Mitchell J. Machiela

LDlink: a web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants

UNLABELLED Assessing linkage disequilibrium (LD) across ancestral populations is a powerful approach for investigating population-specific genetic structure as well as functionally mapping regions of disease susceptibility. Here, we present LDlink, a web-based collection of bioinformatic modules that query single nucleotide polymorphisms (SNPs) in population groups of interest to generate haplotype tables and interactive plots. Modules are designed with an emphasis on ease of use, query flexibility, and interactive visualization of results. Phase 3 haplotype data from the 1000 Genomes Project are referenced for calculating pairwise metrics of LD, searching for proxies in high LD, and enumerating all observed haplotypes. LDlink is tailored for investigators interested in mapping common and uncommon disease susceptibility loci by focusing on output linking correlated alleles and highlighting putative functional variants. AVAILABILITY AND IMPLEMENTATION LDlink is a free and publically available web tool which can be accessed at http://analysistools.nci.nih.gov/LDlink/. CONTACT mitchell.machiela@nih.gov.

Two susceptibility loci identified for prostate cancer aggressiveness

Most men diagnosed with prostate cancer will experience indolent disease; hence discovering genetic variants that distinguish aggressive from non-aggressive prostate cancer is of critical clinical importance for disease prevention and treatment. In a multistage, case-only genome-wide association study of 12,518 prostate cancer cases, we identify two loci associated with Gleason score, a pathological measure of disease aggressiveness: rs35148638 at 5q14.3 (RASA1, P=6.49×10-9) and rs78943174 at 3q26.31 (NAALADL2, P=4.18×10-8). In a stratified case-control analysis, the SNP at 5q14.3 appears specific for aggressive prostate cancer (P=8.85×10-5) with no association for non-aggressive prostate cancer compared to controls (P=0.57). The proximity of these loci to genes involved in vascular disease suggests potential biological mechanisms worthy of further investigation.

Chromosome 17q12 variants contribute to risk of early-onset prostate cancer

In a recent genome-wide association study by Gudmundsson and colleagues, two prostate cancer susceptibility loci were identified on chromosome 17q. The first locus, at 17q12, was distinguished by two intronic single-nucleotide polymorphisms (SNPs) in the TCF2 gene (rs4430796 and rs7501939). The second locus was in a gene-poor region of 17q24, where the strongest evidence of association was for SNP rs1859962. To determine if these loci were also associated with hereditary prostate cancer, we genotyped them in a family-based association sample of 403 non-Hispanic white families, including 1,015 men with and without prostate cancer. SNPs rs4430796 and rs7501939, which were in strong linkage disequilibrium (r(2) = 0.68), showed the strongest evidence of prostate cancer association. Using a family-based association test, the A allele of SNP rs4430796 was overtransmitted to affected men (P = 0.006), with an odds ratio of 1.40 (95% confidence interval, 1.09-1.81) under an additive genetic model. Notably, rs4430796 was significantly associated with prostate cancer among men diagnosed at an early (<50 years) but not later age (P = 0.006 versus P = 0.118). Our results confirm the prostate cancer association with SNPs on chromosome 17q12 initially reported by Gudmundsson and colleagues. In addition, our results suggest that the increased risk associated with these SNPs is approximately doubled in individuals predisposed to develop early-onset disease. Importantly, these SNPs do not account for a significant portion of our prior prostate cancer linkage evidence on chromosome 17. Thus, there likely exist one or more additional independent prostate cancer susceptibility loci in this region.

Chimeric EWSR1-FLI1 regulates the Ewing sarcoma susceptibility gene EGR2 via a GGAA microsatellite

Deciphering the ways in which somatic mutations and germline susceptibility variants cooperate to promote cancer is challenging. Ewing sarcoma is characterized by fusions between EWSR1 and members of the ETS gene family, usually EWSR1-FLI1, leading to the generation of oncogenic transcription factors that bind DNA at GGAA motifs. A recent genome-wide association study identified susceptibility variants near EGR2. Here we found that EGR2 knockdown inhibited proliferation, clonogenicity and spheroidal growth in vitro and induced regression of Ewing sarcoma xenografts. Targeted germline deep sequencing of the EGR2 locus in affected subjects and controls identified 291 Ewing-associated SNPs. At rs79965208, the A risk allele connected adjacent GGAA repeats by converting an interspaced GGAT motif into a GGAA motif, thereby increasing the number of consecutive GGAA motifs and thus the EWSR1-FLI1–dependent enhancer activity of this sequence, with epigenetic characteristics of an active regulatory element. EWSR1-FLI1 preferentially bound to the A risk allele, which increased global and allele-specific EGR2 expression. Collectively, our findings establish cooperation between a dominant oncogene and a susceptibility variant that regulates a major driver of Ewing sarcomagenesis.

