Literature DB >> 26891944

Clinical implications of omics and systems medicine: focus on predictive and individualized treatment.

M Benson1.   

Abstract

Many patients with common diseases do not respond to treatment. This is a key challenge to modern health care, which causes both suffering and enormous costs. One important reason for the lack of treatment response is that common diseases are associated with altered interactions between thousands of genes, in combinations that differ between subgroups of patients who do or do not respond to a given treatment. Such subgroups, or even distinct disease entities, have been described recently in asthma, diabetes, autoimmune diseases and cancer. High-throughput techniques (omics) allow identification and characterization of such subgroups or entities. This may have important clinical implications, such as identification of diagnostic markers for individualized medicine, as well as new therapeutic targets for patients who do not respond to existing drugs. For example, whole-genome sequencing may be applied to more accurately guide treatment of neurodevelopmental diseases, or to identify drugs specifically targeting mutated genes in cancer. A study published in 2015 showed that 28% of hepatocellular carcinomas contained mutated genes that potentially could be targeted by drugs already approved by the US Food and Drug Administration. A translational study, which is described in detail, showed how combined omics, computational, functional and clinical studies could identify and validate a novel diagnostic and therapeutic candidate gene in allergy. Another important clinical implication is the identification of potential diagnostic markers and therapeutic targets for predictive and preventative medicine. By combining computational and experimental methods, early disease regulators may be identified and potentially used to predict and treat disease before it becomes symptomatic. Systems medicine is an emerging discipline, which may contribute to such developments through combining omics with computational, functional and clinical studies. The aims of this review are to provide a brief introduction to systems medicine and discuss how it may contribute to the clinical implementation of individualized treatment, using clinically relevant examples.
© 2015 The Association for the Publication of the Journal of Internal Medicine.

Entities:  

Keywords:  clinical translation; omics; systems medicine

Mesh:

Year:  2015        PMID: 26891944     DOI: 10.1111/joim.12412

Source DB:  PubMed          Journal:  J Intern Med        ISSN: 0954-6820            Impact factor:   8.989


  20 in total

Review 1.  [Personalized medicine in allergology].

Authors:  W Pfützner; J Pickert; C Möbs
Journal:  Hautarzt       Date:  2019-01       Impact factor: 0.751

Review 2.  Application of metabolomics in sarcoma: From biomarkers to therapeutic targets.

Authors:  Li Min; Edwin Choy; Chongqi Tu; Francis Hornicek; Zhenfeng Duan
Journal:  Crit Rev Oncol Hematol       Date:  2017-05-13       Impact factor: 6.312

Review 3.  A roadmap for multi-omics data integration using deep learning.

Authors:  Mingon Kang; Euiseong Ko; Tesfaye B Mersha
Journal:  Brief Bioinform       Date:  2022-01-17       Impact factor: 11.622

Review 4.  The current state of omics technologies in the clinical management of asthma and allergic diseases.

Authors:  Brittney M Donovan; Lisa Bastarache; Kedir N Turi; Mary M Zutter; Tina V Hartert
Journal:  Ann Allergy Asthma Immunol       Date:  2019-09-05       Impact factor: 6.347

Review 5.  Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations.

Authors:  Abdellah Tebani; Carlos Afonso; Stéphane Marret; Soumeya Bekri
Journal:  Int J Mol Sci       Date:  2016-09-14       Impact factor: 5.923

6.  The role of the clinician in the multi-omics era: are you ready?

Authors:  Clara D M van Karnebeek; Saskia B Wortmann; Maja Tarailo-Graovac; Mirjam Langeveld; Carlos R Ferreira; Jiddeke M van de Kamp; Carla E Hollak; Wyeth W Wasserman; Hans R Waterham; Ron A Wevers; Tobias B Haack; Ronald J A Wanders; Kym M Boycott
Journal:  J Inherit Metab Dis       Date:  2018-01-23       Impact factor: 4.982

Review 7.  Single-cell analyses to tailor treatments.

Authors:  Alex K Shalek; Mikael Benson
Journal:  Sci Transl Med       Date:  2017-09-20       Impact factor: 17.956

Review 8.  Community effort endorsing multiscale modelling, multiscale data science and multiscale computing for systems medicine.

Authors:  Massimiliano Zanin; Ivan Chorbev; Blaz Stres; Egils Stalidzans; Julio Vera; Paolo Tieri; Filippo Castiglione; Derek Groen; Huiru Zheng; Jan Baumbach; Johannes A Schmid; José Basilio; Peter Klimek; Nataša Debeljak; Damjana Rozman; Harald H H W Schmidt
Journal:  Brief Bioinform       Date:  2019-05-21       Impact factor: 11.622

Review 9.  Resolving Clinical Phenotypes into Endotypes in Allergy: Molecular and Omics Approaches.

Authors:  Tesfaye B Mersha; Yashira Afanador; Elisabet Johansson; Steven P Proper; Jonathan A Bernstein; Marc E Rothenberg; Gurjit K Khurana Hershey
Journal:  Clin Rev Allergy Immunol       Date:  2021-04       Impact factor: 8.667

10.  Systems Cytogenomics: Are We Ready Yet?

Authors:  Ivan Y Iourov; Svetlana G Vorsanova; Yuri B Yurov
Journal:  Curr Genomics       Date:  2021-02       Impact factor: 2.236

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