Cargando…

Insulin-resistance and depression cohort data mining to identify nutraceutical related DNA methylation biomarker for type 2 diabetes

Insulin-resistance (IR) is one of the most important precursors of type 2 diabetes (T2D). Recent evidence suggests an association of depression with the onset of T2D. Accumulating evidence shows that depression and T2D share common biological origins, and DNA methylation examination might reveal the...

Descripción completa

Detalles Bibliográficos
Autores principales: Liang, Fengji, Quan, Yuan, Wu, Andong, Chen, Ying, Xu, Ruifeng, Zhu, Yuexing, Xiong, Jianghui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Chongqing Medical University 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278533/
https://www.ncbi.nlm.nih.gov/pubmed/34291138
http://dx.doi.org/10.1016/j.gendis.2020.01.013
_version_ 1783722281446408192
author Liang, Fengji
Quan, Yuan
Wu, Andong
Chen, Ying
Xu, Ruifeng
Zhu, Yuexing
Xiong, Jianghui
author_facet Liang, Fengji
Quan, Yuan
Wu, Andong
Chen, Ying
Xu, Ruifeng
Zhu, Yuexing
Xiong, Jianghui
author_sort Liang, Fengji
collection PubMed
description Insulin-resistance (IR) is one of the most important precursors of type 2 diabetes (T2D). Recent evidence suggests an association of depression with the onset of T2D. Accumulating evidence shows that depression and T2D share common biological origins, and DNA methylation examination might reveal the link between lifestyle, disease risk, and potential therapeutic targets for T2D. Here we hypothesize that integrative mining of IR and depression cohort data will facilitate predictive biomarkers identification for T2D. We utilized a newly proposed method to extract gene-level information from probe level data on genome-wide DNA methylation array. We identified a set of genes associated with IR and depression in clinical cohorts. By overlapping the IR-related nutraceutical-gene network with depression networks, we identified a common subnetwork centered with Vitamin D Receptor (VDR) gene. Preliminary clinical validation of gene methylation set in a small cohort of T2D patients and controls was established using the Sequenome matrix-assisted laser desorption ionization-time flight mass spectrometry. A set of sites in the promoter regions of VDR showed a significant difference between T2D patients and controls. Using a logistic regression model, the optimal prediction performance of these sites was AUC = 0.902,and an odds ratio = 19.76. Thus, monitoring the methylation status of specific VDR promoter region might help stratify the high-risk individuals who could potentially benefit from vitamin D dietary supplementation. Our results highlight the link between IR and depression, and the DNA methylation analysis might facilitate the search for their shared mechanisms in the etiology of T2D.
format Online
Article
Text
id pubmed-8278533
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Chongqing Medical University
record_format MEDLINE/PubMed
spelling pubmed-82785332021-07-20 Insulin-resistance and depression cohort data mining to identify nutraceutical related DNA methylation biomarker for type 2 diabetes Liang, Fengji Quan, Yuan Wu, Andong Chen, Ying Xu, Ruifeng Zhu, Yuexing Xiong, Jianghui Genes Dis Full Length Article Insulin-resistance (IR) is one of the most important precursors of type 2 diabetes (T2D). Recent evidence suggests an association of depression with the onset of T2D. Accumulating evidence shows that depression and T2D share common biological origins, and DNA methylation examination might reveal the link between lifestyle, disease risk, and potential therapeutic targets for T2D. Here we hypothesize that integrative mining of IR and depression cohort data will facilitate predictive biomarkers identification for T2D. We utilized a newly proposed method to extract gene-level information from probe level data on genome-wide DNA methylation array. We identified a set of genes associated with IR and depression in clinical cohorts. By overlapping the IR-related nutraceutical-gene network with depression networks, we identified a common subnetwork centered with Vitamin D Receptor (VDR) gene. Preliminary clinical validation of gene methylation set in a small cohort of T2D patients and controls was established using the Sequenome matrix-assisted laser desorption ionization-time flight mass spectrometry. A set of sites in the promoter regions of VDR showed a significant difference between T2D patients and controls. Using a logistic regression model, the optimal prediction performance of these sites was AUC = 0.902,and an odds ratio = 19.76. Thus, monitoring the methylation status of specific VDR promoter region might help stratify the high-risk individuals who could potentially benefit from vitamin D dietary supplementation. Our results highlight the link between IR and depression, and the DNA methylation analysis might facilitate the search for their shared mechanisms in the etiology of T2D. Chongqing Medical University 2020-01-27 /pmc/articles/PMC8278533/ /pubmed/34291138 http://dx.doi.org/10.1016/j.gendis.2020.01.013 Text en © 2020 Chongqing Medical University. Production and hosting by Elsevier B.V. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Full Length Article
Liang, Fengji
Quan, Yuan
Wu, Andong
Chen, Ying
Xu, Ruifeng
Zhu, Yuexing
Xiong, Jianghui
Insulin-resistance and depression cohort data mining to identify nutraceutical related DNA methylation biomarker for type 2 diabetes
title Insulin-resistance and depression cohort data mining to identify nutraceutical related DNA methylation biomarker for type 2 diabetes
title_full Insulin-resistance and depression cohort data mining to identify nutraceutical related DNA methylation biomarker for type 2 diabetes
title_fullStr Insulin-resistance and depression cohort data mining to identify nutraceutical related DNA methylation biomarker for type 2 diabetes
title_full_unstemmed Insulin-resistance and depression cohort data mining to identify nutraceutical related DNA methylation biomarker for type 2 diabetes
title_short Insulin-resistance and depression cohort data mining to identify nutraceutical related DNA methylation biomarker for type 2 diabetes
title_sort insulin-resistance and depression cohort data mining to identify nutraceutical related dna methylation biomarker for type 2 diabetes
topic Full Length Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278533/
https://www.ncbi.nlm.nih.gov/pubmed/34291138
http://dx.doi.org/10.1016/j.gendis.2020.01.013
work_keys_str_mv AT liangfengji insulinresistanceanddepressioncohortdataminingtoidentifynutraceuticalrelateddnamethylationbiomarkerfortype2diabetes
AT quanyuan insulinresistanceanddepressioncohortdataminingtoidentifynutraceuticalrelateddnamethylationbiomarkerfortype2diabetes
AT wuandong insulinresistanceanddepressioncohortdataminingtoidentifynutraceuticalrelateddnamethylationbiomarkerfortype2diabetes
AT chenying insulinresistanceanddepressioncohortdataminingtoidentifynutraceuticalrelateddnamethylationbiomarkerfortype2diabetes
AT xuruifeng insulinresistanceanddepressioncohortdataminingtoidentifynutraceuticalrelateddnamethylationbiomarkerfortype2diabetes
AT zhuyuexing insulinresistanceanddepressioncohortdataminingtoidentifynutraceuticalrelateddnamethylationbiomarkerfortype2diabetes
AT xiongjianghui insulinresistanceanddepressioncohortdataminingtoidentifynutraceuticalrelateddnamethylationbiomarkerfortype2diabetes