High-throughput sequencing of the synaptome in major depressive disorder

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21 Scopus citations

Abstract

Major depressive disorder (MDD) is among the leading causes of worldwide disability. Despite its significant heritability, large-scale genome-wide association studies (GWASs) of MDD have yet to identify robustly associated common variants. Although increased sample sizes are being amassed for the next wave of GWAS, few studies have as yet focused on rare genetic variants in the study of MDD. We sequenced the exons of 1742 synaptic genes previously identified by proteomic experiments. PLINK/SEQ was used to perform single variant, gene burden and gene set analyses. The GeneMANIA interaction database was used to identify protein-protein interaction-based networks. Cases were selected from a familial collection of early-onset, recurrent depression and were compared with screened controls. After extensive quality control, we analyzed 259 cases with familial, early-onset MDD and 334 controls. The distribution of association test statistics for the single variant and gene burden analyses were consistent with the null hypothesis. However, analysis of prioritized gene sets showed a significant association with damaging singleton variants in a Cav2-adaptor gene set (odds ratio=2.6; P=0.0008) that survived correction for all gene sets and annotation categories tested (empirical P=0.049). In addition, we also found statistically significant evidence for an enrichment of rare variants in a protein-based network of 14 genes involved in actin polymerization and dendritic spine formation (nominal P=0.0031). In conclusion, we have identified a statistically significant gene set and gene network of rare variants that are over-represented in MDD, providing initial evidence that calcium signaling and dendrite regulation may be involved in the etiology of depression.

Original languageEnglish (US)
Pages (from-to)650-655
Number of pages6
JournalMolecular psychiatry
Volume21
Issue number5
DOIs
StatePublished - May 1 2016

ASJC Scopus subject areas

  • Molecular Biology
  • Cellular and Molecular Neuroscience
  • Psychiatry and Mental health

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