Biallelic variation in the choline and ethanolamine transporter FLVCR1 underlies a severe developmental disorder spectrum.

PURPOSE: FLVCR1 encodes a solute carrier (SLC) protein implicated in heme, choline, and ethanolamine transport. While Flvcr1-/- mice exhibit skeletal malformations and defective erythropoiesis reminiscent of Diamond-Blackfan anemia (DBA), biallelic FLVCR1 variants in humans have previously only been linked to childhood or adult-onset ataxia, sensory neuropathy, and retinitis pigmentosa. METHODS: We identified individuals with undiagnosed neurodevelopmental disorders and biallelic FLVCR1 variants through international data sharing and characterized the functional consequences of their FLVCR1 variants. RESULTS: We ascertained 30 patients from 23 unrelated families with biallelic FLVCR1 variants and characterized a novel FLVCR1-related phenotype: severe developmental disorders with profound developmental delay, microcephaly (Z-score -2.5 to -10.5), brain malformations, epilepsy, spasticity, and premature death. Brain malformations ranged from mild brain volume reduction to hydranencephaly. Severely affected patients share traits including macrocytic anemia and skeletal malformations with Flvcr1-/- mice and DBA. FLVCR1 variants significantly reduce choline and ethanolamine transport and/or disrupt mRNA splicing. CONCLUSION: These data demonstrate a broad FLVCR1-related phenotypic spectrum ranging from severe multiorgan developmental disorders resembling DBA to adult-onset neurodegeneration. Our study expands our understanding of Mendelian choline and ethanolamine disorders and illustrates the importance of anticipating a wide phenotypic spectrum for known disease genes and incorporating model organism data into genome analysis to maximize genetic testing yield.

Exome sequencing implicates ancestry-related Mendelian variation at SYNE1 in childhood-onset essential hypertension.

Childhood-onset essential hypertension (COEH) is an uncommon form of hypertension that manifests in childhood or adolescence and, in the United States, disproportionately affects children of African ancestry. The etiology of COEH is unknown, but its childhood onset, low prevalence, high heritability, and skewed ancestral demography suggest the potential to identify rare genetic variation segregating in a Mendelian manner among affected individuals and thereby implicate genes important to disease pathogenesis. However, no COEH genes have been reported to date. Here, we identify recessive segregation of rare and putatively damaging missense variation in the spectrin domain of spectrin repeat containing nuclear envelope protein 1 (SYNE1), a cardiovascular candidate gene, in 3 of 16 families with early-onset COEH without an antecedent family history. By leveraging exome sequence data from an additional 48 COEH families, 1,700 in-house trios, and publicly available data sets, we demonstrate that compound heterozygous SYNE1 variation in these COEH individuals occurred more often than expected by chance and that this class of biallelic rare variation was significantly enriched among individuals of African genetic ancestry. Using in vitro shRNA knockdown of SYNE1, we show that reduced SYNE1 expression resulted in a substantial decrease in the elasticity of smooth muscle vascular cells that could be rescued by pharmacological inhibition of the downstream RhoA/Rho-associated protein kinase pathway. These results provide insights into the molecular genetics and underlying pathophysiology of COEH and suggest a role for precision therapeutics in the future.

Multilocus pathogenic variants contribute to intrafamilial clinical heterogeneity: a retrospective study of sibling pairs with neurodevelopmental disorders.

BACKGROUND: Multilocus pathogenic variants (MPVs) are genetic changes that affect multiple gene loci or regions of the genome, collectively leading to multiple molecular diagnoses. MPVs may also contribute to intrafamilial phenotypic variability between affected individuals within a nuclear family. In this study, we aim to gain further insights into the influence of MPVs on a disease manifestation in individual research subjects and explore the complexities of the human genome within a familial context. METHODS: We conducted a systematic reanalysis of exome sequencing data and runs of homozygosity (ROH) regions of 47 sibling pairs previously diagnosed with various neurodevelopmental disorders (NDD). RESULTS: We found siblings with MPVs driven by long ROH regions in 8.5% of families (4/47). The patients with MPVs exhibited significantly higher FROH values (p-value = 1.4e-2) and larger total ROH length (p-value = 1.8e-2). Long ROH regions mainly contribute to this pattern; the siblings with MPVs have a larger total size of long ROH regions than their siblings in all families (p-value = 6.9e-3). Whereas the short ROH regions in the siblings with MPVs are lower in total size compared to their sibling pairs with single locus pathogenic variants (p-value = 0.029), and there are no statistically significant differences in medium ROH regions between sibling pairs (p-value = 0.52). CONCLUSION: This study sheds light on the significance of considering MPVs in families with affected sibling pairs and the role of ROH as an adjuvant tool in explaining clinical variability within families. Identifying individuals carrying MPVs may have implications for disease management, identification of possible disease risks to different family members, genetic counseling and exploring personalized treatment approaches.

