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An integrated multi-omic approach demonstrates distinct molecular signatures between human obesity with and without metabolic complications: a case–control study

OBJECTIVES: To examine the hypothesis that obesity complicated by the metabolic syndrome, compared to uncomplicated obesity, has distinct molecular signatures and metabolic pathways. METHODS: We analyzed a cohort of 39 participants with obesity that included 21 with metabolic syndrome, age-matched t...

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Autores principales: Mir, Fayaz Ahmad, Mall, Raghvendra, Ullah, Ehsan, Iskandarani, Ahmad, Cyprian, Farhan, Samra, Tareq A., Alkasem, Meis, Abdalhakam, Ibrahem, Farooq, Faisal, Taheri, Shahrad, Abou-Samra, Abdul-Badi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10053148/
https://www.ncbi.nlm.nih.gov/pubmed/36991398
http://dx.doi.org/10.1186/s12967-023-04074-x
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author Mir, Fayaz Ahmad
Mall, Raghvendra
Ullah, Ehsan
Iskandarani, Ahmad
Cyprian, Farhan
Samra, Tareq A.
Alkasem, Meis
Abdalhakam, Ibrahem
Farooq, Faisal
Taheri, Shahrad
Abou-Samra, Abdul-Badi
author_facet Mir, Fayaz Ahmad
Mall, Raghvendra
Ullah, Ehsan
Iskandarani, Ahmad
Cyprian, Farhan
Samra, Tareq A.
Alkasem, Meis
Abdalhakam, Ibrahem
Farooq, Faisal
Taheri, Shahrad
Abou-Samra, Abdul-Badi
author_sort Mir, Fayaz Ahmad
collection PubMed
description OBJECTIVES: To examine the hypothesis that obesity complicated by the metabolic syndrome, compared to uncomplicated obesity, has distinct molecular signatures and metabolic pathways. METHODS: We analyzed a cohort of 39 participants with obesity that included 21 with metabolic syndrome, age-matched to 18 without metabolic complications. We measured in whole blood samples 754 human microRNAs (miRNAs), 704 metabolites using unbiased mass spectrometry metabolomics, and 25,682 transcripts, which include both protein coding genes (PCGs) as well as non-coding transcripts. We then identified differentially expressed miRNAs, PCGs, and metabolites and integrated them using databases such as mirDIP (mapping between miRNA-PCG network), Human Metabolome Database (mapping between metabolite-PCG network) and tools like MetaboAnalyst (mapping between metabolite-metabolic pathway network) to determine dysregulated metabolic pathways in obesity with metabolic complications. RESULTS: We identified 8 significantly enriched metabolic pathways comprising 8 metabolites, 25 protein coding genes and 9 microRNAs which are each differentially expressed between the subjects with obesity and those with obesity and metabolic syndrome. By performing unsupervised hierarchical clustering on the enrichment matrix of the 8 metabolic pathways, we could approximately segregate the uncomplicated obesity strata from that of obesity with metabolic syndrome. CONCLUSIONS: The data suggest that at least 8 metabolic pathways, along with their various dysregulated elements, identified via our integrative bioinformatics pipeline, can potentially differentiate those with obesity from those with obesity and metabolic complications. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-04074-x.
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spelling pubmed-100531482023-03-30 An integrated multi-omic approach demonstrates distinct molecular signatures between human obesity with and without metabolic complications: a case–control study Mir, Fayaz Ahmad Mall, Raghvendra Ullah, Ehsan Iskandarani, Ahmad Cyprian, Farhan Samra, Tareq A. Alkasem, Meis Abdalhakam, Ibrahem Farooq, Faisal Taheri, Shahrad Abou-Samra, Abdul-Badi J Transl Med Research OBJECTIVES: To examine the hypothesis that obesity complicated by the metabolic syndrome, compared to uncomplicated obesity, has distinct molecular signatures and metabolic pathways. METHODS: We analyzed a cohort of 39 participants with obesity that included 21 with metabolic syndrome, age-matched to 18 without metabolic complications. We measured in whole blood samples 754 human microRNAs (miRNAs), 704 metabolites using unbiased mass spectrometry metabolomics, and 25,682 transcripts, which include both protein coding genes (PCGs) as well as non-coding transcripts. We then identified differentially expressed miRNAs, PCGs, and metabolites and integrated them using databases such as mirDIP (mapping between miRNA-PCG network), Human Metabolome Database (mapping between metabolite-PCG network) and tools like MetaboAnalyst (mapping between metabolite-metabolic pathway network) to determine dysregulated metabolic pathways in obesity with metabolic complications. RESULTS: We identified 8 significantly enriched metabolic pathways comprising 8 metabolites, 25 protein coding genes and 9 microRNAs which are each differentially expressed between the subjects with obesity and those with obesity and metabolic syndrome. By performing unsupervised hierarchical clustering on the enrichment matrix of the 8 metabolic pathways, we could approximately segregate the uncomplicated obesity strata from that of obesity with metabolic syndrome. CONCLUSIONS: The data suggest that at least 8 metabolic pathways, along with their various dysregulated elements, identified via our integrative bioinformatics pipeline, can potentially differentiate those with obesity from those with obesity and metabolic complications. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-04074-x. BioMed Central 2023-03-29 /pmc/articles/PMC10053148/ /pubmed/36991398 http://dx.doi.org/10.1186/s12967-023-04074-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Mir, Fayaz Ahmad
Mall, Raghvendra
Ullah, Ehsan
Iskandarani, Ahmad
Cyprian, Farhan
Samra, Tareq A.
Alkasem, Meis
Abdalhakam, Ibrahem
Farooq, Faisal
Taheri, Shahrad
Abou-Samra, Abdul-Badi
An integrated multi-omic approach demonstrates distinct molecular signatures between human obesity with and without metabolic complications: a case–control study
title An integrated multi-omic approach demonstrates distinct molecular signatures between human obesity with and without metabolic complications: a case–control study
title_full An integrated multi-omic approach demonstrates distinct molecular signatures between human obesity with and without metabolic complications: a case–control study
title_fullStr An integrated multi-omic approach demonstrates distinct molecular signatures between human obesity with and without metabolic complications: a case–control study
title_full_unstemmed An integrated multi-omic approach demonstrates distinct molecular signatures between human obesity with and without metabolic complications: a case–control study
title_short An integrated multi-omic approach demonstrates distinct molecular signatures between human obesity with and without metabolic complications: a case–control study
title_sort integrated multi-omic approach demonstrates distinct molecular signatures between human obesity with and without metabolic complications: a case–control study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10053148/
https://www.ncbi.nlm.nih.gov/pubmed/36991398
http://dx.doi.org/10.1186/s12967-023-04074-x
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