Identification of a mosaic MTOR variant in purified neuronal DNA in a patient with focal cortical dysplasia using a novel depth electrode harvesting technique.

OBJECTIVE: Recent studies have identified brain somatic variants as a cause of focal epilepsy. These studies relied on resected tissue from epilepsy surgery, which is not available in most patients. The use of trace tissue adherent to depth electrodes used for stereo electroencephalography (EEG) has been proposed as an alternative but is hampered by the low cell quality and contamination by nonbrain cells. Here, we use our improved depth electrode harvesting technique that purifies neuronal nuclei to achieve molecular diagnosis in a patient with focal cortical dysplasia (FCD). METHODS: Depth electrode tips were collected, pooled by brain region and seizure onset zone, and nuclei were isolated and sorted using fluorescence-activated nuclei sorting (FANS). Somatic DNA was amplified from neuronal and astrocyte nuclei using primary template amplification followed by exome sequencing of neuronal DNA from the affected pool, unaffected pool, and saliva. The identified variant was validated using droplet digital polymerase chain reaction (PCR). RESULTS: An 11-year-old male with drug-resistant genetic-structural epilepsy due to left anterior insula FCD had seizures from age 3 years. Stereo EEG confirmed seizure onset in the left anterior insula. The two anterior insula electrodes were combined as the affected pool and three frontal electrodes as the unaffected pool. FANS isolated 140 neuronal nuclei from the affected and 245 neuronal nuclei from the unaffected pool. A novel somatic missense MTOR variant (p.Leu489Met, CADD score 23.7) was identified in the affected neuronal sample. Droplet digital PCR confirmed a mosaic gradient (variant allele frequency = .78% in affected neuronal sample; variant was absent in all other samples). SIGNIFICANCE: Our findings confirm that harvesting neuronal DNA from depth electrodes followed by molecular analysis to identify brain somatic variants is feasible. Our novel method represents a significant improvement compared to the previous method by focusing the analysis on high-quality cells of the cell type of interest.

CIAO1 and MMS19 deficiency: A lethal neurodegenerative phenotype caused by cytosolic Fe-S cluster protein assembly disorders.

PURPOSE: The functionality of many cellular proteins depends on cofactors; yet, they have only been implicated in a minority of Mendelian diseases. Here, we describe the first 2 inherited disorders of the cytosolic iron-sulfur protein assembly system. METHODS: Genetic testing via genome sequencing was applied to identify the underlying disease cause in 3 patients with microcephaly, congenital brain malformations, progressive developmental and neurologic impairments, recurrent infections, and a fatal outcome. Studies in patient-derived skin fibroblasts and zebrafish models were performed to investigate the biochemical and cellular consequences. RESULTS: Metabolic analysis showed elevated uracil and thymine levels in body fluids but no pathogenic variants in DPYD, encoding dihydropyrimidine dehydrogenase. Genome sequencing identified compound heterozygosity in 2 patients for missense variants in CIAO1, encoding cytosolic iron-sulfur assembly component 1, and homozygosity for an in-frame 3-nucleotide deletion in MMS19, encoding the MMS19 homolog, cytosolic iron-sulfur assembly component, in the third patient. Profound alterations in the proteome, metabolome, and lipidome were observed in patient-derived fibroblasts. We confirmed the detrimental effect of deficiencies in CIAO1 and MMS19 in zebrafish models. CONCLUSION: A general failure of cytosolic and nuclear iron-sulfur protein maturation caused pleiotropic effects. The critical function of the cytosolic iron-sulfur protein assembly machinery for antiviral host defense may well explain the recurrent severe infections occurring in our patients.

GPAD: a natural language processing-based application to extract the gene-disease association discovery information from OMIM.

