Abstract Background NPTN encodes human neuroplastin (hNp), a transmembrane immunoglobulin (Ig)-superfamily glycoprotein and a subunit of the plasma membrane calcium (Ca2+)-ATPases (PMCA). The critical importance of hNp and its associations with PMCA in the human brain remains unknown. Methods Here, we describe de novo NPTN variants in individuals with autism and mild-to-severe DD/ID and evaluate their effects using animal models and in silico, molecular, and cellular approaches. Results Four individuals present variants affecting the two hNp isoforms, hNp55 and hNp65. Other four variants affect only the hNp65 isoform. Two individuals independently carry the same loss-of-function nonsense variant, predicted to cause haploinsufficient production of all hNp isoforms. Haploinsufficient Nptn +/– mice displayed reduced levels of Np and PMCA and exhibited altered social behavior. Insufficient Np55/65 production in neurons resulted in reduced PMCA expression and function. Two missense variants caused particular structural and thermodynamic abnormalities and lower expression of hNps in human embryonic kidney (HEK) cells. In primary neurons, these hNp variants failed to regulate cytosolic Ca2⁺ transients. In Drosophila, a missense mutation affecting the PMCA interaction failed to prevent the lethal phenotype caused by hNp ortholog elimination. Conclusions We show that a novel neurodevelopmental disorder characterized by intellectual disability and autism originates from haploinsufficient NPTN gene dosage or insufficient functionality of mutant hNp related to PMCA hypofunction.

ZNF536 encodes a C2H2 zinc-finger transcription factor that functions as a transcriptional repressor. While common noncoding variants at the ZNF536 locus have been reported to be associated with schizophrenia in a genome-wide association study (GWAS), the contribution of rare, protein-altering variants to human disease has not been systematically investigated. Through an international collaboration, we assembled a cohort of 21 affected individuals carrying 18 unique, rare, heterozygous, protein-altering ZNF536 variants. Most variants (15/18) were predicted loss-of-function (LoF) alleles, with the remainder being missense variants. Among families with available inheritance data (17/20), most variants arose de novo (12/17), while others were inherited from mosaic or mildly affected parents (5/17). Clinically, affected individuals presented with developmental delay along with high rates of autism spectrum disorder, intellectual disability, hyperactivity, aggressive behavior, anxiety, and hyperphagia; epilepsy and sleep disturbances were also frequently observed. To assess functional consequences of a proband-associated ZNF536 variant, we generated a Zfp536p.Gln169Ter knock-in mouse model. Homozygous mutants were non-viable, while heterozygotes survived but displayed autism-like behaviors, increased anxiety, and impaired recognition memory. Embryonic brain analysis revealed reduced cortical size, cortical thickness, and decreased deep-layer neuronal density. These features are consistent with phenotypes of a publicly available mouse knockout model and support our clinical cohort findings that rare monoallelic LoF variants in ZNF536 underlie a genetic neurodevelopmental disorder characterized by developmental delay, autism, and behavioral dysregulation. The pathogenicity of missense variants in disease remains to be determined. These results support a role for ZNF536 as a dosage-sensitive regulator of cortical development.

Objectives:We report on a patient with a distinct clinical and neuroradiologic phenotype and a de novo variant in the FTH1 gene. Methods:The patient was a 25-year-old woman with developmental delay and pontocerebellar hypoplasia, who after years of stable condition visited our hospital at age 20 years because of clinical deterioration. With consent from the patients' family, we obtained clinical, imaging, and genetic data from the patient's medical record. Results:Neurologic examination demonstrated a new hypertonia, ataxia, dystonia, dysarthria, and apathy. Cerebral MRI revealed new bilateral symmetrical signal abnormalities of the basal nuclei, thalamus, cerebral peduncles, and hippocampus, indicating iron accumulation. Exome sequencing revealed a de novo monoallelic variant in the FTH1 gene, c.510_511delTC. Discussion:Similar de novo FTH1 gene variants were reported in a case series of 5 patients with a similar, distinctive phenotype. Because this is a recently discovered cause of prenatal-onset cerebellar atrophy with later-onset neuroferritinopathy, our case adds to the literature to learn more about this distinct disease.

