Mendelian randomization and transcriptome analysis identified immune-related biomarkers for osteoarthritis
BackgroundThe immune microenvironment assumes a significant role in the pathogenesis of osteoarthritis (OA). However, the current biomarkers for the diagnosis and treatment of OA are not satisfactory. Our study aims to identify new OA immune-related biomarkers to direct the prevention and treatment...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
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Frontiers Media S.A.
2024-04-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2024.1334479/full |
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| author | Wei-Wei Pang Yi-Sheng Cai Chong Cao Fu-Rong Zhang Qin Zeng Dan-Yang Liu Ning Wang Xiao-Chao Qu Xiang-Ding Chen Hong-Wen Deng Li-Jun Tan |
| author_facet | Wei-Wei Pang Yi-Sheng Cai Chong Cao Fu-Rong Zhang Qin Zeng Dan-Yang Liu Ning Wang Xiao-Chao Qu Xiang-Ding Chen Hong-Wen Deng Li-Jun Tan |
| author_sort | Wei-Wei Pang |
| collection | DOAJ |
| description | BackgroundThe immune microenvironment assumes a significant role in the pathogenesis of osteoarthritis (OA). However, the current biomarkers for the diagnosis and treatment of OA are not satisfactory. Our study aims to identify new OA immune-related biomarkers to direct the prevention and treatment of OA using multi-omics data.MethodsThe discovery dataset integrated the GSE89408 and GSE143514 datasets to identify biomarkers that were significantly associated with the OA immune microenvironment through multiple machine learning methods and weighted gene co-expression network analysis (WGCNA). The identified signature genes were confirmed using two independent validation datasets. We also performed a two-sample mendelian randomization (MR) study to generate causal relationships between biomarkers and OA using OA genome-wide association study (GWAS) summary data (cases n = 24,955, controls n = 378,169). Inverse-variance weighting (IVW) method was used as the main method of causal estimates. Sensitivity analyses were performed to assess the robustness and reliability of the IVW results.ResultsThree signature genes (FCER1G, HLA-DMB, and HHLA-DPA1) associated with the OA immune microenvironment were identified as having good diagnostic performances, which can be used as biomarkers. MR results showed increased levels of FCER1G (OR = 1.118, 95% CI 1.031-1.212, P = 0.041), HLA-DMB (OR = 1.057, 95% CI 1.045 -1.069, P = 1.11E-21) and HLA-DPA1 (OR = 1.030, 95% CI 1.005-1.056, P = 0.017) were causally and positively associated with the risk of developing OA.ConclusionThe present study identified the 3 potential immune-related biomarkers for OA, providing new perspectives for the prevention and treatment of OA. The MR study provides genetic support for the causal effects of the 3 biomarkers with OA and may provide new insights into the molecular mechanisms leading to the development of OA. |
| first_indexed | 2024-04-24T10:59:14Z |
| format | Article |
| id | doaj.art-03b968bb8b5144b7b29fc1f48875d72e |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-04-24T10:59:14Z |
| publishDate | 2024-04-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Immunology |
| spelling | doaj.art-03b968bb8b5144b7b29fc1f48875d72e2024-04-12T04:13:53ZengFrontiers Media S.A.Frontiers in Immunology1664-32242024-04-011510.3389/fimmu.2024.13344791334479Mendelian randomization and transcriptome analysis identified immune-related biomarkers for osteoarthritisWei-Wei Pang0Yi-Sheng Cai1Chong Cao2Fu-Rong Zhang3Qin Zeng4Dan-Yang Liu5Ning Wang6Xiao-Chao Qu7Xiang-Ding Chen8Hong-Wen Deng9Li-Jun Tan10Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, ChinaLaboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, ChinaLaboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, ChinaLaboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, ChinaLaboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, ChinaLaboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, ChinaLaboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, ChinaLaboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, ChinaLaboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, ChinaTulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United StatesLaboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, ChinaBackgroundThe immune microenvironment assumes a significant role in the pathogenesis of osteoarthritis (OA). However, the current biomarkers for the diagnosis and treatment of OA are not satisfactory. Our study aims to identify new OA immune-related biomarkers to direct the prevention and treatment of OA using multi-omics data.MethodsThe discovery dataset integrated the GSE89408 and GSE143514 datasets to identify biomarkers that were significantly associated with the OA immune microenvironment through multiple machine learning methods and weighted gene co-expression network analysis (WGCNA). The identified signature genes were confirmed using two independent validation datasets. We also performed a two-sample mendelian randomization (MR) study to generate causal relationships between biomarkers and OA using OA genome-wide association study (GWAS) summary data (cases n = 24,955, controls n = 378,169). Inverse-variance weighting (IVW) method was used as the main method of causal estimates. Sensitivity analyses were performed to assess the robustness and reliability of the IVW results.ResultsThree signature genes (FCER1G, HLA-DMB, and HHLA-DPA1) associated with the OA immune microenvironment were identified as having good diagnostic performances, which can be used as biomarkers. MR results showed increased levels of FCER1G (OR = 1.118, 95% CI 1.031-1.212, P = 0.041), HLA-DMB (OR = 1.057, 95% CI 1.045 -1.069, P = 1.11E-21) and HLA-DPA1 (OR = 1.030, 95% CI 1.005-1.056, P = 0.017) were causally and positively associated with the risk of developing OA.ConclusionThe present study identified the 3 potential immune-related biomarkers for OA, providing new perspectives for the prevention and treatment of OA. The MR study provides genetic support for the causal effects of the 3 biomarkers with OA and may provide new insights into the molecular mechanisms leading to the development of OA.https://www.frontiersin.org/articles/10.3389/fimmu.2024.1334479/fullosteoarthritismendelian randomizationmulti-omics dataimmune microenvironmentbiomarkers |
| spellingShingle | Wei-Wei Pang Yi-Sheng Cai Chong Cao Fu-Rong Zhang Qin Zeng Dan-Yang Liu Ning Wang Xiao-Chao Qu Xiang-Ding Chen Hong-Wen Deng Li-Jun Tan Mendelian randomization and transcriptome analysis identified immune-related biomarkers for osteoarthritis Frontiers in Immunology osteoarthritis mendelian randomization multi-omics data immune microenvironment biomarkers |
| title | Mendelian randomization and transcriptome analysis identified immune-related biomarkers for osteoarthritis |
| title_full | Mendelian randomization and transcriptome analysis identified immune-related biomarkers for osteoarthritis |
| title_fullStr | Mendelian randomization and transcriptome analysis identified immune-related biomarkers for osteoarthritis |
| title_full_unstemmed | Mendelian randomization and transcriptome analysis identified immune-related biomarkers for osteoarthritis |
| title_short | Mendelian randomization and transcriptome analysis identified immune-related biomarkers for osteoarthritis |
| title_sort | mendelian randomization and transcriptome analysis identified immune related biomarkers for osteoarthritis |
| topic | osteoarthritis mendelian randomization multi-omics data immune microenvironment biomarkers |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2024.1334479/full |
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