Rare-variant analysis is commonly used in whole-exome or genome sequencing studies. Compared to common variants, rare variants tend to have larger effect sizes and often directly point out causal genes. These potential benefits make association analysis with rare variants a priority for human genetics researchers. To improve the power of such studies, numerous methods have been developed to aggregate information of all variants of a gene. However, these gene-based methods often make unrealistic assumptions, e.g., the commonly used burden test effectively assumes that all variants chosen in the analysis have the same effects. In practice, current methods are often underpowered. We propose a Bayesian method: mixture-model-based rare-variant analysis on genes (MIRAGE). MIRAGE analyzes summary statistics (i.e., variant counts from inherited variants in trio sequencing or from ancestry-matched case-control studies). MIRAGE captures the heterogeneity of variant effects by treating all variants of a gene as a mixture of risk and non-risk variants and uses external information of variants to model the prior probabilities of being risk variants. We demonstrate, in both simulations and analysis of an exome-sequencing dataset of autism, that MIRAGE significantly outperforms current methods for rare-variant analysis. The top genes identified by MIRAGE are highly enriched with known or plausible autism-risk genes.

Autism Spectrum Disorder (ASD) arises from complex genetic and environmental factors, with inherited genetic variation playing a substantial role. This study introduces a novel approach to uncover moderate effect size (MES) genes in ASD, which individually do not meet the ASD liability threshold but collectively contribute when paired with specific other MES genes. Analyzing 10,795 families from the SPARK dataset, we identified 97 MES genes forming 50 significant gene pairs, demonstrating a substantial association with ASD when considered in tandem, but not individually. Our method leverages familial inheritance patterns and statistical analyses, refined by comparisons against control cohorts, to elucidate these gene pairs' contribution to ASD liability. Furthermore, expression profile analyses of these genes in brain tissues underscore their relevance to ASD pathology. This study underscores the complexity of ASD's genetic landscape, suggesting that gene combinations, beyond high impact single-gene mutations, significantly contribute to the disorder's etiology and heterogeneity. Our findings pave the way for new avenues in understanding ASD's genetic underpinnings and developing targeted therapeutic strategies.

Neurodevelopmental disorders (NDDs) are among the most genetically complex human conditions, yet even in the era of routine exome sequencing (ES), a large fraction of patients remains without a molecular diagnosis. Here, we analyzed 203 unrelated families from NeuroWES‐Macedonia, the first national genomic initiative in North Macedonia, using a fully integrated diagnostic strategy that combined trio‐based ES, copy number variant (CNV) analysis, RNA studies, and DNA methylation (episignature) profiling. Rather than focusing solely on diagnostic yield, we systematically examined recurrent interpretative failure modes that lead to missed, delayed, or incomplete diagnoses in routine clinical genomics. Likely pathogenic or pathogenic variants were identified in 29.6% (60/203) of probands, with diagnostic yield rising to 62.3% (38/61) in syndromic NDDs. However, many of the most instructive cases lay beyond conventional Mendelian expectations. We uncovered cryptic splicing defects evade in silico prediction, low‐level parental and proband mosaicism, multilocus genomic disease, and inherited pathogenic variants concealed by subtle or unrecognized parental phenotypes. Epigenomic profiling proved particularly powerful in resolving cases involving chromosomal abnormalities, mosaic aneuploidies, and overlapping syndromes, allowing us to disentangle primary from secondary molecular drivers. Beyond improving diagnostic understanding, analysis of this cohort expanded the mutational and phenotypic spectra of known NDD genes and yielded novel candidate disease genes, several of which were independently validated through international data sharing. Importantly, multiple cases demonstrated how rigid inheritance assumptions, reliance on de novo filtering, and compartmentalized analysis of SNVs and CNVs can actively obscure true disease mechanisms—even when high‐quality sequencing data are available. Together, our findings show that the persistent diagnostic gap in NDDs is driven not only by missing genes but also by systematic blind spots in variant interpretation. Integrating multiomic data with phenotype‐driven, flexible analytic frameworks is essential to unlock the full potential of genomic medicine in NDDs.

