Brain functional connectivity mirrors genetic pleiotropy in psychiatric conditions.

Pleiotropy occurs when a genetic variant influences more than one trait. This is a key property of the genomic architecture of psychiatric disorders and has been observed for rare and common genomic variants. It is reasonable to hypothesize that the microscale genetic overlap (pleiotropy) across psychiatric conditions and cognitive traits may lead to similar overlaps at the macroscale brain level such as large-scale brain functional networks. We took advantage of brain connectivity, measured by resting-state functional MRI to measure the effects of pleiotropy on large-scale brain networks, a putative step from genes to behaviour. We processed nine resting-state functional MRI datasets including 32 726 individuals and computed connectome-wide profiles of seven neuropsychiatric copy-number-variants, five polygenic scores, neuroticism and fluid intelligence as well as four idiopathic psychiatric conditions. Nine out of 19 pairs of conditions and traits showed significant functional connectivity correlations (rFunctional connectivity), which could be explained by previously published levels of genomic (rGenetic) and transcriptomic (rTranscriptomic) correlations with moderate to high concordance: rGenetic-rFunctional connectivity = 0.71 [0.40-0.87] and rTranscriptomic-rFunctional connectivity = 0.83 [0.52; 0.94]. Extending this analysis to functional connectivity profiles associated with rare and common genetic risk showed that 30 out of 136 pairs of connectivity profiles were correlated above chance. These similarities between genetic risks and psychiatric disorders at the connectivity level were mainly driven by the overconnectivity of the thalamus and the somatomotor networks. Our findings suggest a substantial genetic component for shared connectivity profiles across conditions and traits, opening avenues to delineate general mechanisms-amenable to intervention-across psychiatric conditions and genetic risks.

Rare copy number variation in posttraumatic stress disorder.

Posttraumatic stress disorder (PTSD) is a heritable (h2 = 24-71%) psychiatric illness. Copy number variation (CNV) is a form of rare genetic variation that has been implicated in the etiology of psychiatric disorders, but no large-scale investigation of CNV in PTSD has been performed. We present an association study of CNV burden and PTSD symptoms in a sample of 114,383 participants (13,036 cases and 101,347 controls) of European ancestry. CNVs were called using two calling algorithms and intersected to a consensus set. Quality control was performed to remove strong outlier samples. CNVs were examined for association with PTSD within each cohort using linear or logistic regression analysis adjusted for population structure and CNV quality metrics, then inverse variance weighted meta-analyzed across cohorts. We examined the genome-wide total span of CNVs, enrichment of CNVs within specified gene-sets, and CNVs overlapping individual genes and implicated neurodevelopmental regions. The total distance covered by deletions crossing over known neurodevelopmental CNV regions was significant (beta = 0.029, SE = 0.005, P = 6.3 × 10-8). The genome-wide neurodevelopmental CNV burden identified explains 0.034% of the variation in PTSD symptoms. The 15q11.2 BP1-BP2 microdeletion region was significantly associated with PTSD (beta = 0.0206, SE = 0.0056, P = 0.0002). No individual significant genes interrupted by CNV were identified. 22 gene pathways related to the function of the nervous system and brain were significant in pathway analysis (FDR q < 0.05), but these associations were not significant once NDD regions were removed. A larger sample size, better detection methods, and annotated resources of CNV are needed to explore this relationship further.

Genome-wide analysis of gene dosage in 24,092 individuals estimates that 10,000 genes modulate cognitive ability.

Genomic copy number variants (CNVs) are routinely identified and reported back to patients with neuropsychiatric disorders, but their quantitative effects on essential traits such as cognitive ability are poorly documented. We have recently shown that the effect size of deletions on cognitive ability can be statistically predicted using measures of intolerance to haploinsufficiency. However, the effect sizes of duplications remain unknown. It is also unknown if the effect of multigenic CNVs are driven by a few genes intolerant to haploinsufficiency or distributed across tolerant genes as well. Here, we identified all CNVs > 50 kilobases in 24,092 individuals from unselected and autism cohorts with assessments of general intelligence. Statistical models used measures of intolerance to haploinsufficiency of genes included in CNVs to predict their effect size on intelligence. Intolerant genes decrease general intelligence by 0.8 and 2.6 points of intelligence quotient when duplicated or deleted, respectively. Effect sizes showed no heterogeneity across cohorts. Validation analyses demonstrated that models could predict CNV effect sizes with 78% accuracy. Data on the inheritance of 27,766 CNVs showed that deletions and duplications with the same effect size on intelligence occur de novo at the same frequency. We estimated that around 10,000 intolerant and tolerant genes negatively affect intelligence when deleted, and less than 2% have large effect sizes. Genes encompassed in CNVs were not enriched in any GOterms but gene regulation and brain expression were GOterms overrepresented in the intolerant subgroup. Such pervasive effects on cognition may be related to emergent properties of the genome not restricted to a limited number of biological pathways.

