De novo Mutations From Whole Exome Sequencing in Neurodevelopmental and Psychiatric Disorders: From Discovery to Application

Meta-analysis of 46,000 germline de novo mutations linked to human inherited disease

BACKGROUND

De novo mutations (DNMs) are variants that occur anew in the offspring of noncarrier parents. They are not inherited from either parent but rather result from endogenous mutational processes involving errors of DNA repair/replication. These spontaneous errors play a significant role in the causation of genetic disorders, and their importance in the context of molecular diagnostic medicine has become steadily more apparent as more DNMs have been reported in the literature. In this study, we examined 46,489 disease-associated DNMs annotated by the Human Gene Mutation Database (HGMD) to ascertain their distribution across gene and disease categories.

RESULTS

Most disease-associated DNMs reported to date are found to be associated with developmental and psychiatric disorders, a reflection of the focus of sequencing efforts over the last decade. Of the 13,277 human genes in which DNMs have so far been found, the top-10 genes with the highest proportions of DNM relative to gene size were H3-3 A, DDX3X, CSNK2B, PURA, ZC4H2, STXBP1, SCN1A, SATB2, H3-3B and TUBA1A. The distribution of CADD and REVEL scores for both disease-associated DNMs and those mutations not reported to be de novo revealed a trend towards higher deleteriousness for DNMs, consistent with the likely lower selection pressure impacting them. This contrasts with the non-DNMs, which are presumed to have been subject to continuous negative selection over multiple generations.

CONCLUSION

This meta-analysis provides important information on the occurrence and distribution of disease-associated DNMs in association with heritable disease and should make a significant contribution to our understanding of this major type of mutation.

Proteome-Wide Assessment of Clustering of Missense Variants in Neurodevelopmental Disorders Versus Cancer

Missense de novo variants (DNVs) and missense somatic variants contribute to neurodevelopmental disorders (NDDs) and cancer, respectively. Proteins with statistical enrichment based on analyses of these variants exhibit convergence in the differing NDD and cancer phenotypes. Herein, the question of why some of the same proteins are identified in both phenotypes is examined through investigation of clustering of missense variation at the protein level. Our hypothesis is that missense variation is present in different protein locations in the two phenotypes leading to the distinct phenotypic outcomes. We tested this hypothesis in 1D protein space using our software CLUMP. Furthermore, we newly developed 3D-CLUMP that uses 3D protein structures to spatially test clustering of missense variation for proteome-wide significance. We examined missense DNVs in 39,883 parent-child sequenced trios with NDDs and missense somatic variants from 10,543 sequenced tumors covering five TCGA cancer types and two COSMIC pan-cancer aggregates of tissue types. There were 57 proteins with proteome-wide significant missense variation clustering in NDDs when compared to cancers and 79 proteins with proteome-wide significant missense clustering in cancers compared to NDDs. While our main objective was to identify differences in patterns of missense variation, we also identified a novel NDD protein BLTP2. Overall, our study is innovative, provides new insights into differential missense variation in NDDs and cancer at the protein-level, and contributes necessary information toward building a framework for thinking about prognostic and therapeutic aspects of these proteins.

Whole-exome sequencing reveals genetic variants that may play a role in neurocytomas

OBJECTIVES

Neurocytomas (NCs) are rare intracranial tumors that can often be surgically resected. However, disease course is unpredictable in many patients and medical therapies are lacking. We have used whole exome sequencing to explore the molecular etiology for neurocytoma and assist in target identification to develop novel therapeutic interventions.

METHODS

We used whole exome sequencing (WES) to compare the molecular landscape of 21 primary & recurrent NCs to five normal cerebellar control samples. WES data was analyzed using the Qiagen Clinical Insight program, variants of interest (VOI) were interrogated using ConSurf, ScoreCons, & Ingenuity Pathway Analysis Software to predict their potential functional effects, and Copy number variations (CNVs) in the genes of interest were analyzed by Genewiz (Azenta Life Sciences).

RESULTS

Of 40 VOI involving thirty-six genes, 7 were pathogenic, 17 likely-pathogenic, and 16 of uncertain-significance. Of seven pathogenic NC associated variants, Glucosylceramidase beta 1 [GBA1 c.703T > C (p.S235P)] was mutated in 5/21 (24%), Coagulation factor VIII [F8 c.3637dupA (p.I1213fs*28)] in 4/21 (19%), Phenylalanine hydroxylase [PAH c.975C > A (p.Y325*)] in 3/21 (14%), and Fanconi anemia complementation group C [FANCC c.1162G > T (p.G388*)], Chromodomain helicase DNA binding protein 7 [CHD7 c.2839C > T (p.R947*)], Myosin VIIA [MYO7A c.940G > T (p.E314*)] and Dynein axonemal heavy chain 11 [DNAH11 c.3544C > T (p.R1182*)] in 2/21 (9.5%) NCs respectively. CNVs were noted in 85% of these latter 7 genes. Interestingly, a Carboxy-terminal domain RNA polymerase II polypeptide A small phosphatase 2 [CTDSP2 c.472G > A (p.E158K)] of uncertain significance was also found in > 70% of NC cases.

INTERPRETATION

The variants of interest we identified in the NCs regulate a variety of neurological processes including cilia motility, cell metabolism, immune responses, and DNA damage repair and provide novel insights into the molecular pathogenesis of these extremely rare tumors.

DOCK3-Associated Neurodevelopmental Disorder-Clinical Features and Molecular Basis

The protein product of DOCK3 is highly expressed in neurons and has a role in cell adhesion and neuronal outgrowth through its interaction with the actin cytoskeleton and key cell signaling molecules. The DOCK3 protein is essential for normal cell growth and migration. Biallelic variants in DOCK3 associated with complete or partial loss of function of the gene were recently reported in six patients with intellectual disability and muscle hypotonia. Only one of the reported patients had congenital malformations outside of the CNS. Further studies are necessary to better determine the prevalence of DOCK3-associated neurodevelopmental disorders and the frequency of non-CNS clinical manifestations in these patients. Since deficiency of the DOCK3 protein product is now an established pathway of this neurodevelopmental condition, supplementing the deficient gene product using a gene therapy approach may be an efficient treatment strategy.

