Tracking Cancer Evolution Reveals Constrained Routes to Metastases: TRACERx Renal.

Clear-cell renal cell carcinoma (ccRCC) exhibits a broad range of metastatic phenotypes that have not been systematically studied to date. Here, we analyzed 575 primary and 335 metastatic biopsies across 100 patients with metastatic ccRCC, including two cases sampledat post-mortem. Metastatic competence was afforded by chromosome complexity, and we identify 9p loss as a highly selected event driving metastasis and ccRCC-related mortality (p = 0.0014). Distinct patterns of metastatic dissemination were observed, including rapid progression to multiple tissue sites seeded by primary tumors of monoclonal structure. By contrast, we observed attenuated progression in cases characterized by high primary tumor heterogeneity, with metastatic competence acquired gradually and initial progression to solitary metastasis. Finally, we observed early divergence of primitive ancestral clones and protracted latency of up to two decades as a feature of pancreatic metastases.

Genetic perturbation of the maize methylome.

DNA methylation can play important roles in the regulation of transposable elements and genes. A collection of mutant alleles for 11 maize (Zea mays) genes predicted to play roles in controlling DNA methylation were isolated through forward- or reverse-genetic approaches. Low-coverage whole-genome bisulfite sequencing and high-coverage sequence-capture bisulfite sequencing were applied to mutant lines to determine context- and locus-specific effects of these mutations on DNA methylation profiles. Plants containing mutant alleles for components of the RNA-directed DNA methylation pathway exhibit loss of CHH methylation at many loci as well as CG and CHG methylation at a small number of loci. Plants containing loss-of-function alleles for chromomethylase (CMT) genes exhibit strong genome-wide reductions in CHG methylation and some locus-specific loss of CHH methylation. In an attempt to identify stocks with stronger reductions in DNA methylation levels than provided by single gene mutations, we performed crosses to create double mutants for the maize CMT3 orthologs, Zmet2 and Zmet5, and for the maize DDM1 orthologs, Chr101 and Chr106. While loss-of-function alleles are viable as single gene mutants, the double mutants were not recovered, suggesting that severe perturbations of the maize methylome may have stronger deleterious phenotypic effects than in Arabidopsis thaliana.

Somatic retrotransposition alters the genetic landscape of the human brain.

Retrotransposons are mobile genetic elements that use a germline 'copy-and-paste' mechanism to spread throughout metazoan genomes. At least 50 per cent of the human genome is derived from retrotransposons, with three active families (L1, Alu and SVA) associated with insertional mutagenesis and disease. Epigenetic and post-transcriptional suppression block retrotransposition in somatic cells, excluding early embryo development and some malignancies. Recent reports of L1 expression and copy number variation in the human brain suggest that L1 mobilization may also occur during later development. However, the corresponding integration sites have not been mapped. Here we apply a high-throughput method to identify numerous L1, Alu and SVA germline mutations, as well as 7,743 putative somatic L1 insertions, in the hippocampus and caudate nucleus of three individuals. Surprisingly, we also found 13,692 somatic Alu insertions and 1,350 SVA insertions. Our results demonstrate that retrotransposons mobilize to protein-coding genes differentially expressed and active in the brain. Thus, somatic genome mosaicism driven by retrotransposition may reshape the genetic circuitry that underpins normal and abnormal neurobiological processes.

Proteome-wide epitope mapping of antibodies using ultra-dense peptide arrays.

Antibodies are of importance for the field of proteomics, both as reagents for imaging cells, tissues, and organs and as capturing agents for affinity enrichment in mass-spectrometry-based techniques. It is important to gain basic insights regarding the binding sites (epitopes) of antibodies and potential cross-reactivity to nontarget proteins. Knowledge about an antibody's linear epitopes is also useful in, for instance, developing assays involving the capture of peptides obtained from trypsin cleavage of samples prior to mass spectrometry analysis. Here, we describe, for the first time, the design and use of peptide arrays covering all human proteins for the analysis of antibody specificity, based on parallel in situ photolithic synthesis of a total of 2.1 million overlapping peptides. This has allowed analysis of on- and off-target binding of both monoclonal and polyclonal antibodies, complemented with precise mapping of epitopes based on full amino acid substitution scans. The analysis suggests that linear epitopes are relatively short, confined to five to seven residues, resulting in apparent off-target binding to peptides corresponding to a large number of unrelated human proteins. However, subsequent analysis using recombinant proteins suggests that these linear epitopes have a strict conformational component, thus giving us new insights regarding how antibodies bind to their antigens.

