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Multiomic approach in precision medicine

NextEdge Admin

23 Sep 2023

2 min 40 sec

A multiomic approach to precision medicine involves integrating data from various “omics” disciplines, including genomics, transcriptomics, proteomics, metabolomics, and epigenomics, to gain a comprehensive understanding of an individual’s health and to tailor medical interventions accordingly. Here’s how the multiomic approach is applied in precision medicine:

Genomics: Genomic data involves sequencing an individual’s entire genome to identify genetic variations, including single nucleotide polymorphisms (SNPs), insertions, deletions, and structural variants. This information can reveal genetic predispositions to certain diseases, drug metabolism capabilities, and potential risk factors.

Transcriptomics: Transcriptomics focuses on the study of RNA molecules, including messenger RNA (mRNA) and non-coding RNA. It provides insights into gene expression patterns, allowing researchers to understand which genes are active and to what extent. This information helps identify dysregulated pathways and potential therapeutic targets.

Proteomics: Proteomic data involves the identification and quantification of proteins in an individual’s cells, tissues, or body fluids. Proteomics can reveal post-translational modifications and protein-protein interactions, shedding light on the functional aspects of cellular processes. Understanding the proteome is crucial for drug development and personalized treatment strategies.

Metabolomics: Metabolomics measures small molecules, known as metabolites, in biological samples. These molecules are the end products of various biochemical pathways and can reflect the metabolic status of an individual. Metabolomics is valuable for understanding disease mechanisms, identifying biomarkers, and predicting drug responses.

Epigenomics: Epigenomic data focuses on modifications to the DNA molecule and associated proteins, such as DNA methylation and histone modifications. Epigenetic changes can influence gene expression and are implicated invarious diseases. Epigenomic data can help identify epigenetic markers associated with disease risk and prognosis.