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DOI 10.18632/aging.202995

Медицинская библиотека · Aging · 2021

Gene expression signatures differentiating major depressive disorder from subsyndromal symptomatic depression.

Hu Guoqin, Yu Shunying, Yuan Chengmei, Hong Wu, Wang Zuowei, Zhang Ran, Wang Dongxiang, Li Zezhi, Yi Zhenghui, Fang Yiru

СтатьяПоддержка исследования: вне правительства СШАПеревод пока не подготовлен

Аннотация

Subsyndromal symptomatic depression (SSD) and major depressive disorder (MDD) have been classified as distinct diseases, due to their dissimilar gene expression profiles and responses to venlafaxine. To identify specific biomarkers of these two diseases, we conducted a secondary analysis of the gene expression signatures of SSD patients, MDD patients and healthy controls (n=8/group) from the study of Yi et al. Global, individual, specific, enrichment and co-expression analyses were used to compare the transcriptomic profiles of peripheral blood lymphocytes from the three groups. The global and individual analyses revealed that different genes were up- and downregulated in the SSD and MDD groups. Through our specific analysis, we identified 1719 and 3278 differentially expressed genes specifically associated with MDD and SSD, respectively. Enrichment and co-expression analyses demonstrated that the genes specific to MDD were enriched in pathways associated with hormone levels and immune responses, while those specific to SSD were associated with immune function. The specific hub gene for the MDD co-expression network was transmembrane protein 132B (TMEM132B), while the hub genes for SSD were actin-related protein 2/3 complex (ARPC2) and solute carrier family 5 member 5 (SLC5A5). This bioinformatic analysis has provided potential biomarkers that can distinguish SSD from MDD.

Для цитирования: Hu Guoqin, Yu Shunying, Yuan Chengmei, Hong Wu, Wang Zuowei, Zhang Ran, Wang Dongxiang, Li Zezhi, Yi Zhenghui, Fang Yiru. Gene expression signatures differentiating major depressive disorder from subsyndromal symptomatic depression.. Aging. 2021. DOI: 10.18632/aging.202995.

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