Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity.

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels

Obesity and Blood Pressure in 17-Year-Old Offspring of Mothers with Gestational Diabetes: Insights from the Jerusalem Perinatal Study

Objective. Gestational diabetes mellitus (GDM) influences fetal development and offspring's metabolic risk. We evaluated this association in 17-year-old offspring adjusting for birth weight (BW) and prepregnancy maternal BMI (mBMI). Study Design. The JPS birth cohort contains extensive data on 92,408 births from 1964 to 1976. Offspring's BMI and blood pressure (BP) were obtained from military records. For a subcohort born between 1974 and 1976, prepregnancy mBMI was available. Offspring were classified as born to mothers with GDM (n = 293) or born to mothers without recorded GDM (n = 59,499). Results. GDM offspring had higher mean BMI and systolic and diastolic BP compared to no-recorded-GDM offspring. After adjusting for BW, GDM remained significantly associated with offspring BMI and diastolic BP (β = 1.169 and 1.520, resp.). In the subcohort, when prepregnancy mBMI was entered to the models, it markedly attenuated the associations with GDM. Conclusions. Maternal characteristics have long-term effects on cardiometabolic outcomes of their offspring aged 17 years

Are C-Reactive Protein Associated Genetic Variants Associated with Serum Levels and Retinal Markers of Microvascular Pathology in Asian Populations from Singapore?

Introduction:C-reactive protein (CRP) levels are associated with cardiovascular disease and systemic inflammation. We assessed whether CRP-associated loci were associated with serum CRP and retinal markers of microvascular disease, in Asian populations.Methods:Genome-wide association analysis (GWAS) for serum CRP was performed in East-Asian Chinese (N = 2,434) and Malays (N = 2,542) and South-Asian Indians (N = 2,538) from Singapore. Leveraging on GWAS data, we assessed, in silico, association levels among the Singaporean datasets for 22 recently identified CRP-associated loci. At loci where directional inconsistencies were observed, quantification of inter-ethnic linkage disequilibrium (LD) difference was determined. Next, we assessed association for a variant at CRP and retinal vessel traits [central retinal artery equivalent (CRAE) and central retinal vein equivalent (CRVE)] in a total of 24,132 subjects of East-Asian, South-Asian and European ancestry.Results:Serum CRP was associated with SNPs in/near APOE, CRP, HNF1A and LEPR (p-values ≤4.7×10-8) after meta-analysis of Singaporean populations. Using a candidate-SNP approach, we further replicated SNPs at 4 additional loci that had been recently identified to be associated with serum CRP (IL6R, GCKR, IL6 and IL1F10) (p-values ≤0.009), in the Singaporean datasets. SNPs from these 8 loci explained 4.05% of variance in serum CRP. Two SNPs (rs2847281 and rs6901250) were detected to be significant (p-value ≤0.036) but with opposite effect directions in the Singaporean populations as compared to original European studies. At these loci we did not detect significant inter-population LD differences. We further did not observe a significant association between CRP variant and CRVE or CRAE levels after meta-analysis of all Singaporean and European datasets (p-value >0.058).Conclusions:Common variants associated with serum CRP, first detected in primarily European studies, are also associated with CRP levels in East-Asian and South-Asian populations. We did not find a causal link between CRP and retinal measures of microvascular disease

Genetic loci associated with plasma phospholipid N-3 fatty acids: A Meta-Analysis of Genome-Wide association studies from the charge consortium

