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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. This Article was originally published without the accompanying supplementary file “All evaluated CNVs”. This file is now available in the HTML version of the Article; the PDF was correct from the time of publication. A Correction to this paper has been published: https://doi.org/10.1038/s41436-021-01150-9 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 National Institutes of Health (NIH)–funded Clinical Genome Resource (ClinGen) project. This update introduces a quantitative, evidence-based scoring framework; encourages the implementation of the five-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.

This large, systematic study of prenatal diagnosis shows that chromosomal microarray analysis provided additional, clinically significant cytogenetic information as compared with karyotyping but did not identify triploidies and balanced translocations. The development of array-based molecular cytogenetic techniques has improved the detection of small genomic deletions and duplications (called copy-number variants) that are not routinely seen on karyotyping, the standard cytogenetic analysis performed. Copy-number variants result in a variation from the expected number of copies of a segment of DNA (i.e., the number in a normal genome). Copy-number variants can be either benign or pathogenic, depending on their location and genetic content. They are identified with the use of chromosomal microarray analysis in which a test sample of DNA from the patient is compared directly or indirectly with a reference (normal) . . .

A Correction to this paper has been published: https://doi.org/10.1038/s41436-021-01150-9

The assignment of pathogenic status to genetic variants has been stymied by conflicting study results and lack of a publicly accessible database, such as ClinVar, which is now part of the Clinical Genome Resource. On autopsy, a patient is found to have hypertrophic cardiomyopathy. The patient’s family pursues genetic testing that shows a “likely pathogenic” variant for the condition on the basis of a study in an original research publication. Given the dominant inheritance of the condition and the risk of sudden cardiac death, other family members are tested for the genetic variant to determine their risk. Several family members test negative and are told that they are not at risk for hypertrophic cardiomyopathy and sudden cardiac death, and those who test positive are told that they need to be regularly monitored for cardiomyopathy . . .

Purpose Chromosomal microarray (CMA) is recommended as the first-tier test in evaluation of individuals with neurodevelopmental disability and congenital anomalies. CMA may not detect balanced cytogenomic abnormalities or uniparental disomy (UPD), and deletion/duplications and regions of homozygosity may require additional testing to clarify the mechanism and inform accurate counseling. We conducted an evidence review to synthesize data regarding the benefit of additional testing after CMA to inform a genetic diagnosis. Methods The review was guided by key questions related to the detection of genomic events that may require additional testing. A PubMed search for original research articles, systematic reviews, and meta-analyses was evaluated from articles published between 1 January 1983 and 31 March 2017. Based on the key questions, articles were retrieved and data extracted in parallel with comparison of results and discussion to resolve discrepancies. Variables assessed included study design and outcomes. Results A narrative synthesis was created for each question to describe the occurrence of, and clinical significance of, additional diagnostic findings from subsequent testing performed after CMA. Conclusion These findings may be used to assist the laboratory and clinician when making recommendations about additional testing after CMA, as it impacts clinical care, counseling, and diagnosis.

A female protective effect has long been postulated as the primary explanation for the four-fold increase of autism spectrum disorder (ASD) diagnoses in males versus females. However, genetic and epidemiological investigations of this hypothesis have so far failed to explain the large difference in ASD prevalence between the sexes. To address this knowledge gap, we examined sex chromosome aneuploidy in a large ASD case-control cohort to evaluate the relationship between X and Y chromosome dosage and ASD risk. From these data, we modeled three relationships between sex chromosome dosage and ASD risk: the extra Y effect, the extra X effect, and sex chromosome haploinsufficiency. We found that the extra Y effect increased ASD risk significantly more than the extra X effect. Among females, we observed a large association between 45, X and ASD, confirming sex chromosome haploinsufficiency as a strong ASD risk factor. These results provide a framework for understanding the relationship between X and Y chromosome dosage on ASD, which may inform future research investigating genomic contributors to the observed sex difference. Genetic and epidemiological investigations have yet to reveal what drives the large difference in ASD prevalence between the sexes. Here authors examine chromosome aneuploidy in a large ASD case-control cohort and report sex chromosome haploinsufficiency is a strong ASD risk factor, while the extra Y effect increases ASD risk significantly more than the extra X effect.

Purpose Variant classifications and gene–disease relationships may evolve. Professional societies have suggested patients share the responsibility to remain up-to-date on the implications genetic results have on their health, and that novel methods of recontact are needed. GenomeConnect, the ClinGen patient registry, has implemented a process to provide variant classification and gene–disease relationship updates to participants. Here, we report on our experience with this recontacting process. Methods GenomeConnect shares data with ClinVar and Matchmaker Exchange enabling the identification of updates to variant classifications and gene–disease relationships. For any updates identified, the reporting laboratory is contacted, and updates are shared with participants opting to receive them. Results Of 1,419 variants shared with ClinVar by GenomeConnect, 49 (3.4%) variant reclassifications were identified and 34 were shared with participants. Of 97 candidate genes submitted to Matchmaker Exchange, 10 (10.3%) gene–disease relationships have been confirmed and 9 were shared with participants. Details available from a subset of participants highlight that updated information is not always shared with the patient by testing laboratories. Conclusion Patient registries can provide a mechanism for patients and their providers to remain informed about changes to the interpretation and clinical significance of their genetic results, leading to important implications for care. Graphical Abstract