KBG syndrome (KBGS, OMIM #148050) is a rare genetic disorder caused by heterozygous truncating or missense variants in the ANKRD11 gene or a deletion of 16q24.3 involving ANKRD11. While truncating variants clearly disrupt protein function, the interpretation of missense variants is more challenging, as many remain variants of uncertain significance (VUS). To address this, we evaluated PhenoScore, an open-source AI-based phenomics framework integrating facial recognition and medical data analysis, for predicting the pathogenicity of ANKRD11 missense variants and providing supporting evidence for variant interpretation within the ACMG framework, specifically the PP4 criterion. PhenoScore was trained on 79 individuals with truncating variants in ANKRD11 and age-, sex-, and ethnicity-matched controls with other neurodevelopmental disorders, and its performance was compared to AlphaMissense, REVEL, and the evaluation of a clinical geneticist. Six individuals with functionally confirmed pathogenic missense variants were used for testing. PhenoScore achieved high predictive accuracy with an area under the curve (AUC) of 0.95 and a Brier score of 0.089, and pathogenic missense variants in the test set received a mean prediction score of 0.94. PhenoScore significantly outperformed REVEL (p < 0.01), especially in cases supported by functional and clinical evidence, while no significant difference was observed compared to AlphaMissense (p = 0.63); importantly, the two tools showed complementary strengths. These findings suggest that PhenoScore represents a promising tool for clinical variant interpretation, as it quantifies phenotypic concordance with KBGS and provides objective evidence that can strengthen the PP4 criterion within the ACMG framework. Combined with molecular prediction tools like AlphaMissense, PhenoScore may help reduce uncertainty surrounding VUS in ANKRD11 by complementing these scores.

RNA-binding proteins (RBPs) regulate gene expression, and a number of RBPs have been implicated in brain function and behavior. Here, we report 16 individuals with a neurodevelopmental disorder and de novo heterozygous variants in ELAVL2, encoding an RBP not previously linked to Mendelian disease. Thirteen individuals were identified through GeneMatcher. Their ELAVL2 variants include two structural, five nonsense, and six missense variants, supporting haploinsufficiency as the primary disease mechanism. The cohort presented with developmental delay, intellectual disability, autism spectrum disorder, seizures, sleep problems, sensory processing issues, emotional instability, and difficulty with socialization. Three additional variants (two missense and one terminal exon truncation), each previously reported in a different large cohort study, were also included for follow-up investigations. We provide multiple lines of evidence linking variants in ELAVL2 to the observed neurodevelopmental and behavioral phenotypes. First, we show that common genetic variants in ELAVL2 are significantly associated with intelligence, motor development, sleep-related traits, and sociability in the general population. Drosophila loss-of-function models provide further independent evidence for a conserved role in the regulation of seizure-like behavior, sensory processing, and sleep. Molecular studies confirm that some of the missense variants are deleterious, leading to decreased protein levels. Together, our integrative study combining Mendelian genetics, clinical and association studies, and animal and molecular modeling supports variants in ELAVL2 as a cause of a neurodevelopmental disorder, with haploinsufficiency as the disease mechanism, and identifies crucial roles of ELAVL2 in neuronal function, cognition, and behavior.

Diagnosing children with developmental disorders is often challenging due to the large number of rare syndromes and their variable clinical presentations. While next-generation sequencing has improved diagnostic yield, results are frequently inconclusive, highlighting the continued importance of detailed phenotypic assessment. Three-dimensional (3D) facial imaging has shown advantages over traditional two-dimensional (2D) photographs in syndrome identification, offering new opportunities for more accurate diagnosis. In this study, we explored the benefits of 3D shape analysis for three syndromes seen at the Radboudumc expertise clinic for neurodevelopmental disorders: Koolen-de Vries syndrome (KdVS, N = 16), Jansen-de Vries syndrome (JdVS, N = 9) and KBG syndrome (N = 16). Each patient's facial shape was aligned with a 3D growth curve derived from healthy controls, which allowed us to objectively evaluate how their features compared to their age- and sex-matched average. This analysis aligned with previously recognized features for all three syndromes and led to the identification of a novel phenotypical feature for JdVS, supraorbital grooves. The consistency of the facial features for each of these three syndromes was calculated using a cosine distance analysis and compared with that of 19 other dysmorphically well-characterized syndromes, for the overall face as well as for eight facial segments. In line with current understanding facial phenotypic consistency was highest for KdVS, whereas features of JdVS and KBG syndrome were more diverse in this cohort. These small cohort derived results indicate the potential of 3D imaging for neurodevelopmental disorders, enhance current phenotypical knowledge and provide a foundation for future 3D shape analysis of these three syndromes.