Nucleotide polymorphism and copy number variant detection using exome capture and next-generation sequencing in the polyploid grass Panicum virgatum.

Switchgrass (Panicum virgatum) is a polyploid, outcrossing grass species native to North America and has recently been recognized as a potential biofuel feedstock crop. Significant phenotypic variation including ploidy is present across the two primary ecotypes of switchgrass, referred to as upland and lowland switchgrass. The tetraploid switchgrass genome is approximately 1400 Mbp, split between two subgenomes, with significant repetitive sequence content limiting the efficiency of re-sequencing approaches for determining genome diversity. To characterize genetic diversity in upland and lowland switchgrass as a first step in linking genotype to phenotype, we designed an exome capture probe set based on transcript assemblies that represent approximately 50 Mb of annotated switchgrass exome sequences. We then evaluated and optimized the probe set using solid phase comparative genome hybridization and liquid phase exome capture followed by next-generation sequencing. Using the optimized probe set, we assessed variation in the exomes of eight switchgrass genotypes representing tetraploid lowland and octoploid upland cultivars to benchmark our exome capture probe set design. We identified ample variation in the switchgrass genome including 1,395,501 single nucleotide polymorphisms (SNPs), 8173 putative copy number variants and 3336 presence/absence variants. While the majority of the SNPs (84%) detected was bi-allelic, a substantial number was tri-allelic with limited occurrence of tetra-allelic polymorphisms consistent with the heterozygous and polyploid nature of the switchgrass genome. Collectively, these data demonstrate the efficacy of exome capture for discovery of genome variation in a polyploid species with a large, repetitive and heterozygous genome.

Discovery of previously unidentified genomic disorders from the duplication architecture of the human genome.

Genomic disorders are characterized by the presence of flanking segmental duplications that predispose these regions to recurrent rearrangement. Based on the duplication architecture of the genome, we investigated 130 regions that we hypothesized as candidates for previously undescribed genomic disorders. We tested 290 individuals with mental retardation by BAC array comparative genomic hybridization and identified 16 pathogenic rearrangements, including de novo microdeletions of 17q21.31 found in four individuals. Using oligonucleotide arrays, we refined the breakpoints of this microdeletion, defining a 478-kb critical region containing six genes that were deleted in all four individuals. We mapped the breakpoints of this deletion and of four other pathogenic rearrangements in 1q21.1, 15q13, 15q24 and 17q12 to flanking segmental duplications, suggesting that these are also sites of recurrent rearrangement. In common with the 17q21.31 deletion, these breakpoint regions are sites of copy number polymorphism in controls, indicating that these may be inherently unstable genomic regions.

Barley whole exome capture: a tool for genomic research in the genus Hordeum and beyond.

Advanced resources for genome-assisted research in barley (Hordeum vulgare) including a whole-genome shotgun assembly and an integrated physical map have recently become available. These have made possible studies that aim to assess genetic diversity or to isolate single genes by whole-genome resequencing and in silico variant detection. However such an approach remains expensive given the 5 Gb size of the barley genome. Targeted sequencing of the mRNA-coding exome reduces barley genomic complexity more than 50-fold, thus dramatically reducing this heavy sequencing and analysis load. We have developed and employed an in-solution hybridization-based sequence capture platform to selectively enrich for a 61.6 megabase coding sequence target that includes predicted genes from the genome assembly of the cultivar Morex as well as publicly available full-length cDNAs and de novo assembled RNA-Seq consensus sequence contigs. The platform provides a highly specific capture with substantial and reproducible enrichment of targeted exons, both for cultivated barley and related species. We show that this exome capture platform provides a clear path towards a broader and deeper understanding of the natural variation residing in the mRNA-coding part of the barley genome and will thus constitute a valuable resource for applications such as mapping-by-sequencing and genetic diversity analyzes.

Acquired copy number alterations in adult acute myeloid leukemia genomes.

