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There are several cardiac- and patient-related factors that come into play when considering patients for protected percutaneous coronary intervention (PCI). Cardiac factors include complexity/location of coronary lesions, the degree of left or right ventricular impairment, the presence of valvular lesions, and ventricular arrhythmias. Patient related factors include comorbidities that would render the patient at a higher risk of death should cardiogenic shock ensue during the procedure. Comorbidities include chronic lung disease (chronic obstructive airways disease, asthma, pulmonary fibrosis), renal or liver impairment, other cardiovascular diseases (such as previous cerebrovascular accident or transient ischemic attack, peripheral arterial disease, carotid stenosis), diabetes, frailty and advanced age. Here, we present three very different cases where left ventricular support was deemed appropriate to reduce peri-procedural risk and optimize outcomes.

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.

BACKGROUND Myocardial mass is a key determinant of cardiac muscle function and hypertrophy. Myocardial depolarization leading to cardiac muscle contraction is reflected by the amplitude and duration of the QRS complex on the electrocardiogram (ECG). Abnormal QRS amplitude or duration reflect changes in myocardial mass and conduction, and are associated with increased risk of heart failure and death.OBJECTIVES This meta-analysis sought to gain insights into the genetic determinants of myocardial mass.METHODS We carried out a genome-wide association meta-analysis of 4 QRS traits in up to 73,518 individuals of European ancestry, followed by extensive biological and functional assessment.RESULTS We identified 52 genomic loci, of which 32 are novel, that are reliably associated with 1 or more QRS phenotypes at p CONCLUSIONS Taken together, our findings provide new insights into genes and biological pathways controlling myocardial mass and may help identify novel therapeutic targets. (C) 2016 by the American College of Cardiology Foundation.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files. This article is open access. Nearly three-quarters of the 143 genetic signals associated with platelet and erythrocyte phenotypes identified by meta-analyses of genome-wide association (GWA) studies are located at non-protein-coding regions. Here, we assessed the role of candidate regulatory variants associated with cell type-restricted, closely related hematological quantitative traits in biologically relevant hematopoietic cell types. We used formaldehyde-assisted isolation of regulatory elements followed by next-generation sequencing (FAIRE-seq) to map regions of open chromatin in three primary human blood cells of the myeloid lineage. In the precursors of platelets and erythrocytes, as well as in monocytes, we found that open chromatin signatures reflect the corresponding hematopoietic lineages of the studied cell types and associate with the cell type-specific gene expression patterns. Dependent on their signal strength, open chromatin regions showed correlation with promoter and enhancer histone marks, distance to the transcription start site, and ontology classes of nearby genes. Cell type-restricted regions of open chromatin were enriched in sequence variants associated with hematological indices. The majority (63.6%) of such candidate functional variants at platelet quantitative trait loci (QTLs) coincided with binding sites of five transcription factors key in regulating megakaryopoiesis. We experimentally tested 13 candidate regulatory variants at 10 platelet QTLs and found that 10 (76.9%) affected protein binding, suggesting that this is a frequent mechanism by which regulatory variants influence quantitative trait levels. Our findings demonstrate that combining large-scale GWA data with open chromatin profiles of relevant cell types can be a powerful means of dissecting the genetic architecture of closely related quantitative traits. Marie-Curie Initial Training Network NETSIM British Heart Foundation RG/09/12/28096 National Institutes for Health RP-PG-0310-1002 Wellcome Trust 098051 info:eu-repo/grantAgreement/EC/FP7/282510

Background Indian Asians, who make up a quarter of the world's population, are at high risk of developing type 2 diabetes. We investigated whether DNA methylation is associated with future type 2 diabetes incidence in Indian Asians and whether differences in methylation patterns between Indian Asians and Europeans are associated with, and could be used to predict, differences in the magnitude of risk of developing type 2 diabetes. Methods We did a nested case-control study of DNA methylation in Indian Asians and Europeans with incident type 2 diabetes who were identified from the 8-year follow-up of 25 372 participants in the London Life Sciences Prospective Population (LOLIPOP) study. Patients were recruited between May 1, 2002, and Sept 12, 2008. We did epigenome-wide association analysis using samples from Indian Asians with incident type 2 diabetes and age-matched and sex-matched Indian Asian controls, followed by replication testing of top-ranking signals in Europeans. For both discovery and replication, DNA methylation was measured in the baseline blood sample, which was collected before the onset of type 2 diabetes. Epigenome-wide significance was set at p

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery., The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Funding for this study was provided by the Aase and Ejner Danielsens Foundation; Academy of Finland (102318; 104781, 120315, 123885, 129619, 286284, 134309, 126925, 121584, 124282, 129378, 117787, 250207, 258753, 41071, 77299, 124243, 1114194, 24300796); Accare Center for Child and Adolescent Psychiatry; Action on Hearing Loss (G51); Agence Nationale de la Recherche; Agency for Health Care Policy Research (HS06516); Age UK Research into Ageing Fund; Åke Wiberg Foundation; ALF/LUA Research Grant in Gothenburg; ALFEDIAM; ALK-Abello´ A/S (Hørsholm, Denmark); American Heart Association (13POST16500011, 10SDG269004); Ardix Medical; Arthritis Research UK; Association Diabète Risque Vasculaire; AstraZeneca; Australian Associated Brewers; Australian National Health and Medical Research Council (241944, 339462, 389927, 389875, 389891, 389892, 389938, 442915, 442981, 496739, 552485, 552498); Avera Research Institute; Bayer Diagnostics; Becton Dickinson; Biobanking and Biomolecular Resources Research Infrastructure (BBMRI –NL, 184.021.007); Biocentrum Helsinki; Boston Obesity Nutrition Research Center (DK46200); British Heart Foundation (RG/10/12/28456, SP/04/002); Canada Foundation for Innovation; Canadian Institutes of Health Research (FRN-CCT-83028); Cancer