Eric Vallabh Minikel

Analysis of protein-coding genetic variation in 60,706 humans

Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human ‘knockout’ variants in protein-coding genes.

Reassessment of Mendelian gene pathogenicity using 7,855 cardiomyopathy cases and 60,706 reference samples

Purpose:The accurate interpretation of variation in Mendelian disease genes has lagged behind data generation as sequencing has become increasingly accessible. Ongoing large sequencing efforts present huge interpretive challenges, but they also provide an invaluable opportunity to characterize the spectrum and importance of rare variation.Methods:We analyzed sequence data from 7,855 clinical cardiomyopathy cases and 60,706 Exome Aggregation Consortium (ExAC) reference samples to obtain a better understanding of genetic variation in a representative autosomal dominant disorder.Results:We found that in some genes previously reported as important causes of a given cardiomyopathy, rare variation is not clinically informative because there is an unacceptably high likelihood of false-positive interpretation. By contrast, in other genes, we find that diagnostic laboratories may be overly conservative when assessing variant pathogenicity.Conclusions:We outline improved analytical approaches that evaluate which genes and variant classes are interpretable and propose that these will increase the clinical utility of testing across a range of Mendelian diseases.Genet Med 19 2, 192–203.

Quantifying prion disease penetrance using large population control cohorts

Large genomic reference data sets reveal a spectrum of pathogenicity in the prion protein gene and provide genetic validation for a therapeutic strategy in prion disease. Share trumps rare No longer just buzz words, “patient empowerment” and “data sharing” are enabling breakthrough research on rare genetic diseases. Although more than 100,000 genetic variants are believed to drive disease in humans, little is known about penetrance—the probability that a mutation will actually cause disease in the carrier. This conundrum persists because small sample sizes breed imperfect alliance estimates between mutations and disease risk. Now, a patient-turned-scientist joined with a large bioinformatics team to analyze vast amounts of shared data—from the Exome Aggregation Consortium and the 23andMe database—to provide insights into genetic-variant penetrance and possible treatment approaches for a rare, fatal genetic prion disease. More than 100,000 genetic variants are reported to cause Mendelian disease in humans, but the penetrance—the probability that a carrier of the purported disease-causing genotype will indeed develop the disease—is generally unknown. We assess the impact of variants in the prion protein gene (PRNP) on the risk of prion disease by analyzing 16,025 prion disease cases, 60,706 population control exomes, and 531,575 individuals genotyped by 23andMe Inc. We show that missense variants in PRNP previously reported to be pathogenic are at least 30 times more common in the population than expected on the basis of genetic prion disease prevalence. Although some of this excess can be attributed to benign variants falsely assigned as pathogenic, other variants have genuine effects on disease susceptibility but confer lifetime risks ranging from <0.1 to ~100%. We also show that truncating variants in PRNP have position-dependent effects, with true loss-of-function alleles found in healthy older individuals, a finding that supports the safety of therapeutic suppression of prion protein expression.

Human genomics. Effect of predicted protein-truncating genetic variants on the human transcriptome

Expression, genetic variation, and tissues Human genomes show extensive genetic variation across individuals, but we have only just started documenting the effects of this variation on the regulation of gene expression. Furthermore, only a few tissues have been examined per genetic variant. In order to examine how genetic expression varies among tissues within individuals, the Genotype-Tissue Expression (GTEx) Consortium collected 1641 postmortem samples covering 54 body sites from 175 individuals. They identified quantitative genetic traits that affect gene expression and determined which of these exhibit tissue-specific expression patterns. Melé et al. measured how transcription varies among tissues, and Rivas et al. looked at how truncated protein variants affect expression across tissues. Science, this issue p. 648, p. 660, p. 666; see also p. 640 Protein-truncated variants impact gene expression levels and splicing across human tissues. [Also see Perspective by Gibson] Accurate prediction of the functional effect of genetic variation is critical for clinical genome interpretation. We systematically characterized the transcriptome effects of protein-truncating variants, a class of variants expected to have profound effects on gene function, using data from the Genotype-Tissue Expression (GTEx) and Geuvadis projects. We quantitated tissue-specific and positional effects on nonsense-mediated transcript decay and present an improved predictive model for this decay. We directly measured the effect of variants both proximal and distal to splice junctions. Furthermore, we found that robustness to heterozygous gene inactivation is not due to dosage compensation. Our results illustrate the value of transcriptome data in the functional interpretation of genetic variants.

Using high-resolution variant frequencies to empower clinical genome interpretation

PurposeWhole-exome and whole-genome sequencing have transformed the discovery of genetic variants that cause human Mendelian disease, but discriminating pathogenic from benign variants remains a daunting challenge. Rarity is recognized as a necessary, although not sufficient, criterion for pathogenicity, but frequency cutoffs used in Mendelian analysis are often arbitrary and overly lenient. Recent very large reference datasets, such as the Exome Aggregation Consortium (ExAC), provide an unprecedented opportunity to obtain robust frequency estimates even for very rare variants.MethodsWe present a statistical framework for the frequency-based filtering of candidate disease-causing variants, accounting for disease prevalence, genetic and allelic heterogeneity, inheritance mode, penetrance, and sampling variance in reference datasets.ResultsUsing the example of cardiomyopathy, we show that our approach reduces by two-thirds the number of candidate variants under consideration in the average exome, without removing true pathogenic variants (false-positive rate<0.001).ConclusionWe outline a statistically robust framework for assessing whether a variant is “too common” to be causative for a Mendelian disorder of interest. We present precomputed allele frequency cutoffs for all variants in the ExAC dataset.

