Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78 , associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity.

The relationship between omega-3 polyunsaturated fatty acids (n-3 PUFA) from seafood (eicosapentaenoic acid, EPA; docosahexaenoic acid, DHA) or plant (alpha-linolenic acid, ALA) sources and risk of type 2 diabetes mellitus (DM) remains unclear. We systematically searched multiple literature databases through June 2011 to identify prospective studies examining relations of dietary n-3 PUFA, dietary fish and/or seafood, and circulating n-3 PUFA biomarkers with incidence of DM. Data were independently extracted in duplicate by 2 investigators, including multivariate-adjusted relative risk (RR) estimates and corresponding 95% CIs. Generalized least-squares trend estimation was used to assess dose-response relationships, with pooled summary estimates calculated by both fixed-effect and random-effect models. From 288 identified abstracts, 16 studies met inclusion criteria, including 18 separate cohorts comprising 540,184 individuals and 25,670 cases of incident DM. Consumption of fish and/or seafood was not significantly associated with DM (n=13 studies; RR per 100g/d=1.12, 95% CI=0.94, 1.34); nor were consumption of EPA+DHA (n=16 cohorts; RR per 250mg/d=1.04, 95% CI=0.97, 1.10) or circulating levels of EPA+DHA biomarkers (n=5 cohorts; RR per 3% of total fatty acids=0.94, 95% CI=0.75, 1.17). Both dietary ALA (n=7 studies; RR per 0.5g/d=0.93, 95% CI=0.83, 1.04) and circulating ALA biomarker levels (n=6 studies; RR per 0.1% of total fatty acid=0.90, 95% CI=0.80, 1.00, P=0.06) were associated with non-significant trend towards lower risk of DM. Substantial heterogeneity (I2~80%) was observed among studies of fish/seafood or EPA+DHA and DM; moderate heterogeneity (<55%) was seen for dietary and biomarker ALA and DM. In unadjusted meta-regressions, study location (Asia vs. North America/Europe), mean BMI, and duration of follow-up each modified the association between fish/seafood and EPA+DHA consumption and DM risk (P-Interaction ≤ 0.02 each). We had limited statistical power to determine the independent effect of these sources of heterogeneity due to their high collinearity. The overall pooled findings do not support either major harms or benefits of fish/seafood or EPA+DHA on development of DM, and suggest that ALA may be associated with modestly lower risk. Reasons for potential heterogeneity of effects, which could include true biologic heterogeneity, publication bias, or chance, deserve further investigation.

Background Asymptomatic individuals account for a majority of sudden cardiac deaths (SCDs). Development of effective, low-cost, and non-invasive SCD risk stratification tools are necessary. Methods and Results Participants from the Atherosclerosis Risk in Communities study and Cardiovascular Health Study (n=20,177; age 59.3±10.1 years; age range 44–100; 56% female; 77% white) were followed for 14.0 years (median). Five ECG markers of global electrical heterogeneity (GEH) (sum absolute QRST integral, spatial QRST angle, spatial ventricular gradient (SVG) magnitude, SVG elevation, and SVG azimuth) were measured on standard 12-lead ECGs. Cox proportional hazards and competing risks models evaluated associations between GEH ECG parameters and SCD. A SCD competing risks score was derived using demographics, comorbidities, and GEH parameters. SCD incidence was 1.86 per 1,000 person-years. After multivariable adjustment, baseline GEH parameters and large increases in GEH parameters over time were independently associated with SCD. Final SCD risk scores included age, sex, race, diabetes, hypertension, coronary heart disease, and stroke, and GEH parameters as continuous variables. When GEH parameters were added to clinical/demographic factors, the C-statistic increased from 0.777 to 0.790 (p=0.008), the risk score classified 10-year SCD risk as high (>5%) in 7.2% of participants, 10% of SCD victims were appropriately reclassified into a high-risk category, and only 1.4% of SCD victims were inappropriately reclassified from high- to intermediate-risk. Net reclassification index was 18.3%. Conclusions Abnormal electrophysiological substrate quantified by GEH parameters is independently associated with SCD in the general population. Addition of GEH parameters to clinical characteristics improves SCD risk prediction.