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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Online Access: | https://doi.org/10.1186/s41232-021-00173-8 |
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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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1721245916678062080 |