A comparison of Bayesian and frequentist approaches to incorporating external information for the prediction of prostate cancer risk.

We present the most comprehensive comparison to date of the predictive benefit of genetics in addition to currently used clinical variables, using genotype data for 33 single-nucleotide polymorphisms (SNPs) in 1,547 Caucasian men from the placebo arm of the REduction by DUtasteride of prostate Cancer Events (REDUCE®) trial. Moreover, we conducted a detailed comparison of three techniques for incorporating genetics into clinical risk prediction. The first method was a standard logistic regression model, which included separate terms for the clinical covariates and for each of the genetic markers. This approach ignores a substantial amount of external information concerning effect sizes for these Genome Wide Association Study (GWAS)-replicated SNPs. The second and third methods investigated two possible approaches to incorporating meta-analysed external SNP effect estimates - one via a weighted PCa 'risk' score based solely on the meta analysis estimates, and the other incorporating both the current and prior data via informative priors in a Bayesian logistic regression model. All methods demonstrated a slight improvement in predictive performance upon incorporation of genetics. The two methods that incorporated external information showed the greatest receiver-operating-characteristic AUCs increase from 0.61 to 0.64. The value of our methods comparison is likely to lie in observations of performance similarities, rather than difference, between three approaches of very different resource requirements. The two methods that included external information performed best, but only marginally despite substantial differences in complexity.

Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.

Deep sequencing of the LRRK2 gene in 14,002 individuals reveals evidence of purifying selection and independent origin of the p.Arg1628Pro mutation in Europe.

Genetic variation in LRRK2 predisposes to Parkinson disease (PD), which underpins its development as a therapeutic target. Here, we aimed to identify novel genotype-phenotype associations that might support developing LRRK2 therapies for other conditions. We sequenced the 51 exons of LRRK2 in cases comprising 12 common diseases (n = 9,582), and in 4,420 population controls. We identified 739 single-nucleotide variants, 62% of which were observed in only one person, including 316 novel exonic variants. We found evidence of purifying selection for the LRRK2 gene and a trend suggesting that this is more pronounced in the central (ROC-COR-kinase) core protein domains of LRRK2 than the flanking domains. Population genetic analyses revealed that LRRK2 is not especially polymorphic or differentiated in comparison to 201 other drug target genes. Among Europeans, we identified 17 carriers (0.13%) of pathogenic LRRK2 mutations that were not significantly enriched within any disease or in those reporting a family history of PD. Analysis of pathogenic mutations within Europe reveals that the p.Arg1628Pro (c4883G>C) mutation arose independently in Europe and Asia. Taken together, these findings demonstrate how targeted deep sequencing can help to reveal fundamental characteristics of clinically important loci.

An 18-kDa translocator protein (TSPO) polymorphism explains differences in binding affinity of the PET radioligand PBR28.

[(11)C]PBR28 binds the 18-kDa Translocator Protein (TSPO) and is used in positron emission tomography (PET) to detect microglial activation. However, quantitative interpretations of signal are confounded by large interindividual variability in binding affinity, which displays a trimodal distribution compatible with a codominant genetic trait. Here, we tested directly for an underlying genetic mechanism to explain this. Binding affinity of PBR28 was measured in platelets isolated from 41 human subjects and tested for association with polymorphisms in TSPO and genes encoding other proteins in the TSPO complex. Complete agreement was observed between the TSPO Ala147Thr genotype and PBR28 binding affinity phenotype (P value=3.1 × 10(-13)). The TSPO Ala147Thr polymorphism predicts PBR28 binding affinity in human platelets. As all second-generation TSPO PET radioligands tested hitherto display a trimodal distribution in binding affinity analogous to PBR28, testing for this polymorphism may allow quantitative interpretation of TSPO PET studies with these radioligands.

Performance of genotype imputation for rare variants identified in exons and flanking regions of genes.

