Diagnosis of Genetic White Matter Disorders by Singleton Whole-Exome and Genome Sequencing Using Interactome-Driven Prioritization

Acute neurological regression following fever as presenting sign of pontocerebellar hypoplasia type 2D (SEPSECS mutation)

Pontocerebellar hypoplasia type 2D (PCH2D) is caused by mutations in the gene encoding O-phosphoseryl-tRNA:selenocysteinyl-tRNA synthase (SEPSECS; chromosome 4p15.2). This is a key enzyme in the biosynthesis of selenoproteins, which act in maintaining antioxidant systems. To date, 26 patients with PCH2D have been reported, all with neurological involvement characterized by progressive pontocerebellar and cerebral atrophy. The present study reports on a patient with compound heterozygosity in the SEPSECS gene, including a novel missense variant, c.440G>A (p.Ser147Asn). The patient exhibited acute neurological regression following a vaccination-related fever, which is reminiscent of primary mitochondrial disease. In addition, the patient displayed severe spastic tetraparesis, convergent strabismus and postnatal onset of microcephaly, as well as recurrent blood lactate elevation. Brain MRI showed multiple alterations in the peri/supraventricular and subcortical white matter and progressive pontocerebellar and cerebral atrophy. A review of the clinical spectrum associated with SEPSECS mutations was conducted and the first report on a patient with SEPSECS mutations of acute neurological regression following a catabolic stressor at the onset of PCH2D was provided. This study broadens the genetic background of PCH2D and associated PCH2D phenotype, supporting the causal link between selenoprotein biosynthesis deficiency and mitochondrial disorders.

Intracranial calcifications simulating Aicardi-Goutières syndrome in PARS2-related mitochondrial disease

PARS2 encodes an aminoacyl-tRNA synthetase that catalyzes the ligation of proline to mitochondrial prolyl-tRNA molecules. Diseases associated with PARS2 primarily affect the central nervous system, causing early infantile developmental epileptic encephalopathies (EIDEE; DEE75; MIM #618437) with infantile-onset neurodegeneration. Dilated cardiomyopathy has also been reported in the affected individuals. About 10 individuals to date have been described with pathogenic biallelic variants in PARS2. While many of the reported individuals succumbed to the disease in the first two decades of life, autopsy findings have not yet been reported. Here, we describe neuropathological findings in a deceased male with evidence of intracranial calcifications in the basal ganglia, thalamus, cerebellum, and white matter, similar to Aicardi-Goutières syndrome. This report describes detailed autopsy findings in a child with PARS2-related mitochondrial disease and provides plausible evidence that intracranial calcifications may be a previously unrecognized feature of this disorder.

ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization

BACKGROUND

Whole-exome sequencing (WES) and whole-genome sequencing (WGS) have become indispensable tools to solve rare Mendelian genetic conditions. Nevertheless, there is still an urgent need for sensitive, fast algorithms to maximise WES/WGS diagnostic yield in rare disease patients. Most tools devoted to this aim take advantage of patient phenotype information for prioritization of genomic data, although are often limited by incomplete gene-phenotype knowledge stored in biomedical databases and a lack of proper benchmarking on real-world patient cohorts.

METHODS

We developed ClinPrior, a novel method for the analysis of WES/WGS data that ranks candidate causal variants based on the patient's standardized phenotypic features (in Human Phenotype Ontology (HPO) terms). The algorithm propagates the data through an interactome network-based prioritization approach. This algorithm was thoroughly benchmarked using a synthetic patient cohort and was subsequently tested on a heterogeneous prospective, real-world series of 135 families affected by hereditary spastic paraplegia (HSP) and/or cerebellar ataxia (CA).

RESULTS

ClinPrior successfully identified causative variants achieving a final positive diagnostic yield of 70% in our real-world cohort. This includes 10 novel candidate genes not previously associated with disease, 7 of which were functionally validated within this project. We used the knowledge generated by ClinPrior to create a specific interactome for HSP/CA disorders thus enabling future diagnoses as well as the discovery of novel disease genes.

CONCLUSIONS

ClinPrior is an algorithm that uses standardized phenotype information and interactome data to improve clinical genomic diagnosis. It helps in identifying atypical cases and efficiently predicts novel disease-causing genes. This leads to increasing diagnostic yield, shortening of the diagnostic Odysseys and advancing our understanding of human illnesses.