De novo variants are a leading cause of neurodevelopmental disorders (NDDs), but because every monogenic NDD is different and usually extremely rare, it remains a major challenge to understand the complete phenotype and genotype spectrum of any morbid gene. According to OMIM, heterozygous variants in KDM6B cause "neurodevelopmental disorder with coarse facies and mild distal skeletal abnormalities."Here, by examining the molecular and clinical spectrum of 85 reported individuals with mostly de novo (likely) pathogenic KDM6B variants, we demonstrate that this description is inaccurate and potentially misleading. Cognitive deficits are seen consistently in all individuals, but the overall phenotype is highly variable. Notably, coarse facies and distal skeletal anomalies, as defined by OMIM, are rare in this expanded cohort while other features are unexpectedly common (e.g., hypotonia, psychosis, etc.). Using 3D protein structure analysis and an innovative dual Drosophila gain-of-function assay, we demonstrated a disruptive effect of 11 missense/in-frame indels located in or near the enzymatic JmJC or Zn-containing domain of KDM6B. Consistent with the role of KDM6B in human cognition, we demonstrated a role for the Drosophila KDM6B ortholog in memory and behavior. Taken together, we accurately define the broad clinical spectrum of the KDM6B-related NDD, introduce an innovative functional testing paradigm for the assessment of KDM6B variants, and demonstrate a conserved role for KDM6B in cognition and behavior. Our study demonstrates the critical importance of international collaboration, sharing of clinical data, and rigorous functional analysis of genetic variants to ensure correct disease diagnosis for rare disorders.

BACKGROUND:Large language models (LLMs) are increasingly used medicine for diverse applications including differential diagnostic support. The training data used to create LLMs such as the Generative Pretrained Transformer (GPT) predominantly consist of English-language texts, but LLMs could be used across the globe to support diagnostics if language barriers could be overcome. Initial pilot studies on the utility of LLMs for differential diagnosis in languages other than English have shown promise, but a large-scale assessment on the relative performance of these models in a variety of European and non-European languages on a comprehensive corpus of challenging rare-disease cases is lacking. METHODS:We created 4917 clinical vignettes using structured data captured with Human Phenotype Ontology (HPO) terms with the Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema. These clinical vignettes span a total of 360 distinct genetic diseases with 2525 associated phenotypic features. We used translations of the Human Phenotype Ontology together with language-specific templates to generate prompts in English, Chinese, Czech, Dutch, French, German, Italian, Japanese, Spanish, and Turkish. We applied GPT-4o, version gpt-4o-2024-08-06, and the medically fine-tuned Meditron3-70B to the task of delivering a ranked differential diagnosis using a zero-shot prompt. An ontology-based approach with the Mondo disease ontology was used to map synonyms and to map disease subtypes to clinical diagnoses in order to automate evaluation of LLM responses. FINDINGS:For English, GPT-4o placed the correct diagnosis at the first rank 19.9% and within the top-3 ranks 27.0% of the time. In comparison, for the nine non-English languages tested here the correct diagnosis was placed at rank 1 between 16.9% and 20.6%, within top-3 between 25.4% and 28.6% of cases. The Meditron3 model placed the correct diagnosis within the first 3 ranks for 20.9% of cases in English and between 19.9% and 24.0% for the other nine languages. INTERPRETATION:The differential diagnostic performance of LLMs across a comprehensive corpus of rare-disease cases was largely consistent across the ten languages tested. This suggests that the utility of LLMs in clinical settings may extend to non-English clinical settings. FUNDING:NHGRI 5U24HG011449, 5RM1HG010860, R01HD103805 and R24OD011883. P.N.R. was supported by a Professorship of the Alexander von Humboldt Foundation; P.L. was supported by a National Grant (PMP21/00063 ONTOPREC-ISCIII, Fondos FEDER). C.M., J.R. and J.H.C. were supported in part by the Director, Office of Science, Office of Basic Energy Sciences, of the US Department of Energy (Contract No. DE-AC0205CH11231).