Research UK; Cardionics; Center for Medical Systems Biology; Center of Excellence in Complex Disease Genetics and SALVECenter of Excellence in Genomics (EXCEGEN); Chief Scientist Office of the Scottish Government; City of Kuopio; Cohortes Santé TGIR; Contrat de Projets État-Région; Croatian Science Foundation (8875); Danish Agency for Science, Technology and Innovation; Danish Council for Independent Research (DFF–1333-00124, DFF–1331-007308); Danish Diabetes Academy; Danish Medical Research Council; Department of Psychology and Education of the VU University Amsterdam; Diabetes Hilfs- und Forschungsfonds Deutschland; Dutch Brain Foundation; Dutch Ministry of Justice; Emil Aaltonen Foundation; Erasmus Medical Center; Erasmus University; Estonian Government (IUT20-60, IUT24-6); Estonian Ministry of Education and Research (3.2.0304.11-0312); European Commission (230374, 284167, 323195, 692145, FP7 EurHEALTHAgeing-277849, FP7 BBMRI-LPC 313010, nr 602633, HEALTH-F2-2008-201865-GEFOS, HEALTH-F4-2007-201413, FP6 LSHM-CT-2004-005272, FP5 QLG2-CT-2002-01254, FP6 LSHG-CT-2006-01947, FP7 HEALTH-F4-2007-201413, FP7 279143, FP7 201668, FP7 305739, FP6 LSHG-CT-2006-018947, HEALTH-F4-2007-201413, QLG1-CT-2001-01252); European Regional Development Fund; European Science Foundation (EuroSTRESS project FP-006, ESF, EU/QLRT-2001-01254); Faculty of Biology and Medicine of Lausanne; Federal Ministry of Education and Research (01ZZ9603, 01ZZ0103, 01ZZ0403, 03ZIK012, 03IS2061A); Federal State of Mecklenburg - West Pomerania; Fédération Française de Cardiologie; Finnish Cultural Foundation; Finnish Diabetes Association; Finnish Foundation of Cardiovascular Research; Finnish Heart Association; Food Standards Agency; Fondation de France; Fonds Santé; Genetic Association Information Network of the Foundation for the National Institutes of Health; German Diabetes Association; German Federal Ministry of Education and Research (BMBF, 01ER1206, 01ER1507); German Research Council (SFB-1052, SPP 1629 TO 718/2-1); GlaxoSmithKline; Göran Gustafssons Foundation; Göteborg Medical Society; Health and Safety Executive; Heart Foundation of Northern Sweden; Icelandic Heart Association; Icelandic Parliament; Imperial College Healthcare NHS Trust; INSERM, Réseaux en Santé Publique, Interactions entre les déterminants de la santé; Interreg IV Oberrhein Program (A28); Italian Ministry of Economy and Finance; Italian Ministry of Health (ICS110.1/RF97.71); John D and Catherine T MacArthur Foundation; Juho Vainio Foundation; King's College London; Kjell och Märta Beijers Foundation; Kuopio University Hospital; Kuopio, Tampere and Turku University Hospital Medical Funds (X51001); Leiden University Medical Center; Lilly; LMUinnovativ; Lundbeck Foundation; Lundberg Foundation; Medical Research Council of Canada; MEKOS Laboratories (Denmark); Merck Santé; Mid-Atlantic Nutrition Obesity Research Center (P30 DK72488); Ministère de l’Économie, de l’Innovation et des Exportations; Ministry for Health, Welfare and Sports of the Netherlands; Ministry of Cultural Affairs of the Federal State of Mecklenburg-West Pomerania; Ministry of Education and Culture of Finland (627;2004-2011); Ministry of Education, Culture and Science of the Netherlands; MRC Human Genetics Unit; MRC-GlaxoSmithKline Pilot Programme Grant (G0701863); Municipality of Rotterdam; Netherlands Bioinformatics Centre (2008.024); Netherlands Consortium for Healthy Aging (050-060-810); Netherlands Genomics Initiative; Netherlands Organisation for Health Research and Development (904-61-090, 985-10-002, 904-61-193, 480-04-004, 400-05-717, Addiction-31160008, Middelgroot-911-09-032, Spinozapremie 56-464-14192); Netherlands Organisation for Health Research and Development (2010/31471/ZONMW); Netherlands Organisation for Scientific Research (10-000-1002, GB-MW 940-38-011, 100-001-004, 60-60600-97-118, 261-98-710, GB-MaGW 480-01-006, GB-MaGW 480-07-001, GB-MaGW 452-04-314, GB-MaGW 452-06-004, 175.010.2003.005, 175.010.2005.011, 481-08-013, 480-05-003, 911-03-012); Neuroscience Campus Amsterdam; NHS Foundation Trust; Novartis Pharmaceuticals; Novo Nordisk; Office National Interprofessionel des Vins; Paavo Nurmi Foundation; Påhlssons Foundation; Päivikki and Sakari Sohlberg Foundation; Pierre Fabre; Republic of Croatia Ministry of Science, Education and Sport (108-1080315-0302); Research Centre for Prevention and Health, the Capital Region for Denmark; Research Institute for Diseases in the Elderly (014-93-015, RIDE2); Roche; Russian Foundation for Basic Research (NWO-RFBR 047.017.043); Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06); Sanofi-Aventis; Scottish Executive Health Department (CZD/16/6); Siemens Healthcare; Social Insurance Institution of Finland (4/26/2010); Social Ministry of the Federal State of Mecklenburg-West Pomerania; Société Francophone du Diabète; State of Bavaria; Stroke Association; Swedish Diabetes Association; Swedish Foundation for Strategic Research; Swedish Heart-Lung Foundation (20140543); Swedish Research Council (2015-03657); Swedish Medical Research Council (K2007-66X-20270-01-3, 2011-2354); Swedish Society for Medical Research; Swiss National Science Foundation (33CSCO-122661, 33CS30-139468, 33CS30-148401); Tampere Tuberculosis Foundation; The Marcus Borgström Foundation; The Royal Society; The Wellcome Trust (084723/Z/08/Z, 088869/B/09/Z); Timber Merchant Vilhelm Bangs Foundation; Topcon; Torsten and Ragnar Söderberg's Foundation; UK Department of Health; UK Diabetes Association; UK Medical Research Council (MC_U106179471, G0500539, G0600705, G0601966, G0700931, G1002319, K013351, MC_UU_12019/1); UK National Institute for Health Research BioResource Clinical Research Facility and Biomedical Research Centre; UK National Institute for Health Research (NIHR) Comprehensive Biomedical Research Centre; UK National Institute for Health Research (RP-PG-0407-10371); Umeå University Career Development Award; United States – Israel Binational Science Foundation Grant (2011036); University Hospital Oulu (75617); University Medical Center Groningen; University of Tartu (SP1GVARENG); National Institutes of Health (AG13196, CA047988, HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, HHSC271201100004C, HHSN268200900041C, HHSN268201300025C, HHSN268201300026C, HHSN268201300027C, HHSN268201300028C, HHSN268201300029C, HHSN268201500001I, HL36310, HG002651, HL034594, HL054457, HL054481, HL071981, HL084729, HL119443, HL126024, N01-AG12100, N01-AG12109, N01-HC25195, N01-HC55015, N01-HC55016, N01-HC55018, N01-HC55019, N01-HC55020, N01-HC55021, N01-HC55022, N01-HD95159, N01-HD95160, N01-HD95161, N01-HD95162, N01-HD95163, N01-HD95164, N01-HD95165, N01-HD95166, N01-HD95167, N01-HD95168, N01-HD95169, N01-HG65403, N02-HL64278, R01-HD057194, R01-HL087641, R01-HL59367, R01HL-086694, R01-HL088451, R24-HD050924, U01-HG-004402, HHSN268200625226C, UL1-RR025005, UL1-RR025005, UL1-TR-001079, UL1-TR-00040, AA07535, AA10248, AA11998, AA13320, AA13321, AA13326, AA14041, AA17688, DA12854, MH081802, MH66206, R01-D004215701A, R01-DK075787, R01-DK089256, R01-DK8925601, R01-HL088451, R01-HL117078, R01-DK062370, R01-DK072193, DK091718, DK100383, DK078616, 