Cytogenetic analysis of acute myeloid leukemia (AML) cells has accelerated the identification of genes important for AML pathogenesis. To complement cytogenetic studies and to identify genes altered in AML genomes, we performed genome-wide copy number analysis with paired normal and tumor DNA obtained from 86 adult patients with de novo AML using 1.85 million feature SNP arrays. Acquired copy number alterations (CNAs) were confirmed using an ultra-dense array comparative genomic hybridization platform. A total of 201 somatic CNAs were found in the 86 AML genomes (mean, 2.34 CNAs per genome), with French-American-British system M6 and M7 genomes containing the most changes (10-29 CNAs per genome). Twenty-four percent of AML patients with normal cytogenetics had CNA, whereas 40% of patients with an abnormal karyotype had additional CNA detected by SNP array, and several CNA regions were recurrent. The mRNA expression levels of 57 genes were significantly altered in 27 of 50 recurrent CNA regions <5 megabases in size. A total of 8 uniparental disomy (UPD) segments were identified in the 86 genomes; 6 of 8 UPD calls occurred in samples with a normal karyotype. Collectively, 34 of 86 AML genomes (40%) contained alterations not found with cytogenetics, and 98% of these regions contained genes. Of 86 genomes, 43 (50%) had no CNA or UPD at this level of resolution. In this study of 86 adult AML genomes, the use of an unbiased high-resolution genomic screen identified many genes not previously implicated in AML that may be relevant for pathogenesis, along with many known oncogenes and tumor suppressor genes.

Comparative analysis of genome-wide DNA methylation identifies patterns that associate with conserved transcriptional programs in osteosarcoma.

Osteosarcoma is an aggressive tumor of the bone that primarily affects young adults and adolescents. Osteosarcoma is characterized by genomic chaos and heterogeneity. While inactivation of tumor protein p53 (TP53) is nearly universal other high frequency mutations or structural variations have not been identified. Despite this genomic heterogeneity, key conserved transcriptional programs associated with survival have been identified across human, canine and induced murine osteosarcoma. The epigenomic landscape, including DNA methylation, plays a key role in establishing transcriptional programs in all cell types. The role of epigenetic dysregulation has been studied in a variety of cancers but has yet to be explored at scale in osteosarcoma. Here we examined genome-wide DNA methylation patterns in 24 human and 44 canine osteosarcoma samples identifying groups of highly correlated DNA methylation marks in human and canine osteosarcoma samples. We also link specific DNA methylation patterns to key transcriptional programs in both human and canine osteosarcoma. Building on previous work, we built a DNA methylation-based measure for the presence and abundance of various immune cell types in osteosarcoma. Finally, we determined that the underlying state of the tumor, and not changes in cell composition, were the main driver of differences in DNA methylation across the human and canine samples. SIGNIFICANCE: Genome wide comparison of DNA methylation patterns in osteosarcoma across two species lays the ground work for the exploration of DNA methylation programs that help establish conserved transcriptional programs in the context of varied mutational landscapes.

Progressive multifocal leukoencephalopathy genetic risk variants for pharmacovigilance of immunosuppressant therapies.

Background: Progressive multifocal leukoencephalopathy (PML) is a rare and often lethal brain disorder caused by the common, typically benign polyomavirus 2, also known as JC virus (JCV). In a small percentage of immunosuppressed individuals, JCV is reactivated and infects the brain, causing devastating neurological defects. A wide range of immunosuppressed groups can develop PML, such as patients with: HIV/AIDS, hematological malignancies (e.g., leukemias, lymphomas, and multiple myeloma), autoimmune disorders (e.g., psoriasis, rheumatoid arthritis, and systemic lupus erythematosus), and organ transplants. In some patients, iatrogenic (i.e., drug-induced) PML occurs as a serious adverse event from exposure to immunosuppressant therapies used to treat their disease (e.g., hematological malignancies and multiple sclerosis). While JCV infection and immunosuppression are necessary, they are not sufficient to cause PML. Methods: We hypothesized that patients may also have a genetic susceptibility from the presence of rare deleterious genetic variants in immune-relevant genes (e.g., those that cause inborn errors of immunity). In our prior genetic study of 184 PML cases, we discovered 19 candidate PML risk variants. In the current study of another 152 cases, we validated 4 of 19 variants in both population controls (gnomAD 3.1) and matched controls (JCV+ multiple sclerosis patients on a PML-linked drug ≥ 2 years). Results: The four variants, found in immune system genes with strong biological links, are: C8B, 1-57409459-C-A, rs139498867; LY9 (alias SLAMF3), 1-160769595-AG-A, rs763811636; FCN2, 9-137779251-G-A, rs76267164; STXBP2, 19-7712287-G-C, rs35490401. Carriers of any one of these variants are shown to be at high risk of PML when drug-exposed PML cases are compared to drug-exposed matched controls: P value = 3.50E-06, OR = 8.7 [3.7-20.6]. Measures of clinical validity and utility compare favorably to other genetic risk tests, such as BRCA1 and BRCA2 screening for breast cancer risk and HLA-B*15:02 pharmacogenetic screening for pharmacovigilance of carbamazepine to prevent Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis. Conclusion: For the first time, a PML genetic risk test can be implemented for screening patients taking or considering treatment with a PML-linked drug in order to decrease the incidence of PML and enable safer use of highly effective therapies used to treat their underlying disease.

Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples.

BACKGROUND: Clinical laboratories routinely use formalin-fixed paraffin-embedded (FFPE) tissue or cell block cytology samples in oncology panel sequencing to identify mutations that can predict patient response to targeted therapy. To understand the technical error due to FFPE processing, a robustly characterized diploid cell line was used to create FFPE samples with four different pre-tissue processing formalin fixation times. A total of 96 FFPE sections were then distributed to different laboratories for targeted sequencing analysis by four oncopanels, and variants resulting from technical error were identified. RESULTS: Tissue sections that fail more frequently show low cellularity, lower than recommended library preparation DNA input, or target sequencing depth. Importantly, sections from block surfaces are more likely to show FFPE-specific errors, akin to "edge effects" seen in histology, while the inner samples display no quality degradation related to fixation time. CONCLUSIONS: To assure reliable results, we recommend avoiding the block surface portion and restricting mutation detection to genomic regions of high confidence.

A high-resolution map of active promoters in the human genome.

In eukaryotic cells, transcription of every protein-coding gene begins with the assembly of an RNA polymerase II preinitiation complex (PIC) on the promoter. The promoters, in conjunction with enhancers, silencers and insulators, define the combinatorial codes that specify gene expression patterns. Our ability to analyse the control logic encoded in the human genome is currently limited by a lack of accurate information regarding the promoters for most genes. Here we describe a genome-wide map of active promoters in human fibroblast cells, determined by experimentally locating the sites of PIC binding throughout the human genome. This map defines 10,567 active promoters corresponding to 6,763 known genes and at least 1,196 un-annotated transcriptional units. Features of the map suggest extensive use of multiple promoters by the human genes and widespread clustering of active promoters in the genome. In addition, examination of the genome-wide expression profile reveals four general classes of promoters that define the transcriptome of the cell. These results provide a global view of the functional relationships among transcriptional machinery, chromatin structure and gene expression in human cells.

High-resolution genome-wide cytosine methylation profiling with simultaneous copy number analysis and optimization for limited cell numbers.

Many genome-wide assays involve the generation of a subset (or representation) of the genome following restriction enzyme digestion. The use of enzymes sensitive to cytosine methylation allows high-throughput analysis of this epigenetic regulatory process. We show that the use of a dual-adapter approach allows us to generate genomic representations that includes fragments of <200 bp in size, previously not possible when using the standard approach of using a single adapter. By expanding the representation to smaller fragments using HpaII or MspI, we increase the representation by these isoschizomers to more than 1.32 million loci in the human genome, representing 98.5% of CpG islands and 91.1% of refSeq promoters. This advance allows the development of a new, high-resolution version of our HpaII-tiny fragment Enrichment by Ligation-mediated PCR (HELP) assay to study cytosine methylation. We also show that the MspI representation generates information about copy-number variation, that the assay can be used on as little as 10 ng of DNA and that massively parallel sequencing can be used as an alternative to microarrays to read the output of the assay, making this a powerful discovery platform for studies of genomic and epigenomic abnormalities.

Advancing NGS quality control to enable measurement of actionable mutations in circulating tumor DNA.

The primary objective of the FDA-led Sequencing and Quality Control Phase 2 (SEQC2) project is to develop standard analysis protocols and quality control metrics for use in DNA testing to enhance scientific research and precision medicine. This study reports a targeted next-generation sequencing (NGS) method that will enable more accurate detection of actionable mutations in circulating tumor DNA (ctDNA) clinical specimens. To accomplish this, a synthetic internal standard spike-in was designed for each actionable mutation target, suitable for use in NGS following hybrid capture enrichment and unique molecular index (UMI) or non-UMI library preparation. When mixed with contrived ctDNA reference samples, internal standards enabled calculation of technical error rate, limit of blank, and limit of detection for each variant at each nucleotide position in each sample. True-positive mutations with variant allele fraction too low for detection by current practice were detected with this method, thereby increasing sensitivity.

