A Statistical Framework for Mapping Risk Genes from De Novo Mutations in Whole-Genome-Sequencing Studies

CWAS-Plus: estimating category-wide association of rare noncoding variation from whole-genome sequencing data with cell-type-specific functional data

Variants in cis-regulatory elements link the noncoding genome to human pathology; however, detailed analytic tools for understanding the association between cell-level brain pathology and noncoding variants are lacking. CWAS-Plus, adapted from a Python package for category-wide association testing (CWAS), enhances noncoding variant analysis by integrating both whole-genome sequencing (WGS) and user-provided functional data. With simplified parameter settings and an efficient multiple testing correction method, CWAS-Plus conducts the CWAS workflow 50 times faster than CWAS, making it more accessible and user-friendly for researchers. Here, we used a single-nuclei assay for transposase-accessible chromatin with sequencing to facilitate CWAS-guided noncoding variant analysis at cell-type-specific enhancers and promoters. Examining autism spectrum disorder WGS data (n = 7280), CWAS-Plus identified noncoding de novo variant associations in transcription factor binding sites within conserved loci. Independently, in Alzheimer's disease WGS data (n = 1087), CWAS-Plus detected rare noncoding variant associations in microglia-specific regulatory elements. These findings highlight CWAS-Plus's utility in genomic disorders and scalability for processing large-scale WGS data and in multiple-testing corrections. CWAS-Plus and its user manual are available at https://github.com/joonan-lab/cwas/ and https://cwas-plus.readthedocs.io/en/latest/, respectively.

Zmiz1 is a novel regulator of lymphatic endothelial cell gene expression and function

Zinc Finger MIZ-Type Containing 1 (Zmiz1), also known as ZIMP10 or RAI17, is a transcription cofactor and member of the Protein Inhibitor of Activated STAT (PIAS) family of proteins. Zmiz1 is critical for a variety of biological processes including vascular development. However, its role in the lymphatic vasculature is unknown. In this study, we utilized human dermal lymphatic endothelial cells (HDLECs) and an inducible, lymphatic endothelial cell (LEC)-specific Zmiz1 knockout mouse model to investigate the role of Zmiz1 in LECs. Transcriptional profiling of ZMIZ1-deficient HDLECs revealed downregulation of genes crucial for lymphatic vessel development. Additionally, our findings demonstrated that loss of Zmiz1 results in reduced expression of proliferation and migration genes in HDLECs and reduced proliferation and migration in vitro. We also presented evidence that Zmiz1 regulates Prox1 expression in vitro and in vivo by modulating chromatin accessibility at Prox1 regulatory regions. Furthermore, we observed that loss of Zmiz1 in mesenteric lymphatic vessels significantly reduced valve density. Collectively, our results highlight a novel role of Zmiz1 in LECs and as a transcriptional regulator of Prox1, shedding light on a previously unknown regulatory factor in lymphatic vascular biology.

CWAS-Plus: Estimating category-wide association of rare noncoding variation from whole-genome sequencing data with cell-type-specific functional data

Variants in cis-regulatory elements link the noncoding genome to human brain pathology; however, detailed analytic tools for understanding the association between cell-level brain pathology and noncoding variants are lacking. CWAS-Plus, adapted from a Python package for category-wide association testing (CWAS) employs both whole-genome sequencing and user-provided functional data to enhance noncoding variant analysis, with a faster and more efficient execution of the CWAS workflow. Here, we used single-nuclei assay for transposase-accessible chromatin with sequencing to facilitate CWAS-guided noncoding variant analysis at cell-type specific enhancers and promoters. Examining autism spectrum disorder whole-genome sequencing data (n = 7,280), CWAS-Plus identified noncoding de novo variant associations in transcription factor binding sites within conserved loci. Independently, in Alzheimer's disease whole-genome sequencing data (n = 1,087), CWAS-Plus detected rare noncoding variant associations in microglia-specific regulatory elements. These findings highlight CWAS-Plus's utility in genomic disorders and scalability for processing large-scale whole-genome sequencing data and in multiple-testing corrections. CWAS-Plus and its user manual are available at https://github.com/joonan-lab/cwas/ and https://cwas-plus.readthedocs.io/en/latest/, respectively.