Long-chain n-3 polyunsaturated fatty acids (PUFAs) can derive from diet or from α-linolenic acid (ALA) by elongation and desaturation. We investigated the association of common genetic variation with plasma phospholipid levels of the four major n-3 PUFAs by performing genome-wide association studies in five population-based cohorts comprising 8,866 subjects of European ancestry. Minor alleles of SNPs in FADS1 and FADS2 (desaturases) were associated with higher levels of ALA (p = 3×10-64) and lower levels of eicosapentaenoic acid (EPA, p = 5×10-58) and docosapentaenoic acid (DPA, p = 4×10-154). Minor alleles of SNPs in ELOVL2 (elongase) were associated with higher EPA (p = 2×10-12) and DPA (p = 1×10-43) and lower docosahexaenoic acid (DHA, p = 1×10-15). In addition to genes in the n-3 pathway, we identified a novel association of DPA with several SNPs in GCKR (glucokinase regulator, p = 1×10-8). We observed a weaker association between ALA and EPA among carriers of the minor allele of a representative SNP in FADS2 (rs1535), suggesting a lower rate of ALA-to-EPA conversion in these subjects. In samples of African, Chinese, and Hispanic ancestry, associations of n-3 PUFAs were similar with a representative SNP in FADS1 but less consistent with a representative SNP in ELOVL2. Our findings show that common variation in n-3 metabolic pathway genes and in GCKR influences plasma phospholipid levels of n-3 PUFAs in populations of European ancestry and, for FADS1, in other ancestries

Socioeconomic disparities in breast cancer incidence and survival among parous women: findings from a population-based cohort, 1964–2008

Background Socioeconomic position (SEP) has been associated with breast cancer incidence and survival. We examined the associations between two socioeconomic indicators and long-term breast cancer incidence and survival in a population-based cohort of parous women. Methods Residents of Jerusalem who gave birth between 1964–1976 (n = 40,586) were linked to the Israel Cancer Registry and Israel Population Registry to determine breast cancer incidence and vital status through mid-2008. SEP was assessed by husband’s occupation and the woman’s education. We used log ranks tests to compare incidence and survival curves by SEP, and Cox proportional hazard models to adjust for demographic, reproductive and diagnostic factors and assess effect modification by ethnic origin. Results In multivariable models, women of high SEP had a greater risk of breast cancer compared to women of low SEP (Occupation: HR 1.18, 95 % CI 1.03-1.35; Education: HR 1.39, 95 % CI 1.21-1.60) and women of low SEP had a greater risk of mortality after a breast cancer diagnosis (Occupation: HR 1.33, 95 % CI 1.04-1.70; Education: HR 1.37, 95 % CI 1.06-1.76). The association between education and survival was modified by ethnic origin, with a gradient effect observed only among women of European origin. Women of Asian, North African and Israeli origin showed no such trend. Conclusions SEP was associated with long-term breast cancer incidence and survival among Israeli Jews. Education had a stronger effect on breast cancer outcomes than occupation, suggesting that a behavioral mechanism may underlie disparities. More research is needed to explain the difference in the effect of education on survival among European women compared to women of other ethnicities

FTO genetic variants, dietary intake and body mass index: insights from 177 330 individuals

FTO is the strongest known genetic susceptibility locus for obesity. Experimental studies in animals suggest the potential roles of FTO in regulating food intake. The interactive relation among FTO variants, dietary intake and body mass index (BMI) is complex and results from previous often small-scale studies in humans are highly inconsistent. We performed large-scale analyses based on data from 177 330 adults (154 439 Whites, 5776 African Americans and 17 115 Asians) from 40 studies to examine: (i) the association between the FTO-rs9939609 variant (or a proxy single-nucleotide polymorphism) and total energy and macronutrient intake and (ii) the interaction between the FTO variant and dietary intake on BMI. The minor allele (A-allele) of the FTO-rs9939609 variant was associated with higher BMI in Whites (effect per allele = 0.34 [0.31, 0.37] kg/m2, P = 1.9 × 10−105), and all participants (0.30 [0.30, 0.35] kg/m2, P = 3.6 × 10−107). The BMI-increasing allele of the FTO variant showed a significant association with higher dietary protein intake (effect per allele = 0.08 [0.06, 0.10] %, P = 2.4 × 10−16), and relative weak associations with lower total energy intake (−6.4 [−10.1, −2.6] kcal/day, P = 0.001) and lower dietary carbohydrate intake (−0.07 [−0.11, −0.02] %, P = 0.004). The associations with protein (P = 7.5 × 10−9) and total energy (P = 0.002) were attenuated but remained significant after adjustment for BMI. We did not find significant interactions between the FTO variant and dietary intake of total energy, protein, carbohydrate or fat on BMI. Our findings suggest a positive association between the BMI-increasing allele of FTO variant and higher dietary protein intake and offer insight into potential link between FTO, dietary protein intake and adiposit

