Cargando…
A new predictive model for the concurrent risk of diabetic retinopathy in type 2 diabetes patients and the effect of metformin on amino acids
OBJECTIVE: This study established a model to predict the risk of diabetic retinopathy (DR) with amino acids selected by partial least squares (PLS) method, and evaluated the effect of metformin on the effect of amino acids on DR in the model. METHODS: In Jinzhou, Liaoning Province, China, we retriev...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9434554/ https://www.ncbi.nlm.nih.gov/pubmed/36060930 http://dx.doi.org/10.3389/fendo.2022.985776 |
_version_ | 1784780897229209600 |
---|---|
author | Song, Zicheng Luo, Weiming Huang, Bing Cao, Yunfeng Jiang, Rongzhen |
author_facet | Song, Zicheng Luo, Weiming Huang, Bing Cao, Yunfeng Jiang, Rongzhen |
author_sort | Song, Zicheng |
collection | PubMed |
description | OBJECTIVE: This study established a model to predict the risk of diabetic retinopathy (DR) with amino acids selected by partial least squares (PLS) method, and evaluated the effect of metformin on the effect of amino acids on DR in the model. METHODS: In Jinzhou, Liaoning Province, China, we retrieved 1031 patients with type 2 diabetes (T2D) from the First Affiliated Hospital of Liaoning Medical University. After sorting the amino acids using the PLS method, the top 10 amino acids were included in the model. Multivariate logistic regression was used to analyze the relationship between different amino acids and DR. And then the effects of metformin on amino acids were explored through interaction. Finally, Spearman’s rank correlation analysis was used to analyze the correlation between different amino acids. RESULTS: After sorting by PLS, Gly, Pro, Leu, Lyr, Glu, Phe, Tyr, His, Val and Ser were finally included in the DR risk prediction model. The predictive model after adding amino acids was statistically different from the model that only included traditional risk factors (p=0.001). Metformin had a significant effect on the relationship between DR and 7 amino acids (Gly, Glu, Phe, Tyr, His, Val, Ser, p<0.05), and the population who are not using metformin and have high levels of Glu (OR: 0.44, 95%CI: 0.27-0.71) had an additive protection effect for the occurrence of DR. And the similar results can be seen in high levels of Gly (OR: 0.46, 95%CI: 0.29-0.75), Leu (OR: 0.48, 95%CI: 0.29-0.8), His (OR: 0.46, 95%CI: 0.29-0.75), Phe (OR: 0.24, 95%CI: 0.14-0.42) and Tyr (OR: 0.41, 95%CI: 0.24 -0.68) in population who are not using metformin. CONCLUSIONS: We established a prediction model of DR by amino acids and found that the use of metformin reduced the protective effect of amino acids on DR developing, suggesting that amino acids as biomarkers for predicting DR would be affected by metformin use. |
format | Online Article Text |
id | pubmed-9434554 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94345542022-09-02 A new predictive model for the concurrent risk of diabetic retinopathy in type 2 diabetes patients and the effect of metformin on amino acids Song, Zicheng Luo, Weiming Huang, Bing Cao, Yunfeng Jiang, Rongzhen Front Endocrinol (Lausanne) Endocrinology OBJECTIVE: This study established a model to predict the risk of diabetic retinopathy (DR) with amino acids selected by partial least squares (PLS) method, and evaluated the effect of metformin on the effect of amino acids on DR in the model. METHODS: In Jinzhou, Liaoning Province, China, we retrieved 1031 patients with type 2 diabetes (T2D) from the First Affiliated Hospital of Liaoning Medical University. After sorting the amino acids using the PLS method, the top 10 amino acids were included in the model. Multivariate logistic regression was used to analyze the relationship between different amino acids and DR. And then the effects of metformin on amino acids were explored through interaction. Finally, Spearman’s rank correlation analysis was used to analyze the correlation between different amino