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Admixture Mapping of Quantitative Trait Loci for BMI in African Americans: Evidence for Loci on Chromosomes 3q, 5q, and 15q
dc.contributor.authorBasu, Analabhaen_US
dc.contributor.authorTang, Huaen_US
dc.contributor.authorArnett, Donnaen_US
dc.contributor.authorGu, C. Charlesen_US
dc.contributor.authorMosley, Tomen_US
dc.contributor.authorKardia, Sharonen_US
dc.contributor.authorLuke, Amyen_US
dc.contributor.authorTayo, Bamideleen_US
dc.contributor.authorCooper, Richarden_US
dc.contributor.authorZhu, Xiaofengen_US
dc.contributor.authorRisch, Neilen_US
dc.date.accessioned2012-10-02T17:20:24Z
dc.date.available2012-10-02T17:20:24Z
dc.date.issued2009-06en_US
dc.identifier.citationBasu, Analabha; Tang, Hua; Arnett, Donna; Gu, C. Charles; Mosley, Tom; Kardia, Sharon; Luke, Amy; Tayo, Bamidele; Cooper, Richard; Zhu, Xiaofeng; Risch, Neil (2009). "Admixture Mapping of Quantitative Trait Loci for BMI in African Americans: Evidence for Loci on Chromosomes 3q, 5q, and 15q." Obesity 17(6). <http://hdl.handle.net/2027.42/93743>en_US
dc.identifier.issn1930-7381en_US
dc.identifier.issn1930-739Xen_US
dc.identifier.urihttps://hdl.handle.net/2027.42/93743
dc.publisherWiley Periodicals, Inc.en_US
dc.publisherBlackwell Publishing Ltden_US
dc.titleAdmixture Mapping of Quantitative Trait Loci for BMI in African Americans: Evidence for Loci on Chromosomes 3q, 5q, and 15qen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelEndocrinologyen_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USAen_US
dc.contributor.affiliationotherDepartment of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, Ohio, USAen_US
dc.contributor.affiliationotherDepartment of Epidemiology and Biostatistics, University of California, San Francisco, California, USAen_US
dc.contributor.affiliationotherDivision of Research, Kaiser Permanente, Oakland, California, USAen_US
dc.contributor.affiliationotherInstitute for Human Genetics, University of California, San Francisco, California, USAen_US
dc.contributor.affiliationotherDepartment of Genetics, Stanford University, Stanford, California, USAen_US
dc.contributor.affiliationotherDepartment of Epidemiology, School of Public Health, University of Alabama, Birmingham, Alabama, USAen_US
dc.contributor.affiliationotherDivision of Biostatistics, Washington University School of Medicine, St Louis, Missouri, USAen_US
dc.contributor.affiliationotherDepartment of Epidemiology, University of Mississippi Medical Center, Jackson, Mississippi, USAen_US
dc.contributor.affiliationotherDepartment of Preventive Medicine & Epidemiology, Loyola University, Maywood, Illinois, USAen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/93743/1/oby_1443_sm_2.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/93743/2/oby_1443_sm_1.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/93743/3/oby.2009.24.pdf
dc.identifier.doi10.1038/oby.2009.24en_US
dc.identifier.sourceObesityen_US
dc.identifier.citedreferenceGorlova OY, Amos CI, Wang NW et al. Genetic linkage and imprinting effects on body mass index in children and young adults. Eur J Hum Genet 2003; 11: 425 – 432.en_US
dc.identifier.citedreferenceFrayling TM, Timpson NJ, Weedon MN et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 2007; 316: 889 – 894.en_US
dc.identifier.citedreferenceBenzinou M, Creemers JW, Choquet H et al. Common nonsynonymous variants in PCSK1 confer risk of obesity. Nat Genet 2008; 40: 943 – 945.en_US
dc.identifier.citedreferenceRisch N. Mapping Genes for complex diseases using association studies in admixed populations. Am J Hum Genet 1992; 51: 13.en_US
dc.identifier.citedreferenceStephens JC, Briscoe D, O'Brien SJ. Mapping by admixture linkage disequilibrium in human populations: limits and guidelines. Am J Hum Genet 1994; 55: 809 – 824.en_US
