Post genome-wide association study challenges for lipid traits: describing age as a modifier of gene-lipid associations in the Population Architecture using Genomics and Epidemiology (PAGE) study

Logan Dumitrescu; Cara L Carty; Nora Franceschini; Lucia A Hindorff; Shelley A Cole; Petra Bůžková; Fredrick R Schumacher; Charles B Eaton; Robert J Goodloe; David J Duggan; Jeff Haessler; Barbara Cochran; Brian E Henderson; Iona Cheng; Karen C Johnson; Chris S Carlson; Shelly-Ann Love; Kristin Brown-Gentry; Alejandro Q Nato; Miguel Quibrera; Garnet Anderson; Ralph V Shohet; José Luis Ambite; Lynne R Wilkens; Loïc Le Marchand; Christopher A Haiman; Steven Buyske; Charles Kooperberg; Kari E North; Myriam Fornage; Dana C Crawford

doi:10.1111/ahg.12027

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Post genome-wide association study challenges for lipid traits: describing age as a modifier of gene-lipid associations in the Population Architecture using Genomics and Epidemiology (PAGE) study

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Post genome-wide association study challenges for lipid traits: describing age as a modifier of gene-lipid associations in the Population Architecture using Genomics and Epidemiology (PAGE) study

Logan Dumitrescu, Cara L Carty, Nora Franceschini, Lucia A Hindorff, Shelley A Cole, Petra Bůžková, Fredrick R Schumacher, Charles B Eaton, Robert J Goodloe, David J Duggan, …

Annals of human genetics, Vol.77(5), pp.416-425

09/2013

DOI: https://doi.org/10.1111/ahg.12027

PMCID: PMC3796061

PMID: 23808484

Abstract

age

genetic association

lipids

modifier

PAGE

Numerous common genetic variants that influence plasma high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) distributions have been identified via genome-wide association studies (GWAS). However, whether or not these associations are age dependent has largely been overlooked. We conducted an association study and meta-analysis in more than 22,000 European Americans between 49 previously identified GWAS variants and the three lipid traits, stratified by age (males: <50 or ≥50 years of age; females: pre- or post-menopausal). For each variant, a test of heterogeneity was performed between the two age strata and significant P het values were used as evidence of age-specific genetic effects. We identified seven associations in females and eight in males that displayed suggestive heterogeneity by age (P het <0.05). The association between rs174547 ( FADS1) and LDL-C in males displayed the most evidence for heterogeneity between age groups (P het =1.74E-03, I 2 =89.8), with a significant association in older males (P=1.39E-06) but not younger males (P=0.99). However, none of the suggestive modifying effects survived adjustment for multiple testing, highlighting the challenges of identifying modifiers of modest SNP-trait associations despite large sample sizes.

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Title: Post genome-wide association study challenges for lipid traits: describing age as a modifier of gene-lipid associations in the Population Architecture using Genomics and Epidemiology (PAGE) study
Creators: Logan Dumitrescu - Center for Human Genetics Research, Vanderbilt University, Nashville, TN
Cara L Carty - Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
Nora Franceschini - Department of Epidemiology, University of North Carolina, Chapel Hill, NC
Lucia A Hindorff - Office of Population Genomics, National Human Genome Research Institute, Bethesda, MD
Shelley A Cole - Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX
Petra Bůžková - Department of Biostatistics, University of Washington, Seattle, WA
Fredrick R Schumacher - Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA
Charles B Eaton - Department of Family Medicine, Warren Alpert Medical School, Brown University, Providence, RI
Robert J Goodloe - Center for Human Genetics Research, Vanderbilt University, Nashville, TN
David J Duggan - Translational Genomics Research Institute, Phoenix, AZ
Jeff Haessler - Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
Barbara Cochran - Baylor College of Medicine, Houston, TX
Brian E Henderson - Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA
Iona Cheng - Cancer Prevention Institute of California, Fremont, CA
Karen C Johnson - Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN
Chris S Carlson - Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
Shelly-Ann Love - Department of Epidemiology, University of North Carolina, Chapel Hill, NC
Kristin Brown-Gentry - Center for Human Genetics Research, Vanderbilt University, Nashville, TN
Alejandro Q Nato - Department of Genetics, Rutgers University, Piscataway, NJ
Miguel Quibrera - Gillings School of Public Health, University of North Carolina, Chapel Hill, NC
Garnet Anderson - Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
Ralph V Shohet - John A. Burns School of Medicine, University of Hawaii, Honolulu, HI
José Luis Ambite - Information Sciences Institute, University of Southern California, Marina del Rey, CA
Lynne R Wilkens - Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI
Loïc Le Marchand - Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI
Christopher A Haiman - Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA
Steven Buyske - Department of Genetics and Department of Statistics, Rutgers University, Piscataway, NJ
Charles Kooperberg - Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
Kari E North - Department of Epidemiology, University of North Carolina, Chapel Hill, NC
Myriam Fornage - Division of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Sciences Center at Houston, TX
Dana C Crawford - Center for Human Genetics Research, Vanderbilt University, Nashville, TN
Publication Details: Annals of human genetics, Vol.77(5), pp.416-425
Date published: 09/2013
Grant note: U01 HG004803 || HG / National Human Genome Research Institute : NHGRI R01 AG027058 || AG / National Institute on Aging : NIA U01 CA136792 || CA / National Cancer Institute : NCI N01 WH022110-024 || WH / Women's Health Initiative : WHI U01 HG004801 || HG / National Human Genome Research Institute : NHGRI U01 HG004790 || HG / National Human Genome Research Institute : NHGRI N01 HC015103 || HC / Division of Epidemiology & Clinical Applications : NHLBI R37 CA054281 || CA / National Cancer Institute : NCI R01 AG020098 || AG / National Institute on Aging : NIA U01 HL080295 || HL / National Heart, Lung, and Blood Institute : NHLBI U01 HG004798 || HG / National Human Genome Research Institute : NHGRI N01 HC045204 || HC / Division of Epidemiology & Clinical Applications : NHLBI R01 AG015928 || AG / National Institute on Aging : NIA U01 HG004802 || HG / National Human Genome Research Institute : NHGRI R01 AG023629 || AG / National Institute on Aging : NIA N01 HC055018 || HC / Division of Epidemiology & Clinical Applications : NHLBI U01 CA098758 || CA / National Cancer Institute : NCI
Academic Unit: Statistics (SAS)
Language: English
Resource Type: Journal article
Identifiers: 991031665288004646