TY - JOUR T1 - Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture. JF - Nat Genet Y1 - 2012 A1 - Estrada, Karol A1 - Styrkarsdottir, Unnur A1 - Evangelou, Evangelos A1 - Hsu, Yi-Hsiang A1 - Duncan, Emma L A1 - Ntzani, Evangelia E A1 - Oei, Ling A1 - Albagha, Omar M E A1 - Amin, Najaf A1 - Kemp, John P A1 - Koller, Daniel L A1 - Li, Guo A1 - Liu, Ching-Ti A1 - Minster, Ryan L A1 - Moayyeri, Alireza A1 - Vandenput, Liesbeth A1 - Willner, Dana A1 - Xiao, Su-Mei A1 - Yerges-Armstrong, Laura M A1 - Zheng, Hou-Feng A1 - Alonso, Nerea A1 - Eriksson, Joel A1 - Kammerer, Candace M A1 - Kaptoge, Stephen K A1 - Leo, Paul J A1 - Thorleifsson, Gudmar A1 - Wilson, Scott G A1 - Wilson, James F A1 - Aalto, Ville A1 - Alen, Markku A1 - Aragaki, Aaron K A1 - Aspelund, Thor A1 - Center, Jacqueline R A1 - Dailiana, Zoe A1 - Duggan, David J A1 - Garcia, Melissa A1 - García-Giralt, Natalia A1 - Giroux, Sylvie A1 - Hallmans, Göran A1 - Hocking, Lynne J A1 - Husted, Lise Bjerre A1 - Jameson, Karen A A1 - Khusainova, Rita A1 - Kim, Ghi Su A1 - Kooperberg, Charles A1 - Koromila, Theodora A1 - Kruk, Marcin A1 - Laaksonen, Marika A1 - LaCroix, Andrea Z A1 - Lee, Seung Hun A1 - Leung, Ping C A1 - Lewis, Joshua R A1 - Masi, Laura A1 - Mencej-Bedrac, Simona A1 - Nguyen, Tuan V A1 - Nogues, Xavier A1 - Patel, Millan S A1 - Prezelj, Janez A1 - Rose, Lynda M A1 - Scollen, Serena A1 - Siggeirsdottir, Kristin A1 - Smith, Albert V A1 - Svensson, Olle A1 - Trompet, Stella A1 - Trummer, Olivia A1 - van Schoor, Natasja M A1 - Woo, Jean A1 - Zhu, Kun A1 - Balcells, Susana A1 - Brandi, Maria Luisa A1 - Buckley, Brendan M A1 - Cheng, Sulin A1 - Christiansen, Claus A1 - Cooper, Cyrus A1 - Dedoussis, George A1 - Ford, Ian A1 - Frost, Morten A1 - Goltzman, David A1 - González-Macías, Jesús A1 - Kähönen, Mika A1 - Karlsson, Magnus A1 - Khusnutdinova, Elza A1 - Koh, Jung-Min A1 - Kollia, Panagoula A1 - Langdahl, Bente Lomholt A1 - Leslie, William D A1 - Lips, Paul A1 - Ljunggren, Osten A1 - Lorenc, Roman S A1 - Marc, Janja A1 - Mellström, Dan A1 - Obermayer-Pietsch, Barbara A1 - Olmos, José M A1 - Pettersson-Kymmer, Ulrika A1 - Reid, David M A1 - Riancho, José A A1 - Ridker, Paul M A1 - Rousseau, François A1 - Slagboom, P Eline A1 - Tang, Nelson L S A1 - Urreizti, Roser A1 - Van Hul, Wim A1 - Viikari, Jorma A1 - Zarrabeitia, María T A1 - Aulchenko, Yurii S A1 - Castano-Betancourt, Martha A1 - Grundberg, Elin A1 - Herrera, Lizbeth A1 - Ingvarsson, Thorvaldur A1 - Johannsdottir, Hrefna A1 - Kwan, Tony A1 - Li, Rui A1 - Luben, Robert A1 - Medina-Gómez, Carolina A1 - Palsson, Stefan Th A1 - Reppe, Sjur A1 - Rotter, Jerome I A1 - Sigurdsson, Gunnar A1 - van Meurs, Joyce B J A1 - Verlaan, Dominique A1 - Williams, Frances M K A1 - Wood, Andrew R A1 - Zhou, Yanhua A1 - Gautvik, Kaare M A1 - Pastinen, Tomi A1 - Raychaudhuri, Soumya A1 - Cauley, Jane A A1 - Chasman, Daniel I A1 - Clark, Graeme R A1 - Cummings, Steven R A1 - Danoy, Patrick A1 - Dennison, Elaine M A1 - Eastell, Richard A1 - Eisman, John A A1 - Gudnason, Vilmundur A1 - Hofman, Albert A1 - Jackson, Rebecca D A1 - Jones, Graeme A1 - Jukema, J Wouter A1 - Khaw, Kay-Tee A1 - Lehtimäki, Terho A1 - Liu, Yongmei A1 - Lorentzon, Mattias A1 - McCloskey, Eugene A1 - Mitchell, Braxton D A1 - Nandakumar, Kannabiran A1 - Nicholson, Geoffrey C A1 - Oostra, Ben A A1 - Peacock, Munro A1 - Pols, Huibert A P A1 - Prince, Richard L A1 - Raitakari, Olli A1 - Reid, Ian R A1 - Robbins, John A1 - Sambrook, Philip N A1 - Sham, Pak Chung A1 - Shuldiner, Alan R A1 - Tylavsky, Frances A A1 - van Duijn, Cornelia M A1 - Wareham, Nick J A1 - Cupples, L Adrienne A1 - Econs, Michael J A1 - Evans, David M A1 - Harris, Tamara B A1 - Kung, Annie Wai Chee A1 - Psaty, Bruce M A1 - Reeve, Jonathan A1 - Spector, Timothy D A1 - Streeten, Elizabeth A A1 - Zillikens, M Carola A1 - Thorsteinsdottir, Unnur A1 - Ohlsson, Claes A1 - Karasik, David A1 - Richards, J Brent A1 - Brown, Matthew A A1 - Stefansson, Kari A1 - Uitterlinden, André G A1 - Ralston, Stuart H A1 - Ioannidis, John P A A1 - Kiel, Douglas P A1 - Rivadeneira, Fernando KW - Bone Density KW - Computational Biology KW - European Continental Ancestry Group KW - Extracellular Matrix Proteins KW - Female KW - Femur Neck KW - Fractures, Bone KW - Gene Expression Profiling KW - Genetic Predisposition to Disease KW - Genome-Wide Association Study KW - Genotype KW - Glycoproteins KW - Humans KW - Intercellular Signaling Peptides and Proteins KW - Low Density Lipoprotein Receptor-Related Protein-5 KW - Lumbar Vertebrae KW - Male KW - Mitochondrial Membrane Transport Proteins KW - Osteoporosis KW - Phosphoproteins KW - Polymorphism, Single Nucleotide KW - Quantitative Trait Loci KW - Risk Factors KW - Spectrin AB -

