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Precision Medicine Journey Through Omics Approach Publisher



Hasanzad M1, 2 ; Sarhangi N2 ; Ehsani Chimeh S3 ; Ayati N4 ; Afzali M4 ; Khatami F5 ; Nikfar S6 ; Aghaei Meybodi HR2
Authors
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Authors Affiliations
  1. 1. Medical Genomics Research Center, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
  2. 2. Personalized Medicine Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
  3. 3. University of Arizona Cancer Center, Tucson, AZ, United States
  4. 4. Department of Pharmacoeconomics and Pharmaceutical Administration, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
  5. 5. Urology Research Center, Tehran University of Medical Sciences, Tehran, Iran
  6. 6. Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran

Source: Journal of Diabetes and Metabolic Disorders Published:2022


Abstract

It has been well established that understanding the underlying heterogeneity of numerous complex disease process needs new strategies that present in precision medicine for prediction, prevention and personalized treatment strategies. This approach must be tailored for each individual’s unique omics that lead to personalized management of disease. The correlation between different omics data should be considered in precision medicine approach. The interaction provides a hypothesis which is called domino effect in the present minireview. Here we review the various potentials of omics data including genomics, transcriptomics, proteomics, metabolomics, pharmacogenomics. We comprehensively summarize the impact of omics data and its major role in precision medicine and provide a description about the domino effect on the pathophysiology of diseases. Each constituent of the omics data typically provides different information in associated with disease. Current research, although inadequate, clearly indicate that the information of omics data can be applicable in the concept of precision medicine. Integration of different omics data type in domino effect hypothesis can explain the causative changes of disease as it is discussed in the system biology too. While most existing studies investigate the omics data separately, data integration is needed on the horizon of precision medicine by using machine learning. © 2021, Springer Nature Switzerland AG.