ω-3 Polyunsaturated Fatty Acid Biomarkers and Coronary Heart Disease: Pooling Project of 19 Cohort Studies.

IMPORTANCE: The role of ω-3 polyunsaturated fatty acids for primary prevention of coronary heart disease (CHD) remains controversial. Most prior longitudinal studies evaluated self-reported consumption rather than biomarkers. OBJECTIVE: To evaluate biomarkers of seafood-derived eicosapentaenoic acid (EPA; 20:5ω-3), docosapentaenoic acid (DPA; 22:5ω-3), and docosahexaenoic acid (DHA; 22:6ω-3) and plant-derived α-linolenic acid (ALA; 18:3ω-3) for incident CHD. DATA SOURCES: A global consortium of 19 studies identified by November 2014. STUDY SELECTION: Available prospective (cohort, nested case-control) or retrospective studies with circulating or tissue ω-3 biomarkers and ascertained CHD. DATA EXTRACTION AND SYNTHESIS: Each study conducted standardized, individual-level analysis using harmonized models, exposures, outcomes, and covariates. Findings were centrally pooled using random-effects meta-analysis. Heterogeneity was examined by age, sex, race, diabetes, statins, aspirin, ω-6 levels, and FADS desaturase genes. MAIN OUTCOMES AND MEASURES: Incident total CHD, fatal CHD, and nonfatal myocardial infarction (MI). RESULTS: The 19 studies comprised 16 countries, 45 637 unique individuals, and 7973 total CHD, 2781 fatal CHD, and 7157 nonfatal MI events, with ω-3 measures in total plasma, phospholipids, cholesterol esters, and adipose tissue. Median age at baseline was 59 years (range, 18-97 years), and 28 660 (62.8%) were male. In continuous (per 1-SD increase) multivariable-adjusted analyses, the ω-3 biomarkers ALA, DPA, and DHA were associated with a lower risk of fatal CHD, with relative risks (RRs) of 0.91 (95% CI, 0.84-0.98) for ALA, 0.90 (95% CI, 0.85-0.96) for DPA, and 0.90 (95% CI, 0.84-0.96) for DHA. Although DPA was associated with a lower risk of total CHD (RR, 0.94; 95% CI, 0.90-0.99), ALA (RR, 1.00; 95% CI, 0.95-1.05), EPA (RR, 0.94; 95% CI, 0.87-1.02), and DHA (RR, 0.95; 95% CI, 0.91-1.00) were not. Significant associations with nonfatal MI were not evident. Associations appeared generally stronger in phospholipids and total plasma. Restricted cubic splines did not identify evidence of nonlinearity in dose responses. CONCLUSIONS AND RELEVANCE: On the basis of available studies of free-living populations globally, biomarker concentrations of seafood and plant-derived ω-3 fatty acids are associated with a modestly lower incidence of fatal CHD.ARIC was carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C), R01HL087641, R01HL59367 and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. The authors thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. CHS was supported by contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, and grant U01HL080295 from the National Heart, Lung, and Blood Institute (NHLBI), with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided by R01AG023629 from the National Institute on Aging (NIA). A full list of principal CHS investigators and institutions can be found at CHS-NHLBI.org. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health The Costa-Rican adult study was supported by grant R01HL081549 from the National Institutes of Health. EURAMIC was supported by the Commission of the European Communities, as a Concerted Action within Directorate General-XII, with additional support from Directorate General-V Europe against Cancer. The national studies were financed by the Dutch Ministry of Health. Ulster Cancer Foundation and Milk Intervention Board. Grant AKT76 from Cancer Research Switzerland. Swiss National Science Foundation Grant 32-9257-87. Spanish FIS and Ministry of Science and Education, and German Federal Health Office EPIC-Norfolk was funded by grants from Medical Research Council and Cancer Research UK. Dr. Imamura also received support from the Medical Research Council Epidemiology Unit Core Support (MC_UU_12015/5). HPFS was supported by the NIH grants UM1 CA167552, R01 HL35464, AA11181, HL35464, CA55075, HL60712 and P30 DK46200 The InChianti study was supported as a ‘targeted project’ (ICS 110.1\RS97.71) by the Italian Ministry of Health and in part by the Intramural Research Program of the NIH (Contracts N01-AG-916413 and N01-AG-821336 and Contracts 263 MD 9164 13 and 263 MD 821336) KIND (Kuopio Ischaemic Heart Disease Risk Factor Study) was supported by grants from the Academy of Finland, Helsinki, Finland (grants 41471, 1041086) MCCS (Melbourne Collaborative Cohort Study) recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057, 251553 and 504711 and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. MESA and the MESA SHARe project are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-MEHC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-001079, and UL1-TR-000040. Funding for SHARe genotyping was provided by NHLBI Contract N02-HL-64278. Genotyping was performed at Affymetrix (Santa Clara, California, USA) and the Broad Institute of Harvard and MIT (Boston, Massachusetts, USA) using the Affymetric Genome-Wide Human SNP Array 6.0. NSHDS I & II (The Northern Sweden Health & Disease Study I & II) was supported by the Swedish Cancer Society and the Swedish Research Council NHS (Nurses’ Health Study) was supported by research grants UM1 CA186107, R01 CA49449, R01 HL034594, P01CA87969, R01HL034594, and R01HL088521 of the National Institutes of Health The PHS (Physician’s Health Study) was supported by grant R21 HL088081, CA-34944 and CA-40360, and CA-097193 from the National Cancer Institute and grants HL-26490 and HL-34595from the National Heart, Lung, and Blood Institute, Bethesda, MD. The 3C (Three-City) study was conducted under a partnership agreement between the Institut National de la Santé et de la Recherche Médicale (INSERM), the University Bordeaux 2 Victor Segalen and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The Three-City study was also supported by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, MGEN, Institut de la Longévité, Conseils Régionaux d’Aquitaine et Bourgogne, Fondation de France, Ministry of Research-INSERM Programme “Cohortes et collections de données biologiques”, Agence Nationale de la Recherche (grant number COGINUT ANR-06-PNRA-005), the Fondation Plan Alzheimer (grant number FCS 2009-2012), and the Caisse Nationale pour la Solidarité et l’Autonomie (CNSA) . Dr Samieri was on a grant from the “Fondation Plan Alzheimer” SHHEC (Scottish Heart Health Extended Cohort) study was funded by the Scottish Health Department Chief Scientist Organization; British Heart Foundation; FP Fleming Trust. The authors would like to acknowledge Dr. Roger Tavendale for his work with the Scottish Heart Health Study. SCHS (Singapore Chinese Health Study) was supported by the Singapore National Medical Research Council (grant number: NMRC 1270/2010) and the U.S. NIH (grant numbers: R01CA 144034 and UM1 CA182876) ULSAM 50 and 70 were funded by the Swedish Research Council for Health, Working Life and Welfare (FORTE) Uppsala City Council (ALF) and Swedish Research CouncilThis is the final version of the article. It first appeared from American Medical Association via http://dx.doi.org/10.1001/jamainternmed.2016.292