1Z01-HG000024, HL087660, HL100245, R01DK089256, 2T32HL007055-36, U01-HL072515-06, U01-HL84756, NIA-U01AG009740, RC2-AG036495, RC4-AG039029, R03 AG046389, 263-MA-410953, 263-MD-9164, 263-MD-821336, U01-HG004802, R37CA54281, R01CA63, P01CA33619, U01-CA136792, U01-CA98758, RC2-MH089951, MH085520, R01-D0042157-01A, MH081802, 1RC2-MH089951, 1RC2-MH089995, 1RL1MH08326801, U01-HG007376, 5R01-HL08767902, 5R01MH63706:02, HG004790, N01-WH22110, U01-HG007033, UM1CA182913, 24152, 32100-2, 32105-6, 32108-9, 32111-13, 32115, 32118-32119, 32122, 42107-26, 42129-32, 44221); USDA National Institute of Food and Agriculture (2007-35205-17883); Västra Götaland Foundation; Velux Foundation; Veterans Affairs (1 IK2 BX001823); Vleugels Foundation; VU University’s Institute for Health and Care Research (EMGO+, HEALTH-F4-2007-201413) and Neuroscience Campus Amsterdam; Wellcome Trust (090532, 091551, 098051, 098381); Wissenschaftsoffensive TMO; and Yrjö Jahnsson Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Disorders of water balance, an excess or deficit of total body water relative to body electrolyte content, are common and ascertained by plasma hypo- or hypernatremia, respectively. We performed a two-stage genome-wide association study meta-analysis on plasma sodium concentration in 45,889 individuals of European descent (stage 1 discovery) and 17,637 additional individuals of European descent (stage 2 replication), and a transethnic meta-analysis of replicated single-nucleotide polymorphisms in 79,506 individuals (63,526 individuals of European descent, 8765 individuals of Asian Indian descent, and 7215 individuals of African descent). In stage 1, we identified eight loci associated with plasma sodium concentration at P-6. Of these, rs9980 at NFAT5 replicated in stage 2 meta-analysis (P=3.1 3 x 10-5), with combined stages 1 and 2 genomewide significance of P=5.6 x 10-10. Transethnic meta-analysis further supported the association at rs9980 (P=5.9 x 10-12). Additionally, rs16846053 at SLC4A10 showed nominally, but not genome-wide, significant association in combined stages 1 and 2 meta-analysis (P=6.7 x 10-8). NFAT5 encodes a ubiquitously expressed transcription factor that coordinates the intracellular response to hypertonic stress but was not previously implicated in the regulation of systemic water balance. SLC4A10 encodes a sodium bicarbonate transporter with a brain-restricted expression pattern, and variant rs16846053 affects a putative intronic NFAT5 DNA binding motif. The lead variants for NFAT5 and SLC4A10 are cis expression quantitative trait loci in tissues of the central nervous systemand relevant to transcriptional regulation. Thus, genetic variation in NFAT5 and SLC4A10 expression and function in the central nervous system may affect the regulation of systemic water balance.

Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p, We acknowledge the essential role of the Cohorts for Heart and Aging Research in Genome Epidemiology (CHARGE) Consortium in development and support of this manuscript. CHARGE members include the Netherland’s Rotterdam Study (RS), Framingham Heart Study (FHS), Cardiovascular Health Study (CHS), the NHLBI’s Atherosclerosis Risk in Communities (ARIC) Study, and Iceland’s Age, Gene/Environment Susceptibility (AGES) Reykjavik Study. Age, Gene/Environment Susceptibility Reykjavik Study (AGES-Reykjavik): has been funded by NIH contract N01-AG-12100, the NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament). The study is approved by the Icelandic National Bioethics Committee, (VSN: 00-063) and the Data Protection Authority. The researchers are indebted to the participants for their willingness to participate in the study. Old Order Amish (OOA): this work was supported by NIH research grants U01 HL72515, U01 GM074518, R01 HL088119, R01 AR046838, and U01 HL084756. Partial funding was also provided by the Mid-Atlantic Nutrition and Obesity Research Center of Maryland (P30 DK072488).). L.M.Y.-A. was supported by F32AR059469 from NIH/NIAMS. M.F. was supported by American Heart Association grant 10SDG2690004. Cardiovascular Health Study (CHS): This CHS research was supported by NHLBI contracts N01-HC- 85079, N01-HC-85080, N01-HC-85081, N01-HC-85082, N01-HC-85083, N01-HC-85084, N01-HC-85085, N01-HC-85086; N01-HC-35129, N01 HC-15103, N01 HC-55222, N01-HC-75150, N01-HC-45133, N01-HC-85239, and by HHSN268201200036C and NHLBI grants HL080295, HL087652, HL105756, HL103612, HL120393, and HL130114 with additional contribution from NINDS. Additional support was provided through AG-023629, AG-15928, AG-20098, and AG-027058 from the NIA. See also http://www.chs-nhlbi.org/pi.htm. DNA handling and genotyping at Cedars-Sinai Medical Center was supported in part by the National Center for Research Resources, grant UL1RR033176, and is now at the National Center for Advancing Translational Sciences, CTSI grant UL1TR000124; in addition to the National Institute of Diabetes and Digestive and Kidney Disease grant DK063491 to the Southern California Diabetes Endocrinology Research Center. CoLaus: The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (grants 33CSCO-122661, 33CS30-139468, and 33CS30-148401). We thank Vincent Mooser and Gérard Waeber, Co-PIs of the CoLaus study. Special thanks to Yolande Barreau, Mathieu Firmann, Vladimir Mayor, Anne-Lise Bastian, Binasa Ramic, Martine Moranville, Martine Baumer, Marcy Sagette, Jeanne Ecoffey, and Sylvie Mermoud for data collection. Data analysis was supervised by Sven Bergmann and Jacques S. Beckmann. The computations for this paper were performed in part at the Vital-IT Center for high-performance computing of the Swiss Institute of Bioinformatics. deCODE Study: The study was funded by deCODE Genetics, ehf. We thank all the participants of this study, the staff of deCODE Genetics core facilities and recruitment center and the densitometry clinic at the University Hospital for their important contributions to this work. The EPIC Study: The EPIC Obesity study is funded by Cancer Research United Kingdom and the Medical Research Council. I.B. acknowledges support from EU FP6 funding (contract no. LSHM-CT-2003-503041) and by the Wellcome Trust (WT098051). Erasmus Rucphen Family (ERF) Study: The study was supported by grants from The Netherlands Organisation for Scientific Research (NWO), Erasmus MC, the Centre for Medical Systems Biology (CMSB), and the European Community’s