Brain monoamine vesicular transport disease caused by homozygous SLC18A2 variants: A study in 42 affected individuals.

PURPOSE: Brain monoamine vesicular transport disease is an infantile-onset movement disorder that mimics cerebral palsy. In 2013, the homozygous SLC18A2 variant, p.Pro387Leu, was first reported as a cause of this rare disorder, and dopamine agonists were efficient for treating affected individuals from a single large family. To date, only 6 variants have been reported. In this study, we evaluated genotype-phenotype correlations in individuals with biallelic SLC18A2 variants. METHODS: A total of 42 affected individuals with homozygous SLC18A2 variant alleles were identified. We evaluated genotype-phenotype correlations and the missense variants in the affected individuals based on the structural modeling of rat VMAT2 encoded by Slc18a2, with cytoplasm- and lumen-facing conformations. A Caenorhabditis elegans model was created for functional studies. RESULTS: A total of 19 homozygous SLC18A2 variants, including 3 recurrent variants, were identified using exome sequencing. The affected individuals typically showed global developmental delay, hypotonia, dystonia, oculogyric crisis, and autonomic nervous system involvement (temperature dysregulation/sweating, hypersalivation, and gastrointestinal dysmotility). Among the 58 affected individuals described to date, 16 (28%) died before the age of 13 years. Of the 17 patients with p.Pro237His, 9 died, whereas all 14 patients with p.Pro387Leu survived. Although a dopamine agonist mildly improved the disease symptoms in 18 of 21 patients (86%), some affected individuals with p.Ile43Phe and p.Pro387Leu showed milder phenotypes and presented prolonged survival even without treatment. The C. elegans model showed behavioral abnormalities. CONCLUSION: These data expand the phenotypic and genotypic spectra of SLC18A2-related disorders.

Long-read sequencing revealing intragenic deletions in exome-negative spastic paraplegias.

Hereditary spastic paraplegias (HSPs) are a heterogeneous group of neurodegenerative disorders characterized by progressive spasticity and weakness in the lower extremities. To date, a total of 88 types of SPG are known. To diagnose HSP, multiple technologies, including microarray, direct sequencing, multiplex ligation-dependent probe amplification, and short-read next-generation sequencing, are often chosen based on the frequency of HSP subtypes. Exome sequencing (ES) is commonly used. We used ES to analyze ten cases of HSP from eight families. We identified pathogenic variants in three cases (from three different families); however, we were unable to determine the cause of the other seven cases using ES. We therefore applied long-read sequencing to the seven undetermined HSP cases (from five families). We detected intragenic deletions within the SPAST gene in four families, and a deletion within PSEN1 in the remaining family. The size of the deletion ranged from 4.7 to 12.5 kb and involved 1-7 exons. All deletions were entirely included in one long read. We retrospectively performed an ES-based copy number variation analysis focusing on pathogenic deletions, but were not able to accurately detect these deletions. This study demonstrated the efficiency of long-read sequencing in detecting intragenic pathogenic deletions in ES-negative HSP patients.

Efficient detection of copy-number variations using exome data: Batch- and sex-based analyses.

Many algorithms to detect copy number variations (CNVs) using exome sequencing (ES) data have been reported and evaluated on their sensitivity and specificity, reproducibility, and precision. However, operational optimization of such algorithms for a better performance has not been fully addressed. ES of 1199 samples including 763 patients with different disease profiles was performed. ES data were analyzed to detect CNVs by both the eXome Hidden Markov Model (XHMM) and modified Nord's method. To efficiently detect rare CNVs, we aimed to decrease sequencing biases by analyzing, at the same time, the data of all unrelated samples sequenced in the same flow cell as a batch, and to eliminate sex effects of X-linked CNVs by analyzing female and male sequences separately. We also applied several filtering steps for more efficient CNV selection. The average number of CNVs detected in one sample was <5. This optimization together with targeted CNV analysis by Nord's method identified pathogenic/likely pathogenic CNVs in 34 patients (4.5%, 34/763). In particular, among 142 patients with epilepsy, the current protocol detected clinically relevant CNVs in 19 (13.4%) patients, whereas the previous protocol identified them in only 14 (9.9%) patients. Thus, this batch-based XHMM analysis efficiently selected rare pathogenic CNVs in genetic diseases.

Long-read whole-genome sequencing identified a partial MBD5 deletion in an exome-negative patient with neurodevelopmental disorder.