Bone mineral density (BMD) is the most widely used predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and east Asian ancestry. We tested the top BMD-associated markers for replication in 50,933 independent subjects and for association with risk of low-trauma fracture in 31,016 individuals with a history of fracture (cases) and 102,444 controls. We identified 56 loci (32 new) associated with BMD at genome-wide significance (P < 5 × 10(-8)). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal stem cell differentiation, endochondral ossification and Wnt signaling pathways. However, we also discovered loci that were localized to genes not known to have a role in bone biology. Fourteen BMD-associated loci were also associated with fracture risk (P < 5 × 10(-4), Bonferroni corrected), of which six reached P < 5 × 10(-8), including at 18p11.21 (FAM210A), 7q21.3 (SLC25A13), 11q13.2 (LRP5), 4q22.1 (MEPE), 2p16.2 (SPTBN1) and 10q21.1 (DKK1). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility.

VL - 44 IS - 5 ER - TY - JOUR T1 - Generalization and dilution of association results from European GWAS in populations of non-European ancestry: the PAGE study. JF - PLoS Biol Y1 - 2013 A1 - Carlson, Christopher S A1 - Matise, Tara C A1 - North, Kari E A1 - Haiman, Christopher A A1 - Fesinmeyer, Megan D A1 - Buyske, Steven A1 - Schumacher, Fredrick R A1 - Peters, Ulrike A1 - Franceschini, Nora A1 - Ritchie, Marylyn D A1 - Duggan, David J A1 - Spencer, Kylee L A1 - Dumitrescu, Logan A1 - Eaton, Charles B A1 - Thomas, Fridtjof A1 - Young, Alicia A1 - Carty, Cara A1 - Heiss, Gerardo A1 - Le Marchand, Loïc A1 - Crawford, Dana C A1 - Hindorff, Lucia A A1 - Kooperberg, Charles L KW - African Americans KW - Asian Americans KW - Body Mass Index KW - Diabetes Mellitus, Type 2 KW - European Continental Ancestry Group KW - Gene Frequency KW - Genetic Predisposition to Disease KW - Genetic Variation KW - Genome-Wide Association Study KW - Hispanic Americans KW - Humans KW - Indians, North American KW - Lipids KW - Metagenomics KW - Oceanic Ancestry Group KW - Polymorphism, Single Nucleotide AB -

