Integrating Genetic and Transcriptomic Data to Identify Genes Underlying Obesity Risk Loci.

Autor: Xu H; Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA., Gupta S; Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA., Dinsmore I; Department of Genomic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA., Kollu A; Department of Psychology and Neuroscience, University of North Carolina, 235 E. Cameron Avenue, Chapel Hill, NC, 27599, USA., Cawley AM; Marsico Lung Institute, University of North Carolina, 125 Mason Farm Rd, Chapel Hill, NC, 27599, USA., Anwar MY; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA., Chen HH; Institute of Biomedical Sciences, Academia Sinica, No. 128, Section 2, Academia Rd., Taipei, Nangang District, 115201, Taiwan.; Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA., Petty LE; Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA., Seshadri S; Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA.; Department of Neurology, School of Medicine, Boston University, 85 East Concord Street, Boston, MA, 02118, USA.; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, UT Health San Antonio, 8300 Floyd Curl Drive, San Antonio, TX, 78229, USA., Graff M; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA., Below P; Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA., Brody JA; Department of Medicine, Cardiovascular Health Research Unit, University of Washington, 1730 Minor Ave, Seattle, WA, 98101, USA., Chittoor G; Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA., Fisher-Hoch SP; Department of Epidemiology, School of Public Health, UT Health Houston, Regional Academic Health Center, One West University Blvd, Brownsville, TX, 78520, USA., Heard-Costa NL; Framingham Heart Study, 73 Mt Wayte Ave, Framingham, MA, 01702, USA.; Department of Neurology, Chobanian & Avedisian School of Medicine, Boston University, 72 E Concord St, Boston, MA, 02118, USA., Levy D; Population Sciences Branch, National Heart, Lung, and Blood Institute of the National Institutes of Health, 6701 Rockledge Drive, Bethesda, MD, 20892, USA., Lin H; Department of Medicine, University of Massachusetts Chan Medical School, 55 N Lake Ave, Worcester, MA, 01655, USA., Loos RJ; Charles Bronfman Institute for Personalized Medicine at Mount Sinai, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY, 10029, USA.; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3A, 2200, Copenhagen, Denmark., Mccormick JB; Department of Epidemiology, School of Public Health, UT Health Houston, Regional Academic Health Center, One West University Blvd, Brownsville, TX, 78520, USA., Rotter JI; Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, 1124 West Carson Street, Torrance, CA, 90502, USA., Mirshahi T; Department of Genomic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA., Still CD; Center for Obesity and Metabolic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA., Destefano A; Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA.; Department of Neurology, School of Medicine, Boston University, 85 East Concord Street, Boston, MA, 02118, USA., Cupples LA; Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA., Mohlke KL; Department of Genetics, School of Medicine, University of North Carolina, Chapel Hill, NC, 27599, USA., North KE; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA., Justice AE; Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA., Liu CT; Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA.
Jazyk: angličtina
Zdroj: MedRxiv : the preprint server for health sciences [medRxiv] 2024 Jun 12. Date of Electronic Publication: 2024 Jun 12.
DOI: 10.1101/2024.06.11.24308730
Abstrakt: Genome-wide association studies (GWAS) have identified numerous body mass index (BMI) loci. However, most underlying mechanisms from risk locus to BMI remain unknown. Leveraging omics data through integrative analyses could provide more comprehensive views of biological pathways on BMI. We analyzed genotype and blood gene expression data in up to 5,619 samples from the Framingham Heart Study (FHS). Using 3,992 single nucleotide polymorphisms (SNPs) at 97 BMI loci and 20,692 transcripts within 1 Mb, we performed separate association analyses of transcript with BMI and SNP with transcript (P BMI and P SNP , respectively) and then a correlated meta-analysis between the full summary data sets (P META ). We identified transcripts that met Bonferroni-corrected significance for each omic, were more significant in the correlated meta-analysis than each omic, and were at least nominally associated with BMI in FHS data. Among 308 significant SNP-transcript-BMI associations, we identified seven genes ( NT5C2 , GSTM3 , SNAPC3 , SPNS1 , TMEM245 , YPEL3 , and ZNF646 ) in five association regions. Using an independent sample of blood gene expression data, we validated results for SNAPC3 and YPEL3 . We tested for generalization of these associations in hypothalamus, nucleus accumbens, and liver and observed significant (P META <0.05 & P META

SNP & P META

BMI ) results for YPEL3 in nucleus accumbens and NT5C2 , SNAPC3 , TMEM245 , YPEL3 , and ZNF646 in liver. The identified genes help link the genetic variation at obesity risk loci to biological mechanisms and health outcomes, thus translating GWAS findings to function.
Competing Interests: CONFLICTS OF INTEREST None to report.

Databáze: MEDLINE