Risk SNP-Mediated Promoter-Enhancer Switching Drives Prostate Cancer through lncRNA PCAT19.

The prostate cancer (PCa) risk-associated SNP rs11672691 is positively associated with aggressive disease at diagnosis. We showed that rs11672691 maps to the promoter of a short isoform of long noncoding RNA PCAT19 (PCAT19-short), which is in the third intron of the long isoform (PCAT19-long). The risk variant is associated with decreased and increased levels of PCAT19-short and PCAT19-long, respectively. Mechanistically, the risk SNP region is bifunctional with both promoter and enhancer activity. The risk variants of rs11672691 and its LD SNP rs887391 decrease binding of transcription factors NKX3.1 and YY1 to the promoter of PCAT19-short, resulting in weaker promoter but stronger enhancer activity that subsequently activates PCAT19-long. PCAT19-long interacts with HNRNPAB to activate a subset of cell-cycle genes associated with PCa progression, thereby promoting PCa tumor growth and metastasis. Taken together, these findings reveal a risk SNP-mediated promoter-enhancer switching mechanism underlying both initiation and progression of aggressive PCa.

Polygenic risk for prostate cancer: Decreasing relative risk with age but little impact on absolute risk.

Polygenic risk scores (PRSs) for a variety of diseases have recently been shown to have relative risks that depend on age, and genetic relative risks decrease with increasing age. A refined understanding of the age dependency of PRSs for a disease is important for personalized risk predictions and risk stratification. To further evaluate how the PRS relative risk for prostate cancer depends on age, we refined analyses for a validated PRS for prostate cancer by using 64,274 prostate cancer cases and 46,432 controls of diverse ancestry (82.8% European, 9.8% African American, 3.8% Latino, 2.8% Asian, and 0.8% Ghanaian). Our strategy applied a novel weighted proportional hazards model to case-control data to fully utilize age to refine how the relative risk decreased with age. We found significantly greater relative risks for younger men (age 30-55 years) compared with older men (70-88 years) for both relative risk per standard deviation of the PRS and dichotomized according to the upper 90th percentile of the PRS distribution. For the largest European ancestral group that could provide reliable resolution, the log-relative risk decreased approximately linearly from age 50 to age 75. Despite strong evidence of age-dependent genetic relative risk, our results suggest that absolute risk predictions differed little from predictions that assumed a constant relative risk over ages, from short-term to long-term predictions, simplifying implementation of risk discussions into clinical practice.

Frailty screening for determination of hemodialysis access placement.

OBJECTIVE: Choosing the right hemodialysis vascular access for frail patients remains difficult because the patient's preferences and the likelihood of access function and survival must be considered. We hypothesize that patients identified before arteriovenous (AV) access as frail by the PRISMA-7 score may have worse outcomes, indicating that fistula creation may not be the most clinically beneficial option and it would be in the best interest of the patient to receive either AV graft (AVG) placement or dialysis through a percutaneous catheter. Our pilot study aims to determine whether an association exists between patient frailty as defined by PRISMA-7 and newly created AV fistula (AVF) and AVG access outcomes. METHODS: This was a single institutional prospective cohort study of patients undergoing new AVF or AVG intervention from April 2021 to May 2023. Patients were assessed using the PRISMA-7 frailty questionnaire before their AV access surgery. Patients were grouped by frailty score and score groups were examined for trends. Univariable analysis was performed for baseline differences between frail and nonfrail patients. Failure to achieve maturation, postoperative infection, and 180-day mortality difference was also investigated for frail vs nonfrail patients. Univariable analysis was performed for nonmaturation using standard comorbidities, arterial and venous diameters, and frailty. Multivariable binary logistic regression was performed for the outcome of nonmaturation using frailty as one of the variables in conjunction with the univariable risks associated with nonmaturation. RESULTS: A total of 40 patients undergoing new AV access placement were investigated, among whom 53% were designated as frail (PRISMA-7 score ≥3). When comparing the frail and nonfrail new AV access groups, the access (AVF and AVG combined) failed in 48% (10/21) of the frail patients, but only failed in 5% (1/19) of the nonfrail patients 1 (P = .012). When distinguishing between AV access types, AVF creations followed the overall trend with 60% of AVF access (9/15) sites in frail patients failing to mature when compared with nonfrail patients, who all had fistulas that matured to use (P = .049). Surgical site infection was absent in all frail patients and present in 5% of nonfrail patients (1/19). Both 30-day and 60-day readmission rates were higher in the frail group compared with the nonfrail group. There was 180-day mortality present in 5 of frail patients % (1/21) and absent in nonfrail patients. Multivariable analysis revealed that both frailty (adjusted odd ratio, 10.19; 95% confidence interval, 1.20-82.25); P = .033) and younger age (adjusted odd ratio, 0.953; 95% confidence interval, 0.923-0.983; P = .002) both had a significant association with nonmaturation. Power analysis revealed a power statistic of 0.898 indicating a probability of type 2 error of 10.02% with a P value of .002. Hosmer-Lemeshow goodness of fit for the logistic regression had 75% overall accuracy for the model. CONCLUSIONS: Patient frailty is significantly associated with an increased incidence of AV access failure to mature.

