From variants to mechanisms: Neurogenomics in the post-GWAS era

Area of Science:

• Genetics
• Neuroscience
• Computational Biology

Background:

• Genome-wide association studies (GWASs) have identified numerous variants associated with neuropsychiatric disorders (NPDs) like autism spectrum disorder (ASD), schizophrenia (SCZ), and Alzheimer's disease (AD).
• Understanding the causal biological mechanisms and pathways of these variants is a significant challenge for NPD pathogenesis research.
• NPDs are polygenic, involving pleiotropic variants often located in non-coding genomic regions.

Purpose of the Study:

• To discuss functional genomic, machine learning, and experimental approaches for deciphering variant effects in NPDs.
• To identify disease-relevant cell types and states for mechanistic insight.
• To integrate findings across loci to pinpoint pathways of polygenic convergence.

Main Methods:

• Functional genomics to map variant-to-gene effects.
• Machine learning to analyze large-scale genomic data.
• Experimental validation of identified pathways.

Main Results:

• The abstract discusses approaches rather than presenting specific results.
• Highlights the need for integrating diverse methodologies for mechanistic understanding.
• Emphasizes the importance of identifying cell-type-specific variant effects.

Conclusions:

• Convergence of results across methodologies and within key disease pathways is crucial.
• These integrated approaches are essential for clinical translation of findings for complex brain disorders.
• Advancing mechanistic insight into NPD pathogenesis requires a multi-pronged strategy.