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Adipose tissue eQTL meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits.
Brotman, Sarah M; El-Sayed Moustafa, Julia S; Guan, Li; Broadaway, K Alaine; Wang, Dongmeng; Jackson, Anne U; Welch, Ryan; Currin, Kevin W; Tomlinson, Max; Vadlamudi, Swarooparani; Stringham, Heather M; Roberts, Amy L; Lakka, Timo A; Oravilahti, Anniina; Silva, Lilian Fernandes; Narisu, Narisu; Erdos, Michael R; Yan, Tingfen; Bonnycastle, Lori L; Raulerson, Chelsea K; Raza, Yasrab; Yan, Xinyu; Parker, Stephen C J; Kuusisto, Johanna; Pajukanta, Päivi; Tuomilehto, Jaakko; Collins, Francis S; Boehnke, Michael; Love, Michael I; Koistinen, Heikki A; Laakso, Markku; Mohlke, Karen L; Small, Kerrin S; Scott, Laura J.
Afiliação
  • Brotman SM; Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
  • El-Sayed Moustafa JS; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Guan L; Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
  • Broadaway KA; Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
  • Wang D; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Jackson AU; Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
  • Welch R; Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
  • Currin KW; Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
  • Tomlinson M; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Vadlamudi S; Department of Medical and Molecular Genetics, King's College London, London, UK.
  • Stringham HM; Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
  • Roberts AL; Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
  • Lakka TA; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Oravilahti A; Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland.
  • Silva LF; Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland.
  • Narisu N; Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland.
  • Erdos MR; Institute of Clinical Medicine, Kuopio University Hospital, University of Eastern Finland, Kuopio, Finland.
  • Yan T; Institute of Clinical Medicine, Kuopio University Hospital, University of Eastern Finland, Kuopio, Finland.
  • Bonnycastle LL; Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
  • Raulerson CK; Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
  • Raza Y; Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
  • Yan X; Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
  • Parker SCJ; Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
  • Kuusisto J; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Pajukanta P; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Tuomilehto J; Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
  • Collins FS; Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA.
  • Boehnke M; Department of Medicine and Clinical Research, Kuopio University Hospital, Kuopio, Finland.
  • Love MI; Department of Human Genetics and Institute for Precision Health, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
  • Koistinen HA; Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland.
  • Laakso M; Department of Public Health, University of Helsinki, Helsinki, Finland.
  • Mohlke KL; Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia.
  • Small KS; Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
  • Scott LJ; Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
bioRxiv ; 2023 Oct 27.
Article em En | MEDLINE | ID: mdl-37961277
Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. Here, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34K conditionally distinct expression quantitative trait locus (eQTL) signals in 18K genes. Over half of eQTL genes exhibited at least two eQTL signals. Compared to primary signals, non-primary signals had lower effect sizes, lower minor allele frequencies, and less promoter enrichment; they corresponded to genes with higher heritability and higher tolerance for loss of function. Colocalization of eQTL with conditionally distinct genome-wide association study signals for 28 cardiometabolic traits identified 3,605 eQTL signals for 1,861 genes. Inclusion of non-primary eQTL signals increased colocalized signals by 46%. Among 30 genes with ≥2 pairs of colocalized signals, 21 showed a mediating gene dosage effect on the trait. Thus, expanded eQTL identification reveals more mechanisms underlying complex traits and improves understanding of the complexity of gene expression regulation.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Systematic_reviews Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Systematic_reviews Idioma: En Ano de publicação: 2023 Tipo de documento: Article