Association of Type 2 Diabetes Susceptibility Variants With Advanced Prostate Cancer Risk in the Breast and Prostate Cancer Cohort Consortium

Observational studies have found an inverse association between type 2 diabetes (T2D) and prostate cancer (PCa), and genome-wide association studies have found common variants near 3 loci associated with both diseases. The authors examined whether a genetic background that favors T2D is associated with risk of advanced PCa. Data from the National Cancer Institutes Breast and Prostate Cancer Cohort Consortium, a genome-wide association study of 2,782 advanced PCa cases and 4,458 controls, were used to evaluate whether individual single nucleotide polymorphisms or aggregations of these 36 T2D susceptibility loci are associated with PCa. Ten T2D markers near 9 loci (NOTCH2, ADCY5, JAZF1, CDKN2A/B, TCF7L2, KCNQ1, MTNR1B, FTO, and HNF1B) were nominally associated with PCa (P < 0.05); the association for single nucleotide polymorphism rs757210 at the HNF1B locus was significant when multiple comparisons were accounted for (adjusted P = 0.001). Genetic risk scores weighted by the T2D log odds ratio and multilocus kernel tests also indicated a significant relation between T2D variants and PCa risk. A mediation analysis of 9,065 PCa cases and 9,526 controls failed to produce evidence that diabetes mediates the association of the HNF1B locus with PCa risk. These data suggest a shared genetic component between T2D and PCa and add to the evidence for an interrelation between these diseases.

Deep sequencing of HPV16 genomes: A new high-throughput tool for exploring the carcinogenicity and natural history of HPV16 infection

For unknown reasons, there is huge variability in risk conferred by different HPV types and, remarkably, strong differences even between closely related variant lineages within each type. HPV16 is a uniquely powerful carcinogenic type, causing approximately half of cervical cancer and most other HPV-related cancers. To permit the large-scale study of HPV genome variability and precancer/cancer, starting with HPV16 and cervical cancer, we developed a high-throughput next-generation sequencing (NGS) whole-genome method. We designed a custom HPV16 AmpliSeq™ panel that generated 47 overlapping amplicons covering 99% of the genome sequenced on the Ion Torrent Proton platform. After validating with Sanger, the current “gold standard” of sequencing, in 89 specimens with concordance of 99.9%, we used our NGS method and custom annotation pipeline to sequence 796 HPV16-positive exfoliated cervical cell specimens. The median completion rate per sample was 98.0%. Our method enabled us to discover novel SNPs, large contiguous deletions suggestive of viral integration (OR of 27.3, 95% CI 3.3–222, P=0.002), and the sensitive detection of variant lineage coinfections. This method represents an innovative high-throughput, ultra-deep coverage technique for HPV genomic sequencing, which, in turn, enables the investigation of the role of genetic variation in HPV epidemiology and carcinogenesis.

A Genome-Wide Scan Identifies Variants in NFIB Associated with Metastasis in Patients with Osteosarcoma

UNLABELLED Metastasis is the leading cause of death in patients with osteosarcoma, the most common pediatric bone malignancy. We conducted a multistage genome-wide association study of osteosarcoma metastasis at diagnosis in 935 osteosarcoma patients to determine whether germline genetic variation contributes to risk of metastasis. We identified an SNP, rs7034162, in NFIB significantly associated with metastasis in European osteosarcoma cases, as well as in cases of African and Brazilian ancestry (meta-analysis of all cases: P = 1.2 × 10(-9); OR, 2.43; 95% confidence interval, 1.83-3.24). The risk allele was significantly associated with lowered NFIB expression, which led to increased osteosarcoma cell migration, proliferation, and colony formation. In addition, a transposon screen in mice identified a significant proportion of osteosarcomas harboring inactivating insertions in Nfib and with lowered NFIB expression. These data suggest that germline genetic variation at rs7034162 is important in osteosarcoma metastasis and that NFIB is an osteosarcoma metastasis susceptibility gene. SIGNIFICANCE Metastasis at diagnosis in osteosarcoma is the leading cause of death in these patients. Here we show data that are supportive for the NFIB locus as associated with metastatic potential in osteosarcoma.

