Genetic Impact of Structural Variants on Brain Function and Neurodegeneration

Structural variants (SVs), large genomic rearrangements exceeding 50 base pairs, significantly contribute to genetic diversity and phenotypic variation. Despite extensive studies linking SVs to diseases like schizophrenia and autism, their role in brain function and neurodegenerative diseases remains underexplored. This study addresses this gap by analyzing SVs in brain tissues using whole-genome sequencing (WGS) and multi-omics approaches, revealing their extensive impact on gene regulation.

Methods and Data Sources
Researchers analyzed 1,760 human genomes from aging cohorts, including ROS/MAP, Mayo Clinic, and Mount Sinai Brain Bank (MSBB), using WGS and multi-omics data. The integration involved:
RNA sequencing (RNA-seq): Measuring mRNA levels.
Histone acetylation (H3K9ac ChIP-seq): Assessing epigenetic modifications.
Proteomics (TMT-MS): Evaluating protein abundance.

SVs were classified into deletions, duplications, insertions, inversions, and complex rearrangements. Advanced computational tools and rigorous quality controls ensured accurate variant detection and phenotypic associations.

Key Findings
Discovery and Characterization of SVs:
Over 170,000 SVs were identified, with most being rare variants (< 5% allele frequency).
The ROS/MAP cohort showed the highest SV detection, attributed to larger sample sizes and diverse ancestry representation.

Impact on Molecular Phenotypes:
Gene Expression (eQTL): 3,191 SVs were associated with altered RNA expression, with deletions showing the strongest effects.
Splicing (sQTL): SVs influenced alternative splicing patterns in over 2,800 cases.
Histone Modifications (haQTL): 1,454 SVs were linked to changes in H3K9ac peaks, highlighting their role in chromatin regulation.
Protein Abundance (pQTL): Nearly 400 SVs affected protein levels, often correlating with RNA changes.

Multi-Phenotype Effects:
Concordant effects were observed in 87% of SV-associated RNA and protein pairs, underscoring a shared regulatory mechanism.
Mediation analysis revealed histone acetylation and splicing as intermediate steps for SV effects on gene expression and protein levels.

Rare SVs and Outliers:
Rare variants (< 1% frequency) significantly enriched gene expression and protein outliers, with examples of deletions reducing expression and duplications increasing it.

Implications for Neurodegenerative Diseases
This study identified SVs associated with progressive supranuclear palsy (PSP) and other brain disorders. For example:
A 1-megabase inversion at the 17q21.31 locus was linked to PSP, impacting gene expression and splicing in the MAPT region.
SVs near Alzheimer’s and schizophrenia risk loci showed significant molecular phenotypic effects, including altered histone acetylation and RNA expression.

Challenges and Limitations
While robust, this research faced limitations:
Short-read sequencing constraints: Reduced sensitivity for large and complex SVs.
Small sample sizes for proteomics: Limited statistical power compared to RNA-seq and histone data.

Conclusion
This comprehensive study underscores the pivotal role of SVs in regulating brain gene expression, splicing, and protein abundance. By integrating WGS with multi-omic data, it advances our understanding of genetic mechanisms in brain function and neurodegeneration. Future research should leverage long-read sequencing and larger cohorts to enhance SV detection and explore their causal relationships with neurological diseases.

References:
Vialle, R.A., de Paiva Lopes, K., Bennett, D.A. et al. Integrating whole-genome sequencing with multi-omic data reveals the impact of structural variants on gene regulation in the human brain. Nat Neurosci 25, 504–514 (2022).