Genome-wide association study reveals new insights into the heritability and genetic correlates of developmental dyslexia.

Developmental dyslexia (DD) is a learning disorder affecting the ability to read, with a heritability of 40-60%. A notable part of this heritability remains unexplained, and large genetic studies are warranted to identify new susceptibility genes and clarify the genetic bases of dyslexia. We carried out a genome-wide association study (GWAS) on 2274 dyslexia cases and 6272 controls, testing associations at the single variant, gene, and pathway level, and estimating heritability using single-nucleotide polymorphism (SNP) data. We also calculated polygenic scores (PGSs) based on large-scale GWAS data for different neuropsychiatric disorders and cortical brain measures, educational attainment, and fluid intelligence, testing them for association with dyslexia status in our sample. We observed statistically significant (p < 2.8 × 10-6) enrichment of associations at the gene level, for LOC388780 (20p13; uncharacterized gene), and for VEPH1 (3q25), a gene implicated in brain development. We estimated an SNP-based heritability of 20-25% for DD, and observed significant associations of dyslexia risk with PGSs for attention deficit hyperactivity disorder (at pT = 0.05 in the training GWAS: OR = 1.23[1.16; 1.30] per standard deviation increase; p = 8 × 10-13), bipolar disorder (1.53[1.44; 1.63]; p = 1 × 10-43), schizophrenia (1.36[1.28; 1.45]; p = 4 × 10-22), psychiatric cross-disorder susceptibility (1.23[1.16; 1.30]; p = 3 × 10-12), cortical thickness of the transverse temporal gyrus (0.90[0.86; 0.96]; p = 5 × 10-4), educational attainment (0.86[0.82; 0.91]; p = 2 × 10-7), and intelligence (0.72[0.68; 0.76]; p = 9 × 10-29). This study suggests an important contribution of common genetic variants to dyslexia risk, and novel genomic overlaps with psychiatric conditions like bipolar disorder, schizophrenia, and cross-disorder susceptibility. Moreover, it revealed the presence of shared genetic foundations with a neural correlate previously implicated in dyslexia by neuroimaging evidence.

Estimating the effects of copy-number variants on intelligence using hierarchical Bayesian models.

It is challenging to estimate the phenotypic impact of the structural genome changes known as copy-number variations (CNVs), since there are many unique CNVs which are nonrecurrent, and most are too rare to be studied individually. In recent work, we found that CNV-aggregated genomic annotations, that is, specifically the intolerance to mutation as measured by the pLI score (probability of being loss-of-function intolerant), can be strong predictors of intellectual quotient (IQ) loss. However, this aggregation method only estimates the individual CNV effects indirectly. Here, we propose the use of hierarchical Bayesian models to directly estimate individual effects of rare CNVs on measures of intelligence. Annotation information on the impact of major mutations in genomic regions is extracted from genomic databases and used to define prior information for the approach we call HBIQ. We applied HBIQ to the analysis of CNV deletions and duplications from three datasets and identified several genomic regions containing CNVs demonstrating significant deleterious effects on IQ, some of which validate previously known associations. We also show that several CNVs were identified as deleterious by HBIQ even if they have a zero pLI score, and the converse is also true. Furthermore, we show that our new model yields higher out-of-sample concordance (78%) for predicting the consequences of carrying known recurrent CNVs compared with our previous approach.

Cannabinoids and psychotic symptoms: A potential role for a genetic variant in the P2X purinoceptor 7 (P2RX7) gene.