FTO genetic variants, dietary intake and body mass index: insights from 177 330 individuals

FTO is the strongest known genetic susceptibility locus for obesity. Experimental studies in animals suggest the potential roles of FTO in regulating food intake. The interactive relation among FTO variants, dietary intake and body mass index (BMI) is complex and results from previous often small-scale studies in humans are highly inconsistent. We performed large-scale analyses based on data from 177 330 adults (154 439 Whites, 5776 African Americans and 17 115 Asians) from 40 studies to examine: (i) the association between the FTO-rs9939609 variant (or a proxy single-nucleotide polymorphism) and total energy and macronutrient intake and (ii) the interaction between the FTO variant and dietary intake on BMI. The minor allele (A-allele) of the FTO-rs9939609 variant was associated with higher BMI in Whites (effect per allele = 0.34 [0.31, 0.37] kg/m2, P = 1.9 × 10−105), and all participants (0.30 [0.30, 0.35] kg/m2, P = 3.6 × 10−107). The BMI-increasing allele of the FTO variant showed a significant association with higher dietary protein intake (effect per allele = 0.08 [0.06, 0.10] %, P = 2.4 × 10−16), and relative weak associations with lower total energy intake (−6.4 [−10.1, −2.6] kcal/day, P = 0.001) and lower dietary carbohydrate intake (−0.07 [−0.11, −0.02] %, P = 0.004). The associations with protein (P = 7.5 × 10−9) and total energy (P = 0.002) were attenuated but remained significant after adjustment for BMI. We did not find significant interactions between the FTO variant and dietary intake of total energy, protein, carbohydrate or fat on BMI. Our findings suggest a positive association between the BMI-increasing allele of FTO variant and higher dietary protein intake and offer insight into potential link between FTO, dietary protein intake and adiposity

Interethnic analyses of blood pressure loci in populations of East Asian and European descent