Zmiz1 is a novel regulator of brain development associated with autism and intellectual disability

Neurodevelopmental disorders (NDDs) are a class of pathologies arising from perturbations in brain circuit formation and maturation with complex etiological triggers often classified as environmental and genetic. Neuropsychiatric conditions such as autism spectrum disorders (ASD), intellectual disability (ID), and attention deficit hyperactivity disorders (ADHD) are common NDDs characterized by their hereditary underpinnings and inherent heterogeneity. Genetic risk factors for NDDs are increasingly being identified in non-coding regions and proteins bound to them, including transcriptional regulators and chromatin remodelers. Importantly, de novo mutations are emerging as important contributors to NDDs and neuropsychiatric disorders. Recently, de novo mutations in transcriptional co-factor Zmiz1 or its regulatory regions have been identified in unrelated patients with syndromic ID and ASD. However, the role of Zmiz1 in brain development is unknown. Here, using publicly available databases and a Zmiz1 mutant mouse model, we reveal that Zmiz1 is highly expressed during embryonic brain development in mice and humans, and though broadly expressed across the brain, Zmiz1 is enriched in areas prominently impacted in ID and ASD such as cortex, hippocampus, and cerebellum. We investigated the relationship between Zmiz1 structure and pathogenicity of protein variants, the epigenetic marks associated with Zmiz1 regulation, and protein interactions and signaling pathways regulated by Zmiz1. Our analysis reveals that Zmiz1 regulates multiple developmental processes, including neurogenesis, neuron connectivity, and synaptic signaling. This work paves the way for future studies on the functions of Zmiz1 and highlights the importance of combining analysis of mouse models and human data.

Statistical methods for assessing the effects of de novo variants on birth defects

With the development of next-generation sequencing technology, de novo variants (DNVs) with deleterious effects can be identified and investigated for their effects on birth defects such as congenital heart disease (CHD). However, statistical power is still limited for such studies because of the small sample size due to the high cost of recruiting and sequencing samples and the low occurrence of DNVs. DNV analysis is further complicated by genetic heterogeneity across diseased individuals. Therefore, it is critical to jointly analyze DNVs with other types of genomic/biological information to improve statistical power to identify genes associated with birth defects. In this review, we discuss the general workflow, recent developments in statistical methods, and future directions for DNV analysis.

Tanc1/2 TPR domain interacts with Myo18a C-terminus and undergoes liquid-liquid phase separation

Tanc1 and its homologous protein Tanc2 are critical synaptic scaffold proteins which regulate synaptic spine densities and excitatory synapse strength. Recent studies indicated TANC1 and TANC2 are candidate genes of several neurodevelopmental disorders (NDDs). In this study, we identified and characterized a novel interaction between Tanc1/2 and Myo18a, mediated by the Tanc1/2 TPR domains and Myo18a coiled-coil domain and C-extension (CCex). Sequence analysis and size exclusion chromatography experiments reveal that high salt disrupts the interaction between Myo18a and Tanc1/2, indicating that the interaction is primarily driven by charge-charge interactions. More importantly, we found that the Tanc1-TPR/Myo18a CCex interaction could undergo liquid-liquid phase separation (LLPS) in both cultured cells and test tubes, which provides the biochemical basis and potential molecular mechanisms for the LLPS-mediated interactions between Myo18a and Tanc1/2.

Single-cell long-read sequencing in human cerebral organoids uncovers cell-type-specific and autism-associated exons

Dysregulation of alternative splicing has been repeatedly associated with neurodevelopmental disorders, but the extent of cell-type-specific splicing in human neural development remains largely uncharted. Here, single-cell long-read sequencing in induced pluripotent stem cell (iPSC)-derived cerebral organoids identifies over 31,000 uncatalogued isoforms and 4,531 cell-type-specific splicing events. Long reads uncover coordinated splicing and cell-type-specific intron retention events, which are challenging to study with short reads. Retained neuronal introns are enriched in RNA splicing regulators, showing shorter lengths, higher GC contents, and weaker 5' splice sites. We use this dataset to explore the biological processes underlying neurological disorders, focusing on autism. In comparison with prior transcriptomic data, we find that the splicing program in autistic brains is closer to the progenitor state than differentiated neurons. Furthermore, cell-type-specific exons harbor significantly more de novo mutations in autism probands than in siblings. Overall, these results highlight the importance of cell-type-specific splicing in autism and neuronal gene regulation.

Finding Needles in the Haystack: Strategies for Uncovering Noncoding Regulatory Variants

Despite accumulating evidence implicating noncoding variants in human diseases, unraveling their functionality remains a significant challenge. Systematic annotations of the regulatory landscape and the growth of sequence variant data sets have fueled the development of tools and methods to identify causal noncoding variants and evaluate their regulatory effects. Here, we review the latest advances in the field and discuss potential future research avenues to gain a more in-depth understanding of noncoding regulatory variants.

