SCZEWAS

SCZEWAS analyzes the co-localization of genetic associations and differential DNA methylation to identify regulatory variation underlying complex neuropsychiatric disorders such as schizophrenia.

Key Features:

• Multi-Stage Epigenome-Wide Association Study (EWAS): Quantifies genome-wide DNA methylation patterns across multiple independent cohorts to identify differentially methylated positions and regions (DMPs/DMRs).
• Confounder Adjustment: Ensures identified methylation associations are evaluated with statistical control for confounders such as smoking.
• Polygenic Nature Analysis: Assesses how epigenetic variation across loci contributes to the polygenic architecture of disorders and integrates DNA methylation quantitative trait loci (meQTLs).
• Bayesian Co-Localization Analyses and Annotation: Applies Bayesian co-localization to annotate extended genomic regions and distinguish putative causal regulatory variation from mere correlation.
• Polygenic Risk Score Integration: Correlates molecular variation with etiological factors using polygenic risk scores.

Scientific Applications:

• Schizophrenia research: Systematic analysis of genetic and epigenetic variation to nominate potential causal genes and regulatory mechanisms in schizophrenia.
• Complex trait and disease analysis: Framework for integrating genetic, meQTL, methylation, and polygenic risk data applicable to other complex traits and diseases.

Methodology:

Combines epigenome-wide DNA methylation profiling (EWAS) across multiple cohorts with Bayesian co-localization analyses; integrates meQTL mapping and polygenic risk score correlation; applies statistical adjustment for confounders such as smoking and annotates extended genomic regions to identify regulatory variation.