AbstractBlood pressure (BP) is a major risk factor for cardiovascular disease and more than 200 genetic loci associated with BP are known. Here, we perform a multi-stage genome-wide association study for BP (max N = 289,038) principally in East Asians and meta-analysis in East Asians and Europeans. We report 19 new genetic loci and ancestry-specific BP variants, conforming to a common ancestry-specific variant association model. At 10 unique loci, distinct non-rare ancestry-specific variants colocalize within the same linkage disequilibrium block despite the significantly discordant effects for the proxy shared variants between the ethnic groups. The genome-wide transethnic correlation of causal-variant effect-sizes is 0.898 and 0.851 for systolic and diastolic BP, respectively. Some of the ancestry-specific association signals are also influenced by a selective sweep. Our results provide new evidence for the role of common ancestry-specific variants and natural selection in ethnic differences in complex traits such as BP.AcknowledgementsMarie Loh71,72 (Institute of Health Sciences, University of Oulu, P.O.Box 5000FI-90014 Oulu, Finland and Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK),Niek Verweij73 (Department of Cardiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Weihua Zhang72,74 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK and Ealing Hospital NHS Trust, Middlesex UB1 3HW, UK),Benjamin Lehne72 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK),Irene Mateo Leach73 (Department of Cardiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Alexander Drong75 (Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK),James Abbott76 (Bioinformatics Support Service, Imperial College London, South Kensington, London SW7 2AZ, UK),Sian-Tsung Tan74,77 (Ealing Hospital NHS Trust, Middlesex UB1 3HW, UK and National Heart and Lung Institute, Imperial College London, London W12 0NN, UK),William R. Scott72,77 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK and Lung Institute, Imperial College London, London W12 0NN, UK),Gianluca Campanella72 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK),Marc Chadeau-Hyam72 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK),Uzma Afzal72,74 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK and Ealing Hospital NHS Trust, Middlesex UB1 3HW, UK),Tõnu Esko78,79,80,81 (Estonian Genome Center, University of Tartu, Riia 23c, 51010 Tartu, Estonia and Division of Endocrinology, Children’s Hospital Boston, Longwood 300, Boston, MA 02115, USA and Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA and Program in Medical and Population Genetics, Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA),Sarah E. Harris82,83 (Medical Genetics Section, University of Edinburgh Molecular Medicine Centre and MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, UK and Centre for Cognitive Aging and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK),Jaana Hartiala84,85 (Department of Preventive Medicine, USC Keck School of Medicine, Los Angeles, CA 90033, USA and Institute for Genetic Medicine, USC Keck School of Medicine, Los Angeles, CA 90033, USA),Marcus E. Kleber86 (Medical Clinic V, Mannheim Medical Faculty, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany),Richa Saxena87 (Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA),Alexandre F.R. Stewart88,89 (University of Ottawa Heart Institute, Cardiovascular Research Methods Centre, Ontario K1Y 4W7, Canada and Ruddy Canadian Cardiovascular Genetics Centre, Ontario K1Y 4W7, Canada),Tarunveer S. Ahluwalia90 (Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark),Imke Aits91 (Institute of Epidemiology and Biobank Popgen, Christian-Albrechts-University of Kiel, 24105 Kiel, Germany),Alexessander Da Silva Couto Alves92 (Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPE) Centre for Environment and Health, School of Public Health, Imperial College London, London SW7 2AZ, UK),Shikta Das92 (Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPE) Centre for Environment and Health, School of Public Health, Imperial College London, London SW7 2AZ, UK),Jemma C. Hopewell93 (Clinical Trial Service Unit & Epidemiological Studies Unit, University of Oxford, Richard Doll Building, Old Road Campus, Roosevelt Drive, Oxford OX3 7LF, UK),Robert W. Koivula94 (Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Skåne University Hospital Malmö, SE-205 02 Malmö, Sweden),Leo-Pekka Lyytikäinen95,96 (Department of Clinical Chemistry, Fimlab Laboratories, FI-33520 Tampere, Finland and Department of Clinical Chemistry, University of Tampere School of Medicine, FI-33014 Tampere, Finland),Iris Postmus97,98 (Department of Gerontology and Geriatrics, Leiden University Medical Center, 2300 RC Leiden, Netherlands and Netherlands Consortium for Healthy Ageing, Leiden 2333 ZC, Netherlands),Olli T. Raitakari99,100 (Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, FI-20521 Turku, Finland and Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, FI-20520 Turku, Finland),Robert A. Scott101 (MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0QQ, UK),Rossella Sorice102 (Institute of Genetics and Biophysics A. Buzzati-Traverso, CNR, 80131 Naples, Italy),Vinicius Tragante103 (Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, 3508 GA Utrecht, Netherlands),Michela Traglia104,105 (Division of Genetics and Cell Biology, San Raffaele Scientific Institute, 20132 Milano, Italy and Institute for Maternal and Child Health—IRCCS ‘‘Burlo Garofolo’’—Trieste, 34137 Trieste, Italy),Jon White106 (UCL Genetics Institute, Department of Genetics, Environment and Evolution, UCL, London WC1E 6BT, UK),Inês Barroso107,108,109 (Metabolic Disease Group, The Wellcome Trust Sanger Institute, Cambridge CB10 1SA, UK and NIHR Cambridge Biomedical Research