Urinary Sediment Transcriptomic and Longitudinal Data to Investigate Renal Function Decline in Type 1 Diabetes
Introduction: Using a discovery/validation approach we investigated associations between a panel of genes selected from a transcriptomic study and the estimated glomerular filtration rate (eGFR) decline across time in a cohort of type 1 diabetes (T1D) patients.Experimental: Urinary sediment transcri...
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| Format: | Article |
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Frontiers Media S.A.
2020-04-01
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| Series: | Frontiers in Endocrinology |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fendo.2020.00238/full |
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| author | Maria Beatriz Monteiro Tatiana S. Pelaes Daniele P. Santos-Bezerra Karina Thieme Antonio M. Lerario Sueli M. Oba-Shinjo Ubiratan F. Machado Marisa Passarelli Marisa Passarelli Suely K. N. Marie Maria Lúcia Corrêa-Giannella Maria Lúcia Corrêa-Giannella |
| author_facet | Maria Beatriz Monteiro Tatiana S. Pelaes Daniele P. Santos-Bezerra Karina Thieme Antonio M. Lerario Sueli M. Oba-Shinjo Ubiratan F. Machado Marisa Passarelli Marisa Passarelli Suely K. N. Marie Maria Lúcia Corrêa-Giannella Maria Lúcia Corrêa-Giannella |
| author_sort | Maria Beatriz Monteiro |
| collection | DOAJ |
| description | Introduction: Using a discovery/validation approach we investigated associations between a panel of genes selected from a transcriptomic study and the estimated glomerular filtration rate (eGFR) decline across time in a cohort of type 1 diabetes (T1D) patients.Experimental: Urinary sediment transcriptomic was performed to select highly modulated genes in T1D patients with rapid eGFR decline (decliners) vs. patients with stable eGFR (non-decliners). The selected genes were validated in samples from a T1D cohort (n = 54, mean diabetes duration of 21 years, 61% women) followed longitudinally for a median of 12 years in a Diabetes Outpatient Clinic.Results: In the discovery phase, the transcriptomic study revealed 158 genes significantly different between decliners and non-decliners. Ten genes increasingly up or down-regulated according to renal function worsening were selected for validation by qRT-PCR; the genes CYP4F22, and PMP22 were confirmed as differentially expressed comparing decliners vs. non-decliners after adjustment for potential confounders. CYP4F22, LYPD3, PMP22, MAP1LC3C, HS3ST2, GPNMB, CDH6, and PKD2L1 significantly modified the slope of eGFR in T1D patients across time.Conclusions: Eight genes identified as differentially expressed in the urinary sediment of T1D patients presenting different eGFR decline rates significantly increased the accuracy of predicted renal function across time in the studied cohort. These genes may be a promising way of unveiling novel mechanisms associated with diabetic kidney disease progression. |
| first_indexed | 2024-12-21T13:40:13Z |
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| institution | Directory Open Access Journal |
| issn | 1664-2392 |
| language | English |
| last_indexed | 2024-12-21T13:40:13Z |
| publishDate | 2020-04-01 |
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| series | Frontiers in Endocrinology |
| spelling | doaj.art-5a4e3390fcd54a8196ea42af99e1dff62022-12-21T19:02:03ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922020-04-011110.3389/fendo.2020.00238497946Urinary Sediment Transcriptomic and Longitudinal Data to Investigate Renal Function Decline in Type 1 DiabetesMaria Beatriz Monteiro0Tatiana S. Pelaes1Daniele P. Santos-Bezerra2Karina Thieme3Antonio M. Lerario4Sueli M. Oba-Shinjo5Ubiratan F. Machado6Marisa Passarelli7Marisa Passarelli8Suely K. N. Marie9Maria Lúcia Corrêa-Giannella10Maria Lúcia Corrêa-Giannella11Laboratório de Carboidratos e Radioimunoensaio (LIM-18), Faculdade de Medicina, Hospital das Clinicas HCFMUSP, Universidade de São Paulo, São Paulo, BrazilLaboratório de Carboidratos e Radioimunoensaio (LIM-18), Faculdade de Medicina, Hospital das Clinicas HCFMUSP, Universidade de São Paulo, São Paulo, BrazilLaboratório de Carboidratos e Radioimunoensaio (LIM-18), Faculdade de Medicina, Hospital das Clinicas HCFMUSP, Universidade de São Paulo, São Paulo, BrazilDepartment of Physiology and