Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders

Phenotypic and ancestry-related assortative mating in autism

BACKGROUND

Positive assortative mating (AM) in several neuropsychiatric traits, including autism, has been noted. However, it is unknown whether the pattern of AM is different in phenotypically defined autism subgroups [e.g., autism with and without intellectually disability (ID)]. It is also unclear what proportion of the phenotypic AM can be explained by the genetic similarity between parents of children with an autism diagnosis, and the consequences of AM on the genetic structure of the population.

METHODS

To address these questions, we analyzed two family-based autism collections: the Simons Foundation Powering Autism Research for Knowledge (SPARK) (1575 families) and the Simons Simplex Collection (SSC) (2283 families).

RESULTS

We found a similar degree of phenotypic and ancestry-related AM in parents of children with an autism diagnosis regardless of the presence of ID. We did not find evidence of AM for autism based on autism polygenic scores (PGS) (at a threshold of |r|> 0.1). The adjustment of ancestry-related AM or autism PGS accounted for only 0.3-4% of the fractional change in the estimate of the phenotypic AM. The ancestry-related AM introduced higher long-range linkage disequilibrium (LD) between single nucleotide polymorphisms (SNPs) on different chromosomes that are highly ancestry-informative compared to SNPs that are less ancestry-informative (D2 on the order of 1 × 10-5).

LIMITATIONS

We only analyzed participants of European ancestry, limiting the generalizability of our results to individuals of non-European ancestry. SPARK and SSC were both multicenter studies. Therefore, there could be ancestry-related AM in SPARK and SSC due to geographic stratification. The study participants from each site were unknown, so we were unable to evaluate for geographic stratification.

CONCLUSIONS

This study showed similar patterns of AM in autism with and without ID, and demonstrated that the common genetic influences of autism are likely relevant to both autism groups. The adjustment of ancestry-related AM and autism PGS accounted for < 5% of the fractional change in the estimate of the phenotypic AM. Future studies are needed to evaluate if the small increase of long-range LD induced by ancestry-related AM has impact on the downstream analysis.

Genetic and phenotypic heterogeneity in early neurodevelopmental traits in the Norwegian Mother, Father and Child Cohort Study

BACKGROUND

Autism and different neurodevelopmental conditions frequently co-occur, as do their symptoms at sub-diagnostic threshold levels. Overlapping traits and shared genetic liability are potential explanations.

METHODS

In the population-based Norwegian Mother, Father, and Child Cohort study (MoBa), we leverage item-level data to explore the phenotypic factor structure and genetic architecture underlying neurodevelopmental traits at age 3 years (N = 41,708-58,630) using maternal reports on 76 items assessing children's motor and language development, social functioning, communication, attention, activity regulation, and flexibility of behaviors and interests.

RESULTS

We identified 11 latent factors at the phenotypic level. These factors showed associations with diagnoses of autism and other neurodevelopmental conditions. Most shared genetic liabilities with autism, ADHD, and/or schizophrenia. Item-level GWAS revealed trait-specific genetic correlations with autism (items rg range = - 0.27-0.78), ADHD (items rg range = - 0.40-1), and schizophrenia (items rg range = - 0.24-0.34). We find little evidence of common genetic liability across all neurodevelopmental traits but more so for several genetic factors across more specific areas of neurodevelopment, particularly social and communication traits. Some of these factors, such as one capturing prosocial behavior, overlap with factors found in the phenotypic analyses. Other areas, such as motor development, seemed to have more heterogenous etiology, with specific traits showing a less consistent pattern of genetic correlations with each other.

CONCLUSIONS

These exploratory findings emphasize the etiological complexity of neurodevelopmental traits at this early age. In particular, diverse associations with neurodevelopmental conditions and genetic heterogeneity could inform follow-up work to identify shared and differentiating factors in the early manifestations of neurodevelopmental traits and their relation to autism and other neurodevelopmental conditions. This in turn could have implications for clinical screening tools and programs.