RINT1 deficiency disrupts lipid metabolism and underlies a complex hereditary spastic paraplegia

The Rad50 interacting protein 1 (Rint1) is a key player in vesicular trafficking between the ER and Golgi apparatus. Biallelic variants in RINT1 cause infantile-onset episodic acute liver failure (ALF). Here, we describe 3 individuals from 2 unrelated families with novel biallelic RINT1 loss-of-function variants who presented with early onset spastic paraplegia, ataxia, optic nerve hypoplasia, and dysmorphic features, broadening the previously described phenotype. Our functional and lipidomic analyses provided evidence that pathogenic RINT1 variants induce defective lipid-droplet biogenesis and profound lipid abnormalities in fibroblasts and plasma that impact both neutral lipid and phospholipid metabolism, including decreased triglycerides and diglycerides, phosphatidylcholine/phosphatidylserine ratios, and inhibited Lands cycle. Further, RINT1 mutations induced intracellular ROS production and reduced ATP synthesis, affecting mitochondria with membrane depolarization, aberrant cristae ultrastructure, and increased fission. Altogether, our results highlighted the pivotal role of RINT1 in lipid metabolism and mitochondria function, with a profound effect in central nervous system development.

Individualised human phenotype ontology gene panels improve clinical whole exome and genome sequencing analytical efficacy in a cohort of developmental and epileptic encephalopathies

BACKGROUND

The majority of genetic epilepsies remain unsolved in terms of specific genotype. Phenotype-based genomic analyses have shown potential to strengthen genomic analysis in various ways, including improving analytical efficacy.

METHODS

We have tested a standardised phenotyping method termed 'Phenomodels' for integrating deep-phenotyping information with our in-house developed clinical whole exome/genome sequencing analytical pipeline. Phenomodels includes a user-friendly epilepsy phenotyping template and an objective measure for selecting which template terms to include in individualised Human Phenotype Ontology (HPO) gene panels. In a pilot study of 38 previously solved cases of developmental and epileptic encephalopathies, we compared the sensitivity and specificity of the individualised HPO gene panels with the clinical epilepsy gene panel.

RESULTS

The Phenomodels template showed high sensitivity for capturing relevant phenotypic information, where 37/38 individuals' HPO gene panels included the causative gene. The HPO gene panels also had far fewer variants to assess than the epilepsy gene panel.

CONCLUSION

We have demonstrated a viable approach for incorporating standardised phenotype information into clinical genomic analyses, which may enable more efficient analysis.

Utility of genetic testing in children with leukodystrophy

BACKGROUND

Leukodystrophies are monogenic disorders primarily affecting the white matter. We aimed to evaluate the utility of genetic testing and time-to-diagnosis in a retrospective cohort of children with suspected leukodystrophy.

METHODS

Medical records of patients who attended the leukodystrophy clinic at the Dana-Dwek Children's Hospital between June 2019 and December 2021 were retrieved. Clinical, molecular, and neuroimaging data were reviewed, and the diagnostic yield was compared across genetic tests.

RESULTS

Sixty-seven patients (Female/Male ratio 35/32) were included. Median age at symptom onset was 9 months (interquartile range (IQR) 3-18 months), and median length of follow-up was 4.75 years (IQR 3-8.5). Time from symptom onset to a confirmed genetic diagnosis was 15months (IQR 11-30). Pathogenic variants were identified in 60/67 (89.6%) patients; classic leukodystrophy (55/67, 82.1%), leukodystrophy mimics (5/67, 7.5%). Seven patients (10.4%) remained undiagnosed. Exome sequencing showed the highest diagnostic yield (34/41, 82.9%), followed by single-gene sequencing (13/24, 54%), targeted panels (3/9, 33.3%) and chromosomal microarray (2/25, 8%). Familial pathogenic variant testing confirmed the diagnosis in 7/7 patients. A comparison between patients who presented before (n = 31) and after (n = 21) next-generation sequencing (NGS) became clinically available in Israel revealed that the time-to-diagnosis was shorter in the latter group with a median of 12months (IQR 3.5-18.5) vs. a median of 19 months (IQR 13-51) (p = 0.005).

CONCLUSIONS

NGS carries the highest diagnostic yield in children with suspected leukodystrophy. Access to advanced sequencing technologies accelerates speed to diagnosis, which is increasingly crucial as targeted treatments become available.

Solving inherited white matter disorder etiologies in the neurology clinic: Challenges and lessons learned using next-generation sequencing

Introduction

Rare neurodevelopmental disorders, including inherited white matter disorders or leukodystrophies, often present a diagnostic challenge on a genetic level given the large number of causal genes associated with a range of disease subtypes. This study aims to demonstrate the challenges and lessons learned in the genetic investigations of leukodystrophies through presentation of a series of cases solved using exome or genome sequencing.