To investigate the biological mechanisms underlying the higher risk for psychosis in those that use cannabis, we conducted a genome-wide environment-interaction study (GWEIS). In a sample of individuals without a psychiatric disorder (N = 1262), we analyzed the interactions between regular cannabis use and genotype with psychotic-like experiences (PLE) as outcome. PLE were measured using the Community Assessment of Psychic Experiences (CAPE). The sample was enriched for those at the extremes of both cannabis use and PLE to increase power. A single nucleotide polymorphism in the P2RX7 gene (rs7958311) was associated with risk for a high level of psychotic experiences in regular cannabis users (p = 1.10 x10-7) and in those with high levels of lifetime cannabis use (p = 4.5 × 10-6). This interaction was replicated in individuals with high levels of lifetime cannabis use in the IMAGEN cohort (N = 1217, p = 0.020). Functional relevance of P2RX7 in cannabis users was suggested by in vitro experiments on activated monocytes. Exposure of these cells to tetrahydrocannabinol (THC) or cannabidiol (CBD) reduced the immunological response of the P2X7 receptor, which was dependent on the identified genetic variant. P2RX7 variants have been implicated in psychiatric disorders before and the P2X7 receptor is involved in pathways relevant to psychosis, such as neurotransmission, synaptic plasticity and immune regulation. We conclude that P2RX7 plays a role in vulnerability to develop psychotic symptoms when using cannabis and point to a new pathway that can potentially be targeted by newly developed P2X7 antagonists.

Anatomy and Cell Biology of Autism Spectrum Disorder: Lessons from Human Genetics.

Until recently autism spectrum disorder (ASD) was regarded as a neurodevelopmental condition with unknown causes and pathogenesis. In the footsteps of the revolution of genome technologies and genetics, and with its high degree of heritability, ASD became the first neuropsychiatric disorder for which clues towards molecular and cellular pathogenesis were uncovered by genetic identification of susceptibility genes. Currently several hundreds of risk genes have been assigned, with a recurrence below 1% in the ASD population. The multitude and diversity of known ASD genes has extended the clinical notion that ASD comprises very heterogeneous conditions ranging from severe intellectual disabilities to mild high-functioning forms. The results of genetics have allowed to pinpoint a limited number of cellular and molecular processes likely involved in ASD including protein synthesis, signal transduction, transcription/chromatin remodelling and synaptic function all playing an essential role in the regulation of synaptic homeostasis during brain development. In this context, we highlight the role of protein synthesis as a key process in ASD pathogenesis as it might be central in synaptic deregulation and a potential target for intervention. These current insights should lead to a rational design of interventions in molecular and cellular pathways of ASD pathogenesis that may be applied to affected individuals in the future.

Meta-analysis of SHANK Mutations in Autism Spectrum Disorders: a gradient of severity in cognitive impairments.

SHANK genes code for scaffold proteins located at the post-synaptic density of glutamatergic synapses. In neurons, SHANK2 and SHANK3 have a positive effect on the induction and maturation of dendritic spines, whereas SHANK1 induces the enlargement of spine heads. Mutations in SHANK genes have been associated with autism spectrum disorders (ASD), but their prevalence and clinical relevance remain to be determined. Here, we performed a new screen and a meta-analysis of SHANK copy-number and coding-sequence variants in ASD. Copy-number variants were analyzed in 5,657 patients and 19,163 controls, coding-sequence variants were ascertained in 760 to 2,147 patients and 492 to 1,090 controls (depending on the gene), and, individuals carrying de novo or truncating SHANK mutations underwent an extensive clinical investigation. Copy-number variants and truncating mutations in SHANK genes were present in ∼1% of patients with ASD: mutations in SHANK1 were rare (0.04%) and present in males with normal IQ and autism; mutations in SHANK2 were present in 0.17% of patients with ASD and mild intellectual disability; mutations in SHANK3 were present in 0.69% of patients with ASD and up to 2.12% of the cases with moderate to profound intellectual disability. In summary, mutations of the SHANK genes were detected in the whole spectrum of autism with a gradient of severity in cognitive impairment. Given the rare frequency of SHANK1 and SHANK2 deleterious mutations, the clinical relevance of these genes remains to be ascertained. In contrast, the frequency and the penetrance of SHANK3 mutations in individuals with ASD and intellectual disability-more than 1 in 50-warrant its consideration for mutation screening in clinical practice.

