期刊
JOURNAL OF AFFECTIVE DISORDERS
卷 243, 期 -, 页码 16-22出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jad.2018.09.003
关键词
Major depressive disorder; Systems biology; Chronic obstructive pulmonary disease; Smokers; Genome-wide association study
资金
- National Heart, Lung, and Blood Institute [R01 HL089897, R01 HL089856]
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 x 10(-6)), is near CHRM3. Another SNP was near MDGA2 (rs17118176, p = 3.52 x 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 x 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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据