Murat Sincan

The National Institutes of Health Undiagnosed Diseases Program: insights into rare diseases

Purpose:This report describes the National Institutes of Health Undiagnosed Diseases Program, details the Program’s application of genomic technology to establish diagnoses, and details the Program’s success rate during its first 2 years.Methods:Each accepted study participant was extensively phenotyped. A subset of participants and selected family members (29 patients and 78 unaffected family members) was subjected to an integrated set of genomic analyses including high-density single-nucleotide polymorphism arrays and whole exome or genome analysis.Results:Of 1,191 medical records reviewed, 326 patients were accepted and 160 were admitted directly to the National Institutes of Health Clinical Center on the Undiagnosed Diseases Program service. Of those, 47% were children, 55% were females, and 53% had neurologic disorders. Diagnoses were reached on 39 participants (24%) on clinical, biochemical, pathologic, or molecular grounds; 21 diagnoses involved rare or ultra-rare diseases. Three disorders were diagnosed based on single-nucleotide polymorphism array analysis and three others using whole exome sequencing and filtering of variants. Two new disorders were discovered. Analysis of the single-nucleotide polymorphism array study cohort revealed that large stretches of homozygosity were more common in affected participants relative to controls.Conclusion:The National Institutes of Health Undiagnosed Diseases Program addresses an unmet need, i.e., the diagnosis of patients with complex, multisystem disorders. It may serve as a model for the clinical application of emerging genomic technologies and is providing insights into the characteristics of diseases that remain undiagnosed after extensive clinical workup.Genet Med 2012:14(1):51–59

Detecting false positive signals in exome sequencing

Disease gene discovery has been transformed by affordable sequencing of exomes and genomes. Identification of disease‐causing mutations requires sifting through a large number of sequence variants. A subset of the variants are unlikely to be good candidates for disease causation based on one or more of the following criteria: (1) being located in genomic regions known to be highly polymorphic, (2) having characteristics suggesting assembly misalignment, and/or (3) being labeled as variants based on misleading reference genome information. We analyzed exome sequence data from 118 individuals in 29 families seen in the NIH Undiagnosed Diseases Program (UDP) to create lists of variants and genes with these characteristics. Specifically, we identified several groups of genes that are candidates for provisional exclusion during exome analysis: 23,389 positions with excess heterozygosity suggestive of alignment errors and 1,009 positions in which the hg18 human genome reference sequence appeared to contain a minor allele. Exclusion of such variants, which we provide in supplemental lists, will likely enhance identification of disease‐causing mutations using exome sequence data. Hum Mutat 33:609–613, 2012.

Characteristics of Congenital Hepatic Fibrosis in a Large Cohort of Patients With Autosomal Recessive Polycystic Kidney Disease

BACKGROUND & AIMS Autosomal recessive polycystic kidney disease (ARPKD), the most common ciliopathy of childhood, is characterized by congenital hepatic fibrosis and progressive cystic degeneration of kidneys. We aimed to describe congenital hepatic fibrosis in patients with ARPKD, confirmed by detection of mutations in PKHD1. METHODS Patients with ARPKD and congenital hepatic fibrosis were evaluated at the National Institutes of Health from 2003 to 2009. We analyzed clinical, molecular, and imaging data from 73 patients (age, 1-56 years; average, 12.7 ± 13.1 years) with kidney and liver involvement (based on clinical, imaging, or biopsy analyses) and mutations in PKHD1. RESULTS Initial symptoms were liver related in 26% of patients, and others presented with kidney disease. One patient underwent liver and kidney transplantation, and 10 others received kidney transplants. Four presented with cholangitis and one with variceal bleeding. Sixty-nine percent of patients had enlarged left lobes on magnetic resonance imaging, 92% had increased liver echogenicity on ultrasonography, and 65% had splenomegaly. Splenomegaly started early in life; 60% of children younger than 5 years had enlarged spleens. Spleen volume had an inverse correlation with platelet count and prothrombin time but not with serum albumin level. Platelet count was the best predictor of spleen volume (area under the curve of 0.88905), and spleen length corrected for patients height correlated inversely with platelet count (R(2) = 0.42, P < .0001). Spleen volume did not correlate with renal function or type of PKHD1 mutation. Twenty-two of 31 patients who underwent endoscopy were found to have varices. Five had variceal bleeding, and 2 had portosystemic shunts. Forty-percent had Caroli syndrome, and 30% had an isolated dilated common bile duct. CONCLUSIONS Platelet count is the best predictor of the severity of portal hypertension, which has early onset but is underdiagnosed in patients with ARPKD. Seventy percent of patients with ARPKD have biliary abnormalities. Kidney and liver disease are independent, and variability in severity is not explainable by type of PKHD1 mutation; ClinicalTrials.gov number, NCT00068224.

