Pulmonary arterial hypertension (PAH) is a rare disease characterized by distinctive changes in pulmonary arterioles that lead to progressive pulmonary arterial pressures, right-sided heart failure, and a high mortality rate. Up to 30% of adult and 75% of pediatric PAH cases are associated with congenital heart disease (PAH-CHD), and the underlying etiology is largely unknown. There are no known major risk genes for PAH-CHD. To identify novel genetic causes of PAH-CHD, we performed whole exome sequencing in 256 PAH-CHD patients. We performed a case-control gene-based association test of rare deleterious variants using 7509 gnomAD whole genome sequencing population controls. We then screened a separate cohort of 413 idiopathic and familial PAH patients without CHD for rare deleterious variants in the top association gene. We identified SOX17 as a novel candidate risk gene (p = 5.5e−7). SOX17 is highly constrained and encodes a transcription factor involved in Wnt/β-catenin and Notch signaling during development. We estimate that rare deleterious variants contribute to approximately 3.2% of PAH-CHD cases. The coding variants identified include likely gene-disrupting (LGD) and deleterious missense, with most of the missense variants occurring in a highly conserved HMG-box protein domain. We further observed an enrichment of rare deleterious variants in putative targets of SOX17, many of which are highly expressed in developing heart and pulmonary vasculature. In the cohort of PAH without CHD, rare deleterious variants of SOX17 were observed in 0.7% of cases. These data strongly implicate SOX17 as a new risk gene contributing to PAH-CHD as well as idiopathic/familial PAH. Replication in other PAH cohorts and further characterization of the clinical phenotype will be important to confirm the precise role of SOX17 and better estimate the contribution of genes regulated by SOX17.

Background: Pulmonary arterial hypertension (PAH) is a rare disease characterized by pulmonary arteriole remodeling, elevated arterial pressure and resistance, and subsequent heart failure. Compared with adult-onset disease, pediatric-onset PAH is more heterogeneous and often associated with worse prognosis. Although BMPR2 mutations underlie ≈70% of adult familial PAH (FPAH) cases, the genetic basis of PAH in children is less understood. Methods: We performed genetic analysis of 155 pediatric- and 257 adult-onset PAH patients, including both FPAH and sporadic, idiopathic PAH (IPAH). After screening for 2 common PAH risk genes, mutation-negative FPAH and all IPAH cases were evaluated by exome sequencing. RESULTS: We observed similar frequencies of rare, deleterious BMPR2 mutations in pediatric- and adult-onset patients: ≈55% in FPAH and 10% in IPAH patients in both age groups. However, there was significant enrichment of TBX4 mutations in pediatric- compared with adult-onset patients (IPAH: 10/130 pediatric versus 0/178 adult-onset), and TBX4 carriers had younger mean age-of-onset compared with BMPR2 carriers. Mutations in other known PAH risk genes were infrequent in both age groups. Notably, among pediatric IPAH patients without mutations in known risk genes, exome sequencing revealed a 2-fold enrichment of de novo likely gene-damaging and predicted deleterious missense variants. Conclusions: Mutations in known PAH risk genes accounted for ≈70% to 80% of FPAH in both age groups, 21% of pediatric-onset IPAH, and 11% of adult-onset IPAH. Rare, predicted deleterious variants in TBX4 are enriched in pediatric patients and de novo variants in novel genes may explain ≈19% of pediatric-onset IPAH cases.

