A 6-CpG validated methylation risk score model for metabolic syndrome: The HyperGEN and GOLDN studies

There has been great interest in genetic risk prediction using risk scores in recent years, however, the utility of scores developed in European populations and later applied to non-European populations has not been successful. The goal of this study was to create a methylation risk score (MRS) for...

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Autores principales:	Bertha A. Hidalgo, Bre Minniefield, Amit Patki, Rikki Tanner, Minoo Bagheri, Hemant K. Tiwari, Donna K. Arnett, Marguerite Ryan Irvin
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/7f2fe72c0c62478ea914cbc42a971962
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spelling	oai:doaj.org-article:7f2fe72c0c62478ea914cbc42a9719622021-11-25T05:54:26ZA 6-CpG validated methylation risk score model for metabolic syndrome: The HyperGEN and GOLDN studies1932-6203https://doaj.org/article/7f2fe72c0c62478ea914cbc42a9719622021-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8592434/?tool=EBIhttps://doaj.org/toc/1932-6203There has been great interest in genetic risk prediction using risk scores in recent years, however, the utility of scores developed in European populations and later applied to non-European populations has not been successful. The goal of this study was to create a methylation risk score (MRS) for metabolic syndrome (MetS), demonstrating the utility of MRS across race groups using cross-sectional data from the Hypertension Genetic Epidemiology Network (HyperGEN, N = 614 African Americans (AA)) and the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, N = 995 European Americans (EA)). To demonstrate this, we first selected cytosine-guanine dinucleotides (CpG) sites measured on Illumina Methyl450 arrays previously reported to be significantly associated with MetS and/or component conditions in more than one race/ethnic group (CPT1A cg00574958, PHOSPHO1 cg02650017, ABCG1 cg06500161, SREBF1 cg11024682, SOCS3 cg18181703, TXNIP cg19693031). Second, we calculated the parameter estimates for the 6 CpGs in the HyperGEN data (AA) and used the beta estimates as weights to construct a MRS in HyperGEN (AA), which was validated in GOLDN (EA). We performed association analyses using logistic mixed models to test the association between the MRS and MetS, adjusting for covariates. Results showed the MRS was significantly associated with MetS in both populations. In summary, a MRS for MetS was a strong predictor for the condition across two race groups, suggesting MRS may be useful to examine metabolic disease risk or related complications across race/ethnic groups.Bertha A. HidalgoBre MinniefieldAmit PatkiRikki TannerMinoo BagheriHemant K. TiwariDonna K. ArnettMarguerite Ryan IrvinPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Bertha A. Hidalgo Bre Minniefield Amit Patki Rikki Tanner Minoo Bagheri Hemant K. Tiwari Donna K. Arnett Marguerite Ryan Irvin A 6-CpG validated methylation risk score model for metabolic syndrome: The HyperGEN and GOLDN studies
description	There has been great interest in genetic risk prediction using risk scores in recent years, however, the utility of scores developed in European populations and later applied to non-European populations has not been successful. The goal of this study was to create a methylation risk score (MRS) for metabolic syndrome (MetS), demonstrating the utility of MRS across race groups using cross-sectional data from the Hypertension Genetic Epidemiology Network (HyperGEN, N = 614 African Americans (AA)) and the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, N = 995 European Americans (EA)). To demonstrate this, we first selected cytosine-guanine dinucleotides (CpG) sites measured on Illumina Methyl450 arrays previously reported to be significantly associated with MetS and/or component conditions in more than one race/ethnic group (CPT1A cg00574958, PHOSPHO1 cg02650017, ABCG1 cg06500161, SREBF1 cg11024682, SOCS3 cg18181703, TXNIP cg19693031). Second, we calculated the parameter estimates for the 6 CpGs in the HyperGEN data (AA) and used the beta estimates as weights to construct a MRS in HyperGEN (AA), which was validated in GOLDN (EA). We performed association analyses using logistic mixed models to test the association between the MRS and MetS, adjusting for covariates. Results showed the MRS was significantly associated with MetS in both populations. In summary, a MRS for MetS was a strong predictor for the condition across two race groups, suggesting MRS may be useful to examine metabolic disease risk or related complications across race/ethnic groups.
format	article
author	Bertha A. Hidalgo Bre Minniefield Amit Patki Rikki Tanner Minoo Bagheri Hemant K. Tiwari Donna K. Arnett Marguerite Ryan Irvin
author_facet	Bertha A. Hidalgo Bre Minniefield Amit Patki Rikki Tanner Minoo Bagheri Hemant K. Tiwari Donna K. Arnett Marguerite Ryan Irvin
author_sort	Bertha A. Hidalgo
title	A 6-CpG validated methylation risk score model for metabolic syndrome: The HyperGEN and GOLDN studies
title_short	A 6-CpG validated methylation risk score model for metabolic syndrome: The HyperGEN and GOLDN studies
title_full	A 6-CpG validated methylation risk score model for metabolic syndrome: The HyperGEN and GOLDN studies
title_fullStr	A 6-CpG validated methylation risk score model for metabolic syndrome: The HyperGEN and GOLDN studies
title_full_unstemmed	A 6-CpG validated methylation risk score model for metabolic syndrome: The HyperGEN and GOLDN studies
title_sort	6-cpg validated methylation risk score model for metabolic syndrome: the hypergen and goldn studies
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/7f2fe72c0c62478ea914cbc42a971962
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A 6-CpG validated methylation risk score model for metabolic syndrome: The HyperGEN and GOLDN studies

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