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Next-generation sequencing of common osteogenesis imperfecta-related genes in clinical practice.

ABSTRACT: Next generation sequencing (NGS) is a rapidly developing area in genetics. Utilizing this technology in the management of disorders with complex genetic background and not recurrent mutation hot spots can be extremely useful. In this study, we applied NGS, namely semiconductor sequencing to determine the most significant osteogenesis imperfecta-related genetic variants in the clinical practice. We selected genes coding collagen type I alpha-1 and-2 (COL1A1, COL1A2) which are responsible for more than 90% of all cases. CRTAP and LEPRE1/P3H1 genes involved in the background of the recessive forms with relatively high frequency (type VII and VIII) represent less than 10% of the disease. In our six patients (1-41 years), we identified 23 different variants. We found a total of 14 single nucleotide variants (SNV) in COL1A1 and COL1A2, 5 in CRTAP and 4 in LEPRE1. Two novel and two already well-established pathogenic SNVs have been identified. Among the newly recognized mutations, one results in an amino acid change and one of them is a stop codon. We have shown that a new full-scale cost-effective NGS method can be developed and utilized to supplement diagnostic process of osteogenesis imperfecta with molecular genetic data in clinical practice.

SUBMITTER: Arvai K

PROVIDER: S-EPMC4917842 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Next-generation sequencing of common osteogenesis imperfecta-related genes in clinical practice.

Árvai Kristóf K Horváth Péter P Balla Bernadett B Tobiás Bálint B Kató Karina K Kirschner Gyöngyi G Klujber Valéria V Lakatos Péter P Kósa János P JP

Scientific reports 20160623

Next generation sequencing (NGS) is a rapidly developing area in genetics. Utilizing this technology in the management of disorders with complex genetic background and not recurrent mutation hot spots can be extremely useful. In this study, we applied NGS, namely semiconductor sequencing to determine the most significant osteogenesis imperfecta-related genetic variants in the clinical practice. We selected genes coding collagen type I alpha-1 and-2 (COL1A1, COL1A2) which are responsible for more ...[more]

PMID: 27335225

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Project description:Amelogenesis imperfecta (AI) is a heterogeneous group of genetic rare diseases disrupting enamel development (Smith et al., Front Physiol, 2017a, 8, 333). The clinical enamel phenotypes can be described as hypoplastic, hypomineralized or hypomature and serve as a basis, together with the mode of inheritance, to Witkop's classification (Witkop, J Oral Pathol, 1988, 17, 547-553). AI can be described in isolation or associated with others symptoms in syndromes. Its occurrence was estimated to range from 1/700 to 1/14,000. More than 70 genes have currently been identified as causative. Objectives: We analyzed using next-generation sequencing (NGS) a heterogeneous cohort of AI patients in order to determine the molecular etiology of AI and to improve diagnosis and disease management. Methods: Individuals presenting with so called "isolated" or syndromic AI were enrolled and examined at the Reference Centre for Rare Oral and Dental Diseases (O-Rares) using D4/phenodent protocol (www.phenodent.org). Families gave written informed consents for both phenotyping and molecular analysis and diagnosis using a dedicated NGS panel named GenoDENT. This panel explores currently simultaneously 567 genes. The study is registered under NCT01746121 and NCT02397824 (https://clinicaltrials.gov/). Results: GenoDENT obtained a 60% diagnostic rate. We reported genetics results for 221 persons divided between 115 AI index cases and their 106 associated relatives from a total of 111 families. From this index cohort, 73% were diagnosed with non-syndromic amelogenesis imperfecta and 27% with syndromic amelogenesis imperfecta. Each individual was classified according to the AI phenotype. Type I hypoplastic AI represented 61 individuals (53%), Type II hypomature AI affected 31 individuals (27%), Type III hypomineralized AI was diagnosed in 18 individuals (16%) and Type IV hypoplastic-hypomature AI with taurodontism concerned 5 individuals (4%). We validated the genetic diagnosis, with class 4 (likely pathogenic) or class 5 (pathogenic) variants, for 81% of the cohort, and identified candidate variants (variant of uncertain significance or VUS) for 19% of index cases. Among the 151 sequenced variants, 47 are newly reported and classified as class 4 or 5. The most frequently discovered genotypes were associated with MMP20 and FAM83H for isolated AI. FAM20A and LTBP3 genes were the most frequent genes identified for syndromic AI. Patients negative to the panel were resolved with exome sequencing elucidating for example the gene involved ie ACP4 or digenic inheritance. Conclusion: NGS GenoDENT panel is a validated and cost-efficient technique offering new perspectives to understand underlying molecular mechanisms of AI. Discovering variants in genes involved in syndromic AI (CNNM4, WDR72, FAM20A … ) transformed patient overall care. Unravelling the genetic basis of AI sheds light on Witkop's AI classification.

Dataset Information

Next-generation sequencing of common osteogenesis imperfecta-related genes in clinical practice.

Publications

Next-generation sequencing of common osteogenesis imperfecta-related genes in clinical practice.

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