Cross-oncopanel study reveals high sensitivity and accuracy with overall analytical performance depending on genomic regions.

BACKGROUND: Targeted sequencing using oncopanels requires comprehensive assessments of accuracy and detection sensitivity to ensure analytical validity. By employing reference materials characterized by the U.S. Food and Drug Administration-led SEquence Quality Control project phase2 (SEQC2) effort, we perform a cross-platform multi-lab evaluation of eight Pan-Cancer panels to assess best practices for oncopanel sequencing. RESULTS: All panels demonstrate high sensitivity across targeted high-confidence coding regions and variant types for the variants previously verified to have variant allele frequency (VAF) in the 5-20% range. Sensitivity is reduced by utilizing VAF thresholds due to inherent variability in VAF measurements. Enforcing a VAF threshold for reporting has a positive impact on reducing false positive calls. Importantly, the false positive rate is found to be significantly higher outside the high-confidence coding regions, resulting in lower reproducibility. Thus, region restriction and VAF thresholds lead to low relative technical variability in estimating promising biomarkers and tumor mutational burden. CONCLUSION: This comprehensive study provides actionable guidelines for oncopanel sequencing and clear evidence that supports a simplified approach to assess the analytical performance of oncopanels. It will facilitate the rapid implementation, validation, and quality control of oncopanels in clinical use.

A verified genomic reference sample for assessing performance of cancer panels detecting small variants of low allele frequency.

BACKGROUND: Oncopanel genomic testing, which identifies important somatic variants, is increasingly common in medical practice and especially in clinical trials. Currently, there is a paucity of reliable genomic reference samples having a suitably large number of pre-identified variants for properly assessing oncopanel assay analytical quality and performance. The FDA-led Sequencing and Quality Control Phase 2 (SEQC2) consortium analyze ten diverse cancer cell lines individually and their pool, termed Sample A, to develop a reference sample with suitably large numbers of coding positions with known (variant) positives and negatives for properly evaluating oncopanel analytical performance. RESULTS: In reference Sample A, we identify more than 40,000 variants down to 1% allele frequency with more than 25,000 variants having less than 20% allele frequency with 1653 variants in COSMIC-related genes. This is 5-100× more than existing commercially available samples. We also identify an unprecedented number of negative positions in coding regions, allowing statistical rigor in assessing limit-of-detection, sensitivity, and precision. Over 300 loci are randomly selected and independently verified via droplet digital PCR with 100% concordance. Agilent normal reference Sample B can be admixed with Sample A to create new samples with a similar number of known variants at much lower allele frequency than what exists in Sample A natively, including known variants having allele frequency of 0.02%, a range suitable for assessing liquid biopsy panels. CONCLUSION: These new reference samples and their admixtures provide superior capability for performing oncopanel quality control, analytical accuracy, and validation for small to large oncopanels and liquid biopsy assays.

Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology.

Circulating tumor DNA (ctDNA) sequencing is being rapidly adopted in precision oncology, but the accuracy, sensitivity and reproducibility of ctDNA assays is poorly understood. Here we report the findings of a multi-site, cross-platform evaluation of the analytical performance of five industry-leading ctDNA assays. We evaluated each stage of the ctDNA sequencing workflow with simulations, synthetic DNA spike-in experiments and proficiency testing on standardized, cell-line-derived reference samples. Above 0.5% variant allele frequency, ctDNA mutations were detected with high sensitivity, precision and reproducibility by all five assays, whereas, below this limit, detection became unreliable and varied widely between assays, especially when input material was limited. Missed mutations (false negatives) were more common than erroneous candidates (false positives), indicating that the reliable sampling of rare ctDNA fragments is the key challenge for ctDNA assays. This comprehensive evaluation of the analytical performance of ctDNA assays serves to inform best practice guidelines and provides a resource for precision oncology.

wuHMM: a robust algorithm to detect DNA copy number variation using long oligonucleotide microarray data.

