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

Reduction of native prion protein (PrP) levels in the brain is an attractive strategy for the treatment or prevention of human prion disease. 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 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 the 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 wk 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, and will facilitate development of prion disease therapeutics with this mechanism of action

Insights into the genetic epidemiology of Crohn's and rare diseases in the Ashkenazi Jewish population

As part of a broader collaborative network of exome sequencing studies, we developed a jointly called data set of 5,685 Ashkenazi Jewish exomes. We make publicly available a resource of site and allele frequencies, which should serve as a reference for medical genetics in the Ashkenazim (hosted in part at https://ibd.broadinstitute.org, also available in gnomAD at http://gnomad.broadinstitute.org). We estimate that 34% of protein-coding alleles present in the Ashkenazi Jewish population at frequencies greater than 0.2% are significantly more frequent (mean 15-fold) than their maximum frequency observed in other reference populations. Arising via a well-described founder effect approximately 30 generations ago, this catalog of enriched alleles can contribute to differences in genetic risk and overall prevalence of diseases between populations. As validation we document 148 AJ enriched protein-altering alleles that overlap with "pathogenic" ClinVar alleles (table available at https://github.com/macarthur-lab/clinvar/blob/master/output/clinvar.tsv), including those that account for 10-100 fold differences in prevalence between AJ and non-AJ populations of some rare diseases, especially recessive conditions, including Gaucher disease (GBA, p.Asn409Ser, 8-fold enrichment); Canavan disease (ASPA, p.Glu285Ala, 12-fold enrichment); and Tay-Sachs disease (HEXA, c.1421+1G>C, 27-fold enrichment; p.Tyr427IlefsTer5, 12-fold enrichment). We next sought to use this catalog, of well-established relevance to Mendelian disease, to explore Crohn's disease, a common disease with an estimated two to four-fold excess prevalence in AJ. We specifically attempt to evaluate whether strong acting rare alleles, particularly protein-truncating or otherwise large effect-size alleles, enriched by the same founder-effect, contribute excess genetic risk to Crohn's disease in AJ, and find that ten rare genetic risk factors in NOD2 and LRRK2 are enriched in AJ (p < 0.005), including several novel contributing alleles, show evidence of association to CD. Independently, we find that genomewide common variant risk defined by GWAS shows a strong difference between AJ and non-AJ European control population samples (0.97 s.d. higher, p<10-16). Taken together, the results suggest coordinated selection in AJ population for higher CD risk alleles in general. The results and approach illustrate the value of exome sequencing data in case-control studies along with reference data sets like ExAC (sites VCF available via FTP at ftp.broadinstitute.org/pub/ExAC_release/release0.3/) to pinpoint genetic variation that contributes to variable disease predisposition across populations

Predictors for a dementia gene mutation based on gene-panel next-generation sequencing of a large dementia referral series

Next-generation genetic sequencing (NGS) technologies facilitate the screening of multiple genes linked to neurodegenerative dementia, but there is little guidance available about their use in clinical practice. Guidelines on which patients would most profit from testing, and information on the likelihood of discovery of a causal variant in a clinical syndrome, are conspicuously absent from the literature, mostly for a lack of large-scale studies. We applied a validated NGS dementia panel to 3241 patients with dementia and healthy aged controls; 13,152 variants were classified by likelihood of pathogenicity. We identified 354 deleterious variants (DV, 12.6% of patients); 39 were novel DVs. Age at clinical onset, clinical syndrome and family history each strongly predict the likelihood of finding a DV, but healthcare setting and gender did not. DVs were frequently found in genes not usually associated with the clinical syndrome. Patients recruited from primary referral centres were compared to those seen at higher-level research centres and a national clinical neurogenetic laboratory; rates of discovery were comparable, making selection bias unlikely and the results generalizable to clinical practice. We estimated penetrance of DVs using large-scale online genomic population databases and found 71 with evidence of reduced penetrance. Two DVs in the same patient were found more frequently than expected. These publicly-available data should provide a basis for informed counselling and clinical decision making

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

Correction: Insights into the genetic epidemiology of Crohn's and rare diseases in the Ashkenazi Jewish population

Correction of 2018 article: PLoS Genet 14(5): e1007329. https://doi.org/10.1371/journal.pgen.1007329 PMID: 2979557

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.Peer reviewe