Genotype imputation has the potential to assess human genetic variation at a lower cost than assaying the variants using laboratory techniques. The performance of imputation for rare variants has not been comprehensively studied. We utilized 8865 human samples with high depth resequencing data for the exons and flanking regions of 202 genes and Genome-Wide Association Study (GWAS) data to characterize the performance of genotype imputation for rare variants. We evaluated reference sets ranging from 100 to 3713 subjects for imputing into samples typed for the Affymetrix (500K and 6.0) and Illumina 550K GWAS panels. The proportion of variants that could be well imputed (true r(2)>0.7) with a reference panel of 3713 individuals was: 31% (Illumina 550K) or 25% (Affymetrix 500K) with MAF (Minor Allele Frequency) less than or equal 0.001, 48% or 35% with 0.0010.05. The performance for common SNPs (MAF>0.05) within exons and flanking regions is comparable to imputation of more uniformly distributed SNPs. The performance for rare SNPs (0.01

Pazopanib efficacy in renal cell carcinoma: evidence for predictive genetic markers in angiogenesis-related and exposure-related genes.

PURPOSE: Pazopanib, an oral angiogenesis inhibitor, is approved for the treatment of advanced renal cell carcinoma (RCC). Response to pazopanib monotherapy varies between patients, and no validated biomarkers predictive of treatment outcome have been identified. We tested the hypothesis that this variability is partially dependent on germline genetic variants that may affect pazopanib exposure or angiogenesis pathways. PATIENTS AND METHODS: Twenty-seven functional polymorphisms within 13 genes were evaluated in 397 patients with RCC. Genetic association with progression-free survival (PFS) and objective response rate (RR) was analyzed using the Cox proportional hazards model and proportional odds model, respectively. RESULTS: Three polymorphisms in IL8 and HIF1A and five polymorphisms in HIF1A, NR1I2, and VEGFA showed nominally significant association (P ≤ .05) with PFS and RR, respectively. Compared with the wild-type AA genotype (median PFS, 48 weeks), the IL8 2767TT variant genotype showed inferior PFS (27 weeks, P = .009). The HIF1A 1790AG genotype was associated with inferior PFS and reduced RR, compared with the wild-type GG genotype (median PFS, 20 v 44 weeks; P = .03; RR, 30% v 43%, P = .02). Reductions in RR were detected for the NR1I2 -25385TT genotype, compared with the wild-type CC genotype (37% v 50%, P = .03), and for the VEGFA -1498CC genotype compared with the TT genotypes (33% v 51%). CONCLUSION: Germline variants in angiogenesis- and exposure-related genes may predict treatment response to pazopanib monotherapy in patients with RCC. If validated, these markers may explain why certain patients fail antiangiogenesis therapy and they may support the use of alternative strategies to circumvent this issue.

HLA-DQA1*02:01 is a major risk factor for lapatinib-induced hepatotoxicity in women with advanced breast cancer.

PURPOSE: Hepatobiliary adverse events (AEs) have been observed in a small proportion of patients with metastatic breast cancer (MBC) treated with lapatinib. This study sought to identify gene variants associated with lapatinib-induced ALT elevation and hepatobiliary AEs. PATIENTS AND METHODS: A two-stage pharmacogenetic investigation of ALT elevation was conducted in lapatinib-treated patients with MBC. Exploratory marker identification evaluated classical HLA alleles, candidate genes, and genome-wide screening in 37 cases with ALT greater than 3 times the upper limit of normal (ULN) and 286 controls with ALT ≤ 1× ULN, selected from 901 lapatinib-treated patients in 12 trials. Markers achieving prespecified association thresholds were progressed to an independent confirmatory data set of 24 ALT cases and 155 controls selected from a subsequent trial of 374 lapatinib-treated patients. RESULTS: Of 58 variants associated with ALT elevation in the exploratory data set, four exceeded the prespecified significance threshold in the confirmatory analysis. These variants reside in the same MHC genomic locus and include HLA-DQA1*02:01. In the confirmatory study, DQA1*02:01 allele carriage was present in 71% of ALT cases and in 21% of controls (P < .001; odds ratio, 9.0; 95% CI, 3.2 to 27.4). As a predictor of liver safety risk in ALT cases versus noncases, DQA1*02:01 had negative and positive predictive values of 0.97 (95% CI, 0.95 to 0.99) and 0.17 (95% CI 0.10 to 0.26), respectively. CONCLUSION: These results support a role for immune mechanisms in lapatinib-induced hepatotoxicity. Further work is required to determine whether testing for DQA1*02:01 allele carriage is clinically useful in managing liver safety risk during lapatinib treatment.

