Cabana-Domínguez · Translational psychiatry 2022 · secondary gene-set analysis of GWAS meta-analyses · n=>435,000 (>160,000 cases and >275,000 controls)

Comprehensive exploration of the genetic contribution of the dopaminergic and serotonergic pathways to psychiatric disorders.

Level 4 - case-series / case-control

Secondary gene-set and pathway analysis of observational case-control genome-wide association studies

PubMed 35013130 · doi:10.1038/s41398-021-01771-3 · record verified 2026-08-26

What was done

Researchers evaluated the genetic contribution of dopamine (DA) and serotonin (SERT) pathways across eight psychiatric disorders: attention-deficit hyperactivity disorder (ADHD), anorexia nervosa (ANO), autism spectrum disorder (ASD), bipolar disorder (BIP), major depression (MD), obsessive-compulsive disorder (OCD), schizophrenia (SCZ), and Tourette's syndrome (TS). They analyzed publicly available Psychiatric Genomics Consortium GWAS datasets comprising over 160,000 cases and 275,000 controls. Four gene sets were tested: two broad sets derived from Gene Ontology and KEGG pathways, and two manually curated core sets for DA and SERT.

What was found

Across the DA and SERT gene sets, 67 genes reached significant association with at least one disorder, and 12 genes were associated with two different disorders. In gene-set level analyses, the wide DA gene set was significantly associated with ADHD, ASD, and an omnibus cross-disorder GWAS meta-analysis of all eight conditions. The wide SERT gene set was significantly associated with BIP, while the core SERT gene set was significantly associated with MD. The abstract reports gene counts and categorical associations but does not provide exact p-values, odds ratios, or effect sizes.

Why it matters

This study provides systematic pathway-level evidence that dopaminergic and serotonergic gene variations confer shared and distinct genetic liability across multiple psychiatric diagnoses.

Limits

The abstract does not report specific effect sizes, variance explained, or exact p-values. Findings rely on secondary analysis of existing summary statistics rather than functional biological validation. In addition, gene-set definitions depend on pathway database annotations and curation choices that may be incomplete.