Functional neurogenomics in autism spectrum disorders: A decade of progress

Advances in autism spectrum disorder (ASD) genetics have identified many genetic causes, reflecting remarkable progress while at the same time identifying challenges such as heterogeneity and pleiotropy, which complicate attempts to connect genetic risk to mechanisms. High-throughput functional genomic approaches have yielded progress by defining a molecular pathology in the brain of individuals with ASD and in identifying convergent biological pathways through which risk genes are predicted to act. These studies indicate that ASD genetic risk converges in early brain development, primarily during the period of cortical neurogenesis. Over development, genetic perturbations in turn lead to broad neuronal signaling dysregulation, most prominent in glutamatergic cortical-cortical projecting neurons and somatostatin positive interneurons, which is accompanied by glial dyshomeostasis throughout the cerebral cortex. Connecting these developmental perturbations to disrupted neuronal and glial function in the postnatal brain is an important direction in current research. Coupling functional genomic approaches with advances in induced pluripotent stem cell-derived neural organoid development provides a promising avenue for connecting brain pathology to developmental mechanisms.

The Importance of Large-Scale Genomic Studies to Unravel Genetic Risk Factors for Autism

Autism spectrum disorder (ASD) is a common and highly heritable neurodevelopmental disorder. During the last 15 years, advances in genomic technologies and the availability of increasingly large patient cohorts have greatly expanded our knowledge of the genetic architecture of ASD and its neurobiological mechanisms. Over two hundred risk regions and genes carrying rare de novo and transmitted high-impact variants have been identified. Additionally, common variants with small individual effect size are also important, and a number of loci are now being uncovered. At the same time, these new insights have highlighted ongoing challenges. In this perspective article, we summarize developments in ASD genetic research and address the enormous impact of large-scale genomic initiatives on ASD gene discovery.

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.

Polygenic scores for autism are associated with neurite density in adults and children from the general population

Genetic variants linked to autism are thought to change cognition and behaviour by altering the structure and function of the brain. Although a substantial body of literature has identified structural brain differences in autism, it is unknown whether autism-associated common genetic variants are linked to changes in cortical macro- and micro-structure. We investigated this using neuroimaging and genetic data from adults (UK Biobank, N = 31,748) and children (ABCD, N = 4,928). Using polygenic scores and genetic correlations we observe a robust negative association between common variants for autism and a magnetic resonance imaging derived phenotype for neurite density (intracellular volume fraction) in the general population. This result is consistent across both children and adults, in both the cortex and in white matter tracts, and confirmed using polygenic scores and genetic correlations. There were no sex differences in this association. Mendelian randomisation analyses provide no evidence for a causal relationship between autism and intracellular volume fraction, although this should be revisited using better powered instruments. Overall, this study provides evidence for shared common variant genetics between autism and cortical neurite density.

Interpreting population- and family-based genome-wide association studies in the presence of confounding

A central aim of genome-wide association studies (GWASs) is to estimate direct genetic effects: the causal effects on an individual's phenotype of the alleles that they carry. However, estimates of direct effects can be subject to genetic and environmental confounding and can also absorb the "indirect" genetic effects of relatives' genotypes. Recently, an important development in controlling for these confounds has been the use of within-family GWASs, which, because of the randomness of mendelian segregation within pedigrees, are often interpreted as producing unbiased estimates of direct effects. Here, we present a general theoretical analysis of the influence of confounding in standard population-based and within-family GWASs. We show that, contrary to common interpretation, family-based estimates of direct effects can be biased by genetic confounding. In humans, such biases will often be small per-locus, but can be compounded when effect-size estimates are used in polygenic scores (PGSs). We illustrate the influence of genetic confounding on population- and family-based estimates of direct effects using models of assortative mating, population stratification, and stabilizing selection on GWAS traits. We further show how family-based estimates of indirect genetic effects, based on comparisons of parentally transmitted and untransmitted alleles, can suffer substantial genetic confounding. We conclude that, while family-based studies have placed GWAS estimation on a more rigorous footing, they carry subtle issues of interpretation that arise from confounding.

Maternal separation stress through triggering of the neuro-immune response in the hippocampus induces autistic-like behaviors in male mice

Autism spectrum disorder (ASD) is the fastest-growing neurodevelopmental disease throughout the world. Neuro-immune responses from prenatal to adulthood stages of life induce developmental defects in synaptic signaling, neurotransmitter imbalance, and even structural changes in the brain. In this study, we aimed to focus on the possible role of neuroinflammatory response in the hippocampus in development of the autistic-like behaviors following maternal separation (MS) stress in mice. To do this, mice neonates daily separated from their mothers from postnatal day (PND) 2 to PND 14 for 3 h. During PND45-60, behavioral tests related to autistic-like behaviors including three-chamber sociability, Morris water maze (MWM), shuttle box, resident-intruder, and marble burying tests were performed. Then, hippocampi were dissected out, and the gene expression of inflammatory mediators including TNF-α, IL-1β, TLR4, HMGB1, and NLRP3 was assessed in the hippocampus using RT-PCR. Results showed that MS mice exerted impaired sociability preference, repetitive behaviors, impaired passive avoidance, and spatial memories. The gene expression of inflammatory mediators significantly increased in the hippocampi of MS mice. We concluded that MS stress probably via activating of the HMGB1/TLR4 signaling cascade in the hippocampus induced autistic-like behaviors in mice.

