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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Combinatorial search methods for multi-SNP disease association.

Dumitru Brinza¹, Jingwu He, Alexander Zelikovsky

¹Dept. of Comput. Sci., Georgia State Univ., Atlanta, GA 30303, USA. dima@cs.gsu.edu

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference

|October 20, 2007

Summary

This study introduces a new method to efficiently identify complex disease associations using multi-SNP combinations (MSCs). The approach successfully detected significant genetic markers for Crohn's disease and autoimmune disorders, outperforming single-locus analyses.

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Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

Area of Science:

Genetics
Computational Biology
Disease Association Studies

Background:

Genome-wide association studies (GWAS) are crucial for understanding complex diseases.
Current GWAS often focus on single or two-locus interactions, potentially missing deeper multi-locus associations.
Exhaustive multi-locus analysis is computationally infeasible due to the vast number of single nucleotide polymorphisms (SNPs).

Purpose of the Study:

To develop an efficient computational method for identifying multi-SNP combinations (MSCs) associated with complex diseases.
To overcome the computational limitations of exhaustive multi-locus analysis in GWAS.
To discover novel disease-associated genetic interactions beyond single-locus associations.

Main Methods:

Proposed a method to select informative "indexing" SNPs for efficient genome representation.
Developed a novel combinatorial approach to analyze multi-SNP combinations (MSCs) within the reduced SNP set.
Applied the methods to real-world genetic datasets for Crohn's disease and autoimmune disorders.

Main Results:

Successfully identified statistically significant unphased MSCs associated with Crohn's disease, with p-values below 0.05 after multiple testing correction.
The identified MSCs showed significant associations where single SNPs or pairs of SNPs did not.
Discovered new unphased and phased MSCs linked to autoimmune disorders in a separate dataset.

Conclusions:

The proposed method effectively identifies significant multi-SNP disease associations, overcoming limitations of single-locus analyses.
This approach enables the discovery of complex genetic interactions relevant to common complex diseases.
The findings highlight the importance of multi-locus analysis in advancing our understanding of disease genetics.