Event Date:
April 11th 12:00 PM - 2:00 PM
Makaela Mews, BS
PhD Candidate in Systems Biology & Bioinformatics (SYBB)
Advisor: William S. Bush, PhD
Advisor: William S. Bush, PhD
Location: Biomedical Research Building Room 105 or via Livestream:
Abstract:
Elucidating the Genetic Architecture Underlying Gene Expression Regulation in Alzheimer’s Disease
Alzheimer's disease (AD) affects over 30 million people worldwide, with substantial economic and social burdens. Despite high heritability (60-80%), known genetic variants explain only 30% of AD's genetic variance and nearly all of the identified associations fall within non-coding regions of the genome making their role in AD risk difficult to interpret. A key component to the translation of these findings into drug targets is understanding how these non-coding variants influence gene expression. This study addresses this knowledge gap by integrating large-scale transcriptomic data from the blood and brain with genome-wide association studies to identify functional mechanisms underlying AD genetic risk. Additionally, we investigated how AD status modulates whole blood gene expression regulation across diverse cohorts to elucidate dynamic interplay between an AD context and functional genetic variation.
Our TWAS framework identified and validated two novel genes in cortical brain tissue (BPHL and SPATA7) and several genes proximal to known AD loci, including MTCH2 and NDUFS3. Using AD-related disorders (ADRD) summary statistics, we identified TRAF3 in blood and IRAG1 in brain as novel associations. Fine-mapping causal eQTLs improved AD-TWAS power for several genes, including MYBPC3 in blood and MTCH2 in brain. Our eQTL analysis across diverse cohorts revealed substantial population-specific effects in AD-responsive eQTLs (ADR-eQTLs), with 11-22% of shared ADR-eQTLs showing cohort-specific effects. We identified 68 ADR-eGenes shared among multiple cohorts, suggesting core regulatory mechanisms in AD, with enrichment for transcription factors ELF2 and ZFHX3 target genes. Notably, ADR-eQTLs displayed distinct distribution patterns compared to conventional eQTLs, primarily located upstream and downstream of gene regions rather than within intragenic regions.
These findings expand our understanding of AD-related genetic mechanisms, identifying genes involved in homocysteine detoxification, immune signaling, mitochondrial function, and vascular regulation. The observed cohort-specific effects in gene expression regulation underscore the importance of diverse sampling in AD research. This work bridges the gap between statistical associations and actionable biological insights, providing potential targets for therapeutic development while highlighting the complex interplay between genetics, gene expression, and AD pathogenesis across diverse populations.
Alzheimer's disease (AD) affects over 30 million people worldwide, with substantial economic and social burdens. Despite high heritability (60-80%), known genetic variants explain only 30% of AD's genetic variance and nearly all of the identified associations fall within non-coding regions of the genome making their role in AD risk difficult to interpret. A key component to the translation of these findings into drug targets is understanding how these non-coding variants influence gene expression. This study addresses this knowledge gap by integrating large-scale transcriptomic data from the blood and brain with genome-wide association studies to identify functional mechanisms underlying AD genetic risk. Additionally, we investigated how AD status modulates whole blood gene expression regulation across diverse cohorts to elucidate dynamic interplay between an AD context and functional genetic variation.
Our TWAS framework identified and validated two novel genes in cortical brain tissue (BPHL and SPATA7) and several genes proximal to known AD loci, including MTCH2 and NDUFS3. Using AD-related disorders (ADRD) summary statistics, we identified TRAF3 in blood and IRAG1 in brain as novel associations. Fine-mapping causal eQTLs improved AD-TWAS power for several genes, including MYBPC3 in blood and MTCH2 in brain. Our eQTL analysis across diverse cohorts revealed substantial population-specific effects in AD-responsive eQTLs (ADR-eQTLs), with 11-22% of shared ADR-eQTLs showing cohort-specific effects. We identified 68 ADR-eGenes shared among multiple cohorts, suggesting core regulatory mechanisms in AD, with enrichment for transcription factors ELF2 and ZFHX3 target genes. Notably, ADR-eQTLs displayed distinct distribution patterns compared to conventional eQTLs, primarily located upstream and downstream of gene regions rather than within intragenic regions.
These findings expand our understanding of AD-related genetic mechanisms, identifying genes involved in homocysteine detoxification, immune signaling, mitochondrial function, and vascular regulation. The observed cohort-specific effects in gene expression regulation underscore the importance of diverse sampling in AD research. This work bridges the gap between statistical associations and actionable biological insights, providing potential targets for therapeutic development while highlighting the complex interplay between genetics, gene expression, and AD pathogenesis across diverse populations.