Zmiz1 is a novel regulator of lymphatic endothelial cell gene expression and function

Zinc Finger MIZ-Type Containing 1 (Zmiz1), also known as ZIMP10 or RAI17, is a transcription cofactor and member of the Protein Inhibitor of Activated STAT (PIAS) family of proteins. Zmiz1 is critical for a variety of biological processes including vascular development. However, its role in the lymphatic vasculature is unknown. In this study, we utilized human dermal lymphatic endothelial cells (HDLECs) and an inducible, lymphatic endothelial cell (LEC)-specific Zmiz1 knockout mouse model to investigate the role of Zmiz1 in LECs. Transcriptional profiling of Zmiz1-deficient HDLECs revealed downregulation of genes crucial for lymphatic vessel development. Additionally, our findings demonstrated that loss of Zmiz1 results in reduced expression of proliferation and migration genes in HDLECs and reduced proliferation and migration in vitro. We also presented evidence that Zmiz1 regulates Prox1 expression in vitro and in vivo by modulating chromatin accessibility at Prox1 regulatory regions. Furthermore, we observed that loss of Zmiz1 in mesenteric lymphatic vessels significantly reduced valve density. Collectively, our results highlight a novel role of Zmiz1 in LECs and as a transcriptional regulator of Prox1, shedding light on a previously unknown regulatory factor in lymphatic vascular biology.

Genome-wide rare variant score associates with morphological subtypes of autism spectrum disorder

Defining different genetic subtypes of autism spectrum disorder (ASD) can enable the prediction of developmental outcomes. Based on minor physical and major congenital anomalies, we categorize 325 Canadian children with ASD into dysmorphic and nondysmorphic subgroups. We develop a method for calculating a patient-level, genome-wide rare variant score (GRVS) from whole-genome sequencing (WGS) data. GRVS is a sum of the number of variants in morphology-associated coding and non-coding regions, weighted by their effect sizes. Probands with dysmorphic ASD have a significantly higher GRVS compared to those with nondysmorphic ASD (P = 0.03). Using the polygenic transmission disequilibrium test, we observe an over-transmission of ASD-associated common variants in nondysmorphic ASD probands (P = 2.9 × 10^-3). These findings replicate using WGS data from 442 ASD probands with accompanying morphology data from the Simons Simplex Collection. Our results provide support for an alternative genomic classification of ASD subgroups using morphology data, which may inform intervention protocols.

Network assisted analysis of de novo variants using protein-protein interaction information identified 46 candidate genes for congenital heart disease

De novo variants (DNVs) with deleterious effects have proved informative in identifying risk genes for early-onset diseases such as congenital heart disease (CHD). A number of statistical methods have been proposed for family-based studies or case/control studies to identify risk genes by screening genes with more DNVs than expected by chance in Whole Exome Sequencing (WES) studies. However, the statistical power is still limited for cohorts with thousands of subjects. Under the hypothesis that connected genes in protein-protein interaction (PPI) networks are more likely to share similar disease association status, we developed a Markov Random Field model that can leverage information from publicly available PPI databases to increase power in identifying risk genes. We identified 46 candidate genes with at least 1 DNV in the CHD study cohort, including 18 known human CHD genes and 35 highly expressed genes in mouse developing heart. Our results may shed new insight on the shared protein functionality among risk genes for CHD.

The topologic information in a pathway may be informative to identify functionally interrelated genes and help improve statistical power in DNV studies. Under the hypothesis that connected genes in PPI networks are more likely to share similar disease association status, we developed a novel statistical model that can leverage information from publicly available PPI databases. Through simulation studies under multiple settings, we proved our method can increase statistical power in identifying additional risk genes compared to methods without using the PPI network information. We then applied our method to a real example for CHD DNV data, and then visualized the subnetwork of candidate genes to find potential functional gene clusters for CHD.

Computational Genomics in the Era of Precision Medicine: Applications to Variant Analysis and Gene Therapy

Rapid methodological advances in statistical and computational genomics have enabled researchers to better identify and interpret both rare and common variants responsible for complex human diseases. As we continue to see an expansion of these advances in the field, it is now imperative for researchers to understand the resources and methodologies available for various data types and study designs. In this review, we provide an overview of recent methods for identifying rare and common variants and understanding their roles in disease etiology. Additionally, we discuss the strategy, challenge, and promise of gene therapy. As computational and statistical approaches continue to improve, we will have an opportunity to translate human genetic findings into personalized health care.

