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      Genotype–phenotype correlations and novel molecular insights into the DHX30-associated neurodevelopmental disorders

      research-article
      1 , 2 , 3 , 4 , 5 , 6 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 1 , 16 , 17 , 18 , 19 , 20 , 20 , 21 , 22 , 23 , 23 , 24 , 24 , 25 , 1 , 26 , 15 , 7 , 8 , 27 , 28 , 29 , 30 , 1 , 16 , 17 , 31 , 32 , 5 , 33 , 34 , 35 , 36 , 37 , 12 , 27 , 28 , 5 , 35 , 38 , 2 , 20 , 37 , 39 , 15 , 40 , 41 , 21 , 13 , 40 , 42 , 43 , 20 , 2 , 36 , 30 , 44 , 45 , 45 , 4 , 5 , 46 , 3 , 2 , , 1 , , 1 ,
      Genome Medicine
      BioMed Central

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          Abstract

          Background

          We aimed to define the clinical and variant spectrum and to provide novel molecular insights into the DHX30-associated neurodevelopmental disorder.

          Methods

          Clinical and genetic data from affected individuals were collected through Facebook-based family support group, GeneMatcher, and our network of collaborators. We investigated the impact of novel missense variants with respect to ATPase and helicase activity, stress granule (SG) formation, global translation, and their effect on embryonic development in zebrafish. SG formation was additionally analyzed in CRISPR/Cas9-mediated DHX30-deficient HEK293T and zebrafish models, along with in vivo behavioral assays.

          Results

          We identified 25 previously unreported individuals, ten of whom carry novel variants, two of which are recurrent, and provide evidence of gonadal mosaicism in one family. All 19 individuals harboring heterozygous missense variants within helicase core motifs (HCMs) have global developmental delay, intellectual disability, severe speech impairment, and gait abnormalities. These variants impair the ATPase and helicase activity of DHX30, trigger SG formation, interfere with global translation, and cause developmental defects in a zebrafish model. Notably, 4 individuals harboring heterozygous variants resulting either in haploinsufficiency or truncated proteins presented with a milder clinical course, similar to an individual harboring a de novo mosaic HCM missense variant. Functionally, we established DHX30 as an ATP-dependent RNA helicase and as an evolutionary conserved factor in SG assembly. Based on the clinical course, the variant location, and type we establish two distinct clinical subtypes. DHX30 loss-of-function variants cause a milder phenotype whereas a severe phenotype is caused by HCM missense variants that, in addition to the loss of ATPase and helicase activity, lead to a detrimental gain-of-function with respect to SG formation. Behavioral characterization of dhx30-deficient zebrafish revealed altered sleep-wake activity and social interaction, partially resembling the human phenotype.

          Conclusions

          Our study highlights the usefulness of social media to define novel Mendelian disorders and exemplifies how functional analyses accompanied by clinical and genetic findings can define clinically distinct subtypes for ultra-rare disorders. Such approaches require close interdisciplinary collaboration between families/legal representatives of the affected individuals, clinicians, molecular genetics diagnostic laboratories, and research laboratories.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13073-021-00900-3.

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          Most cited references45

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          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.
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            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.
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              Prevalence and architecture of de novo mutations in developmental disorders

              (2017)
              Summary Individuals with severe, undiagnosed developmental disorders (DDs) are enriched for damaging de novo mutations (DNMs) in developmentally important genes. We exome sequenced 4,293 families with individuals with DDs, and meta-analysed these data with another 3,287 individuals with similar disorders. We show that the most significant factors influencing the diagnostic yield of DNMs are the sex of the affected individual, the relatedness of their parents, whether close relatives are affected and parental ages. We identified 94 genes enriched for damaging DNMs, including 14 without previous compelling evidence. We have characterised the phenotypic diversity among these disorders. We estimate that 42% of our cohort carry pathogenic DNMs in coding sequences, and approximately half disrupt gene function, with the remainder resulting in altered-function. We estimate that developmental disorders caused by DNMs have an average birth prevalence of 1 in 213 to 1 in 448, depending on parental age. Given current global demographics, this equates to almost 400,000 children born per year.
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                Author and article information