Methods

Each of the six patients had a leukodystrophy associated with hypomyelination or delayed myelination on MRI, and inconclusive clinical diagnostic genetic testing results. We performed next generation sequencing (case-based exome or genome sequencing) to further investigate the genetic cause of disease.

Results

Following different lines of investigation, molecular diagnoses were obtained for each case, with patients harboring pathogenic variants in a range of genes including TMEM106B, GJA1, AGA, POLR3A, and TUBB4A. We describe the lessons learned in reaching the genetic diagnosis, including the importance of (a) utilizing proper multi-gene panels in clinical testing, (b) assessing the reliability of biochemical assays in supporting diagnoses, and (c) understanding the limitations of exome sequencing methods in regard to CNV detection and region coverage in GC-rich areas.

Discussion

This study illustrates the importance of applying a collaborative diagnostic approach by combining detailed phenotyping data and metabolic results from the clinical environment with advanced next generation sequencing analysis techniques from the research environment to increase the diagnostic yield in patients with genetically unresolved leukodystrophies.

Laboratory testing for mitochondrial diseases: biomarkers for diagnosis and follow-up

The currently available biomarkers generally lack the specificity and sensitivity needed for the diagnosis and follow-up of patients with mitochondrial diseases (MDs). In this group of rare genetic disorders (mutations in approximately 350 genes associated with MDs), all clinical presentations, ages of disease onset and inheritance types are possible. Blood, urine, and cerebrospinal fluid surrogates are well-established biomarkers that are used in clinical practice to assess MD. One of the main challenges is validating specific and sensitive biomarkers for the diagnosis of disease and prediction of disease progression. Profiling of lactate, amino acids, organic acids, and acylcarnitine species is routinely conducted to assess MD patients. New biomarkers, including some proteins and circulating cell-free mitochondrial DNA, with increased diagnostic specificity have been identified in the last decade and have been proposed as potentially useful in the assessment of clinical outcomes. Despite these advances, even these new biomarkers are not sufficiently specific and sensitive to assess MD progression, and new biomarkers that indicate MD progression are urgently needed to monitor the success of novel therapeutic strategies. In this report, we review the mitochondrial biomarkers that are currently analyzed in clinical laboratories, new biomarkers, an overview of the most common laboratory diagnostic techniques, and future directions regarding targeted versus untargeted metabolomic and genomic approaches in the clinical laboratory setting. Brief descriptions of the current methodologies are also provided.

Identification of a Novel Non-Canonical Splice-Site Variant in ABCD1

Cerebral adrenoleukodystrophy (CALD) is a fatal genetic disease characterized by rapid, devastating neurological decline, with a narrow curative treatment window in the early stage. Non-canonical splice-site (NCSS) variants can easily be missed during genomic DNA analyses, and only a few of them in ABCD1 have been explored. Here, we studied a Chinese patient with clinical features similar to those of early-stage CALD but with a negative molecular diagnosis and a sibling who had presumably died of CALD. Trio-based whole-exome sequencing (trio-WES) and RNA sequencing (RNA-Seq) revealed a novel hemizygote NCSS variant c.901-25_901-9 del in ABCD1 intron 1, resulting in a complex splicing pattern. The in vitro minigene assay revealed that the c.901-25_901-9 del construct contained two aberrant transcripts that caused skipping of exon 2 and a small 48-bp deletion on left of the same exon. We identified a novel NCSS variant, that extends the spectrum of the known ABCD1 variants, and demonstrated the pathogenicity of this gene variant. Our findings highlight the importance of combining RNA-Seq and WES techniques for prompt diagnosis of leukodystrophy with NCSS variants.

Loss of seryl-tRNA synthetase (SARS1) causes complex spastic paraplegia and cellular senescence

BACKGROUND

Aminoacyl-tRNA synthetases (ARS) are key enzymes catalysing the first reactions in protein synthesis, with increasingly recognised pleiotropic roles in tumourgenesis, angiogenesis, immune response and lifespan. Germline mutations in several ARS genes have been associated with both recessive and dominant neurological diseases. Recently, patients affected with microcephaly, intellectual disability and ataxia harbouring biallelic variants in the seryl-tRNA synthetase encoded by seryl-tRNA synthetase 1 (SARS1) were reported.

METHODS

We used exome sequencing to identify the causal variant in a patient affected by complex spastic paraplegia with ataxia, intellectual disability, developmental delay and seizures, but without microcephaly. Complementation and serylation assays using patient's fibroblasts and an Saccharomyces cerevisiae model were performed to examine this variant's pathogenicity.

