Despite the advances in high-throughput sequencing, many rare disease patients remain undiagnosed. In particular, the patients with well-defined clinical phenotypes and established clinical diagnosis, yet missing or partial genetic diagnosis, may hold a clue to more complex genetic mechanisms of a disease that could be missed by available clinical tests. Here, we report a patient with a clinical diagnosis of Tuberous sclerosis, combined with unusual secondary features, but negative clinical tests including TSC1 and TSC2 Short-read whole-genome sequencing combined with advanced bioinformatics analyses were successful in uncovering a de novo pericentric 87-Mb inversion with breakpoints in TSC2 and ANKRD11, which explains the TSC clinical diagnosis, and confirms a second underlying monogenic disorder, KBG syndrome. Our findings illustrate how complex variants, such as large inversions, may be missed by clinical tests and further highlight the importance of well-defined clinical diagnoses in uncovering complex molecular mechanisms of a disease, such as complex variants and "double trouble" effects.

Four children in three unrelated families (one consanguineous) presented with lethargy, hyperlactatemia, and hyperammonemia of unexplained origin during the neonatal period and early childhood. We identified and validated three different CA5A alterations, including a homozygous missense mutation (c.697T>C) in two siblings, a homozygous splice site mutation (c.555G>A) leading to skipping of exon 4, and a homozygous 4 kb deletion of exon 6. The deleterious nature of the homozygous mutation c.697T>C (p.Ser233Pro) was demonstrated by reduced enzymatic activity and increased temperature sensitivity. Carbonic anhydrase VA (CA-VA) was absent in liver in the child with the homozygous exon 6 deletion. The metabolite profiles in the affected individuals fit CA-VA deficiency, showing evidence of impaired provision of bicarbonate to the four enzymes that participate in key pathways in intermediary metabolism: carbamoylphosphate synthetase 1 (urea cycle), pyruvate carboxylase (anaplerosis, gluconeogenesis), propionyl-CoA carboxylase, and 3-methylcrotonyl-CoA carboxylase (branched chain amino acids catabolism). In the three children who were administered carglumic acid, hyperammonemia resolved. CA-VA deficiency should therefore be added to urea cycle defects, organic acidurias, and pyruvate carboxylase deficiency as a treatable condition in the differential diagnosis of hyperammonemia in the neonate and young child.

Over the last decades, a growing spectrum of monogenic disorders of human magnesium homeostasis has been clinically characterized, and genetic studies in affected individuals have identified important molecular components of cellular and epithelial magnesium transport. Here, we describe three infants who are from non-consanguineous families and who presented with a disease phenotype consisting of generalized seizures in infancy, severe hypomagnesemia, and renal magnesium wasting. Seizures persisted despite magnesium supplementation and were associated with significant intellectual disability. Whole-exome sequencing and conventional Sanger sequencing identified heterozygous de novo mutations in the catalytic Na+, K+-ATPase α1 subunit (ATP1A1). Functional characterization of mutant Na+, K+-ATPase α1 subunits in heterologous expression systems revealed not only a loss of Na+, K+-ATPase function but also abnormal cation permeabilities, which led to membrane depolarization and possibly aggravated the effect of the loss of physiological pump activity. These findings underline the indispensable role of the α1 isoform of the Na+, K+-ATPase for renal-tubular magnesium handling and cellular ion homeostasis, as well as maintenance of physiologic neuronal activity.

Distal hereditary motor neuropathies represent a group of rare genetic disorders characterized by progressive distal motor weakness without sensory loss. Their genetic heterogeneity is high and thus eligible for diagnostic whole exome sequencing. The authors report successful application of whole exome sequencing in diagnosing a second consanguineous family with distal hereditary motor neuropathy due to a homozygous c.151+1G>T variant in SIGMAR1. This variant was recently proposed as causal for the same condition in a consanguineous Chinese family. Compared to this family, the Afghan ethnic origin of our patient is distinct, yet the features are identical, validating the SIGMAR1 deficiency phenotype: progressive muscle wasting/weakness in lower and upper limbs without sensory loss. Rapid disease progression during adolescent growth is similar and may be due to SIGMAR1's role in regulating axon elongation and tau phosphorylation. Finally, the authors conclude that SIGMAR1 deficiency should be added to the differential diagnosis of distal hereditary motor neuropathies.