M-DATA: A statistical approach to jointly analyzing de novo mutations for multiple traits

Recent studies have demonstrated that multiple early-onset diseases have shared risk genes, based on findings from de novo mutations (DNMs). Therefore, we may leverage information from one trait to improve statistical power to identify genes for another trait. However, there are few methods that can jointly analyze DNMs from multiple traits. In this study, we develop a framework called M-DATA (Multi-trait framework for De novo mutation Association Test with Annotations) to increase the statistical power of association analysis by integrating data from multiple correlated traits and their functional annotations. Using the number of DNMs from multiple diseases, we develop a method based on an Expectation-Maximization algorithm to both infer the degree of association between two diseases as well as to estimate the gene association probability for each disease. We apply our method to a case study of jointly analyzing data from congenital heart disease (CHD) and autism. Our method was able to identify 23 genes for CHD from joint analysis, including 12 novel genes, which is substantially more than single-trait analysis, leading to novel insights into CHD disease etiology.

Identification of putative causal loci in whole-genome sequencing data via knockoff statistics

The analysis of whole-genome sequencing studies is challenging due to the large number of rare variants in noncoding regions and the lack of natural units for testing. We propose a statistical method to detect and localize rare and common risk variants in whole-genome sequencing studies based on a recently developed knockoff framework. It can (1) prioritize causal variants over associations due to linkage disequilibrium thereby improving interpretability; (2) help distinguish the signal due to rare variants from shadow effects of significant common variants nearby; (3) integrate multiple knockoffs for improved power, stability, and reproducibility; and (4) flexibly incorporate state-of-the-art and future association tests to achieve the benefits proposed here. In applications to whole-genome sequencing data from the Alzheimer's Disease Sequencing Project (ADSP) and COPDGene samples from NHLBI Trans-Omics for Precision Medicine (TOPMed) Program we show that our method compared with conventional association tests can lead to substantially more discoveries.

Tanc2-mediated mTOR inhibition balances mTORC1/2 signaling in the developing mouse brain and human neurons

mTOR signaling, involving mTORC1 and mTORC2 complexes, critically regulates neural development and is implicated in various brain disorders. However, we do not fully understand all of the upstream signaling components that can regulate mTOR signaling, especially in neurons. Here, we show a direct, regulated inhibition of mTOR by Tanc2, an adaptor/scaffolding protein with strong neurodevelopmental and psychiatric implications. While Tanc2-null mice show embryonic lethality, Tanc2-haploinsufficient mice survive but display mTORC1/2 hyperactivity accompanying synaptic and behavioral deficits reversed by mTOR-inhibiting rapamycin. Tanc2 interacts with and inhibits mTOR, which is suppressed by mTOR-activating serum or ketamine, a fast-acting antidepressant. Tanc2 and Deptor, also known to inhibit mTORC1/2 minimally affecting neurodevelopment, distinctly inhibit mTOR in early- and late-stage neurons. Lastly, Tanc2 inhibits mTORC1/2 in human neural progenitor cells and neurons. In summary, our findings show that Tanc2 is a mTORC1/2 inhibitor affecting neurodevelopment.

An increased burden of rare exonic variants in NRXN1 microdeletion carriers is likely to enhance the penetrance for autism spectrum disorder

Autism spectrum disorder (ASD) is characterized by a complex polygenic background, but with the unique feature of a subset of cases (~15%‐30%) presenting a rare large‐effect variant. However, clinical interpretation in these cases is often complicated by incomplete penetrance, variable expressivity and different neurodevelopmental trajectories. NRXN1 intragenic deletions represent the prototype of such ASD‐associated susceptibility variants. From chromosomal microarrays analysis of 104 ASD individuals, we identified an inherited NRXN1 deletion in a trio family. We carried out whole‐exome sequencing and deep sequencing of mitochondrial DNA (mtDNA) in this family, to evaluate the burden of rare variants which may contribute to the phenotypic outcome in NRXN1 deletion carriers. We identified an increased burden of exonic rare variants in the ASD child compared to the unaffected NRXN1 deletion‐transmitting mother, which remains significant if we restrict the analysis to potentially deleterious rare variants only (P = 6.07 × 10⁻⁵). We also detected significant interaction enrichment among genes with damaging variants in the proband, suggesting that additional rare variants in interacting genes collectively contribute to cross the liability threshold for ASD. Finally, the proband's mtDNA presented five low‐level heteroplasmic mtDNA variants that were absent in the mother, and two maternally inherited variants with increased heteroplasmic load. This study underlines the importance of a comprehensive assessment of the genomic background in carriers of large‐effect variants, as penetrance modulation by additional interacting rare variants to might represent a widespread mechanism in neurodevelopmental disorders.

