Metabolomics in personalized medicine

Publish Year: 1395
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:

IPMCMED01_130

تاریخ نمایه سازی: 23 آذر 1397

Abstract:

The sequencing of the human genome and other genomes assigns potent protein data sets for making beneficial contributions to medicine and human health issues. Personalized medicine that focuses on molecular diagnostics makes it possible to improve safety, effectiveness and the costs of the treatment based on patient’s individual needs. Identification of novel, better biomarkers would allow understanding of the molecular pathways involved in the pathophysiology of the rheumatoid arthritis (RA) and more appropriate selection of the optimal treatments for first-line care. Because multiple genes are involved in the pathogenesis of RA, genome-wide association studies (GWAS) could be a more potent approach for identifying candidate genes. Because the effect size of genetic associations with clinical phenotypes is often small, large populations need to be screened in order to obtain sufficient statistical power for the identification of new disease-causing genetic variants. Metabolomics which is the rapidly evolving field of measuring all endogenous metabolites in a cell or body fluid may contribute to solving this problem. Biochemical measurements of particular intermediate phenotypes on a continuous scale can be expected to provide more details on potentially affected pathways and to be more directly related to the etiology of the disease. Metabolomics delivers its promise of providing access to functionally relevant endpoints in the framework of GWA studies, and thereby opens new avenues for a functional investigation of the role of gene environment interactions in the etiology of complex diseases. The investigation of the genetically determined metabolomics in their biochemical context might help to better understand the pathogenesis of common diseases and gene–environment interactions. These findings could result in a step towards personalized health care and nutrition based on a combination of genotyping and metabolic characterization.

Authors

Golbarg Mehrpoor

Alborz university of medical sciences