BACKGROUND: 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. RESULTS: GPAD applies a series of language-based techniques to the text obtained from OMIM API to extract GDA discovery-related information. GPAD can inform when a particular gene was associated with a specific phenotype, as well as the type of validation-whether through model organisms or cohort-based patient-matching approaches-for such an association. GPAD extracted data was validated with published reports and was compared with large language model. Utilizing GPAD's extracted data, we analysed trends in GDA discoveries, noting a significant increase in their rate after the introduction of exome sequencing, rising from an average of about 150-250 discoveries each year. Contrary to hopes of resolving most GDAs for Mendelian disorders by now, our data indicate a substantial decline in discovery rates over the past five years (2017-2022). This decline appears to be linked to the increasing necessity for larger cohorts to substantiate GDAs. The rising use of zebrafish and Drosophila as model organisms in providing evidential support for GDAs is also observed. CONCLUSIONS: GPAD's real-time analyzing capacity offers an up-to-date view of GDA discovery and could help in planning and managing the research strategies. In future, this solution can be extended or modified to capture other information in OMIM and scientific literature.

Single variant, yet "double trouble": TSC and KBG syndrome because of a large de novo inversion.

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.

Model Organism Modifier (MOM): a user-friendly Galaxy workflow to detect modifiers from genome sequencing data using Caenorhabditis elegans.

Genetic modifiers are variants modulating phenotypic outcomes of a primary detrimental variant. They contribute to rare diseases phenotypic variability, but their identification is challenging. Genetic screening with model organisms is a widely used method for demystifying genetic modifiers. Forward genetics screening followed by whole genome sequencing allows the detection of variants throughout the genome but typically produces thousands of candidate variants making the interpretation and prioritization process very time-consuming and tedious. Despite whole genome sequencing is more time and cost-efficient, usage of computational pipelines specific to modifier identification remains a challenge for biological-experiment-focused laboratories doing research with model organisms. To facilitate a broader implementation of whole genome sequencing in genetic screens, we have developed Model Organism Modifier or MOM, a pipeline as a user-friendly Galaxy workflow. Model Organism Modifier analyses raw short-read whole genome sequencing data and implements tailored filtering to provide a Candidate Variant List short enough to be further manually curated. We provide a detailed tutorial to run the Galaxy workflow Model Organism Modifier and guidelines to manually curate the Candidate Variant Lists. We have tested Model Organism Modifier on published and validated Caenorhabditis elegans modifiers screening datasets. As whole genome sequencing facilitates high-throughput identification of genetic modifiers in model organisms, Model Organism Modifier provides a user-friendly solution to implement the bioinformatics analysis of the short-read datasets in laboratories without expertise or support in Bioinformatics.

Molecular basis of essential and morphological variations across 12 balancer strains in C. elegans.

Balancers are primarily chromosomal rearrangements that allow lethal or sterile mutations to be stably maintained as heterozygotes. Strains with balanced lethal/sterile mutations are available at the Caenorhabditis Genetics Center. Such strains harbor morphological markers, with associated molecular changes, that are in trans to the balancer. In many cases, only the genetic position (in cM) has been described for balanced mutations or morphological markers. We used short-read whole genome sequencing to uncover the genomic position of those variants (balanced mutations and linked markers) and predicted their effect. We investigated 12 different strains, and characterized at a molecular level 12 variants.

Mitogen-induced defective mitosis transforms neural progenitor cells.

BACKGROUND: Chromosome instability (CIN) with recurrent copy number alterations is a feature of many solid tumors, including glioblastoma (GBM), yet the genes that regulate cell division are rarely mutated in cancers. Here, we show that the brain-abundant mitogen, platelet-derived growth factor-A (PDGFA) fails to induce the expression of kinetochore and spindle assembly checkpoint genes leading to defective mitosis in neural progenitor cells (NPCs). METHODS: Using a recently reported in vitro model of the initiation of high-grade gliomas from murine NPCs, we investigated the immediate effects of PDGFA exposure on the nuclear and mitotic phenotypes and patterns of gene and protein expression in NPCs, a putative GBM cell of origin. RESULTS: NPCs divided abnormally in defined media containing PDGFA with P53-dependent effects. In wild-type cells, defective mitosis was associated with P53 activation and cell death, but in some null cells, defective mitosis was tolerated. Surviving cells had unstable genomes and proliferated in the presence of PDGFA accumulating random and clonal chromosomal rearrangements. The outcome of this process was a population of tumorigenic NPCs with recurrent gains and losses of chromosomal regions that were syntenic to those recurrently gained and lost in human GBM. By stimulating proliferation without setting the stage for successful mitosis, PDGFA-transformed NPCs lacking P53 function. CONCLUSIONS: Our work describes a mechanism of transformation of NPCs by a brain-associated mitogen, raising the possibility that the unique genomic architecture of GBM is an adaptation to defective mitosis that ensures the survival of affected cells.