Copy number variants (CNVs) are currently defined as genomic sequences that are polymorphic in copy number and range in length from 1000 to several million base pairs. Among current array-based CNV detection platforms, long-oligonucleotide arrays promise the highest resolution. However, the performance of currently available analytical tools suffers when applied to these data because of the lower signal:noise ratio inherent in oligonucleotide-based hybridization assays. We have developed wuHMM, an algorithm for mapping CNVs from array comparative genomic hybridization (aCGH) platforms comprised of 385 000 to more than 3 million probes. wuHMM is unique in that it can utilize sequence divergence information to reduce the false positive rate (FPR). We apply wuHMM to 385K-aCGH, 2.1M-aCGH and 3.1M-aCGH experiments comparing the 129X1/SvJ and C57BL/6J inbred mouse genomes. We assess wuHMM's performance on the 385K platform by comparison to the higher resolution platforms and we independently validate 10 CNVs. The method requires no training data and is robust with respect to changes in algorithm parameters. At a FPR of <10%, the algorithm can detect CNVs with five probes on the 385K platform and three on the 2.1M and 3.1M platforms, resulting in effective resolutions of 24 kb, 2-5 kb and 1 kb, respectively.

A high-resolution map of segmental DNA copy number variation in the mouse genome.

Submicroscopic (less than 2 Mb) segmental DNA copy number changes are a recently recognized source of genetic variability between individuals. The biological consequences of copy number variants (CNVs) are largely undefined. In some cases, CNVs that cause gene dosage effects have been implicated in phenotypic variation. CNVs have been detected in diverse species, including mice and humans. Published studies in mice have been limited by resolution and strain selection. We chose to study 21 well-characterized inbred mouse strains that are the focus of an international effort to measure, catalog, and disseminate phenotype data. We performed comparative genomic hybridization using long oligomer arrays to characterize CNVs in these strains. This technique increased the resolution of CNV detection by more than an order of magnitude over previous methodologies. The CNVs range in size from 21 to 2,002 kb. Clustering strains by CNV profile recapitulates aspects of the known ancestry of these strains. Most of the CNVs (77.5%) contain annotated genes, and many (47.5%) colocalize with previously mapped segmental duplications in the mouse genome. We demonstrate that this technique can identify copy number differences associated with known polymorphic traits. The phenotype of previously uncharacterized strains can be predicted based on their copy number at these loci. Annotation of CNVs in the mouse genome combined with sequence-based analysis provides an important resource that will help define the genetic basis of complex traits.

Germline Genetic Risk Variants for Progressive Multifocal Leukoencephalopathy.

Progressive multifocal leukoencephalopathy (PML) is a rare demyelinating disorder of the brain caused by reactivation of the JC virus (JCV), a polyomavirus that infects at least 60% of the population but is asymptomatic or results in benign symptoms in most people. PML occurs as a secondary disease in a variety of disorders or as a serious adverse event from immunosuppressant agents, but is mainly found in three groups: HIV-infected patients, patients with hematological malignancies, or multiple sclerosis (MS) patients on the immunosuppressant therapy natalizumab. It is severely debilitating and is deadly in ~50% HIV cases, ~90% of hematological malignancy cases, and ~24% of MS-natalizumab cases. A PML risk prediction test would have clinical utility in all at risk patient groups but would be particularly beneficial in patients considering therapy with immunosuppressant agents known to cause PML, such as natalizumab, rituximab, and others. While a JC antibody test is currently used in the clinical decision process for natalizumab, it is suboptimal because of its low specificity and requirement to periodically retest patients for seroconversion or to assess if a patient's JCV index has increased. Whereas a high specificity genetic risk prediction test comprising host genetic risk variants (i.e., germline variants occurring at higher frequency in PML patients compared to the general population) could be administered one time to provide clinicians with additional risk prediction information that is independent of JCV serostatus. Prior PML case reports support the hypothesis that PML risk is greater in patients with a genetically caused immunodeficiency disorder. To identify germline PML risk variants, we performed exome sequencing on 185 PML cases (70 in a discovery cohort and 115 in a replication cohort) and used the gnomAD variant database for interpretation. Our study yielded 19 rare variants (maximum allele frequency of 0.02 in gnomAD ethnically matched populations) that impact 17 immune function genes (10 are known to cause inborn errors of immunity). Modeling of these variants in a PML genetic risk test for MS patients considering natalizumab treatment indicates that at least a quarter of PML cases may be preventable.