Investigation of center-specific saphenous vein utilization rates in femoral popliteal artery bypass and associated impact of conduit on outcomes.

OBJECTIVE: The purpose of this study is to investigate variation in great saphenous vein (GSV) use among the various centers participating in the Vascular Quality Initiative infrainguinal bypass modules. Further, differences in outcomes in femoral-popliteal artery bypass with single segment GSV conduit vs prosthetic conduit will be documented. Center GSV use rate impact on outcomes will be investigated. METHODS: Primary exclusions were patients undergoing redo bypass, urgent or emergent bypass, and those in whom prosthetic graft was used while having undergone prior coronary artery bypass grafting. The distribution of GSV use across the 260 centers participating in Vascular Quality Initiative infrainguinal bypass module was placed into histogram and variance in mean GSV use evaluated with analysis of variance analysis. Centers that used GSV in >50% of bypasses were categorized as high use centers and centers that used the GSV in <30% of cases were categorized as low use centers. Baseline differences in patient characteristics and comorbidities in those undergoing bypass with GSV vs prosthetic conduit were analyzed with χ2 testing and the Student t test, as were those undergoing treatment in high vs low use centers. Multivariable time-dependent Cox regression analyses were then performed for the primary outcomes of major amputation ipsilateral to the operative side and mortality in long-term follow-up. High vs low use center was a dichotomous variable in these regressions. Secondary outcomes of freedom from graft infection and freedom from loss of primary patency were performed with Kaplan-Meier analysis. RESULTS: Among centers with >50 patients meeting inclusion criteria for this study, GSV use ranged from 15% to 93% (analysis of variance P < .001). When considering all centers irrespective of number of patients, the range was 0% to 100%. On Kaplan-Meier analysis, GSV conduit use was associated with improved freedom from loss of primary or primary assisted patency, improved freedom from major amputation after index hospitalization, improved freedom from graft infection after the index hospitalization, and improved freedom from mortality in long-term follow-up (log-rank P < .001 for all four outcomes). Both low use center (hazard ratio, 1.35; P < .001) and prosthetic graft use (hazard ratio, 1.24; P < .001) achieved multivariable significance as risks for mortality in long-term follow-up. Other variables with a multivariable mortality association are presented in the manuscript. Low use center and prosthetic bypass were significant univariable but not multivariable risks for major amputation after index hospitalization. CONCLUSIONS: There is remarkably wide variation in GSV use for femoral popliteal artery bypass among various medical centers. GSV use is associated with enhanced long-term survival as well as freedom from loss of bypass patency and graft infection. The data herein indicate institutional patterns of prosthetic conduit choice, which has the potential to be altered to enhance outcomes.

Health care disparities involved in establishing functional arteriovenous fistula hemodialysis access.

