Data to genetic risk assessment on high-density cholesterol level associated polymorphisms in Hungarian general and Roma populations

Péter Pikó, Szilvia Fiatal, Zsigmond Kósa, J. Sándor, R. Ádány

Research output: Article

2 Citations (Scopus)

Abstract

Data obtained by genotyping single nucleotide polymorphisms (SNPs) related to high-density lipoprotein cholesterol (HDL-C) levels were utilized in Genetic Risk Score [unweighted (GRS) and weighted (wGRS)] computation on Hungarian general and Roma populations. The selection process of the SNPs as well as the results obtained are published in our research article (Piko et al., 2017) [1]. Linkage analyses were performed by study groups. Study populations were stratified by quintiles of weighted Genetic Risk Score. Multivariate linear regression analyses were performed using Genetic Risk Scores and HDL-C levels as dependent variables; and ethnicity, sex and age as independent variables. The study subjects were categorized into quintiles according their wGRS values. Associations of Genetic Risk Scores with plasma HDL-C levels (as a continuous variable) were observed in both populations. Finally, the two populations were merged and analyzed together by multivariate logistic regression where reduced plasma HDL-C level was the dependent variable; while ethnicity, age and sex were the independent ones.

Original languageEnglish
Pages (from-to)354-359
Number of pages6
JournalData in Brief
Volume14
DOIs
Publication statusPublished - okt. 1 2017

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title = "Data to genetic risk assessment on high-density cholesterol level associated polymorphisms in Hungarian general and Roma populations",
abstract = "Data obtained by genotyping single nucleotide polymorphisms (SNPs) related to high-density lipoprotein cholesterol (HDL-C) levels were utilized in Genetic Risk Score [unweighted (GRS) and weighted (wGRS)] computation on Hungarian general and Roma populations. The selection process of the SNPs as well as the results obtained are published in our research article (Piko et al., 2017) [1]. Linkage analyses were performed by study groups. Study populations were stratified by quintiles of weighted Genetic Risk Score. Multivariate linear regression analyses were performed using Genetic Risk Scores and HDL-C levels as dependent variables; and ethnicity, sex and age as independent variables. The study subjects were categorized into quintiles according their wGRS values. Associations of Genetic Risk Scores with plasma HDL-C levels (as a continuous variable) were observed in both populations. Finally, the two populations were merged and analyzed together by multivariate logistic regression where reduced plasma HDL-C level was the dependent variable; while ethnicity, age and sex were the independent ones.",
keywords = "Genetic risk score, Genetic susceptibility, High-density lipoprotein cholesterol, Roma population, Single nucleotide polymorphism",
author = "P{\'e}ter Pik{\'o} and Szilvia Fiatal and Zsigmond K{\'o}sa and J. S{\'a}ndor and R. {\'A}d{\'a}ny",
year = "2017",
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T1 - Data to genetic risk assessment on high-density cholesterol level associated polymorphisms in Hungarian general and Roma populations

AU - Pikó, Péter

AU - Fiatal, Szilvia

AU - Kósa, Zsigmond

AU - Sándor, J.

AU - Ádány, R.

PY - 2017/10/1

Y1 - 2017/10/1

N2 - Data obtained by genotyping single nucleotide polymorphisms (SNPs) related to high-density lipoprotein cholesterol (HDL-C) levels were utilized in Genetic Risk Score [unweighted (GRS) and weighted (wGRS)] computation on Hungarian general and Roma populations. The selection process of the SNPs as well as the results obtained are published in our research article (Piko et al., 2017) [1]. Linkage analyses were performed by study groups. Study populations were stratified by quintiles of weighted Genetic Risk Score. Multivariate linear regression analyses were performed using Genetic Risk Scores and HDL-C levels as dependent variables; and ethnicity, sex and age as independent variables. The study subjects were categorized into quintiles according their wGRS values. Associations of Genetic Risk Scores with plasma HDL-C levels (as a continuous variable) were observed in both populations. Finally, the two populations were merged and analyzed together by multivariate logistic regression where reduced plasma HDL-C level was the dependent variable; while ethnicity, age and sex were the independent ones.

AB - Data obtained by genotyping single nucleotide polymorphisms (SNPs) related to high-density lipoprotein cholesterol (HDL-C) levels were utilized in Genetic Risk Score [unweighted (GRS) and weighted (wGRS)] computation on Hungarian general and Roma populations. The selection process of the SNPs as well as the results obtained are published in our research article (Piko et al., 2017) [1]. Linkage analyses were performed by study groups. Study populations were stratified by quintiles of weighted Genetic Risk Score. Multivariate linear regression analyses were performed using Genetic Risk Scores and HDL-C levels as dependent variables; and ethnicity, sex and age as independent variables. The study subjects were categorized into quintiles according their wGRS values. Associations of Genetic Risk Scores with plasma HDL-C levels (as a continuous variable) were observed in both populations. Finally, the two populations were merged and analyzed together by multivariate logistic regression where reduced plasma HDL-C level was the dependent variable; while ethnicity, age and sex were the independent ones.

KW - Genetic risk score

KW - Genetic susceptibility

KW - High-density lipoprotein cholesterol

KW - Roma population

KW - Single nucleotide polymorphism

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