                Contributors
                nyeo@uab.edu
                kreienkamp@uke.de
                d.lessel@uke.de
                Journal
                Genome Med
                Genome Med
                Genome Medicine
                BioMed Central (London )
                1756-994X
                21 May 2021
                21 May 2021
                2021
                : 13
                : 90
                Affiliations
                [1 ]GRID grid.13648.38, ISNI 0000 0001 2180 3484, Institute of Human Genetics, , University Medical Center Hamburg-Eppendorf, ; 20246 Hamburg, Germany
                [2 ]GRID grid.265892.2, ISNI 0000000106344187, Department of Pharmacology and Toxicology, , University of Alabama, ; Birmingham, USA
                [3 ]GRID grid.8379.5, ISNI 0000 0001 1958 8658, Department of Biochemistry, Theodor Boveri Institute, , Biocenter of the University of Würzburg, ; 97070 Würzburg, Germany
                [4 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, , University of California Los Angeles, ; Los Angeles, CA USA
                [5 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, UCLA Clinical Genomics Center, , University of California Los Angeles, ; Los Angeles, CA USA
                [6 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Department of Physiology, , University of California Los Angeles, ; Los Angeles, CA USA
                [7 ]GRID grid.498924.a, Manchester Centre for Genomic Medicine, St Mary’s Hospital, , Manchester University NHS Foundation Trust, Health Innovation Manchester, ; Manchester, UK
                [8 ]GRID grid.5379.8, ISNI 0000000121662407, Division of Evolution & Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, , University of Manchester, ; Manchester, UK
                [9 ]GRID grid.1012.2, ISNI 0000 0004 1936 7910, Faculty of Medicine and Health Sciences, , University of Western Australia, ; Perth, WA Australia
                [10 ]GRID grid.415259.e, ISNI 0000 0004 0625 8678, Western Australian Register of Developmental Anomalies, , King Edward Memorial Hospital, ; Perth, Australia
                [11 ]GRID grid.414659.b, ISNI 0000 0000 8828 1230, Telethon Kids Institute, ; Perth, Australia
                [12 ]GRID grid.412750.5, ISNI 0000 0004 1936 9166, Division of Child Neurology, Department of Neurology, , University of Rochester School of Medicine, ; Rochester, NY USA
                [13 ]GRID grid.410421.2, ISNI 0000 0004 0380 7336, Clinical Genetics Department, , University Hospitals Bristol and Weston, ; Bristol, UK
                [14 ]GRID grid.428608.0, ISNI 0000 0004 0444 4338, Joe DiMaggio Children’s Hospital, ; Hollywood, FL USA
                [15 ]GRID grid.412008.f, ISNI 0000 0000 9753 1393, Department of Medical Genetics, , Haukeland University Hospital, ; 5021 Bergen, Norway
                [16 ]GRID grid.411162.1, ISNI 0000 0000 9336 4276, Department of Medical Genetics, , Centre Hospitalier Universitaire de Poitiers, ; Poitiers, France
                [17 ]GRID grid.11166.31, ISNI 0000 0001 2160 6368, Laboratoire de Neurosciences Cliniques et Expérimentales-INSERM U1084, , Université de Poitiers, ; Poitiers, France
                [18 ]GRID grid.7914.b, ISNI 0000 0004 1936 7443, Department of Clinical Medicine (K1), , University of Bergen, ; Bergen, Norway
                [19 ]GRID grid.412008.f, ISNI 0000 0000 9753 1393, Department of Neurology, , Haukeland University Hospital, ; Bergen, Norway
                [20 ]GRID grid.416950.f, ISNI 0000 0004 0627 3771, Department of Medical Genetics, , Telemark Hospital Trust, ; Skien, Norway
                [21 ]GRID grid.266102.1, ISNI 0000 0001 2297 6811, Division of Medical Genetics, Department of Pediatrics, , University of California San Francisco, ; San Francisco, CA USA
                [22 ]GRID grid.13648.38, ISNI 0000 0001 2180 3484, Department of Pediatrics, , University Medical Center Eppendorf, ; 20246 Hamburg, Germany
                [23 ]GRID grid.413971.9, ISNI 0000 0000 9901 8083, Peyton Manning Children’s Hospital, , Ascension Health, ; Indianapolis, IN USA
                [24 ]GRID grid.280418.7, ISNI 0000 0001 0705 8684, Department of Pediatrics, , Southern Illinois University School of Medicine, ; Springfield, IL 62702 USA
                [25 ]GRID grid.10417.33, ISNI 0000 0004 0444 9382, Department of Pediatric Neurology, Amalia Children’s Hospital and Donders Institute for Brain, Cognition and Behavior, , Radboud University Nijmegen Medical Center, ; Nijmegen, The Netherlands