Indicators of HSV1 Infection, ECM-Receptor Interaction, and Chromatin Modulation in a Nuclear Family with Schizophrenia

Schizophrenia (SCZ) is a complex psychiatric disorder with high heritability; identifying risk genes is essential for deciphering the disorder's pathogenesis and developing novel treatments. Using whole-exome sequencing, we screened for mutations within protein-coding sequences in a single family of patients with SCZ. In a pathway enrichment analysis, we found multiple transmitted variant genes associated with two KEGG pathways: herpes simplex virus 1 (HSV1) infection and the extracellular matrix (ECM)-receptor interaction. When searching for rare variants, six variants, SLC6A19p.L541R, CYP2E1p.T376S, NAT10p.E811D, N4BP1p.L7V, CBX2p.S520C, and ZNF460p.K190E, segregated with SCZ. A bioinformatic analysis showed that three of these mutated genes were associated with chromatin modulation. We found that HSV1 infection, ECM-receptor interaction pathways, and epigenetic mechanisms may contribute to the pathogenesis of SCZ in certain families. The identified polygenetic risk factors from the sample family provide distinctive underlying biological mechanisms of the pathophysiology of SCZ and may be useful in clinical practice and patient care.

Inferring the Effects of Protein Variants on Protein-Protein Interactions with Interpretable Transformer Representations

Identifying pathogenetic variants and inferring their impact on protein-protein interactions sheds light on their functional consequences on diseases. Limited by the availability of experimental data on the consequences of protein interaction, most existing methods focus on building models to predict changes in protein binding affinity. Here, we introduced MIPPI, an end-to-end, interpretable transformer-based deep learning model that learns features directly from sequences by leveraging the interaction data from IMEx. MIPPI was specifically trained to determine the types of variant impact (increasing, decreasing, disrupting, and no effect) on protein-protein interactions. We demonstrate the accuracy of MIPPI and provide interpretation through the analysis of learned attention weights, which exhibit correlations with the amino acids interacting with the variant. Moreover, we showed the practicality of MIPPI in prioritizing de novo mutations associated with complex neurodevelopmental disorders and the potential to determine the pathogenic and driving mutations. Finally, we experimentally validated the functional impact of several variants identified in patients with such disorders. Overall, MIPPI emerges as a versatile, robust, and interpretable model, capable of effectively predicting mutation impacts on protein-protein interactions and facilitating the discovery of clinically actionable variants.

Proband only exome sequencing in 403 Indian children with neurodevelopmental disorders: Diagnostic yield, utility and challenges in a resource-limited setting

Whole exome sequencing is recommended as the first tier test for neurodevelopmental disorders (NDDs) with trio being an ideal option for the detection of de novo variants. Cost constraints have led to adoption of sequential testing i.e. proband-only whole exome followed by targeted testing of parents. The reported diagnostic yield for proband exome approach ranges between 31 and 53%. Typically, these study designs have aptly incorporated targeted parental segregation before concluding a genetic diagnosis to be confirmed. The reported estimates however do not accurately reflect the yield of proband only standalone whole -exome, a question commonly posed to the referring clinician in self pay medical systems like India. To assess the utility of standalone proband exome (without follow up targeted parental testing), we retrospectively evaluated 403 cases of neurodevelopmental disorders referred for proband-only whole exome sequencing at Neuberg Centre for Genomic Medicine (NCGM), Ahmedabad during the period of January 2019 and December 2021. A diagnosis was considered confirmed only upon the detection of Pathogenic/Likely Pathogenic variants in concordance with patient's phenotype as well as established inheritance pattern. Targeted parental/familial segregation analysis was recommended as a follow up test where applicable. The diagnostic yield of the proband-only standalone whole exome was 31.5%. Only 20 families submitted samples for follow up targeted testing, and a genetic diagnosis was confirmed in twelve cases increasing the yield to 34.5%. To understand factors leading to poor uptake of sequential parental testing, we focused on cases where an ultra-rare variant was detected in hitherto described de novo dominant neurodevelopmental disorder. A total of 40 novel variants in genes associated with de novo autosomal dominant disorders could not be reclassified as parental segregation was denied. Semi-structured telephonic interviews were conducted upon informed consent to comprehend reasons for denial. Major factors influencing decision making included lack of definitive cure in the detected disorders; especially when couples not planning further conception and financial constraints to fund further targeted testing. Our study thus depicts the utility and challenges of proband-only exome approach and highlights the need for larger studies to understand factors influencing decision making in sequential testing.

Whole genome sequencing analysis reveals post-zygotic mutation variability in monozygotic twins discordant for amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is a heterogeneous, fatal neurodegenerative disease, characterized by motor neuron loss and in 50% of cases also by cognitive and/or behavioral changes. Mendelian forms of ALS comprise approximately 10-15% of cases. The majority is however considered sporadic, but also with a high contribution of genetic risk factors. To explore the contribution of somatic mutations and/or epigenetic changes to disease risk, we performed whole genome sequencing and methylation analyses using samples from multiple tissues on a cohort of 26 monozygotic twins discordant for ALS, followed by in-depth validation and replication experiments. The results of these analyses implicate several mechanisms in ALS pathophysiology, which include a role for de novo mutations, defects in DNA damage repair and accelerated aging.

Prevalence and Penetrance of Rare Pathogenic Variants in Neurodevelopmental Psychiatric Genes in a Health Care System Population

OBJECTIVE

Autism, schizophrenia, and other clinically distinct neurodevelopmental psychiatric disorders (NPDs) have shared genetic etiologies, including single-gene and multigenic copy number variants (CNVs). Because rare variants are primarily investigated in clinical cohorts, population-based estimates of their prevalence and penetrance are lacking. The authors determined the prevalence, penetrance, and NPD risk of pathogenic single-gene variants in a large health care system population.

