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      Prevalence and phenotypic impact of rare potentially damaging variants in autism spectrum disorder

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          Abstract

          Background

          The Autism Sequencing Consortium identified 102 high-confidence autism spectrum disorder (ASD) genes, showing that individuals with ASD and with potentially damaging single nucleotide variation (pdSNV) in these genes had lower cognitive levels and delayed age at walking, when compared to ASD participants without pdSNV. Here, we made use of a Swedish sample of individuals with ASD (called PAGES, for Population-Based Autism Genetics & Environment Study) to evaluate the frequency of pdSNV and their impact on medical and psychiatric phenotypes, using an epidemiological frame and universal health reporting. We then combine findings with those for potentially damaging copy number variation (pdCNV).

          Methods

          SNV and CNV calls were generated from whole-exome sequencing and chromosome microarray data, respectively. Birth and medical register data were used to collect phenotypes.

          Results

          Of 808 individuals assessed by sequencing, 69 (9%) had pdSNV in the 102 ASC genes, and 144 (18%) had pdSNV in the 102 ASC genes or in a larger set of curated neurodevelopmental genes (from the Deciphering Developmental Disorders study, the gene2phenotype database, and the Radboud University gene lists). Three or more individuals had pdSNV in GRIN2B, POGZ, SATB1, DYNC1H1, SCN8A, or CREBBP. In comparison, out of the 996 individuals from whom CNV were called, 105 (11%) carried one or more pdCNV, including four or more individuals with CNV in the recurrent 15q11q13, 22q11.2, and 16p11.2 loci. Carriers of pdSNV were more likely to have intellectual disability (ID) and epilepsy, while carriers of pdCNV showed increased rates of congenital anomalies and scholastic skill disorders. Carriers of either pdSNV or pdCNV were more likely to have ID, scholastic skill disorders, and epilepsy.

          Limitations

          The cohort only included individuals with autistic disorder, the more severe form of ASD, and phenotypes are defined from medical registers. Not all genes studied are definitively ASD genes, and we did not have de novo information to aid in classification.

          Conclusions

          In this epidemiological sample, rare pdSNV were more common than pdCNV and the combined yield of potentially damaging variation was substantial at 27%. The results provide compelling rationale for the use of high-throughout sequencing as part of routine clinical workup for ASD and support the development of precision medicine in ASD.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13229-021-00465-3.

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          Most cited references32

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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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            Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism

            We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n = 35,584 total samples, 11,986 with ASD). Using an enhanced analytical framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate of 0.1 or less. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained to have severe neurodevelopmental delay, whereas 53 show higher frequencies in individuals ascertained to have ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In cells from the human cortex, expression of risk genes is enriched in excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.
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              Technical standards for the interpretation and reporting of constitutional copy number variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen)

              Copy number analysis to detect disease-causing losses and gains across the genome is recommended for the evaluation of individuals with neurodevelopmental disorders and/or multiple congenital anomalies, as well as for fetuses with ultrasound abnormalities. In the decade that this analysis has been in widespread clinical use, tremendous strides have been made in understanding the effects of copy number variants (CNVs) in both affected individuals and the general population. However, continued broad implementation of array- and next-generation sequencing-based technologies will expand the types of CNVs encountered in the clinical setting, as well as our understanding of their impact on human health. To assist clinical laboratories in the classification and reporting of CNVs, irrespective of the technology used to identify them, the American College of Medical Genetics and Genomics has developed the following professional standards in collaboration with the NIH-funded Clinical Genome Resource (ClinGen) project. This update introduces a quantitative, evidence-based scoring framework; encourages the implementation of the 5-tier classification system widely used in sequence variant classification; and recommends “uncoupling” the evidence-based classification of a variant from its potential implications for a particular individual. These professional standards will guide the evaluation of constitutional CNVs and encourage consistency and transparency across clinical laboratories.
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                Author and article information

