4
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      At a glance: the largest Niemann-Pick type C1 cohort with 602 patients diagnosed over 15 years

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Niemann-Pick type C1 disease (NPC1 [OMIM 257220]) is a rare and severe autosomal recessive disorder, characterized by a multitude of neurovisceral clinical manifestations and a fatal outcome with no effective treatment to date. Aiming to gain insights into the genetic aspects of the disease, clinical, genetic, and biomarker PPCS data from 602 patients referred from 47 countries and diagnosed with NPC1 in our laboratory were analyzed. Patients’ clinical data were dissected using Human Phenotype Ontology (HPO) terms, and genotype–phenotype analysis was performed. The median age at diagnosis was 10.6 years (range 0–64.5 years), with 287 unique pathogenic/likely pathogenic (P/LP) variants identified, expanding NPC1 allelic heterogeneity. Importantly, 73 P/LP variants were previously unpublished. The most frequent variants detected were: c.3019C > G, p.(P1007A), c.3104C > T, p.(A1035V), and c.2861C > T, p.(S954L). Loss of function (LoF) variants were significantly associated with earlier age at diagnosis, highly increased biomarker levels, and a visceral phenotype (abnormal abdomen and liver morphology). On the other hand, the variants p.(P1007A) and p.(S954L) were significantly associated with later age at diagnosis ( p < 0.001) and mildly elevated biomarker levels ( p ≤ 0.002), consistent with the juvenile/adult form of NPC1. In addition, p.(I1061T), p.(S954L), and p.(A1035V) were associated with abnormality of eye movements (vertical supranuclear gaze palsy, p ≤ 0.05). We describe the largest and most heterogenous cohort of NPC1 patients published to date. Our results suggest that besides its utility in variant classification, the biomarker PPCS might serve to indicate disease severity/progression. In addition, we establish new genotype–phenotype relationships for “frequent” NPC1 variants.

          Related collections

          Most cited references37

          • Record: found
          • Abstract: found
          • Article: not found

          Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology

          The American College of Medical Genetics and Genomics (ACMG) previously developed guidance for the interpretation of sequence variants. 1 In the past decade, sequencing technology has evolved rapidly with the advent of high-throughput next generation sequencing. By adopting and leveraging next generation sequencing, clinical laboratories are now performing an ever increasing catalogue of genetic testing spanning genotyping, single genes, gene panels, exomes, genomes, transcriptomes and epigenetic assays for genetic disorders. By virtue of increased complexity, this paradigm shift in genetic testing has been accompanied by new challenges in sequence interpretation. In this context, the ACMG convened a workgroup in 2013 comprised of representatives from the ACMG, the Association for Molecular Pathology (AMP) and the College of American Pathologists (CAP) to revisit and revise the standards and guidelines for the interpretation of sequence variants. The group consisted of clinical laboratory directors and clinicians. This report represents expert opinion of the workgroup with input from ACMG, AMP and CAP stakeholders. These recommendations primarily apply to the breadth of genetic tests used in clinical laboratories including genotyping, single genes, panels, exomes and genomes. This report recommends the use of specific standard terminology: ‘pathogenic’, ‘likely pathogenic’, ‘uncertain significance’, ‘likely benign’, and ‘benign’ to describe variants identified in Mendelian disorders. Moreover, this recommendation describes a process for classification of variants into these five categories based on criteria using typical types of variant evidence (e.g. population data, computational data, functional data, segregation data, etc.). Because of the increased complexity of analysis and interpretation of clinical genetic testing described in this report, the ACMG strongly recommends that clinical molecular genetic testing should be performed in a CLIA-approved laboratory with results interpreted by a board-certified clinical molecular geneticist or molecular genetic pathologist or equivalent.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            The Human Gene Mutation Database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies

            The Human Gene Mutation Database (HGMD®) constitutes a comprehensive collection of published germline mutations in nuclear genes that underlie, or are closely associated with human inherited disease. At the time of writing (March 2017), the database contained in excess of 203,000 different gene lesions identified in over 8000 genes manually curated from over 2600 journals. With new mutation entries currently accumulating at a rate exceeding 17,000 per annum, HGMD represents de facto the central unified gene/disease-oriented repository of heritable mutations causing human genetic disease used worldwide by researchers, clinicians, diagnostic laboratories and genetic counsellors, and is an essential tool for the annotation of next-generation sequencing data. The public version of HGMD (http://www.hgmd.org) is freely available to registered users from academic institutions and non-profit organisations whilst the subscription version (HGMD Professional) is available to academic, clinical and commercial users under license via QIAGEN Inc.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Niemann-Pick C1 disease gene: homology to mediators of cholesterol homeostasis.

              Niemann-Pick type C (NP-C) disease, a fatal neurovisceral disorder, is characterized by lysosomal accumulation of low density lipoprotein (LDL)-derived cholesterol. By positional cloning methods, a gene (NPC1) with insertion, deletion, and missense mutations has been identified in NP-C patients. Transfection of NP-C fibroblasts with wild-type NPC1 cDNA resulted in correction of their excessive lysosomal storage of LDL cholesterol, thereby defining the critical role of NPC1 in regulation of intracellular cholesterol trafficking. The 1278-amino acid NPC1 protein has sequence similarity to the morphogen receptor PATCHED and the putative sterol-sensing regions of SREBP cleavage-activating protein (SCAP) and 3-hydroxy-3-methyl-glutaryl coenzyme A (HMG-CoA) reductase.
                Bookmark

                Author and article information

                Contributors
                Peter.Bauer@centogene.com
                Journal
                Eur J Hum Genet
                Eur J Hum Genet
                European Journal of Human Genetics
                Springer International Publishing (Cham )
                1018-4813
                1476-5438
                11 July 2023
                11 July 2023
                October 2023
                : 31
                : 10
                : 1108-1116
                Affiliations
                [1 ]GRID grid.511058.8, ISNI 0000 0004 0548 4972, CENTOGENE GmbH, ; Rostock, Germany
                [2 ]Univesrity of Rostock, ( https://ror.org/03zdwsf69) Rostock, Germany
                Author information
                http://orcid.org/0000-0003-1447-6459
                http://orcid.org/0000-0001-8402-5448
                http://orcid.org/0000-0003-3791-7050
                http://orcid.org/0000-0002-9821-2313
                http://orcid.org/0000-0001-9841-1104
                http://orcid.org/0000-0001-9414-4555
                http://orcid.org/0000-0001-9544-1877
                Article
                1408
                10.1038/s41431-023-01408-7
                10545733
                37433892
                0ab0af98-a270-4c8e-91e5-1e6b8cab3cdf
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 29 November 2022
                : 4 May 2023
                : 7 June 2023
                Categories
                Article
                Custom metadata
                © European Society of Human Genetics 2023

                Genetics
                metabolic disorders,medical genomics
                Genetics
                metabolic disorders, medical genomics

                Comments

                Comment on this article