Applying next-generation sequencing and multi-omics in chronic obstructive pulmonary disease

Microbiomics have significantly advanced over the last decade, driven by the widespread availability of next-generation sequencing (NGS) and multi-omic technologies. Integration of NGS and multi-omic datasets allow for a holistic assessment of endophenotypes across a range of chronic respiratory dis...

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Main Authors: Tiew, Pei Yee, Meldrum, Oliver W., Chotirmall, Sanjay Haresh
Other Authors: Lee Kong Chian School of Medicine (LKCMedicine)
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/165603
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1656032023-04-09T15:37:46Z Applying next-generation sequencing and multi-omics in chronic obstructive pulmonary disease Tiew, Pei Yee Meldrum, Oliver W. Chotirmall, Sanjay Haresh Lee Kong Chian School of Medicine (LKCMedicine) Tan Tock Seng Hospital Science::Medicine Microbiome Next Generation Sequencing Microbiomics have significantly advanced over the last decade, driven by the widespread availability of next-generation sequencing (NGS) and multi-omic technologies. Integration of NGS and multi-omic datasets allow for a holistic assessment of endophenotypes across a range of chronic respiratory disease states, including chronic obstructive pulmonary disease (COPD). Valuable insight has been attained into the nature, function, and significance of microbial communities in disease onset, progression, prognosis, and response to treatment in COPD. Moving beyond single-biome assessment, there now exists a growing literature on functional assessment and host-microbe interaction and, in particular, their contribution to disease progression, severity, and outcome. Identifying specific microbes and/or metabolic signatures associated with COPD can open novel avenues for therapeutic intervention and prognosis-related biomarkers. Despite the promise and potential of these approaches, the large amount of data generated by such technologies can be challenging to analyze and interpret, and currently, there remains a lack of standardized methods to address this. This review outlines the current use and proposes future avenues for the application of NGS and multi-omic technologies in the endophenotyping, prognostication, and treatment of COPD. Ministry of Health (MOH) National Medical Research Council (NMRC) Published version This research is supported by the Singapore Ministry of Health’s National Medical Research Council under its Clinician Scientist Award (MOH-000710) (S.H.C) and the Open Fund-Individual Research Grant (MOH-000955) (S.H.C). 2023-04-03T07:50:21Z 2023-04-03T07:50:21Z 2023 Journal Article Tiew, P. Y., Meldrum, O. W. & Chotirmall, S. H. (2023). Applying next-generation sequencing and multi-omics in chronic obstructive pulmonary disease. International Journal of Molecular Sciences, 24(3), 2955-. https://dx.doi.org/10.3390/ijms24032955 1661-6596 https://hdl.handle.net/10356/165603 10.3390/ijms24032955 36769278 2-s2.0-85147893931 3 24 2955 en MOH-000710 MOH-000955 International Journal of Molecular Sciences © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Science::Medicine
Microbiome
Next Generation Sequencing
spellingShingle Science::Medicine
Microbiome
Next Generation Sequencing
Tiew, Pei Yee
Meldrum, Oliver W.
Chotirmall, Sanjay Haresh
Applying next-generation sequencing and multi-omics in chronic obstructive pulmonary disease
description Microbiomics have significantly advanced over the last decade, driven by the widespread availability of next-generation sequencing (NGS) and multi-omic technologies. Integration of NGS and multi-omic datasets allow for a holistic assessment of endophenotypes across a range of chronic respiratory disease states, including chronic obstructive pulmonary disease (COPD). Valuable insight has been attained into the nature, function, and significance of microbial communities in disease onset, progression, prognosis, and response to treatment in COPD. Moving beyond single-biome assessment, there now exists a growing literature on functional assessment and host-microbe interaction and, in particular, their contribution to disease progression, severity, and outcome. Identifying specific microbes and/or metabolic signatures associated with COPD can open novel avenues for therapeutic intervention and prognosis-related biomarkers. Despite the promise and potential of these approaches, the large amount of data generated by such technologies can be challenging to analyze and interpret, and currently, there remains a lack of standardized methods to address this. This review outlines the current use and proposes future avenues for the application of NGS and multi-omic technologies in the endophenotyping, prognostication, and treatment of COPD.
author2 Lee Kong Chian School of Medicine (LKCMedicine)
author_facet Lee Kong Chian School of Medicine (LKCMedicine)
Tiew, Pei Yee
Meldrum, Oliver W.
Chotirmall, Sanjay Haresh
format Article
author Tiew, Pei Yee
Meldrum, Oliver W.
Chotirmall, Sanjay Haresh
author_sort Tiew, Pei Yee
title Applying next-generation sequencing and multi-omics in chronic obstructive pulmonary disease
title_short Applying next-generation sequencing and multi-omics in chronic obstructive pulmonary disease
title_full Applying next-generation sequencing and multi-omics in chronic obstructive pulmonary disease
title_fullStr Applying next-generation sequencing and multi-omics in chronic obstructive pulmonary disease
title_full_unstemmed Applying next-generation sequencing and multi-omics in chronic obstructive pulmonary disease
title_sort applying next-generation sequencing and multi-omics in chronic obstructive pulmonary disease
publishDate 2023
url https://hdl.handle.net/10356/165603
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