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Proteomics

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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
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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

Multi-omics profiling approach in food allergy.

Ashley Devonshire¹, Yadu Gautam², Elisabet Johansson²

¹Division of Allergy and Immunology, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA.

The World Allergy Organization Journal

|May 22, 2023

Summary

Food allergy (FA) is rising in children, causing anaphylaxis. Omics studies, integrating genomics, proteomics, and metabolomics, offer new ways to find biomarkers for better diagnosis and precision medicine.

Keywords:

Food allergy Genomics Immunoglobulin E Multi-omics Oral food challenge Skin prick test

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Area of Science:

Immunology
Genetics
Environmental Health

Background:

Food allergy (FA) prevalence in children is increasing, impacting 8% and causing anaphylaxis.
FA is a complex, multifactorial disease involving immune responses, genetics, and environmental factors.
Early environmental exposures significantly influence immune development and allergen responses.

Purpose of the Study:

To review current omics studies for food allergy biomarker discovery.
To discuss the integration of multi-omics data for advancing FA research.
To highlight the potential for precision medicine in food allergy management.

Main Methods:

Genomic, transcriptomic, epigenomic, proteomic, exposomic, and metabolomic approaches.
Review of high-throughput omics technologies for biomarker screening.
Discussion of multi-omics data integration with clinical data.

Main Results:

Omics studies screen for genes, transcripts, proteins, and metabolites as potential FA biomarkers.
Individual omics technologies provide limited insights into FA's complexity.
Multi-omics integration with clinical data is crucial for robust biomarker discovery.

Conclusions:

Integrating population-based multi-omics and clinical data can advance FA biomarker discovery.
Advances in biomarker discovery can lead to improved disease management and precision medicine.
Future research should focus on multi-omics integration for comprehensive FA understanding.