The vast majority of genome-wide association study (GWAS) findings reported to date are from populations with European Ancestry (EA), and it is not yet clear how broadly the genetic associations described will generalize to populations of diverse ancestry. The Population Architecture Using Genomics and Epidemiology (PAGE) study is a consortium of multi-ancestry, population-based studies formed with the objective of refining our understanding of the genetic architecture of common traits emerging from GWAS. In the present analysis of five common diseases and traits, including body mass index, type 2 diabetes, and lipid levels, we compare direction and magnitude of effects for GWAS-identified variants in multiple non-EA populations against EA findings. We demonstrate that, in all populations analyzed, a significant majority of GWAS-identified variants have allelic associations in the same direction as in EA, with none showing a statistically significant effect in the opposite direction, after adjustment for multiple testing. However, 25% of tagSNPs identified in EA GWAS have significantly different effect sizes in at least one non-EA population, and these differential effects were most frequent in African Americans where all differential effects were diluted toward the null. We demonstrate that differential LD between tagSNPs and functional variants within populations contributes significantly to dilute effect sizes in this population. Although most variants identified from GWAS in EA populations generalize to all non-EA populations assessed, genetic models derived from GWAS findings in EA may generate spurious results in non-EA populations due to differential effect sizes. Regardless of the origin of the differential effects, caution should be exercised in applying any genetic risk prediction model based on tagSNPs outside of the ancestry group in which it was derived. Models based directly on functional variation may generalize more robustly, but the identification of functional variants remains challenging.

VL - 11 IS - 9 U1 - http://www.ncbi.nlm.nih.gov/pubmed/24068893?dopt=Abstract ER - TY - JOUR T1 - Investigation of gene-by-sex interactions for lipid traits in diverse populations from the population architecture using genomics and epidemiology study. JF - BMC Genet Y1 - 2013 A1 - Taylor, Kira C A1 - Carty, Cara L A1 - Dumitrescu, Logan A1 - Bůzková, Petra A1 - Cole, Shelley A A1 - Hindorff, Lucia A1 - Schumacher, Fred R A1 - Wilkens, Lynne R A1 - Shohet, Ralph V A1 - Quibrera, P Miguel A1 - Johnson, Karen C A1 - Henderson, Brian E A1 - Haessler, Jeff A1 - Franceschini, Nora A1 - Eaton, Charles B A1 - Duggan, David J A1 - Cochran, Barbara A1 - Cheng, Iona A1 - Carlson, Chris S A1 - Brown-Gentry, Kristin A1 - Anderson, Garnet A1 - Ambite, Jose Luis A1 - Haiman, Christopher A1 - Le Marchand, Loïc A1 - Kooperberg, Charles A1 - Crawford, Dana C A1 - Buyske, Steven A1 - North, Kari E A1 - Fornage, Myriam KW - Female KW - Genetic Heterogeneity KW - Genome, Human KW - Genome-Wide Association Study KW - Humans KW - Lipids KW - Male KW - Polymorphism, Single Nucleotide KW - Population Groups AB -

BACKGROUND: High-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels are influenced by both genes and the environment. Genome-wide association studies (GWAS) have identified ~100 common genetic variants associated with HDL-C, LDL-C, and/or TG levels, mostly in populations of European descent, but little is known about the modifiers of these associations. Here, we investigated whether GWAS-identified SNPs for lipid traits exhibited heterogeneity by sex in the Population Architecture using Genomics and Epidemiology (PAGE) study.

RESULTS: A sex-stratified meta-analysis was performed for 49 GWAS-identified SNPs for fasting HDL-C, LDL-C, and ln(TG) levels among adults self-identified as European American (25,013). Heterogeneity by sex was established when phet < 0.001. There was evidence for heterogeneity by sex for two SNPs for ln(TG) in the APOA1/C3/A4/A5/BUD13 gene cluster: rs28927680 (p(het) = 7.4 x 10(-7)) and rs3135506 (p(het) = 4.3 x 10(-4)one SNP in PLTP for HDL levels (rs7679; p(het) = 9.9 x 10(-4)), and one in HMGCR for LDL levels (rs12654264; p(het) = 3.1 x 10(-5)). We replicated heterogeneity by sex in five of seventeen loci previously reported by genome-wide studies (binomial p = 0.0009). We also present results for other racial/ethnic groups in the supplementary materials, to provide a resource for future meta-analyses.