Exome sequencing and SNP analysis detect novel compound heterozygosity in fatty acid hydroxylase-associated neurodegeneration

Fatty acid hydroxylase-associated neurodegeneration due to fatty acid 2-hydroxylase deficiency presents with a wide range of phenotypes including spastic paraplegia, leukodystrophy, and/or brain iron deposition. All previously described families with this disorder were consanguineous, with homozygous mutations in the probands. We describe a 10-year-old male, from a non-consanguineous family, with progressive spastic paraplegia, dystonia, ataxia, and cognitive decline associated with a sural axonal neuropathy. The use of high-throughput sequencing techniques combined with SNP array analyses revealed a novel paternally derived missense mutation and an overlapping novel maternally derived ∼28-kb genomic deletion in FA2H. This patient provides further insight into the consistent features of this disorder and expands our understanding of its phenotypic presentation. The presence of a sural nerve axonal neuropathy had not been previously associated with this disorder and so may extend the phenotype.

The implications of familial incidental findings from exome sequencing: the NIH Undiagnosed Diseases Program experience.

Purpose:Using exome sequence data from 159 families participating in the National Institutes of Health Undiagnosed Diseases Program, we evaluated the number and inheritance mode of reportable incidental sequence variants.Methods:Following the American College of Medical Genetics and Genomics recommendations for reporting of incidental findings from next-generation sequencing, we extracted variants in 56 genes from the exome sequence data of 543 subjects and determined the reportable incidental findings for each participant. We also defined variant status as inherited or de novo for those with available parental sequence data.Results:We identified 14 independent reportable variants in 159 (8.8%) families. For nine families with parental sequence data in our cohort, a parent transmitted the variant to one or more children (nine minor children and four adult children). The remaining five variants occurred in adults for whom parental sequences were unavailable.Conclusion:Our results are consistent with the expectation that a small percentage of exomes will result in identification of an incidental finding under the American College of Medical Genetics and Genomics recommendations. Additionally, our analysis of family sequence data highlights that genome and exome sequencing of families has unavoidable implications for immediate family members and therefore requires appropriate counseling for the family.Genet Med 16 10, 741–750.

An analysis of exome sequencing for diagnostic testing of the genes associated with muscle disease and spastic paraplegia.

In this study, we assess exome sequencing (ES) as a diagnostic alternative for genetically heterogeneous disorders. Because ES readily identified a previously reported homozygous mutation in the CAPN3 gene for an individual with an undiagnosed limb girdle muscular dystrophy, we evaluated ES as a generalizable clinical diagnostic tool by assessing the targeting efficiency and sequencing coverage of 88 genes associated with muscle disease (MD) and spastic paraplegia (SPG). We used three exome‐capture kits on 125 individuals. Exons constituting each gene were defined using the UCSC and CCDS databases. The three exome‐capture kits targeted 47–92% of bases within the UCSC‐defined exons and 97–99% of bases within the CCDS‐defined exons. An average of 61.2–99.5% and 19.1–99.5% of targeted bases per gene were sequenced to 20X coverage within the CCDS‐defined MD and SPG coding exons, respectively. Greater than 95–99% of targeted known mutation positions were sequenced to ≥1X coverage and 55–87% to ≥20X coverage in every exome. We conclude, therefore, that ES is a rapid and efficient first‐tier method to screen for mutations, particularly within the CCDS annotated exons, although its application requires disclosure of the extent of coverage for each targeted gene and supplementation with second‐tier Sanger sequencing for full coverage. Hum Mutat 33:614–626, 2012.

Computational evaluation of exome sequence data using human and model organism phenotypes improves diagnostic efficiency.