Biophysics, Institute of Biomedical Sciences, University of São Paulo, São Paulo, BrazilDivision of Metabolism, Endocrinology, and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United StatesLaboratory of Molecular and Cellular Biology (LIM-15, Faculdade de Medicina, Hospital das Clinicas HCFMUSP, Universidade de São Paulo, São Paulo, BrazilDepartment of Physiology and Biophysics, Institute of Biomedical Sciences, University of São Paulo, São Paulo, BrazilLaboratório de Lípides (LIM-10), Faculdade de Medicina, Hospital das Clinicas HCFMUSP, Universidade de São Paulo, São Paulo, BrazilPrograma de Pós-graduação em Medicina, Universidade Nove de Julho (UNINOVE), São Paulo, BrazilLaboratory of Molecular and Cellular Biology (LIM-15, Faculdade de Medicina, Hospital das Clinicas HCFMUSP, Universidade de São Paulo, São Paulo, BrazilLaboratório de Carboidratos e Radioimunoensaio (LIM-18), Faculdade de Medicina, Hospital das Clinicas HCFMUSP, Universidade de São Paulo, São Paulo, BrazilPrograma de Pós-graduação em Medicina, Universidade Nove de Julho (UNINOVE), São Paulo, BrazilIntroduction: Using a discovery/validation approach we investigated associations between a panel of genes selected from a transcriptomic study and the estimated glomerular filtration rate (eGFR) decline across time in a cohort of type 1 diabetes (T1D) patients.Experimental: Urinary sediment transcriptomic was performed to select highly modulated genes in T1D patients with rapid eGFR decline (decliners) vs. patients with stable eGFR (non-decliners). The selected genes were validated in samples from a T1D cohort (n = 54, mean diabetes duration of 21 years, 61% women) followed longitudinally for a median of 12 years in a Diabetes Outpatient Clinic.Results: In the discovery phase, the transcriptomic study revealed 158 genes significantly different between decliners and non-decliners. Ten genes increasingly up or down-regulated according to renal function worsening were selected for validation by qRT-PCR; the genes CYP4F22, and PMP22 were confirmed as differentially expressed comparing decliners vs. non-decliners after adjustment for potential confounders. CYP4F22, LYPD3, PMP22, MAP1LC3C, HS3ST2, GPNMB, CDH6, and PKD2L1 significantly modified the slope of eGFR in T1D patients across time.Conclusions: Eight genes identified as differentially expressed in the urinary sediment of T1D patients presenting different eGFR decline rates significantly increased the accuracy of predicted renal function across time in the studied cohort. These genes may be a promising way of unveiling novel mechanisms associated with diabetic kidney disease progression.https://www.frontiersin.org/article/10.3389/fendo.2020.00238/fulldiabetic kidney diseasetranscriptomicsrenal function declinelongitudinal datatype 1 diabetesurine |
| spellingShingle | Maria Beatriz Monteiro Tatiana S. Pelaes Daniele P. Santos-Bezerra Karina Thieme Antonio M. Lerario Sueli M. Oba-Shinjo Ubiratan F. Machado Marisa Passarelli Marisa Passarelli Suely K. N. Marie Maria Lúcia Corrêa-Giannella Maria Lúcia Corrêa-Giannella Urinary Sediment Transcriptomic and Longitudinal Data to Investigate Renal Function Decline in Type 1 Diabetes Frontiers in Endocrinology diabetic kidney disease transcriptomics renal function decline longitudinal data type 1 diabetes urine |
| title | Urinary Sediment Transcriptomic and Longitudinal Data to Investigate Renal Function Decline in Type 1 Diabetes |
| title_full | Urinary Sediment Transcriptomic and Longitudinal Data to Investigate Renal Function Decline in Type 1 Diabetes |
| title_fullStr | Urinary Sediment Transcriptomic and Longitudinal Data to Investigate Renal Function Decline in Type 1 Diabetes |
| title_full_unstemmed | Urinary Sediment Transcriptomic and Longitudinal Data to Investigate Renal Function Decline in Type 1 Diabetes |
| title_short | Urinary Sediment Transcriptomic and Longitudinal Data to Investigate Renal Function Decline in Type 1 Diabetes |
| title_sort | urinary sediment transcriptomic and longitudinal data to investigate renal function decline in type 1 diabetes |
| topic | diabetic kidney disease transcriptomics renal function decline longitudinal data type 1 diabetes urine |
| url | https://www.frontiersin.org/article/10.3389/fendo.2020.00238/full |
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