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Network Analysis of Depression-Related Transcriptomic Profiles.

Xiao MiaoBin FanRongqun LiShaoping ZhangHonghuang Linnull null
Published in: Neuromolecular medicine (2019)
Major depressive disorder is a common debilitating disorder that is associated with increased morbidity and mortality. However, the molecular mechanism underlying depression remains largely unknown. The current study investigated the association of depression with blood gene expression using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Depression was measured by the geriatric depression scale, and the blood gene expression was measured by the Affymetrix Human Genome U219 Array. Linear regression was used to test the association between gene expression and depression, and the model was adjusted for age and sex. A total of 671 participants were included in our study (mean age 75 ± 8 years, 43.2% women). We found three genes were associated with depression, including COL1A2 (P = 8.9 × 10-8), RNF150 (P = 1.4 × 10-7) and CTGF (P = 8.3 × 10-7). An interaction network was built, and the pathway analysis indicated that many depression-related genes were involved in the neurotrophin signaling pathway (P = 2.1 × 10-7). Future studies are necessary to validate our findings and further investigate potential mechanism of depression.
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