Profiling of insulin-resistant kidney models and human biopsies reveals common and cell-type-specific mechanisms underpinning Diabetic Kidney Disease
Abstract Diabetic kidney disease (DKD) is the leading cause of end stage kidney failure worldwide, of which cellular insulin resistance is a major driver. Here, we study key human kidney cell types implicated in DKD (podocytes, glomerular endothelial, mesangial and proximal tubular cells) in insulin...
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Nature Portfolio
2024-11-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-54089-1 |
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| author | Abigail C. Lay Van Du T. Tran Viji Nair Virginie Betin Jennifer A. Hurcombe Alexandra F. Barrington Robert JP Pope Frédéric Burdet Florence Mehl Dmytro Kryvokhyzha Abrar Ahmad Matthew C. Sinton Philip Lewis Marieangela C. Wilson Rajasree Menon Edgar Otto Kate J. Heesom Mark Ibberson Helen C. Looker Robert G. Nelson Wenjun Ju Matthias Kretzler Simon C. Satchell Maria F. Gomez Richard J. M. Coward BEAt-DKD consortium |
| author_facet | Abigail C. Lay Van Du T. Tran Viji Nair Virginie Betin Jennifer A. Hurcombe Alexandra F. Barrington Robert JP Pope Frédéric Burdet Florence Mehl Dmytro Kryvokhyzha Abrar Ahmad Matthew C. Sinton Philip Lewis Marieangela C. Wilson Rajasree Menon Edgar Otto Kate J. Heesom Mark Ibberson Helen C. Looker Robert G. Nelson Wenjun Ju Matthias Kretzler Simon C. Satchell Maria F. Gomez Richard J. M. Coward BEAt-DKD consortium |
| author_sort | Abigail C. Lay |
| collection | DOAJ |
| description | Abstract Diabetic kidney disease (DKD) is the leading cause of end stage kidney failure worldwide, of which cellular insulin resistance is a major driver. Here, we study key human kidney cell types implicated in DKD (podocytes, glomerular endothelial, mesangial and proximal tubular cells) in insulin sensitive and resistant conditions, and perform simultaneous transcriptomics and proteomics for integrated analysis. Our data is further compared with bulk- and single-cell transcriptomic kidney biopsy data from early- and advanced-stage DKD patient cohorts. We identify several consistent changes (individual genes, proteins, and molecular pathways) occurring across all insulin-resistant kidney cell types, together with cell-line-specific changes occurring in response to insulin resistance, which are replicated in DKD biopsies. This study provides a rich data resource to direct future studies in elucidating underlying kidney signalling pathways and potential therapeutic targets in DKD. |
| format | Article |
| id | doaj-art-b623e2a205714bcbbfbb61ff109ce900 |
| institution | OA Journals |
| issn | 2041-1723 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-b623e2a205714bcbbfbb61ff109ce9002025-08-20T02:22:24ZengNature PortfolioNature Communications2041-17232024-11-0115111910.1038/s41467-024-54089-1Profiling of insulin-resistant kidney models and human biopsies reveals common and cell-type-specific mechanisms underpinning Diabetic Kidney DiseaseAbigail C. Lay0Van Du T. Tran1Viji Nair2Virginie Betin3Jennifer A. Hurcombe4Alexandra F. Barrington5Robert JP Pope6Frédéric Burdet7Florence Mehl8Dmytro Kryvokhyzha9Abrar Ahmad10Matthew C. Sinton11Philip Lewis12Marieangela C. Wilson13Rajasree Menon14Edgar Otto15Kate J. Heesom16Mark Ibberson17Helen C. Looker18Robert G. Nelson19Wenjun Ju20Matthias Kretzler21Simon C. Satchell22Maria F. Gomez23Richard J. M. Coward24BEAt-DKD consortiumBristol Renal, Bristol Medical School, University of BristolVital-IT group, SIB Swiss Institute of BioinformaticsDivision of Nephrology, Department of Internal Medicine, University of MichiganBristol Renal, Bristol Medical School, University of BristolBristol Renal, Bristol Medical School, University of BristolBristol Renal, Bristol Medical School, University of BristolBristol Renal, Bristol Medical School, University of BristolVital-IT