Identification and validation of depression-associated genetic variants in the UK Biobank cohort with transcriptome and DNA methylation analyses in independent cohorts
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 transcri...
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Elsevier
2025-01-01
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| author | Muataz S. Lafta Aleksandr V. Sokolov Gull Rukh Helgi B. Schiöth |
| author_facet | Muataz S. Lafta Aleksandr V. Sokolov Gull Rukh Helgi B. Schiöth |
| author_sort | Muataz S. Lafta |
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| description | 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. |
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| institution | Kabale University |
| issn | 2405-8440 |
| language | English |
| publishDate | 2025-01-01 |
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| spelling | doaj-art-dce05df215c44937bc560d21dbb0932b2025-02-02T05:28:25ZengElsevierHeliyon2405-84402025-01-01112e41865Identification and validation of depression-associated genetic variants in the UK Biobank cohort with transcriptome and DNA methylation analyses in independent cohortsMuataz S. Lafta0Aleksandr V. Sokolov1Gull Rukh2Helgi B. Schiöth3Department of Surgical Sciences, Functional Pharmacology and Neuroscience, Uppsala University, Uppsala, SwedenDepartment of Surgical Sciences, Functional Pharmacology and Neuroscience, Uppsala University, Uppsala, SwedenCorresponding author. Department of Surgical Sciences Uppsala University Husargatan 3 BOX 593, 751 24 Uppsala Sweden.; Department of Surgical Sciences, Functional Pharmacology and Neuroscience, Uppsala University, Uppsala, SwedenDepartment of Surgical Sciences, Functional Pharmacology and Neuroscience, Uppsala University, Uppsala, SwedenDepression 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.http://www.sciencedirect.com/science/article/pii/S2405844025002452UK biobankDepressionIndependent genetic variantsGenetic risk scoreTranscriptomeMethylation |
| spellingShingle | Muataz S. Lafta Aleksandr V. Sokolov Gull Rukh Helgi B. Schiöth Identification and validation of depression-associated genetic variants in the UK Biobank cohort with transcriptome and DNA methylation analyses in independent cohorts Heliyon UK biobank Depression Independent genetic variants Genetic risk score Transcriptome Methylation |
| title | Identification and validation of depression-associated genetic variants in the UK Biobank cohort with transcriptome and DNA methylation analyses in independent cohorts |
| title_full | Identification and validation of depression-associated genetic variants in the UK Biobank cohort with transcriptome and DNA methylation analyses in independent cohorts |
| title_fullStr | Identification and validation of depression-associated genetic variants in the UK Biobank cohort with transcriptome and DNA methylation analyses in independent cohorts |
| title_full_unstemmed | Identification and validation of depression-associated genetic variants in the UK Biobank cohort with transcriptome and DNA methylation analyses in independent cohorts |
| title_short | Identification and validation of depression-associated genetic variants in the UK Biobank cohort with transcriptome and DNA methylation analyses in independent cohorts |
| title_sort | identification and validation of depression associated genetic variants in the uk biobank cohort with transcriptome and dna methylation analyses in independent cohorts |
| topic | UK biobank Depression Independent genetic variants Genetic risk score Transcriptome Methylation |
| url | http://www.sciencedirect.com/science/article/pii/S2405844025002452 |
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