Roles of circadian rhythm and metabolic pathways in depression: identifying biomarkers and predicting novel therapeutic compounds_West China Medical Journal

Authors：

YANG Chenghao ¹ ,  WANG Wei ² , LUO Xiaobin ¹ , ZOU Yong ¹ , ZHANG Minghui ¹

1. Department of Neurosurgery, Zigong Fourth People’s Hospital, Zigong, Sichuan 643000, P. R. China;
2. Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P. R. China;

Corresponding author：

WANG Wei, Email: wcnsww@163.com

Keywords：

Depression; markers; bioinformatics

DOI：

10.7507/1002-0179.202310239

Video：

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Objective To explore depression-related biomarkers and potential therapeutic drugs in order to alleviate depression symptoms and improve patients’ quality of life. Methods From November 2022 to January 2024, gene expression profiles of depression patients and healthy volunteers were downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed to identify differentially expressed genes. Enrichment analysis of these genes was conducted, followed by the construction of a protein-protein interaction network. Finally, Cytoscape software with the Cytohubba plugin was used to identify potential key genes, and drug prediction was performed. Results Through differential expression analysis, a total of 110 differentially expressed genes (74 upregulated and 36 downregulated) were identified. Protein-protein interaction network identified 10 key genes, and differential expression analysis showed that 8 of these genes (CPA3, HDC, IL3RA, ENPP3, PTGDR2, VTN, SPP1, and SERPINE1) exhibited significant differences in expression levels between healthy volunteers and patients with depression (P<0.05). Enrichment analysis revealed that the upregulated genes were significantly enriched in pathways related to circadian rhythm, niacin and nicotinamide metabolism, and pyrimidine metabolism, while the downregulated genes were primarily enriched in extracellular matrix-receptor interaction and interleukin-17 signaling pathways. Six overlapping verification genes (SALL2, AKAP12, GCSAML, CPA3, FCRL3, and MS4A3) were obtained across two datasets using the Wayn diagram. Single-cell sequencing analysis indicated that these genes were significantly expressed in astrocytes and neurons. Mendelian randomization analysis suggested that the FCRL3 gene might play a critical role in the development of depression. Drug prediction analysis revealed several potential antidepressant agents, such as cefotiam, harmol, lincomycin, and ribavirin. Conclusions Circadian rhythm, nicotinate and nicotinamide metabolism, and pyrimidine metabolism pathways may represent potential pathogenic mechanisms in depression. Harmol may be a potential therapeutic drug for the treatment of depression.

Citation： YANG Chenghao, WANG Wei, LUO Xiaobin, ZOU Yong, ZHANG Minghui. Roles of circadian rhythm and metabolic pathways in depression: identifying biomarkers and predicting novel therapeutic compounds. West China Medical Journal, 2024, 39(9): 1457-1464. doi: 10.7507/1002-0179.202310239 Copy

1.	WHO Regional Office for the Americas. Depression and other common mental disorders. Geneva: WHO Regional Office for the Americas, 2017.
2.	World Federation for Mental Health. DEPRESSION: a global crisis. World Mental Health Day, October 10 2012. Occoquan, VA: World Federation for Mental Health, 2012.
3.	Smith K. Mental health: a world of depression. Nature, 2014, 515(7526): 181.
4.	Wooller SK, Benstead-Hume G, Chen X, et al. Bioinformatics in translational drug discovery. Biosci Rep, 2017, 37(4): BSR20160180.
5.	高瑜, 陈图农, 徐成, 等. 美国《精神障碍诊断与统计手册》第 5 版人格特质的稳定性和变化性研究. 临床精神医学杂志, 2021, 31(1): 42-46.
6.	Chin CH, Chen SH, Wu HH, et al. cytoHubba: identifying hub objects and sub-networks from complex interactome. BMC Syst Biol, 2014, 8(Suppl 4): S11.
7.	Wu T, Hu E, Xu S, et al. clusterProfiler 4.0: a universal enrichment tool for interpreting omics data. Innovation (Camb), 2021, 2(3): 100141.
8.	Gao Y, Kim S, Lee YI, et al. Cellular stress-modulating drugs can potentially be identified by in silico screening with connectivity map (CMap). Int J Mol Sci, 2019, 20(22): E5601.
9.	Han T, Zhou Y, Li D. Relationship between hepatocellular carcinoma and depression via online database analysis. Bioengineered, 2021, 12(1): 1689-1697.
10.	Lisowski P, Wieczorek M, Goscik J, et al. Effects of chronic stress on prefrontal cortex transcriptome in mice displaying different genetic backgrounds. J Mol Neurosci, 2013, 50(1): 33-57.
11.	Satyanarayanan SK, Su H, Lin YW, et al. Circadian rhythm and melatonin in the treatment of depression. Curr Pharm Des, 2018, 24(22): 2549-2555.
12.	Varinthra P, Liu IY. Molecular basis for the association between depression and circadian rhythm. Tzu Chi Med J, 2019, 31(2): 67-72.
13.	Ma WN, Zhou MM, Gou XJ, et al. Urinary metabolomic study of chlorogenic acid in a rat model of chronic sleep deprivation using gas chromatography-mass spectrometry. Int J Genomics, 2018, 2018: 1361402.
14.	Zhao S, Chi A, Yan J, et al. Feature of heart rate variability and metabolic mechanism in female college students with depression. Biomed Res Int, 2020, 2020: 5246350.
15.	Zeng P, Wang XM, Ye CY, et al. Mechanistic insights into the anti-depressant effect of emodin: an integrated systems pharmacology study and experimental validation. Aging (Albany NY), 2021, 13(11): 15078-15099.
16.	Wang Y, Jiang H, Meng H, et al. Antidepressant mechanism research of acupuncture: insights from a genome-wide transcriptome analysis of frontal cortex in rats with chronic restraint stress. Evid Based Complement Alternat Med, 2017, 2017: 1676808.
17.	Watanabe Y, Nunokawa A, Kaneko N, et al. Two-stage case-control association study of polymorphisms in rheumatoid arthritis susceptibility genes with schizophrenia. J Hum Genet, 2009, 54(1): 62-65.
18.	Hamid HA, Ramli AN, Yusoff MM. Indole alkaloids from plants as potential leads for antidepressant drugs: a mini review. Front Pharmacol, 2017, 8: 96.
19.	Jawna-Zboińska K, Blecharz-Klin K, Joniec-Maciejak I, et al. Passiflora incarnata L. improves spatial memory, reduces stress, and affects neurotransmission in rats. Phytother Res, 2016, 30(5): 781-789.
20.	Castellvi P, Navinés R, Gutierrez F, et al. Pegylated interferon and ribavirin-induced depression in chronic hepatitis C: role of personality. J Clin Psychiatry, 2009, 70(6): 817-828.

