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Circulating microRNAs differentiate fast-progressing from slow-progressing and non-progressing knee osteoarthritis in the Osteoarthritis Initiative cohort

INTRODUCTION: The objective of this study is to identify circulating microRNAs that distinguish fast-progressing radiographic knee osteoarthritis (OA) in the Osteoarthritis Initiative cohort by applying microRNA-sequencing. METHODS: Participants with Kellgren–Lawrence (KL) grade 0/1 at baseline were...

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Autores principales: Ali, Shabana Amanda, Espin-Garcia, Osvaldo, Wong, Andy K., Potla, Pratibha, Pastrello, Chiara, McIntyre, Madison, Lively, Starlee, Jurisica, Igor, Gandhi, Rajiv, Kapoor, Mohit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8935408/
https://www.ncbi.nlm.nih.gov/pubmed/35321117
http://dx.doi.org/10.1177/1759720X221082917
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author Ali, Shabana Amanda
Espin-Garcia, Osvaldo
Wong, Andy K.
Potla, Pratibha
Pastrello, Chiara
McIntyre, Madison
Lively, Starlee
Jurisica, Igor
Gandhi, Rajiv
Kapoor, Mohit
author_facet Ali, Shabana Amanda
Espin-Garcia, Osvaldo
Wong, Andy K.
Potla, Pratibha
Pastrello, Chiara
McIntyre, Madison
Lively, Starlee
Jurisica, Igor
Gandhi, Rajiv
Kapoor, Mohit
author_sort Ali, Shabana Amanda
collection PubMed
description INTRODUCTION: The objective of this study is to identify circulating microRNAs that distinguish fast-progressing radiographic knee osteoarthritis (OA) in the Osteoarthritis Initiative cohort by applying microRNA-sequencing. METHODS: Participants with Kellgren–Lawrence (KL) grade 0/1 at baseline were included (N = 106). Fast-progressors were defined by an increase to KL 3/4 by 4-year follow-up (N = 20), whereas slow-progressors showed an increase to KL 2/3/4 only at 8-year follow-up (N = 35). Non-progressors remained at KL 0/1 by 8-year follow-up (N = 51). MicroRNA-sequencing was performed on plasma collected at baseline and 4-year follow-up from the same participants. Negative binomial models were fitted to identify differentially expressed (DE) microRNAs. Penalized logistic regression (PLR) analyses were performed to select combinations of DE microRNAs that distinguished fast-progressors. Area under the receiver operating characteristic curves (AUC) were constructed to evaluate predictive ability. RESULTS: DE analyses revealed 48 microRNAs at baseline and 2 microRNAs at 4-year follow-up [false discovery rate (FDR) < 0.05] comparing fast-progressors with both slow-progressors and non-progressors. Among these were hsa-miR-320b, hsa-miR-320c, hsa-miR-320d, and hsa-miR-320e, which were predicted to target gene families, including members of the 14-3-3 gene family, involved in signal transduction. PLR models included miR-320 members as top predictors of fast-progressors and yielded AUC ranging from 82.6 to 91.9, representing good accuracy. CONCLUSION: The miR-320 family is associated with fast-progressing radiographic knee OA and merits further investigation as potential biomarkers and mechanistic drivers of knee OA.
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spelling pubmed-89354082022-03-22 Circulating microRNAs differentiate fast-progressing from slow-progressing and non-progressing knee osteoarthritis in the Osteoarthritis Initiative cohort Ali, Shabana Amanda Espin-Garcia, Osvaldo Wong, Andy K. Potla, Pratibha Pastrello, Chiara McIntyre, Madison Lively, Starlee Jurisica, Igor Gandhi, Rajiv Kapoor, Mohit Ther Adv Musculoskelet Dis Addressing the Challenges Associated with the Development, Testing and Approval of Novel Therapeutics for Osteoarthritis INTRODUCTION: The objective of this study is to identify circulating microRNAs that distinguish fast-progressing radiographic knee osteoarthritis (OA) in the Osteoarthritis Initiative cohort by applying microRNA-sequencing. METHODS: Participants with Kellgren–Lawrence (KL) grade 0/1 at baseline were included (N = 106). Fast-progressors were defined by an increase to KL 3/4 by 4-year follow-up (N = 20), whereas slow-progressors showed an increase to KL 2/3/4 only at 8-year follow-up (N = 35). Non-progressors remained at KL 0/1 by 8-year follow-up (N = 51). MicroRNA-sequencing was performed on plasma collected at baseline and 4-year follow-up from the same participants. Negative binomial models were fitted to identify differentially expressed (DE) microRNAs. Penalized logistic regression (PLR) analyses were performed to select combinations of DE microRNAs that distinguished fast-progressors. Area under the receiver operating characteristic curves (AUC) were constructed to evaluate predictive ability. RESULTS: DE analyses revealed 48 microRNAs at baseline and 2 microRNAs at 4-year follow-up [false discovery rate (FDR) < 0.05] comparing fast-progressors with both slow-progressors and non-progressors. Among these were hsa-miR-320b, hsa-miR-320c, hsa-miR-320d, and hsa-miR-320e, which were predicted to target gene families, including members of the 14-3-3 gene family, involved in signal transduction. PLR models included miR-320 members as top predictors of fast-progressors and yielded AUC ranging from 82.6 to 91.9, representing good accuracy. CONCLUSION: The miR-320 family is associated with fast-progressing radiographic knee OA and merits further investigation as potential biomarkers and mechanistic drivers of knee OA. SAGE Publications 2022-03-18 /pmc/articles/PMC8935408/ /pubmed/35321117 http://dx.doi.org/10.1177/1759720X221082917 Text en © The Author(s), 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Addressing the Challenges Associated with the Development, Testing and Approval of Novel Therapeutics for Osteoarthritis
Ali, Shabana Amanda
Espin-Garcia, Osvaldo
Wong, Andy K.
Potla, Pratibha
Pastrello, Chiara
McIntyre, Madison
Lively, Starlee
Jurisica, Igor
Gandhi, Rajiv
Kapoor, Mohit
Circulating microRNAs differentiate fast-progressing from slow-progressing and non-progressing knee osteoarthritis in the Osteoarthritis Initiative cohort
title Circulating microRNAs differentiate fast-progressing from slow-progressing and non-progressing knee osteoarthritis in the Osteoarthritis Initiative cohort
title_full Circulating microRNAs differentiate fast-progressing from slow-progressing and non-progressing knee osteoarthritis in the Osteoarthritis Initiative cohort
title_fullStr Circulating microRNAs differentiate fast-progressing from slow-progressing and non-progressing knee osteoarthritis in the Osteoarthritis Initiative cohort
title_full_unstemmed Circulating microRNAs differentiate fast-progressing from slow-progressing and non-progressing knee osteoarthritis in the Osteoarthritis Initiative cohort
title_short Circulating microRNAs differentiate fast-progressing from slow-progressing and non-progressing knee osteoarthritis in the Osteoarthritis Initiative cohort
title_sort circulating micrornas differentiate fast-progressing from slow-progressing and non-progressing knee osteoarthritis in the osteoarthritis initiative cohort
topic Addressing the Challenges Associated with the Development, Testing and Approval of Novel Therapeutics for Osteoarthritis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8935408/
https://www.ncbi.nlm.nih.gov/pubmed/35321117
http://dx.doi.org/10.1177/1759720X221082917
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