CONCLUSIONS: We provide further evidence for sex-specific effects of SNPs in the APOA1/C3/A4/A5/BUD13 gene cluster, PLTP, and HMGCR on fasting triglyceride levels in European Americans from the PAGE study. Our findings emphasize the need for considering context-specific effects when interpreting genetic associations emerging from GWAS, and also highlight the difficulties in replicating interaction effects across studies and across racial/ethnic groups.

VL - 14 U1 - http://www.ncbi.nlm.nih.gov/pubmed/23634756?dopt=Abstract ER - TY - JOUR T1 - No evidence of interaction between known lipid-associated genetic variants and smoking in the multi-ethnic PAGE population. JF - Hum Genet Y1 - 2013 A1 - Dumitrescu, Logan A1 - Carty, Cara L A1 - Franceschini, Nora A1 - Hindorff, Lucia A A1 - Cole, Shelley A A1 - Bůzková, Petra A1 - Schumacher, Fredrick R A1 - Eaton, Charles B A1 - Goodloe, Robert J A1 - Duggan, David J A1 - Haessler, Jeff A1 - Cochran, Barbara A1 - Henderson, Brian E A1 - Cheng, Iona A1 - Johnson, Karen C A1 - Carlson, Chris S A1 - Love, Shelly-Anne A1 - Brown-Gentry, Kristin A1 - Nato, Alejandro Q A1 - Quibrera, Miguel A1 - Shohet, Ralph V A1 - Ambite, Jose Luis A1 - Wilkens, Lynne R A1 - Le Marchand, Loïc A1 - Haiman, Christopher A A1 - Buyske, Steven A1 - Kooperberg, Charles A1 - North, Kari E A1 - Fornage, Myriam A1 - Crawford, Dana C KW - Cholesterol, HDL KW - Cholesterol, LDL KW - Cohort Studies KW - Ethnic Groups KW - Female KW - Gene Frequency KW - Gene-Environment Interaction KW - Genetics, Population KW - Genome-Wide Association Study KW - Humans KW - Lipid Metabolism KW - Male KW - Polymorphism, Single Nucleotide KW - Prevalence KW - Smoking KW - Triglycerides KW - Young Adult AB -

Genome-wide association studies (GWAS) have identified many variants that influence high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and/or triglycerides. However, environmental modifiers, such as smoking, of these known genotype-phenotype associations are just recently emerging in the literature. We have tested for interactions between smoking and 49 GWAS-identified variants in over 41,000 racially/ethnically diverse samples with lipid levels from the Population Architecture Using Genomics and Epidemiology (PAGE) study. Despite their biological plausibility, we were unable to detect significant SNP × smoking interactions.

VL - 132 IS - 12 U1 - http://www.ncbi.nlm.nih.gov/pubmed/24100633?dopt=Abstract ER - TY - JOUR T1 - 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. JF - Ann Hum Genet Y1 - 2013 A1 - Dumitrescu, Logan A1 - Carty, Cara L A1 - Franceschini, Nora A1 - Hindorff, Lucia A A1 - Cole, Shelley A A1 - Bůzková, Petra A1 - Schumacher, Fredrick R A1 - Eaton, Charles B A1 - Goodloe, Robert J A1 - Duggan, David J A1 - Haessler, Jeff A1 - Cochran, Barbara A1 - Henderson, Brian E A1 - Cheng, Iona A1 - Johnson, Karen C A1 - Carlson, Chris S A1 - Love, Shelly-Ann A1 - Brown-Gentry, Kristin A1 - Nato, Alejandro Q A1 - Quibrera, Miguel A1 - Anderson, Garnet A1 - Shohet, Ralph V A1 - Ambite, Jose Luis A1 - Wilkens, Lynne R A1 - Marchand, Loic Le A1 - Haiman, Christopher A A1 - Buyske, Steven A1 - Kooperberg, Charles A1 - North, Kari E A1 - Fornage, Myriam A1 - Crawford, Dana C KW - Adult KW - Aged KW - European Continental Ancestry Group KW - Female KW - Genetic Association Studies KW - Genome-Wide Association Study KW - Humans KW - Lipids KW - Male KW - Middle Aged KW - Polymorphism, Single Nucleotide KW - Quantitative Trait Loci KW - Quantitative Trait, Heritable KW - Risk Factors AB -

Numerous common genetic variants that influence plasma high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), and triglyceride 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 postmenopausal). For each variant, a test of heterogeneity was performed between the two age strata and significant Phet 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 (Phet < 0.05). The association between rs174547 (FADS1) and LDL-C in males displayed the most evidence for heterogeneity between age groups (Phet = 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.

VL - 77 IS - 5 U1 - http://www.ncbi.nlm.nih.gov/pubmed/23808484?dopt=Abstract ER -