NODAL variants are associated with a continuum of laterality defects from simple D-transposition of the great arteries to heterotaxy.

BACKGROUND: NODAL signaling plays a critical role in embryonic patterning and heart development in vertebrates. Genetic variants resulting in perturbations of the TGF-ß/NODAL signaling pathway have reproducibly been shown to cause laterality defects in humans. To further explore this association and improve genetic diagnosis, the study aims to identify and characterize a broader range of NODAL variants in a large number of individuals with laterality defects. METHODS: We re-analyzed a cohort of 321 proband-only exomes of individuals with clinically diagnosed laterality congenital heart disease (CHD) using family-based, rare variant genomic analyses. To this cohort we added 12 affected subjects with known NODAL variants and CHD from institutional research and clinical cohorts to investigate an allelic series. For those with candidate contributory variants, variant allele confirmation and segregation analysis were studied by Sanger sequencing in available family members. Array comparative genomic hybridization and droplet digital PCR were utilized for copy number variants (CNV) validation and characterization. We performed Human Phenotype Ontology (HPO)-based quantitative phenotypic analyses to dissect allele-specific phenotypic differences. RESULTS: Missense, nonsense, splice site, indels, and/or structural variants of NODAL were identified as potential causes of heterotaxy and other laterality defects in 33 CHD cases. We describe a recurrent complex indel variant for which the nucleic acid secondary structure predictions implicate secondary structure mutagenesis as a possible mechanism for formation. We identified two CNV deletion alleles spanning NODAL in two unrelated CHD cases. Furthermore, 17 CHD individuals were found (16/17 with known Hispanic ancestry) to have the c.778G > A:p.G260R NODAL missense variant which we propose reclassification from variant of uncertain significance (VUS) to likely pathogenic. Quantitative HPO-based analyses of the observed clinical phenotype for all cases with p.G260R variation, including heterozygous, homozygous, and compound heterozygous cases, reveal clustering of individuals with biallelic variation. This finding provides evidence for a genotypic-phenotypic correlation and an allele-specific gene dosage model. CONCLUSION: Our data further support a role for rare deleterious variants in NODAL as a cause for sporadic human laterality defects, expand the repertoire of observed anatomical complexity of potential cardiovascular anomalies, and implicate an allele specific gene dosage model.

Biallelic variation in the choline and ethanolamine transporter FLVCR1 underlies a pleiotropic disease spectrum from adult neurodegeneration to severe developmental disorders.

FLVCR1 encodes Feline leukemia virus subgroup C receptor 1 (FLVCR1), a solute carrier (SLC) transporter within the Major Facilitator Superfamily. FLVCR1 is a widely expressed transmembrane protein with plasma membrane and mitochondrial isoforms implicated in heme, choline, and ethanolamine transport. While Flvcr1 knockout mice die in utero with skeletal malformations and defective erythropoiesis reminiscent of Diamond-Blackfan anemia, rare biallelic pathogenic FLVCR1 variants are linked to childhood or adult-onset neurodegeneration of the retina, spinal cord, and peripheral nervous system. We ascertained from research and clinical exome sequencing 27 individuals from 20 unrelated families with biallelic ultra-rare missense and predicted loss-of-function (pLoF) FLVCR1 variant alleles. We characterize an expansive FLVCR1 phenotypic spectrum ranging from adult-onset retinitis pigmentosa to severe developmental disorders with microcephaly, reduced brain volume, epilepsy, spasticity, and premature death. The most severely affected individuals, including three individuals with homozygous pLoF variants, share traits with Flvcr1 knockout mice and Diamond-Blackfan anemia including macrocytic anemia and congenital skeletal malformations. Pathogenic FLVCR1 missense variants primarily lie within transmembrane domains and reduce choline and ethanolamine transport activity compared with wild-type FLVCR1 with minimal impact on FLVCR1 stability or subcellular localization. Several variants disrupt splicing in a mini-gene assay which may contribute to genotype-phenotype correlations. Taken together, these data support an allele-specific gene dosage model in which phenotypic severity reflects residual FLVCR1 activity. This study expands our understanding of Mendelian disorders of choline and ethanolamine transport and demonstrates the importance of choline and ethanolamine in neurodevelopment and neuronal homeostasis.