User preference learning is generally a hard problem. Individual preferences are typically unknown even to users themselves, while the space of choices is infinite. Here we study user preference learning from information-theoretic perspective. We model preference learning as a system with two interacting sub-systems, one representing a user with his/her preferences and another one representing an agent that has to learn these preferences. The user with his/her behavior is modeled by a parametric preference function. To efficiently learn the preferences and reduce search space quickly, we propose the agent that interacts with the user to collect the most informative data for learning. The agent presents two proposals to the user for evaluation, and the user rates them based on his/her preference function. We show that the optimum agent strategy for data collection and preference learning is a result of maximin optimization of the normalized weighted Kullback-Leibler (KL) divergence between true and agent-assigned predictive user response distributions. The resulting value of the KL-divergence, which we also call of a remaining system uncertainty (RSU), provides an efficient performance metric in the absence of the ground truth. This metric characterizes how well the agent can predict user and, thus, the quality of the underlying learned user (preference) model. Our proposed agent comprises sequential mechanisms for user model inference and proposal generation. To infer the user model (preference function), Bayesian approximate inference is used in the agent. The data collection strategy is to generate proposals, responses to which help resolving uncertainty associated with prediction of the user responses the most. The efficiency of our approach is validated by numerical simulations. Also a real-life example of preference learning application is provided.

Neurodevelopmental disorder with or without autism or seizures (NEDAUS) is a neurodevelopmental disorder characterized by global developmental delay, speech delay, seizures, autistic features, and/or behavior abnormalities. It is caused by CUL3 (Cullin-3 ubiquitin ligase) haploinsufficiency. We collected clinical and molecular data from 26 individuals carrying pathogenic variants and variants of uncertain significance (VUS) in the CUL3 gene, including 20 previously unreported cases. By comparing their DNA methylation (DNAm) classifiers with those of healthy controls and other neurodevelopmental disorders characterized by established episignatures, we aimed to create a diagnostic biomarker (episignature) and gain more knowledge of the molecular pathophysiology. We discovered a sensitive and specific DNAm episignature for patients with pathogenic variants in CUL3 and utilized it to reclassify patients carrying a VUS in the CUL3 gene. Comparative epigenomic analysis revealed similarities between NEDAUS and several other rare genetic neurodevelopmental disorders with previously identified episignatures, highlighting the broader implication of our findings. In addition, we performed genotype-phenotype correlation studies to explain the variety in clinical presentation between the cases. We discovered a highly accurate DNAm episignature serving as a robust diagnostic biomarker for NEDAUS. Furthermore, we broadened the phenotypic spectrum by identifying 20 new individuals and confirming five previously reported cases of NEDAUS.

Germline mutations of YY1 cause Gabriele-de Vries syndrome (GADEVS), a neurodevelopmental disorder featuring intellectual disability and a wide range of systemic manifestations. To dissect the cellular and molecular mechanisms underlying GADEVS, we combined large-scale imaging, single-cell multiomics and gene regulatory network reconstruction in 2D and 3D patient-derived physiopathologically relevant cell lineages. YY1 haploinsufficiency causes a pervasive alteration of cell type specific transcriptional networks, disrupting corticogenesis at the level of neural progenitors and terminally differentiated neurons, including cytoarchitectural defects reminiscent of GADEVS clinical features. Transcriptional alterations in neurons propagated to neighboring astrocytes through a major non-cell autonomous pro-inflammatory effect that grounds the rationale for modulatory interventions. Together, neurodevelopmental trajectories, synaptic formation and neuronal-astrocyte cross talk emerged as salient domains of YY1 dosage-dependent vulnerability. Mechanistically, cell-type resolved reconstruction of gene regulatory networks uncovered the regulatory interplay between YY1, NEUROG2 and ETV5 and its aberrant rewiring in GADEVS. Our findings underscore the reach of advanced in vitro models in capturing developmental antecedents of clinical features and exposing their underlying mechanisms to guide the search for targeted interventions.

