No abstract

Vascular anomalies are variably associated with overgrowth, skeletal anomalies, and abnormalities of the brain, leptomeninges, and eye. We assembled a 16-institution network to determine the range of genetic variants associated with a spectrum of vascular anomalies with overgrowth, ranging from mild to severe. Because of the overlap between cancer-associated variants and previously described somatic variants in vascular overgrowth syndromes, we employed tumor genetic profiling via high-depth next-generation sequencing using a panel to assay affected tissue from a diverse cohort of subjects with vascular anomalies with overgrowth. Seventy-five percent (43/57) harbored pathogenic or likely pathogenic variants in 10 genes. We identified two genes (mTOR, PIK3R1) and several variants previously described in the setting of cancer but that, to our knowledge, have not been described in vascular malformations. All were identified at low variant allele frequency consistent with somatic mosaic etiology. By leveraging somatic variant detection technology typically applied to cancer in a cohort inclusive of broad phenotypic severity, we demonstrated that most vascular anomalies with overgrowth harbor postzygotic gain-of-function mutations in oncogenes. Furthermore, continued interrogation of oncogenes in benign developmental disorders could provide insight into fundamental mechanisms regulating cell growth.

Next-generation sequencing (NGS) has revolutionized the approach of studying sequence variation, and has been well described in the clinical laboratory setting for the detection of constitutional alterations, as well as somatic tumor-associated variants. It is increasingly recognized that post-zygotic somatic alteration can be associated with congenital phenotypic abnormalities. Variation within the PI3K/AKT/mTOR pathway, including PIK3CA, has been described in somatic overgrowth syndromes and vascular malformations. Detection of PIK3CA somatic alteration is challenging because of low variant allele frequency (VAF) along with the need to assay involved tissue, thus necessitating a highly sensitive methodology. Here we describe the utility of target hybrid capture coupled with NGS for the identification of somatic variation in the PIK3CA-related overgrowth spectrum (PROS) among 14 patients submitted for clinical testing. Assay detection of low allelic fraction variation is coverage dependent with >90% sensitivity at 400× unique read depth for VAF of 10%, and approaching 100% at 1000×. Average read depth among the patient dataset across PIK3CA coding regions was 788.4. The diagnostic yield among this cohort was 71%, including the detection of two PIK3CA alterations novel in the setting of PROS. This report expands the mutational scope and phenotypic attributes of PROS disorders.

Non-obstructive azoospermia (NOA) is the most severe form of male infertility and typically incurable. Defining the genetic basis of NOA has proven challenging, and the most advanced classification of NOA subforms is not based on genetics, but simple description of testis histology. In this study, we exome-sequenced over 1000 clinically diagnosed NOA cases and identified a plausible recessive Mendelian cause in 20%. We find further support for 21 genes in a 2-stage burden test with 2072 cases and 11,587 fertile controls. The disrupted genes are primarily on the autosomes, enriched for undescribed human “knockouts”, and, for the most part, have yet to be linked to a Mendelian trait. Integration with single-cell RNA sequencing data shows that azoospermia genes can be grouped into molecular subforms with synchronized expression patterns, and analogs of these subforms exist in mice. This analysis framework identifies groups of genes with known roles in spermatogenesis but also reveals unrecognized subforms, such as a set of genes expressed across mitotic divisions of differentiating spermatogonia. Our findings highlight NOA as an understudied Mendelian disorder and provide a conceptual structure for organizing the complex genetics of male infertility, which may provide a rational basis for disease classification.