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J Affect Disord. 2019 Jan 15;243:16-22. doi: 10.1016/j.jad.2018.09.003. Epub 2018 Sep 7.

GWAS and systems biology analysis of depressive symptoms among smokers from the COPDGene cohort.

Author information

1
Department of Psychiatry, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
2
Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA; Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA.
3
Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
4
Department of Medicine, National Jewish Health, Denver, CO, USA; Department of Epidemiology, Colorado School of Public Health, University of Colorado, Aurora, CO, USA.
5
Department of Medicine, National Jewish Health, Denver, CO, USA.
6
Department of Epidemiology, Colorado School of Public Health, University of Colorado, Aurora, CO, USA.
7
Department of Medicine, National Jewish Health, Denver, CO, USA; Department of Psychiatry, University of Colorado School of Medicine at the Anschutz Medical Campus, Aurora, CO, USA.
8
Department of Thoracic Medicine and Surgery, Temple University School of Medicine, Philadelphia, PA, USA.
9
Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA; Lung Health Center, University of Alabama at Birmingham, Birmingham, AL, USA; Health Services, Outcomes, and Effectiveness Research Training Program, University of Alabama at Birmingham, Birmingham, AL, USA.
10
Department of Psychiatry, University of Iowa Hospitals and Clinics, Iowa City, IA, USA; Department of Psychiatry, Johns Hopkins University, Baltimore, MD, USA.
11
Department of Psychiatry, University of Iowa Hospitals and Clinics, Iowa City, IA, USA. Electronic address: gen-shinozaki@uiowa.edu.

Abstract

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 × 10-6), is near CHRM3. Another SNP was near MDGA2 (rs17118176, p = 3.52 × 10-6). Top genes formed networks for synaptic transmission with a statistically significant level of more co-expression in brain than other tissues, particularly in the basal ganglia (p = 1.00 × 10-4).

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.

KEYWORDS:

Chronic obstructive pulmonary disease; Genome-wide association study; Major depressive disorder; Smokers; Systems biology

PMID:
30219690
PMCID:
PMC6186181
[Available on 2020-01-15]
DOI:
10.1016/j.jad.2018.09.003

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