Identification of SETBP1 Mutations by Gene Panel Sequencing in Individuals With Intellectual Disability or With "Developmental and Epileptic Encephalopathy"

SETBP1 mutations are associated with the Schinzel-Giedion syndrome (SGS), characterized by profound neurodevelopmental delay, typical facial features, and multiple congenital malformations (OMIM 269150). Refractory epilepsy is a common feature of SGS. Loss of function mutations have been typically associated with a distinct and milder phenotype characterized by intellectual disability and expressive speech impairment. Here we report three variants of SETBP1, two novel de novo truncating mutations, identified by NGS analysis of an Intellectual Disability gene panel in 600 subjects with non-specific neurodevelopmental disorders, and one missense identified by a developmental epilepsy gene panel tested in 56 pediatric epileptic cases. The three individuals carrying the identified SETBP1 variants presented mild to severe developmental delay and lacked the cardinal features of classical SGS. One of these subjects, carrying the c.1765C>T (p.Arg589^*) mutation, had mild Intellectual Disability with speech delay; the second one carrying the c.2199_2203del (p.Glu734Alafs19^*) mutation had generalized epilepsy, responsive to treatment, and moderate Intellectual Disability; the third patient showed a severe cognitive defects and had a history of drug resistant epilepsy with West syndrome evolved into a Lennox-Gastaut syndrome. This latter subject carries the missense c.2572G>A (p.Glu858Lys) variant, which is absent from the control population, reported as de novo in a subject with ASD, and located close to the SETBP1 hot spot for SGS-associated mutations. Our findings contribute to further characterizing the associated phenotypes and suggest inclusion of SETBP1 in the list of prioritized genes for the genetic diagnosis of overlapping phenotypes ranging from non-specific neurodevelopmental disorders to “developmental and epileptic encephalopathy” (DEE).

Leveraging large genomic datasets to illuminate the pathobiology of autism spectrum disorders

"Big data" approaches in the form of large-scale human genomic studies have led to striking advances in autism spectrum disorder (ASD) genetics. Similar to many other psychiatric syndromes, advances in genotyping technology, allowing for inexpensive genome-wide assays, has confirmed the contribution of polygenic inheritance involving common alleles of small effect, a handful of which have now been definitively identified. However, the past decade of gene discovery in ASD has been most notable for the application, in large family-based cohorts, of high-density microarray studies of submicroscopic chromosomal structure as well as high-throughput DNA sequencing-leading to the identification of an increasingly long list of risk regions and genes disrupted by rare, de novo germline mutations of large effect. This genomic architecture offers particular advantages for the illumination of biological mechanisms but also presents distinctive challenges. While the tremendous locus heterogeneity and functional pleiotropy associated with the more than 100 identified ASD-risk genes and regions is daunting, a growing armamentarium of comprehensive, large, foundational -omics databases, across species and capturing developmental trajectories, are increasingly contributing to a deeper understanding of ASD pathology.

Rare variant association testing in the non-coding genome

The development of next-generation sequencing technologies has opened-up some new possibilities to explore the contribution of genetic variants to human diseases and in particular that of rare variants. Statistical methods have been developed to test for association with rare variants that require the definition of testing units and, in these testing units, the selection of qualifying variants to include in the test. In the coding regions of the genome, testing units are usually the different genes and qualifying variants are selected based on their functional effects on the encoded proteins. Extending these tests to the non-coding regions of the genome is challenging. Testing units are difficult to define as the non-coding genome organisation is still rather unknown. Qualifying variants are difficult to select as the functional impact of non-coding variants on gene expression is hard to predict. These difficulties could explain why very few investigators so far have analysed the non-coding parts of their whole genome sequencing data. These non-coding parts yet represent the vast majority of the genome and some studies suggest that they could play a major role in disease susceptibility. In this review, we discuss recent experimental and statistical developments to gain knowledge on the non-coding genome and how this knowledge could be used to include rare non-coding variants in association tests. We describe the few studies that have considered variants from the non-coding genome in association tests and how they managed to define testing units and select qualifying variants.