DDX3X-related neurodevelopmental disorder is one of the most common monogenic causes of intellectual disability in females, with currently >1000 females diagnosed worldwide. In contrast, reports on affected males with DDX3X variants are scarce. The limited knowledge on this X-linked disorder in males hinders the interpretation of hemizygous DDX3X variants in clinical practice. In this study, we present a new cohort of 19 affected males (from 17 unrelated families) with (possibly) disease-causing DDX3X variants, for whom we collected clinical and molecular data. Additionally, we reviewed the existing literature on 13 males with DDX3X variants. The phenotype in males is diverse, including intellectual disability, speech/language delays, behavioural challenges and structural brain abnormalities. The vast majority of males have missense variants, including two recurrent variants (p.(Arg351Gln) and p.(Arg488Cys)). No truncating variants have been reported, consistent with the presumed embryonic lethality of complete loss-of-function of DDX3X in males. In our novel cohort, 6/17 variants are de novo in the affected male and 3/17 variants are de novo in the mother. This study provides significant insights in the genetic and phenotypic spectrum of males with DDX3X variants, by presenting the data of a combined cohort (n = 32) of novel and published individuals. Our data show that variants in DDX3X can cause an X-linked neurodevelopmental disorder in males, with unaffected or mildly affected carrier females. These findings will aid the interpretation of hemizygous missense variants in DDX3X and can guide clinical management and counselling, in particular with regard to recurrence risks in the respective families.

NPTN encodes human neuroplastin (hNp), a subunit of plasma membrane Ca 2+ -ATPases (PMCA). The critical importance of hNp and its associations with PMCA are unknown for the human brain. Here, we describe de novo NPTN variants in seven individuals with autism and mild-to-severe DD/ID and evaluate them using animal models and in silico , molecular and cellular approaches. We identified NPTN variants with dominant-negative (missense) or loss-of-function (nonsense/ frameshift) effect on hNp-PMCA expression and function. The missense variants caused structural and thermodynamic molecular abnormalities and lower expression of hNp in HEK cells. In neurons, hNp missense variants affected PMCA levels and cytosolic Ca²⁺ regulation. In Drosophila , a missense mutation with affected PMCA interaction failed to prevent a lethal phenotype caused by hNp ortholog elimination. In Nptn +/− mice, levels of Np and PMCA were reduced and insufficient for normal social behavior. Therefore, we show that de novo variants in NPTN cause a neurodevelopmental disorder with intellectual disability and autism, likely linked to PMCA dysfunction.

Different types of germline de novo SETBP1 variants cause clinically distinct and heterogeneous neurodevelopmental disorders: Schinzel-Giedion syndrome (SGS, via missense variants at a critical degron region) and SETBP1-haploinsufficiency disorder. However, due to the lack of systematic investigation of genotype-phenotype associations of different types of SETBP1 variants, and limited understanding of its roles in neurodevelopment, the extent of clinical heterogeneity and how this relates to underlying pathophysiological mechanisms remains elusive. This imposes challenges for diagnosis. Here, we present a comprehensive investigation of the largest cohort to date of individuals carrying SETBP1 missense variants outside the degron region (n = 18). We performed thorough clinical and speech phenotyping with functional follow-up using cellular assays and transcriptomics. Our findings suggest that such variants cause a clinically and functionally variable developmental syndrome, showing only partial overlaps with classical SGS and SETBP1-haploinsufficiency disorder. We provide evidence of loss-of-function pathophysiological mechanisms impairing ubiquitination, DNA-binding, transcription, and neuronal differentiation capacity and morphologies. In contrast to SGS and SETBP1 haploinsufficiency, these effects are independent of protein abundance. Overall, our study provides important novel insights into diagnosis, patient care, and aetiology of SETBP1-related disorders.

