| Title: | Identification and validation of depression-associated genetic variants in the UK Biobank cohort with transcriptome and DNA methylation analyses in independent cohorts |
| Journal: | Heliyon |
| Published: | 10 Jan 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39897774/ |
| DOI: | https://doi.org/10.1016/j.heliyon.2025.e41865 |
Publication 14535
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Abstract
Depression is one of the most common psychiatric conditions resulting from a complex interaction of genetic, epigenetic and environmental factors. The present study aimed to identify independent genetic variants in the protein-coding genes that associate with depression and to analyze their transcriptomic and methylation profile. Data from the GWAS Catalogue was used to identify independent genetic variants for depression. The identified genetic variants were validated in the UK Biobank cohort and used to calculate a genetic risk score for depression. Data was also used from publicly available cohorts to conduct transcriptome and methylation analyses. Eight SNPs corresponding to six protein-coding genes (TNXB, NCAM1, LTBP3, BTN3A2, DAG1, FHIT) were identified that were highly associated with depression. These validated genetic variants for depression were used to calculate a genetic risk score that showed a significant association with depression (p < 0.05) but not with co-morbid traits. The transcriptome and methylation analyses suggested nominal significance for some gene probes (TNXB- and NCAM1) with depressed phenotype. The present study identified six protein-coding genes associated with depression and primarily involved in inflammation (TNXB), neuroplasticity (NCAM1 and LTBP3), immune response (BTN3A2), cell survival (DAG1) and circadian clock modification (FHIT). Our findings confirmed previous evidence for TNXB- and NCAM1 in the pathophysiology of depression and suggested new potential candidate genes (LTBP3, BTN3A2, DAG1 and FHIT) that warrant further investigation.</p>
4 Authors
- Muataz S. Lafta
- Aleksandr V. Sokolov
- Gull Rukh
- Helgi B. Schiöth
1 Application
| Application ID | Title |
|---|---|
| 30172 | Comorbidities between addiction and mental disorders ? association of genetics, biomarkers and environment (e.g. lifestyle) with mental health and cognitive function |
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