Motivation Gene-damaging mutations are highly informative for studies seeking to discover genes underlying developmental disorders. Traditionally, these de novo variants are recognized by evaluating high-quality DNA sequence from affected offspring and parents. However, when parental sequence is unavailable, methods are required to infer de novo status and use this inference for association studies.Results We use data from autism spectrum disorder to illustrate and evaluate methods. Separating de novo from rare inherited variants is challenging because the latter are far more common. Using a classifier for unbalanced data and variants of known inheritance class, we build an inheritance model and then a de novo score for variants when parental data are missing. Next, we propose a new Random Draw (RD) model to use this score for gene discovery. Built into an existing inferential framework, RD produces a more powerful gene-based association test and controls the false discovery rate.Availability and implementation Codes are available at Github (https://github.com/HaeunM/TADA-RD) and Zenodo (DOI: https://doi.org/10.5281/zenodo.18531769).

Eating disorder (ED) and obsessive-compulsive disorder (OCD) exhibit clinical and genetic overlap, yet whether they converge at the molecular level in the human brain is unknown. We perform large-scale transcriptomic profiling of the dorsolateral prefrontal cortex (DLPFC) and caudate in postmortem tissue from 86 controls, 57 individuals with ED, and 27 with OCD. ED shows robust, region-specific transcriptional dysregulation (102 differentially expressed genes [DEGs] in DLPFC and 222 in caudate at FDR <1%) that replicates in an independent cohort. OCD shows no single-cohort DEGs, but meta-analysis across three datasets identifies 57 caudate-associated genes. Despite these differences, transcriptome-wide effects strongly correlate between ED and OCD (DLPFC r = 0.67; caudate r = 0.75), indicating shared molecular pathology. Joint ED + OCD analysis identifies 233 DEGs in DLPFC and 815 in caudate, implicating GABAergic signaling, neuroendocrine regulation, mitochondrial metabolism, and CHD8-associated networks. Genetically regulated expression analyses identifies five genes (WDR6, NCKIPSD, P4HTM, DALRD3, and SHISA5) with convergent risk associations across disorders and brain regions, all mapping to a gene-dense region on chromosome 3. These findings define a shared cortico-striatal transcriptional architecture and identify candidate genes for transdiagnostic intervention.

Objective:Obsessive-compulsive disorder (OCD) frequently co-occurs with bipolar disorder (BD) or schizophrenia (SCZ), and, importantly, can often precede their onset. However, the genetic architecture and directionality underlying these relationships remain unclear. We leveraged large-scale genome-wide association study (GWAS) data to examine shared genetic architecture and directional relationships among OCD, BD and SCZ, and used major depressive disorder (MDD) as a comparator. Methods:Using linkage disequilibrium score regression (LDSC), MiXeR, and Generalized Summary-data-based Mendelian Randomization (GSMR) as well as complementary Mendelian randomization approaches, we characterized genetic correlations, polygenic overlap (Dice coefficient), and effect direction concordance (ρβ) across disorders. Results:We observed substantial genetic correlations between OCD and BD (rg=0.37), BD type 2 (BD2) (rg=0.54), and SCZ (rg=0.39), with a large proportion of shared causal variants between OCD and both BD (Dice=0.85) and SCZ (Dice=0.84). MiXeR analyses indicated that OCD and BD2 share a smaller proportion of causal variants (Dice=0.57) but there is a high concordance of effect directions amongst these causal variants (ρβ=0.96), whereas OCD and MDD showed minimal overlap but strong concordance among shared variants (Dice=0.09, ρβ=1). Directional GSMR and complementary TwoSampleMR analyses supported a causal effect of genetic risk to OCD on liability to BD (b=0.20, p=1.5×10), SCZ (b=0.52, p=9.5×10 21), and MDD (b=0.24, p=1.06×10), with little evidence for reverse causal effects. Conclusions:Together, these findings indicate that genetic liability to OCD can represent an early component of transdiagnostic psychiatric risk, with implications for understanding and potentially predicting the emergence of broader psychopathology across the life course.

