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. 2014 Aug;43(4):1205-14.
doi: 10.1093/ije/dyu090. Epub 2014 Apr 30.

Shared common variants in prostate cancer and blood lipids

Affiliations

Shared common variants in prostate cancer and blood lipids

Ole A Andreassen et al. Int J Epidemiol. 2014 Aug.

Abstract

Background: Epidemiological and clinical studies suggest comorbidity between prostate cancer (PCA) and cardiovascular disease (CVD) risk factors. However, the relationship between these two phenotypes is still not well understood. Here we sought to identify shared genetic loci between PCA and CVD risk factors.

Methods: We applied a genetic epidemiology method based on conjunction false discovery rate (FDR) that combines summary statistics from different genome-wide association studies (GWAS), and allows identification of genetic overlap between two phenotypes. We evaluated summary statistics from large, multi-centre GWA studies of PCA (n=50 000) and CVD risk factors (n=200 000) [triglycerides (TG), low-density lipoprotein (LDL) cholesterol and high-density lipoprotein (HDL) cholesterol, systolic blood pressure, body mass index, waist-hip ratio and type 2 diabetes (T2D)]. Enrichment of single nucleotide polymorphisms (SNPs) associated with PCA and CVD risk factors was assessed with conditional quantile-quantile plots and the Anderson-Darling test. Moreover, we pinpointed shared loci using conjunction FDR.

Results: We found the strongest enrichment of P-values in PCA was conditional on LDL and conditional on TG. In contrast, we found only weak enrichment conditional on HDL or conditional on the other traits investigated. Conjunction FDR identified altogether 17 loci; 10 loci were associated with PCA and LDL, 3 loci were associated with PCA and TG and additionally 4 loci were associated with PCA, LDL and TG jointly (conjunction FDR <0.01). For T2D, we detected one locus adjacent to HNF1B.

Conclusions: We found polygenic overlap between PCA predisposition and blood lipids, in particular LDL and TG, and identified 17 pleiotropic gene loci between PCA and LDL, and PCA and TG, respectively. These findings provide novel pathobiological insights and may have implications for trials using targeting lipid-lowering agents in a prevention or cancer setting.

Keywords: Prostate cancer; blood lipids; cholesterol; genetic epidemiology; pleiotropy; type 2 diabetes.

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Figures

Figure 1.
Figure 1.
Conditional Q-Q plots : PCA | CVD factors (LDL, HDL, TG, T2D). Conditional Q-Q plot’ of nominal vs empirical -log10 P-values (corrected for inflation) in prostate cancer (PCA) below the standard GWAS threshold of -log10 P-values equal to 7.3 (equals P-values above 5 x 10-8) as a function of significance of association with (A) low-density lipoprotein cholesterol (LDL), (B) and high-density lipoprotein cholesterol (HDL, (C) triglycerides (TG) and (D) type 2 diabetes (T2D) at the level of -log10(p) >0, -log10(p) >1, -log10(p) >2, -log10(p) >3 corresponding to P < 1, P <0.1, P < 0.01, P < 0.001, respectively. Dotted lines indicate the theoretical line in case of no association.
Figure 2.
Figure 2.
Conjunction FDR Manhattan plot. ‘Conjunction FDR Manhattan plot’ of conjunction -log10 (FDR) values for prostate cancer (PCA) and low-density lipoprotein cholesterol (LDL) and triglycerides (TG); the conjunctions are denoted as PCA&LDL, and PCA&TG, respectively. SNPs with -log10 (FDR) >2, (i.e. FDR <0.01) for both PCA & LDL (red), PCA and TG (violet), respectively, are shown with large points. A black line around the large points indicates the SNP with the strongest association in each LDL block and this SNP was annotated with the closest gene, which is listed above the symbols in each chromosome. The figure shows the localization of the ‘pleiotropic loci’, and further details are provided in Table 1.

References

    1. Pierce BL. Why are diabetics at reduced risk for prostate cancer? A review of the epidemiologic evidence. Urol Oncol 2012;30:735–43. - PubMed
    1. Cohen JH, Kristal AR, Stanford JL. Fruit and vegetable intakes and prostate cancer risk. J Natl Cancer Inst 2000;92:61–68. - PubMed
    1. Chan JM, Giovannucci EL. Dairy products, calcium, and vitamin D and risk of prostate cancer. Epidemiol Rev 2001;23:87–92. - PubMed
    1. International Consortium for Blood Pressure Genome-Wide Association S, Ehret GB, Munroe PB, et al. Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk. Nature 2011;478:103–09. - PMC - PubMed
    1. Global Lipids Genetics C, Willer CJ, Schmidt EM, et al. Discovery and refinement of loci associated with lipid levels. Nat Genet 2013;45:1274–83. - PMC - PubMed

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