Centre, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK and University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK),Andrew Bjonnes87 (Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA),Rory Collins103 (Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, 3508 GA Utrecht, Netherlands),Gail Davies110 (Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK),Graciela Delgado86 (Medical Clinic V, Mannheim Medical Faculty, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany),Pieter A. Doevendans103 (Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, 3508 GA Utrecht, Netherlands),Lude Franke111 (Department of Genetics, University Medical Center, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Ron T. Gansevoort112 (Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Tanja B. Grammer86 (Medical Clinic V, Mannheim Medical Faculty, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany),Niels Grarup86 (Medical Clinic V, Mannheim Medical Faculty, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany),Jagvir Grewal72,74 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK and Ealing Hospital NHS Trust, Middlesex UB1 3HW, UK),Anna-Liisa Hartikainen113,114 (Department of Obstetrics and Gynecology, University Hospital of Oulu, University of Oulu, Oulu FI-90014, Finland and Department of Clinical Sciences/Obsterics and Gynecology, University of Oulu, Oulu FI-90014, Finland),Stanley L. Hazen115,116 (Center for Cardiovascular Diagnostics and Prevention, Cleveland Clinic, Cleveland, OH 44195, USA and Department of Cellular and Molecular Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA),Chris Hsu117 (Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA),Lise L.N. Husemoen118 (Research Centre for Prevention and Health, Glostrup University Hospital, 2600 Glostrup, Denmark),Johanne M. Justesen90 (Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark),Meena Kumari119 (Department of Epidemiology and Public Health, UCL, London WC1E 6BT, UK),Wolfgang Lieb91 (Institute of Epidemiology and Biobank Popgen, Christian-Albrechts-University of Kiel, 24105 Kiel, Germany),David C.M. Liewald110 (Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK),Evelin Mihailov78 (Estonian Genome Center, University of Tartu, Riia 23c, 51010 Tartu, Estonia),Lili Milani78 (Estonian Genome Center, University of Tartu, Riia 23c, 51010 Tartu, Estonia),Rebecca Mills74 (Ealing Hospital NHS Trust, Middlesex UB1 3HW, UK),Nina Mononen95,96 (Department of Clinical Chemistry, Fimlab Laboratories, FI-33520 Tampere, Finland and Department of Clinical Chemistry, University of Tampere School of Medicine, FI-33014 Tampere, Finland),Kjell Nikus120 (Heart Centre, Department of Cardiology, Tampere University Hospital, and University of Tampere School of Medicine, FI-33521 Tampere, Finland),Teresa Nutile102 (Institute of Genetics and Biophysics A. Buzzati-Traverso, CNR, 80131 Naples, Italy),Sarah Parish93 (Clinical Trial Service Unit & Epidemiological Studies Unit, University of Oxford, Richard Doll Building, Old Road Campus, Roosevelt Drive, Oxford OX3 7LF, UK),Olov Rolandsson121 (Department of Public Health & Clinical Medicine, Section for Family Medicine, Umeå universitet, SE-901 85 Umeå, Sweden),Daniela Ruggiero102 (Institute of Genetics and Biophysics A. Buzzati-Traverso, CNR, 80131 Naples, Italy),Cinzia F. Sala104 (Division of Genetics and Cell Biology, San Raffaele Scientific Institute, 20132 Milano, Italy),Harold Snieder122 (Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Thomas H.W. Spasø90 (Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark),Wilko Spiering123 (Department of Vascular Medicine, University Medical Center Utrecht, 3508 GA Utrecht, Netherlands),John M. Starr83,124 (Centre for Cognitive Aging and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK and Alzheimer Scotland Dementia Research Centre, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK),David J. Stott125 (Academic Section of Geriatric Medicine, Institute of Cardiovascular and Medical Sciences, Faculty of Medicine, University of Glasgow, Glasgow G4 0SF, UK),Daniel O. Stram117 (Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA),Silke Szymczak126 (Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel 24105, Germany),W.H.Wilson Tang115,116 (Center for Cardiovascular Diagnostics and Prevention, Cleveland Clinic, Cleveland, OH 44195, USA and Department of Cellular and Molecular Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA),Stella Trompet127 (Department of Cardiology, Leiden University Medical Center, 2300 RC Leiden, Netherlands),Väinö Turjanmaa128,129 (Department of Clinical Physiology, Tampere University Hospital, FI-33521 Tampere, Finland and Department of Clinical Physiology, University of Tampere School of Medicine, FI-33014 Tampere, Finland),Marja Vaarasmaki130 (Department of Obstetrics and Gynecology, Oulu University Hospital, PO Box 23FI-90029 Oulu, Finland),Wiek H. van Gilst73 (Department of Cardiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Dirk J. van Veldhuisen73 (Department of Cardiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Jorma S. Viikari131,132 (Department of Medicine, Turku University Hospital, FI-20521 Turku, Finland and Department of Medicine, University of Turku, FI-20014 Turku, Finland),Folkert W. Asselbergs103,133,134 (Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, 3508 GA Utrecht, Netherlands and Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, 3511 GC Utrecht, Netherlands and Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London WC1E 6BT, UK),Marina Ciullo102 (Institute of Genetics and Biophysics A. Buzzati-Traverso, CNR, 80131 Naples, Italy),Andre Franke126 (Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel 24105, Germany),Paul W. Franks94,121,135 (Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Skåne University Hospital