Phelan-McDermid syndrome (PMS) is a genetic neurodevelopmental disorder caused by a microdeletion within chromosome 22q13.3 1-6, and accounts for ~1-3% of cases of autism spectrum disorders (ASD). Individuals with PMS typically present with neonatal hypotonia, severe speech delay, intellectual disability, motor impairments, and autism-related features, although additional manifestations such as epilepsy, sleep disturbances, and developmental regression are common. As in ASD, there is considerable heterogeneity in cognitive and behavioral impairments in PMS, making it difficult to determine which features arise directly from SHANK3/Shank3 deficiency and how deficits manifest across development. In the present study, we transferred the targeted Shank3 mutation, previously characterized on the Sprague Dawley background, onto the Long-Evans strain and performed a longitudinal behavioral assessment of Shank3-deficient rats from infancy to adulthood. The rats were evaluated for delays in early sensory and motor development, and ultrasonic vocalizations as neonates, social behavior, short term memory and gait as juveniles, and cognitive-executive dysfunction using a touchscreen-based visual discrimination and reversal learning task as adults. Despite profound reductions and/or complete loss of Shank3 protein expression, heterozygous and homozygous male and female rats showed normal physical and neurological reflexes across development, yet female Shank3 knockout pups showed a selective reduction in distress-associated ultrasonic vocalizations. As juveniles, subtle abnormalities emerged in short-term memory and limb coordination, while social preference for novelty and recognition was normal. Prominent behavioral abnormalities were observed in adults characterized by rapid and error-prone responding to visual stimuli during discrimination learning and reversal. These data suggest that rats with complete or partial Shank3 deficiency produce a selective behavioral profile in which high-order cognitive dysfunction is more pronounced than deficits in basic sensorimotor or select social behaviors. More broadly, these findings highlight executive dysfunction as a key consequence of the loss of Shank3. For the first time, we report the loss of Shank3 expression on a Long-Evans background strain as a valuable translational tool for investigating cognitive dysfunction and therapeutic windows in Shank3-associated disorders.

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.

Psychiatric disorders are highly heritable and polygenic, influenced by environmental factors and often comorbid. Large-scale genome-wide association studies (GWASs) through consortium efforts have identified genetic risk loci and revealed the underlying biology of psychiatric disorders and traits. However, over 85% of psychiatric GWAS participants are of European ancestry, limiting the applicability of these findings to non-European populations. Latin America and the Caribbean, regions marked by diverse genetic admixture, distinct environments and healthcare disparities, remain critically understudied in psychiatric genomics. This threatens access to precision psychiatry, where diversity is crucial for innovation and equity. This Review evaluates the current state and advancements in psychiatric genomics within Latin America and the Caribbean, discusses the prevalence and burden of psychiatric disorders, explores contributions to psychiatric GWASs from these regions and highlights methods that account for genetic diversity. We also identify existing gaps and challenges and propose recommendations to promote equity in psychiatric genomics.