Many inborn errors of metabolism (IEMs) are amenable to treatment, therefore early diagnosis is imperative. Whole-exome sequencing (WES) variant prioritization coupled with phenotype-guided clinical and bioinformatics expertise is typically used to identify disease-causing variants; however, it can be challenging to identify the causal candidate gene when a large number of rare and potentially pathogenic variants are detected. Here, we present a network-based approach, metPropagate, that uses untargeted metabolomics (UM) data from a single patient and a group of controls to prioritize candidate genes in patients with suspected IEMs. We validate metPropagate on 107 patients with IEMs diagnosed in Miller et al. (2015) and 11 patients with both CNS and metabolic abnormalities. The metPropagate method ranks candidate genes by label propagation, a graph-smoothing algorithm that considers each gene's metabolic perturbation in addition to the network of interactions between neighbors. metPropagate was able to prioritize at least one causative gene in the top 20th percentile of candidate genes for 92% of patients with known IEMs. Applied to patients with suspected neurometabolic disease, metPropagate placed at least one causative gene in the top 20th percentile in 9/11 patients, and ranked the causative gene more highly than Exomiser's phenotype-based ranking in 6/11 patients. Interestingly, ranking by a weighted combination of metPropagate and Exomiser scores resulted in improved prioritization. The results of this study indicate that network-based analysis of UM data can provide an additional mode of evidence to prioritize causal genes in patients with suspected IEMs.

Guanidinoacetate methyltransferase (GAMT) deficiency is a creatine deficiency disorder and an inborn error of metabolism presenting with progressive intellectual and neurological deterioration. As most cases are identified and treated in early childhood, adult phenotypes that can help in understanding the natural history of the disorder are rare. We describe two adult cases of GAMT deficiency from a consanguineous family in Pakistan that presented with a history of global developmental delay, cognitive impairments, excessive drooling, behavioral abnormalities, contractures and apparent bone deformities initially presumed to be the reason for abnormal gait. Exome sequencing identified a homozygous nonsense variant in GAMT: NM_000156.5:c.134G>A (p.Trp45*). We also performed a literature review and compiled the genetic and clinical characteristics of all adult cases of GAMT deficiency reported to date. When compared to the adult cases previously reported, the musculoskeletal phenotype and the rapidly progressive nature of neurological and motor decline seen in our patients is striking. This study presents an opportunity to gain insights into the adult presentation of GAMT deficiency and highlights the need for in-depth evaluation and reporting of clinical features to expand our understanding of the phenotypic spectrum.

Intragenic modifiers (in-phase, second-site variants) are known to have dramatic effects on clinical outcomes, affecting disease attributes such as severity or age of onset. However, despite their clinical importance, the focus of many genetic screens in model systems is on the discovery of extragenic variants, with many labs still relying upon more traditional methods to identify modifiers. However, traditional methods such as PCR and Sanger sequencing can be time-intensive and do not permit a thorough understanding of the intragenic modifier effects in the context of non-isogenic genomic backgrounds.

Doxorubicin is an anthracycline chemotherapy agent effective in treating a wide range of malignancies, but its use is limited by dose-dependent cardiotoxicity. A recent genome-wide association study identified a SNP (rs2229774) in retinoic acid receptor-γ (RARG) as statistically associated with increased risk of anthracycline-induced cardiotoxicity. Here, we show that human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from patients with rs2229774 and who suffered doxorubicin-induced cardiotoxicity (DIC) are more sensitive to doxorubicin. We determine that the mechanism of this RARG variant effect is mediated via suppression of topoisomerase 2β (TOP2B) expression and activation of the cardioprotective extracellular regulated kinase (ERK) pathway. We use patient-specific hiPSC-CMs as a drug discovery platform, determining that the RARG agonist CD1530 attenuates DIC, and we confirm this cardioprotective effect in an established in vivo mouse model of DIC. This study provides a rationale for clinical prechemotherapy genetic screening for rs2229774 and a foundation for the clinical use of RARG agonist treatment to protect cancer patients from DIC.

Thousands of genes have been associated with different Mendelian conditions. One of the valuable sources to track these gene-disease associations (GDAs) is the Online Mendelian Inheritance in Man (OMIM) database. However, most of the information in OMIM is textual, and heterogeneous (e.g. summarized by different experts), which complicates automated reading and understanding of the data. Here, we used Natural Language Processing (NLP) to make a tool (Gene-Phenotype Association Discovery (GPAD)) that could syntactically process OMIM text and extract the data of interest.