Files and links (1)
Published, Version of Record (VoR)CC BY V4.0, Open
Journal article
Expression of socially sensitive genes: The multi-ethnic study of atherosclerosis
PloS one, v 14(4), pp e0214061-e0214061
2019
PMID: 30973896
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Gene expression may be an important biological mediator in associations between social factors and health. However, previous studies were limited by small sample sizes and use of differing cell types with heterogeneous expression patterns. We use a large population-based cohort with gene expression measured solely in monocytes to investigate associations between seven social factors and expression of genes previously found to be sensitive to social factors.
We employ three methodological approaches: 1) omnibus test for the entire gene set (Global ANCOVA), 2) assessment of each association individually (linear regression), and 3) machine learning method that performs variable selection with correlated predictors (elastic net).
In global analyses, significant associations with the a priori defined socially sensitive gene set were detected for major or lifetime discrimination and chronic burden (p = 0.019 and p = 0.047, respectively). Marginally significant associations were detected for loneliness and adult socioeconomic status (p = 0.066, p = 0.093, respectively). No associations were significant in linear regression analyses after accounting for multiple testing. However, a small percentage of gene expressions (up to 11%) were associated with at least one social factor using elastic net.
The Global ANCOVA and elastic net findings suggest that a small percentage of genes may be "socially sensitive," (i.e. demonstrate differential expression by social factor), yet single gene approaches such as linear regression may be ill powered to capture this relationship. Future research should further investigate the biological mechanisms through which social factors act to influence gene expression and how systemic changes in gene expression affect overall health.
Metrics
Details
- Title
- Expression of socially sensitive genes: The multi-ethnic study of atherosclerosis
- Creators
- Kristen M Brown - Emory UniversityAna V Diez-Roux - Drexel UniversityJennifer A Smith - Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of AmericaBelinda L Needham - University of Michigan–Ann ArborBhramar Mukherjee - University of Michigan–Ann ArborErin B Ware - University of Michigan–Ann ArborYongmei Liu - Wake Forest UniversitySteven W Cole - Department of Medicine, Division of Hematology-Oncology, University of California-Los Angeles, Los Angeles, California, United States of AmericaTeresa E Seeman - University of California, Los AngelesSharon L R Kardia - University of Michigan–Ann Arbor
- Publication Details
- PloS one, v 14(4), pp e0214061-e0214061
- Publisher
- Public LIbrary of Science (PLOS)
- Grant note
- R01 AG055406 / NIA NIH HHS N01 HC095164 / NHLBI NIH HHS N01 HC095160 / NHLBI NIH HHS N01 HC095168 / NHLBI NIH HHS UL1 TR001881 / NCATS NIH HHS T32 HL130025 / NHLBI NIH HHS N01 HC095165 / NHLBI NIH HHS N01 HC095169 / NHLBI NIH HHS HHSN263201500003I / NIH HHS N01 HC095162 / NHLBI NIH HHS R25 GM058641 / NIGMS NIH HHS R01 HL135009 / NHLBI NIH HHS N01 HC095159 / NHLBI NIH HHS N01 HC095166 / NHLBI NIH HHS N01 HC095163 / NHLBI NIH HHS UL1 TR000040 / NCATS NIH HHS P60 MD002249 / NIMHD NIH HHS N01 HC095161 / NHLBI NIH HHS R01 DK103531 / NIDDK NIH HHS UL1 TR001079 / NCATS NIH HHS R01 HL101161 / NHLBI NIH HHS R01 HL101250 / NHLBI NIH HHS UL1 TR001420 / NCATS NIH HHS N01 HC095167 / NHLBI NIH HHS
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Urban Health Collaborative
- Web of Science ID
- WOS:000464095000011
- Scopus ID
- 2-s2.0-85064412046
- Other Identifier
- 991019168649904721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Multidisciplinary Sciences