Modeling neuronal consequences of autism-associated gene regulatory variants with human induced pluripotent stem cells

Genetic factors contribute to the development of autism spectrum disorder (ASD), and although non-protein-coding regions of the genome are being increasingly implicated in ASD, the functional consequences of these variants remain largely uncharacterized. Induced pluripotent stem cells (iPSCs) enable the production of personalized neurons that are genetically matched to people with ASD and can therefore be used to directly test the effects of genomic variation on neuronal gene expression, synapse function, and connectivity. The combined use of human pluripotent stem cells with genome editing to introduce or correct specific variants has proved to be a powerful approach for exploring the functional consequences of ASD-associated variants in protein-coding genes and, more recently, long non-coding RNAs (lncRNAs). Here, we review recent studies that implicate lncRNAs, other non-coding mutations, and regulatory variants in ASD susceptibility. We also discuss experimental design considerations for using iPSCs and genome editing to study the role of the non-protein-coding genome in ASD.

Autosomal dominant inheritance in a recently described ZMIZ1-related neurodevelopmental disorder: Case report of siblings and an affected parent

ZMIZ1, zinc finger MIZ-domain containing 1, has recently been described in association with syndromic intellectual disability in which the primary phenotypic features include intellectual disability/developmental delay, seizures, hearing loss, behavioral issues, failure to thrive, and various congenital malformations. Most reported cases have been found to result from de novo mutations except for one set of three siblings in which parental testing could not be performed. With informed consent from the family, we report on a father and his two sons demonstrating autosomal dominant inheritance of a novel pathogenic ZMIZ1 variant, c.1310delC (p.Pro437ArgfsX84), causing this recently described neurodevelopmental syndrome. While they all show syndromic findings along with short stature and intellectual disability, only one child had sensorineural hearing loss. Moreover, severity of intellectual disability and eyelid ptosis were variable among the affected members. Our report demonstrates that phenotypic features of ZMIZ1-related neurodevelopmental syndrome are variable even within the same family and that parental testing to identify a mildly affected parent is needed.

Purification and mutagenesis studies of TANC1 ankyrin repeats domain provide clues to understand mis-sense variants from diseases

TANC1 and its close relative TANC2 are two important synaptic scaffold proteins which play critical roles in regulating densities of synaptic spines and excitatory synapse strength. Recent studies indicated TANC1 and TANC2 are candidate genes of several neurodevelopmental disorders (NDD). So far, the biochemical properties of TANC1/2 proteins remain largely unknown. In this study, Ankyrin-repeats (AR) domain of TANC1 was expressed and purified using Escherichia coli. (E. coli.) cells, which showed low solubility and stability after removing the maltose binding protein (MBP) tag. Sequence analysis revealed that the TANC1 AR domain is lack of canonical N, C-capping units. By introducing two point mutations in the C-capping unit and replacing the N-capping unit, monomeric and well-folded TANC1 AR domain was purified and characterized by size exclusion chromatography coupled with multi-angle static light scattering (SEC-MALS) and circular dichroism spectroscopy (CD). In addition, mutations from intellectual disability (ID) patients and cancer patients were imported into the TANC1 AR domain. The ID mutant exhibited marginal effects in terms of conformation and protein folding stability changes. By contrast, the cancer mutants dramatically decreased protein solubility. Combined with structural prediction, we speculated that mis-sense variants tested in this study may either affect protein folding or disrupt the interaction between TANC1/2 AR domains and their binding partners.

ZMIZ1 Variants Cause a Syndromic Neurodevelopmental Disorder

ZMIZ1 is a coactivator of several transcription factors, including p53, the androgen receptor, and NOTCH1. Here, we report 19 subjects with intellectual disability and developmental delay carrying variants in ZMIZ1. The associated features include growth failure, feeding difficulties, microcephaly, facial dysmorphism, and various other congenital malformations. Of these 19, 14 unrelated subjects carried de novo heterozygous single-nucleotide variants (SNVs) or single-base insertions/deletions, 3 siblings harbored a heterozygous single-base insertion, and 2 subjects had a balanced translocation disrupting ZMIZ1 or involving a regulatory region of ZMIZ1. In total, we identified 13 point mutations that affect key protein regions, including a SUMO acceptor site, a central disordered alanine-rich motif, a proline-rich domain, and a transactivation domain. All identified variants were absent from all available exome and genome databases. In vitro, ZMIZ1 showed impaired coactivation of the androgen receptor. In vivo, overexpression of ZMIZ1 mutant alleles in developing mouse brains using in utero electroporation resulted in abnormal pyramidal neuron morphology, polarization, and positioning, underscoring the importance of ZMIZ1 in neural development and supporting mutations in ZMIZ1 as the cause of a rare neurodevelopmental syndrome.