Decoding complex inherited phenotypes in rare disorders: the DECIPHERD initiative for rare undiagnosed diseases in Chile.

Rare diseases affect millions of people worldwide, and most have a genetic etiology. The incorporation of next-generation sequencing into clinical settings, particularly exome and genome sequencing, has resulted in an unprecedented improvement in diagnosis and discovery in the past decade. Nevertheless, these tools are unavailable in many countries, increasing health care gaps between high- and low-and-middle-income countries and prolonging the "diagnostic odyssey" for patients. To advance genomic diagnoses in a setting of limited genomic resources, we developed DECIPHERD, an undiagnosed diseases program in Chile. DECIPHERD was implemented in two phases: training and local development. The training phase relied on international collaboration with Baylor College of Medicine, and the local development was structured as a hybrid model, where clinical and bioinformatics analysis were performed in-house and sequencing outsourced abroad, due to lack of high-throughput equipment in Chile. We describe the implementation process and findings of the first 103 patients. They had heterogeneous phenotypes, including congenital anomalies, intellectual disabilities and/or immune system dysfunction. Patients underwent clinical exome or research exome sequencing, as solo cases or with parents using a trio design. We identified pathogenic, likely pathogenic or variants of unknown significance in genes related to the patients´ phenotypes in 47 (45.6%) of them. Half were de novo informative variants, and half of the identified variants have not been previously reported in public databases. DECIPHERD ended the diagnostic odyssey for many participants. This hybrid strategy may be useful for settings of similarly limited genomic resources and lead to discoveries in understudied populations.

HMZDupFinder: a robust computational approach for detecting intragenic homozygous duplications from exome sequencing data.

Homozygous duplications contribute to genetic disease by altering gene dosage or disrupting gene regulation and can be more deleterious to organismal biology than heterozygous duplications. Intragenic exonic duplications can result in loss-of-function (LoF) or gain-of-function (GoF) alleles that when homozygosed, i.e. brought to homozygous state at a locus by identity by descent or state, could potentially result in autosomal recessive (AR) rare disease traits. However, the detection and functional interpretation of homozygous duplications from exome sequencing data remains a challenge. We developed a framework algorithm, HMZDupFinder, that is designed to detect exonic homozygous duplications from exome sequencing (ES) data. The HMZDupFinder algorithm can efficiently process large datasets and accurately identifies small intragenic duplications, including those associated with rare disease traits. HMZDupFinder called 965 homozygous duplications with three or less exons from 8,707 ES with a recall rate of 70.9% and a precision of 16.1%. We experimentally confirmed 8/10 rare homozygous duplications. Pathogenicity assessment of these copy number variant alleles allowed clinical genomics contextualization for three homozygous duplications alleles, including two affecting known OMIM disease genes EDAR (MIM# 224900), TNNT1(MIM# 605355), and one variant in a novel candidate disease gene: PAAF1.

aenmd: annotating escape from nonsense-mediated decay for transcripts with protein-truncating variants.