Ascertainment Bias Causes False Signal of Anticipation in Genetic Prion Disease

Anticipation is the phenomenon whereby age of onset in genetic disease decreases in successive generations. Three independent reports have claimed anticipation in Creutzfeldt-Jakob disease (CJD) caused by the c.598G > A mutation in PRNP encoding a p.Glu200Lys (E200K) substitution in the prion protein. If confirmed, this finding would carry clear implications for genetic counseling. We analyzed pedigrees with this mutation from four prion centers worldwide (n = 217 individuals with the mutation) to analyze age of onset and death in affected and censored individuals. We show through simulation that selective ascertainment of individuals whose onset falls within the historical window since the mutations 1989 discovery is sufficient to create robust false signals both of anticipation and of heritability of age of onset. In our data set, the number of years of anticipation observed depends upon how strictly the data are limited by the ascertainment window. Among individuals whose disease was directly observed at a study center, a 28-year difference between parent and child age of onset is observed (p = 0.002), but including individuals ascertained retrospectively through family history reduces this figure to 7 years (p = 0.005). Applying survival analysis to the most thoroughly ascertained subset of data eliminates the signal of anticipation. Moreover, even non-CJD deaths exhibit 16 years anticipation (p = 0.002), indicating that ascertainment bias can entirely explain observed anticipation. We suggest that reports of anticipation in genetic prion disease are driven entirely by ascertainment bias. Guidelines for future studies claiming statistical evidence for anticipation are suggested.

Pathogenic ASXL1 somatic variants in reference databases complicate germline variant interpretation for Bohring‐Opitz Syndrome

The clinical interpretation of genetic variants has come to rely heavily on reference population databases such as the Exome Aggregation Consortium (ExAC) database. Pathogenic variants in genes associated with severe, pediatric‐onset, highly penetrant, autosomal dominant conditions are assumed to be absent or rare in these databases. Exome sequencing of a 6‐year‐old female patient with seizures, developmental delay, dysmorphic features, and failure to thrive identified an ASXL1 variant previously reported as causative of Bohring–Opitz syndrome (BOS). Surprisingly, the variant was observed seven times in the ExAC database, presumably in individuals without BOS. Although the BOS phenotype fit, the presence of the variant in reference population databases introduced ambiguity in result interpretation. Review of the literature revealed that acquired somatic mosaicism of ASXL1 variants (including pathogenic variants) during hematopoietic clonal expansion can occur with aging in healthy individuals. We examined all ASXL1 truncating variants in the ExAC database and determined most are likely somatic. Failure to consider somatic mosaicism may lead to the inaccurate assumption that conditions like BOS have reduced penetrance, or the misclassification of potentially pathogenic variants.

ClinVar data parsing

This software repository provides a pipeline for converting raw ClinVar data files into analysis-friendly tab-delimited tables, and also provides these tables for the most recent ClinVar release. Separate tables are generated for genome builds GRCh37 and GRCh38 as well as for mono-allelic variants and complex multi-allelic variants. Additionally, the tables are augmented with allele frequencies from the ExAC and gnomAD datasets as these are often consulted when analyzing ClinVar variants. Overall, this work provides ClinVar data in a format that is easier to work with and can be directly loaded into a variety of popular analysis tools such as R, python pandas, and SQL databases.

Prion protein quantification in cerebrospinal fluid as a tool for prion disease drug development

Reduction of native prion protein (PrP) levels in the brain is an attractive and genetically validated strategy for the treatment or prevention of human prion diseases. However, clinical development of any PrP-reducing therapeutic will require an appropriate pharmacodynamic biomarker: a practical and robust method for quantifying PrP, and reliably demonstrating its reduction, in the central nervous system (CNS) of a living patient. Here we evaluate the potential of enzyme-linked immunosorbent assay (ELISA)-based quantification of human PrP in human cerebrospinal fluid (CSF) to serve as a biomarker for PrP-reducing therapeutics. We show that CSF PrP is highly sensitive to plastic adsorption during handling and storage, but its loss can be minimized by addition of detergent. We find that blood contamination does not affect CSF PrP levels, and that CSF PrP and hemoglobin are uncorrelated, together suggesting that CSF PrP is CNS-derived, supporting its relevance for monitoring the tissue of interest and in keeping with high PrP abundance in brain relative to blood. In a cohort with controlled sample handling, CSF PrP exhibits good within-subject test-retest reliability (mean coefficient of variation 13% in samples collected 8-11 weeks apart), a sufficiently stable baseline to allow therapeutically meaningful reductions in brain PrP to be readily detected in CSF. Together, these findings supply a method for monitoring the effect of a PrP-reducing drug in the CNS, enabling the development of prion disease therapeutics with this mechanism of action.

Age of onset in genetic prion disease and the design of preventive clinical trials

Regulatory agencies worldwide have adopted programs to facilitate drug development for diseases where the traditional approach of a randomized trial with a clinical endpoint is expected to be prohibitively lengthy or difficult. Here we provide quantitative evidence that this criterion is met for the prevention of genetic prion disease. We assemble age of onset or death data from N=1,094 individuals with high penetrance mutations in the prion protein gene (PRNP), generate survival and hazard curves, and estimate statistical power for clinical trials. We show that, due to dramatic and unexplained variability in age of onset, randomized preventive trials would require hundreds or thousands of at-risk individuals in order to be statistically powered for an endpoint of clinical onset, posing prohibitive cost and delay and likely exceeding the number of individuals available for such trials. Instead, the characterization of biomarkers suitable to serve as surrogate endpoints will be essential for the prevention of genetic prion disease. Biomarker-based trials may require post-marketing studies to confirm clinical benefit. Parameters such as longer trial duration, increased enrollment, and the use of historical controls in a post-marketing study could provide opportunities for subsequent determination of clinical benefit.