METHODS

The authors analyzed linked genomic and electronic health record (EHR) data in a subset of 90,595 participants from Geisinger's MyCode Community Health Initiative, known as the DiscovEHR cohort. Loss-of-function pathogenic variants in 94 high-confidence NPD genes were identified through exome sequencing, and NPD penetrance was calculated using preselected EHR diagnosis codes. NPD risk was estimated using a case-control comparison of DiscovEHR participants with and without NPD diagnoses. Results from single-gene variant analyses were also compared with those from 31 previously reported pathogenic NPD CNVs.

RESULTS

Pathogenic variants were identified in 0.34% of the DiscovEHR cohort and demonstrated a 34.3% penetrance for NPDs. Similar to CNVs, sequence variants collectively conferred a substantial risk for several NPD diagnoses, including autism, schizophrenia, and bipolar disorder. Significant NPD risk remained after participants with intellectual disability were excluded from the analysis, confirming the association with major psychiatric disorders in individuals without severe cognitive deficits.

CONCLUSIONS

Collectively, rare single-gene variants and CNVs were found in >1% of individuals in a large health care system population and play an important contributory role in mental health disorders. Diagnostic genetic testing for pathogenic variants among symptomatic individuals with NPDs could improve clinical outcomes through early intervention and anticipatory therapeutic support.

The Role of Genetics, Epigenetics, and the Environment in ASD: A Mini Review

According to recent findings, variances in autism spectrum disorder (ASD) risk factors might be determined by several factors, including molecular genetic variants. Accumulated evidence has also revealed the important role of biological and chemical pathways in ASD aetiology. In this paper, we assess several reviews with regard to their quality of evidence and provide a brief outline of the presumed mechanisms of the genetic, epigenetic, and environmental risk factors of ASD. We also review some of the critical literature, which supports the basis of each factor in the underlying and specific risk patterns of ASD. Finally, we consider some of the implications of recent research regarding potential molecular targets for future investigations.

Deep phenotyping and whole-exome sequencing improved the diagnostic yield for nuclear pedigrees with neurodevelopmental disorders

Background

Neurodevelopmental disorders, a group of early‐onset neurological disorders with significant clinical and genetic heterogeneity, remain a diagnostic challenge for clinical genetic evaluation. Therefore, we assessed the diagnostic yield by combining standard phenotypes and whole‐exome sequencing in families with these disorders that were “not yet diagnosed” by the traditional testing methods.

Methods

Using a standardized vocabulary of phenotypic abnormalities from human phenotype ontology (HPO), we performed deep phenotyping for 45 “not yet diagnosed” pedigrees to characterize multiple clinical features extracted from Chinese electronic medical records (EMRs). By matching HPO terms with known human diseases and phenotypes from model organisms, together with whole‐exome sequencing data, we prioritized candidate mutations/genes. We made probable genetic diagnoses for the families.

Results

We obtained a diagnostic yield of 29% (13 out of 45) with probably genetic diagnosis, of which compound heterozygosity and de novo mutations accounted for 77% (10/13) of the diagnosis. Of note, these pedigrees are accompanied by a more significant number of non‐neurological features.

Conclusions

Deep phenotyping and whole‐exome sequencing improve the etiological evaluation for neurodevelopmental disorders in the clinical setting.

Genome interpretation using in silico predictors of variant impact

Estimating the effects of variants found in disease driver genes opens the door to personalized therapeutic opportunities. Clinical associations and laboratory experiments can only characterize a tiny fraction of all the available variants, leaving the majority as variants of unknown significance (VUS). In silico methods bridge this gap by providing instant estimates on a large scale, most often based on the numerous genetic differences between species. Despite concerns that these methods may lack reliability in individual subjects, their numerous practical applications over cohorts suggest they are already helpful and have a role to play in genome interpretation when used at the proper scale and context. In this review, we aim to gain insights into the training and validation of these variant effect predicting methods and illustrate representative types of experimental and clinical applications. Objective performance assessments using various datasets that are not yet published indicate the strengths and limitations of each method. These show that cautious use of in silico variant impact predictors is essential for addressing genome interpretation challenges.

Current Status of Next-Generation Sequencing Approaches for Candidate Gene Discovery in Familial Parkinson´s Disease

Parkinson’s disease is a neurodegenerative disorder with a heterogeneous genetic etiology. The advent of next-generation sequencing (NGS) technologies has aided novel gene discovery in several complex diseases, including PD. This Perspective article aimed to explore the use of NGS approaches to identify novel loci in familial PD, and to consider their current relevance. A total of 17 studies, spanning various populations (including Asian, Middle Eastern and European ancestry), were identified. All the studies used whole-exome sequencing (WES), with only one study incorporating both WES and whole-genome sequencing. It is worth noting how additional genetic analyses (including linkage analysis, haplotyping and homozygosity mapping) were incorporated to enhance the efficacy of some studies. Also, the use of consanguineous families and the specific search for de novo mutations appeared to facilitate the finding of causal mutations. Across the studies, similarities and differences in downstream analysis methods and the types of bioinformatic tools used, were observed. Although these studies serve as a practical guide for novel gene discovery in familial PD, these approaches have not significantly resolved the “missing heritability” of PD. We speculate that what is needed is the use of third-generation sequencing technologies to identify complex genomic rearrangements and new sequence variation, missed with existing methods. Additionally, the study of ancestrally diverse populations (in particular those of Black African ancestry), with the concomitant optimization and tailoring of sequencing and analytic workflows to these populations, are critical. Only then, will this pave the way for exciting new discoveries in the field.