New insights into genetic etiological factors underlying autism and related neurodevelopmental and neuropsychiatric conditions have progressed rapidly, driven by accelerating data aggregation and analytic innovations. Large-scale sequencing of rare coding variation has enabled robust gene discovery and deeper insights into biological mechanisms underlying human development and cognition. Here, we report the largest-to-date analysis of rare variants in autism, encompassing 62,470 individuals diagnosed with autism, including 38,545 probands with parental data from complete families. By integrating de novo and inherited data across single-nucloetide and copy number variation in this cohort via the TADA Bayesian model, we identify 257 genes robustly associated with autism at a false discovery rate (FDR) < 0.001. Not only do these genes recapitulate strong enrichment in pathways such as those involved in chromatin remodeling, development, and synaptic communication/signaling, but many of them have also recently been shown to be significantly associated in studies across a range of neuropsychiatric disorders.We sought to contextualize these findings in the broader landscape of neuropsychiatric genetics by systematically aggregating our results gene and pathway level findings from large-scale studies of schizophrenia (SCHEMA; 24,248 cases, 97,322 controls), epilepsy (Epi25K; 20,979 cases, 33,444 controls), and bipolar disorder (BIPEX; 13,933 cases, 14,422 controls). Burden heritability regression reveals that autism harbors the greatest rare variant heritability (>3%), followed by schizophrenia and epilepsy (1–2%). We observe moderate genetic correlation between autism and each of schizophrenia, epilepsy, and bipolar disorder based on rare variants (∼0.2), while the highest rare variant genetic correlation is between schizophrenia and epilepsy (∼0.5), and in schizophrenia with bipolar disorder (∼0.4). Partitioning rare variant heritability reveals that 25% of rare variant heritability in autism resides in the 257 autism-associated genes, while the same genes account for ∼20% of rare variant heritability in epilepsy, but less than 10% in schizophrenia and bipolar disorder, suggesting both shared and distinct pathways of disruption. At a gene-set level, the autism associated genes are significantly more likely to also be associated with schizophrenia (Odds ratio [OR]=10.8, p=1.5e-14) and epilepsy (OR=11.6, p=1.1e-11), with weaker enrichment in bipolar disorder (OR=2.8, p=0.094). Finally, autism genes in chromatin, development, and synaptic signaling pathways are significantly enriched for genes associated with schizophrenia (OR=1.76, p=7.6e-2) and epilepsy (OR=2.22, p=3.2e-4).Our findings highlight a core set of highly penetrant genes with impact across autism and neuropsychiatric phenotypes, while also revealing disorder-specific genetic architecture differences. Additional efforts to integrate these gene-level discoveries with developmental expression patterns, cell-type specificity, and functional networks will further inform functional mechanisms for rare variant risk across diagnostic boundaries.

The Developmental Synaptopathies Consortium is a multisite natural history network studying rare, neurogenetic syndromes associated with synaptic dysfunction and developmental delays. One aim of the Consortium is clinical trial readiness, including identifying clinical concepts and validating their measurement. We evaluated the scope and limitations of conventional cognitive and behavioral measurement strategies in 2-21-year-olds with Phelan-McDermid syndrome (PMS; N = 98), Tuberous Sclerosis Complex (TSC; N = 98), and PTEN Hamartoma Tumor syndrome (PHTS; N = 69). On average, intellectual disability (ID) severity was severe-to-profound in PMS, mild-to-moderate for TSC, and borderline (or absent) in PHTS. Severity of ID invalidated the use of many assessments, including standardized autism diagnostic measures. These results will inform trial planning for these and other similarly medically complex neurodevelopmental conditions.

Tourette Syndrome (TS) and Persistent Tic Disorder (PTD) are childhood-onset neuropsychiatric conditions with high heritability. Due to current sample size limitations, identifying TS/PTD risk genes has been challenging. This study addressed this issue by conducting a meta-analysis of microarray copy number variant (CNV) studies from three TS/PTD genomics consortia, supplemented with new data from 3,291 cases. This approach more than doubled the sample size of previous TS/PTD CNV studies, with CNV calls generated from 5,725 TS/PTD cases and 10,982 matched controls. The results confirmed that TS/PTD cases 1) have a higher burden of ultra-rare deletions overlapping loss-of-function intolerant genes (OR = 1.68, P = 9.3×10^-5) and 2) are more likely to carry established neurodevelopmental CNVs (OR = 1.42, P = 3.9×10^-2) compared to controls. Additionally, a novel, genome-wide significant CNV locus for TS/PTD was discovered, involving duplications at 17q12 (hg19 chr17:34.8 - 36.2 Mb). This locus is associated with a known duplication syndrome associated with variable neuropsychiatric traits, but has not been previously linked to tic disorders. Eight cases and one control carried the canonical ~1.4 Mb duplication at chr17:34.8 - 36.2 Mb, while one additional case had a smaller 110 kb duplication within this known CNV that included only one gene, ACACA (acetyl-CoA carboxylase, OR = 26.7, P = 5.69×10^-7). Overall, this study provides further evidence that rare, genic CNVs play a substantial role in the genetic architecture of TS/PTD and identifies a new genome-wide significant association with this neurodevelopmental disorder.