Seventh Framework Programme (FP7/2007-2013), ENGAGE Consortium, grant agreement HEALTH-F4-2007-201413. We are grateful to all general practitioners for their contributions, to Petra Veraart for her help in genealogy, Jeannette Vergeer for the supervision of the laboratory work and Peter Snijders for his help in data collection. Fenland: The Fenland Study is funded by the Wellcome Trust and the Medical Research Council, as well as by the Support for Science Funding programme and CamStrad. We are grateful to all the volunteers for their time and help, and to the General Practitioners and practice staff for help with recruitment. We thank the Fenland Study co-ordination team and the Field Epidemiology team of the MRC Epidemiology Unit for recruitment and clinical testing. Tuomas O. Kilpeläinen was supported by the Danish Council for Independent Research (DFF—1333-00124 and Sapere Aude program grant DFF—1331-00730B). Framingham Osteoporosis Study (FOS)/Framingham Heart Study (FHS): The study was funded by grants from the US National Institute for Arthritis, Musculoskeletal and Skin Diseases and National Institute on Aging (R01 AR 41398 and U24AG051129; D.P.K. and R01AR057118; D.K. D.K. was also supported by FP7-PEOPLE-2012-Marie Curie Career Integration Grants (CIG)). The Framingham Heart Study of the National Heart, Lung, and Blood Institute of the National Institutes of Health and Boston University School of Medicine were supported by the National Heart, Lung, and Blood Institute’s Framingham Heart Study (N01-HC-25195) and its contract with Affymetrix, Inc. for genotyping services (N02-HL-6-4278). Analyses reflect intellectual input and resource development from the Framingham Heart Study investigators participating in the SNP Health Association Resource (SHARe) project. A portion of this research was conducted using the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. eQTL HOb Study: The study was supported by Genome Quebec, Genome Canada and the Canadian Institutes of Health Research (CIHR). Gothenburg Osteoporosis and Obesity Determinants Study (GOOD): The study was funded by the Swedish Research Council, the Swedish Foundation for Strategic Research, The ALF/LUA research grant in Gothenburg, the Lundberg Foundation, the Emil and Vera Cornell Foundation, the Torsten and Ragnar Söderberg’s Foundation, Petrus and Augusta Hedlunds Foundation, the Västra Götaland Foundation, and the Göteborg Medical Society. We would like to thank Dr Tobias A. Knoch, Luc V. de Zeeuw, Anis Abuseiris, and Rob de Graaf as well as their institutions the Erasmus Computing Grid, Rotterdam, The Netherlands, and especially the national German MediGRID and Services@MediGRID part of the German D-Grid, both funded by the German Bundesministerium fuer Forschung und Technology under grants #01 AK 803 A-H and # 01 IG 07015G for access to their grid resources. We also thank Karol Estrada, Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands for advice regarding the grid resources. Health Aging and Body Composition Study (Health ABC): This study was funded by the National Institutes of Aging. This research was supported by NIA contracts N01AG62101, N01AG62103, and N01AG62106. The genome-wide association study was funded by NIA grant 1R01AG032098-01A1 to Wake Forest University Health Sciences and genotyping services were provided by the Center for Inherited Disease Research (CIDR). CIDR is fully funded through a federal contract from the National Institutes of Health to The Johns Hopkins University, contract number HHSN268200782096C. Indiana: We thank the individuals who participated in this study, as well as the study coordinators, without whom this work would not have been possible. This work was supported by National Institutes of Health grants R01 AG 041517 and M01 RR-00750. Genotyping services were provided by CIDR. CIDR is fully funded through a federal contract from the National Institutes of Health to The Johns Hopkins University, contract number HHSN268200782096C. This research was supported in part by the Intramural Research Program of the NIH, National Library of Medicine. Kora (KORA F3 and KORA F4): The KORA research platform was initiated and financed by the Helmholtz Center Munich, German Research Center for Environmental Health, which is funded by the German Federal Ministry of Education and Research (BMBF) and by the State of Bavaria. Part of this work was financed by the German National Genome Research Network (NGFN-2 and NGFNPlus: 01GS0823). Our research was supported within the Munich Center of Health Sciences (MC Health) as part of LMUinnovativ. The London Life Sciences Population (LOLIPOP): The study was funded by the British Heart Foundation, Wellcome Trust, the Medical Research Council, and Kidney Research UK. The study also receives support from a National Institute for Health Research (NIHR) programme grant. Rotterdam Study (RSI, RSII & RSIII): The generation and management of GWAS genotype data for the Rotterdam Study (RS I, RS II, RS III) was executed by the Human Genotyping Facility of the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands. The GWAS datasets are supported by the Netherlands Organisation of Scientific Research NWO Investments (no. 175.010.2005.011, 911-03-012), the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC, the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO) Netherlands Consortium for Healthy Aging (NCHA), project no. 050-060-810. We thank Pascal Arp, Mila Jhamai, Marijn Verkerk, Lizbeth Herrera, Marjolein Peters, MSc, and Carolina Medina-Gomez, MSc, for their help in creating the GWAS database, and Karol Estrada, PhD, Yurii Aulchenko, PhD, and Carolina Medina-Gomez, PhD, for the creation and analysis of imputed data. The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. We are grateful to the study participants, the staff from the Rotterdam Study and the participating general practitioners and pharmacists. We thank Dr Karol Estrada, Dr Fernando Rivadeneira, Dr Tobias A. Knoch, Anis Abuseiris, and Rob de Graaf (Erasmus MC Rotterdam, The Netherlands) for their help in creating GRIMP, and we thank BigGRID, MediGRID, and Services@MediGRID/D-Grid (funded by the German Bundesministerium fuer Forschung und Technology; grants 01 AK 803 A-H, 01 IG 07015G) for access to their grid computing resources. Rush Memory and Aging Project (MAP): The Memory and Aging Project was supported by National Institute on Aging grants R01AG17917, R01AG15819, and R01AG24480, the Illinois Department of Public Health, the Rush Clinical Translational Science Consortium, and a gift from Ms Marsha Dowd. TwinsUK (TUK): The study was funded by the Wellcome Trust, Arthritis Research UK, and the Chronic Disease Research Foundation. The study also received support from a