Identification of ultra-rare disruptive variants in voltage-gated calcium channel-encoding genes in Japanese samples of schizophrenia and autism spectrum disorder

Several large-scale whole-exome sequencing studies in patients with schizophrenia (SCZ) and autism spectrum disorder (ASD) have identified rare variants with modest or strong effect size as genetic risk factors. Dysregulation of cellular calcium homeostasis might be involved in SCZ/ASD pathogenesis, and genes encoding L-type voltage-gated calcium channel (VGCC) subunits Ca_v1.1 (CACNA1S), Ca_v1.2 (CACNA1C), Ca_v1.3 (CACNA1D), and T-type VGCC subunit Ca_v3.3 (CACNA1I) recently were identified as risk loci for psychiatric disorders. We performed a screening study, using the Ion Torrent Personal Genome Machine (PGM), of exon regions of these four candidate genes (CACNA1C, CACNA1D, CACNA1S, CACNA1I) in 370 Japanese patients with SCZ and 192 with ASD. Variant filtering was applied to identify biologically relevant mutations that were not registered in the dbSNP database or that have a minor allele frequency of less than 1% in East-Asian samples from databases; and are potentially disruptive, including nonsense, frameshift, canonical splicing site single nucleotide variants (SNVs), and non-synonymous SNVs predicted as damaging by five different in silico analyses. Each of these filtered mutations were confirmed by Sanger sequencing. If parental samples were available, segregation analysis was employed for measuring the inheritance pattern. Using our filter, we discovered one nonsense SNV (p.C1451* in CACNA1D), one de novo SNV (p.A36V in CACNA1C), one rare short deletion (p.E1675del in CACNA1D), and 14 NSstrict SNVs (non-synonymous SNV predicted as damaging by all of five in silico analyses). Neither p.A36V in CACNA1C nor p.C1451* in CACNA1D were found in 1871 SCZ cases, 380 ASD cases, or 1916 healthy controls in the independent sample set, suggesting that these SNVs might be ultra-rare SNVs in the Japanese population. The neuronal splicing isoform of Ca_v1.2 with the p.A36V mutation, discovered in the present study, showed reduced Ca²⁺-dependent inhibition, resulting in excessive Ca²⁺ entry through the mutant channel. These results suggested that this de novo SNV in CACNA1C might predispose to SCZ by affecting Ca²⁺ homeostasis. Thus, our analysis successfully identified several ultra-rare and potentially disruptive gene variants, lending partial support to the hypothesis that VGCC-encoding genes may contribute to the risk of SCZ/ASD.

Diagnostic yield of next-generation sequencing in 87 families with neurodevelopmental disorders

Background

Neurodevelopmental disorders (NDDs) are a group of heterogeneous conditions, which include mainly intellectual disability, developmental delay (DD) and autism spectrum disorder (ASD), among others. These diseases are highly heterogeneous and both genetic and environmental factors play an important role in many of them. The introduction of next generation sequencing (NGS) has lead to the detection of genetic variants in several genetic diseases. The main aim of this report is to discuss the impact and advantages of the implementation of NGS in the diagnosis of NDDs. Herein, we report diagnostic yields of applying whole exome sequencing in 87 families affected by NDDs and additional data of whole genome sequencing (WGS) from 12 of these families.

Results

The use of NGS technologies allowed identifying the causative gene alteration in approximately 36% (31/87) of the families. Among them, de novo mutation represented the most common cause of genetic alteration found in 48% (15/31) of the patients with diagnostic mutations. The majority of variants were located in known neurodevelopmental disorders genes. Nevertheless, some of the diagnoses were made after the use of GeneMatcher tools which allow the identification of additional patients carrying mutations in THOC2, SETD1B and CHD9 genes. Finally the use of WGS only allowed the identification of disease causing variants in 8% (1/12) of the patients in which previous WES failed to identify a genetic aetiology.

Conclusion

NGS is more powerful in identifying causative pathogenic variant than conventional algorithms based on chromosomal microarray as first-tier test. Our results reinforce the implementation of NGS as a first-test in genetic diagnosis of NDDs.

De novo mutations identified by whole-genome sequencing implicate chromatin modifications in obsessive-compulsive disorder

Obsessive-compulsive disorder (OCD) is a chronic anxiety disorder with a substantial genetic basis and a broadly undiscovered etiology. Recent studies of de novo mutation (DNM) exome-sequencing studies for OCD have reinforced the hypothesis that rare variation contributes to the risk. We performed, to our knowledge, the first whole-genome sequencing on 53 parent-offspring families with offspring affected with OCD to investigate all rare de novo variants and insertions/deletions. We observed higher mutation rates in promoter-anchored chromatin loops (empirical P = 0.0015) and regions with high frequencies of histone marks (empirical P = 0.0001). Mutations affecting coding regions were significantly enriched within coexpression modules of genes involved in chromatin modification during human brain development. Four genes—SETD5, KDM3B, ASXL3, and FBL—had strong aggregated evidence and functionally converged on transcription’s epigenetic regulation, suggesting an important OCD risk mechanism. Our data characterized different genome-wide DNMs and highlighted the contribution of chromatin modification in the etiology of OCD.

Prediction of genetic alteration of phospholipase C isozymes in brain disorders: Studies with deep learning

Genetic mutations leading to the development of various diseases, such as cancer, diabetes, and neurodegenerative disorders, can be attributed to multiple mechanisms and exposure to diverse environments. These disorders further increase gene mutation rates and affect the activity of translated proteins, both phenomena associated with cellular responses. Therefore, maintaining the integrity of genetic and epigenetic information is critical for disease suppression and prevention. With the advent of genome sequencing technologies, large-scale genomic data-based machine learning tools, including deep learning, have been used to predict and identify somatic inactivation or negative dominant expression of target genes in various diseases. Although deep learning studies have recently been highlighted for their ability to distinguish between the genetic information of diseases, conventional wisdom is also necessary to explain the correlation between genotype and phenotype. Herein, we summarize the current understanding of phosphoinositide-specific phospholipase C isozymes (PLCs) and an overview of their associations with genetic variation, as well as their emerging roles in several diseases. We also predicted and discussed new findings of cryptic PLC splice variants by deep learning and the clinical implications of the PLC genetic variations predicted using these tools.