1. WHO Regional Office for the Americas. Depression and other common mental disorders. Geneva: WHO Regional Office for the Americas, 2017.
2. World Federation for Mental Health. DEPRESSION: a global crisis. World Mental Health Day, October 10 2012. Occoquan, VA: World Federation for Mental Health, 2012.
3. Smith K. Mental health: a world of depression. Nature, 2014, 515(7526): 181.
4. Wooller SK, Benstead-Hume G, Chen X, et al. Bioinformatics in translational drug discovery. Biosci Rep, 2017, 37(4): BSR20160180.
5. 高瑜, 陈图农, 徐成, 等. 美国《精神障碍诊断与统计手册》第 5 版人格特质的稳定性和变化性研究. 临床精神医学杂志, 2021, 31(1): 42-46.
6. Chin CH, Chen SH, Wu HH, et al. cytoHubba: identifying hub objects and sub-networks from complex interactome. BMC Syst Biol, 2014, 8(Suppl 4): S11.
7. Wu T, Hu E, Xu S, et al. clusterProfiler 4.0: a universal enrichment tool for interpreting omics data. Innovation (Camb), 2021, 2(3): 100141.
8. Gao Y, Kim S, Lee YI, et al. Cellular stress-modulating drugs can potentially be identified by in silico screening with connectivity map (CMap). Int J Mol Sci, 2019, 20(22): E5601.
9. Han T, Zhou Y, Li D. Relationship between hepatocellular carcinoma and depression via online database analysis. Bioengineered, 2021, 12(1): 1689-1697.
10. Lisowski P, Wieczorek M, Goscik J, et al. Effects of chronic stress on prefrontal cortex transcriptome in mice displaying different genetic backgrounds. J Mol Neurosci, 2013, 50(1): 33-57.
11. Satyanarayanan SK, Su H, Lin YW, et al. Circadian rhythm and melatonin in the treatment of depression. Curr Pharm Des, 2018, 24(22): 2549-2555.
12. Varinthra P, Liu IY. Molecular basis for the association between depression and circadian rhythm. Tzu Chi Med J, 2019, 31(2): 67-72.
13. Ma WN, Zhou MM, Gou XJ, et al. Urinary metabolomic study of chlorogenic acid in a rat model of chronic sleep deprivation using gas chromatography-mass spectrometry. Int J Genomics, 2018, 2018: 1361402.
14. Zhao S, Chi A, Yan J, et al. Feature of heart rate variability and metabolic mechanism in female college students with depression. Biomed Res Int, 2020, 2020: 5246350.
15. Zeng P, Wang XM, Ye CY, et al. Mechanistic insights into the anti-depressant effect of emodin: an integrated systems pharmacology study and experimental validation. Aging (Albany NY), 2021, 13(11): 15078-15099.
16. Wang Y, Jiang H, Meng H, et al. Antidepressant mechanism research of acupuncture: insights from a genome-wide transcriptome analysis of frontal cortex in rats with chronic restraint stress. Evid Based Complement Alternat Med, 2017, 2017: 1676808.
17. Watanabe Y, Nunokawa A, Kaneko N, et al. Two-stage case-control association study of polymorphisms in rheumatoid arthritis susceptibility genes with schizophrenia. J Hum Genet, 2009, 54(1): 62-65.
18. Hamid HA, Ramli AN, Yusoff MM. Indole alkaloids from plants as potential leads for antidepressant drugs: a mini review. Front Pharmacol, 2017, 8: 96.
19. Jawna-Zboińska K, Blecharz-Klin K, Joniec-Maciejak I, et al. Passiflora incarnata L. improves spatial memory, reduces stress, and affects neurotransmission in rats. Phytother Res, 2016, 30(5): 781-789.
20. Castellvi P, Navinés R, Gutierrez F, et al. Pegylated interferon and ribavirin-induced depression in chronic hepatitis C: role of personality. J Clin Psychiatry, 2009, 70(6): 817-828.

West China Medical Journal

Roles of circadian rhythm and metabolic pathways in depression: identifying biomarkers and predicting novel therapeutic compounds

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