A novel FAME1 repeat configuration in a European family identified using a combined genomics approach.

Familial adult myoclonic epilepsy (FAME) is an adult-onset neurological disease characterized by cortical tremor, myoclonus, and seizures due to a pentanucleotide repeat expansion: a combination of pathogenic TTTCA expansion associated with a TTTTA repeat in introns of six different genes. Repeat-primed PCR (RP-PCR) is an inexpensive test for expansions at known loci. The analysis of the SAMD12 locus revealed that the repeats have different size, configuration, and composition. The TTTCA repeats can be very long (>1000 repeats) but also very short (14 being the shortest identified). Here, we report siblings of European descent with the clinical diagnosis of FAME yet a negative RP-PCR test. Using short-read genome sequencing, we identified the pentanucleotide expansion in intron 4 of SAMD12, which was confirmed by CRIPSR-Cas9-mediated enrichment and long-read sequencing to be of (TTTTA)~879 (TTTCA)3 (TTTTA)7 (TTTCA)7 configuration. Our finding is the first to associate the SAMD12 locus in European patients with FAME and currently represents the shortest identified TTTCA expansion. Our results suggest that the SAMD12 locus should be tested in patients with suspected FAME independent of ethnicity. Furthermore, RP-PCR may miss the underlying mutation, and genome sequencing may be needed to confirm the pathogenic repeat.

The Power of Clinical Diagnosis for Deciphering Complex Genetic Mechanisms in Rare Diseases.

Complex genetic disease mechanisms, such as structural or non-coding variants, currently pose a substantial difficulty in frontline diagnostic tests. They thus may account for most unsolved rare disease patients regardless of the clinical phenotype. However, the clinical diagnosis can narrow the genetic focus to just a couple of genes for patients with well-established syndromes defined by prominent physical and/or unique biochemical phenotypes, allowing deeper analyses to consider complex genetic origin. Then, clinical-diagnosis-driven genome sequencing strategies may expedite the development of testing and analytical methods to account for complex disease mechanisms as well as to advance functional assays for the confirmation of complex variants, clinical management, and the development of new therapies.

Genome sequencing of C. elegans balancer strains reveals previously unappreciated complex genomic rearrangements.

Genetic balancers in Caenorhabditis elegans are complex variants that allow lethal or sterile mutations to be stably maintained in a heterozygous state by suppressing crossover events. Balancers constitute an invaluable tool in the C. elegans scientific community and have been widely used for decades. The first/traditional balancers were created by applying X-rays, UV, or gamma radiation on C. elegans strains, generating random genomic rearrangements. Their structures have been mostly explored with low-resolution genetic techniques (e.g., fluorescence in situ hybridization or PCR), before genomic mapping and molecular characterization through sequencing became feasible. As a result, the precise nature of most chromosomal rearrangements remains unknown, whereas, more recently, balancers have been engineered using the CRISPR-Cas9 technique for which the structure of the chromosomal rearrangement has been predesigned. Using short-read whole-genome sequencing (srWGS) and tailored bioinformatic analyses, we previously interpreted the structure of four chromosomal balancers randomly created by mutagenesis processes. Here, we have extended our analyses to five CRISPR-Cas9 balancers and 17 additional traditional balancing rearrangements. We detected and experimentally validated their breakpoints and have interpreted the balancer structures. Many of the balancers were found to be more intricate than previously described, being composed of complex genomic rearrangements (CGRs) such as chromoanagenesis-like events. Furthermore, srWGS revealed additional structural variants and CGRs not known to be part of the balancer genomes. Altogether, our study provides a comprehensive resource of complex genomic variations in C. elegans and highlights the power of srWGS to study the complexity of genomes by applying tailored analyses.

Genome-wide sequencing and the clinical diagnosis of genetic disease: The CAUSES study.