Polycomb-dependent histone H2A ubiquitination links developmental disorders with cancer

Cell identity is tightly controlled by specific transcriptional programs which require post-translational modifications of histones. These histone modifications allow the establishment and maintenance of active and repressed chromatin domains. Histone H2A lysine 119 ubiquitination (H2AK119ub1) has an essential role in building repressive chromatin domains during development. It is regulated by the counteracting activities of the Polycomb repressive complex 1 (PRC1) and the Polycomb repressive-deubiquitinase (PR-DUB) complexes, two multi-subunit ensembles that write and erase this modification, respectively. We have catalogued the recurrent genetic alterations in subunits of the PRC1 and PR-DUB complexes in both neurodevelopmental disorders and cancer. These genetic lesions are often shared across disorders, and we highlight common mechanisms of H2AK119ub1 dysregulation and how they affect development in multiple disease contexts.

Identifying disease-causing mutations with privacy protection

Motivation

The use of genome data for diagnosis and treatment is becoming increasingly common. Researchers need access to as many genomes as possible to interpret the patient genome, to obtain some statistical patterns and to reveal disease–gene relationships. The sensitive information contained in the genome data and the high risk of re-identification increase the privacy and security concerns associated with sharing such data. In this article, we present an approach to identify disease-associated variants and genes while ensuring patient privacy. The proposed method uses secure multi-party computation to find disease-causing mutations under specific inheritance models without sacrificing the privacy of individuals. It discloses only variants or genes obtained as a result of the analysis. Thus, the vast majority of patient data can be kept private.

Results

Our prototype implementation performs analyses on thousands of genomic data in milliseconds, and the runtime scales logarithmically with the number of patients. We present the first inheritance model (recessive, dominant and compound heterozygous) based privacy-preserving analyses of genomic data to find disease-causing mutations. Furthermore, we re-implement the privacy-preserving methods (MAX, SETDIFF and INTERSECTION) proposed in a previous study. Our MAX, SETDIFF and INTERSECTION implementations are 2.5, 1122 and 341 times faster than the corresponding operations of the state-of-the-art protocol, respectively.

Availability and implementation

https://gitlab.com/DIFUTURE/privacy-preserving-genomic-diagnosis.

Supplementary information

Supplementary data are available at Bioinformatics online.

MutationTaster2021

Here we present an update to MutationTaster, our DNA variant effect prediction tool. The new version uses a different prediction model and attains higher accuracy than its predecessor, especially for rare benign variants. In addition, we have integrated many sources of data that only became available after the last release (such as gnomAD and ExAC pLI scores) and changed the splice site prediction model. To more easily assess the relevance of detected known disease mutations to the clinical phenotype of the patient, MutationTaster now provides information on the diseases they cause. Further changes represent a major overhaul of the interfaces to increase user-friendliness whilst many changes under the hood have been designed to accelerate the processing of uploaded VCF files. We also offer an API for the rapid automated query of smaller numbers of variants from within other software. MutationTaster2021 integrates our disease mutation search engine, MutationDistiller, to prioritise variants from VCF files using the patient's clinical phenotype. The novel version is available at https://www.genecascade.org/MutationTaster2021/. This website is free and open to all users and there is no login requirement.

[Genetic risk factors and their influence on neural development in autism spectrum disorders]

Genetic risk factors and their influence on neural development in autism spectrum disorders Abstract. Abstract. Autism spectrum disorders are etiologically based on genetic and specific gene x biologically relevant environmental risk factors. They are diagnosed based on behavioral characteristics, such as impaired social communication and stereotyped, repetitive behavior and sensory as well as special interests. The genetic background is heterogeneous, i. e., it comprises diverse genetic risk factors across the disorder and high interindividual differences of specific genetic risk factors. Nevertheless, risk factors converge regarding underlying biological mechanisms and shared pathways, which likely cause the autism-specific behavioral characteristics. The current selective literature review summarizes differential genetic risk factors and focuses particularly on mechanisms and pathways currently being discussed by international research. In conclusion, clinically relevant aspects and open translational research questions are presented.

The Role of Neurod Genes in Brain Development, Function, and Disease

Transcriptional regulation is essential for the correct functioning of cells during development and in postnatal life. The basic Helix-loop-Helix (bHLH) superfamily of transcription factors is well conserved throughout evolution and plays critical roles in tissue development and tissue maintenance. A subgroup of this family, called neural lineage bHLH factors, is critical in the development and function of the central nervous system. In this review, we will focus on the function of one subgroup of neural lineage bHLH factors, the Neurod family. The Neurod family has four members: Neurod1, Neurod2, Neurod4, and Neurod6. Available evidence shows that these four factors are key during the development of the cerebral cortex but also in other regions of the central nervous system, such as the cerebellum, the brainstem, and the spinal cord. We will also discuss recent reports that link the dysfunction of these transcription factors to neurological disorders in humans.

Clinical Utility of Whole Exome Sequencing and Targeted Panels for the Identification of Inborn Errors of Immunity in a Resource-Constrained Setting

Primary immunodeficiency disorders (PIDs) are inborn errors of immunity (IEI) that cause immune system impairment. To date, more than 400 single-gene IEI have been well defined. The advent of next generation sequencing (NGS) technologies has improved clinical diagnosis and allowed for discovery of novel genes and variants associated with IEI. Molecular diagnosis provides clear clinical benefits for patients by altering management, enabling access to certain treatments and facilitates genetic counselling. Here we report on an 8-year experience using two different NGS technologies, namely research-based WES and targeted gene panels, in patients with suspected IEI in the South African healthcare system. A total of 52 patients' had WES only, 26 had a targeted gene panel only, and 2 had both panel and WES. Overall, a molecular diagnosis was achieved in 30% (24/80) of patients. Clinical management was significantly altered in 67% of patients following molecular results. All 24 families with a molecular diagnosis received more accurate genetic counselling and family cascade testing. Results highlight the clinical value of expanded genetic testing in IEI and its relevance to understanding the genetic and clinical spectrum of the IEI-related disorders in Africa. Detection rates under 40% illustrate the complexity and heterogeneity of these disorders, especially in an African population, thus highlighting the need for expanded genomic testing and research to further elucidate this.