group, SIB Swiss Institute of BioinformaticsVital-IT group, SIB Swiss Institute of BioinformaticsDepartment of Clinical Sciences, Lund University Diabetes Centre, Lund UniversityDepartment of Clinical Sciences, Lund University Diabetes Centre, Lund UniversityDivision of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of ManchesterProteomics Facility, University of BristolProteomics Facility, University of BristolDivision of Nephrology, Department of Internal Medicine, University of MichiganDivision of Nephrology, Department of Internal Medicine, University of MichiganProteomics Facility, University of BristolVital-IT group, SIB Swiss Institute of BioinformaticsChronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of HealthChronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of HealthDivision of Nephrology, Department of Internal Medicine, University of MichiganDivision of Nephrology, Department of Internal Medicine, University of MichiganBristol Renal, Bristol Medical School, University of BristolDepartment of Clinical Sciences, Lund University Diabetes Centre, Lund UniversityBristol Renal, Bristol Medical School, University of BristolAbstract Diabetic kidney disease (DKD) is the leading cause of end stage kidney failure worldwide, of which cellular insulin resistance is a major driver. Here, we study key human kidney cell types implicated in DKD (podocytes, glomerular endothelial, mesangial and proximal tubular cells) in insulin sensitive and resistant conditions, and perform simultaneous transcriptomics and proteomics for integrated analysis. Our data is further compared with bulk- and single-cell transcriptomic kidney biopsy data from early- and advanced-stage DKD patient cohorts. We identify several consistent changes (individual genes, proteins, and molecular pathways) occurring across all insulin-resistant kidney cell types, together with cell-line-specific changes occurring in response to insulin resistance, which are replicated in DKD biopsies. This study provides a rich data resource to direct future studies in elucidating underlying kidney signalling pathways and potential therapeutic targets in DKD.https://doi.org/10.1038/s41467-024-54089-1 |
| spellingShingle | Abigail C. Lay Van Du T. Tran Viji Nair Virginie Betin Jennifer A. Hurcombe Alexandra F. Barrington Robert JP Pope Frédéric Burdet Florence Mehl Dmytro Kryvokhyzha Abrar Ahmad Matthew C. Sinton Philip Lewis Marieangela C. Wilson Rajasree Menon Edgar Otto Kate J. Heesom Mark Ibberson Helen C. Looker Robert G. Nelson Wenjun Ju Matthias Kretzler Simon C. Satchell Maria F. Gomez Richard J. M. Coward BEAt-DKD consortium Profiling of insulin-resistant kidney models and human biopsies reveals common and cell-type-specific mechanisms underpinning Diabetic Kidney Disease Nature Communications |
| title | Profiling of insulin-resistant kidney models and human biopsies reveals common and cell-type-specific mechanisms underpinning Diabetic Kidney Disease |
| title_full | Profiling of insulin-resistant kidney models and human biopsies reveals common and cell-type-specific mechanisms underpinning Diabetic Kidney Disease |
| title_fullStr | Profiling of insulin-resistant kidney models and human biopsies reveals common and cell-type-specific mechanisms underpinning Diabetic Kidney Disease |
| title_full_unstemmed | Profiling of insulin-resistant kidney models and human biopsies reveals common and cell-type-specific mechanisms underpinning Diabetic Kidney Disease |
| title_short | Profiling of insulin-resistant kidney models and human biopsies reveals common and cell-type-specific mechanisms underpinning Diabetic Kidney Disease |
| title_sort | profiling of insulin resistant kidney models and human biopsies reveals common and cell type specific mechanisms underpinning diabetic kidney disease |
| url | https://doi.org/10.1038/s41467-024-54089-1 |
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