Multi-omics approach to precision medicine for immune-mediated diseases

Abstract Recent innovation in high-throughput sequencing technologies has drastically empowered the scientific research. Consequently, now, it is possible to capture comprehensive profiles of samples at multiple levels including genome, epigenome, and transcriptome at a time. Applying these kinds of...

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Main Authors: Mineto Ota, Keishi Fujio
Format: Article
Language:English
Published: BMC 2021-08-01
Series:Inflammation and Regeneration
Subjects:
Online Access:https://doi.org/10.1186/s41232-021-00173-8
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spelling doaj-b1b5e2c8c82541dabb19597fff661d252021-08-01T11:31:39ZengBMCInflammation and Regeneration1880-81902021-08-014111610.1186/s41232-021-00173-8Multi-omics approach to precision medicine for immune-mediated diseasesMineto Ota0Keishi Fujio1Department of Allergy and Rheumatology, Graduate School of Medicine, The University of TokyoDepartment of Allergy and Rheumatology, Graduate School of Medicine, The University of TokyoAbstract Recent innovation in high-throughput sequencing technologies has drastically empowered the scientific research. Consequently, now, it is possible to capture comprehensive profiles of samples at multiple levels including genome, epigenome, and transcriptome at a time. Applying these kinds of rich information to clinical settings is of great social significance. For some traits such as cardiovascular diseases, attempts to apply omics datasets in clinical practice for the prediction of the disease risk have already shown promising results, although still under way for immune-mediated diseases. Multiple studies have tried to predict treatment response in immune-mediated diseases using genomic, transcriptomic, or clinical information, showing various possible indicators. For better prediction of treatment response or disease outcome in immune-mediated diseases, combining multi-layer information together may increase the power. In addition, in order to efficiently pick up meaningful information from the massive data, high-quality annotation of genomic functions is also crucial. In this review, we discuss the achievement so far and the future direction of multi-omics approach to immune-mediated diseases.https://doi.org/10.1186/s41232-021-00173-8Multi-omics analysisImmune-mediated diseaseGenomeTranscriptomeExpression quantitative trait lociPolygenic risk score
collection DOAJ
language English
format Article
sources DOAJ
author Mineto Ota
Keishi Fujio
spellingShingle Mineto Ota
Keishi Fujio
Multi-omics approach to precision medicine for immune-mediated diseases
Inflammation and Regeneration
Multi-omics analysis
Immune-mediated disease
Genome
Transcriptome
Expression quantitative trait loci
Polygenic risk score
author_facet Mineto Ota
Keishi Fujio
author_sort Mineto Ota
title Multi-omics approach to precision medicine for immune-mediated diseases
title_short Multi-omics approach to precision medicine for immune-mediated diseases
title_full Multi-omics approach to precision medicine for immune-mediated diseases
title_fullStr Multi-omics approach to precision medicine for immune-mediated diseases
title_full_unstemmed Multi-omics approach to precision medicine for immune-mediated diseases
title_sort multi-omics approach to precision medicine for immune-mediated diseases
publisher BMC
series Inflammation and Regeneration
issn 1880-8190
publishDate 2021-08-01
description Abstract Recent innovation in high-throughput sequencing technologies has drastically empowered the scientific research. Consequently, now, it is possible to capture comprehensive profiles of samples at multiple levels including genome, epigenome, and transcriptome at a time. Applying these kinds of rich information to clinical settings is of great social significance. For some traits such as cardiovascular diseases, attempts to apply omics datasets in clinical practice for the prediction of the disease risk have already shown promising results, although still under way for immune-mediated diseases. Multiple studies have tried to predict treatment response in immune-mediated diseases using genomic, transcriptomic, or clinical information, showing various possible indicators. For better prediction of treatment response or disease outcome in immune-mediated diseases, combining multi-layer information together may increase the power. In addition, in order to efficiently pick up meaningful information from the massive data, high-quality annotation of genomic functions is also crucial. In this review, we discuss the achievement so far and the future direction of multi-omics approach to immune-mediated diseases.
topic Multi-omics analysis
Immune-mediated disease
Genome
Transcriptome
Expression quantitative trait loci
Polygenic risk score
url https://doi.org/10.1186/s41232-021-00173-8
work_keys_str_mv AT minetoota multiomicsapproachtoprecisionmedicineforimmunemediateddiseases
AT keishifujio multiomicsapproachtoprecisionmedicineforimmunemediateddiseases
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