dc.identifier.citedreferenceZhu X, Luke A, Cooper RS et al. Admixture mapping for hypertension loci with genome‐scan markers. Nat Genet 2005; 37: 177 – 181.en_US
dc.identifier.citedreferenceParra EJ, Kittles RA, Argyropoulos G et al. Ancestral proportions and admixture dynamics in geographically defined African Americans living in South Carolina. Am J Phys Anthropol 2001; 114: 18 – 29.en_US
dc.identifier.citedreferenceParra EJ, Marcini A, Akey J et al. Estimating African American admixture proportions by use of population‐specific alleles. Am J Hum Genet 1998; 63: 1839 – 1851.en_US
dc.identifier.citedreferenceTang H, Jorgenson E, Gadde M et al. Racial admixture and its impact on BMI and blood pressure in African and Mexican Americans. Hum Genet 2006; 119: 624 – 633.en_US
dc.identifier.citedreferenceFernandez JR, Shriver MD, Beasley TM et al. Association of African genetic admixture with resting metabolic rate and obesity among women. Obes Res 2003; 11: 904 – 911.en_US
dc.identifier.citedreferenceShaffer JR, Kammerer CM, Reich D et al. Genetic markers for ancestry are correlated with body composition traits in older African Americans. Osteoporos Int 2007; 18: 733 – 741.en_US
dc.identifier.citedreferenceReiner AP, Carlson CS, Ziv E et al. Genetic ancestry, population sub‐structure, and cardiovascular disease‐related traits among African‐American participants in the CARDIA Study. Hum Genet 2007; 121: 565 – 575.en_US
dc.identifier.citedreferenceFBPP Investigators. Multi‐center genetic study of hypertension: The Family Blood Pressure Program (FBPP). Hypertension 2002; 39: 3 – 9.en_US
dc.identifier.citedreferencePritchard JK, Stephens M, Donnelly P. Inference of population structure using multilocus genotype data. Genetics 2000; 155: 945 – 959.en_US
dc.identifier.citedreferenceFalush D, Stephens M, Pritchard JK. Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 2003; 164: 1567 – 1587.en_US
dc.identifier.citedreferenceRosenberg NA, Pritchard JK, Weber JL et al. Genetic structure of human populations. Science 2002; 298: 2381 – 2385.en_US
dc.identifier.citedreferenceBarreto‐Filho JA, Alcantara MR, Salvatori R et al. Familial isolated growth hormone deficiency is associated with increased systolic blood pressure, central obesity, and dyslipidemia. J Clin Endocrinol Metab 2002; 87: 2018 – 2023.en_US
dc.identifier.citedreferenceBrockmann GA, Haley CS, Renne U, Knott SA, Schwerin M. Quantitative trait loci affecting body weight and fatness from a mouse line selected for extreme high growth. Genetics 1998; 150: 369 – 381.en_US
dc.identifier.citedreferenceAdeyemo A, Luke A, Cooper R et al. A genome‐wide scan for body mass index among Nigerian families. Obes Res 2003; 11: 266 – 273.en_US
dc.identifier.citedreferenceChen W, Li S, Cook NR et al. An autosomal genome scan for loci influencing longitudinal burden of body mass index from childhood to young adulthood in white sibships: the Bogalusa Heart Study. Int J Obes Relat Metab Disord 2004; 28: 462 – 469.en_US
dc.identifier.citedreferenceHsueh WC, Mitchell BD, Schneider JL et al. Genome‐wide scan of obesity in the Old Order Amish. J Clin Endocrinol Metab 2001; 86: 1199 – 1205.en_US
dc.identifier.citedreferenceChaves FJ, Giner V, Corella D et al. Body weight changes and the A‐6G polymorphism of the angiotensinogen gene. Int J Obes Relat Metab Disord 2002; 26: 1173 – 1178.en_US
dc.identifier.citedreferenceHegele RA, Brunt JH, Connelly PW. Genetic variation on chromosome 1 associated with variation in body fat distribution in men. Circulation 1995; 92: 1089 – 1093.en_US
dc.identifier.citedreferencePrat‐Larquemin L, Oppert JM, Clement K et al. Adipose angiotensinogen secretion, blood pressure, and AGT M235T polymorphism in obese patients. Obes Res 2004; 12: 556 – 561.en_US
