Mutations in NOTCH2 in families with Hajdu-Cheney syndrome
ABSTRACT Hajdu-Cheney syndrome (HCS) is a rare genetic disorder whose hallmark is acro-osteolysis, shortening of terminal phalanges, and generalized osteoporosis. We assembled a cohort of seven families with the condition and performed whole exome resequencing on a selected set of affected patients. One protein-coding gene, NOTCH2, carried heterozygous truncating variants in all patients and their affected family members. Our results replicate recently published studies of HCS and further support this as the causal gene for the disorder. In total, we identified five novel and one previously reported mutation, all clustered near the carboxyl terminus of the gene, suggesting an allele specific genotype-phenotype effect since other mutations in NOTCH2 have been reported to cause a form of Alagille syndrome. Notch-mediated signaling is known to play a role in bone metabolism. Our results support a potential therapeutic role for Notch pathways in treatment of osteoporosis.
- SourceAvailable from: Ashok Kumar Manickaraj
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- "Approaches like the Cohort Allelic Sums Test (CAST) (Morgenthaler and Thilly, 2007) and Combined Multivariate and Collapsing (CMC) method (Li and Leal, 2008) aggregate the rare variants seen within a gene or a pathway to mitigate this, but the applicability of association-based methods remains extremely limited for small cohorts. The alternative approach of prioritizing disease-causing single nucleotide variants (SNVs) based on their population frequency, conservation and the type of change (radical versus conservative amino acid change, introduction of a stop codon, etc.) has been extremely effective at identifying causal non-synonymous mutations in a number of Mendelian disorders, including Charcot– Marie–Tooth neuropathy (Lupski et al., 2010), Hajdu–Cheney syndrome (Majewski et al., 2011a) and Miller syndrome (Ng et al., 2009). In this approach, the variants identified in the genome are filtered to those with low allele frequencies (common variants are unlikely to cause rare disorders) and are sorted based on a 'harmfulness' score generated by tools such as PolyPhen, SIFT or PANTHER (Adzhubei et al., 2010; Ng and Henikoff, 2003; Thomas et al., 2003). "
ABSTRACT: MOTIVATION: The prioritization and identification of disease-causing mutations is one of the most significant challenges in medical genomics. Currently available methods address this problem for non-synonymous single nucleotide variants and variation in promoters/enhancers, however recent research has implicated synonymous (silent) exonic mutations in a number of disorders. RESULTS: We have curated 33 such variants from literature and developed the Silent Variant Analyzer (SilVA), a machine learning approach to separate these from amongst a large set of rare polymorphisms. We evaluate SilVA's performance on in silico "infection" experiments, in which we implant known disease-causing mutations into a human genome, and show that for 15/33 disorders we rank the implanted mutation among the top 5 most deleterious ones. Furthermore, we apply the SilVA method to two additional datasets: synonymous variants associated with Meckel syndrome, and a collection of silent variants clinically observed and stratified by a molecular diagnostics laboratory, and show that SilVA is able to accurately predict the harmfulness of silent variants in these datasets. AVAILABILITY: SilVA is open source and freely available from the project website: http://compbio.cs.toronto.edu/silva CONTACT: firstname.lastname@example.org.Bioinformatics 06/2013; 29(15). DOI:10.1093/bioinformatics/btt308 · 4.62 Impact Factor
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ABSTRACT: Alagille syndrome (ALGS) is a dominant, multisystem disorder caused by mutations in the Jagged1 (JAG1) ligand in 94% of patients, and in the NOTCH2 receptor in <1%. There are only two NOTCH2 families reported to date. This study hypothesised that additional NOTCH2 mutations would be present in patients with clinical features of ALGS without a JAG1 mutation. The study screened a cohort of JAG1-negative individuals with clinical features suggestive or diagnostic of ALGS for NOTCH2 mutations. Eight individuals with novel NOTCH2 mutations (six missense, one splicing, and one non-sense mutation) were identified. Three of these patients met classic criteria for ALGS and five patients only had a subset of features. The mutations were distributed across the extracellular (N=5) and intracellular domains (N=3) of the protein. Functional analysis of four missense, one nonsense, and one splicing mutation demonstrated decreased Notch signalling of these proteins. Subjects with NOTCH2 mutations demonstrated highly variable expressivity of the affected systems, as with JAG1 individuals. Liver involvement was universal in NOTCH2 probands and they had a similar prevalence of ophthalmologic and renal anomalies to JAG1 patients. There was a trend towards less cardiac involvement in the NOTCH2 group (60% vs 100% in JAG1). NOTCH2 (+) probands exhibited a significantly decreased penetrance of vertebral abnormalities (10%) and facial features (20%) when compared to the JAG1 (+) cohort. This work confirms the importance of NOTCH2 as a second disease gene in ALGS and expands the repertoire of the NOTCH2 related disease phenotype.Journal of Medical Genetics 12/2011; 49(2):138-44. DOI:10.1136/jmedgenet-2011-100544 · 5.64 Impact Factor
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ABSTRACT: Following the "finished," euchromatic, haploid human reference genome sequence, the rapid development of novel, faster, and cheaper sequencing technologies is making possible the era of personalized human genomics. Personal diploid human genome sequences have been generated, and each has contributed to our better understanding of variation in the human genome. We have consequently begun to appreciate the vastness of individual genetic variation from single nucleotide to structural variants. Translation of genome-scale variation into medically useful information is, however, in its infancy. This review summarizes the initial steps undertaken in clinical implementation of personal genome information, and describes the application of whole-genome and exome sequencing to identify the cause of genetic diseases and to suggest adjuvant therapies. Better analysis tools and a deeper understanding of the biology of our genome are necessary in order to decipher, interpret, and optimize clinical utility of what the variation in the human genome can teach us. Personal genome sequencing may eventually become an instrument of common medical practice, providing information that assists in the formulation of a differential diagnosis. We outline herein some of the remaining challenges.Annual review of medicine 02/2012; 63(1):35-61. DOI:10.1146/annurev-med-051010-162644 · 15.48 Impact Factor