A Genome Wide Association Study (GWAS) to Detect Single-nucleotide Polymorphisms (SNPs) and Identify Risk Loci for Parkinson Disease
Session Number
Project ID: MEDH 14
Advisor(s)
Dr. Steven Lubbe, Feinberg School of Medicine, Northwestern University
Discipline
Medical and Health Sciences
Start Date
20-4-2022 10:25 AM
End Date
20-4-2022 10:40 AM
Abstract
Parkinson’s disease (PD) is a severe neurodegenerative disease, resulting from complex interactions between genetic and environmental factors. To analyze the genetic foundations of the disease, a genome-wide association study (GWAS) can be employed to filter genetic markers, identify single-nucleotide polymorphisms (SNPs), and associate genetic variants. Identification of SNPs significantly contributes to the accuracy of polygenic risk scores (PRS; risk score dependent on SNPs in independent cases).
Through a hypothesis-free whole-exome sequencing (WES) analysis of 10,035 control samples and 5,333 case samples, predominantly from individuals of European descent, we identified multiple risk locus and markers of early-onset PD (less than 40 years). Methodology was three-fold: quality control (QC), population stratification, and association. QC enabled the removal of 2,000+ data-skewing samples through comparison to the Human Genome Database, testing for sex, inbreeding, heterozygosity, SNP missingness, and minor allele frequency. Population stratification enabled the identification of a sample demographic (EU). Genome association allowed for the generation of Manhattan plots (with baseline significance of p = 5.0 x 10-8), which
compared statistificance significance (as -log10p) against chromosomes. Results indicated SNPs of this sample existed most significantly on
locis 4, 13, 15, and 17.
A Genome Wide Association Study (GWAS) to Detect Single-nucleotide Polymorphisms (SNPs) and Identify Risk Loci for Parkinson Disease
Parkinson’s disease (PD) is a severe neurodegenerative disease, resulting from complex interactions between genetic and environmental factors. To analyze the genetic foundations of the disease, a genome-wide association study (GWAS) can be employed to filter genetic markers, identify single-nucleotide polymorphisms (SNPs), and associate genetic variants. Identification of SNPs significantly contributes to the accuracy of polygenic risk scores (PRS; risk score dependent on SNPs in independent cases).
Through a hypothesis-free whole-exome sequencing (WES) analysis of 10,035 control samples and 5,333 case samples, predominantly from individuals of European descent, we identified multiple risk locus and markers of early-onset PD (less than 40 years). Methodology was three-fold: quality control (QC), population stratification, and association. QC enabled the removal of 2,000+ data-skewing samples through comparison to the Human Genome Database, testing for sex, inbreeding, heterozygosity, SNP missingness, and minor allele frequency. Population stratification enabled the identification of a sample demographic (EU). Genome association allowed for the generation of Manhattan plots (with baseline significance of p = 5.0 x 10-8), which
compared statistificance significance (as -log10p) against chromosomes. Results indicated SNPs of this sample existed most significantly on
locis 4, 13, 15, and 17.