Genome-wide sequencing (GWS) is a standard of care for diagnosis of suspected genetic disorders, but the proportion of patients found to have pathogenic or likely pathogenic variants ranges from less than 30% to more than 60% in reported studies. It has been suggested that the diagnostic rate can be improved by interpreting genomic variants in the context of each affected individual's full clinical picture and by regular follow-up and reinterpretation of GWS laboratory results. Trio exome sequencing was performed in 415 families and trio genome sequencing in 85 families in the CAUSES study. The variants observed were interpreted by a multidisciplinary team including laboratory geneticists, bioinformaticians, clinical geneticists, genetic counselors, pediatric subspecialists, and the referring physician, and independently by a clinical laboratory using standard American College of Medical Genetics and Genomics (ACMG) criteria. Individuals were followed for an average of 5.1 years after testing, with clinical reassessment and reinterpretation of the GWS results as necessary. The multidisciplinary team established a diagnosis of genetic disease in 43.0% of the families at the time of initial GWS interpretation, and longitudinal follow-up and reinterpretation of GWS results produced new diagnoses in 17.2% of families whose initial GWS interpretation was uninformative or uncertain. Reinterpretation also resulted in rescinding a diagnosis in four families (1.9%). Of the families studied, 33.6% had ACMG pathogenic or likely pathogenic variants related to the clinical indication. Close collaboration among clinical geneticists, genetic counselors, laboratory geneticists, bioinformaticians, and individuals' primary physicians, with ongoing follow-up, reanalysis, and reinterpretation over time, can improve the clinical value of GWS.

Case Report: Biallelic Loss of Function ATM due to Pathogenic Synonymous and Novel Deep Intronic Variant c.1803-270T > G Identified by Genome Sequencing in a Child With Ataxia-Telangiectasia.

Ataxia-telangiectasia (AT) is a complex neurodegenerative disease with an increased risk for bone marrow failure and malignancy. AT is caused by biallelic loss of function variants in ATM, which encodes a phosphatidylinositol 3-kinase that responds to DNA damage. Herein, we report a child with progressive ataxia, chorea, and genome instability, highly suggestive of AT. The clinical ataxia gene panel identified a maternal heterozygous synonymous variant (NM_000051.3: c.2250G > A), previously described to result in exon 14 skipping. Subsequently, trio genome sequencing led to the identification of a novel deep intronic variant [NG_009830.1(NM_000051.3): c.1803-270T > G] inherited from the father. Transcript analyses revealed that c.1803-270T > G results in aberrant inclusion of 56 base pairs of intron 11. In silico tests predicted a premature stop codon as a consequence, suggesting non-functional ATM; and DNA repair analyses confirmed functional loss of ATM. Our findings highlight the power of genome sequencing, considering deep intronic variants in undiagnosed rare disease patients.

Rare disorders have many faces: in silico characterization of rare disorder spectrum.

BACKGROUND: The diagnostic journey for many rare disease patients remains challenging despite use of latest genetic technological advancements. We hypothesize that some patients remain undiagnosed due to more complex diagnostic scenarios that are currently not considered in genome analysis pipelines. To better understand this, we characterized the rare disorder (RD) spectrum using various bioinformatics resources (e.g., Orphanet/Orphadata, Human Phenotype Ontology, Reactome pathways) combined with custom-made R scripts. RESULTS: Our in silico characterization led to identification of 145 borderline-common, 412 rare and 2967 ultra-rare disorders. Based on these findings and point prevalence, we would expect that approximately 6.53%, 0.34%, and 0.30% of individuals in a randomly selected population have a borderline-common, rare, and ultra-rare disorder, respectively (equaling to 1 RD patient in 14 people). Importantly, our analyses revealed that (1) a higher proportion of borderline-common disorders were caused by multiple gene defects and/or other factors compared with the rare and ultra-rare disorders, (2) the phenotypic expressivity was more variable for the borderline-common disorders than for the rarer disorders, and (3) unique clinical characteristics were observed across the disorder categories forming the spectrum. CONCLUSIONS: Recognizing that RD patients who remain unsolved even after genome sequencing might belong to the more common end of the RD spectrum support the usage of computational pipelines that account for more complex genetic and phenotypic scenarios.

Driving mosaicism: somatic variants in reference population databases and effect on variant interpretation in rare genetic disease.

