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Updated: Feb 10, 2026
08:27
Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
4.9K
[Genome-wide association studies: recent advances and future directions]
Kazuhiko Nakabayashi1, Atsushi Tajima, Senji Shirasawa
1Department of Maternal-Fetal Biology, National Center for Child Health and Development.
Nihon Rinsho. Japanese Journal of Clinical Medicine
|March 14, 2009
Summary
Genome-wide association studies (GWAS) are now feasible thanks to advances in human genetic variation data and genotyping technology. These studies have identified numerous disease risk loci, but future research will focus on structural variants and rare SNPs for deeper insights.
Area of Science:
- Human Genetics
- Genomics
- Molecular Biology
Context:
- The HapMap project and high-throughput genotyping have enabled genome-wide association studies (GWAS).
- Recent GWAS have identified numerous genetic loci associated with common diseases like rheumatoid arthritis and systemic lupus erythematosus.
- These studies have fostered consensus on methodological and technical aspects of genetic research.
Purpose:
- To review the progress and limitations of common single nucleotide polymorphism (SNP)-based GWAS.
- To highlight the ongoing efforts in cataloguing broader human genetic variation, including structural variants and rare SNPs.
- To underscore the potential of comprehensive genetic variation data in identifying disease risk variants.
Summary:
- Genome-wide association studies (GWAS) have become technically feasible due to advancements in human genetic variation data and genotyping technologies.
- Numerous disease-associated genetic loci have been identified for common conditions, validating the GWAS approach.
- Current limitations in common SNP-based GWAS are recognized, prompting research into structural variants and rare SNPs for a more comprehensive understanding of genetic risk.
Impact:
- Accelerated identification of genetic risk variants for common diseases.
- Improved understanding of the genetic architecture of complex human diseases.
- Advancement of personalized medicine through genetic risk profiling.
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