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Causality of genetically determined metabolites and metabolic pathways on osteoarthritis: a two-sample mendelian randomization study

BACKGROUND: Osteoarthritis (OA) is one of the most prevalent musculoskeletal diseases and is the leading cause of pain and disability in the aged population. However, the underlying biological mechanism has not been fully understood. This study aims to reveal the causal effect of circulation metabol...

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Autores principales: Gu, Yifei, Jin, Qianmei, Hu, Jinquan, Wang, Xinwei, Yu, Wenchao, Wang, Zhanchao, Wang, Chen, Liu, Yang, Chen, Yu, Yuan, Wen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10230782/
https://www.ncbi.nlm.nih.gov/pubmed/37259122
http://dx.doi.org/10.1186/s12967-023-04165-9
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author Gu, Yifei
Jin, Qianmei
Hu, Jinquan
Wang, Xinwei
Yu, Wenchao
Wang, Zhanchao
Wang, Chen
Liu, Yang
Chen, Yu
Yuan, Wen
author_facet Gu, Yifei
Jin, Qianmei
Hu, Jinquan
Wang, Xinwei
Yu, Wenchao
Wang, Zhanchao
Wang, Chen
Liu, Yang
Chen, Yu
Yuan, Wen
author_sort Gu, Yifei
collection PubMed
description BACKGROUND: Osteoarthritis (OA) is one of the most prevalent musculoskeletal diseases and is the leading cause of pain and disability in the aged population. However, the underlying biological mechanism has not been fully understood. This study aims to reveal the causal effect of circulation metabolites on OA susceptibility. METHODS: A two-sample Mendelian Randomization (MR) analysis was performed to estimate the causality of GDMs on OA. A genome-wide association study (GWAS) of 486 metabolites was used as the exposure, whereas 8 different OA phenotypes, including any-site OA (All OA), knee and/or hip OA (knee/hip OA), knee OA, hip OA, spine OA, finger and/or thumb OA (hand OA), finger OA, thumb OA, were set the outcomes. Inverse-variance weighted (IVW) was used for calculating causal estimates. Methods including weight mode, weight median, MR-egger, and MR-PRESSO were used for the sensitive analysis. Furthermore, metabolic pathway analysis was performed via the web-based Metaconflict 4.0. All statistical analyses were performed in R software. RESULTS: In this MR analysis, a total of 235 causative associations between metabolites and different OA phenotypes were observed. After false discovery rate (FDR) correction and sensitive analysis, 9 robust causative associations between 7 metabolites (e.g., arginine, kynurenine, and isovalerylcarnitine) and 5 OA phenotypes were finally identified. Additionally, eleven significant metabolic pathways in 4 OA phenotypes were identified by metabolic pathway analysis. CONCLUSION: The finding of our study suggested that identified metabolites and metabolic pathways can be considered useful circulating metabolic biomarkers for OA screening and prevention in clinical practice, and can also serve as candidate molecules for future mechanism exploration and drug target selection. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-04165-9.
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spelling pubmed-102307822023-06-01 Causality of genetically determined metabolites and metabolic pathways on osteoarthritis: a two-sample mendelian randomization study Gu, Yifei Jin, Qianmei Hu, Jinquan Wang, Xinwei Yu, Wenchao Wang, Zhanchao Wang, Chen Liu, Yang Chen, Yu Yuan, Wen J Transl Med Research BACKGROUND: Osteoarthritis (OA) is one of the most prevalent musculoskeletal diseases and is the leading cause of pain and disability in the aged population. However, the underlying biological mechanism has not been fully understood. This study aims to reveal the causal effect of circulation metabolites on OA susceptibility. METHODS: A two-sample Mendelian Randomization (MR) analysis was performed to estimate the causality of GDMs on OA. A genome-wide association study (GWAS) of 486 metabolites was used as the exposure, whereas 8 different OA phenotypes, including any-site OA (All OA), knee and/or hip OA (knee/hip OA), knee OA, hip OA, spine OA, finger and/or thumb OA (hand OA), finger OA, thumb OA, were set the outcomes. Inverse-variance weighted (IVW) was used for calculating causal estimates. Methods including weight mode, weight median, MR-egger, and MR-PRESSO were used for the sensitive analysis. Furthermore, metabolic pathway analysis was performed via the web-based Metaconflict 4.0. All statistical analyses were performed in R software. RESULTS: In this MR analysis, a total of 235 causative associations between metabolites and different OA phenotypes were observed. After false discovery rate (FDR) correction and sensitive analysis, 9 robust causative associations between 7 metabolites (e.g., arginine, kynurenine, and isovalerylcarnitine) and 5 OA phenotypes were finally identified. Additionally, eleven significant metabolic pathways in 4 OA phenotypes were identified by metabolic pathway analysis. CONCLUSION: The finding of our study suggested that identified metabolites and metabolic pathways can be considered useful circulating metabolic biomarkers for OA screening and prevention in clinical practice, and can also serve as candidate molecules for future mechanism exploration and drug target selection. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-04165-9. BioMed Central 2023-05-31 /pmc/articles/PMC10230782/ /pubmed/37259122 http://dx.doi.org/10.1186/s12967-023-04165-9 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
Gu, Yifei
Jin, Qianmei
Hu, Jinquan
Wang, Xinwei
Yu, Wenchao
Wang, Zhanchao
Wang, Chen
Liu, Yang
Chen, Yu
Yuan, Wen
Causality of genetically determined metabolites and metabolic pathways on osteoarthritis: a two-sample mendelian randomization study
title Causality of genetically determined metabolites and metabolic pathways on osteoarthritis: a two-sample mendelian randomization study
title_full Causality of genetically determined metabolites and metabolic pathways on osteoarthritis: a two-sample mendelian randomization study
title_fullStr Causality of genetically determined metabolites and metabolic pathways on osteoarthritis: a two-sample mendelian randomization study
title_full_unstemmed Causality of genetically determined metabolites and metabolic pathways on osteoarthritis: a two-sample mendelian randomization study
title_short Causality of genetically determined metabolites and metabolic pathways on osteoarthritis: a two-sample mendelian randomization study
title_sort causality of genetically determined metabolites and metabolic pathways on osteoarthritis: a two-sample mendelian randomization study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10230782/
https://www.ncbi.nlm.nih.gov/pubmed/37259122
http://dx.doi.org/10.1186/s12967-023-04165-9
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