GWAS and systems biology analysis of depressive symptoms among smokers from the COPDGene cohort.
Black or African American
/ genetics
Aged
Antidepressive Agents
/ therapeutic use
Cohort Studies
Depression
/ genetics
Female
Genetic Predisposition to Disease
Genome-Wide Association Study
Genotype
Humans
Male
Middle Aged
Polymorphism, Single Nucleotide
Risk Factors
Smoking
/ genetics
Systems Biology
White People
/ genetics
Chronic obstructive pulmonary disease
Genome-wide association study
Major depressive disorder
Smokers
Systems biology
Journal
Journal of affective disorders
ISSN: 1573-2517
Titre abrégé: J Affect Disord
Pays: Netherlands
ID NLM: 7906073
Informations de publication
Date de publication:
15 01 2019
15 01 2019
Historique:
received:
04
04
2018
revised:
24
07
2018
accepted:
06
09
2018
pubmed:
17
9
2018
medline:
26
2
2019
entrez:
17
9
2018
Statut:
ppublish
Résumé
Large sample GWAS is needed to identify genetic factors associated with depression. This study used genome-wide genotypic and phenotypic data from the COPDGene study to identify genetic risk factors for depression. Data were from 9716 COPDGene subjects with ≥10 pack-year history. Depression was defined as antidepressant use and/or a HADS depression subscale score ≥8. Non-Hispanic White (6576) and African-American (3140) subsets were analyzed. A GWAS pipeline identified SNPs associated with depression in each group. Network analysis software analyzed gene interactions through common biological pathways, genetic interactions, and tissue-specific gene expression. The mean age was 59.4 years (SD 9.0) with 46.5% female subjects. Depression was in 24.7% of the NHW group (1622) and 12.5% of the AA group (391). No SNPs had genome-wide significance. One of the top SNPs, rs12036147 (p = 1.28 × 10 Limitations included a depression definition based on antidepressant use and a limited HADS score subgroup, which could increase false negatives in depressed patients not on antidepressants. Antidepressants used for smoking cessation in non-depressed patients could lead to false positives. Systems biology analysis identified statistically significant pathways whereby multiple genes influence depression. The gene set pathway analysis and COPDGene data can help investigate depression in future studies.
Sections du résumé
BACKGROUND
Large sample GWAS is needed to identify genetic factors associated with depression. This study used genome-wide genotypic and phenotypic data from the COPDGene study to identify genetic risk factors for depression.
METHODS
Data were from 9716 COPDGene subjects with ≥10 pack-year history. Depression was defined as antidepressant use and/or a HADS depression subscale score ≥8. Non-Hispanic White (6576) and African-American (3140) subsets were analyzed. A GWAS pipeline identified SNPs associated with depression in each group. Network analysis software analyzed gene interactions through common biological pathways, genetic interactions, and tissue-specific gene expression.
RESULTS
The mean age was 59.4 years (SD 9.0) with 46.5% female subjects. Depression was in 24.7% of the NHW group (1622) and 12.5% of the AA group (391). No SNPs had genome-wide significance. One of the top SNPs, rs12036147 (p = 1.28 × 10
LIMITATIONS
Limitations included a depression definition based on antidepressant use and a limited HADS score subgroup, which could increase false negatives in depressed patients not on antidepressants. Antidepressants used for smoking cessation in non-depressed patients could lead to false positives.
CONCLUSIONS
Systems biology analysis identified statistically significant pathways whereby multiple genes influence depression. The gene set pathway analysis and COPDGene data can help investigate depression in future studies.
Identifiants
pubmed: 30219690
pii: S0165-0327(18)30698-0
doi: 10.1016/j.jad.2018.09.003
pmc: PMC6186181
mid: NIHMS1506884
pii:
doi:
Substances chimiques
Antidepressive Agents
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
16-22Subventions
Organisme : NHLBI NIH HHS
ID : R01 HL089897
Pays : United States
Organisme : NHLBI NIH HHS
ID : T35 HL007485
Pays : United States
Organisme : NHLBI NIH HHS
ID : U01 HL089897
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL089856
Pays : United States
Organisme : NHLBI NIH HHS
ID : U01 HL089856
Pays : United States
Informations de copyright
Copyright © 2018 Elsevier B.V. All rights reserved.
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