Purpose Copy number variants (CNVs) have emerged as a major cause of human disease such as autism and intellectual disabilities. Because CNVs are common in normal individuals, determining the functional and clinical significance of rare CNVs in patients remains challenging. The adoption of whole-genome chromosomal microarray analysis (CMA) as a first-tier diagnostic test for individuals with unexplained developmental disabilities provides a unique opportunity to obtain large CNV datasets generated through routine patient care. Methods A consortium of diagnostic laboratories was established [the International Standards for Cytogenomic Arrays (ISCA) consortium] to share CNV and phenotypic data in a central, public database. We present the largest CNV case-control study to date comprising 15,749 ISCA cases and 10,118 published controls, focusing our initial analysis on recurrent deletions and duplications involving 14 CNV regions. Results Compared to controls, fourteen deletions, and seven duplications were significantly overrepresented in cases, providing a clinical diagnosis as pathogenic. Conclusion Given the rapid expansion of clinical CMA testing, very large datasets will be available to determine the functional significance of increasingly rare CNVs. This data will provide an evidenced-based guide to clinicians across many disciplines involved in the diagnosis, management, and care of these patients and their families.

Autism spectrum disorders (ASD) and schizophrenia are neurodevelopmental disorders for which recent evidence indicates an important etiologic role for rare copy number variants (CNVs) and suggests common genetic mechanisms. We performed cytogenomic array analysis in a discovery sample of patients with neurodevelopmental disorders referred for clinical testing. We detected a recurrent 1.4 Mb deletion at 17q12, which harbors HNF1B, the gene responsible for renal cysts and diabetes syndrome (RCAD), in 18/15,749 patients, including several with ASD, but 0/4,519 controls. We identified additional shared phenotypic features among nine patients available for clinical assessment, including macrocephaly, characteristic facial features, renal anomalies, and neurocognitive impairments. In a large follow-up sample, the same deletion was identified in 2/1,182 ASD/neurocognitive impairment and in 4/6,340 schizophrenia patients, but in 0/47,929 controls (corrected p = 7.37 × 10⁻⁵). These data demonstrate that deletion 17q12 is a recurrent, pathogenic CNV that confers a very high risk for ASD and schizophrenia and show that one or more of the 15 genes in the deleted interval is dosage sensitive and essential for normal brain development and function. In addition, the phenotypic features of patients with this CNV are consistent with a contiguous gene syndrome that extends beyond RCAD, which is caused by HNF1B mutations only.

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Conflict resolution in genomic variant interpretation is a critical step toward improving patient care. Evaluating interpretation discrepancies in copy number variants (CNVs) typically involves assessing overlapping genomic content with focus on genes/regions that may be subject to dosage sensitivity (haploinsufficiency (HI) and/or triplosensitivity (TS)). CNVs containing dosage sensitive genes/regions are generally interpreted as "likely pathogenic" (LP) or "pathogenic" (P), and CNVs involving the same known dosage sensitive gene(s) should receive the same clinical interpretation. We compared the Clinical Genome Resource (ClinGen) Dosage Map, a publicly available resource documenting known HI and TS genes/regions, against germline, clinical CNV interpretations within the ClinVar database. We identified 251 CNVs overlapping known dosage sensitive genes/regions but not classified as LP or P; these were sent back to their original submitting laboratories for re-evaluation. Of 246 CNVs re-evaluated, an updated clinical classification was warranted in 157 cases (63.8%); no change was made to the current classification in 79 cases (32.1%); and 10 cases (4.1%) resulted in other types of updates to ClinVar records. This effort will add curated interpretation data into the public domain and allow laboratories to focus attention on more complex discrepancies.