Estimates of biological age based on DNA methylation patterns, often referred to as “epigenetic age”, “DNAm age”, have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2×10−9), independent of chronological age, even after adjusting for additional risk factors (p<5.4×10−4), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5×10−43). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality.

SummaryBackgroundVarious genome-wide association studies (GWAS) have been done in ischaemic stroke, identifying a few loci associated with the disease, but sample sizes have been 3500 cases or less. We established the METASTROKE collaboration with the aim of validating associations from previous GWAS and identifying novel genetic associations through meta-analysis of GWAS datasets for ischaemic stroke and its subtypes.MethodsWe meta-analysed data from 15 ischaemic stroke cohorts with a total of 12 389 individuals with ischaemic stroke and 62 004 controls, all of European ancestry. For the associations reaching genome-wide significance in METASTROKE, we did a further analysis, conditioning on the lead single nucleotide polymorphism in every associated region. Replication of novel suggestive signals was done in 13 347 cases and 29 083 controls.FindingsWe verified previous associations for cardioembolic stroke near PITX2 (p=2·8×10−16) and ZFHX3 (p=2·28×10−8), and for large-vessel stroke at a 9p21 locus (p=3·32×10−5) and HDAC9 (p=2·03×10−12). Additionally, we verified that all associations were subtype specific. Conditional analysis in the three regions for which the associations reached genome-wide significance (PITX2, ZFHX3, and HDAC9) indicated that all the signal in each region could be attributed to one risk haplotype. We also identified 12 potentially novel loci at p<5×10−6. However, we were unable to replicate any of these novel associations in the replication cohort.InterpretationOur results show that, although genetic variants can be detected in patients with ischaemic stroke when compared with controls, all associations we were able to confirm are specific to a stroke subtype. This finding has two implications. First, to maximise success of genetic studies in ischaemic stroke, detailed stroke subtyping is required. Second, different genetic pathophysiological mechanisms seem to be associated with different stroke subtypes.FundingWellcome Trust, UK Medical Research Council (MRC), Australian National and Medical Health Research Council, National Institutes of Health (NIH) including National Heart, Lung and Blood Institute (NHLBI), the National Institute on Aging (NIA), the National Human Genome Research Institute (NHGRI), and the National Institute of Neurological Disorders and Stroke (NINDS).

IMPORTANCE Over ⅔ of U.S. women are overweight or obese, placing them at increased risk for postmenopausal breast cancer. OBJECTIVE To investigate the associations of overweight and obesity with risk of postmenopausal invasive breast cancer after extended follow-up in the Women’s Health Initiative (WHI) Clinical Trial. DESIGN The WHI protocol incorporated measured height and weight, baseline and annual or biennial mammography, and adjudicated breast cancer endpoints. SETTING 40 U.S. clinical centers. PARTICIPANTS n=67,142 postmenopausal women aged 50–79 years were enrolled from 1993–1998 with a median of 13 years of follow-up through 2010; 3388 invasive breast cancers were observed. MAIN OUTCOMES AND MEASURES Height and weight were measured at baseline and weight was measured annually thereafter. Data were collected on demographic characteristics, personal and family medical history and personal habits (smoking, physical activity). Women underwent annual or biennial mammograms. Breast cancers were verified by medical records reviewed by physician adjudicators. RESULTS Women who were overweight and obese had an increased invasive breast cancer risk vs. normal weight women. Risk was greatest for obesity grades 2+3 (BMI>35.0 kg/m2) (hazard ratio [HR] for invasive breast cancer =1.58, 95% CI 1.40–1.79). BMI ≥ 35.0 kg/m2 was strongly associated with risk for ER+/PR+ breast cancers (HR=1.86 95% CI 1.60–2.17), but was not associated with ER− cancers. Obesity grade 2+3 was also associated with advanced disease including larger tumor size (HR=2.12 95%CI 1.67–2.69). (P=0.02), positive lymph nodes (HR=1.89 95%CI 1.46–2.45), (P=0.06), regional/distant stage (HR=1.94, 95%CI 1.52–2.47) (P=0.05) and deaths after breast cancer (HR=2.11 95%CI 1.57–2.84) (P<0.001). Women with baseline BMI<25.0 kg/m2 who gained >5% of bodyweight over the follow-up period had an increased breast cancer risk (HR=1.36 95% CI 1.1–1.65), but among women already overweight or obese we found no association of weight change (gain or loss) with breast cancer during follow-up. There was no effect modification of the BMI-breast cancer relationship by postmenopausal hormone therapy (HT) and the direction of association across BMI categories was similar for never, past and current HT use. CONCLUSIONS/RELEVANCE Obesity is associated with increased invasive breast cancer risk in postmenopausal women. These clinically meaningful findings should motivate programs for obesity prevention.

SummaryBackgroundStatin treatment and variants in the gene encoding HMG-CoA reductase are associated with reductions in both the concentration of LDL cholesterol and the risk of coronary heart disease, but also with modest hyperglycaemia, increased bodyweight, and modestly increased risk of type 2 diabetes, which in no way offsets their substantial benefits. We sought to investigate the associations of LDL cholesterol-lowering PCSK9 variants with type 2 diabetes and related biomarkers to gauge the likely effects of PCSK9 inhibitors on diabetes risk.MethodsIn this mendelian randomisation study, we used data from cohort studies, randomised controlled trials, case control studies, and genetic consortia to estimate associations of PCSK9 genetic variants with LDL cholesterol, fasting blood glucose, HbA1c, fasting insulin, bodyweight, waist-to-hip ratio, BMI, and risk of type 2 diabetes, using a standardised analysis plan, meta-analyses, and weighted gene-centric scores.FindingsData were available for more than 550 000 individuals and 51 623 cases of type 2 diabetes. Combined analyses of four independent PCSK9 variants (rs11583680, rs11591147, rs2479409, and rs11206510) scaled to 1 mmol/L lower LDL cholesterol showed associations with increased fasting glucose (0·09 mmol/L, 95% CI 0·02 to 0·15), bodyweight (1·03 kg, 0·24 to 1·82), waist-to-hip ratio (0·006, 0·003 to 0·010), and an odds ratio for type diabetes of 1·29 (1·11 to 1·50). Based on the collected data, we did not identify associations with HbA1c (0·03%, −0·01 to 0·08), fasting insulin (0·00%, −0·06 to 0·07), and BMI (0·11 kg/m2, −0·09 to 0·30).InterpretationPCSK9 variants associated with lower LDL cholesterol were also associated with circulating higher fasting glucose concentration, bodyweight, and waist-to-hip ratio, and an increased risk of type 2 diabetes. In trials of PCSK9 inhibitor drugs, investigators should carefully assess these safety outcomes and quantify the risks and benefits of PCSK9 inhibitor treatment, as was previously done for statins.FundingBritish Heart Foundation, and University College London Hospitals NHS Foundation Trust (UCLH) National Institute for Health Research (NIHR) Biomedical Research Centre.

A multi-ethnic study demonstrates that the extrapolation of genetic disease risk models from European populations to other ethnicities is compromised more strongly by genetic structure than by environmental or global genetic background in differential genetic risk associations across ethnicities.