Examining the generalizability of research findings from archival data

This initiative examined systematically the extent to which a large set of archival research findings generalizes across contexts. We repeated the key analyses for 29 original strategic management effects in the same context (direct reproduction) as well as in 52 novel time periods and geographies; 45% of the reproductions returned results matching the original reports together with 55% of tests in different spans of years and 40% of tests in novel geographies. Some original findings were associated with multiple new tests. Reproducibility was the best predictor of generalizability—for the findings that proved directly reproducible, 84% emerged in other available time periods and 57% emerged in other geographies. Overall, only limited empirical evidence emerged for context sensitivity. In a forecasting survey, independent scientists were able to anticipate which effects would find support in tests in new samples

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Adult height and the risk of cause-specific death and vascular morbidity in 1 million people: individual participant meta-analysis.

BACKGROUND: The extent to which adult height, a biomarker of the interplay of genetic endowment and early-life experiences, is related to risk of chronic diseases in adulthood is uncertain. METHODS: We calculated hazard ratios (HRs) for height, assessed in increments of 6.5 cm, using individual-participant data on 174374 deaths or major non-fatal vascular outcomes recorded among 1085949 people in 121 prospective studies. RESULTS: For people born between 1900 and 1960, mean adult height increased 0.5-1 cm with each successive decade of birth. After adjustment for age, sex, smoking and year of birth, HRs per 6.5 cm greater height were 0.97 (95% confidence interval: 0.96-0.99) for death from any cause, 0.94 (0.93-0.96) for death from vascular causes, 1.04 (1.03-1.06) for death from cancer and 0.92 (0.90-0.94) for death from other causes. Height was negatively associated with death from coronary disease, stroke subtypes, heart failure, stomach and oral cancers, chronic obstructive pulmonary disease, mental disorders, liver disease and external causes. In contrast, height was positively associated with death from ruptured aortic aneurysm, pulmonary embolism, melanoma and cancers of the pancreas, endocrine and nervous systems, ovary, breast, prostate, colorectum, blood and lung. HRs per 6.5 cm greater height ranged from 1.26 (1.12-1.42) for risk of melanoma death to 0.84 (0.80-0.89) for risk of death from chronic obstructive pulmonary disease. HRs were not appreciably altered after further adjustment for adiposity, blood pressure, lipids, inflammation biomarkers, diabetes mellitus, alcohol consumption or socio-economic indicators. CONCLUSION: Adult height has directionally opposing relationships with risk of death from several different major causes of chronic diseases