Novel de novo mutation substantiates ATP6V0C as a gene causing epilepsy with intellectual disability

BACKGROUND

In approximately half of patients with epilepsy and intellectual disability (ID), the cause is unidentified and could be a mutation in a new disease gene.

PATIENT DESCRIPTION

To determine the discovery of disease-causing mutation in a female patient with epilepsy and ID, we performed trio whole-exome sequencing, reverse transcription polymerase chain reaction (RT-PCR) followed by Sanger sequencing.

RESULTS

Trio whole-exome sequencing was performed and revealed a novel de novo heterozygous stop-loss c.467A > T (p.*156Leuext*35) mutation in the ATP6V0C gene. Using RNA from leukocytes, RT-PCR followed by Sanger sequencing showed the existence of the mutant RNA, and real-time PCR demonstrated that the patient's ATP6V0C RNA level was approximately half of that in her parents, suggesting haploinsufficiency as a pathomechanism.

CONCLUSION

These findings, along with previous reports of individuals with similar phenotypes and variants in the same gene, substantiate ATP6V0C as a gene causing epilepsy with ID.

Genomic, Clinical, and Behavioral Characterization of 15q11.2 BP1-BP2 Deletion (Burnside-Butler) Syndrome in Five Families

The 15q11.2 BP1-BP2 deletion (Burnside-Butler) syndrome is emerging as the most common cytogenetic finding in patients with neurodevelopmental or autism spectrum disorders (ASD) presenting for microarray genetic testing. Clinical findings in Burnside-Butler syndrome include developmental and motor delays, congenital abnormalities, learning and behavioral problems, and abnormal brain findings. To better define symptom presentation, we performed comprehensive cognitive and behavioral testing, collected medical and family histories, and conducted clinical genetic evaluations. The 15q11.2 BP1-BP2 region includes the TUBGCP5, CYFIP1, NIPA1, and NIPA2 genes. To determine if additional genomic variation outside of the 15q11.2 region influences expression of symptoms in Burnside-Butler syndrome, whole-exome sequencing was performed on the parents and affected children for the first time in five families with at least one parent and child with the 15q1l.2 BP1-BP2 deletion. In total, there were 453 genes with possibly damaging variants identified across all of the affected children. Of these, 99 genes had exclusively de novo variants and 107 had variants inherited exclusively from the parent without the deletion. There were three genes (APBB1, GOLGA2, and MEOX1) with de novo variants that encode proteins evidenced to interact with CYFIP1. In addition, one other gene of interest (FAT3) had variants inherited from the parent without the deletion and encoded a protein interacting with CYFIP1. The affected individuals commonly displayed a neurodevelopmental phenotype including ASD, speech delay, abnormal reflexes, and coordination issues along with craniofacial findings and orthopedic-related connective tissue problems. Of the 453 genes with variants, 35 were associated with ASD. On average, each affected child had variants in 6 distinct ASD-associated genes (x¯ = 6.33, sd = 3.01). In addition, 32 genes with variants were included on clinical testing panels from Clinical Laboratory Improvement Amendments (CLIA) approved and accredited commercial laboratories reflecting other observed phenotypes. Notably, the dataset analyzed in this study was small and reported results will require validation in larger samples as well as functional follow-up. Regardless, we anticipate that results from our study will inform future research into the genetic factors influencing diverse symptoms in patients with Burnside-Butler syndrome, an emerging disorder with a neurodevelopmental behavioral phenotype.

Dosage-sensitive functions in embryonic development drove the survival of genes on sex-specific chromosomes in snakes, birds, and mammals

Different ancestral autosomes independently evolved into sex chromosomes in snakes, birds, and mammals. In snakes and birds, females are ZW and males are ZZ; in mammals, females are XX and males are XY. Although X and Z Chromosomes retain nearly all ancestral genes, sex-specific W and Y Chromosomes suffered extensive genetic decay. In both birds and mammals, the genes that survived on sex-specific chromosomes are enriched for broadly expressed, dosage-sensitive regulators of gene expression, subject to strong purifying selection. To gain deeper insight into the processes that govern survival on sex-specific chromosomes, we carried out a meta-analysis of survival across 41 species-three snakes, 24 birds, and 14 mammals-doubling the number of ancestral genes under investigation and increasing our power to detect enrichments among survivors relative to nonsurvivors. Of 2564 ancestral genes, representing an eighth of the ancestral amniote genome, only 324 survive on present-day sex-specific chromosomes. Survivors are enriched for dosage-sensitive developmental processes, particularly development of neural crest-derived structures, such as the face. However, there was no enrichment for expression in sex-specific tissues, involvement in sex determination or gonadogenesis pathways, or conserved sex-biased expression. Broad expression and dosage sensitivity contributed independently to gene survival, suggesting that pleiotropy imposes additional constraints on the evolution of dosage compensation. We propose that maintaining the viability of the heterogametic sex drove gene survival on amniote sex-specific chromosomes, and that subtle modulation of the expression of survivor genes and their autosomal orthologs has disproportionately large effects on development and disease.

Overlapping Molecular Pathways Leading to Autism Spectrum Disorders, Fragile X Syndrome, and Targeted Treatments

Autism spectrum disorders (ASD) are subdivided into idiopathic (unknown) etiology and secondary, based on known etiology. There are hundreds of causes of ASD and most of them are genetic in origin or related to the interplay of genetic etiology and environmental toxicology. Approximately 30 to 50% of the etiologies can be identified when using a combination of available genetic testing. Many of these gene mutations are either core components of the Wnt signaling pathway or their modulators. The full mutation of the fragile X mental retardation 1 (FMR1) gene leads to fragile X syndrome (FXS), the most common cause of monogenic origin of ASD, accounting for ~ 2% of the cases. There is an overlap of molecular mechanisms in those with idiopathic ASD and those with FXS, an interaction between various signaling pathways is suggested during the development of the autistic brain. This review summarizes the cross talk between neurobiological pathways found in ASD and FXS. These signaling pathways are currently under evaluation to target specific treatments in search of the reversal of the molecular abnormalities found in both idiopathic ASD and FXS.