National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre award to Guy’s & St Thomas’ NHS Foundation Trust in partnership with King’s College London. We thank the staff and volunteers of the TwinsUK study. The study was also supported by Israel Science Foundation, grant number 994/10. Age, Gene/Environment Susceptibility Reykjavik Study (AGES-Reykjavik) has been funded by NIH contract N01-AG-12100, the NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament). The study is approved by the Icelandic National Bioethics Committee (VSN: 00-063) and the Data Protection Authority. The researchers are indebted to the participants for their willingness to participate in the study. Berlin Aging Study II (BASE-II) was supported by the German Federal Ministry of Education and Research (BMBF (grants #16SV5536K, #16SV5537, #16SV5538, and #16SV5837; previously #01UW0808)). Additional contributions (e.g., financial, equipment, logistics, personnel) are made from each of the other participating sites, i.e., the Max Planck Institute for Human Development (MPIB), Max Planck Institute for Molecular Genetics (MPIMG), Charite University Medicine, German Institute for Economic Research (DIW), all located in Berlin, Germany, and University of Lübeck in Lübeck, Germany. B-vitamins in the prevention of osteoporotic fractures (B-PROOF): B-PROOF is supported and funded by The Netherlands Organization for Health Research and Development (ZonMw, grant 6130.0031), the Hague; unrestricted grant from NZO (Dutch Dairy Association), Zoetermeer; Orthica, Almere; NCHA (Netherlands Consortium Healthy Ageing) Leiden/Rotterdam; Ministry of Economic Affairs, Agriculture and Innovation (project KB-15-004-003), the Hague; Wageningen University, Wageningen; VU University Medical Center, Amsterdam; Erasmus Medical Center, Rotterdam. All organizations are based in the Netherlands. We thank Dr Tobias A. Knoch, Anis Abuseiris, Karol Estrada, and Rob de Graaf as well as their institutions the Erasmus Grid Office, Erasmus MC Rotterdam, The Netherlands, and especially the national German MediGRID and Services@MediGRID part of the German D-Grid, both funded by the German Bundesministerium fuer Forschung und Technology (grants #01 AK 803 A-H and #01 IG 07015G) for access to their gird resources. Further, we gratefully thank all participants. Calcium Intake Fracture Outcome Study (CAIFOS): This study was funded by Healthway Health Promotion Foundation of Western Australia, Australasian Menopause Society and the Australian National Health and Medical Research Council Project Grants (254627, 303169, and 572604). We are grateful to the participants of the CAIFOS Study. The salary of Dr Lewis is supported by a National Health and Medical Research Council of Australia Career Development Fellowship. Danish Osteoporosis Study (DOPS): The study was supported by Karen Elise Jensen foundation. Family Heart Study (FamHS): The study was supported by NIH grants R01-HL-117078, R01-HL-087700, and R01-HL-088215 from NHLBI; and R01-DK-089256 and R01-DK-075681 from NIDDK. GenMets (Health 2000): S.R. was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (213506 and 129680), Academy of Finland (251217), the Finnish foundation for Cardiovascular Research and the Sigrid Juselius Foundation. S.M. was supported by grants #136895 and #141005, V.S. by grants #139635 and 129494, and M.P. by grant #269517 from the Academy of Finland and a grant from the Finnish Foundation for Cardiovascular Research. M.P. was supported by the Yrjö Jahnsson Foundation. Helsinki Birth Cohort Study (HBCS): We thank all study participants as well as everybody involved in the HBCS. HBCS has been supported by grants from the Academy of Finland, the Finnish Diabetes Research Society, Samfundet Folkhälsann, Novo Nordisk Foundation, Liv och Hälsa, Finska Läkaresällskapet, Signe and Ane Gyllenberg Foundation, University of Helsinki, European Science Foundation (EUROSTRESS), Ministry of Education, Ahokas Foundation, Emil Aaltonen Foundation, Juho Vainio Foundation, and Wellcome Trust (grant number WT089062). Johnston County Study: The Johnston County Osteoarthritis Project is supported in part by cooperative agreements S043, S1734, and S3486 from the Centers for Disease Control and Prevention/Association of Schools of Public Health; the NIAMS Multipurpose Arthritis and Musculoskeletal Disease Center grant 5-P60-AR30701; and the NIAMS Multidisciplinary Clinical Research Center grant 5 P60 AR49465-03. Genotyping services were provided by Algynomics company. Korean Genome Epidemiology Study (KoGES): Korean Genome Epidemiology Study (KoGES): This work was supported by the Research Program funded by the Korea Centers for Disease Control and Prevention (found 2001-347-6111-221, 2002-347-6111-221, 2009-E71007-00, 2010-E71004-00). Kora F3 and Kora F4: The KORA research platform was initiated and financed by the Helmholtz Center Munich, German Research Center for Environmental Health, which is funded by the German Federal Ministry of Education and Research (BMBF) and by the State of Bavaria. Part of this work was financed by the German National Genome Research Network (NGFN-2 and NGFNPlus: 01GS0823). Our research was supported within the Munich Center of Health Sciences (MC Health) as part of LMUinnovativ. LOLIP-REP-IA610: The study was supported by the Wellcome Trust. We thank the participants and research teams involved in LOLIPOP. LOLIP-REP-IA_I: The study was supported by the British Heart Foundation Grant SP/04/002. LOLIP-REP-IA_P: The study was supported by the British Heart Foundation Grant SP/04/002. METSIM: The study was supported by the Academy of Finland, the Finnish Diabetes Research Foundation, the Finnish Cardiovascular Research Foundation, the Strategic Research Funding from the University of Eastern Finland, Kuopio, and the EVO grant 5263 from the Kuopio University Hospital. MrOS Sweden: Financial support was received from the Swedish Research Council (2006-3832), the Swedish Foundation for Strategic Research, the ALF/LUA research grant in Gothenburg, the Lundberg Foundation, the Torsten and Ragnar Söderberg’s Foundation, Petrus and Augusta Hedlunds Foundation, the Västra Götaland Foundation, the Göteborg Medical Society, and the Novo Nordisk foundation. Greta and Johan Kock Foundation, A. Påhlsson Foundation, A. Osterlund Foundation, Malmö University Hospital Research Foundation, Research and Development Council of Region Skåne, Sweden, the Swedish Medical Society. MrOS US: The Osteoporotic Fractures in Men (MrOS) Study is supported by National Institutes of Health funding. The following institutes provide support: the National Institute on Aging (NIA), the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), the National Center for Advancing Translational Sciences (NCATS), and NIH Roadmap for