In-depth exploration of the shared genetic signature and molecular mechanisms between end-stage renal disease and osteoporosis
Background: Osteoporosis (OS) and fractures are common in patients with end-stage renal disease (ESRD) and maintenance dialysis patients. However, diagnosing osteoporosis in this population is challenging. The aim of this research is to explore the common genetic profile and potential molecular mech...
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| Format: | Article |
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Frontiers Media S.A.
2023-11-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2023.1159868/full |
| _version_ | 1827643671580770304 |
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| author | Weijuan Lou Wenhui Li Ming Yang Chong Yuan Rui Jing Shunjie Chen Cheng Fang |
| author_facet | Weijuan Lou Wenhui Li Ming Yang Chong Yuan Rui Jing Shunjie Chen Cheng Fang |
| author_sort | Weijuan Lou |
| collection | DOAJ |
| description | Background: Osteoporosis (OS) and fractures are common in patients with end-stage renal disease (ESRD) and maintenance dialysis patients. However, diagnosing osteoporosis in this population is challenging. The aim of this research is to explore the common genetic profile and potential molecular mechanisms of ESRD and OS.Methods and results: Download microarray data for ESRD and OS from the Gene Expression Omnibus (GEO) database. Weighted correlation network analysis (WGCNA) was used to identify co-expression modules associated with ESRD and OS. Random Forest (RF) and Lasso Regression were performed to identify candidate genes, and consensus clustering for hierarchical analysis. In addition, miRNAs shared in ESRD and OS were identified by differential analysis and their target genes were predicted by Tragetscan. Finally, we constructed a common miRNAs-mRNAs network with candidate genes and shared miRNAs. By WGCNA, two important modules of ESRD and one important module of OS were identified, and the functions of three major clusters were identified, including ribosome, RAS pathway, and MAPK pathway. Eight gene signatures obtained by using RF and Lasso machine learning methods with area under curve (AUC) values greater than 0.7 in ESRD and in OS confirmed their diagnostic performance. Consensus clustering successfully stratified ESRD patients, and C1 patients with more severe ESRD phenotype and OS phenotype were defined as “OS-prone group”.Conclusion: Our work identifies biological processes and underlying mechanisms shared by ESRD and OS, and identifies new candidate genes that can be used as biomarkers or potential therapeutic targets, revealing molecular alterations in susceptibility to OS in ESRD patients. |
| first_indexed | 2024-03-09T18:00:23Z |
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| id | doaj.art-c07ad8feeefa46ab923b5beab77b8438 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-03-09T18:00:23Z |
| publishDate | 2023-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-c07ad8feeefa46ab923b5beab77b84382023-11-24T09:57:11ZengFrontiers Media S.A.Frontiers in Genetics1664-80212023-11-011410.3389/fgene.2023.11598681159868In-depth exploration of the shared genetic signature and molecular mechanisms between end-stage renal disease and osteoporosisWeijuan Lou0Wenhui Li1Ming Yang2Chong Yuan3Rui Jing4Shunjie Chen5Cheng Fang6Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Gynecology and Obstetrics, Changhai Hospital, Second Military Medical University, Shanghai, ChinaDepartment of Nephrology, Shanghai Fourth People’s Hospital, Shanghai, ChinaDepartment of Pathology, School of Basic Medicine, Fudan University, Shanghai, ChinaDepartment of Nephrology, Xijing Hospital, The Fourth Military Medical University, Xi’an, ChinaDepartment of Nephrology, Shanghai Fourth People’s Hospital, Shanghai, ChinaDepartment of Hepatic Surgery IV, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, ChinaBackground: Osteoporosis (OS) and fractures are common in patients with end-stage renal disease (ESRD) and maintenance dialysis patients. However, diagnosing osteoporosis in this population is challenging. The aim of this research is to explore the common genetic profile and potential molecular mechanisms of ESRD and OS.Methods and results: Download microarray data for ESRD and OS from the Gene Expression Omnibus (GEO) database. Weighted correlation network analysis (WGCNA) was used to identify co-expression modules associated with ESRD and OS. Random Forest (RF) and Lasso Regression were performed to identify candidate genes, and consensus clustering for hierarchical analysis. In addition, miRNAs shared in ESRD and OS were identified by differential analysis and their target genes were predicted by Tragetscan. Finally, we constructed a common miRNAs-mRNAs network with candidate genes and shared miRNAs. By WGCNA, two important modules of ESRD and one important module of OS were identified, and the functions of three major clusters were identified, including ribosome, RAS pathway, and MAPK pathway. Eight gene signatures obtained by using RF and Lasso machine learning methods with area under curve (AUC) values greater than 0.7 in ESRD and in OS confirmed their diagnostic performance. Consensus clustering successfully stratified ESRD patients, and C1 patients with more severe ESRD phenotype and OS phenotype were defined as “OS-prone group”.Conclusion: Our work identifies biological processes and underlying mechanisms shared by ESRD and OS, and identifies new candidate genes that can be used as biomarkers or potential therapeutic targets, revealing molecular alterations in susceptibility to OS in ESRD patients.https://www.frontiersin.org/articles/10.3389/fgene.2023.1159868/fulldiagnostic geneend stage renal diseaseosteoporosismachine learningweighted gene co-expression network analysis |
| spellingShingle | Weijuan Lou Wenhui Li Ming Yang Chong Yuan Rui Jing Shunjie Chen Cheng Fang In-depth exploration of the shared genetic signature and molecular mechanisms between end-stage renal disease and osteoporosis Frontiers in Genetics diagnostic gene end stage renal disease osteoporosis machine learning weighted gene co-expression network analysis |
| title | In-depth exploration of the shared genetic signature and molecular mechanisms between end-stage renal disease and osteoporosis |
| title_full | In-depth exploration of the shared genetic signature and molecular mechanisms between end-stage renal disease and osteoporosis |
| title_fullStr | In-depth exploration of the shared genetic signature and molecular mechanisms between end-stage renal disease and osteoporosis |
| title_full_unstemmed | In-depth exploration of the shared genetic signature and molecular mechanisms between end-stage renal disease and osteoporosis |
| title_short | In-depth exploration of the shared genetic signature and molecular mechanisms between end-stage renal disease and osteoporosis |
| title_sort | in depth exploration of the shared genetic signature and molecular mechanisms between end stage renal disease and osteoporosis |
| topic | diagnostic gene end stage renal disease osteoporosis machine learning weighted gene co-expression network analysis |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2023.1159868/full |
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