The genetic landscapes of autism spectrum disorders.

The autism spectrum disorders (ASD) are characterized by impairments in social interaction and stereotyped behaviors. For the majority of individuals with ASD, the causes of the disorder remain unknown; however, in up to 25% of cases, a genetic cause can be identified. Chromosomal rearrangements as well as rare and de novo copy-number variants are present in ∼10-20% of individuals with ASD, compared with 1-2% in the general population and/or unaffected siblings. Rare and de novo coding-sequence mutations affecting neuronal genes have also been identified in ∼5-10% of individuals with ASD. Common variants such as single-nucleotide polymorphisms seem to contribute to ASD susceptibility, but, taken individually, their effects appear to be small. Despite a heterogeneous genetic landscape, the genes implicated thus far-which are involved in chromatin remodeling, metabolism, mRNA translation, and synaptic function-seem to converge in common pathways affecting neuronal and synaptic homeostasis. Animal models developed to study these genes should lead to a better understanding of the diversity of the genetic landscapes of ASD.

SHANK1 Deletions in Males with Autism Spectrum Disorder.

Recent studies have highlighted the involvement of rare (<1% frequency) copy-number variations and point mutations in the genetic etiology of autism spectrum disorder (ASD); these variants particularly affect genes involved in the neuronal synaptic complex. The SHANK gene family consists of three members (SHANK1, SHANK2, and SHANK3), which encode scaffolding proteins required for the proper formation and function of neuronal synapses. Although SHANK2 and SHANK3 mutations have been implicated in ASD and intellectual disability, the involvement of SHANK1 is unknown. Here, we assess microarray data from 1,158 Canadian and 456 European individuals with ASD to discover microdeletions at the SHANK1 locus on chromosome 19. We identify a hemizygous SHANK1 deletion that segregates in a four-generation family in which male carriers--but not female carriers--have ASD with higher functioning. A de novo SHANK1 deletion was also detected in an unrelated male individual with ASD with higher functioning, and no equivalent SHANK1 mutations were found in >15,000 controls (p = 0.009). The discovery of apparent reduced penetrance of ASD in females bearing inherited autosomal SHANK1 deletions provides a possible contributory model for the male gender bias in autism. The data are also informative for clinical-genetics interpretations of both inherited and sporadic forms of ASD involving SHANK1.

11q24.2-25 micro-rearrangements in autism spectrum disorders: Relation to brain structures.

Jacobsen syndrome (JS) is characterized by intellectual disability and higher risk for autism spectrum disorders (ASD). All patients with JS are carriers of contiguous de novo deletions of 11q24.2-25, but the causative genes remain unknown. Within the critical interval, we hypothesized that haploinsufficiency of the neuronal cell adhesion molecule Neurotrimin (NTM) might increase the risk for ASD and could affect brain structure volumes. We searched for deleterious mutations affecting NTM in 1256 ASD patients and 1287 controls, using SNP arrays, and by direct sequencing of 250 ASD patients and 180 controls. We compared our results to those obtained from independent cohorts of ASD patients and controls. We identified two patients with Copy Number Variants (CNV) encompassing NTM, one with a large de novo deletion, and a clinical phenotype of JS (including macrocephaly), and a second with a paternally inherited duplication, not consistent with JS. Interestingly, no similar CNVs were observed in controls. We did not observe enrichment for deleterious NTM mutations in our cohort. We then explored if the macrocephaly in the patient with JS was associated with a homogeneous increase of brain structures volumes using automatic segmentation. Compared to subjects without NTM micro-rearrangements (n=188), the patient had an increased volume of the sub-cortical structures but a decrease of the occipital gray matter. Finally our explorations could not incriminate NTM as a susceptibility gene for ASD, but provides new information on the impact of the 11q24.2-25 deletion on brain anatomy.

Genetic and functional analyses of SHANK2 mutations suggest a multiple hit model of autism spectrum disorders.