OBJECTIVE: Race-related disparities in outcomes associated with cardiovascular disease are well-documented. Arteriovenous fistula (AVF) maturation can be a challenge in establishing functional access in the population of patients with end-stage renal disease requiring hemodialysis. We sought to investigate the incidence of adjunctive procedures required to establish fistula maturation and evaluate the association with demographic factors including patient race. METHODS: This study was a single-institution retrospective review of patients undergoing first-time AVF creation for hemodialysis from January 1, 2007, to December 31, 2021. Subsequent arteriovenous access interventions, such as percutaneous angioplasty, fistula superficialization, branch ligation and embolization, surgical revision, and thrombectomy, were recorded. The total number of interventions performed after index operation was recorded. Demographic data including age, sex, race, and ethnicity was recorded. The need for and number of subsequent interventions was evaluated using multivariable analysis. RESULTS: A total of 669 patients were included in this study. Patients were 60.8% male and 39.2% female. Race was reported as White in 329 (49.2%), Black in 211 (31.5%), Asian in 27 (4.0%), and other/unknown in 102 (15.3%). Of the patients, 355 (53.1%) underwent no additional procedures after initial AVF creation, 188 (28.1%) underwent one additional procedure, 73 (10.9%) had two additional procedures, and 53 (7.9%) had three or more additional procedures. As compared with the White reference group, Black patients were at higher risk of having maintenance interventions (relative risk [RR], 1.900; P ≤ .0001) and additional AVF creation interventions (RR, 1.332; P = .05), and total interventions (RR, 1.551; P ≤ .0001). CONCLUSIONS: Black patients were at significantly higher risk of undergoing additional surgical procedures, including both maintenance and new fistula creations, as compared with their counterparts of other racial groups. Further exploration of the root cause of these disparities is necessary to facilitate the achievement of equivalent high-quality outcomes across racial groups.

Familial recurrence risk with varying amount of family history.

The familial recurrence risk is the probability a person will have disease, given a reported family history. When family histories are obtained as simple counts of disease among family members, as often obtained in cancer registries or surveys, we propose methods to estimate recurrence risks based on truncated binomial distributions. By this approach, we are able to obtain unbiased estimates of risk for a person with at least k-affected relatives, where k can be specified to determine how risk varies with k. We also derive robust variances of the recurrence risk estimate, to account for correlations within families, such as those induced by shared genes or shared environment, without explicitly modeling the factors that cause familial correlations. Furthermore, we illustrate how mixture models can be used to account for a sample composed of low- and high-risk families. Using simulations, we illustrate the properties of the proposed methods. Application of our methods to a family history survey of prostate cancer shows that the recurrence risk for prostate cancer increased from 16%, when there was at least one affected relative, to 52%, when there was at least five affected relatives.

A pilot study using environmental screening to determine the prevalence of Mycobacterium avium subspecies paratuberculosis (MAP) and antimicrobial resistance (AMR) in Irish cattle herds.

BACKGROUND: Dairy and beef cattle can be reservoirs of many pathogens, including Salmonella and Mycobacterium avium subsp. paratuberculosis (MAP), the causative agent of Johne's disease (JD). Farm environments may provide potential entry points for the transmission of infectious agents into the food chain. Antibiotics are used to treat a wide variety of infections on farms, and administration of antimicrobial agents to cattle is considered to be a driving factor for antimicrobial resistance (AMR). Control of JD and AMR are priority for animal health initiatives in Ireland. A national JD pilot programme was introduced by Animal Health Ireland in 2014, while the national action plan launched by Department of Health and Department of Agriculture, Food and Marine introduced in 2017 aims to improve the surveillance of AMR. The current investigation was undertaken as a pilot study to determine the proportion of herds positive for MAP, Salmonella species (Salmonella spp), commensal Escherichia coli (E. coli), Extended-spectrum beta-lactamase (ESBL) AmpC ß-lactamase and carbapenemase-producing E. coli from 157 environmental faecal samples in Irish farms. RESULTS: MAP was detected in 10.2% of samples collected; on culture in 4 (4.9%) of the dairy herds and from 1 (1.3%) of the beef/suckler herds, and by PCR in 10 (12.3%) and 6 (7.9%) of these herds respectively. All culture positive herds were also positive by PCR. An additional 11 herds were positive by PCR only. Salmonella was not detected, while commensal E. coli were isolated from 70.7% of the samples (111/157) with 101 of these isolates shown to be fully susceptible to all antimicrobials tested. Of the 27 presumptive ESBL AmpC ß-lactamase producing E. coli detected, one isolate was resistant to ten antimicrobials, nine isolates were resistant to nine antimicrobials, and four isolates were resistant to eight antimicrobials. Carbapenemase-producing E. coli were not isolated. CONCLUSIONS: The results highlight the importance of monitoring farm environments for Johne's disease. This disease is a growing concern for dairy and beef producers in Ireland, and sampling the farm environment may offer a useful means to rapidly screen for the presence of MAP. Non-pathogenic common enteric commensal and multiple-drug-resistant E. coli may contribute to AMR acting as a reservoir and transferring resistance to other species/pathogens in the environment.

REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants.

The vast majority of coding variants are rare, and assessment of the contribution of rare variants to complex traits is hampered by low statistical power and limited functional data. Improved methods for predicting the pathogenicity of rare coding variants are needed to facilitate the discovery of disease variants from exome sequencing studies. We developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, MutationTaster, LRT, GERP, SiPhy, phyloP, and phastCons. REVEL was trained with recently discovered pathogenic and rare neutral missense variants, excluding those previously used to train its constituent tools. When applied to two independent test sets, REVEL had the best overall performance (p < 10-12) as compared to any individual tool and seven ensemble methods: MetaSVM, MetaLR, KGGSeq, Condel, CADD, DANN, and Eigen. Importantly, REVEL also had the best performance for distinguishing pathogenic from rare neutral variants with allele frequencies <0.5%. The area under the receiver operating characteristic curve (AUC) for REVEL was 0.046-0.182 higher in an independent test set of 935 recent SwissVar disease variants and 123,935 putatively neutral exome sequencing variants and 0.027-0.143 higher in an independent test set of 1,953 pathogenic and 2,406 benign variants recently reported in ClinVar than the AUCs for other ensemble methods. We provide pre-computed REVEL scores for all possible human missense variants to facilitate the identification of pathogenic variants in the sea of rare variants discovered as sequencing studies expand in scale.

Genome-wide analyses as part of the international FTLD-TDP whole-genome sequencing consortium reveals novel disease risk factors and increases support for immune dysfunction in FTLD.

Frontotemporal lobar degeneration with neuronal inclusions of the TAR DNA-binding protein 43 (FTLD-TDP) represents the most common pathological subtype of FTLD. We established the international FTLD-TDP whole-genome sequencing consortium to thoroughly characterize the known genetic causes of FTLD-TDP and identify novel genetic risk factors. Through the study of 1131 unrelated Caucasian patients, we estimated that C9orf72 repeat expansions and GRN loss-of-function mutations account for 25.5% and 13.9% of FTLD-TDP patients, respectively. Mutations in TBK1 (1.5%) and other known FTLD genes (1.4%) were rare, and the disease in 57.7% of FTLD-TDP patients was unexplained by the known FTLD genes. To unravel the contribution of common genetic factors to the FTLD-TDP etiology in these patients, we conducted a two-stage association study comprising the analysis of whole-genome sequencing data from 517 FTLD-TDP patients and 838 controls, followed by targeted genotyping of the most associated genomic loci in 119 additional FTLD-TDP patients and 1653 controls. We identified three genome-wide significant FTLD-TDP risk loci: one new locus at chromosome 7q36 within the DPP6 gene led by rs118113626 (p value = 4.82e - 08, OR = 2.12), and two known loci: UNC13A, led by rs1297319 (p value = 1.27e - 08, OR = 1.50) and HLA-DQA2 led by rs17219281 (p value = 3.22e - 08, OR = 1.98). While HLA represents a locus previously implicated in clinical FTLD and related neurodegenerative disorders, the association signal in our study is independent from previously reported associations. Through inspection of our whole-genome sequence data for genes with an excess of rare loss-of-function variants in FTLD-TDP patients (n ≥ 3) as compared to controls (n = 0), we further discovered a possible role for genes functioning within the TBK1-related immune pathway (e.g., DHX58, TRIM21, IRF7) in the genetic etiology of FTLD-TDP. Together, our study based on the largest cohort of unrelated FTLD-TDP patients assembled to date provides a comprehensive view of the genetic landscape of FTLD-TDP, nominates novel FTLD-TDP risk loci, and strongly implicates the immune pathway in FTLD-TDP pathogenesis.

Identification of missing variants by combining multiple analytic pipelines.