acids. RESULTS: After sorting by PLS, Gly, Pro, Leu, Lyr, Glu, Phe, Tyr, His, Val and Ser were finally included in the DR risk prediction model. The predictive model after adding amino acids was statistically different from the model that only included traditional risk factors (p=0.001). Metformin had a significant effect on the relationship between DR and 7 amino acids (Gly, Glu, Phe, Tyr, His, Val, Ser, p<0.05), and the population who are not using metformin and have high levels of Glu (OR: 0.44, 95%CI: 0.27-0.71) had an additive protection effect for the occurrence of DR. And the similar results can be seen in high levels of Gly (OR: 0.46, 95%CI: 0.29-0.75), Leu (OR: 0.48, 95%CI: 0.29-0.8), His (OR: 0.46, 95%CI: 0.29-0.75), Phe (OR: 0.24, 95%CI: 0.14-0.42) and Tyr (OR: 0.41, 95%CI: 0.24 -0.68) in population who are not using metformin. CONCLUSIONS: We established a prediction model of DR by amino acids and found that the use of metformin reduced the protective effect of amino acids on DR developing, suggesting that amino acids as biomarkers for predicting DR would be affected by metformin use. Frontiers Media S.A. 2022-08-18 /pmc/articles/PMC9434554/ /pubmed/36060930 http://dx.doi.org/10.3389/fendo.2022.985776 Text en Copyright © 2022 Song, Luo, Huang, Cao and Jiang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Song, Zicheng Luo, Weiming Huang, Bing Cao, Yunfeng Jiang, Rongzhen A new predictive model for the concurrent risk of diabetic retinopathy in type 2 diabetes patients and the effect of metformin on amino acids |
title | A new predictive model for the concurrent risk of diabetic retinopathy in type 2 diabetes patients and the effect of metformin on amino acids |
title_full | A new predictive model for the concurrent risk of diabetic retinopathy in type 2 diabetes patients and the effect of metformin on amino acids |
title_fullStr | A new predictive model for the concurrent risk of diabetic retinopathy in type 2 diabetes patients and the effect of metformin on amino acids |
title_full_unstemmed | A new predictive model for the concurrent risk of diabetic retinopathy in type 2 diabetes patients and the effect of metformin on amino acids |
title_short | A new predictive model for the concurrent risk of diabetic retinopathy in type 2 diabetes patients and the effect of metformin on amino acids |
title_sort | new predictive model for the concurrent risk of diabetic retinopathy in type 2 diabetes patients and the effect of metformin on amino acids |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9434554/ https://www.ncbi.nlm.nih.gov/pubmed/36060930 http://dx.doi.org/10.3389/fendo.2022.985776 |
work_keys_str_mv | AT songzicheng anewpredictivemodelfortheconcurrentriskofdiabeticretinopathyintype2diabetespatientsandtheeffectofmetforminonaminoacids AT luoweiming anewpredictivemodelfortheconcurrentriskofdiabeticretinopathyintype2diabetespatientsandtheeffectofmetforminonaminoacids AT huangbing anewpredictivemodelfortheconcurrentriskofdiabeticretinopathyintype2diabetespatientsandtheeffectofmetforminonaminoacids AT caoyunfeng anewpredictivemodelfortheconcurrentriskofdiabeticretinopathyintype2diabetespatientsandtheeffectofmetforminonaminoacids AT jiangrongzhen anewpredictivemodelfortheconcurrentriskofdiabeticretinopathyintype2diabetespatientsandtheeffectofmetforminonaminoacids AT songzicheng newpredictivemodelfortheconcurrentriskofdiabeticretinopathyintype2diabetespatientsandtheeffectofmetforminonaminoacids AT luoweiming newpredictivemodelfortheconcurrentriskofdiabeticretinopathyintype2diabetespatientsandtheeffectofmetforminonaminoacids AT huangbing newpredictivemodelfortheconcurrentriskofdiabeticretinopathyintype2diabetespatientsandtheeffectofmetforminonaminoacids AT caoyunfeng newpredictivemodelfortheconcurrentriskofdiabeticretinopathyintype2diabetespatientsandtheeffectofmetforminonaminoacids AT jiangrongzhen newpredictivemodelfortheconcurrentriskofdiabeticretinopathyintype2diabetespatientsandtheeffectofmetforminonaminoacids |