BACKGROUND:The Helsmoortel-Van der Aa syndrome is an autosomal-dominant neurodevelopment disorder caused by heterozygous de novo variants in the Activity-Dependent Neuroprotective Protein (ADNP) gene, characterized by autism, intellectual disability, dysmorphic facial features, and deficits in multiple organ systems. ADNP is a zinc finger DNA-binding protein that primarily interacts with chromatin remodelers regulating embryonic development, while also associating with components of the cytoskeleton, thereby regulating autophagy and microtubule dynamics during development. In this study, we investigated these nucleocytoskeletal alterations explaining neurodevelopmental delay in a child with Helsmoortel-Van der Aa syndrome who had an unaffected dizygotic twin brother. RESULTS:We performed a genome-wide methylation array on PBMCs from dizygotic twins, showing a predominant CpG hypomethylation episignature. Enrichment analysis of methylated genes revealed significant pathway changes in actin filament organization, Wnt signaling, embryonic development, heart development, and the immune system. In addition, transcriptome sequencing substantiated the affected pathways regulating nuclear and cytoskeletal filamentous alterations associated with autism and neurodevelopmental delay. Brain magnetic resonance imaging showed a mild generalized prominence of the subarachnoid space overlying both hemispheres, revealing intricate patterns of neurodevelopmental delay. CONCLUSIONS:We report the first molecular study performed on dizygotic twins of which one was diagnosed with Helsmoortel-Van der Aa syndrome, revealing Wnt signaling and filamentous cytoskeletal alterations as a potential drug targets for therapy. LIMITATIONS:Indications for neurodegeneration, following these cytoskeletal perturbations, have been observed in cellular and murine models for the Helsmoortel-Van der Aa syndrome. However, clinical evidence remains unclear due to the young age of patients, limiting long-term studies on the aging brain. Further longitudinal imaging studies combined with histopathological autopsy sections are required to study the impact of an ADNP variant in the brain as patients come to age.

Bayesian model reduction provides an efficient approach for comparing the performance of all nested sub-models of a model, without re-evaluating any of these sub-models. Until now, Bayesian model reduction has been applied mainly in the computational neuroscience community on simple models. In this paper, we formulate and apply Bayesian model reduction to perform principled pruning of Bayesian neural networks, based on variational free energy minimization. Direct application of Bayesian model reduction, however, gives rise to approximation errors. Therefore, a novel iterative pruning algorithm is presented to alleviate the problems arising with naive Bayesian model reduction, as supported experimentally on the publicly available UCI datasets for different inference algorithms. This novel parameter pruning scheme solves the shortcomings of current state-of-the-art pruning methods that are used by the signal processing community. The proposed approach has a clear stopping criterion and minimizes the same objective that is used during training. Next to these benefits, our experiments indicate better model performance in comparison to state-of-the-art pruning schemes.

Trithorax-related H3K4 methyltransferases, KMT2C and KMT2D, are critical epigenetic modifiers. Haploinsufficiency of KMT2C was only recently recognized as a cause of neurodevelopmental disorder (NDD), so the clinical and molecular spectrums of the KMT2C-related NDD (now designated as Kleefstra syndrome 2) are largely unknown. We ascertained 98 individuals with rare KMT2C variants, including 75 with protein-truncating variants (PTVs). Notably, ∼15% of KMT2C PTVs were inherited. Although the most highly expressed KMT2C transcript consists of only the last four exons, pathogenic PTVs were found in almost all the exons of this large gene. KMT2C variant interpretation can be challenging due to segmental duplications and clonal hematopoesis-induced artifacts. Using samples from 27 affected individuals, divided into discovery and validation cohorts, we generated a moderate strength disorder-specific KMT2C DNA methylation (DNAm) signature and demonstrate its utility in classifying non-truncating variants. Based on 81 individuals with pathogenic/likely pathogenic variants, we demonstrate that the KMT2C-related NDD is characterized by developmental delay, intellectual disability, behavioral and psychiatric problems, hypotonia, seizures, short stature, and other comorbidities. The facial module of PhenoScore, applied to photographs of 34 affected individuals, reveals that the KMT2C-related facial gestalt is significantly different from the general NDD population. Finally, using PhenoScore and DNAm signatures, we demonstrate that the KMT2C-related NDD is clinically and epigenetically distinct from Kleefstra and Kabuki syndromes. Overall, we define the clinical features, molecular spectrum, and DNAm signature of the KMT2C-related NDD and demonstrate they are distinct from Kleefstra and Kabuki syndromes highlighting the need to rename this condition.

