Cargando…
Metabolomics profiles associated with diabetic retinopathy in type 2 diabetes patients
Diabetic retinopathy (DR) is a common complication of diabetes, and it is the consequence of microvascular retinal changes due to high glucose levels over a long time. Metabolomics profiling is a rapidly evolving method used to identify the metabolites in biological fluids and investigate disease pr...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7595280/ https://www.ncbi.nlm.nih.gov/pubmed/33119699 http://dx.doi.org/10.1371/journal.pone.0241365 |
_version_ | 1783601835416748032 |
---|---|
author | Yun, Jun Ho Kim, Jeong-Min Jeon, Hyun Jeong Oh, Taekeun Choi, Hyung Jin Kim, Bong-Jo |
author_facet | Yun, Jun Ho Kim, Jeong-Min Jeon, Hyun Jeong Oh, Taekeun Choi, Hyung Jin Kim, Bong-Jo |
author_sort | Yun, Jun Ho |
collection | PubMed |
description | Diabetic retinopathy (DR) is a common complication of diabetes, and it is the consequence of microvascular retinal changes due to high glucose levels over a long time. Metabolomics profiling is a rapidly evolving method used to identify the metabolites in biological fluids and investigate disease progression. In this study, we used a targeted metabolomics approach to quantify the serum metabolites in type 2 diabetes (T2D) patients. Diabetes patients were divided into three groups based on the status of their complications: non-DR (NDR, n = 143), non-proliferative DR (NPDR, n = 123), and proliferative DR (PDR, n = 51) groups. Multiple logistic regression analysis and multiple testing corrections were performed to identify the significant differences in the metabolomics profiles of the different analysis groups. The concentrations of 62 metabolites of the NDR versus DR group, 53 metabolites of the NDR versus NPDR group, and 30 metabolites of the NDR versus PDR group were found to be significantly different. Finally, sixteen metabolites were selected as specific metabolites common to NPDR and PDR. Among them, three metabolites including total DMA, tryptophan, and kynurenine were potential makers of DR progression in T2D patients. Additionally, several metabolites such as carnitines, several amino acids, and phosphatidylcholines also showed a marker potential. The metabolite signatures identified in this study will provide insight into the mechanisms underlying DR development and progression in T2D patients in future studies. |
format | Online Article Text |
id | pubmed-7595280 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-75952802020-11-02 Metabolomics profiles associated with diabetic retinopathy in type 2 diabetes patients Yun, Jun Ho Kim, Jeong-Min Jeon, Hyun Jeong Oh, Taekeun Choi, Hyung Jin Kim, Bong-Jo PLoS One Research Article Diabetic retinopathy (DR) is a common complication of diabetes, and it is the consequence of microvascular retinal changes due to high glucose levels over a long time. Metabolomics profiling is a rapidly evolving method used to identify the metabolites in biological fluids and investigate disease progression. In this study, we used a targeted metabolomics approach to quantify the serum metabolites in type 2 diabetes (T2D) patients. Diabetes patients were divided into three groups based on the status of their complications: non-DR (NDR, n = 143), non-proliferative DR (NPDR, n = 123), and proliferative DR (PDR, n = 51) groups. Multiple logistic regression analysis and multiple testing corrections were performed to identify the significant differences in the metabolomics profiles of the different analysis groups. The concentrations of 62 metabolites of the NDR versus DR group, 53 metabolites of the NDR versus NPDR group, and 30 metabolites of the NDR versus PDR group were found to be significantly different. Finally, sixteen metabolites were selected as specific metabolites common to NPDR and PDR. Among them, three metabolites including total DMA, tryptophan, and kynurenine were potential makers of DR progression in T2D patients. Additionally, several metabolites such as carnitines, several amino acids, and phosphatidylcholines also showed a marker potential. The metabolite signatures identified in this study will provide insight into the mechanisms underlying DR development and progression in T2D patients in future studies. Public Library of Science 2020-10-29 /pmc/articles/PMC7595280/ /pubmed/33119699 http://dx.doi.org/10.1371/journal.pone.0241365 Text en © 2020 Yun et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Yun, Jun Ho Kim, Jeong-Min Jeon, Hyun Jeong Oh, Taekeun Choi, Hyung Jin Kim, Bong-Jo Metabolomics profiles associated with diabetic retinopathy in type 2 diabetes patients |
title | Metabolomics profiles associated with diabetic retinopathy in type 2 diabetes patients |
title_full | Metabolomics profiles associated with diabetic retinopathy in type 2 diabetes patients |
title_fullStr | Metabolomics profiles associated with diabetic retinopathy in type 2 diabetes patients |
title_full_unstemmed | Metabolomics profiles associated with diabetic retinopathy in type 2 diabetes patients |
title_short | Metabolomics profiles associated with diabetic retinopathy in type 2 diabetes patients |
title_sort | metabolomics profiles associated with diabetic retinopathy in type 2 diabetes patients |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7595280/ https://www.ncbi.nlm.nih.gov/pubmed/33119699 http://dx.doi.org/10.1371/journal.pone.0241365 |
work_keys_str_mv | AT yunjunho metabolomicsprofilesassociatedwithdiabeticretinopathyintype2diabetespatients AT kimjeongmin metabolomicsprofilesassociatedwithdiabeticretinopathyintype2diabetespatients AT jeonhyunjeong metabolomicsprofilesassociatedwithdiabeticretinopathyintype2diabetespatients AT ohtaekeun metabolomicsprofilesassociatedwithdiabeticretinopathyintype2diabetespatients AT choihyungjin metabolomicsprofilesassociatedwithdiabeticretinopathyintype2diabetespatients AT kimbongjo metabolomicsprofilesassociatedwithdiabeticretinopathyintype2diabetespatients |