Cutting-edge genetics in obsessive-compulsive disorder

This article reviews recent advances in the genetics of obsessive-compulsive disorder (OCD). We cover work on the following: genome-wide association studies, whole-exome sequencing studies, copy number variation studies, gene expression, polygenic risk scores, gene–environment interaction, experimental animal systems, human cell models, imaging genetics, pharmacogenetics, and studies of endophenotypes. Findings from this work underscore the notion that the genetic architecture of OCD is highly complex and shared with other neuropsychiatric disorders. Also, the latest evidence points to the participation of gene networks involved in synaptic transmission, neurodevelopment, and the immune and inflammatory systems in this disorder. We conclude by highlighting that further study of the genetic architecture of OCD, a great part of which remains to be elucidated, could benefit the development of diagnostic and therapeutic approaches based on the biological basis of the disorder. Studies to date revealed that OCD is not a simple homogeneous entity, but rather that the underlying biological pathways are variable and heterogenous. We can expect that translation from bench to bedside, through continuous effort and collaborative work, will ultimately transform our understanding of what causes OCD and thus how best to treat it.

Brain Organoids as Model Systems for Genetic Neurodevelopmental Disorders

Neurodevelopmental disorders (NDDs) are a group of disorders in which the development of the central nervous system (CNS) is disturbed, resulting in different neurological and neuropsychiatric features, such as impaired motor function, learning, language or non-verbal communication. Frequent comorbidities include epilepsy and movement disorders. Advances in DNA sequencing technologies revealed identifiable genetic causes in an increasingly large proportion of NDDs, highlighting the need of experimental approaches to investigate the defective genes and the molecular pathways implicated in abnormal brain development. However, targeted approaches to investigate specific molecular defects and their implications in human brain dysfunction are prevented by limited access to patient-derived brain tissues. In this context, advances of both stem cell technologies and genome editing strategies during the last decade led to the generation of three-dimensional (3D) in vitro-models of cerebral organoids, holding the potential to recapitulate precise stages of human brain development with the aim of personalized diagnostic and therapeutic approaches. Recent progresses allowed to generate 3D-structures of both neuronal and non-neuronal cell types and develop either whole-brain or region-specific cerebral organoids in order to investigate in vitro key brain developmental processes, such as neuronal cell morphogenesis, migration and connectivity. In this review, we summarized emerging methodological approaches in the field of brain organoid technologies and their application to dissect disease mechanisms underlying an array of pediatric brain developmental disorders, with a particular focus on autism spectrum disorders (ASDs) and epileptic encephalopathies.

Schizophrenia in a genomic era: a review from the pathogenesis, genetic and environmental etiology to diagnosis and treatment insights

Schizophrenia is a common multigenic and debilitating neurological disorder characterized by chronic psychotic symptoms and psychosocial impairment. Complex interactions of genetics and environmental factors have been implicated in etiology of schizophrenia. There is no central pathophysiology mechanism, diagnostic neuropathology, or biological markers have been defined for schizophrenia. However, a number of different hypotheses including neurodevelopmental and neurochemical hypotheses have been proposed to explain the neuropathology of schizophrenia. This review provides an overview of pathogenesis, genetic and environmental etiologies to diagnosis and treatment insights in clinical management of schizophrenia in light of the recent discoveries of genetic loci associated with susceptibility to schizophrenia.

Gene4Denovo: an integrated database and analytic platform for de novo mutations in humans

De novo mutations (DNMs) significantly contribute to sporadic diseases, particularly in neuropsychiatric disorders. Whole-exome sequencing (WES) and whole-genome sequencing (WGS) provide effective methods for detecting DNMs and prioritizing candidate genes. However, it remains a challenge for scientists, clinicians, and biologists to conveniently access and analyse data regarding DNMs and candidate genes from scattered publications. To fill the unmet need, we integrated 580 799 DNMs, including 30 060 coding DNMs detected by WES/WGS from 23 951 individuals across 24 phenotypes and prioritized a list of candidate genes with different degrees of statistical evidence, including 346 genes with false discovery rates <0.05. We then developed a database called Gene4Denovo (http://www.genemed.tech/gene4denovo/), which allowed these genetic data to be conveniently catalogued, searched, browsed, and analysed. In addition, Gene4Denovo integrated data from >60 genomic sources to provide comprehensive variant-level and gene-level annotation and information regarding the DNMs and candidate genes. Furthermore, Gene4Denovo provides end-users with limited bioinformatics skills to analyse their own genetic data, perform comprehensive annotation, and prioritize candidate genes using custom parameters. In conclusion, Gene4Denovo conveniently allows for the accelerated interpretation of DNM pathogenicity and the clinical implication of DNMs in humans.

Insufficient Evidence for "Autism-Specific" Genes

Despite evidence that deleterious variants in the same genes are implicated across multiple neurodevelopmental and neuropsychiatric disorders, there has been considerable interest in identifying genes that, when mutated, confer risk that is largely specific for autism spectrum disorder (ASD). Here, we review the findings and limitations of recent efforts to identify relatively “autism-specific” genes, efforts which focus on rare variants of large effect size that are thought to account for the observed phenotypes. We present a divergent interpretation of published evidence; discuss practical and theoretical issues related to studying the relationships between rare, large-effect deleterious variants and neurodevelopmental phenotypes; and describe potential future directions of this research. We argue that there is currently insufficient evidence to establish meaningful ASD specificity of any genes based on large-effect rare-variant data.

