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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

Genetics of allergic diseases.

Romina A Ortiz¹, Kathleen C Barnes¹

¹Department of Medicine, The Johns Hopkins Asthma and Allergy Center, 5501 Hopkins Bayview Circle, Room 3A.62, Baltimore, MD 21224, USA.

Immunology and Allergy Clinics of North America

|December 3, 2014

Summary

Genome-wide association studies (GWAS) have identified nearly 100 asthma genes. Advanced sequencing now helps pinpoint causal variants for allergic diseases, but diverse data and big data management remain challenges.

Keywords:

Allergic disease Epigenetics Genetics Genome-wide association study Next-generation sequencing Single nucleotide polymorphism Transcriptome

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Area of Science:

Genetics and genomics
Immunology
Allergic diseases research

Background:

Genome-wide association studies (GWAS) have identified nearly 100 genes/loci associated with asthma.
GWAS in allergic diseases have fostered large-scale collaborations and meta-analyses.
Genetic associations are often specific to particular allergic disease sub-phenotypes.

Purpose of the Study:

To review the advancements in genetic research for allergic diseases.
To highlight the role of next-generation sequencing in identifying causal variants.
To identify unmet needs in the field, including cohort diversity and data management.

Main Methods:

Review of genome-wide association studies (GWAS) findings in allergic diseases.
Discussion of next-generation sequencing (NGS) strategies.
Analysis of collaborative efforts and consortia meta-analyses.

Main Results:

Identification of nearly 100 asthma-associated genes/loci through GWAS.
Demonstration of the specificity of genetic associations to allergic disease sub-phenotypes.
Advancements in molecular genetics enabling precise identification of causal variants.

Conclusions:

Next-generation sequencing offers powerful tools for identifying causal variants in allergic diseases.
The field requires more diverse cohorts to ensure generalizability of findings.
Effective strategies for managing large datasets are crucial for future progress in allergic disease genetics.