BACKGROUND: After decades of identifying risk factors using array-based genome-wide association studies (GWAS), genetic research of complex diseases has shifted to sequencing-based rare variants discovery. This requires large sample sizes for statistical power and has brought up questions about whether the current variant calling practices are adequate for large cohorts. It is well-known that there are discrepancies between variants called by different pipelines, and that using a single pipeline always misses true variants exclusively identifiable by other pipelines. Nonetheless, it is common practice today to call variants by one pipeline due to computational cost and assume that false negative calls are a small percent of total. RESULTS: We analyzed 10,000 exomes from the Alzheimer's Disease Sequencing Project (ADSP) using multiple analytic pipelines consisting of different read aligners and variant calling strategies. We compared variants identified by using two aligners in 50,100, 200, 500, 1000, and 1952 samples; and compared variants identified by adding single-sample genotyping to the default multi-sample joint genotyping in 50,100, 500, 2000, 5000 and 10,000 samples. We found that using a single pipeline missed increasing numbers of high-quality variants correlated with sample sizes. By combining two read aligners and two variant calling strategies, we rescued 30% of pass-QC variants at sample size of 2000, and 56% at 10,000 samples. The rescued variants had higher proportions of low frequency (minor allele frequency [MAF] 1-5%) and rare (MAF < 1%) variants, which are the very type of variants of interest. In 660 Alzheimer's disease cases with earlier onset ages of ≤65, 4 out of 13 (31%) previously-published rare pathogenic and protective mutations in APP, PSEN1, and PSEN2 genes were undetected by the default one-pipeline approach but recovered by the multi-pipeline approach. CONCLUSIONS: Identification of the complete variant set from sequencing data is the prerequisite of genetic association analyses. The current analytic practice of calling genetic variants from sequencing data using a single bioinformatics pipeline is no longer adequate with the increasingly large projects. The number and percentage of quality variants that passed quality filters but are missed by the one-pipeline approach rapidly increased with sample size.

gsSKAT: Rapid gene set analysis and multiple testing correction for rare-variant association studies using weighted linear kernels.

Next-generation sequencing technologies have afforded unprecedented characterization of low-frequency and rare genetic variation. Due to low power for single-variant testing, aggregative methods are commonly used to combine observed rare variation within a single gene. Causal variation may also aggregate across multiple genes within relevant biomolecular pathways. Kernel-machine regression and adaptive testing methods for aggregative rare-variant association testing have been demonstrated to be powerful approaches for pathway-level analysis, although these methods tend to be computationally intensive at high-variant dimensionality and require access to complete data. An additional analytical issue in scans of large pathway definition sets is multiple testing correction. Gene set definitions may exhibit substantial genic overlap, and the impact of the resultant correlation in test statistics on Type I error rate control for large agnostic gene set scans has not been fully explored. Herein, we first outline a statistical strategy for aggregative rare-variant analysis using component gene-level linear kernel score test summary statistics as well as derive simple estimators of the effective number of tests for family-wise error rate control. We then conduct extensive simulation studies to characterize the behavior of our approach relative to direct application of kernel and adaptive methods under a variety of conditions. We also apply our method to two case-control studies, respectively, evaluating rare variation in hereditary prostate cancer and schizophrenia. Finally, we provide open-source R code for public use to facilitate easy application of our methods to existing rare-variant analysis results.

Comprehensively evaluating cis-regulatory variation in the human prostate transcriptome by using gene-level allele-specific expression.

The identification of cis-acting regulatory variation in primary tissues has the potential to elucidate the genetic basis of complex traits and further our understanding of transcriptomic diversity across cell types. Expression quantitative trait locus (eQTL) association analysis using RNA sequencing (RNA-seq) data can improve upon the detection of cis-acting regulatory variation by leveraging allele-specific expression (ASE) patterns in association analysis. Here, we present a comprehensive evaluation of cis-acting eQTLs by analyzing RNA-seq gene-expression data and genome-wide high-density genotypes from 471 samples of normal primary prostate tissue. Using statistical models that integrate ASE information, we identified extensive cis-eQTLs across the prostate transcriptome and found that approximately 70% of expressed genes corresponded to a significant eQTL at a gene-level false-discovery rate of 0.05. Overall, cis-eQTLs were heavily concentrated near the transcription start and stop sites of affected genes, and effects were negatively correlated with distance. We identified multiple instances of cis-acting co-regulation by using phased genotype data and discovered 233 SNPs as the most strongly associated eQTLs for more than one gene. We also noted significant enrichment (25/50, p = 2E-5) of previously reported prostate cancer risk SNPs in prostate eQTLs. Our results illustrate the benefit of assessing ASE data in cis-eQTL analyses by showing better reproducibility of prior eQTL findings than of eQTL mapping based on total expression alone. Altogether, our analysis provides extensive functional context of thousands of SNPs in prostate tissue, and these results will be of critical value in guiding studies examining disease of the human prostate.