Whole-exome sequencing (WES) can detect not only single-nucleotide variants in causal genes, but also pathogenic copy-number variations using several methods. However, there may be overlooked pathogenic variations in the out of target genome regions of WES analysis (e.g., promoters), leaving many patients undiagnosed. Whole-genome sequencing (WGS) can potentially analyze such regions. We applied long-read nanopore WGS and our recently developed analysis pipeline "dnarrange" to a patient who was undiagnosed by trio-based WES analysis, and identified a heterozygous 97-kb deletion partially involving 5'-untranslated exons of MBD5, which was outside the WES target regions. The phenotype of the patient, a 32-year-old male, was consistent with haploinsufficiency of MBD5. The transcript level of MBD5 in the patient's lymphoblastoid cells was reduced. We therefore concluded that the partial MBD5 deletion is the culprit for this patient. Furthermore, we found other rare structural variations (SVs) in this patient, i.e., a large inversion and a retrotransposon insertion, which were not seen in 33 controls. Although we considered that they are benign SVs, this finding suggests that our pipeline using long-read WGS is useful for investigating various types of potentially pathogenic SVs. In conclusion, we identified a 97-kb deletion, which causes haploinsufficiency of MBD5 in a patient with neurodevelopmental disorder, demonstrating that long-read WGS is a powerful technique to discover pathogenic SVs.

A novel PAK1 variant causative of neurodevelopmental disorder with postnatal macrocephaly.

p21-activated kinases (PAKs) are protein serine/threonine kinases stimulated by Rho-family p21 GTPases such as CDC42 and RAC. PAKs have been implicated in several human disorders, with pathogenic variants in PAK3 associated with intellectual disability and several PAK members, especially PAK1 and PAK4, overexpressed in human cancer. Recently, de novo PAK1 variants were reported to be causative of neurodevelopmental disorder (ND) with secondary macrocephaly in three patients. We herein report a fourth patient with ND, epilepsy, and macrocephaly caused by a de novo PAK1 missense variant. Two previously reported missense PAK1 variants functioned as activating alleles by reducing PAK1 homodimerization. To examine the pathogenicity of the identified novel p.Ser110Thr variant, we carried out in silico structural analysis. Our findings suggest that this variant also prevents PAK1 homodimerization, leading to constitutive PAK1 activation.

Heterozygous c.175C>T variant in PURA gene causes severe developmental delay.

Key Clinical Message: This case report presents a child with PURA-related neurodevelopmental disorder, caused by the heterozygous pathogenic variant c.175C>T (p.Gln59*). The clinical symptoms included microcephaly, brachygnathia, central and peripheral hypotonia, and developmental delay (non-verbal), among others. On comparison with published literature, even patients with the same mutation present different clinical symptoms. Abstract: This case report presents a child with PURA-related neurodevelopmental disorder, caused by the heterozygous pathogenic variant c.175C>T (p.Gln59*), whose symptoms included microcephaly, brachygnathia, the development of a high anterior hairline, hip dysplasia, strabismus, severe hypotonia, developmental delay (non-meaningful verbal), feeding difficulties, and respiratory difficulties. His development ceased with age, such that his development at 10 years corresponded to an infant of 6 months. Moreover, even patients with the same variant can have different clinical symptoms, such as the presence or absence of epilepsy or congenital malformations. Therefore, we should follow his long-term clinical course and provide medical support as necessary.

Biallelic structural variations within FGF12 detected by long-read sequencing in epilepsy.

We discovered biallelic intragenic structural variations (SVs) in FGF12 by applying long-read whole genome sequencing to an exome-negative patient with developmental and epileptic encephalopathy (DEE). We also found another DEE patient carrying a biallelic (homozygous) single-nucleotide variant (SNV) in FGF12 that was detected by exome sequencing. FGF12 heterozygous recurrent missense variants with gain-of-function or heterozygous entire duplication of FGF12 are known causes of epilepsy, but biallelic SNVs/SVs have never been described. FGF12 encodes intracellular proteins interacting with the C-terminal domain of the alpha subunit of voltage-gated sodium channels 1.2, 1.5, and 1.6, promoting excitability by delaying fast inactivation of the channels. To validate the molecular pathomechanisms of these biallelic FGF12 SVs/SNV, highly sensitive gene expression analyses using lymphoblastoid cells from the patient with biallelic SVs, structural considerations, and Drosophila in vivo functional analysis of the SNV were performed, confirming loss-of-function. Our study highlights the importance of small SVs in Mendelian disorders, which may be overlooked by exome sequencing but can be detected efficiently by long-read whole genome sequencing, providing new insights into the pathomechanisms of human diseases.