Autism spectrum disorders (ASD) are a heterogeneous group of neurodevelopmental disorders with a complex inheritance pattern. While many rare variants in synaptic proteins have been identified in patients with ASD, little is known about their effects at the synapse and their interactions with other genetic variations. Here, following the discovery of two de novo SHANK2 deletions by the Autism Genome Project, we identified a novel 421 kb de novo SHANK2 deletion in a patient with autism. We then sequenced SHANK2 in 455 patients with ASD and 431 controls and integrated these results with those reported by Berkel et al. 2010 (n = 396 patients and n = 659 controls). We observed a significant enrichment of variants affecting conserved amino acids in 29 of 851 (3.4%) patients and in 16 of 1,090 (1.5%) controls (P = 0.004, OR = 2.37, 95% CI = 1.23-4.70). In neuronal cell cultures, the variants identified in patients were associated with a reduced synaptic density at dendrites compared to the variants only detected in controls (P = 0.0013). Interestingly, the three patients with de novo SHANK2 deletions also carried inherited CNVs at 15q11-q13 previously associated with neuropsychiatric disorders. In two cases, the nicotinic receptor CHRNA7 was duplicated and in one case the synaptic translation repressor CYFIP1 was deleted. These results strengthen the role of synaptic gene dysfunction in ASD but also highlight the presence of putative modifier genes, which is in keeping with the "multiple hit model" for ASD. A better knowledge of these genetic interactions will be necessary to understand the complex inheritance pattern of ASD.

Common variants in genes of the postsynaptic FMRP signalling pathway are risk factors for autism spectrum disorders.

Autism spectrum disorders (ASD) are heterogeneous disorders with a high heritability and complex genetic architecture. Due to the central role of the fragile X mental retardation gene 1 protein (FMRP) pathway in ASD we investigated common functional variants of ASD risk genes regulating FMRP. We genotyped ten SNPs in two German patient sets (N = 192 and N = 254 families, respectively) and report association for rs7170637 (CYFIP1; set 1 and combined sets), rs6923492 (GRM1; combined sets), and rs25925 (CAMK4; combined sets). An additional risk score based on variants with an odds ratio (OR) >1.25 in set 1 and weighted by their respective log transmitted/untransmitted ratio revealed a significant effect (OR 1.30, 95 % CI 1.11-1.53; P = 0.0013) in the combined German sample. A subsequent meta-analysis including the two German samples, the "Strict/European" ASD subsample of the Autism Genome Project (1,466 families) and a French case/control (541/366) cohort showed again association of rs7170637-A (OR 0.85, 95 % CI 0.75-0.96; P = 0.007) and rs25925-G (OR 1.31, 95 % CI 1.04-1.64; P = 0.021) with ASD. Functional analyses revealed that these minor alleles predicted to alter splicing factor binding sites significantly increase levels of an alternative mRNA isoform of the respective gene while keeping the overall expression of the gene constant. These findings underpin the role of ASD candidate genes in postsynaptic FMRP regulation suggesting that an imbalance of specific isoforms of CYFIP1, an FMRP interaction partner, and CAMK4, a transcriptional regulator of the FMRP gene, modulates ASD risk. Both gene products are related to neuronal regulation of synaptic plasticity, a pathomechanism underlying ASD and may thus present future targets for pharmacological therapies in ASD.

Copy-number variants differ in frequency across genetic ancestry groups.

Copy-number variants (CNVs) have been implicated in a variety of neuropsychiatric and cognitive phenotypes. We found that deleterious CNVs are less prevalent in non-European ancestry groups than they are in European ancestry groups of both the UK Biobank (UKBB) and a US replication cohort (SPARK). We also identified specific recurrent CNVs that consistently differ in frequency across ancestry groups in both the UKBB and SPARK. These ancestry-related differences in CNV prevalence present in both an unselected community population and a family cohort enriched with individuals diagnosed with autism spectrum disorder (ASD) strongly suggest that genetic ancestry should be considered when probing associations between CNVs and health outcomes.

Clinical correlates of diagnostic certainty in children and youths with Autistic Disorder.

