Urinary Sediment Transcriptomic and Longitudinal Data to Investigate Renal Function Decline in Type 1 Diabetes

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art_MONTEIRO_Urinary_Sediment_Transcriptomic_and_Longitudinal_Data_to_Investigate_2020.PDF (839.77 KB)
Citações na Scopus
5
Tipo de produção
article
Data de publicação
2020
DOI
Scopus
Web of Science
PubMed
Título da Revista
ISSN da Revista
Título do Volume
Editora
FRONTIERS MEDIA SA
Autores
THIEME, Karina
LERARIO, Antonio M.
MACHADO, Ubiratan F.
Citação
FRONTIERS IN ENDOCRINOLOGY, v.11, article ID 238, 8p, 2020
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
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.
Palavras-chave
diabetic kidney disease, transcriptomics, renal function decline, longitudinal data, type 1 diabetes, urine
URI
https://observatorio.fm.usp.br/handle/OPI/36898
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Coleções
Artigos e Materiais de Revistas Científicas - FM/MNE
Artigos e Materiais de Revistas Científicas - FM/MCM
Artigos e Materiais de Revistas Científicas - HC/ICHC
Artigos e Materiais de Revistas Científicas - LIM/10
Artigos e Materiais de Revistas Científicas - LIM/15
Artigos e Materiais de Revistas Científicas - LIM/18
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