                [26 ]GRID grid.16753.36, ISNI 0000 0001 2299 3507, Division of Neurology, Department of Pediatrics, Ann and Robert H. Lurie Children’s Hospital of Chicago, , Northwestern University Feinberg School of Medicine, ; Chicago, IL USA
                [27 ]GRID grid.414896.6, Kaiser Permanente Sacramento, ; Sacramento, USA
                [28 ]GRID grid.50550.35, ISNI 0000 0001 2175 4109, Département de Génétique, Hôpital La Pitié-Salpêtrière, , Assistance Publique-Hôpitaux de Paris, ; Paris, France
                [29 ]Genetic Services of Western Australia, Perth, Western Australia 6008 Australia
                [30 ]GRID grid.5330.5, ISNI 0000 0001 2107 3311, Institute of Human Genetics, , Friedrich-Alexander-Universität Erlangen-Nürnberg, ; 91054 Erlangen, Germany
                [31 ]GRID grid.417292.b, ISNI 0000 0004 0627 3659, Department of Pediatrics, , Vestfold Hospital, ; 3116 Tønsberg, Norway
                [32 ]GRID grid.280062.e, ISNI 0000 0000 9957 7758, Department of Genetics, , Kaiser Permanente Northern California, ; Oakland, USA
                [33 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Semel Institute of Neuroscience and Human Behavior, , University of California Los Angeles, ; Los Angeles, CA USA
                [34 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Department of Pediatrics, Division of Medical Genetics at David Geffen School of Medicine, , University of California Los Angeles, ; Los Angeles, CA USA
                [35 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Department of Human Genetics at David Geffen School of Medicine University of California Los Angeles, ; Los Angeles, CA USA
                [36 ]GRID grid.265892.2, ISNI 0000000106344187, Department of Medicine, Hugh Kaul Precision Medicine Institute, , University of Alabama at Birmingham, ; 510 20th St S, Birmingham, AL 35210 USA
                [37 ]GRID grid.2515.3, ISNI 0000 0004 0378 8438, Division of Genetics and Genomics, , Boston Children’s Hospital, ; Boston, MA USA
                [38 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Center for Duchenne Muscular Dystrophy, , University of California Los Angeles, ; Los Angeles, CA USA
                [39 ]GRID grid.440886.6, ISNI 0000 0004 0594 5118, UF de Génétique Médicale, GHSR, CHU de La Réunion, ; Saint Pierre, La Réunion France
                [40 ]GRID grid.10417.33, ISNI 0000 0004 0444 9382, Department of Human Genetics, , Radboud University Medical Center, ; 6500 HB Nijmegen, the Netherlands
                [41 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Department of Neurology at David Geffen School of Medicine, , University of California Los Angeles, ; Los Angeles, CA USA
                [42 ]GRID grid.412966.e, ISNI 0000 0004 0480 1382, Department of Clinical Genetics, , Maastricht University Medical Center, ; Maastricht, The Netherlands
                [43 ]GRID grid.2515.3, ISNI 0000 0004 0378 8438, Department of Neurology, , Boston Children’s Hospital, ; Boston, MA USA
                [44 ]GRID grid.5734.5, ISNI 0000 0001 0726 5157, Department of Human Genetics, Inselspital, Bern University Hospital, , University of Bern, ; 3010 Bern, Switzerland
                [45 ]GRID grid.428467.b, GeneDx, ; Gaithersburg, MD 20877 USA
                [46 ]GRID grid.266093.8, ISNI 0000 0001 0668 7243, Department of Pathology and Laboratory Medicine, School of Medicine, , University of California Irvine, ; Irvine, CA USA
                Author information
                http://orcid.org/0000-0003-4496-244X
                Article
                900
                10.1186/s13073-021-00900-3
                8140440
                34020708
                748b4c20-d28a-47d4-b693-99a2027f1293
                © The Author(s) 2021

                Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 2 September 2020
                : 28 April 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
                Award ID: LE4223/1-1
                Award ID: Kr1321/8-2
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: U54 OD030167
                Award Recipient :
                Funded by: Universitätsklinikum Hamburg-Eppendorf (UKE) (5411)
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Molecular medicine
                Molecular medicine

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