The myelin regulatory factor gene (MYRF) encodes a transcription factor that is widely expressed. There is increasing evidence that heterozygous loss-of-function variants in MYRF can lead to abnormal development of the heart, genitourinary tract, diaphragm, and lungs. Here, we searched a clinical database containing the results of 12,000 exome sequencing studies. We identified three previously unreported males with putatively deleterious variants in MYRF: one with a point mutation predicted to affect splicing and two with frameshift variants. In all cases where parental DNA was available, these variants were found to have arisen de novo. The phenotypes identified in these subjects included a variety of congenital heart defects (hypoplastic left heart syndrome, scimitar syndrome, septal defects, and valvular anomalies), genitourinary anomalies (ambiguous genitalia, hypospadias, and cryptorchidism), congenital diaphragmatic hernia, and pulmonary hypoplasia. The phenotypes seen in our subjects overlap those described in individuals diagnosed with PAGOD syndrome [MIM# 202660], a clinically defined syndrome characterized by pulmonary artery and lung hypoplasia, agonadism, omphalocele, and diaphragmatic defects that can also be associated with hypoplastic left heart and scimitar syndrome. These cases provide additional evidence that haploinsufficiency of MYRF causes a genetic syndrome whose cardinal features include congenital heart defects, urogenital anomalies, congenital diaphragmatic hernia, and pulmonary hypoplasia. We also conclude that consideration should be given to screening individuals with PAGOD for pathogenic variants in MYRF, and that individuals with MYRF

IMPORTANCE Recent advances in newborn screening (NBS) have improved the diagnosis of inborn errors of metabolism (IEMs); however, many potentially treatable IEMs are not included on NBS panels, nor are they covered in standard, first-line biochemical testing.OBJECTIVE To examine the utility of untargeted metabolomics as a primary screening tool for IEMs by comparing the diagnostic rate of clinical metabolomics with the recommended traditional metabolic screening approach.

Purpose: A primary barrier to improving exome sequencing diagnostic rates is the interpretation of variants of uncertain clinical significance. We aimed to determine the contribution of integrated untargeted metabolomics in the analysis of exome sequencing data by retrospective analysis of patients evaluated by both whole exome sequencing and untargeted metabolomics within the same clinical laboratory. Methods: Exome sequencing and untargeted metabolomic data were collected and analyzed for 170 patients. Pathogenic variants, likely pathogenic variants, and variants of uncertain significance in genes associated with a biochemical phenotype were extracted. Metabolomic data were evaluated to determine if these variants resulted in biochemical abnormalities which could be used to support their interpretation using current ACMG guidelines. Results: Metabolomic data contributed to the interpretation variants in 74 individuals (43.5%) over 73 different genes. The data allowed for the re-classification of 9 variants as likely benign, 15 variants as likely pathogenic, and 3 variants as pathogenic. Metabolomic data confirmed a clinical diagnosis in 21 cases, for a diagnostic rate of 12.3% in this population. Conclusion: Untargeted metabolomics can serve as a useful adjunct to exome sequencing by providing valuable functional data that may not otherwise be clinically available, resulting in improved variant classification.

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Autism spectrum disorders (ASDs) are a group of neurodevelopment disorders characterized by childhood onset deficits in social communication and interaction. Although the exact etiology of most cases of ASDs is unknown, a portion has been proposed to be associated with various metabolic abnormalities including mitochondrial dysfunction, disorders of cholesterol metabolism, and folate abnormalities. Targeted biochemical testing like plasma amino acid and acylcarnitine profiles have demonstrated limited utility in helping to diagnose and manage such patients. Untargeted metabolomics has emerged, however, as a promising tool in screening for underlying biochemical abnormalities and managing treatment and as a means of investigating possible novel biomarkers for the disorder. Here, we review the principles and methodology behind untargeted metabolomics, recent pilot studies utilizing this technology, and areas in which it may be integrated into the care of children with this disorder in the future.