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Abstract 16: Urinary metabolic signatures for differential diagnosis of diabetic and non-diabetic kidney disease
BACKGROUND: Renal involvement in T2DM can be due to diabetes per se (Diabetic Kidney Disease) or causes other than diabetes (Non-diabetic kidney disease). Currently available clinical, biochemical and radiological markers fail to differentiate DKD from NDKD and renal biopsy remains gold standard for...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer - Medknow
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9067843/ http://dx.doi.org/10.4103/2230-8210.342130 |
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author | Basu, Madhurima Islam1, S K Ramiz Neogi, Subhashis Pulai2, Smartya Banerjee, Mainak Sengupta3, Sanghamitra Mukhopadhyay, Pradip Bhattacharyya, Nitai Pada Roychoudhury2, Arpita Manna1, Soumen Kanti Ghosh, Sujoy |
author_facet | Basu, Madhurima Islam1, S K Ramiz Neogi, Subhashis Pulai2, Smartya Banerjee, Mainak Sengupta3, Sanghamitra Mukhopadhyay, Pradip Bhattacharyya, Nitai Pada Roychoudhury2, Arpita Manna1, Soumen Kanti Ghosh, Sujoy |
author_sort | Basu, Madhurima |
collection | PubMed |
description | BACKGROUND: Renal involvement in T2DM can be due to diabetes per se (Diabetic Kidney Disease) or causes other than diabetes (Non-diabetic kidney disease). Currently available clinical, biochemical and radiological markers fail to differentiate DKD from NDKD and renal biopsy remains gold standard for correct diagnosis. While urinary signatures may provide a non-invasive alternative to that end, no study has been reported on urinary metabolomics of biopsy-confirmed DKD and NDKD subjects. AIMS: To identify the expression of urinary metabolic signatures as putative marker for differentiation of biopsy-confirmed DKD and NDKD subjects. METHODS: Consecutive patient with renal involvement were subjected to biopsy and classified as per ISN/RPS Classification. Morning urine sample were collected for analysis by Gas Chromatography and mass spectrometry. Features were extracted and analysed using appropriate statistical method. RESULTS: Urinary metabolites (M1, M2, M3, M4) were found to be depleted in patients with kidney disease (P < 0.004, <0.006, and < 0.01, <0.03 respectively). M5 was exclusively depleted in NDKD (n=16). The level of M6 (<0.01), M7 (<0.03) increased and M8 (<0.05), M9 (0.03), M10 (0.02) were decreased in DKD subjects (n=34) . CONCLUSION: Our pilot study suggests that urinary metabolomics analysis may help to distinguish DKD and NDKD subjects. Our results warrant validation in another cohort. |
format | Online Article Text |
id | pubmed-9067843 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Wolters Kluwer - Medknow |
record_format | MEDLINE/PubMed |
spelling | pubmed-90678432022-05-05 Abstract 16: Urinary metabolic signatures for differential diagnosis of diabetic and non-diabetic kidney disease Basu, Madhurima Islam1, S K Ramiz Neogi, Subhashis Pulai2, Smartya Banerjee, Mainak Sengupta3, Sanghamitra Mukhopadhyay, Pradip Bhattacharyya, Nitai Pada Roychoudhury2, Arpita Manna1, Soumen Kanti Ghosh, Sujoy Indian J Endocrinol Metab Abstracts … Esicon 2021 BACKGROUND: Renal involvement in T2DM can be due to diabetes per se (Diabetic Kidney Disease) or causes other than diabetes (Non-diabetic kidney disease). Currently available clinical, biochemical and radiological markers fail to differentiate DKD from NDKD and renal biopsy remains gold standard for correct diagnosis. While urinary signatures may provide a non-invasive alternative to that end, no study has been reported on urinary metabolomics of biopsy-confirmed DKD and NDKD subjects. AIMS: To identify the expression of urinary metabolic signatures as putative marker for differentiation of biopsy-confirmed DKD and NDKD subjects. METHODS: Consecutive patient with renal involvement were subjected to biopsy and classified as per ISN/RPS Classification. Morning urine sample were collected for analysis by Gas Chromatography and mass spectrometry. Features were extracted and analysed using appropriate statistical method. RESULTS: Urinary metabolites (M1, M2, M3, M4) were found to be depleted in patients with kidney disease (P < 0.004, <0.006, and < 0.01, <0.03 respectively). M5 was exclusively depleted in NDKD (n=16). The level of M6 (<0.01), M7 (<0.03) increased and M8 (<0.05), M9 (0.03), M10 (0.02) were decreased in DKD subjects (n=34) . CONCLUSION: Our pilot study suggests that urinary metabolomics analysis may help to distinguish DKD and NDKD subjects. Our results warrant validation in another cohort. Wolters Kluwer - Medknow 2022-03 /pmc/articles/PMC9067843/ http://dx.doi.org/10.4103/2230-8210.342130 Text en Copyright: © 2022 Indian Journal of Endocrinology and Metabolism https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms. |
spellingShingle | Abstracts … Esicon 2021 Basu, Madhurima Islam1, S K Ramiz Neogi, Subhashis Pulai2, Smartya Banerjee, Mainak Sengupta3, Sanghamitra Mukhopadhyay, Pradip Bhattacharyya, Nitai Pada Roychoudhury2, Arpita Manna1, Soumen Kanti Ghosh, Sujoy Abstract 16: Urinary metabolic signatures for differential diagnosis of diabetic and non-diabetic kidney disease |
title | Abstract 16: Urinary metabolic signatures for differential diagnosis of diabetic and non-diabetic kidney disease |
title_full | Abstract 16: Urinary metabolic signatures for differential diagnosis of diabetic and non-diabetic kidney disease |
title_fullStr | Abstract 16: Urinary metabolic signatures for differential diagnosis of diabetic and non-diabetic kidney disease |
title_full_unstemmed | Abstract 16: Urinary metabolic signatures for differential diagnosis of diabetic and non-diabetic kidney disease |
title_short | Abstract 16: Urinary metabolic signatures for differential diagnosis of diabetic and non-diabetic kidney disease |
title_sort | abstract 16: urinary metabolic signatures for differential diagnosis of diabetic and non-diabetic kidney disease |
topic | Abstracts … Esicon 2021 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9067843/ http://dx.doi.org/10.4103/2230-8210.342130 |
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