Bayesian inference in nonconjugate models such as Bayesian Poisson regression often relies on computationally expensive Monte Carlo methods. This paper introduces Q-conjugacy, a generalization of classical conjugacy that enables efficient closed-form variational inference in certain nonconjugate models. Q-conjugacy is a condition in which a closed-form update scheme expresses the solution minimizing the Kullback-Leibler divergence between a variational distribution and the product of two potentially unnormalized distributions. Leveraging Q-conjugacy within a local message passing framework allows deriving analytic inference update equations for nonconjugate models. The effectiveness of this approach is demonstrated on Bayesian Poisson regression and a model involving a hidden gamma-distributed latent variable with Gaussian-corrupted logarithmic observations. Results show that Q-conjugate triplets, such as (Gamma, LogNormal, Gamma), provide better speed-accuracy trade-offs than Markov Chain Monte Carlo.

The prevalence of comorbidities in individuals with neurodevelopmental disorders (NDDs) is not well understood, yet these are important for accurate diagnosis and prognosis in routine care and for characterizing the clinical spectrum of NDD syndromes. We thus developed PhenomAD-NDD, an aggregated database containing the comorbid phenotypic data of 51,227 individuals with NDD, all harmonized into Human Phenotype Ontology (HPO), with in total 3,054 unique HPO terms. We demonstrate that almost all congenital anomalies are more prevalent in the NDD population than in the general population, and the NDD baseline prevalence allows for an approximation of the enrichment of symptoms. For example, such analyses of 33 genetic NDDs show that 32% of enriched phenotypes are currently not reported in the clinical synopsis in the Online Mendelian Inheritance in Man (OMIM). PhenomAD-NDD is open to all via a visualization online tool and allows us to determine the enrichment of symptoms in NDD. Data from pediatric populations with neurodevelopmental disorders, obtained through a combinatorial strategy of literature review scoping and in-patient appointments, were used to construct a Phenomics Aggregation Database (PhenomAD-NDD) that can aid clinical diagnosis of comorbidities.

PURPOSE:ARID1A/ARID1B haploinsufficiency leads to Coffin-Siris syndrome, duplications of ARID1A lead to a distinct clinical syndrome, whilst ARID1B duplications have not yet been linked to a phenotype. METHODS:We collected patients with duplications encompassing ARID1A and ARID1B duplications. RESULTS:16 ARID1A and 13 ARID1B duplication cases were included with duplication sizes ranging from 0.1 to 1.2 Mb (1-44 genes) for ARID1A and 0.9 to 10.3 Mb (2-101 genes) for ARID1B. Both groups shared features, with ARID1A patients having more severe intellectual disability, growth delay, and congenital anomalies. DNA methylation analysis showed that ARID1A patients had a specific methylation pattern in blood, which differed from controls and from patients with ARID1A or ARID1B loss-of-function variants. ARID1B patients appeared to have a distinct methylation pattern, similar to ARID1A duplication patients, but further research is needed to validate these results. Five cases with duplications including ARID1A or ARID1B initially annotated as duplications of uncertain significance were evaluated using PhenoScore and DNA methylation reanalysis, resulting in the reclassification of 2 ARID1A and 2 ARID1B duplications as pathogenic. CONCLUSION:Our findings reveal that ARID1B duplications manifest a clinical phenotype, and ARID1A duplications have a distinct episignature that overlaps with that of ARID1B duplications, providing further evidence for a distinct and emerging BAFopathy caused by whole-gene duplication rather than haploinsufficiency.