Estimation of ENPP1 deficiency genetic prevalence using a comprehensive literature review and population databases.

BACKGROUND: ENPP1 Deficiency-caused by biallelic variants in ENPP1-leads to widespread arterial calcification in early life (Generalized Arterial Calcification of Infancy, GACI) or hypophosphatemic rickets in later life (Autosomal Recessive Hypophosphatemic Rickets type 2, ARHR2). A prior study using the Exome Aggregation Consortium (ExAC)-a database of exomes obtained from approximately 60,000 individuals-estimated the genetic prevalence at approximately 1 in 200,000 pregnancies. METHODS: We estimated the genetic prevalence of ENPP1 Deficiency by evaluating allele frequencies from a population database, assuming Hardy-Weinberg equilibrium. This estimate benefitted from a comprehensive literature review using Mastermind ( https://mastermind.genomenon.com/ ), which uncovered additional variants and supporting evidence, a larger population database with approximately 140,000 individuals, and improved interpretation of variants as per current clinical guidelines. RESULTS: We estimate a genetic prevalence of approximately 1 in 64,000 pregnancies, thus more than tripling the prior estimate. In addition, the carrier frequency of ENPP1 variants was found to be highest in East Asian populations, albeit based on a small sample. CONCLUSION: These results indicate that a significant number of patients with ENPP1 Deficiency remain undiagnosed. Efforts to increase disease awareness as well as expand genetic testing, particularly in non-European populations are warranted, especially now that clinical trials for enzyme replacement therapy, which proved successful in animal models, are underway.

ENPP1 deficiency: A clinical update on the relevance of individual variants using a locus-specific patient database.

Loss-of-function variants in the ectonucleotide pyrophosphatase/phosphodiesterase family member 1 (ENPP1) cause ENPP1 Deficiency, a rare disorder characterized by pathological calcification, neointimal proliferation, and impaired bone mineralization. The consequence of ENPP1 Deficiency is a broad range of age dependent symptoms and morbidities including cardiovascular complications and 50% mortality in infants, autosomal recessive hypophosphatemic rickets type 2 (ARHR2) in children, and joint pain, osteomalacia and enthesopathies in adults. Recent research continues to add to the growing clinical presentation profile as well as expanding the role of ENPP1 itself. Here we review the current knowledge on the spectrum of clinical and genetic findings of ENPP1 Deficiency reported in patients diagnosed with GACI or ARHR2 phenotypes using a comprehensive database of known ENPP1 variants with associated clinical data. A total of 108 genotypes were identified from 154 patients. Of the 109 ENPP1 variants reviewed, 72.5% were demonstrably disease-causing, a threefold increase in pathogenic/likely pathogenic variants over other databases. There is substantial heterogeneity in disease severity, even among patients with the same variant. The approach to creating a continuously curated database of ENPP1 variants accessible to clinicians is necessary to increase the diagnostic yield of clinical genetic testing and accelerate diagnosis of ENPP1 Deficiency.

Mastermind: A Comprehensive Genomic Association Search Engine for Empirical Evidence Curation and Genetic Variant Interpretation.

Design and interpretation of genome sequencing assays in clinical diagnostics and research labs is complicated by an inability to identify information from the medical literature and related databases quickly, comprehensively and reproducibly. This challenge is compounded by the complexity and heterogeneity of nomenclatures used to describe diseases, genes and genetic variants. Mastermind is a widely-used bioinformatic platform of genomic associations that has indexed more than 7.5 M full-text articles and 2.5 M supplemental datasets. It has automatically identified, disambiguated and annotated >6.1 M genetic variants and identified >50 K disease-gene associations. Here, we describe how Mastermind improves the sensitivity and reproducibility of clinical variant interpretation and produces comprehensive genomic landscapes of genetic variants driving pharmaceutical research. We demonstrate an alarmingly high degree of heterogeneity across commercially available panels for hereditary cancer that is resolved by evidence from Mastermind. We further examined the sensitivity of Mastermind for variant interpretation by examining 108 clinically-encountered variants and comparing the results to alternate methods. Mastermind demonstrated a sensitivity of 98.4% compared to 4.4, 45.6, and 37.4% for alternatives PubMed, Google Scholar, and ClinVar, respectively, and a specificity of 98.5% compared to 45.1, 57.6, and 68.8% as well as an increase in content yield of 22.6-, 2.2-, and 2.6-fold. When curated for clinical significance, Mastermind identified more than 4.9-fold more pathogenic variants than ClinVar for representative genes. For structural variants, we compared Mastermind's ability to sensitively identify evidence for 10 representative disease-causing CNVs versus results identified in PubMed, as well as its ability to identify evidence for fusion events compared to COSMIC. Mastermind demonstrated a 4.0- to 43.9-fold increase in references for specific CNVs compared to PubMed, as well as 5.4-fold more fusion genes when compared with COSMIC's curated database. Additionally, Mastermind produced an 8.0-fold increase in reference citations for fusion events common to Mastermind and outside databases. Taken together, these results demonstrate the utility and superiority of Mastermind in terms of both sensitivity and specificity of automated results for clinical diagnostic variant interpretation for multiple genetic variant types and highlight the potential benefit in informing pharmaceutical research.