BACKGROUND: Genetic variation databases provide invaluable information on the presence and frequency of genetic variants in the 'untargeted' human population, aggregated with the primary goal to facilitate the interpretation of clinically important variants. The presence of somatic variants in such databases can affect variant assessment in undiagnosed rare disease (RD) patients. Previously, the impact of somatic mosaicism was only considered in relation to two Mendelian disease-associated genes. Here, we expand the analyses to identify additional mosaicism-prone genes in blood-derived reference population databases. RESULTS: To identify additional mosaicism-prone genes relevant to RDs, we focused on known/previously established ClinVar pathogenic and likely pathogenic single-nucleotide variants, residing in genes associated with early onset, severe autosomal dominant diseases. We asked whether any of these variants are present in a higher-than-expected frequency in the reference population databases and whether there is evidence of somatic origin (i.e., allelic imbalance) rather than germline heterozygosity (~ half of the reads supporting alternative allele). The mosaicism-prone genes identified were further categorized according to the processes they are involved in. Beyond the previously reported ASXL1 and DNMT3A, we identified 7 additional autosomal dominant RD-associated genes with known pathogenic single-nucleotide variants present in the reference population databases and good evidence of allelic imbalance: BRAF, CBL, FGFR3, IDH2, KRAS, PTPN11 and SETBP1. From this group of 9 genes, the majority (n = 7) was important for hematopoiesis. In addition, 4 of these genes were involved in cell proliferation. Further assessment of the known 156 hematopoietic genes led to identification of 48 genes (21 not yet associated with RDs) with at least some evidence of mosaicism detectable in reference population databases. CONCLUSIONS: These results stress the importance of considering genes involved in hematopoiesis and cell proliferation when interpreting the presence and frequency of genetic variants in blood-derived reference population databases, both public and private. This is especially important when considering new variants of uncertain significance in known hematopoietic/cell proliferation RD genes and future novel gene-disease associations involving this class of genes.

Whole genome sequencing facilitates intragenic variant interpretation following modifier screening in C. elegans.

BACKGROUND: 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. RESULTS: Here, we apply high throughput approaches to identify and understand intragenic modifiers using Caenorhabditis elegans. Specifically, we applied whole genome sequencing (WGS) to a mutagen-induced forward genetic screen to identify intragenic suppressors of a temperature-sensitive zyg-1(it25) allele in C. elegans. ZYG-1 is a polo kinase that is important for centriole function and cell divisions, and mutations that truncate its human orthologue, PLK4, have been associated with microcephaly. Combining WGS and CRISPR/Cas9, we rapidly identify intragenic modifiers, show that these variants are distributed non-randomly throughout zyg-1 and that genomic context plays an important role on phenotypic outcomes. CONCLUSIONS: Ultimately, our work shows that WGS facilitates high-throughput identification of intragenic modifiers in clinically relevant genes by reducing hands-on research time and overall costs and by allowing thorough understanding of the intragenic phenotypic effects in the context of different genetic backgrounds.

Deciphering complex genome rearrangements in C. elegans using short-read whole genome sequencing.

Genomic rearrangements cause congenital disorders, cancer, and complex diseases in human. Yet, they are still understudied in rare diseases because their detection is challenging, despite the advent of whole genome sequencing (WGS) technologies. Short-read (srWGS) and long-read WGS approaches are regularly compared, and the latter is commonly recommended in studies focusing on genomic rearrangements. However, srWGS is currently the most economical, accurate, and widely supported technology. In Caenorhabditis elegans (C. elegans), such variants, induced by various mutagenesis processes, have been used for decades to balance large genomic regions by preventing chromosomal crossover events and allowing the maintenance of lethal mutations. Interestingly, those chromosomal rearrangements have rarely been characterized on a molecular level. To evaluate the ability of srWGS to detect various types of complex genomic rearrangements, we sequenced three balancer strains using short-read Illumina technology. As we experimentally validated the breakpoints uncovered by srWGS, we showed that, by combining several types of analyses, srWGS enables the detection of a reciprocal translocation (eT1), a free duplication (sDp3), a large deletion (sC4), and chromoanagenesis events. Thus, applying srWGS to decipher real complex genomic rearrangements in model organisms may help designing efficient bioinformatics pipelines with systematic detection of complex rearrangements in human genomes.

Secondary biogenic amine deficiencies: genetic etiology, therapeutic interventions, and clinical effects.