BACKGROUND: Clinicians diagnosing autism rely on diagnostic criteria and instruments in combination with an implicit knowledge based on clinical expertise of the specific signs and presentations associated with the condition. This implicit knowledge influences how diagnostic criteria are interpreted, but it cannot be directly observed. Instead, insight into clinicians' understanding of autism can be gained by investigating their diagnostic certainty. Modest correlations between the certainty of an autism diagnosis and symptom load have been previously reported. Here, we investigated the associations of diagnostic certainty with specific items of the ADOS as well as other clinical features including head circumference. METHODS: Phenotypic data from the Simons Simplex Collection was used to investigate clinical correlates of diagnostic certainty in individuals diagnosed with Autistic Disorder (n = 1511, age 4 to 18 years). Participants were stratified by the ADOS module used to evaluate them. We investigated how diagnostic certainty was associated with total ADOS scores, age, and ADOS module. We calculated the odds-ratios of being diagnosed with the highest possible certainty given the presence or absence of different signs during the ADOS evaluation. Associations between diagnostic certainty and other cognitive and clinical variables were also assessed. RESULTS: In each ADOS module, some items showed a larger association with diagnostic certainty than others. Head circumference was significantly higher for individuals with the highest certainty rating across all three ADOS modules. In turn, head circumference was positively correlated with some of the ADOS items that were associated with diagnostic certainty, and was negatively correlated with verbal/nonverbal IQ ratio among those assessed with ADOS module 2. LIMITATIONS: The investigated cohort was heterogeneous, e.g. in terms of age, IQ, language level, and total ADOS score, which could impede the identification of associations that only exist in a subgroup of the population. The variability of the certainty ratings in the sample was low, limiting the power to identify potential associations with other variables. Additionally, the scoring of diagnostic certainty may vary between clinicians. CONCLUSION: Some ADOS items may better capture the signs that are most associated with clinicians' implicit knowledge of Autistic Disorder. If replicated in future studies, new diagnostic instruments with differentiated weighting of signs may be needed to better reflect this, possibly resulting in better specificity in standardized assessments.

Genetic and phenotypic similarity across major psychiatric disorders: a systematic review and quantitative assessment.

There is widespread overlap across major psychiatric disorders, and this is the case at different levels of observations, from genetic variants to brain structures and function and to symptoms. However, it remains unknown to what extent these commonalities at different levels of observation map onto each other. Here, we systematically review and compare the degree of similarity between psychiatric disorders at all available levels of observation. We searched PubMed and EMBASE between January 1, 2009 and September 8, 2022. We included original studies comparing at least four of the following five diagnostic groups: Schizophrenia, Bipolar Disorder, Major Depressive Disorder, Autism Spectrum Disorder, and Attention Deficit Hyperactivity Disorder, with measures of similarities between all disorder pairs. Data extraction and synthesis were performed by two independent researchers, following the PRISMA guidelines. As main outcome measure, we assessed the Pearson correlation measuring the degree of similarity across disorders pairs between studies and biological levels of observation. We identified 2975 studies, of which 28 were eligible for analysis, featuring similarity measures based on single-nucleotide polymorphisms, gene-based analyses, gene expression, structural and functional connectivity neuroimaging measures. The majority of correlations (88.6%) across disorders between studies, within and between levels of observation, were positive. To identify a consensus ranking of similarities between disorders, we performed a principal component analysis. Its first dimension explained 51.4% (95% CI: 43.2, 65.4) of the variance in disorder similarities across studies and levels of observation. Based on levels of genetic correlation, we estimated the probability of another psychiatric diagnosis in first-degree relatives and showed that they were systematically lower than those observed in population studies. Our findings highlight that genetic and brain factors may underlie a large proportion, but not all of the diagnostic overlaps observed in the clinic.

High-effect gene-coding variants impact cognition, mental well-being, and neighborhood safety substrates in brain morphology.

Our genetic makeup, together with environmental and social influences, shape our brain's development. Yet, the imaging genetics field has struggled to integrate all these modalities to investigate the interplay between genetic blueprint, environment, human health, daily living skills and outcomes. Hence, we interrogated the Adolescent Brain Cognitive Development (ABCD) cohort to outline the effects of rare high-effect genetic variants on brain architecture and corresponding implications on cognitive, behavioral, psychosocial, and socioeconomic traits. Specifically, we designed a holistic pattern-learning algorithm that quantitatively dissects the impacts of copy number variations (CNVs) on brain structure and 962 behavioral variables spanning 20 categories in 7,657 adolescents. Our results reveal associations between genetic alterations, higher-order brain networks, and specific parameters of the family well-being (increased parental and child stress, anxiety and depression) or neighborhood dynamics (decreased safety); effects extending beyond the impairment of cognitive ability or language capacity, dominantly reported in the CNV literature. Our investigation thus spotlights a far-reaching interplay between genetic variation and subjective life quality in adolescents and their families.

Integrating genomic variants and developmental milestones to predict cognitive and adaptive outcomes in autistic children.

Although the first signs of autism are often observed as early as 18-36 months of age, there is a broad uncertainty regarding future development, and clinicians lack predictive tools to identify those who will later be diagnosed with co-occurring intellectual disability (ID). Here, we developed predictive models of ID in autistic children (n=5,633 from three cohorts), integrating different classes of genetic variants alongside developmental milestones. The integrated model yielded an AUC ROC=0.65, with this predictive performance cross-validated and generalised across cohorts. Positive predictive values reached up to 55%, accurately identifying 10% of ID cases. The ability to stratify the probabilities of ID using genetic variants was up to twofold greater in individuals with delayed milestones compared to those with typical development. These findings underscore the potential of models in neurodevelopmental medicine that integrate genomics and clinical observations to predict outcomes and target interventions.

Copy-number variants and polygenic risk for intelligence confer risk for autism spectrum disorder irrespective of their effects on cognitive ability.

Introduction: Rare copy number variants (CNVs) and polygenic risk for intelligence (PRS-IQ) both confer susceptibility for autism spectrum disorder (ASD) but have opposing effects on cognitive ability. The field has struggled to disentangle the effects of these two classes of genomic variants on cognitive ability from their effects on ASD susceptibility, in part because previous studies did not include controls with cognitive measures. We aim to investigate the impact of these genomic variants on ASD risk while adjusting for their known effects on cognitive ability. Methods: In a cohort of 8,426 subjects with ASD and 169,804 controls with cognitive assessments, we found that rare coding CNVs and PRS-IQ increased ASD risk, even after adjusting for their effects on cognitive ability. Results: Bottom decile PRS-IQ and CNVs both decreased cognitive ability but had opposing effects on ASD risk. Models combining both classes of variants showed that the effects of rare CNVs and PRS-IQ on ASD risk and cognitive ability were largely additive, further suggesting that susceptibility for ASD is conferred independently from its effects on cognitive ability. Despite imparting mostly additive effects on ASD risk, rare CNVs and PRS-IQ showed opposing effects on core and associated features and developmental history among subjects with ASD. Discussion: Our findings suggest that cognitive ability itself may not be the factor driving the underlying liability for ASD conferred by these two classes of genomic variants. In other words, ASD risk and cognitive ability may be two distinct manifestations of CNVs and PRS-IQ. This study also highlights the challenge of understanding how genetic risk for ASD maps onto its dimensional traits.

Using rare genetic mutations to revisit structural brain asymmetry.

Asymmetry between the left and right hemisphere is a key feature of brain organization. Hemispheric functional specialization underlies some of the most advanced human-defining cognitive operations, such as articulated language, perspective taking, or rapid detection of facial cues. Yet, genetic investigations into brain asymmetry have mostly relied on common variants, which typically exert small effects on brain-related phenotypes. Here, we leverage rare genomic deletions and duplications to study how genetic alterations reverberate in human brain and behavior. We designed a pattern-learning approach to dissect the impact of eight high-effect-size copy number variations (CNVs) on brain asymmetry in a multi-site cohort of 552 CNV carriers and 290 non-carriers. Isolated multivariate brain asymmetry patterns spotlighted regions typically thought to subserve lateralized functions, including language, hearing, as well as visual, face and word recognition. Planum temporale asymmetry emerged as especially susceptible to deletions and duplications of specific gene sets. Targeted analysis of common variants through genome-wide association study (GWAS) consolidated partly diverging genetic influences on the right versus left planum temporale structure. In conclusion, our gene-brain-behavior data fusion highlights the consequences of genetically controlled brain lateralization on uniquely human cognitive capacities.