FIRE: functional inference of genetic variants that regulate gene expression.

MOTIVATION: Interpreting genetic variation in noncoding regions of the genome is an important challenge for personal genome analysis. One mechanism by which noncoding single nucleotide variants (SNVs) influence downstream phenotypes is through the regulation of gene expression. Methods to predict whether or not individual SNVs are likely to regulate gene expression would aid interpretation of variants of unknown significance identified in whole-genome sequencing studies. RESULTS: We developed FIRE (Functional Inference of Regulators of Expression), a tool to score both noncoding and coding SNVs based on their potential to regulate the expression levels of nearby genes. FIRE consists of 23 random forests trained to recognize SNVs in cis-expression quantitative trait loci (cis-eQTLs) using a set of 92 genomic annotations as predictive features. FIRE scores discriminate cis-eQTL SNVs from non-eQTL SNVs in the training set with a cross-validated area under the receiver operating characteristic curve (AUC) of 0.807, and discriminate cis-eQTL SNVs shared across six populations of different ancestry from non-eQTL SNVs with an AUC of 0.939. FIRE scores are also predictive of cis-eQTL SNVs across a variety of tissue types. AVAILABILITY AND IMPLEMENTATION: FIRE scores for genome-wide SNVs in hg19/GRCh37 are available for download at https://sites.google.com/site/fireregulatoryvariation/. CONTACT: nilah@stanford.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Germline miRNA DNA variants and the risk of colorectal cancer by subtype.

MicroRNAs (miRNAs) regulate up to one-third of all protein-coding genes including genes relevant to cancer. Variants within miRNAs have been reported to be associated with prognosis, survival, response to chemotherapy across cancer types, in vitro parameters of cell growth, and altered risks for development of cancer. Five miRNA variants have been reported to be associated with risk for development of colorectal cancer (CRC). In this study, we evaluated germline genetic variation in 1,123 miRNAs in 899 individuals with CRCs categorized by clinical subtypes and in 204 controls. The role of common miRNA variation in CRC was investigated using single variant and miRNA-level association tests. Twenty-nine miRNAs and 30 variants exhibited some marginal association with CRC in at least one subtype of CRC. Previously reported associations were not confirmed (n = 4) or could not be evaluated (n = 1). The variants noted for the CRCs with deficient mismatch repair showed little overlap with the variants noted for CRCs with proficient mismatch repair, consistent with our evolving understanding of the distinct biology underlying these two groups. © 2016 The Authors Genes, Chromosomes & Cancer Published by Wiley Periodicals, Inc.

Post hoc Analysis for Detecting Individual Rare Variant Risk Associations Using Probit Regression Bayesian Variable Selection Methods in Case-Control Sequencing Studies.

Rare variants (RVs) have been shown to be significant contributors to complex disease risk. By definition, these variants have very low minor allele frequencies and traditional single-marker methods for statistical analysis are underpowered for typical sequencing study sample sizes. Multimarker burden-type approaches attempt to identify aggregation of RVs across case-control status by analyzing relatively small partitions of the genome, such as genes. However, it is generally the case that the aggregative measure would be a mixture of causal and neutral variants, and these omnibus tests do not directly provide any indication of which RVs may be driving a given association. Recently, Bayesian variable selection approaches have been proposed to identify RV associations from a large set of RVs under consideration. Although these approaches have been shown to be powerful at detecting associations at the RV level, there are often computational limitations on the total quantity of RVs under consideration and compromises are necessary for large-scale application. Here, we propose a computationally efficient alternative formulation of this method using a probit regression approach specifically capable of simultaneously analyzing hundreds to thousands of RVs. We evaluate our approach to detect causal variation on simulated data and examine sensitivity and specificity in instances of high RV dimensionality as well as apply it to pathway-level RV analysis results from a prostate cancer (PC) risk case-control sequencing study. Finally, we discuss potential extensions and future directions of this work.

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans.

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region.

Genome-wide association of familial prostate cancer cases identifies evidence for a rare segregating haplotype at 8q24.21.