The clinical spectrum of Phelan-McDermid syndrome (PMS) is varied, with wide-ranging degrees of intellectual disability, developmental delays, behavioral abnormalities, and medical features. Different types of genetic variation lead to PMS, and differing genotypes (e.g., size of deletion or type of variant) account for some of this variability, with strong associations between genotype and phenotype observed with degree of intellectual disability and presence of specific medical features such as renal abnormalities. To date, no studies have assessed how genotype is associated with the natural history of developmental or behavioral features in PMS over time. Here, we report on longitudinal data in developmental and behavioral domains from 154 individuals with PMS, comparing those with Class 1 (minimal) deletions, Class 2 deletions, and sequence variants, assessing both within-subject (individual change over time) and between-subject (across age) differences. Consistent with previous results, average scores per group differed in most adaptive and developmental domains, with individuals with Class 1 deletions performing best, followed by individuals with Class 2 deletions and sequence variants, who often performed similarly. However, in most domains of adaptive behavior, intellectual functioning, and behavioral features, genetic groups did not differ in their rate of change over time or in differences in scores across ages. Exceptions, notably in expressive language, existed. These results suggest that, although genotype may be related to overall degree of impairment, individuals with PMS, regardless of genotype, tend to have a similar rate of change over time and age in developmental and behavioral domains. A significant caveat is that sequencing is a relatively recent diagnostic approach, which will bias the results.

Evidence suggests that maternal health in pregnancy is associated with autism in the offspring. However, most diagnoses in pregnant women have not been examined, and the role of familial confounding remains unknown. Our cohort included all children born in Denmark between 1998 and 2015 (n = 1,131,899) and their parents. We fitted Cox proportional hazard regression models to estimate the likelihood of autism associated with each maternal prenatal ICD-10 diagnosis, accounting for disease chronicity and comorbidity, familial correlations and sociodemographic factors. We examined the evidence for familial confounding using discordant sibling and paternal negative control designs. Among the 1,131,899 individuals in our sample, 18,374 (1.6

Rare copy number variants (CNVs) are a key component of the genetic basis of psychiatric conditions, but have not been well characterized for most. We conducted a genome-wide CNV analysis across six diagnostic categories (N = 574,965): autism (ASD), ADHD, bipolar disorder (BD), major depressive disorder (MDD), PTSD, and schizophrenia (SCZ). We identified 35 genome-wide significant associations at 18 loci, including novel associations in SCZ ( SMYD3, USP7 - HAPSTR1 ) and in the combined cross-disorder analysis ( ASTN2 ). Rare CNVs accounted for 1-3% of heritability across diagnoses. In ASD, associations were uniformly positive, consistent with autism having diverse etiologies and clinical presentations. By contrast, CNVs showed a dose-dependent relationship for other diagnoses, including SCZ and PTSD, with reciprocal deletions and duplications having inversely correlated effects and distinct genotype-phenotype relationships. Our findings suggest that genes have effects that are both dose-dependent and pleiotropic, such that a positive influence on one dimension of psychopathology may be accompanied by positive or negative effects on others.

Phelan-McDermid syndrome (PMS) is a genetic condition caused by deletions of chromosome 22q13.3 or pathogenic variants in the SHANK3 gene. Neurologic features typically include intellectual disability, autism spectrum disorder, hypotonia, and absent speech, though there is considerable variability even among individuals with the same molecular cause. This prospective study aimed to explore the utility of genome sequencing to identify additional molecular diagnoses that may contribute to variability in a cohort of patients with PMS. Twenty probands diagnosed with PMS (60% with a 22q13 deletion, 40% with a SHANK3 variant) underwent trio or duo genome sequencing and chromosomal microarray. This analysis identified a second molecular finding associated with a neurological condition in 3/20 participants. Molecular diagnoses related to neurological phenotypes included: (1) spinal muscular atrophy, lower extremity-predominant, 2A, autosomal dominant (SMALED2A), (2) spastic paraplegia 7, and (3) 16p11.2 deletion syndrome. Five additional new molecular diagnoses were associated with a clinically actionable secondary or incidental finding. This exploratory study provides early evidence for the potential utility of expanded sequencing among individuals with PMS, even for those without phenotypic features outside of the expected range.

