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Gene expression associations with body mass index in the Multi-Ethnic Study of Atherosclerosis.
Vargas, Luciana B; Lange, Leslie A; Ferrier, Kendra; Aguet, François; Ardlie, Kristin; Gabriel, Stacey; Gupta, Namrata; Smith, Joshua D; Blackwell, Thomas W; Ding, Jingzhong; Durda, Peter; Tracy, Russell P; Liu, Yongmei; Taylor, Kent D; Craig Johnson, W; Rich, Stephen S; Rotter, Jerome I; Lange, Ethan M; Konigsberg, Iain R.
Afiliação
  • Vargas LB; Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
  • Lange LA; Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
  • Ferrier K; Department of Epidemiology, University of Colorado School of Public Health, Aurora, CO, USA.
  • Aguet F; Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
  • Ardlie K; The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Gabriel S; Illumina Artificial Intelligence Laboratory, Illumina, Inc, San Diego, CA, USA.
  • Gupta N; The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Smith JD; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.
  • Blackwell TW; Genomics Platform, Broad Institute, Cambridge, MA, USA.
  • Ding J; Northwest Genomics Center, University of Washington, Seattle, WA, USA.
  • Durda P; Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
  • Tracy RP; Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA.
  • Liu Y; Department of Pathology and Laboratory Medicine, The Robert Larner, M.D. College of Medicine at University of Vermont, Burlington, VT, USA.
  • Taylor KD; Department of Pathology and Laboratory Medicine, The Robert Larner, M.D. College of Medicine at University of Vermont, Burlington, VT, USA.
  • Craig Johnson W; Divisions of Cardiology & Neurology, Department of Medicine, Duke University Medical Center, Durham, NC, USA.
  • Rich SS; The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
  • Rotter JI; Department of Biostatistics, University of Washington, Seattle, WA, USA.
  • Lange EM; Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA.
  • Konigsberg IR; The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
Int J Obes (Lond) ; 47(2): 109-116, 2023 02.
Article em En | MEDLINE | ID: mdl-36463326
ABSTRACT
BACKGROUND/

OBJECTIVES:

Obesity, defined as excessive fat accumulation that represents a health risk, is increasing in adults and children, reaching global epidemic proportions. Body mass index (BMI) correlates with body fat and future health risk, yet differs in prediction by fat distribution, across populations and by age. Nonetheless, few genetic studies of BMI have been conducted in ancestrally diverse populations. Gene expression association with BMI was assessed in the Multi-Ethnic Study of Atherosclerosis (MESA) in four self-identified race and ethnicity (SIRE) groups to identify genes associated with obesity. SUBJECTS/

METHODS:

RNA-sequencing was performed on 1096 MESA participants (37.8% white, 24.3% Hispanic, 28.4% African American, and 9.5% Chinese American) and linear models were used to assess the association of expression from each gene for its effect on BMI, adjusting for age, sex, sequencing center, study site, five expression and four genetic principal components in each self-identified race group. Sample-size-weighted meta-analysis was performed to identify genes with BMI-associated expression across ancestry groups.

RESULTS:

Within individual SIRE groups, there were zero to three genes whose expression is significantly (p < 1.97 × 10-6) associated with BMI. Across all groups, 45 genes were identified by meta-analysis whose expression was significantly associated with BMI, explaining 29.7% of BMI variation. The 45 genes are expressed in a variety of tissues and cell types and are enriched for obesity-related processes including erythrocyte function, oxygen binding and transport, and JAK-STAT signaling.

CONCLUSIONS:

We have identified genes whose expression is significantly associated with obesity in a multi-ethnic cohort. We have identified novel genes associated with BMI as well as confirmed previously identified genes from earlier genetic analyses. These novel genes and their biological pathways represent new targets for understanding the biology of obesity as well as new therapeutic intervention to reduce obesity and improve global public health.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Índice de Massa Corporal / Expressão Gênica / Obesidade Tipo de estudo: Prognostic_studies / Risk_factors_studies / Systematic_reviews Limite: Adult / Child / Humans Idioma: En Revista: Int J Obes (Lond) Assunto da revista: METABOLISMO Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Índice de Massa Corporal / Expressão Gênica / Obesidade Tipo de estudo: Prognostic_studies / Risk_factors_studies / Systematic_reviews Limite: Adult / Child / Humans Idioma: En Revista: Int J Obes (Lond) Assunto da revista: METABOLISMO Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos