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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
Large-Scale Analyses of GWAS Identify Five Key Pleiotropic Genes Involved in Complex Diseases
Imene Mahdi1, Ghazi Chabchoub2, Najla Kharrat1
1Laboratory of Molecular and Cellular Screening Processes, Centre of Biotechnology of Sfax, University of Sfax, P.O. Box 1177, Sfax 3018, Tunisia.
This study identifies key pleiotropic genes and Single Nucleotide Polymorphisms (SNPs) associated with multiple diseases, revealing genetic insights into complex human conditions.
Area of Science:
- Genetics
- Genomics
- Human Disease Genetics
Background:
- Genome-Wide Association Studies (GWASs) have identified numerous Single Nucleotide Polymorphisms (SNPs) linked to various diseases and traits.
- Extensive pleiotropy, where one gene influences multiple traits, is a common observation in genetic studies.
Purpose of the Study:
- To identify functionally relevant pleiotropic genes using large-scale analysis of the GWAS catalog and variant annotation.
- To prioritize and annotate key pleiotropic genes and their associated variants for genetic and clinical features.
Main Methods:
- Refined an initial set of 494 putative pleiotropic genes to 343 SNP-trait associations involving 53 SNPs and 16 genes.
- Prioritized top genes using a composite score and performed comprehensive annotation of their variants.
Main Results:
- Identified ABO, ALDH2, GCKR, HLA-DQA1, and TERT as key pleiotropic genes with specific associated variants.
- Found that ~70% of SNPs were intronic, with others in UTRs or coding regions, suggesting diverse functional roles.
- Highlighted specific variants like rs8176719 (ABO), rs671 (ALDH2), and rs1260326 (GCKR) with significant associations and functional implications.
Conclusions:
- This research highlights crucial pleiotropic genes and variants contributing to human disease.
- Provides insights into the genetic architecture and underlying mechanisms of complex diseases.
- Emphasizes the importance of variant annotation for understanding pleiotropy and disease.
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