Inviting an author to review:
Find an author and click ‘Invite to review selected article’ near their name.
Search for authorsSearch for similar articles
3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      De novo mutations in childhood cases of sudden unexplained death that disrupt intracellular Ca 2+ regulation

      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.

          Significance

          Approximately 400 United States children 1 y of age and older die suddenly from unexplained causes annually. We studied whole-exome sequence data from 124 “trios” (decedent child and living parents) to identify genetic risk factors. Nonsynonymous mutations, mostly de novo (present in child but absent in both biological parents), were highly enriched in genes associated with cardiac and seizure disorders relative to controls, and contributed to 9% of deaths. We found significant overtransmission of loss-of-function or pathogenic missense variants in cardiac and seizure disorder genes. Most pathogenic variants were de novo in origin, highlighting the importance of trio studies. Many of these pathogenic de novo mutations altered a protein network regulating calcium-related excitability at submembrane junctions in cardiomyocytes and neurons.

          Abstract

          Sudden unexplained death in childhood (SUDC) is an understudied problem. Whole-exome sequence data from 124 “trios” (decedent child, living parents) was used to test for excessive de novo mutations (DNMs) in genes involved in cardiac arrhythmias, epilepsy, and other disorders. Among decedents, nonsynonymous DNMs were enriched in genes associated with cardiac and seizure disorders relative to controls (odds ratio = 9.76, P = 2.15 × 10 −4). We also found evidence for overtransmission of loss-of-function (LoF) or previously reported pathogenic variants in these same genes from heterozygous carrier parents (11 of 14 transmitted, P = 0.03). We identified a total of 11 SUDC proband genotypes (7 de novo, 1 transmitted parental mosaic, 2 transmitted parental heterozygous, and 1 compound heterozygous) as pathogenic and likely contributory to death, a genetic finding in 8.9% of our cohort. Two genes had recurrent missense DNMs, RYR2 and CACNA1C. Both RYR2 mutations are pathogenic ( P = 1.7 × 10 −7) and were previously studied in mouse models. Both CACNA1C mutations lie within a 104-nt exon ( P = 1.0 × 10 −7) and result in slowed L-type calcium channel inactivation and lower current density. In total, six pathogenic DNMs can alter calcium-related regulation of cardiomyocyte and neuronal excitability at a submembrane junction, suggesting a pathway conferring susceptibility to sudden death. There was a trend for excess LoF mutations in LoF intolerant genes, where 1 nonhealthy sample in denovo-db has a similar variant (odds ratio = 6.73, P = 0.02); additional uncharacterized genetic causes of sudden death in children might be discovered with larger cohorts.

          Related collections

          Most cited references66

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

          Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            The mutational constraint spectrum quantified from variation in 141,456 humans

            Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Analysis of protein-coding genetic variation in 60,706 humans

              Summary Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. We describe the aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of truncating variants with 72% having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human “knockout” variants in protein-coding genes.
                Bookmark

                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc Natl Acad Sci U S A
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                20 December 2021
                28 December 2021
                20 December 2021
                : 118
                : 52
                : e2115140118
                Affiliations
                [1] aDepartment of Genetics, University of North Carolina at Chapel Hill , Chapel Hill, NC 27599;
                [2] bInstitute for Genomic Medicine at Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center , New York, NY 10032;
                [3] cComprehensive Epilepsy Center, New York University Grossman School of Medicine , New York, NY 10016;
                [4] dSudden Unexplained Death in Childhood Foundation , Roseland, NJ 07068;
                [5] eNeuroscience Institute, New York University Grossman School of Medicine, New York University , New York, NY 10016;
                [6] fDepartment of Neuroscience and Physiology, New York University , New York, NY 10016;
                [7] gInstitute for Systems Genetics, New York University Grossman School of Medicine , New York, NY 10016;
                [8] hDepartment of Pediatrics, New York University Grossman School of Medicine , New York, NY 10016;
                [9] iDivision of Heart Rhythm Services, Department of Cardiovascular Medicine, Windland Smith Rice Genetic Heart Rhythm Clinic and Windland Smith Rice Sudden Death Genomics Laboratory, Mayo Clinic , Rochester, MN 55902;
                [10] jDivision of Pediatric Cardiology, Department of Pediatric and Adolescent Medicine, Windland Smith Rice Genetic Heart Rhythm Clinic and Windland Smith Rice Sudden Death Genomics Laboratory, Mayo Clinic , Rochester, MN 55902;
                [11] kDepartment of Molecular Pharmacology & Experimental Therapeutics, Windland Smith Rice Genetic Heart Rhythm Clinic and Windland Smith Rice Sudden Death Genomics Laboratory, Mayo Clinic , Rochester, MN 55902;
                [12] lDepartment of Laboratory Medicine and Pathology, Mayo Clinic , Rochester, MN 55902
                Author notes
                3To whom correspondence may be addressed. Email: richard.tsien@ 123456nyulangone.org or Orrin.Devinsky@ 123456nyulangone.org .