Association of the hemochromatosis gene with pazopanib-induced transaminase elevation in renal cell carcinoma.

BACKGROUND & AIMS: Pazopanib has demonstrated clinical benefit in patients with advanced renal cell carcinoma (RCC) and is generally well tolerated. However, transaminase elevations have commonly been observed. This 2-stage study sought to identify genetic determinants of alanine transaminase (ALT) elevations in pazopanib-treated white patients with RCC. METHODS: Data from two separate clinical studies were used to examine the association of genetic polymorphisms with maximum on-treatment ALT levels. RESULTS: Of 6852 polymorphisms in 282 candidate genes examined in an exploratory dataset of 115 patients, 92 polymorphisms in 40 genes were significantly associated with ALT elevation (p<0.01). Two markers (rs2858996 and rs707889) in the HFE gene, which are not yet known to be associated with hemochromatosis, showed evidence for replication. Because of multiple comparisons, there was a 12% likelihood the replication occurred by chance. These two markers demonstrated strong linkage disequilibrium (r(2)=0.99). In the combined dataset, median (25-75th percentile) maximum ALT values were 1.2 (0.7-1.9), 1.1 (0.8-2.5), and 5.4 (1.9-7.6)×ULN for rs2858996 GG (n=148), GT (n=82), and TT (n=1 2) genotypes, respectively. All 12 TT patients had a maximum ALT>ULN, and 8 (67%) had ALT≥3×ULN. The odds ratio (95% CI) for ALT≥3×ULN for TT genotype was 39.7 (2.2-703.7) compared with other genotypes. As a predictor of ALT≥3×ULN, the TT genotype had a negative predictive value of 0.83 and positive predictive value of 0.67. No TT patients developed liver failure. CONCLUSIONS: The rs2858996/rs707889 polymorphisms in the HFE gene may be associated with reversible ALT elevation in pazo-panib-treated patients with RCC.

Genome-wide linkage and association analyses to identify genes influencing adiponectin levels: the GEMS Study.

Adiponectin has a variety of metabolic effects on obesity, insulin sensitivity, and atherosclerosis. To identify genes influencing variation in plasma adiponectin levels, we performed genome-wide linkage and association scans of adiponectin in two cohorts of subjects recruited in the Genetic Epidemiology of Metabolic Syndrome Study. The genome-wide linkage scan was conducted in families of Turkish and southern European (TSE, n = 789) and Northern and Western European (NWE, N = 2,280) origin. A whole genome association (WGA) analysis (500K Affymetrix platform) was carried out in a set of unrelated NWE subjects consisting of approximately 1,000 subjects with dyslipidemia and 1,000 overweight subjects with normal lipids. Peak evidence for linkage occurred at chromosome 8p23 in NWE subjects (lod = 3.10) and at chromosome 3q28 near ADIPOQ, the adiponectin structural gene, in TSE subjects (lod = 1.70). In the WGA analysis, the single-nucleotide polymorphisms (SNPs) most strongly associated with adiponectin were rs3774261 and rs6773957 (P < 10(-7)). These two SNPs were in high linkage disequilibrium (r(2) = 0.98) and located within ADIPOQ. Interestingly, our fourth strongest region of association (P < 2 x 10(-5)) was to an SNP within CDH13, whose protein product is a newly identified receptor for high-molecular-weight species of adiponectin. Through WGA analysis, we confirmed previous studies showing SNPs within ADIPOQ to be strongly associated with variation in adiponectin levels and further observed these to have the strongest effects on adiponectin levels throughout the genome. We additionally identified a second gene (CDH13) possibly influencing variation in adiponectin levels. The impact of these SNPs on health and disease has yet to be determined.