dc.identifier.citedreferenceCollaku A, Rankinen T, Rice T et al. A genome‐wide linkage scan for dietary energy and nutrient intakes: the Health, Risk Factors, Exercise Training, and Genetics (HERITAGE) Family Study. Am J Clin Nutr 2004; 79: 881 – 886.en_US
dc.identifier.citedreferenceChen G, Adeyemo AA, Johnson T et al. A genome‐wide scan for quantitative trait loci linked to obesity phenotypes among West Africans. Int J Obes (Lond) 2005; 29: 255 – 259.en_US
dc.identifier.citedreferenceBell CG, Benzinou M, Siddiq A et al. Genome‐wide linkage analysis for severe obesity in French Caucasians finds significant susceptibility locus on chromosome 19q. Diabetes 2004; 53: 1857 – 1865.en_US
dc.identifier.citedreferenceRice T, Chagnon YC, Perusse L et al. A genomewide linkage scan for abdominal subcutaneous and visceral fat in black and white families: the HERITAGE Family Study. Diabetes 2002; 51: 848 – 855.en_US
dc.identifier.citedreferenceClement K, Philippi A, Jury C et al. Candidate gene approach of familial morbid obesity: linkage analysis of the glucocorticoid receptor gene. Int J Obes Relat Metab Disord 1996; 20: 507 – 512.en_US
dc.identifier.citedreferenceVijayaraghavan S, Hitman GA, Kopelman PG. Apolipoprotein‐D polymorphism: a genetic marker for obesity and hyperinsulinemia. J Clin Endocrinol Metab 1994; 79: 568 – 570.en_US
dc.identifier.citedreferenceChagnon YC, Borecki IB, Perusse L et al. Genome‐wide search for genes related to the fat‐free body mass in the Quebec family study. Metabolism 2000; 49: 203 – 207.en_US
dc.identifier.citedreferenceBouchard L, Bouchard C, Chagnon YC, Perusse L. Evidence of linkage and association with body fatness and abdominal fat on chromosome 15q26. Obesity (Silver Spring) 2007; 15: 2061 – 2070.en_US
dc.identifier.citedreferenceBouchard L, Drapeau V, Provencher V et al. Neuromedin beta: a strong candidate gene linking eating behaviors and susceptibility to obesity. Am J Clin Nutr 2004; 80: 1478 – 1486.en_US
dc.identifier.citedreferenceLewis CE, North KE, Arnett D et al. Sex‐specific findings from a genome‐wide linkage analysis of human fatness in non‐Hispanic whites and African Americans: the HyperGEN study. Int J Obes (Lond) 2005; 29: 639 – 649.en_US
dc.identifier.citedreferenceU.S. Department of Health and Human Services, National Institutes of Health. Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults: The Evidence Report. NHLBI document 98‐4083, 2000.en_US
dc.identifier.citedreferenceCenters for Disease Control and Prevention. U.S. Obesity Trends 1985–2006.en_US
dc.identifier.citedreferenceBleich S, Cutler D, Murray C, Adams A. Why is the developed world obese? Annu Rev Public Health 2008; 29: 273 – 295.en_US
dc.identifier.citedreferenceBell CG, Walley AJ, Froguel P. The genetics of human obesity. Nat Rev Genet 2005; 6: 221 – 234.en_US
dc.identifier.citedreferenceRankinen T, Zuberi A, Chagnon YC et al. The human obesity gene map: the 2005 update. Obesity (Silver Spring) 2006; 14: 529 – 644.en_US
dc.identifier.citedreferenceZhu X, Cooper RS, Luke A et al. A genome‐wide scan for obesity in African‐Americans. Diabetes 2002; 51: 541 – 544.en_US
dc.identifier.citedreferenceWu X, Cooper RS, Borecki I et al. A combined analysis of genomewide linkage scans for body mass index from the National Heart, Lung, and Blood Institute Family Blood Pressure Program. Am J Hum Genet 2002; 70: 1247 – 1256.en_US
dc.identifier.citedreferenceVaisse C, Clement K, Durand E et al. Melanocortin‐4 receptor mutations are a frequent and heterogeneous cause of morbid obesity. J Clin Invest 2000; 106: 253 – 262.en_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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