                Contributed by Richard W. Tsien, October 17, 2021 (sent for review August 17, 2021; reviewed by Alfred L. George and Geoffrey S. Pitt)

                Author contributions: M.H., L.G., X.W., G.G., R.M., M.T.M., D.B.G., R.W.T., and O.D. designed research; M.H., L.G., X.W., G.G., R.M., and R.R. performed research; M.H., L.G., X.W., G.G., R.M., M.T.M., D.B.G., R.W.T., and O.D. analyzed data; R.R., M.J.A., D.J.T., P.T.L., J.G.P., M.T.M., D.B.G., and O.D. contributed new reagents/analytic tools; and M.H., L.G., X.W., G.G., R.W.T., and O.D. wrote the paper.

                1M.H., L.G., and X.W. contributed equally to this work.

                Author information
                https://orcid.org/0000-0001-7428-9722
                https://orcid.org/0000-0003-0044-4632
                Article
                202115140
                10.1073/pnas.2115140118
                8719874
                34930847
                3cb9dc7a-d079-41e9-b9d7-c4f0cae891fb
                Copyright © 2021 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).

                History
                : 20 October 2021
                Page count
                Pages: 9
                Funding
                Funded by: SUDC Foundation
                Award ID: NA
                Award Recipient : Matthew Halvorsen Award Recipient : Laura Gould Award Recipient : Xiaohan Wang Award Recipient : Gariel Grant Award Recipient : Raquel Moya Award Recipient : Rachel Rabin Award Recipient : Michael J. Ackerman Award Recipient : David J. Tester Award Recipient : Peter T Lin Award Recipient : John G Pappas Award Recipient : Matthew Maurano Award Recipient : David B Goldstein Award Recipient : Richard W. Tsien Award Recipient : Orrin Devinsky
                Funded by: Finding A Cure for Epilepsy and Seizures (FACES) 100007321
                Award ID: NA
                Award Recipient : Matthew Halvorsen Award Recipient : Laura Gould Award Recipient : Xiaohan Wang Award Recipient : Gariel Grant Award Recipient : Raquel Moya Award Recipient : Rachel Rabin Award Recipient : Michael J. Ackerman Award Recipient : David J. Tester Award Recipient : Peter T Lin Award Recipient : John G Pappas Award Recipient : Matthew Maurano Award Recipient : David B Goldstein Award Recipient : Richard W. Tsien Award Recipient : Orrin Devinsky
                Funded by: HHS | NIH | National Institute on Drug Abuse (NIDA) 100000026
                Award ID: DA040484
                Award Recipient : Xiaohan Wang Award Recipient : Gariel Grant Award Recipient : Raquel Moya Award Recipient : Richard W. Tsien
                Funded by: HHS | NIH | National Institute of Mental Health (NIMH) 100000025
                Award ID: MH71739
                Award Recipient : Xiaohan Wang Award Recipient : Gariel Grant Award Recipient : Raquel Moya Award Recipient : Richard W. Tsien
                Funded by: Mayo Clinic Windland Smith Rice Comprehensive Sudden Cardiac Death Program
                Award ID: NA
                Award Recipient : Matthew Halvorsen Award Recipient : Laura Gould Award Recipient : Xiaohan Wang Award Recipient : Gariel Grant Award Recipient : Raquel Moya Award Recipient : Rachel Rabin Award Recipient : Michael J. Ackerman Award Recipient : David J. Tester Award Recipient : Peter T Lin Award Recipient : John G Pappas Award Recipient : Matthew Maurano Award Recipient : David B Goldstein Award Recipient : Richard W. Tsien Award Recipient : Orrin Devinsky
                Categories
                422
                Biological Sciences
                Medical Sciences

                sudden death in children,cardiac arrhythmia,seizure disorder,genetics,calcium signaling

                Comments

                Comment on this article