Medical Research under the following grant numbers: U01 AG027810, U01 AG042124, U01 AG042139, U01 AG042140, U01 AG042143, U01 AG042145, U01 AG042168, U01 AR066160, and UL1 TR000128. The National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) provided funding for the MrOS ancillary study “GWAS in MrOS and SOF” under the grant number RC2ARO58973. Osteoporosis Prospective Risk Assessment study (OPRA): This work was supported by grants from the Swedish Research Council (K2009-53X-14691-07-3, K2010-77PK-21362-01-2), FAS (grant 2007-2125), Greta and Johan Kock Foundation, A. Påhlsson Foundation, A. Osterlund Foundation, Malmö University Hospital Research Foundation, Research and Development Council of Region Skåne, Sweden, the Swedish Medical Society. We are thankful to all the women who kindly participated in the study and to the staff at the Clinical and Molecular Osteoporosis Research Unit for helping in recruitment of study individuals. Orkney Complex Disease Study (ORCADES): ORCADES was supported by the Chief Scientist Office of the Scottish Government (CZB/4/276, CZB/4/710), the Royal Society, the MRC Human Genetics Unit, Arthritis Research UK (17539) and the European Union framework program 6 EUROSPAN project (contract no. LSHG-CT-2006-018947). DNA extractions were performed at the Wellcome Trust Clinical Research Facility in Edinburgh. We acknowledge the invaluable contributions of Lorraine Anderson and the research nurses in Orkney, the administrative team in Edinburgh and the people of Orkney. PEAK 25: This work was supported by grants from the Swedish Research Council (K2009-53X-14691-07-3, K2010-77PK-21362-01-2), FAS (grant 2007-2125), Greta and Johan Kock Foundation, A. Påhlsson Foundation, A. Osterlund Foundation, Malmö University Hospital Research Foundation, Research and Development Council of Region Skåne, Sweden, the Swedish Medical Society. We are thankful to all the women who kindly participated in the study and to the staff at the Clinical and Molecular Osteoporosis Research Unit for helping in recruitment of study individuals. Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS): The study was supported by grants from the Swedish research council (projects 2008-2202 and 2005-8214) and ALF/LUA research grants from Uppsala university hospital, Uppsala, Sweden. Relationship between Insulin Sensitivity and Cardiovascular Disease (RISC): The RISC study is supported by European Union Grant QLG1-CT-2001-01252 and AstraZeneca. We thank Merck Research Labs for conducting DNA genotyping on RISC samples.Rotterdam III: Rotterdam Study (RS): See discovery. SHIP and SHIP TREND: This work was supported by SHIP, which is part of the Community Medicine Research Network of the University of Greifswald, Germany, by the Federal Ministry of Education and Research (01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs as well as the Social Ministry of the Federal State of Mecklenburg-West Pomerania and the network “Greifswald Approach to Individualized Medicine (GANI_MED)” funded by the Federal Ministry of Education and Research (03IS2061A). Genome-wide data have been supported by the Federal Ministry of Education and Research (03ZIK012) and a joint grant from Siemens Healthcare, Erlangen, Germany, and the Federal State of Mecklenburg-West Pomerania. The University of Greifswald is a member of the “Center of Knowledge Interchange” program of the Siemens. A.G. and the Cache´ Campus program of the InterSystems GmbH. The SHIP authors are grateful to the contribution of Florian Ernst, Anja Wiechert, and Astrid Petersmann in generating the SNP data and to Mario Stanke for the opportunity to use his Server Cluster for SNP Imputation. Data analyses were further supported by the German Research Foundation (DFG Vo 955/10-1) and the Federal Ministry of Nutrition, Agriculture and Consumer’s Safety. SOF: The Study of Osteoporotic Fractures (SOF) is supported by National Institutes of Health funding. The National Institute on Aging (NIA) provides support under the following grant numbers: R01 AG005407, R01 AR35582, R01 AR35583, R01 AR35584, R01 AG005394, R01 AG027574, and R01 AG027576. The National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) provided funding for the SOF ancillary study “GWAS in MrOS and SOF” under the grant number RC2ARO58973. Uppsala Longitudinal Study of Adult Men (ULSAM): The study was funded by grants from the Swedish research council (projects 2008-2202 and 2005-8214), the Wallenberg foundation, and ALF/LUA research grants from Uppsala university hospital, Uppsala, Sweden. Andrew P. Morris is a Wellcome Trust Senior Fellow in Basic Biomedical Science, grant number WT098017. CROATIA-VIS (VIS): The CROATIA-Vis study was funded by grants from the Medical Research Council (UK) and Republic of Croatia Ministry of Science, Education and Sports research grants to I.R. (108-1080315-0302). We acknowledge the staff of several institutions in Croatia that supported the field work, including but not limited to The University of Split and Zagreb Medical Schools, the Institute for Anthropological Research in Zagreb and Croatian Institute for Public Health. The SNP genotyping for the CROATIA-Vis cohort was performed in the core genotyping laboratory of the Wellcome Trust Clinical Research Facility at the Western General Hospital, Edinburgh, Scotland. Women’s Health Initiative (WHI): The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, US Department of Health and Human Services through contracts N01WH22110, 24152, 32100–2, 32105–6, 32108–9, 32111–13, 32115, 32118–32119, 32122, 42107–26, 42129–32, and 44221. We thank the WHI investigators and staff for their dedication, and the study participants for making the program possible. A listing of WHI investigators can be found at https://www.whi.org/researchers/Documents%20%20Write%20a%20Paper/WHI%20Investigator%20Short%20List.pdf. FUSION: This research was supported in part by US National Institutes of Health grants 1-ZIA-HG000024 (to F.S.C.), U01DK062370 (to M.B.), R00DK099240 (to S.C.J.P.), the American Diabetes Association Pathway to Stop Diabetes Grant 1-14-INI-07 (to S.C.J.P.), and Academy of Finland Grants 271961 and 272741 (to M.L.) and 258753 (to H.A.K.). We thank all the subjects for participation and the study personnel for excellent technical assistance. The Pima Indian Study: This study was supported by the Intramural Research Program of the National Institute of Diabetes and Digestive and Kidney Diseases, NIH, USA. Studies of a Targeted Risk Reduction Intervention with Defined Exercise (STRRIDE): This study was supported by the National Heart Lung and Blood Institute of the National Institutes of Health, HL57453 (WEK). Gene expression in old and young muscle biopsies: S.M. and T.G. were supported in part by NIH U24AG051129.