RESULTS

A de novo splice site deletion in SARS1 was identified in our patient, resulting in a 5-amino acid in-frame insertion near its active site. Complementation assays in S. cerevisiae and serylation assays in both yeast strains and patient fibroblasts proved a loss-of-function, dominant negative effect. Fibroblasts showed an abnormal cell shape, arrested division and increased beta-galactosidase staining along with a senescence-associated secretory phenotype (raised interleukin-6, p21, p16 and p53 levels).

CONCLUSION

We refine the phenotypic spectrum and modes of inheritance of a newly described, ultrarare neurodevelopmental disorder, while unveiling the role of SARS1 as a regulator of cell growth, division and senescence.

Advances and Trends in Omics Technology Development

The human history has witnessed the rapid development of technologies such as high-throughput sequencing and mass spectrometry that led to the concept of “omics” and methodological advancement in systematically interrogating a cellular system. Yet, the ever-growing types of molecules and regulatory mechanisms being discovered have been persistently transforming our understandings on the cellular machinery. This renders cell omics seemingly, like the universe, expand with no limit and our goal toward the complete harness of the cellular system merely impossible. Therefore, it is imperative to review what has been done and is being done to predict what can be done toward the translation of omics information to disease control with minimal cell perturbation. With a focus on the “four big omics,” i.e., genomics, transcriptomics, proteomics, metabolomics, we delineate hierarchies of these omics together with their epiomics and interactomics, and review technologies developed for interrogation. We predict, among others, redoxomics as an emerging omics layer that views cell decision toward the physiological or pathological state as a fine-tuned redox balance.

Molecular Modelling Hurdle in the Next-Generation Sequencing Era

There are challenges in the genetic diagnosis of rare diseases, and pursuing an optimal strategy to identify the cause of the disease is one of the main objectives of any clinical genomics unit. A range of techniques are currently used to characterize the genomic variability within the human genome to detect causative variants of specific disorders. With the introduction of next-generation sequencing (NGS) in the clinical setting, geneticists can study single-nucleotide variants (SNVs) throughout the entire exome/genome. In turn, the number of variants to be evaluated per patient has increased significantly, and more information has to be processed and analyzed to determine a proper diagnosis. Roughly 50% of patients with a Mendelian genetic disorder are diagnosed using NGS, but a fair number of patients still suffer a diagnostic odyssey. Due to the inherent diversity of the human population, as more exomes or genomes are sequenced, variants of uncertain significance (VUSs) will increase exponentially. Thus, assigning relevance to a VUS (non-synonymous as well as synonymous) in an undiagnosed patient becomes crucial to assess the proper diagnosis. Multiple algorithms have been used to predict how a specific mutation might affect the protein's function, but they are far from accurate enough to be conclusive. In this work, we highlight the difficulties of genomic variability determined by NGS that have arisen in diagnosing rare genetic diseases, and how molecular modelling has to be a key component to elucidate the relevance of a specific mutation in the protein's loss of function or malfunction. We suggest that the creation of a multi-omics data model should improve the classification of pathogenicity for a significant amount of the detected genomic variability. Moreover, we argue how it should be incorporated systematically in the process of variant evaluation to be useful in the clinical setting and the diagnostic pipeline.

Systematic Collaborative Reanalysis of Genomic Data Improves Diagnostic Yield in Neurologic Rare Diseases

Many patients experiencing a rare disease remain undiagnosed even after genomic testing. Reanalysis of existing genomic data has shown to increase diagnostic yield, although there are few systematic and comprehensive reanalysis efforts that enable collaborative interpretation and future reinterpretation. The Undiagnosed Rare Disease Program of Catalonia project collated previously inconclusive good quality genomic data (panels, exomes, and genomes) and standardized phenotypic profiles from 323 families (543 individuals) with a neurologic rare disease. The data were reanalyzed systematically to identify relatedness, runs of homozygosity, consanguinity, single-nucleotide variants, insertions and deletions, and copy number variants. Data were shared and collaboratively interpreted within the consortium through a customized Genome-Phenome Analysis Platform, which also enables future data reinterpretation. Reanalysis of existing genomic data provided a diagnosis for 20.7% of the patients, including 1.8% diagnosed after the generation of additional genomic data to identify a second pathogenic heterozygous variant. Diagnostic rate was significantly higher for family-based exome/genome reanalysis compared with singleton panels. Most new diagnoses were attributable to recent gene-disease associations (50.8%), additional or improved bioinformatic analysis (19.7%), and standardized phenotyping data integrated within the Undiagnosed Rare Disease Program of Catalonia Genome-Phenome Analysis Platform functionalities (18%).