Background: Group 1 pulmonary arterial hypertension (PAH) is a rare disease with high mortality despite recent therapeutic advances. Pathogenic remodeling of pulmonary arterioles leads to increased pulmonary pressures, right ventricular hypertrophy, and heart failure. Mutations in bone morphogenetic protein receptor type 2 and other risk genes predispose to disease, but the vast majority of non-familial cases remain genetically undefined.Methods: To identify new risk genes, we performed exome sequencing in a large cohort from the National Biological Sample and Data Repository for PAH (PAH Biobank,n = 2572). We then carried out rare deleterious variant identification followed by case-control gene-based association analyses. To control for population structure, only unrelated European cases (n = 1832) and controls (n = 12,771) were used in association tests. Empiricalpvalues were determined by permutation analyses, and the threshold for significance defined by Bonferroni’s correction for multiple testing.Results: Tissue kallikrein 1 (KLK1) and gamma glutamyl carboxylase (GGCX) were identified as new candidate risk genes for idiopathic PAH (IPAH) with genome-wide significance. We note that variant carriers had later mean age of onset and relatively moderate disease phenotypes compared to bone morphogenetic receptor type 2 variant carriers. We also confirmed the genome-wide association of recently reported growth differentiation factor (GDF2) with IPAH and further implicate T-box 4 (TBX4) with child-onset PAH.Conclusions: We report robust association of novel genesKLK1andGGCXwith IPAH, accounting for ~ 0.4% and 0.9% of PAH Biobank cases, respectively. Both genes play important roles in vascular hemodynamics and inflammation but have not been implicated in PAH previously. These data suggest new genes, pathogenic mechanisms, and therapeutic targets for this lethal vasculopathy.

Congenital diaphragmatic hernia (CDH) is a severe birth defect that is often accompanied by other congenital anomalies. Previous exome sequencing studies for CDH have supported a role of de novo damaging variants but did not identify any recurrently mutated genes. To investigate further the genetics of CDH, we analyzed de novo coding variants in 362 proband-parent trios including 271 new trios reported in this study. We identified four unrelated individuals with damaging de novo variants in MYRF (P = 5.3x10^-8), including one likely gene-disrupting (LGD) and three deleterious missense (D-mis) variants. Eight additional individuals with de novo LGD or missense variants were identified from our other genetic studies or from the literature. Common phenotypes of MYRF de novo variant carriers include CDH, congenital heart disease and genitourinary abnormalities, suggesting that it represents a novel syndrome. MYRF is a membrane associated transcriptional factor highly expressed in developing diaphragm and is depleted of LGD variants in the general population. All de novo missense variants aggregated in two functional protein domains. Analyzing the transcriptome of patient-derived diaphragm fibroblast cells suggest that disease associated variants abolish the transcription factor activity. Furthermore, we showed that the remaining genes with damaging variants in CDH significantly overlap with genes implicated in other developmental disorders. Gene expression patterns and patient phenotypes support pleiotropic effects of damaging variants in these genes on CDH and other developmental disorders. Finally, functional enrichment analysis implicates the disruption of regulation of gene expression, kinase activities, intra-cellular signaling, and cytoskeleton organization as pathogenic mechanisms in CDH. Congenital diaphragmatic hernia (CDH) is a life-threatening condition affecting about 1 every 3000 newborns. Although the role of genetics in the pathogenesis of CDH has been well established, only a handful of disease genes have been identified so far. We and other have previously shown that de novo variants, those carried by the cases but not inherited from parents, are enriched in sporadic CDH cases consistent with their negative effects on reproductive fitness. To further investigate the genetics of CDH, we analyzed de novo variants in 362 proband-father-mother trios from whole exome or genome sequencing data and identified four patients carrying damaging variants in MYRF, a membrane associated transcription factor that is highly expressed in developing diaphragm and heart. We then ascertained a total of 12 patients with MYRF de novo variants, and found they shared common phenotype characteristics including congenital abnormalities in diaphragm, heart and reproductive organs. The high rate of recurrence and similar phenotypic manifestations suggest that de novo variants of MYRF have pleiotropic effects and cause a novel syndrome. The identified new gene is reminiscent of previously identified CDH genes (e.g., GATA4, GATA6, NR2F2, ZFPM2, and WT1) that are also associated with other developmental disorders. Indeed, we found in our cohort more than 20 damaging de novo variants in genes implicated in other developmental disorders but not previously linked to CDH. The overlap was unlikely to occur by chance and can be best explained by their pleiotropic effects. We also showed that, despite the shared genetic basis with other disorders, damaging de novo variants in CDH as a whole were enriched in specific functional pathways that recapitulated our current knowledge about diaphragm development. So additional candidate genes can be prioritized based on the genetic pleiotropy and functional specificity. The findings have general implications in design and analysis in genetic studies of rare birth defects.

Purpose Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. Methods Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. Results The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20–89% and the top 10 accuracy rate by more than 5–99% for the disease-causing gene. Conclusion Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis.