly the consequence of adiposity, rather than the cause. We find the methylation loci are enriched for functional genomic features in multiple tissues (P<0.05), and show that sentinel methylation markers identify gene expression signatures at 38 loci (P<9.0x10-6, range P=5.5x10-6 to 6.1x10-35, N=1,785 samples). The methylation loci identified highlight genes involved in lipid and lipoprotein metabolism, substrate transport, and inflammatory pathways. Finally, we show that the disturbances in DNA methylation predict future type-2 diabetes (relative risk per 1SD increase in Methylation Risk Score: 2.3 [2.07-2.56]; P=1.1x10-54). Our results provide new insights into the biologic pathways influenced by adiposity, and may enable development of new strategies for prediction and prevention of type-2 diabetes and other adverse clinical consequences of obesity.

Retrotransposable elements (RTEs) are deleterious at multiple levels, and failure of host surveillance systems can thus have negative consequences. However, the contribution of RTE activity to aging and age-associated diseases is not known. Here we show that during cellular senescence LINE-1 elements (L1s) become transcriptionally derepressed and activate a type-I interferon (IFN-I) response. The IFN-I response is a novel phenotype of late senescence and contributes to the maintenance of the senescence associated secretory phenotype (SASP). The IFN-I response is triggered by cytoplasmic L1 cDNA, and is antagonized by nucleoside reverse transcriptase inhibitors (NRTIs) that inhibit the L1 reverse transcriptase (RT). Treatment of aged mice with the NRTI lamivudine downregulated IFN-I activation and age-associated inflammation in several tissues. We propose that RTE activation is an important component of sterile inflammation that is a hallmark of aging, and that L1 RT is a relevant target for the treatment of age-associated disorders.

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Longer human lives have led to a global burden of late-life disease. However, some older people experience little ill health, a trait that should be extended to the general population. Interventions into lifestyle, including increased exercise and reduction in food intake and obesity, can help to maintain healthspan. Altered gut microbiota, removal of senescent cells, blood factors obtained from young individuals and drugs can all improve late-life health in animals. Application to humans will require better biomarkers of disease risk and responses to interventions, closer alignment of work in animals and humans, and increased use of electronic health records, biobank resources and cohort studies.