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MicroRNA and metabolomics signatures for adrenomyeloneuropathy disease severity

Adrenomyeloneuropathy (AMN), the slow progressive phenotype of adrenoleukodystrophy (ALD), has no clinical plasma biomarker for disease progression. This feasibility study aimed to determine whether metabolomics and micro‐RNA in blood plasma provide a potential source of biomarkers for AMN disease s...

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Autores principales: Turk, Bela Rui, Poisson, Laila Marie, Nemeth, Christina Linnea, Goodman, Jordan, Moser, Ann B., Jones, Richard Owen, Fatemi, Ali, Singh, Jaspreet
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9626672/
https://www.ncbi.nlm.nih.gov/pubmed/36341174
http://dx.doi.org/10.1002/jmd2.12323
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author Turk, Bela Rui
Poisson, Laila Marie
Nemeth, Christina Linnea
Goodman, Jordan
Moser, Ann B.
Jones, Richard Owen
Fatemi, Ali
Singh, Jaspreet
author_facet Turk, Bela Rui
Poisson, Laila Marie
Nemeth, Christina Linnea
Goodman, Jordan
Moser, Ann B.
Jones, Richard Owen
Fatemi, Ali
Singh, Jaspreet
author_sort Turk, Bela Rui
collection PubMed
description Adrenomyeloneuropathy (AMN), the slow progressive phenotype of adrenoleukodystrophy (ALD), has no clinical plasma biomarker for disease progression. This feasibility study aimed to determine whether metabolomics and micro‐RNA in blood plasma provide a potential source of biomarkers for AMN disease severity. Metabolomics and RNA‐seq were performed on AMN and healthy human blood plasma. Biomarker discovery and pathway analyses were performed using clustering, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and regression against patient's clinical Expanded Disability Status Score (EDSS). Fourteen AMN and six healthy control samples were analyzed. AMN showed strong disease‐severity‐specific metabolic and miRNA clustering signatures. Strong, significant clinical correlations were shown for 7‐alpha‐hydroxy‐3‐oxo‐4‐cholestenoate (7‐HOCA) (r (2) = 0.83, p < 0.00001), dehydroepiandrosterone sulfate (DHEA‐S; r (2) = 0.82, p < 0.00001), hypoxanthine (r (2) = 0.82, p < 0.00001), as well as miRNA‐432‐5p (r (2) = 0.68, p < 0.00001). KEGG pathway comparison of mild versus severe disease identified affected downstream systems: GAREM, IGF‐1, CALCRL, SMAD2&3, glutathione peroxidase, LDH, and NOS. This feasibility study demonstrates that miRNA and metabolomics are a source of potential plasma biomarkers for disease severity in AMN, providing both a disease signature and individual markers with strong clinical correlations. Network analyses of affected systems implicate differentially altered vascular, inflammatory, and oxidative stress pathways, suggesting disease‐severity‐specific mechanisms as a function of disease severity.
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spelling pubmed-96266722022-11-03 MicroRNA and metabolomics signatures for adrenomyeloneuropathy disease severity Turk, Bela Rui Poisson, Laila Marie Nemeth, Christina Linnea Goodman, Jordan Moser, Ann B. Jones, Richard Owen Fatemi, Ali Singh, Jaspreet JIMD Rep Research Reports Adrenomyeloneuropathy (AMN), the slow progressive phenotype of adrenoleukodystrophy (ALD), has no clinical plasma biomarker for disease progression. This feasibility study aimed to determine whether metabolomics and micro‐RNA in blood plasma provide a potential source of biomarkers for AMN disease severity. Metabolomics and RNA‐seq were performed on AMN and healthy human blood plasma. Biomarker discovery and pathway analyses were performed using clustering, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and regression against patient's clinical Expanded Disability Status Score (EDSS). Fourteen AMN and six healthy control samples were analyzed. AMN showed strong disease‐severity‐specific metabolic and miRNA clustering signatures. Strong, significant clinical correlations were shown for 7‐alpha‐hydroxy‐3‐oxo‐4‐cholestenoate (7‐HOCA) (r (2) = 0.83, p < 0.00001), dehydroepiandrosterone sulfate (DHEA‐S; r (2) = 0.82, p < 0.00001), hypoxanthine (r (2) = 0.82, p < 0.00001), as well as miRNA‐432‐5p (r (2) = 0.68, p < 0.00001). KEGG pathway comparison of mild versus severe disease identified affected downstream systems: GAREM, IGF‐1, CALCRL, SMAD2&3, glutathione peroxidase, LDH, and NOS. This feasibility study demonstrates that miRNA and metabolomics are a source of potential plasma biomarkers for disease severity in AMN, providing both a disease signature and individual markers with strong clinical correlations. Network analyses of affected systems implicate differentially altered vascular, inflammatory, and oxidative stress pathways, suggesting disease‐severity‐specific mechanisms as a function of disease severity. John Wiley & Sons, Inc. 2022-08-22 /pmc/articles/PMC9626672/ /pubmed/36341174 http://dx.doi.org/10.1002/jmd2.12323 Text en © 2022 The Authors. JIMD Reports published by John Wiley & Sons Ltd on behalf of SSIEM. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Reports
Turk, Bela Rui
Poisson, Laila Marie
Nemeth, Christina Linnea
Goodman, Jordan
Moser, Ann B.
Jones, Richard Owen
Fatemi, Ali
Singh, Jaspreet
MicroRNA and metabolomics signatures for adrenomyeloneuropathy disease severity
title MicroRNA and metabolomics signatures for adrenomyeloneuropathy disease severity
title_full MicroRNA and metabolomics signatures for adrenomyeloneuropathy disease severity
title_fullStr MicroRNA and metabolomics signatures for adrenomyeloneuropathy disease severity
title_full_unstemmed MicroRNA and metabolomics signatures for adrenomyeloneuropathy disease severity
title_short MicroRNA and metabolomics signatures for adrenomyeloneuropathy disease severity
title_sort microrna and metabolomics signatures for adrenomyeloneuropathy disease severity
topic Research Reports
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9626672/
https://www.ncbi.nlm.nih.gov/pubmed/36341174
http://dx.doi.org/10.1002/jmd2.12323
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