Literature DB >> 35673436

Precision medicine journey through omics approach.

Mandana Hasanzad1,2, Negar Sarhangi2, Sima Ehsani Chimeh3, Nayereh Ayati4, Monireh Afzali4, Fatemeh Khatami5, Shekoufeh Nikfar6, Hamid Reza Aghaei Meybodi2.   

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. © Springer Nature Switzerland AG 2021.

Entities:  

Keywords:  Omics; Personalized medicine; Precision medicine

Year:  2021        PMID: 35673436      PMCID: PMC9167178          DOI: 10.1007/s40200-021-00913-0

Source DB:  PubMed          Journal:  J Diabetes Metab Disord        ISSN: 2251-6581


  73 in total

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Journal:  Nat Rev Drug Discov       Date:  2016-03-11       Impact factor: 84.694

Review 5.  Molecular subtypes, stem cells and heterogeneity: Implications for personalised therapy in glioma.

Authors:  Andrew Morokoff; Wayne Ng; Andrew Gogos; Andrew H Kaye
Journal:  J Clin Neurosci       Date:  2015-05-06       Impact factor: 1.961

Review 6.  Impacts of the Human Gut Microbiome on Therapeutics.

Authors:  Yoshiki Vázquez-Baeza; Chris Callewaert; Justine Debelius; Embriette Hyde; Clarisse Marotz; James T Morton; Austin Swafford; Alison Vrbanac; Pieter C Dorrestein; Rob Knight
Journal:  Annu Rev Pharmacol Toxicol       Date:  2017-10-02       Impact factor: 13.820

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Authors:  Kristian A Gray; Bethan Yates; Ruth L Seal; Mathew W Wright; Elspeth A Bruford
Journal:  Nucleic Acids Res       Date:  2014-10-31       Impact factor: 19.160

8.  Genetic and environmental control of host-gut microbiota interactions.

Authors:  Elin Org; Brian W Parks; Jong Wha J Joo; Benjamin Emert; William Schwartzman; Eun Yong Kang; Margarete Mehrabian; Calvin Pan; Rob Knight; Robert Gunsalus; Thomas A Drake; Eleazar Eskin; Aldons J Lusis
Journal:  Genome Res       Date:  2015-08-10       Impact factor: 9.043

Review 9.  Genome engineering of stem cell organoids for disease modeling.

Authors:  Yingmin Sun; Qiurong Ding
Journal:  Protein Cell       Date:  2017-01-19       Impact factor: 14.870

Review 10.  Multi-omics approaches to disease.

Authors:  Yehudit Hasin; Marcus Seldin; Aldons Lusis
Journal:  Genome Biol       Date:  2017-05-05       Impact factor: 13.583

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