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In Search for the Genetic Basis of Quality of Life in Healthy Swedish Women—A GWAS Study Using the iCOGS Custom Genotyping Array
Author(s) -
Dounya Schoormans,
Hatef Darabi,
Jingmei Li,
Yvonne Brandberg,
Mikael Eriksson,
Koos Zwinderman,
Mirjam A. G. Sprangers,
Per Hall
Publication year - 2015
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0140563
Subject(s) - single nucleotide polymorphism , genome wide association study , population stratification , genotyping , bonferroni correction , genetic association , genetic variation , population , biology , genetics , ancestry informative marker , medicine , bioinformatics , genotype , gene , statistics , mathematics , environmental health
Background Quality of life (QoL) is increasingly measured in both research and clinical practice. QoL-assessments are built on a long, empirically-based, and stringent approach. There is ample evidence that QoL is, in part, heritable. We therefore performed a GWAS relating genetic variation to QoL in healthy females. Methods In 5,142 healthy females, background characteristics (e.g. demographic, clinical, lifestyle and psychological factors) and QoL by means of the EORTC QLQ-C30 were measured. Moreover, women were genotyped using a custom array including ~210,000 single nucleotide polymorphisms (SNPs). Initially, SNPs were related to each QoL-domain, by means of partially adjusted (controlling for age and population stratification) and fully adjusted (controlling for age, population stratification, and background characteristics) regression analyses. Additionally, gene-based analyses were performed relating the combined effect of SNPs within each gene to QoL using the statistical software package VEGAS. Results None of the associations between QoL and genetic variation (i.e. individual SNPs and genes) reached the bonferroni corrected significance level. Conclusion Reasons for a lack of association between genetic markers and QoL could be low variation in QoL-scores; selecting genetic markers not tagging QoL; or that the genetic effect that impacts one’s QoL is mediated through biological pathways rather than the effect of single SNPs or genes. Therefore, we opt for a pathway-based or system biology approach as a complementary and powerful approach to analyze the combined effect of genes and their biological implications in future studies focusing on QoL-issues.

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