Functional Genomics Analysis to Disentangle the Role of Genetic Variants in Major Depression

Genes (Basel). 2022 Jul 15;13(7):1259. doi: 10.3390/genes13071259.

Abstract

Understanding the molecular basis of major depression is critical for identifying new potential biomarkers and drug targets to alleviate its burden on society. Leveraging available GWAS data and functional genomic tools to assess regulatory variation could help explain the role of major depression-associated genetic variants in disease pathogenesis. We have conducted a fine-mapping analysis of genetic variants associated with major depression and applied a pipeline focused on gene expression regulation by using two complementary approaches: cis-eQTL colocalization analysis and alteration of transcription factor binding sites. The fine-mapping process uncovered putative causally associated variants whose proximal genes were linked with major depression pathophysiology. Four colocalizing genetic variants altered the expression of five genes, highlighting the role of SLC12A5 in neuronal chlorine homeostasis and MYRF in nervous system myelination and oligodendrocyte differentiation. The transcription factor binding analysis revealed the potential role of rs62259947 in modulating P4HTM expression by altering the YY1 binding site, altogether regulating hypoxia response. Overall, our pipeline could prioritize putative causal genetic variants in major depression. More importantly, it can be applied when only index genetic variants are available. Finally, the presented approach enabled the proposal of mechanistic hypotheses of these genetic variants and their role in disease pathogenesis.

Keywords: colocalization analysis; eQTL; genetic regulation; genetic variants; major depression; transcription factors.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Depression
  • Depressive Disorder, Major* / genetics
  • Genomics
  • Humans
  • Quantitative Trait Loci*
  • Transcription Factors / genetics

Substances

  • Transcription Factors

Grants and funding

IMI2-JU resources which are composed of financial contributions from the European Union’s Horizon 2020 Research and Innovation Programme and EFPIA [GA: 116030 TransQST and GA: 777365 eTRANSAFE], and the EU H2020 Programme 2014–2020 [GA: 676559 Elixir-Excelerate]; Project 001-P-001647—Valorisation of EGA for Industry and Society funded by the European Regional Development Fund (ERDF) and Generalitat de Catalunya; Agència de Gestió d’Ajuts Universitaris i de Recerca Generalitat de Catalunya [2017SGR00519], and the Institute of Health Carlos III (project IMPaCT-Data, exp. IMP/00019), co-funded by the European Union, European Regional Development Fund (ERDF, “A way to make Europe”). The Research Programme on Biomedical Informatics (GRIB) is a member of the Spanish National Bioinformatics Institute (INB), funded by ISCIII and ERDF (PRB2-ISCIII [PT13/0001/0023, of the PE I + D + i 2013–2016]). The MELIS is a ‘Unidad de Excelencia María de Maeztu’, funded by the MINECO [MDM-2014-0370]. AMR was supported by CONACYT-FORDECYT-PRONACES grant no. [11311], and Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica–Universidad Nacional Autónoma de México (PAPIIT-UNAM) grant nos. IA203021. JPG was supported by Instituto de Salud Carlos III-Fondo Social Europeo [FI18/00034]; Instituto de Salud Carlos III [MV20]. This work reflects only the author’s view and that the IMI2-JU is not responsible for any use that may be made of the information it contains.