The Indian Asian population accounts for a fifth of all global deaths from coronary heart disease (CHD). CHD deaths on the Indian subcontinent have doubled since 1990, and are predicted to rise a further 50% by 2030. Reasons underlying the increased CHD mortality among Indian Asians remain unknown. Although conventional cardiovascular risk factors contribute to CHD in Indian Asians as in other populations, these do not account for their increased risk. Type-2 diabetes, insulin resistance and related metabolic disturbances are more prevalent amongst Indian Asians than Europeans, and have been proposed as major determinants of higher CHD risk among Indian Asians. However, this view is not supported by prospective data. Genome-wide association studies have not identified differences in allele frequencies or effect sizes in known loci to explain the increased CHD risk in Indian Asians. Limited knowledge of mechanisms underlying higher CHD risk amongst Indian Asians presents a major obstacle to reducing the burden of CHD in this population. Systems biology approaches such as genomics, epigenomics, metabolomics and transcriptomics, provide a non-biased approach for discovery of novel biomarkers and disease pathways underlying CHD. Incorporation of these ‘omic’ approaches in prospective Indian Asian cohorts such as the London Life Sciences Population Study (LOLIPOP) provide an exciting opportunity for the identification of new risk factors underlying CHD in this high risk population.

DNA methylation plays a fundamental role in the regulation of the genome, but the optimal strategy for analysis of genome-wide DNA methylation data remains to be determined. We developed a comprehensive analysis pipeline for epigenome-wide association studies (EWAS) using the Illumina Infinium HumanMethylation450 BeadChip, based on 2,687 individuals, with 36 samples measured in duplicate. We propose new approaches to quality control, data normalisation and batch correction through control-probe adjustment and establish a null hypothesis for EWAS using permutation testing. Our analysis pipeline outperforms existing approaches, enabling accurate identification of methylation quantitative trait loci for hypothesis driven follow-up experiments.

Coronary artery disease (CAD) is the commonest cause of death. Here, we report an association analysis in 63,746 CAD cases and 130,681 controls identifying 15 loci reaching genome-wide significance, taking the number of susceptibility loci for CAD to 46, and a further 104 independent variants (r 2 < 0.2) strongly associated with CAD at a 5% false discovery rate (FDR). Together, these variants explain approximately 10.6% of CAD heritability. Of the 46 genome-wide significant lead SNPs, 12 show a significant association with a lipid trait, and 5 show a significant association with blood pressure, but none is significantly associated with diabetes. Network analysis with 233 candidate genes (loci at 10% FDR) generated 5 interaction networks comprising 85% of these putative genes involved in CAD. The four most significant pathways mapping to these networks are linked to lipid metabolism and inflammation, underscoring the causal role of these activities in the genetic etiology of CAD. Our study provides insights into the genetic basis of CAD and identifies key biological pathways. © 2013 Nature America, Inc. All rights reserved.

We carried out a trans-ancestry genome-wide association and replication study of blood pressure phenotypes among up to 320,251 individuals of East Asian, European and South Asian ancestry. We find genetic variants at 12 new loci to be associated with blood pressure (P = 3.9 x 10(-11) to 5.0 x 10(-21)). The sentinel blood pressure SNPs are enriched for association with DNA methylation at multiple nearby CpG sites, suggesting that, at some of the loci identified, DNA methylation may lie on the regulatory pathway linking sequence variation to blood pressure. The sentinel SNPs at the 12 new loci point to genes involved in vascular smooth muscle (IGFBP3, KCNK3, PDE3A and PRDM6) and renal (ARHGAP24, OSR1, SLC22A7 and TBX2) function. The new and known genetic variants predict increased left ventricular mass, circulating levels of NT-proBNP, and cardiovascular and all-cause mortality (P = 0.04 to 8.6 x 10(-6)). Our results provide new evidence for the role of DNA methylation in blood pressure regulation.

DNA methylation plays a fundamental role in the regulation of the genome, but the optimal strategy for analysis of genome-wide DNA methylation data remains to be determined. We developed a comprehensive analysis pipeline for epigenome-wide association studies (EWAS) using the Illumina Infinium HumanMethylation450 BeadChip, based on 2,687 individuals, with 36 samples measured in duplicate. We propose new approaches to quality control, data normalisation and batch correction through control-probe adjustment and establish a null hypothesis for EWAS using permutation testing. Our analysis pipeline outperforms existing approaches, enabling accurate identification of methylation quantitative trait loci for hypothesis driven follow-up experiments. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0600-x) contains supplementary material, which is available to authorized users.