Malmö, SE-205 02 Malmö, Sweden and Department of Public Health & Clinical Medicine, Section for Family Medicine, Umeå universitet, SE-901 85 Umeå, Sweden and Department of Nutrition, Harvard School of Public Health, Boston, MA 02115, USA),Steve Franks136 (Institute of Reproductive and Developmental Biology, Imperial College London, Hammersmith Hospital, London W120HS, UK),Myron D. Gross137 (School of Medicine, University of Minnesota, Minneapolis, MN 55455, USA),Torben Hansen90 (Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark),Marjo-Riitta Jarvelin72,92,138,139,140 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK and Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPE) Centre for Environment and Health, School of Public Health, Imperial College London, London SW7 2AZ, UK and Biocenter Oulu, University of Oulu, P.O. Box 5000 Aapistie 5A, FI-90014 Oulu, Finland and Unit of Primary Care, Oulu University Hospital, Kajaanintie 50 P.O.Box 20FI-90220 Oulu, Finland and Department of Children and Young People and Families, National Institute for Health and Welfare, Aapistie 1, Box 310, FI-90101 Oulu, Finland),Torben Jørgensen118 (Research Centre for Prevention and Health, Glostrup University Hospital, 2600 Glostrup, Denmark),Wouter J. Jukema127,133,141 (Department of Cardiology, Leiden University Medical Center, 2300 RC Leiden, Netherlands and Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, 3511 GC Utrecht, Netherlands and Interuniversity Cardiology Institute of the Netherlands, Utrecht 3511 EP, Netherlands),Mika Kähönen128,129 (Department of Clinical Physiology, Tampere University Hospital, FI-33521 Tampere, Finland and Department of Clinical Physiology, University of Tampere School of Medicine, FI-33014 Tampere, Finland),Mika Kivimaki119 (Department of Epidemiology and Public Health, UCL, London WC1E 6BT, UK),Terho Lehtimäki95,96 (Department of Clinical Chemistry, Fimlab Laboratories, FI-33520 Tampere, Finland and Department of Clinical Chemistry, University of Tampere School of Medicine, FI-33014 Tampere, Finland),Allan Linneberg118 (Research Centre for Prevention and Health, Glostrup University Hospital, 2600 Glostrup, Denmark),Oluf Pedersen90 (Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark),Nilesh J. Samani142,143 (Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester LE3 9QP, UK and National Institute for Health Research Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester LE3 9QP, UK),Daniela Toniolo104,144 (Division of Genetics and Cell Biology, San Raffaele Scientific Institute, 20132 Milano, Italy and Institute of Molecular GeneticsCNR, 27100 Pavia, Italy),Hooman Allayee84,85 (Department of Preventive Medicine, USC Keck School of Medicine, Los Angeles, CA 90033, USA and Institute for Genetic Medicine, USC Keck School of Medicine, Los Angeles, CA 90033, USA),Ian J. Deary83,110 (Centre for Cognitive Aging and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK and Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK),Winfried März86,145,146 (Medical Clinic V, Mannheim Medical Faculty, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany and Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Auenbruggerplatz 15, 8036 Graz, Austria and Synlab Academy, Synlab Services GmbH, Gottlieb-Daimler-Straße 25, 68165 Mannheim, Germany),Andres Metspalu78 (Estonian Genome Center, University of Tartu, Riia 23c, 51010 Tartu, Estonia),Cisca Wijmenga111 (Department of Genetics, University Medical Center, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Bruce H.W. Wolffenbuttel147 (Department of Endocrinology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Paolo Vineis72 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK),Soterios A. KyrtopoulosNational Hellenic Research Foundation, Institute of Biological Research and Biotechnology, Athens 116 35, Greece),Jos C.S. Kleinjans149 (Department of Toxicogenomics, Maastricht University, Universiteitssingel 50, 6229ER Maastricht, Netherlands),Mark I. McCarthy75,150 (Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK and Oxford Centre for Diabetes Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LE, UK),James Scott77 (National Heart and Lung Institute, Imperial College London, London W12 0NN, UK)Abstract Blood pressure (BP) is a major risk factor for cardiovascular disease and more than 200 genetic loci associated with BP are known. Here, we perform a multi-stage genome-wide association study for BP (max N = 289,038) principally in East Asians and meta-analysis in East Asians and Europeans. We report 19 new genetic loci and ancestry-specific BP variants, conforming to a common ancestry-specific variant association model. At 10 unique loci, distinct non-rare ancestry-specific variants colocalize within the same linkage disequilibrium block despite the significantly discordant effects for the proxy shared variants between the ethnic groups. The genome-wide transethnic correlation of causal-variant effect-sizes is 0.898 and 0.851 for systolic and diastolic BP, respectively. Some of the ancestry-specific association signals are also influenced by a selective sweep. Our results provide new evidence for the role of common ancestry-specific variants and natural selection in ethnic differences in complex traits such as BP.Acknowledgements Marie Loh71,72 (Institute of Health Sciences, University of Oulu, P.O.Box 5000FI-90014 Oulu, Finland and Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK),Niek Verweij73 (Department of Cardiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Weihua Zhang72,74 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK and Ealing Hospital NHS Trust, Middlesex UB1 3HW, UK),Benjamin Lehne72 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK),Irene Mateo Leach73 (Department of Cardiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groning

