A biallelic multiple nucleotide length polymorphism explains functional causality at 5p15.33 prostate cancer risk locus.

To date, single-nucleotide polymorphisms (SNPs) have been the most intensively investigated class of polymorphisms in genome wide associations studies (GWAS), however, other classes such as insertion-deletion or multiple nucleotide length polymorphism (MNLPs) may also confer disease risk. Multiple reports have shown that the 5p15.33 prostate cancer risk region is a particularly strong expression quantitative trait locus (eQTL) for Iroquois Homeobox 4 (IRX4) transcripts. Here, we demonstrate using epigenome and genome editing that a biallelic (21 and 47 base pairs (bp)) MNLP is the causal variant regulating IRX4 transcript levels. In LNCaP prostate cancer cells (homozygous for the 21 bp short allele), a single copy knock-in of the 47 bp long allele potently alters the chromatin state, enabling de novo functional binding of the androgen receptor (AR) associated with increased chromatin accessibility, Histone 3 lysine 27 acetylation (H3K27ac), and ~3-fold upregulation of IRX4 expression. We further show that an MNLP is amongst the strongest candidate susceptibility variants at two additional prostate cancer risk loci. We estimated that at least 5% of prostate cancer risk loci could be explained by functional non-SNP causal variants, which may have broader implications for other cancers GWAS. More generally, our results underscore the importance of investigating other classes of inherited variation as causal mediators of human traits.

A Meta-Analysis and Cohort Study of Histopathologic and Clinical Outcomes in ANCA-Negative versus -Positive Vasculitis.

BACKGROUND: ANCA-negative pauci-immune glomerulonephritis (PIGN) represents a rare and often under-studied subgroup of the vasculitides. This study aims to investigate differences in the clinical phenotype, renal histological features, and clinical outcomes of patients with PIGN, with and without serum ANCA positivity. METHODS: A cohort of biopsy-proven PIGN with and without detectable circulating ANCA was constructed from a single center between 2006 and 2016. Primary outcomes compared clinical presentation and histopathological features according to ANCA status, with multivariate Cox regression to compare mortality and ESKD. A systematic review and meta-analysis of the published literature was undertaken. RESULTS: In our cohort of 146 patients, 22% (n=32) had ANCA-negative disease, with a comparatively younger mean age at diagnosis; 51.4 versus 65.6 years (P<0.001). In total, 14 studies, inclusive of our cohort, were eligible for meta-analysis, totaling 301 patients who were ANCA negative. Those with ANCA-negative disease tended to have fewer extrarenal symptoms and a higher frequency of renal-limited disease, but both failed to reach statistical significance (P=0.92 and P=0.07). The risk of ESKD was significantly higher in seronegative disease (RR, 2.28; 95% confidence interval, 1.42 to 3.65; P<0.001), reflecting our experience, with a fivefold increased risk of ESKD in ANCA-negative disease (P<0.001). No significant difference in the chronicity of histopathological findings was seen and the meta-analysis showed no difference in morality (RR, 1.22; 95% confidence interval, 0.63 to 2.38; P=0.55). CONCLUSION: Our findings demonstrate that ANCA-negative PIGN presents in younger patients, with fewer extrarenal manifestations and higher ESKD risk, despite a lack of difference in histopathology. This study provides the impetus for further research into the pathogenesis, treatment response, and duration of immunotherapy in ANCA-negative disease. We suggest that the absence of positive ANCA serology should not discourage treatment and for clinical trials to include patients who are ANCA negative.

chromMAGMA: regulatory element-centric interrogation of risk variants.

Candidate causal risk variants from genome-wide association studies reside almost exclusively in noncoding regions of the genome and innovative approaches are necessary to understand their biological function. Multi-marker analysis of genomic annotation (MAGMA) is a widely used program that nominates candidate risk genes by mapping single-nucleotide polymorphism summary statistics from genome-wide association studies to gene bodies. We augmented MAGMA to create chromatin-MAGMA (chromMAGMA), a method to nominate candidate risk genes based on the presence of risk variants within noncoding regulatory elements (REs). We applied chromMAGMA to a genetic susceptibility dataset for epithelial ovarian cancer (EOC), a rare gynecologic malignancy characterized by high mortality. This identified 155 unique candidate EOC risk genes across five EOC histotypes; 83% (105/127) of high-grade serous ovarian cancer risk genes had not previously been implicated in this EOC histotype. Risk genes nominated by chromMAGMA converged on mRNA splicing and transcriptional dysregulation pathways. chromMAGMA is a pipeline that nominates candidate risk genes through a gene regulation-focused approach and helps interpret the biological mechanism of noncoding risk variants for complex diseases.