SUMMARY: DNA changes that cause premature termination codons (PTCs) represent a large fraction of clinically relevant pathogenic genomic variation. Typically, PTCs induce transcript degradation by nonsense-mediated mRNA decay (NMD) and render such changes loss-of-function alleles. However, certain PTC-containing transcripts escape NMD and can exert dominant-negative or gain-of-function (DN/GOF) effects. Therefore, systematic identification of human PTC-causing variants and their susceptibility to NMD contributes to the investigation of the role of DN/GOF alleles in human disease. Here we present aenmd, a software for annotating PTC-containing transcript-variant pairs for predicted escape from NMD. aenmd is user-friendly and self-contained. It offers functionality not currently available in other methods and is based on established and experimentally validated rules for NMD escape; the software is designed to work at scale, and to integrate seamlessly with existing analysis workflows. We applied aenmd to variants in the gnomAD, Clinvar, and GWAS catalog databases and report the prevalence of human PTC-causing variants in these databases, and the subset of these variants that could exert DN/GOF effects via NMD escape. AVAILABILITY AND IMPLEMENTATION: aenmd is implemented in the R programming language. Code is available on GitHub as an R-package (github.com/kostkalab/aenmd.git), and as a containerized command-line interface (github.com/kostkalab/aenmd_cli.git).

Biallelic missense variants in COG3 cause a congenital disorder of glycosylation with impairment of retrograde vesicular trafficking.

Biallelic variants in genes for seven out of eight subunits of the conserved oligomeric Golgi complex (COG) are known to cause recessive congenital disorders of glycosylation (CDG) with variable clinical manifestations. COG3 encodes a constituent subunit of the COG complex that has not been associated with disease traits in humans. Herein, we report two COG3 homozygous missense variants in four individuals from two unrelated consanguineous families that co-segregated with COG3-CDG presentations. Clinical phenotypes of affected individuals include global developmental delay, severe intellectual disability, microcephaly, epilepsy, facial dysmorphism, and variable neurological findings. Biochemical analysis of serum transferrin from one family showed the loss of a single sialic acid. Western blotting on patient-derived fibroblasts revealed reduced COG3 and COG4. Further experiments showed delayed retrograde vesicular recycling in patient cells. This report adds to the knowledge of the COG-CDG network by providing collective evidence for a COG3-CDG rare disease trait and implicating a likely pathology of the disorder as the perturbation of Golgi trafficking.

PLS3 missense variants affecting the actin-binding domains cause X-linked congenital diaphragmatic hernia and body-wall defects.

Congenital diaphragmatic hernia (CDH) is a relatively common and genetically heterogeneous structural birth defect associated with high mortality and morbidity. We describe eight unrelated families with an X-linked condition characterized by diaphragm defects, variable anterior body-wall anomalies, and/or facial dysmorphism. Using linkage analysis and exome or genome sequencing, we found that missense variants in plastin 3 (PLS3), a gene encoding an actin bundling protein, co-segregate with disease in all families. Loss-of-function variants in PLS3 have been previously associated with X-linked osteoporosis (MIM: 300910), so we used in silico protein modeling and a mouse model to address these seemingly disparate clinical phenotypes. The missense variants in individuals with CDH are located within the actin-binding domains of the protein but are not predicted to affect protein structure, whereas the variants in individuals with osteoporosis are predicted to result in loss of function. A mouse knockin model of a variant identified in one of the CDH-affected families, c.1497G>C (p.Trp499Cys), shows partial perinatal lethality and recapitulates the key findings of the human phenotype, including diaphragm and abdominal-wall defects. Both the mouse model and one adult human male with a CDH-associated PLS3 variant were observed to have increased rather than decreased bone mineral density. Together, these clinical and functional data in humans and mice reveal that specific missense variants affecting the actin-binding domains of PLS3 might have a gain-of-function effect and cause a Mendelian congenital disorder.

Monoallelic variation in DHX9, the gene encoding the DExH-box helicase DHX9, underlies neurodevelopment disorders and Charcot-Marie-Tooth disease.