Postzygotic Somatic Mutations in the Human Brain Expand the Threshold-Liability Model of Schizophrenia

The search for what causes schizophrenia has been onerous. This research has included extensive assessment of a variety of genetic and environmental factors using ever emerging high-resolution technologies and traditional understanding of the biology of the brain. These efforts have identified a large number of schizophrenia-associated genes, some of which are altered by mutational and epi-mutational mechanisms in a threshold liability model of schizophrenia development. The results, however, have limited predictability and the actual cause of the disease remains unknown. This current state asks for conceptualizing the problem differently in light of novel insights into the nature of mutations, the biology of the brain and the fine precision and resolution of emerging technologies. There is mounting evidence that mutations acquired during postzygotic development are more common than germline mutations. Also, the postzygotic somatic mutations including epimutations (PZMs), which often lead to somatic mosaicism, are relatively common in the mammalian brain in comparison to most other tissues and PZMs are more common in patients with neurodevelopmental mental disorders, including schizophrenia. Further, previously inaccessible, detection of PZMs is becoming feasible with the advent of novel technologies that include single-cell genomics and epigenomics and the use of exquisite experimental designs including use of monozygotic twins discordant for the disease. These developments allow us to propose a working hypothesis and expand the threshold liability model of schizophrenia that already encompasses familial genetic, epigenetic and environmental factors to include somatic de novo PZMs. Further, we offer a test for this expanded model using currently available genome sequences and methylome data on monozygotic twins discordant for schizophrenia (MZD) and their parents. The results of this analysis argue that PZMs play a significant role in the development of schizophrenia and explain extensive heterogeneity seen across patients. It also offers the potential to convincingly link PZMs to both nervous system health and disease, an area that has remained challenging to study and relatively under explored.

PsyMuKB: An Integrative De Novo Variant Knowledge Base for Developmental Disorders

De novo variants (DNVs) are one of the most significant contributors to severe early-onset genetic disorders such as autism spectrum disorder, intellectual disability, and other developmental and neuropsychiatric (DNP) disorders. Presently, a plethora of DNVs have been identified using next-generation sequencing, and many efforts have been made to understand their impact at the gene level. However, there has been little exploration of the effects at the isoform level. The brain contains a high level of alternative splicing and regulation, and exhibits a more divergent splicing program than other tissues. Therefore, it is crucial to explore variants at the transcriptional regulation level to better interpret the mechanisms underlying DNP disorders. To facilitate a better usage and improve the isoform-level interpretation of variants, we developed NeuroPsychiatric Mutation Knowledge Base (PsyMuKB). It contains a comprehensive, carefully curated list of DNVs with transcriptional and translational annotations to enable identification of isoform-specific mutations. PsyMuKB allows a flexible search of genes or variants and provides both table-based descriptions and associated visualizations, such as expression, transcript genomic structures, protein interactions, and the mutation sites mapped on the protein structures. It also provides an easy-to-use web interface, allowing users to rapidly visualize the locations and characteristics of mutations and the expression patterns of the impacted genes and isoforms. PsyMuKB thus constitutes a valuable resource for identifying tissue-specific DNVs for further functional studies of related disorders. PsyMuKB is freely accessible at http://psymukb.net.

Update on the Role of the Non-Canonical Wnt/Planar Cell Polarity Pathway in Neural Tube Defects

Neural tube defects (NTDs), including spina bifida and anencephaly, represent the most severe and common malformations of the central nervous system affecting 0.7–3 per 1000 live births. They result from the failure of neural tube closure during the first few weeks of pregnancy. They have a complex etiology that implicate a large number of genetic and environmental factors that remain largely undetermined. Extensive studies in vertebrate models have strongly implicated the non-canonical Wnt/planar cell polarity (PCP) signaling pathway in the pathogenesis of NTDs. The defects in this pathway lead to a defective convergent extension that is a major morphogenetic process essential for neural tube elongation and subsequent closure. A large number of genetic studies in human NTDs have demonstrated an important role of PCP signaling in their etiology. However, the relative contribution of this pathway to this complex etiology awaits a better picture of the complete genetic architecture of these defects. The emergence of new genome technologies and bioinformatics pipelines, complemented with the powerful tool of animal models for variant interpretation as well as significant collaborative efforts, will help to dissect the complex genetics of NTDs. The ultimate goal is to develop better preventive and counseling strategies for families affected by these devastating conditions.

Genetic Causes and Modifiers of Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is one of the most prevalent neurodevelopmental disorders, affecting an estimated 1 in 59 children. ASD is highly genetically heterogeneous and may be caused by both inheritable and de novo gene variations. In the past decade, hundreds of genes have been identified that contribute to the serious deficits in communication, social cognition, and behavior that patients often experience. However, these only account for 10-20% of ASD cases, and patients with similar pathogenic variants may be diagnosed on very different levels of the spectrum. In this review, we will describe the genetic landscape of ASD and discuss how genetic modifiers such as copy number variation, single nucleotide polymorphisms, and epigenetic alterations likely play a key role in modulating the phenotypic spectrum of ASD patients. We also consider how genetic modifiers can alter convergent signaling pathways and lead to impaired neural circuitry formation. Lastly, we review sex-linked modifiers and clinical implications. Further understanding of these mechanisms is crucial for both comprehending ASD and for developing novel therapies.

Genetic Associations between Voltage-Gated Calcium Channels and Psychiatric Disorders

Psychiatric disorders are mental, behavioral or emotional disorders. These conditions are prevalent, one in four adults suffer from any type of psychiatric disorders world-wide. It has always been observed that psychiatric disorders have a genetic component, however, new methods to sequence full genomes of large cohorts have identified with high precision genetic risk loci for these conditions. Psychiatric disorders include, but are not limited to, bipolar disorder, schizophrenia, autism spectrum disorder, anxiety disorders, major depressive disorder, and attention-deficit and hyperactivity disorder. Several risk loci for psychiatric disorders fall within genes that encode for voltage-gated calcium channels (CaVs). Calcium entering through CaVs is crucial for multiple neuronal processes. In this review, we will summarize recent findings that link CaVs and their auxiliary subunits to psychiatric disorders. First, we will provide a general overview of CaVs structure, classification, function, expression and pharmacology. Next, we will summarize tools to study risk loci associated with psychiatric disorders. We will examine functional studies of risk variations in CaV genes when available. Finally, we will review pharmacological evidence of the use of CaV modulators to treat psychiatric disorders. Our review will be of interest for those studying pathophysiological aspects of CaVs.