Robert J. Klein

Disentangling the Effects of Colocalizing Genomic Annotations to Functionally Prioritize Non-coding Variants within Complex-Trait Loci

Identifying genomic annotations that differentiate causal from trait-associated variants is essential to fine mapping disease loci. Although many studies have identified non-coding functional annotations that overlap disease-associated variants, these annotations often colocalize, complicating the ability to use these annotations for fine mapping causal variation. We developed a statistical approach (Genomic Annotation Shifter [GoShifter]) to assess whether enriched annotations are able to prioritize causal variation. GoShifter defines the null distribution of an annotation overlapping an allele by locally shifting annotations; this approach is less sensitive to biases arising from local genomic structure than commonly used enrichment methods that depend on SNP matching. Local shifting also allows GoShifter to identify independent causal effects from colocalizing annotations. Using GoShifter, we confirmed that variants in expression quantitative trail loci drive gene-expression changes though DNase-I hypersensitive sites (DHSs) near transcription start sites and independently through 3′ UTR regulation. We also showed that (1) 15%–36% of trait-associated loci map to DHSs independently of other annotations; (2) loci associated with breast cancer and rheumatoid arthritis harbor potentially causal variants near the summits of histone marks rather than full peak bodies; (3) variants associated with height are highly enriched in embryonic stem cell DHSs; and (4) we can effectively prioritize causal variation at specific loci.

WGSA: an annotation pipeline for human genome sequencing studies.

DNA sequencing technologies continue to make progress in increased throughput and quality, and decreased cost. As we transition from whole exome capture sequencing to whole genome sequencing (WGS), our ability to convert machine-generated variant calls, including single nucleotide variant (SNV) and insertion-deletion variants (indels), into human-interpretable knowledge has lagged far behind the ability to obtain enormous amounts of variants. To help narrow this gap, here we present WGSA (WGS annotator), a functional annotation pipeline for human genome sequencing studies, which is runnable out of the box on the Amazon Compute Cloud and is freely downloadable at (https://sites.google.com/site/jpopgen/wgsa/).nnFunctional annotation is a key step in WGS analysis. In one way, annotation helps the analyst filter to a subset of elements of particular interest (eg, cell type specific enhancers), in another way annotation helps the investigators to increase the power of identifying phenotype-associated loci (eg, association test using functional prediction score as a weight) and interpret potentially interesting findings. Currently, there are several popular gene model based annotation tools, including ANNOVAR,1 SnpEff2 and the Ensembl Variant Effect Predictor (VEP).3 These can annotate a variety of protein coding and non-coding gene models from a range of species. It is well known among practitioners that different databases (eg, RefSeq4 and Ensembl5) use different models for …

Validation and genomic interrogation of the MET variant rs11762213 as a predictor of adverse outcomes in clear cell renal cell carcinoma

The exonic single‐nucleotide variant rs11762213 located in the MET oncogene has recently been identified as a prognostic marker in clear cell renal cell carcinoma (ccRCC). This finding was validated with The Cancer Genome Atlas (TCGA) cohort, and the biologic implications were explored.

Genome-wide Trans-ethnic Meta-analysis Identifies Seven Genetic Loci Influencing Erythrocyte Traits and a Role for RBPMS in Erythropoiesis

Genome-wide association studies (GWASs) have identified loci for erythrocyte traits in primarily European ancestry populations. We conducted GWAS meta-analyses of six erythrocyte traits in 71,638 individuals from European, East Asian, and African ancestries using a Bayesian approach to account for heterogeneity in allelic effects and variation in the structure of linkage disequilibrium between ethnicities. We identified seven loci for erythrocyte traits including a locus (RBPMS/GTF2E2) associated with mean corpuscular hemoglobin and mean corpuscular volume. Statistical fine-mapping at this locus pointed to RBPMS at this locus and excluded nearby GTF2E2. Using zebrafish morpholino to evaluate loss of function, we observed a strong inxa0vivo erythropoietic effect for RBPMS but not for GTF2E2, supporting the statistical fine-mapping at this locus and demonstrating that RBPMS is a regulator of erythropoiesis. Our findings show the utility of trans-ethnic GWASs for discovery and characterization of genetic loci influencing hematologic traits.