                Contributors
                Joseph.Buxbaum@mssm.edu
                Journal
                Mol Autism
                Mol Autism
                Molecular Autism
                BioMed Central (London )
                2040-2392
                6 October 2021
                6 October 2021
                2021
                : 12
                : 65
                Affiliations
                [1 ]GRID grid.59734.3c, ISNI 0000 0001 0670 2351, Seaver Autism Center for Research and Treatment, , Icahn School of Medicine at Mount Sinai, ; New York, NY 10029 USA
                [2 ]GRID grid.59734.3c, ISNI 0000 0001 0670 2351, Department of Psychiatry, , Icahn School of Medicine at Mount Sinai, ; New York, NY USA
                [3 ]GRID grid.4714.6, ISNI 0000 0004 1937 0626, Department of Medical Epidemiology and Biostatistics, , Karolinska Institutet, ; Stockholm, Sweden
                [4 ]GRID grid.59734.3c, ISNI 0000 0001 0670 2351, Friedman Brain Institute, , Icahn School of Medicine at Mount Sinai, ; New York, NY USA
                [5 ]GRID grid.59734.3c, ISNI 0000 0001 0670 2351, The Mindich Child Health and Development Institute, , Icahn School of Medicine at Mount Sinai, ; New York, USA
                [6 ]GRID grid.21925.3d, ISNI 0000 0004 1936 9000, Department of Psychiatry, , University of Pittsburgh School of Medicine, ; Pittsburgh, PA USA
                [7 ]GRID grid.66859.34, Stanley Center for Psychiatric Research, , Broad Institute of MIT and Harvard, ; Cambridge, MA USA
                [8 ]GRID grid.66859.34, Program in Medical and Population Genetics, , Broad Institute of MIT and Harvard, ; Cambridge, MA USA
                [9 ]GRID grid.32224.35, ISNI 0000 0004 0386 9924, Center for Genomic Medicine, , Massachusetts General Hospital, ; Boston, MA USA
                [10 ]GRID grid.38142.3c, ISNI 000000041936754X, Department of Neurology, , Massachusetts General Hospital and Harvard Medical School, ; Boston, MA USA
                [11 ]GRID grid.147455.6, ISNI 0000 0001 2097 0344, Department of Statistics, , Carnegie Mellon University, ; Pittsburgh, PA USA
                [12 ]GRID grid.59734.3c, ISNI 0000 0001 0670 2351, Department of Genetics and Genomic Sciences, , Icahn School of Medicine at Mount Sinai, ; New York, NY USA
                [13 ]GRID grid.59734.3c, ISNI 0000 0001 0670 2351, Department of Neuroscience, , Icahn School of Medicine at Mount Sinai, ; New York, NY USA
                Author information
                http://orcid.org/0000-0001-6087-9537
                http://orcid.org/0000-0001-9383-6883
                http://orcid.org/0000-0003-4524-4968
                http://orcid.org/0000-0001-6187-7680
                http://orcid.org/0000-0003-2889-0992
                http://orcid.org/0000-0001-6994-4884
                http://orcid.org/0000-0002-0327-2410
                http://orcid.org/0000-0002-8833-2549
                http://orcid.org/0000-0002-8869-6254
                http://orcid.org/0000-0003-2524-4290
                http://orcid.org/0000-0001-8898-8313
                Article
                465
                10.1186/s13229-021-00465-3
                8495954
                34615535
                95d96118-fa4b-4b87-940a-e05660587f47
                © 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
                : 5 November 2020
                : 2 September 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100012695, Beatrice and Samuel A. Seaver Foundation;
                Funded by: FundRef http://dx.doi.org/10.13039/100000025, National Institute of Mental Health;
                Award ID: R01MH097849
                Award ID: R01MH097849-S1
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Neurosciences
                autism spectrum disorder,copy number variant,single nucleotide variant,intellectual disability,whole exome sequencing,pages

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