Item does not contain fulltext Anaemia is a chief determinant of global ill health, contributing to cognitive impairment, growth retardation and impaired physical capacity. To understand further the genetic factors influencing red blood cells, we carried out a genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals. Here we identify 75 independent genetic loci associated with one or more red blood cell phenotypes at P < 10(-8), which together explain 4-9% of the phenotypic variance per trait. Using expression quantitative trait loci and bioinformatic strategies, we identify 121 candidate genes enriched in functions relevant to red blood cell biology. The candidate genes are expressed preferentially in red blood cell precursors, and 43 have haematopoietic phenotypes in Mus musculus or Drosophila melanogaster. Through open-chromatin and coding-variant analyses we identify potential causal genetic variants at 41 loci. Our findings provide extensive new insights into genetic mechanisms and biological pathways controlling red blood cell formation and function.

Background South Asians are at ~2 fold higher risk of cardiovascular disease (CVD) than Europeans. Physical inactivity is an independent risk factor for CVD, and may be more common in South Asians than Europeans. However, published studies of physical activity in South Asians have all relied on self-report by questionnaire, an approach of limited accuracy, confounded by linguistic, cultural and reporting bias. Accelerometers are validated tools for measurement of physical activity energy expenditure (PAEE) in Europeans, but are influenced by body habitus and device positioning. The accuracy of accelerometers in South Asians is not known. Aims To identify the accelerometer and accelerometer position that most accurately quantifies physical activity amongst South Asians, and to compare the accuracy of the chosen accelerometer between South Asians and Europeans. Methods We investigated 57 South Asians and 29 Europeans undergoing an exercise treadmill test (ETT) for clinical indications. All participants completed the treadmill test while simultaneously wearing 3 commercially available accelerometers in manufacturer recommended positions: i. Actigraph GT3X (3 positions - ankle, waist and wrist); ii. Geneactiv (3 positions - ankle, waist and wrist) and iii. Actiheart (chest only). Each participant thus had 7 device-position combinations. Personal and medical history was collected by questionnaire, followed by anthropometric measurements (height, weight, waist and hip circumference). We used linear regression and Bland-Altman plots to investigate the relationships between PAEE measured by the accelerometers (Measured) and actual PAEE on the treadmill (Actual). Results The relationship between Measured and Actual PAEE was highest for the Actigraph GT3X in the ankle position (regression beta: 0.55+/-0.03, Table). Wrist-worn devices consistently displayed poor PAEE prediction. Measured and Actual PAEE were similar amongst South Asians and Europeans for all accelerometers and positions (P > 0.05), including the ankle-worn Actigraph GT3X. However, even the ankle-worn Actigraph GT3X underestimated PAEE, especially at high workload (Figure). Conclusion The Actigraph GT3X is the most accurate device for measuring PAEE amongst both South Asians and Europeans. PAEE is best measured by the ankle-worn accelerometers followed by waist-worn accelerometers. Our results will inform the design of future studies to investigate the relationship between physical activity and CVD in the two populations. Relationship between Measured and Actual energy expenditure [beta (SE), from regression] in South Asians and Europeans.

Background National mortality statistics report that UK Indian Asians are at approxiamately 2 fold higher risk of cardiovascular disease mortality compared with people of European ancestry. However, previous studies in North American and European populations suggest that up to 40% of death certificates are incorrect, leading to an overestimation of cardiovascular disease mortality. The validity of routine death certification amongst Indian Asians is unknown. Aims and methods We investigated the accuracy of routine death certification amongst UK Indian Asians, to determine whether incorrect certification contributes to the reported higher cardiovascular disease amongst Indian Asians. We reviewed all available medical records (hospital, primary care and coroner) for a representative sample of 315 Indian Asians and Europeans who died in London, UK between 2002 and 2011. Deaths were independently coded as cardiovascular or non-cardiovascular according to published international diagnostic criteria by 2 cardiologists; where there was disagreement a third adjudicated. Results Age of death was lower amongst Indian Asians than Europeans (66.6 ± 10.1 vs. 69.7 ± 8.2, P = 0.003). Compared to review of records, routine death certification overestimated cardiovascular disease as underlying cause of death amongst Indian Asians (33.6 vs. 29.6%, p Conclusion Routine death certification overestimates cardiovascular deaths by ~20% amongst UK Indian Asians and Europeans, but the accuracy of death certification is similar in the two populations. Inaccurate death certification does not contribute to higher reported cardiovascular disease mortality amongst Indian Asians compared to Europeans.

Introduction Indian Asians have a twofold higher risk of cardiovascular disease compared to Europeans which is not explained by conventional cardiovascular risk factors or known genetic variants. The genetic architecture of Indian Asians has not previously been described. We hypothesised that whole genome sequencing of Indian Asians may identify both common and rare variants specific to this population that contribute to their increased cardiovascular disease risk. Methods We carried out whole genome sequencing (mean depth 28.4×) in eight men of Indian Asian origin participating in the London Life Sciences Population (LOLIPOP) study. Sequencing was carried out using paired end and mate pair libraries on an Illumina GA2 machine. Read alignment was done by BWA, and variants called using GATK and SAMtools. Sensitivity for single nucleotide polymorphism (SNP) detection was assessed by comparison to whole genome data. Results We identified 6 602 840 autosomal variants, 436 823 of which are novel SNPs. Of these, 50 585 appear to be common (present at least twice, corresponding to minor allele frequency >10%). We found 21 659 autosomal SNPs that were expected to affect protein coding, of which 2174 are novel. Among the coding SNPs identified, 145 are in genes linked to human diseases, such as obesity (FTO, UCP1), diabetes mellitus (CDKAL1, GCGR, HNF1B), lipid metabolism (APOB), hypertension (NOS2), and renal disease (NPHP4, PKD1). We also found 65 613 novel autosomal indels of which 35 097 are present at least twice, and 2301 novel deletions >100 bp. We show that >50% of the novel genetic variants are not in high LD (r2iÝ0.8) with tag SNPs and hence not captured on available high-density microarrays. Conclusions We identify more than 500 000 genetic variants not previously reported in 1000 genomes or dbSNP, and likely to be Indian Asian specific. The novel variants identified here are strong candidates for genetic factors underlying the increased risk of diabetes and cardiovascular disease among Indian Asians.