An analysis of the association between prostate cancer risk loci, PSA levels, disease aggressiveness and disease-specific mortality

Background:Genome-wide association studies have identified multiple single-nucleotide polymorphsims (SNPs) associated with prostate cancer (PCa). Although these SNPs have been clearly associated with disease risk, their relationship with clinical outcomes is less clear. Our aim was to assess the frequency of known PCa susceptibility alleles within a single institution ascertainment and to correlate risk alleles with disease-specific outcomes.Methods:We genotyped 1354 individuals treated for localised PCa between June 1988 and December 2007. Blood samples were prospectively collected and de-identified before being genotyped and matched to phenotypic data. We investigated associations between 61 SNPs and disease-specific end points using multivariable analysis and also determined if SNPs were associated with PSA at diagnosis.Results:Seven SNPs showed associations on multivariable analysis (P<0.05), rs13385191 with both biochemical recurrence (BR) and castrate metastasis (CM), rs339331 (BR), rs1894292, rs17178655 and rs11067228 (CM), and rs11902236 and rs4857841 PCa-specific mortality. After applying a Bonferroni correction for number of SNPs (P<0.0008), the only persistent significant association was between rs17632542 (KLK3) and PSA levels at diagnosis (P=1.4 × 10−5).Conclusions:We confirmed that rs17632542 in KLK3 is associated with PSA at diagnosis. No significant association was seen between loci and disease-specific end points when accounting for multiple testing. This provides further evidence that known PCa risk SNPs do not predict likelihood of disease progression.

Collaborative science in the next-generation sequencing era: a viewpoint on how to combine exome sequencing data across sites to identify novel disease susceptibility genes

The purpose of this article is to inform readers about technical challenges that we encountered when assembling exome sequencing data from the Simplifying Complex Exomes (SIMPLEXO) consortium-whose mandate is the discovery of novel genes predisposing to breast and ovarian cancers. Our motivation is to share these obstacles-and our solutions to them-as a means of communicating important technical details that should be discussed early in projects involving massively parallel sequencing.

Tissue-Specific Enrichment of Lymphoma Risk Loci in Regulatory Elements

Though numerous polymorphisms have been associated with risk of developing lymphoma, how these variants function to promote tumorigenesis is poorly understood. Here, we report that lymphoma risk SNPs, especially in the non-Hodgkin’s lymphoma subtype chronic lymphocytic leukemia, are significantly enriched for co-localization with epigenetic marks of active gene regulation. These enrichments were seen in a lymphoid-specific manner for numerous ENCODE datasets, including DNase-hypersensitivity as well as multiple segmentation-defined enhancer regions. Furthermore, we identify putatively functional SNPs that are both in regulatory elements in lymphocytes and are associated with gene expression changes in blood. We developed an algorithm, UES, that uses a Monte Carlo simulation approach to calculate the enrichment of previously identified risk SNPs in various functional elements. This multiscale approach integrating multiple datasets helps disentangle the underlying biology of lymphoma, and more broadly, is generally applicable to GWAS results from other diseases as well.

Novel pedigree analysis implicates DNA repair and chromatin remodeling in multiple myeloma risk

The high-risk pedigree (HRP) design is an established strategy to discover rare, highly-penetrant, Mendelian-like causal variants. Its success, however, in complex traits has been modest, largely due to challenges of genetic heterogeneity and complex inheritance models. We describe a HRP strategy that addresses intra-familial heterogeneity, and identifies inherited segments important for mapping regulatory risk. We apply this new Shared Genomic Segment (SGS) method in 11 extended, Utah, multiple myeloma (MM) HRPs, and subsequent exome sequencing in SGS regions of interest in 1063 MM / MGUS (monoclonal gammopathy of undetermined significance–a precursor to MM) cases and 964 controls from a jointly-called collaborative resource, including cases from the initial 11 HRPs. One genome-wide significant 1.8 Mb shared segment was found at 6q16. Exome sequencing in this region revealed predicted deleterious variants in USP45 (p.Gln691* and p.Gln621Glu), a gene known to influence DNA repair through endonuclease regulation. Additionally, a 1.2 Mb segment at 1p36.11 is inherited in two Utah HRPs, with coding variants identified in ARID1A (p.Ser90Gly and p.Met890Val), a key gene in the SWI/SNF chromatin remodeling complex. Our results provide compelling statistical and genetic evidence for segregating risk variants for MM. In addition, we demonstrate a novel strategy to use large HRPs for risk-variant discovery more generally in complex traits.