Previous genome-wide association studies (GWAS) of prostate cancer risk focused on cases unselected for family history and have reported over 100 significant associations. The International Consortium for Prostate Cancer Genetics (ICPCG) has now performed a GWAS of 2511 (unrelated) familial prostate cancer cases and 1382 unaffected controls from 12 member sites. All samples were genotyped on the Illumina 5M+exome single nucleotide polymorphism (SNP) platform. The GWAS identified a significant evidence for association for SNPs in six regions previously associated with prostate cancer in population-based cohorts, including 3q26.2, 6q25.3, 8q24.21, 10q11.23, 11q13.3, and 17q12. Of note, SNP rs138042437 (p = 1.7e(-8)) at 8q24.21 achieved a large estimated effect size in this cohort (odds ratio = 13.3). 116 previously sampled affected relatives of 62 risk-allele carriers from the GWAS cohort were genotyped for this SNP, identifying 78 additional affected carriers in 62 pedigrees. A test for an excess number of affected carriers among relatives exhibited strong evidence for co-segregation of the variant with disease (p = 8.5e(-11)). The majority (92 %) of risk-allele carriers at rs138042437 had a consistent estimated haplotype spanning approximately 100 kb of 8q24.21 that contained the minor alleles of three rare SNPs (dosage minor allele frequencies <1.7 %), rs183373024 (PRNCR1), previously associated SNP rs188140481, and rs138042437 (CASC19). Strong evidence for co-segregation of a SNP on the haplotype further characterizes the haplotype as a prostate cancer predisposition locus.

Prediction of individual genetic risk to prostate cancer using a polygenic score.

BACKGROUND: Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. METHODS: We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. RESULTS: The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. CONCLUSIONS: Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction.

Associations of prostate cancer risk variants with disease aggressiveness: results of the NCI-SPORE Genetics Working Group analysis of 18,343 cases.

Genetic studies have identified single nucleotide polymorphisms (SNPs) associated with the risk of prostate cancer (PC). It remains unclear whether such genetic variants are associated with disease aggressiveness. The NCI-SPORE Genetics Working Group retrospectively collected clinicopathologic information and genotype data for 36 SNPs which at the time had been validated to be associated with PC risk from 25,674 cases with PC. Cases were grouped according to race, Gleason score (Gleason ≤ 6, 7, ≥ 8) and aggressiveness (non-aggressive, intermediate, and aggressive disease). Statistical analyses were used to compare the frequency of the SNPs between different disease cohorts. After adjusting for multiple testing, only PC-risk SNP rs2735839 (G) was significantly and inversely associated with aggressive (OR = 0.77; 95 % CI 0.69-0.87) and high-grade disease (OR = 0.77; 95 % CI 0.68-0.86) in European men. Similar associations with aggressive (OR = 0.72; 95 % CI 0.58-0.89) and high-grade disease (OR = 0.69; 95 % CI 0.54-0.87) were documented in African-American subjects. The G allele of rs2735839 was associated with disease aggressiveness even at low PSA levels (<4.0 ng/mL) in both European and African-American men. Our results provide further support that a PC-risk SNP rs2735839 near the KLK3 gene on chromosome 19q13 may be associated with aggressive and high-grade PC. Future prospectively designed, case-case GWAS are needed to identify additional SNPs associated with PC aggressiveness.

Multiple genetic variant association testing by collapsing and kernel methods with pedigree or population structured data.

Searching for rare genetic variants associated with complex diseases can be facilitated by enriching for diseased carriers of rare variants by sampling cases from pedigrees enriched for disease, possibly with related or unrelated controls. This strategy, however, complicates analyses because of shared genetic ancestry, as well as linkage disequilibrium among genetic markers. To overcome these problems, we developed broad classes of "burden" statistics and kernel statistics, extending commonly used methods for unrelated case-control data to allow for known pedigree relationships, for autosomes and the X chromosome. Furthermore, by replacing pedigree-based genetic correlation matrices with estimates of genetic relationships based on large-scale genomic data, our methods can be used to account for population-structured data. By simulations, we show that the type I error rates of our developed methods are near the asymptotic nominal levels, allowing rapid computation of P-values. Our simulations also show that a linear weighted kernel statistic is generally more powerful than a weighted "burden" statistic. Because the proposed statistics are rapid to compute, they can be readily used for large-scale screening of the association of genomic sequence data with disease status.