Large-scale discovery of novel neurodevelopmental disorder-related genes through a unified analysis of single-nucleotide and copy number variants.

BACKGROUND: Previous large-scale studies of de novo variants identified a number of genes associated with neurodevelopmental disorders (NDDs); however, it was also predicted that many NDD-associated genes await discovery. Such genes can be discovered by integrating copy number variants (CNVs), which have not been fully considered in previous studies, and increasing the sample size. METHODS: We first constructed a model estimating the rates of de novo CNVs per gene from several factors such as gene length and number of exons. Second, we compiled a comprehensive list of de novo single-nucleotide variants (SNVs) in 41,165 individuals and de novo CNVs in 3675 individuals with NDDs by aggregating our own and publicly available datasets, including denovo-db and the Deciphering Developmental Disorders study data. Third, summing up the de novo CNV rates that we estimated and SNV rates previously established, gene-based enrichment of de novo deleterious SNVs and CNVs were assessed in the 41,165 cases. Significantly enriched genes were further prioritized according to their similarity to known NDD genes using a deep learning model that considers functional characteristics (e.g., gene ontology and expression patterns). RESULTS: We identified a total of 380 genes achieving statistical significance (5% false discovery rate), including 31 genes affected by de novo CNVs. Of the 380 genes, 52 have not previously been reported as NDD genes, and the data of de novo CNVs contributed to the significance of three genes (GLTSCR1, MARK2, and UBR3). Among the 52 genes, we reasonably excluded 18 genes [a number almost identical to the theoretically expected false positives (i.e., 380 × 0.05 = 19)] given their constraints against deleterious variants and extracted 34 "plausible" candidate genes. Their validity as NDD genes was consistently supported by their similarity in function and gene expression patterns to known NDD genes. Quantifying the overall similarity using deep learning, we identified 11 high-confidence (> 90% true-positive probabilities) candidate genes: HDAC2, SUPT16H, HECTD4, CHD5, XPO1, GSK3B, NLGN2, ADGRB1, CTR9, BRD3, and MARK2. CONCLUSIONS: We identified dozens of new candidates for NDD genes. Both the methods and the resources developed here will contribute to the further identification of novel NDD-associated genes.

A pipeline for complete characterization of complex germline rearrangements from long DNA reads.

BACKGROUND: Many genetic/genomic disorders are caused by genomic rearrangements. Standard methods can often characterize these variations only partly, e.g., copy number changes or breakpoints. It is important to fully understand the order and orientation of rearranged fragments, with precise breakpoints, to know the pathogenicity of the rearrangements. METHODS: We performed whole-genome-coverage nanopore sequencing of long DNA reads from four patients with chromosomal translocations. We identified rearrangements relative to a reference human genome, subtracted rearrangements shared by any of 33 control individuals, and determined the order and orientation of rearranged fragments, with our newly developed analysis pipeline. RESULTS: We describe the full characterization of complex chromosomal rearrangements, by filtering out genomic rearrangements seen in controls without the same disease, reducing the number of loci per patient from a few thousand to a few dozen. Breakpoint detection was very accurate; we usually see ~ 0 ± 1 base difference from Sanger sequencing-confirmed breakpoints. For one patient with two reciprocal chromosomal translocations, we find that the translocation points have complex rearrangements of multiple DNA fragments involving 5 chromosomes, which we could order and orient by an automatic algorithm, thereby fully reconstructing the rearrangement. A rearrangement is more than the sum of its parts: some properties, such as sequence loss, can be inferred only after reconstructing the whole rearrangement. In this patient, the rearrangements were evidently caused by shattering of the chromosomes into multiple fragments, which rejoined in a different order and orientation with loss of some fragments. CONCLUSIONS: We developed an effective analytic pipeline to find chromosomal aberration in congenital diseases by filtering benign changes, only from long read sequencing. Our algorithm for reconstruction of complex rearrangements is useful to interpret rearrangements with many breakpoints, e.g., chromothripsis. Our approach promises to fully characterize many congenital germline rearrangements, provided they do not involve poorly understood loci such as centromeric repeats.