Association analyses of East Asian individuals and trans-ancestry analyses with European individuals reveal new loci associated with cholesterol and triglyceride levels

Large-scale meta-analyses of genome-wide association studies (GWAS) have identified >175 loci associated with fasting cholesterol levels, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). With differences in linkage disequilibrium (LD) structure and allele frequencies between ancestry groups, studies in additional large samples may detect new associations. We conducted staged GWAS meta-analyses in up to 69,414 East Asian individuals from 24 studies with participants from Japan, the Philippines, Korea, China, Singapore, and Taiwan. These meta-analyses identified (P < 5 × 10-8) three novel loci associated with HDL-C near CD163-APOBEC1 (P = 7.4 × 10-9), NCOA2 (P = 1.6 × 10-8), and NID2-PTGDR (P = 4.2 × 10-8), and one novel locus associated with TG near WDR11-FGFR2 (P = 2.7 × 10-10). Conditional analyses identified a second signal near CD163-APOBEC1. We then combined results from the East Asian meta-analysis with association results from up to 187,365 European individuals from the Global Lipids Genetics Consortium in a trans-ancestry meta-analysis. This analysis identified (log10Bayes Factor ≥6.1) eight additional novel lipid loci. Among the twelve total loci identified, the index variants at eight loci have demonstrated at least nominal significance with other metabolic traits in prior studies, and two loci exhibited coincident eQTLs (P < 1 × 10-5) in subcutaneous adipose tissue for BPTF and PDGFC. Taken together, these analyses identified multiple novel lipid loci, providing new potential therapeutic targets