Abstract Title

DNA repair polymorphisms and age-related diseases - Alzheimer’s and Cancer: Insights from SNP-set analysis and gene expression association

Presenter Name

Gita Pathak

RAD Assignment Number

1600

Abstract

Purpose: DNA repair response is a common thread for age-related diseases. Genomic stability is the result of an elaborate machinery consisting of damage response, repair, cell-cycle checkpoints, and apoptosis. A compromised DNA damage-repair response either due to time-dependent accumulation of damage or an individual’s reduced DNA repair capacity has been known to derail the genomic defenses, resulting in disease. Recent research findings and epidemiological studies speculate an inverse association between Alzheimer’s and cancer. Since impaired DNA repair is known to accelerate age-related disease, our goal is to evaluate DNA damage/repair genes and identify the role of DNA repair polymorphisms in Alzheimer’s, Breast and Prostate Cancer in individuals.

Methods: The raw genotype and phenotype data were obtained via authorized access application for Alzheimer’s Disease Neuroimaging Initiative and Breast and Prostate Cancer Cohort Consortium; genotype data were generated using the Illumina Human Quad610™ Beadchip. Controls with positive family history were removed; all subjects used were >50 years. Data were processed with in-house codes for QC, mapping SNPs to genes and extracting SNP sets based on 274 candidate genes. SNPs within each set were tested (permutation protocol, mperm=5000) and interpreted for biological relevance after correcting for multiple set-tests. Association analyses accounted for key covariates such as age and sex. Results with genomic inflation of more than 1.03 were adjusted using first three eigenvectors as covariates. Gene expression was imputed for candidate genes. Analyses were performed in Plink(v1.9), EIGENSOFT-6.4, Rstudio 3.4, Bioconductor 3.6, VEGA2, Python 3, PrediXcan and MAGMA.

Results: After two-level QC filtering, the datasets – ADNI, Breast and Prostate cancer – had 677, 578 and 3857 individuals, respectively. Gene-sets of ~167 genes were created for each dataset. Preliminary results point to cancer-specific variants in key DNA repair genes, some of which have not previously been reported. Structured sets of DNA repair pathways and gene expression imputation are in the analysis phase.

Conclusion: This study investigates DNA repair genes in both cancer and Alzheimer’s using SNP-set analysis to improve detection of association that sometimes get lost in whole-genome associations. Our results provide a detailed overview of various DNA repair genes and their association with complex phenotypes of age-associated diseases.

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Research Area

Molecular Genetics

Presentation Type

Poster

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DNA repair polymorphisms and age-related diseases - Alzheimer’s and Cancer: Insights from SNP-set analysis and gene expression association

Purpose: DNA repair response is a common thread for age-related diseases. Genomic stability is the result of an elaborate machinery consisting of damage response, repair, cell-cycle checkpoints, and apoptosis. A compromised DNA damage-repair response either due to time-dependent accumulation of damage or an individual’s reduced DNA repair capacity has been known to derail the genomic defenses, resulting in disease. Recent research findings and epidemiological studies speculate an inverse association between Alzheimer’s and cancer. Since impaired DNA repair is known to accelerate age-related disease, our goal is to evaluate DNA damage/repair genes and identify the role of DNA repair polymorphisms in Alzheimer’s, Breast and Prostate Cancer in individuals.

Methods: The raw genotype and phenotype data were obtained via authorized access application for Alzheimer’s Disease Neuroimaging Initiative and Breast and Prostate Cancer Cohort Consortium; genotype data were generated using the Illumina Human Quad610™ Beadchip. Controls with positive family history were removed; all subjects used were >50 years. Data were processed with in-house codes for QC, mapping SNPs to genes and extracting SNP sets based on 274 candidate genes. SNPs within each set were tested (permutation protocol, mperm=5000) and interpreted for biological relevance after correcting for multiple set-tests. Association analyses accounted for key covariates such as age and sex. Results with genomic inflation of more than 1.03 were adjusted using first three eigenvectors as covariates. Gene expression was imputed for candidate genes. Analyses were performed in Plink(v1.9), EIGENSOFT-6.4, Rstudio 3.4, Bioconductor 3.6, VEGA2, Python 3, PrediXcan and MAGMA.

Results: After two-level QC filtering, the datasets – ADNI, Breast and Prostate cancer – had 677, 578 and 3857 individuals, respectively. Gene-sets of ~167 genes were created for each dataset. Preliminary results point to cancer-specific variants in key DNA repair genes, some of which have not previously been reported. Structured sets of DNA repair pathways and gene expression imputation are in the analysis phase.

Conclusion: This study investigates DNA repair genes in both cancer and Alzheimer’s using SNP-set analysis to improve detection of association that sometimes get lost in whole-genome associations. Our results provide a detailed overview of various DNA repair genes and their association with complex phenotypes of age-associated diseases.