Re-Ranking Sequencing Variants in the Post-GWAS Era for Accurate Causal Variant Identification

Next generation sequencing has dramatically increased our ability to localize disease-causing variants by providing base-pair level information at costs increasingly feasible for the large sample sizes required to detect complex-trait associations. Yet, identification of causal variants within an established region of association remains a challenge. Counter-intuitively, certain factors that increase power to detect an associated region can decrease power to localize the causal variant. First, combining GWAS with imputation or low coverage sequencing to achieve the large sample sizes required for high power can have the unintended effect of producing differential genotyping error among SNPs. This tends to bias the relative evidence for association toward better genotyped SNPs. Second, re-use of GWAS data for fine-mapping exploits previous findings to ensure genome-wide significance in GWAS-associated regions. However, using GWAS findings to inform fine-mapping analysis can bias evidence away from the causal SNP toward the tag SNP and SNPs in high LD with the tag. Together these factors can reduce power to localize the causal SNP by more than half. Other strategies commonly employed to increase power to detect association, namely increasing sample size and using higher density genotyping arrays, can, in certain common scenarios, actually exacerbate these effects and further decrease power to localize causal variants. We develop a re-ranking procedure that accounts for these adverse effects and substantially improves the accuracy of causal SNP identification, often doubling the probability that the causal SNP is top-ranked. Application to the NCI BPC3 aggressive prostate cancer GWAS with imputation meta-analysis identified a new top SNP at 2 of 3 associated loci and several additional possible causal SNPs at these loci that may have otherwise been overlooked. This method is simple to implement using R scripts provided on the authors website.

Mosaic loss of chromosome Y is associated with common variation near TCL1A

Mosaic loss of chromosome Y (mLOY) leading to gonosomal XY/XO commonly occurs during aging, particularly in smokers. We investigated whether mLOY was associated with non-hematological cancer in three prospective cohorts (8,679 cancer cases and 5,110 cancer-free controls) and genetic susceptibility to mLOY. Overall, mLOY was observed in 7% of men, and its prevalence increased with age (per-year odds ratio (OR) = 1.13, 95% confidence interval (CI) = 1.12–1.15; P < 2 × 10−16), reaching 18.7% among men over 80 years old. mLOY was associated with current smoking (OR = 2.35, 95% CI = 1.82–3.03; P = 5.55 × 10−11), but the association weakened with years after cessation. mLOY was not consistently associated with overall or specific cancer risk (for example, bladder, lung or prostate cancer) nor with cancer survival after diagnosis (multivariate-adjusted hazard ratio = 0.87, 95% CI = 0.73–1.04; P = 0.12). In a genome-wide association study, we observed the first example of a common susceptibility locus for genetic mosaicism, specifically mLOY, which maps to TCL1A at 14q32.13, marked by rs2887399 (OR = 1.55, 95% CI = 1.36–1.78; P = 1.37 × 10−10).

Chromosome 8q24 markers: Risk of early‐onset and familial prostate cancer

Recent admixture mapping and linkage/association studies have implicated an ∼1 Mb region on chromosome 8q24 in prostate cancer susceptibility. In a subsequent follow‐up investigation, Haiman et al. (Nat Genet 2007;39:638‐44) observed significant, independent associations between 7 markers within this region and sporadic prostate cancer risk in a multi‐ethnic sample. To clarify the risk associated with hereditary prostate cancer, we tested for prostate cancer association with 6 of these 7 markers in a sample of 1,015 non‐Hispanic white men with and without prostate cancer from 403 familial and early‐onset prostate cancer families. Single nucleotide polymorphisms (SNPs) rs6983561 and rs6983267 showed the strongest evidence of prostate cancer association. Using a family‐based association test, the minor (“C”) allele of rs6983561 and the major (“G”) allele of rs6983267 were preferentially transmitted to affected men (p < 0.05), with estimated odds ratios (ORs) of 2.26 (95% confidence interval of 1.06–4.83) and 1.30 (95% confidence interval of 0.99–1.71), respectively, for an additive model. Notably, rs6983561 was significantly associated with prostate cancer among men diagnosed at an early (<50 years) but not later age (p = 0.03 versus p = 0.21). Similarly, the association with rs6983267 was (not) statistically significant among men with(out) clinically aggressive disease (p = 0.007 versus p = 0.34). Our results confirm the association of prostate cancer with several of the SNPs on chromosome 8q24 initially reported by Haiman et al. In addition, our results suggest that the increased risk associated with these SNPs is approximately doubled in individuals predisposed to develop early onset or clinically aggressive disease.