Germline Lysine-Specific Demethylase 1 (LSD1/KDM1A) Mutations Confer Susceptibility to Multiple Myeloma

Given the frequent and largely incurable occurrence of multiple myeloma, identification of germline genetic mutations that predispose cells to multiple myeloma may provide insight into disease etiology and the developmental mechanisms of its cell of origin, the plasma cell (PC). Here, we identified familial and early-onset multiple myeloma kindreds with truncating mutations in lysine-specific demethylase 1 (LSD1/KDM1A), an epigenetic transcriptional repressor that primarily demethylates histone H3 on lysine 4 and regulates hematopoietic stem cell self-renewal. In addition, we found higher rates of germline truncating and predicted deleterious missense KDM1A mutations in patients with multiple myeloma unselected for family history compared with controls. Both monoclonal gammopathy of undetermined significance (MGUS) and multiple myeloma cells have significantly lower KDM1A transcript levels compared with normal PCs. Transcriptome analysis of multiple myeloma cells from KDM1A mutation carriers shows enrichment of pathways and MYC target genes previously associated with myeloma pathogenesis. In mice, antigen challenge followed by pharmacologic inhibition of KDM1A promoted PC expansion, enhanced secondary immune response, elicited appearance of serum paraprotein, and mediated upregulation of MYC transcriptional targets. These changes are consistent with the development of MGUS. Collectively, our findings show that KDM1A is the first autosomal-dominant multiple myeloma germline predisposition gene providing new insights into its mechanistic roles as a tumor suppressor during post-germinal center B-cell differentiation.Significance: KDM1A is the first germline autosomal dominant predisposition gene identified in multiple myeloma and provides new insights into multiple myeloma etiology and the mechanistic role of KDM1A as a tumor suppressor during post-germinal center B-cell differentiation. Cancer Res; 78(10); 2747-59. ©2018 AACR.

Rare germline variants in Fanconi Anemia genes increase risk for squamous lung cancer

Purpose Lung cancer is the leading cause of cancer deaths worldwide, with substantially better prognosis in early stage as opposed to late stage disease. Identifying genetic factors for lung squamous carcinoma (SqCC) risk will enable their use in risk stratification, and personalized intensive surveillance, early detection, and prevention strategies for high-risk individuals. Study Design and Participants We analyzed whole-exome sequencing datasets of 318 cases and 814 controls (discovery cohort) and then validated our findings in an independent cohort of 444 patients and 3,479 controls (validation cohort), all of European descent, totaling a combined cohort of 765 cases and 4,344 controls. We focused on rare pathogenic variants found in the ClinVar database and used penalized logistic regression to identify genes in which such variants are enriched in cases. All statistical tests were two-sided. Results We observed an overall enrichment of rare, deleterious germline variants in Fanconi Anemia genes in cases with SqCC (joint analysis OR=3.08, p=1.4e-09, 95% confidence interval [CI]=2.2–4.3). Consistent with previous studies, BRCA2 in particular exhibited an increased overall burden of rare, deleterious variants (joint OR=3.2, p=8.7e-08, 95% CI=2.1–4.7). More importantly, rare deleterious germline variants were enriched in Fanconi Anemia genes even without the BRCA2 rs11571833 variant that is strongly enriched in lung SqCC cases (joint OR=2.76, p=7.0e-04, 95% CI=1.6–4.7). Conclusions These findings can be used towards the development of a genetic diagnostic test in the clinic to identify SqCC high-risk individuals, who can benefit from personalized programs, improving prognosis.