The genetic basis of quality of life in healthy Swedish women: A candidate gene approach

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Abstract

Background: Quality of life (QoL) is an increasingly important parameter in clinical practice as it predicts mortality and poor health outcomes. It is hypothesized that one may have a genetic predisposition for QoL. We therefore related 139 candidate genes, selected through a literature search, to QoL in healthy females. Methods: In 5,142 healthy females, background characteristics (i.e. demographic, clinical, lifestyle, and psychological factors) were assessed. QoL was measured by the EORTC QLQ-C30, which consists of 15 domains. For all women genotype information was available. For each candidate gene, single nucleotide polymorphisms (SNPs) were identified based on their functional (n = 2,663) and physical annotation (n = 10,649). SNPs were related to each QoL-domain, while controlling for background characteristics and population stratification. Finally, gene-based analyses were performed relating the combined effect of 10,649 SNPs (selected based on physical annotation) for each gene, to QoL using the statistical software package VEGAS. Results: Overall, we found no relation between genetic variations (SNPs and genes) and 14 out of 15 QoL-domains. The strongest association was found between cognitive functioning and the top SNP rs1468951 (p = 1.21E-05) in the GSTZ1 gene. Furthermore, results of the gene-based test showed that the combined effect of 11 SNPs within the GSTZ1 gene is significantly associated with cognitive functioning (p = 2.60E-05). Conclusion: If validated, the involvement of GSTZ1 in cognitive functioning underscores its heritability which is likely the result of differences in the dopamine pathway, as GSTZ1 contributes to the equilibrium between dopamine and its neurotoxic metabolites via the glutathione redox cycle.

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Schoormans, D., Li, J., Darabi, H., Brandberg, Y., Sprangers, M. A. G., Eriksson, M., … Hall, P. (2015). The genetic basis of quality of life in healthy Swedish women: A candidate gene approach. PLoS ONE, 10(2). https://doi.org/10.1371/journal.pone.0118292

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