Loss-of-function mutations in the transcription factor POU3F2 have been identified in individuals with neurodevelopmental disorders. To elucidate the mechanistic role of POU3F2 in human neurodevelopment, we induced POU3F2 disruption in human neural progenitor cells (NPCs). Mutation of POU3F2 in NPCs causes reduced baseline canonical Wnt signalling and decreased proliferation, resulting in premature specification of radial glia. Additionally, POU3F2 levels across genetically diverse NPCs significantly associate positively with baseline canonical Wnt signalling and negatively with markers of radial glia specification. Through a series of unbiased analyses, we show that SRY-box transcription factor 13 (SOX13) and activity dependent neuroprotector homeobox (ADNP) are transcriptional targets of POU3F2 which mediate POU3F2's effects on Wnt signalling in human NPCs. Finally, we describe five individuals with autism spectrum disorder that harbour loss-of-function mutations in POU3F2, enhancing the genetic evidence for its critical role in human neurodevelopment. Together, these studies define POU3F2 as an activator of canonical Wnt signalling and mechanistically link two high-confidence autism genes, ADNP and POU3F2, in the regulation of neurodevelopment.

Background Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental disorders with high heritability and frequent co-occurrence. Our previous work on the initial iPSYCH exomes (Satterstrom et al., 2019) suggested a similar burden of rare protein-truncating variants (PTVs) across ASD and ADHD and identified MAP1A as a shared risk gene implicated by rare PTVs in both disorders. To build upon these findings, we aimed to 1) expand our gene discovery analysis using an updated dataset with nearly twice the sample size from the latest iPSYCH exomes, 2) quantify the burden heritability attributable to rare coding variants in ASD and ADHD, and 3) evaluate the burden genetic correlation between two disorders. Methods We analyzed exomes of 25,208 individuals from iPSYCH, comprising 7,119 diagnosed with ASD alone (ASD-only), 5,598 with ADHD alone (ADHD-only), 3,794 diagnosed with both conditions (ASD+ADHD), and 8,697 controls. Multivariate Poisson regression models were applied to systematically assess rare variant burdens in various gene sets across the three case groups, further stratifying by the presence or absence of intellectual disability (ID). We employed c-alpha tests to compare the distribution of rare deleterious variants between ASD-only and ADHD-only. We performed burden heritability regression analyses to estimate the burden heritability of ASD and ADHD, respectively, and to measure their burden genetic correlation. For gene discovery, we combined individuals diagnosed with ASD and/or ADHD into a single case group, included non-psychiatric non-Finnish European exome subset of gnomAD as external controls, and applied Fisher’s exact test to identify genes reaching exome-wide significance. Results Consistent with our previous findings, all three case groups demonstrated comparable elevated burdens of class I variants - including rare PTVs and highly deleterious missense variants (AlphaMissense ≥ 0.98 and MPC ≥ 2) in constrained genes compared to controls (ASD-only: OR = 1.49, 95% CI [1.40, 1.58]; ADHD-only: OR = 1.40, 95% CI [1.31, 1.50]; ASD+ADHD: OR = 1.46, 95% CI [1.35, 1.57]). C-alpha tests indicated no significant differences in the distribution of these variants between ASD-only and ADHD-only (P= 0.40), whereas significant differences were observed when comparing each group to controls. Burden heritability estimates of class I variants were 1.8% (s.e. = 0.4%) for ASD and 3.2% (s.e. = 0.7%) for ADHD on the liability scale. The burden genetic correlation between the two disorders was 0.46 (s.e. = 0.17), aligning closely with previously reported common-variant genetic correlation (0.42, s.e. = 0.05; Demontis et al., 2023). In gene discovery, we identified eight exome-wide significant genes associated with both disorders, including MAP1A (the first cross-disorder gene previously identified) and seven new risk genes: five previously implicated in ASD, developmental delay, and neurodevelopmental disorders; one strong candidate gene for ASD; and one novel gene not previously linked to either disorder. Discussion Our findings underscore a substantial shared genetic architecture involving rare coding variants between ASD and ADHD, reinforcing and expanding on earlier research. Moving forward, we aim to explore the distinct genetic risks specific to each disorder and to conduct sex-stratified analyses to uncover potential sex-specific genetic differences. The results will be presented at the conference.