Allele-specific epigenetic activity in prostate cancer and normal prostate tissue implicates prostate cancer risk mechanisms.

Genome-wide association studies (GWASs) of prostate cancer have identified >250 significant risk loci, but the causal variants and mechanisms for these loci remain largely unknown. Here, we sought to identify and characterize risk-harboring regulatory elements by integrating epigenomes from primary prostate tumor and normal tissues of 27 individuals across the H3K27ac, H3K4me3, and H3K4me2 histone marks and FOXA1 and HOXB13 transcription factors. We identified 7,371 peaks with significant allele specificity (allele-specific quantitative trait locus [asQTL] peaks). Showcasing their relevance to prostate cancer risk, H3K27ac T-asQTL peaks were the single annotation most enriched for prostate cancer GWAS heritability (40×), significantly higher than corresponding non-asQTL H3K27ac peaks (14×) or coding regions (14×). Surprisingly, fine-mapped GWAS risk variants were most significantly enriched for asQTL peaks observed in tumors, including asQTL peaks that were differentially imbalanced with respect to tumor-normal states. These data pinpointed putative causal regulatory elements at 20 GWAS loci, of which 11 were detected only in the tumor samples. More broadly, tumor-specific asQTLs were enriched for expression QTLs in benign tissues as well as accessible regions found in stem cells, supporting a hypothesis where some germline variants become reactivated during or after transformation and can be captured by epigenomic profiling of the tumor. Our study demonstrates the power of allele specificity in chromatin signals to uncover GWAS mechanisms, highlights the relevance of tumor-specific regulation in the context of cancer risk, and prioritizes multiple loci for experimental follow-up.

Allele-Specific QTL Fine Mapping with PLASMA.

Although quantitative trait locus (QTL) associations have been identified for many molecular traits such as gene expression, it remains challenging to distinguish the causal nucleotide from nearby variants. In addition to traditional QTLs by association, allele-specific (AS) QTLs are a powerful measure of cis-regulation that are concordant with traditional QTLs but typically less susceptible to technical/environmental noise. However, existing methods for estimating causal variant probabilities (i.e., fine mapping) cannot produce valid estimates from asQTL signals due to complexities in linkage disequilibrium (LD). We introduce PLASMA (Population Allele-Specific Mapping), a fine-mapping method that integrates QTL and asQTL information to improve accuracy. In simulations, PLASMA accurately prioritizes causal variants over a wide range of genetic architectures. Applied to RNA-seq data from 524 kidney tumor samples, PLASMA achieves a greater power at 50 samples than conventional QTL-based fine mapping at 500 samples, with more than 17% of loci fine mapped to within five causal variants, compared to 2% by QTL-based fine mapping, and a 6.9-fold overall reduction in median credible set size compared to QTL-based fine mapping when applied to H3K27AC ChIP-seq from just 28 prostate tumor/normal samples. Variants in the PLASMA credible sets for RNA-seq and ChIP-seq were enriched for open chromatin and chromatin looping, respectively, at a comparable or greater degree than credible variants from existing methods while containing far fewer markers. Our results demonstrate how integrating AS activity can substantially improve the detection of causal variants from existing molecular data.

Genome-wide germline correlates of the epigenetic landscape of prostate cancer.

Oncogenesis is driven by germline, environmental and stochastic factors. It is unknown how these interact to produce the molecular phenotypes of tumors. We therefore quantified the influence of germline polymorphisms on the somatic epigenome of 589 localized prostate tumors. Predisposition risk loci influence a tumor's epigenome, uncovering a mechanism for cancer susceptibility. We identified and validated 1,178 loci associated with altered methylation in tumoral but not nonmalignant tissue. These tumor methylation quantitative trait loci influence chromatin structure, as well as RNA and protein abundance. One prominent tumor methylation quantitative trait locus is associated with AKT1 expression and is predictive of relapse after definitive local therapy in both discovery and validation cohorts. These data reveal intricate crosstalk between the germ line and the epigenome of primary tumors, which may help identify germline biomarkers of aggressive disease to aid patient triage and optimize the use of more invasive or expensive diagnostic assays.