DExD/H-box RNA helicases (DDX/DHX) are encoded by a large paralogous gene family; in a subset of these human helicase genes, pathogenic variation causes neurodevelopmental disorder (NDD) traits and cancer. DHX9 encodes a BRCA1-interacting nuclear helicase regulating transcription, R-loops, and homologous recombination and exhibits the highest mutational constraint of all DDX/DHX paralogs but remains unassociated with disease traits in OMIM. Using exome sequencing and family-based rare-variant analyses, we identified 20 individuals with de novo, ultra-rare, heterozygous missense or loss-of-function (LoF) DHX9 variant alleles. Phenotypes ranged from NDDs to the distal symmetric polyneuropathy axonal Charcot-Marie-Tooth disease (CMT2). Quantitative Human Phenotype Ontology (HPO) analysis demonstrated genotype-phenotype correlations with LoF variants causing mild NDD phenotypes and nuclear localization signal (NLS) missense variants causing severe NDD. We investigated DHX9 variant-associated cellular phenotypes in human cell lines. Whereas wild-type DHX9 was restricted to the nucleus, NLS missense variants abnormally accumulated in the cytoplasm. Fibroblasts from an individual with an NLS variant also showed abnormal cytoplasmic DHX9 accumulation. CMT2-associated missense variants caused aberrant nucleolar DHX9 accumulation, a phenomenon previously associated with cellular stress. Two NDD-associated variants, p.Gly411Glu and p.Arg761Gln, altered DHX9 ATPase activity. The severe NDD-associated variant p.Arg141Gln did not affect DHX9 localization but instead increased R-loop levels and double-stranded DNA breaks. Dhx9-/- mice exhibited hypoactivity in novel environments, tremor, and sensorineural hearing loss. All together, these results establish DHX9 as a critical regulator of mammalian neurodevelopment and neuronal homeostasis.

Gain-of-Function Variomics and Multi-omics Network Biology for Precision Medicine.

Traditionally, disease causal mutations were thought to disrupt gene function. However, it becomes more clear that many deleterious mutations could exhibit a "gain-of-function" (GOF) behavior. Systematic investigation of such mutations has been lacking and largely overlooked. Advances in next-generation sequencing have identified thousands of genomic variants that perturb the normal functions of proteins, further contributing to diverse phenotypic consequences in disease. Elucidating the functional pathways rewired by GOF mutations will be crucial for prioritizing disease-causing variants and their resultant therapeutic liabilities. In distinct cell types (with varying genotypes), precise signal transduction controls cell decision, including gene regulation and phenotypic output. When signal transduction goes awry due to GOF mutations, it would give rise to various disease types. Quantitative and molecular understanding of network perturbations by GOF mutations may provide explanations for 'missing heritability" in previous genome-wide association studies. We envision that it will be instrumental to push current paradigm toward a thorough functional and quantitative modeling of all GOF mutations and their mechanistic molecular events involved in disease development and progression. Many fundamental questions pertaining to genotype-phenotype relationships remain unresolved. For example, which GOF mutations are key for gene regulation and cellular decisions? What are the GOF mechanisms at various regulation levels? How do interaction networks undergo rewiring upon GOF mutations? Is it possible to leverage GOF mutations to reprogram signal transduction in cells, aiming to cure disease? To begin to address these questions, we will cover a wide range of topics regarding GOF disease mutations and their characterization by multi-omic networks. We highlight the fundamental function of GOF mutations and discuss the potential mechanistic effects in the context of signaling networks. We also discuss advances in bioinformatic and computational resources, which will dramatically help with studies on the functional and phenotypic consequences of GOF mutations.

Rare variant enrichment analysis supports GREB1L as a contributory driver gene in the etiology of Mayer-Rokitansky-Küster-Hauser syndrome.

Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome is characterized by aplasia of the female reproductive tract; the syndrome can include renal anomalies, absence or dysgenesis, and skeletal anomalies. While functional models have elucidated several candidate genes, only WNT4 (MIM: 603490) variants have been definitively associated with a subtype of MRKH with hyperandrogenism (MIM: 158330). DNA from 148 clinically diagnosed MRKH probands across 144 unrelated families and available family members from North America, Europe, and South America were exome sequenced (ES) and by family-based genomics analyzed for rare likely deleterious variants. A replication cohort consisting of 442 Han Chinese individuals with MRKH was used to further reproduce GREB1L findings in diverse genetic backgrounds. Proband and OMIM phenotypes annotated using the Human Phenotype Ontology were analyzed to quantitatively delineate the phenotypic spectrum associated with GREB1L variant alleles found in our MRKH cohort and those previously published. This study reports 18 novel GREB1L variant alleles, 16 within a multiethnic MRKH cohort and two within a congenital scoliosis cohort. Cohort-wide analyses for a burden of rare variants within a single gene identified likely damaging variants in GREB1L (MIM: 617782), a known disease gene for renal hypoplasia and uterine abnormalities (MIM: 617805), in 16 of 590 MRKH probands. GREB1L variant alleles, including a CNV null allele, were found in 8 MRKH type 1 probands and 8 MRKH type II probands. This study used quantitative phenotypic analyses in a worldwide multiethnic cohort to identify and strengthen the association of GREB1L to isolated uterine agenesis (MRKH type I) and syndromic MRKH type II.

aenmd: Annotating escape from nonsense-mediated decay for transcripts with protein-truncating variants.

DNA changes that cause premature termination codons (PTCs) represent a large fraction of clinically relevant pathogenic genomic variation. Typically, PTCs induce a transcript's degradation by nonsense-mediated mRNA decay (NMD) and render such changes loss-of-function alleles. However, certain PTC-containing transcripts escape NMD and can exert dominant-negative or gain-of-function (DN/GOF) effects. Therefore, systematic identification of human PTC-causing variants and their susceptibility to NMD contributes to the investigation of the role of DN/GOF alleles in human disease. Here we present aenmd, a software for annotating PTC-containing transcript-variant pairs for predicted escape from NMD. aenmd is user-friendly and self-contained. It offers functionality not currently available in other methods and is based on established and experimentally validated rules for NMD escape; the software is designed to work at scale, and to integrate seamlessly with existing analysis workflows. We applied aenmd to variants in the gnomAD, Clinvar, and GWAS catalog databases and report the prevalence of human PTC-causing variants in these databases, and the subset of these that could exert DN/GOF effects via NMD escape. Availability and implementation: aenmd is implemented in the R programming language. Code is available on GitHub as an R package (github.com/kostkalab/aenmd.git), and as a containerized command-line interface (github.com/kostkalab/aenmd_cli.git).

AI-DrugNet: A network-based deep learning model for drug repurposing and combination therapy in neurological disorders.

Discovering effective therapies is difficult for neurological and developmental disorders in that disease progression is often associated with a complex and interactive mechanism. Over the past few decades, few drugs have been identified for treating Alzheimer's disease (AD), especially for impacting the causes of cell death in AD. Although drug repurposing is gaining more success in developing therapeutic efficacy for complex diseases such as common cancer, the complications behind AD require further study. Here, we developed a novel prediction framework based on deep learning to identify potential repurposed drug therapies for AD, and more importantly, our framework is broadly applicable and may generalize to identifying potential drug combinations in other diseases. Our prediction framework is as follows: we first built a drug-target pair (DTP) network based on multiple drug features and target features, as well as the associations between DTP nodes where drug-target pairs are the DTP nodes and the associations between DTP nodes are represented as the edges in the AD disease network; furthermore, we incorporated the drug-target feature from the DTP network and the relationship information between drug-drug, target-target, drug-target within and outside of drug-target pairs, representing each drug-combination as a quartet to generate corresponding integrated features; finally, we developed an AI-based Drug discovery Network (AI-DrugNet), which exhibits robust predictive performance. The implementation of our network model help identify potential repurposed and combination drug options that may serve to treat AD and other diseases.

AD-Syn-Net: systematic identification of Alzheimer's disease-associated mutation and co-mutation vulnerabilities via deep learning.

