Use of omic technologies in early life gastrointestinal health and disease: from bench to bedside
| Autor: | Claire L Granger, Lauren C Beck, Andrea C Masi, Christopher J. Stewart |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Proteomics
0301 basic medicine medicine.medical_specialty Disease Biochemistry 03 medical and health sciences medicine Humans Metabolomics Biomarker discovery Child Intensive care medicine Molecular Biology 030102 biochemistry & molecular biology business.industry Infant Newborn Omics Bench to bedside Gut microbiome Early life Gastrointestinal Microbiome Gastrointestinal Tract Biomarker 030104 developmental biology Metagenomics business |
| Zdroj: | Expert Review of Proteomics. 18:247-259 |
| ISSN: | 1744-8387 1478-9450 |
| Popis: | Introduction At birth, the gastrointestinal (GI) tract is colonized by a complex community of microorganisms, forming the basis of the gut microbiome. The gut microbiome plays a fundamental role in host health, disorders of which can lead to an array of GI diseases, both short and long-term. Pediatric GI diseases are responsible for significant morbidity and mortality, but many remain poorly understood. The recent advancement of high-throughput technologies has enabled deeper profiling of GI morbidities. Technologies such as metagenomics, transcriptomics, proteomics and metabolomics, have already been used to identify associations with specific pathologies, and highlight an exciting area of research. However, since these diseases are often complex and multifactorial by nature, reliance on a single experimental approach may not capture the true biological complexity. Therefore, multi-omics aims to integrate singular omic data to further enhance our understanding of disease. Areas covered This review will discuss and provide an overview of the main omic technologies that are used to study complex GI pathologies in early life. Expert opinion Multi-omic technologies can help to unravel the complexities of several diseases during early life, aiding in biomarker discovery and enabling the development of novel therapeutics and augment predictive models. |
| Databáze: | OpenAIRE |
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