Purpose:Medical diagnosis and molecular or biochemical confirmation typically rely on the knowledge of the clinician. Although this is very difficult in extremely rare diseases, we hypothesized that the recording of patient phenotypes in Human Phenotype Ontology (HPO) terms and computationally ranking putative disease-associated sequence variants improves diagnosis, particularly for patients with atypical clinical profiles.Methods:Using simulated exomes and the National Institutes of Health Undiagnosed Diseases Program (UDP) patient cohort and associated exome sequence, we tested our hypothesis using Exomiser. Exomiser ranks candidate variants based on patient phenotype similarity to (i) known disease–gene phenotypes, (ii) model organism phenotypes of candidate orthologs, and (iii) phenotypes of protein–protein association neighbors.Results:Benchmarking showed Exomiser ranked the causal variant as the top hit in 97% of known disease–gene associations and ranked the correct seeded variant in up to 87% when detectable disease–gene associations were unavailable. Using UDP data, Exomiser ranked the causative variant(s) within the top 10 variants for 11 previously diagnosed variants and achieved a diagnosis for 4 of 23 cases undiagnosed by clinical evaluation.Conclusion:Structured phenotyping of patients and computational analysis are effective adjuncts for diagnosing patients with genetic disorders.Genet Med 18 6, 608–617.

Analysis of DNA sequence variants detected by high-throughput sequencing†

The Undiagnosed Diseases Program at the National Institutes of Health uses high‐throughput sequencing (HTS) to diagnose rare and novel diseases. HTS techniques generate large numbers of DNA sequence variants, which must be analyzed and filtered to find candidates for disease causation. Despite the publication of an increasing number of successful exome‐based projects, there has been little formal discussion of the analytic steps applied to HTS variant lists. We present the results of our experience with over 30 families for whom HTS sequencing was used in an attempt to find clinical diagnoses. For each family, exome sequence was augmented with high‐density SNP‐array data. We present a discussion of the theory and practical application of each analytic step and provide example data to illustrate our approach. The article is designed to provide an analytic roadmap for variant analysis, thereby enabling a wide range of researchers and clinical genetics practitioners to perform direct analysis of HTS data for their patients and projects. Hum Mutat 33:599–608, 2012.

VAR‐MD: A tool to analyze whole exome–genome variants in small human pedigrees with mendelian inheritance

The analysis of variants generated by exome sequencing (ES) of families with rare Mendelian diseases is a time‐consuming, manual process that represents one barrier to applying the technology routinely. To address this issue, we have developed a software tool, VAR‐MD (http://research.nhgri.nih.gov/software/var‐md/), for analyzing the DNA sequence variants produced by human ES. VAR‐MD generates a ranked list of variants using predicted pathogenicity, Mendelian inheritance models, genotype quality, and population variant frequency data. VAR‐MD was tested using two previously solved data sets and one unsolved data set. In the solved cases, the correct variant was listed at the top of VAR‐MDs variant ranking. In the unsolved case, the correct variant was highly ranked, allowing for subsequent identification and validation. We conclude that VAR‐MD has the potential to enhance mutation identification using family based, annotated next generation sequencing data. Moreover, we predict an incremental advancement in software performance as the reference databases, such as Single Nucleotide Polymorphism Database and Human Gene Mutation Database, continue to improve. Hum Mutat 33:593–598, 2012.

Exome sequencing as a diagnostic tool in a case of undiagnosed juvenile-onset GM1-gangliosidosis.

Objective: To utilize high-throughput sequencing to determine the etiology of juvenile-onset neurodegeneration in a 19-year-old woman with progressive motor and cognitive decline. Methods: Exome sequencing identified an initial list of 133,555 variants in the probands family, which were filtered using segregation analysis, presence in dbSNP, and an empirically derived gene exclusion list. The filtered list comprised 52 genes: 21 homozygous variants and 31 compound heterozygous variants. These variants were subsequently scrutinized with predicted pathogenicity programs and for association with appropriate clinical syndromes. Results: Exome sequencing data identified 2 GLB1 variants (c.602G>A, p.R201H; c.785G>T, p.G262V). β-Galactosidase enzyme analysis prior to our evaluation was reported as normal; however, subsequent testing was consistent with juvenile-onset GM1-gangliosidosis. Urine oligosaccharide analysis was positive for multiple oligosaccharides with terminal galactose residues. Conclusions: We describe a patient with juvenile-onset neurodegeneration that had eluded diagnosis for over a decade. GM1-gangliosidosis had previously been excluded from consideration, but was subsequently identified as the correct diagnosis using exome sequencing. Exome sequencing can evaluate genes not previously associated with neurodegeneration, as well as most known neurodegeneration-associated genes. Our results demonstrate the utility of “agnostic” exome sequencing to evaluate patients with undiagnosed disorders, without prejudice from prior testing results.