Alzheimer's disease (AD) is one of the most challenging neurodegenerative diseases because of its complicated and progressive mechanisms, and multiple risk factors. Increasing research evidence demonstrates that genetics may be a key factor responsible for the occurrence of the disease. Although previous reports identified quite a few AD-associated genes, they were mostly limited owing to patient sample size and selection bias. There is a lack of comprehensive research aimed to identify AD-associated risk mutations systematically. To address this challenge, we hereby construct a large-scale AD mutation and co-mutation framework ('AD-Syn-Net'), and propose deep learning models named Deep-SMCI and Deep-CMCI configured with fully connected layers that are capable of predicting cognitive impairment of subjects effectively based on genetic mutation and co-mutation profiles. Next, we apply the customized frameworks to data sets to evaluate the importance scores of the mutations and identified mutation effectors and co-mutation combination vulnerabilities contributing to cognitive impairment. Furthermore, we evaluate the influence of mutation pairs on the network architecture to dissect the genetic organization of AD and identify novel co-mutations that could be responsible for dementia, laying a solid foundation for proposing future targeted therapy for AD precision medicine. Our deep learning model codes are available open access here: https://github.com/Pan-Bio/AD-mutation-effectors.

A biallelic frameshift indel in PPP1R35 as a cause of primary microcephaly.

Protein phosphatase 1 regulatory subunit 35 (PPP1R35) encodes a centrosomal protein required for recruiting microtubule-binding elongation machinery. Several proteins in this centriole biogenesis pathway correspond to established primary microcephaly (MCPH) genes, and multiple model organism studies hypothesize PPP1R35 as a candidate MCPH gene. Here, using exome sequencing (ES) and family-based rare variant analyses, we report a homozygous, frameshifting indel deleting the canonical stop codon in the last exon of PPP1R35 [Chr7: c.753_*3delGGAAGCGTAGACCinsCG (p.Trp251Cysfs*22)]; the variant allele maps in a 3.7 Mb block of absence of heterozygosity (AOH) in a proband with severe MCPH (-4.3 SD at birth, -6.1 SD by 42 months), pachygyria, and global developmental delay from a consanguineous Turkish kindred. Droplet digital PCR (ddPCR) confirmed mutant mRNA expression in fibroblasts. In silico prediction of the translation of mutant PPP1R35 is expected to be elongated by 18 amino acids before encountering a downstream stop codon. This complex indel allele is absent in public databases (ClinVar, gnomAD, ARIC, 1000 genomes) and our in-house database of 14,000+ exomes including 1800+ Turkish exomes supporting predicted pathogenicity. Comprehensive literature searches for PPP1R35 variants yielded two probands affected with severe microcephaly (-15 SD and -12 SD) with the same homozygous indel from a single, consanguineous, Iranian family from a cohort of 404 predominantly Iranian families. The lack of heterozygous cases in two large cohorts representative of the genetic background of these two families decreased our suspicion of a founder allele and supports the contention of a recurrent mutation. We propose two potential secondary structure mutagenesis models for the origin of this variant allele mediated by hairpin formation between complementary GC rich segments flanking the stop codon via secondary structure mutagenesis.

Biallelic variants in HECT E3 paralogs, HECTD4 and UBE3C, encoding ubiquitin ligases cause neurodevelopmental disorders that overlap with Angelman syndrome.

PURPOSE: Pathogenic variants in genes encoding ubiquitin E3 ligases are known to cause neurodevelopmental syndromes. Additional neurodevelopmental disorders associated with the other genes encoding E3 ligases are yet to be identified. METHODS: Chromosomal analysis and exome sequencing were used to identify the genetic causes in 10 patients from 7 unrelated families with syndromic neurodevelopmental, seizure, and movement disorders and neurobehavioral phenotypes. RESULTS: In total, 4 patients were found to have 3 different homozygous loss-of-function (LoF) variants, and 3 patients had 4 compound heterozygous missense variants in the candidate E3 ligase gene, HECTD4, that were rare, absent from controls as homozygous, and predicted to be deleterious in silico. In 3 patients from 2 families with Angelman-like syndrome, paralog-directed candidate gene approach detected 2 LoF variants in the other candidate E3 ligase gene, UBE3C, a paralog of the Angelman syndrome E3 ligase gene, UBE3A. The RNA studies in 4 patients with LoF variants in HECTD4 and UBE3C provided evidence for the LoF effect. CONCLUSION: HECTD4 and UBE3C are novel biallelic rare disease genes, expand the association of the other HECT E3 ligase group with neurodevelopmental syndromes, and could explain some of the missing heritability in patients with a suggestive clinical diagnosis of Angelman syndrome.