Monoamine neurotransmitter disorders present predominantly with neurologic features, including dystonic or dyskinetic cerebral palsy and movement disorders. Genetic conditions that lead to secondary defects in the synthesis, catabolism, transport, and metabolism of biogenic amines can lead to neurotransmitter abnormalities, which can present with similar features. Eleven patients with secondary neurotransmitter abnormalities were enrolled between 2011 and 2015. All patients underwent research-based whole exome and/or whole genome sequencing (WES/WGS). A trial of treatment with levodopa/carbidopa and 5-hydroxytryptophan was initiated. In six families with abnormal neurotransmitter profiles and neurological phenotypes, variants in known disease-causing genes (KCNJ6, SCN2A, CSTB in 2 siblings, NRNX1, KIF1A and PAK3) were identified, while one patient had a variant of uncertain significance in a candidate gene (DLG4) that may explain her phenotype. In 3 patients, no compelling candidate genes were identified. A trial of neurotransmitter replacement therapy led to improvement in motor and behavioral symptoms in all but two patients. The patient with KCNJ6 variant did not respond to L-dopa therapy, but rather experienced increased dyskinetic movements even at low dose of medication. The patient's symptoms harboring the NRNX1 deletion remained unaltered. This study demonstrates the utility of genome-wide sequencing in further understanding the etiology and pathophysiology of neurometabolic conditions, and the potential of secondary neurotransmitter deficiencies to serve as novel therapeutic targets. As there was a largely favorable response to therapy in our case series, a careful trial of neurotransmitter replacement therapy should be considered in patients with cerebrospinal fluid (CSF) monoamines below reference range.

De novo stop-loss variants in CLDN11 cause hypomyelinating leukodystrophy.

Claudin-11, a tight junction protein, is indispensable in the formation of the radial component of myelin. Here, we report de novo stop-loss variants in the gene encoding claudin-11, CLDN11, in three unrelated individuals presenting with an early-onset spastic movement disorder, expressive speech disorder and eye abnormalities including hypermetropia. Brain MRI showed a myelin deficit with a discrepancy between T1-weighted and T2-weighted images and some progress in myelination especially involving the central and peripheral white matter. Exome sequencing identified heterozygous stop-loss variants c.622T>C, p.(*208Glnext*39) in two individuals and c.622T>G, p.(*208Gluext*39) in one individual, all occurring de novo. At the RNA level, the variant c.622T>C did not lead to a loss of expression in fibroblasts, indicating this transcript is not subject to nonsense-mediated decay and most likely translated into an extended protein. Extended claudin-11 is predicted to form an alpha helix not incorporated into the cytoplasmic membrane, possibly perturbing its interaction with intracellular proteins. Our observations suggest that stop-loss variants in CLDN11 expand the genetically heterogeneous spectrum of hypomyelinating leukodystrophies.

Dissecting the Genetic and Etiological Causes of Primary Microcephaly.

Autosomal recessive primary microcephaly (MCPH; "small head syndrome") is a rare, heterogeneous disease arising from the decreased production of neurons during brain development. As of August 2020, the Online Mendelian Inheritance in Man (OMIM) database lists 25 genes (involved in molecular processes such as centriole biogenesis, microtubule dynamics, spindle positioning, DNA repair, transcriptional regulation, Wnt signaling, and cell cycle checkpoints) that are implicated in causing MCPH. Many of these 25 genes were only discovered in the last 10 years following advances in exome and genome sequencing that have improved our ability to identify disease-causing variants. Despite these advances, many patients still lack a genetic diagnosis. This demonstrates a need to understand in greater detail the molecular mechanisms and genetics underlying MCPH. Here, we briefly review the molecular functions of each MCPH gene and how their loss disrupts the neurogenesis program, ultimately demonstrating that microcephaly arises from cell cycle dysregulation. We also explore the current issues in the genetic basis and clinical presentation of MCPH as additional avenues of improving gene/variant prioritization. Ultimately, we illustrate that the detailed exploration of the etiology and inheritance of MCPH improves the predictive power in identifying previously unknown MCPH candidates and diagnosing microcephalic patients.

metPropagate: network-guided propagation of metabolomic information for prioritization of metabolic disease genes.

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.