Genomic analysis of 116 autism families strengthens known risk genes and highlights promising candidates

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with a strong genetic component in which rare variants contribute significantly to risk. We performed whole genome and/or exome sequencing (WGS and WES) and SNP-array analysis to identify both rare sequence and copy number variants (SNVs and CNVs) in 435 individuals from 116 ASD families. We identified 37 rare potentially damaging de novo SNVs (pdSNVs) in the cases (n = 144). Interestingly, two of them (one stop-gain and one missense variant) occurred in the same gene, BRSK2. Moreover, the identification of 8 severe de novo pdSNVs in genes not previously implicated in ASD (AGPAT3, IRX5, MGAT5B, RAB8B, RAP1A, RASAL2, SLC9A1, YME1L1) highlighted promising candidates. Potentially damaging CNVs (pdCNVs) provided support to the involvement of inherited variants in PHF3, NEGR1, TIAM1 and HOMER1 in neurodevelopmental disorders (NDD), although mostly acting as susceptibility factors with incomplete penetrance. Interpretation of identified pdSNVs/pdCNVs according to the ACMG guidelines led to a molecular diagnosis in 19/144 cases, although this figure represents a lower limit and is expected to increase thanks to further clarification of the role of likely pathogenic variants in ASD/NDD candidate genes not yet established. In conclusion, our study highlights promising ASD candidate genes and contributes to characterize the allelic diversity, mode of inheritance and phenotypic impact of de novo and inherited risk variants in ASD/NDD genes.

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

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

Identification of an Antagonist Targeting G Protein and β-Arrestin Signaling Pathways of 5-HT7R

In consideration of the limited number of FDA-approved drugs for autism spectrum disorder (ASD), significant efforts have been devoted to identifying novel drug candidates. Among these, 5-HT7R modulators have garnered considerable attention due to their potential in alleviating autism-like behaviors in ASD animal models. In this study, we designed and synthesized biphenyl-3-ylmethylpyrrolidines 3 and biphenyl-3-yl-dihydroimidazoles 4 as 5-HT7R modulators. Through extensive biological tests of 3 and 4 in G protein and β-arrestin signaling pathways of 5-HT7R, it was determined that 2-(2'-methoxy-[1,1'-biphenyl]-3-yl)-4,5-dihydro-1H-imidazole 4h acted as a 5-HT7R antagonist in both signaling pathways. In in vivo study with Shank3-/- transgenic (TG) mice, the self-grooming behavior test was performed with 4h, resulting in a significant reduction in the duration of self-grooming. In addition, an immunohistochemical experiment with 4h restored reduced neurogenesis in Shank3-/- TG mice, which is confirmed by the quantification of doublecortin (DCX) positive neurons, suggesting the promising therapeutic potential of 4h.

Evaluating the regulatory function of non-coding autism-associated single nucleotide polymorphisms on gene expression in human brain tissue

Common variants account for most of the estimated heritability associated with autism spectrum disorder (autism). Although several replicable single nucleotide polymorphisms (SNPs) for the condition have been detected using genome-wide association study (GWAS) methodologies, their pathophysiological relevance remains elusive. Examining this is complicated, however, as all detected loci are situated within non-coding regions of the genome. It is therefore likely that they possess roles of regulatory function as opposed to directly affecting gene coding sequences. To bridge the gap between SNP discovery and mechanistic insight, we applied a comprehensive bioinformatic pipeline to functionally annotate autism-associated polymorphisms and their non-coding linkage disequilibrium (i.e., non-randomly associated) partners. We identified 82 DNA variants of probable regulatory function that may contribute to autism pathogenesis. To validate these predictions, we measured the impact of 11 high-confidence candidates and their GWAS linkage disequilibrium partners on gene expression in human brain tissue from Autistic and non-Autistic donors. Although a small number of the surveyed variants exhibited measurable influence on gene expression as determined via quantitative polymerase chain reaction, these did not survive correction for multiple comparisons. Additionally, no significant genotype-by-diagnosis effects were observed for any of the SNP-gene associations. We contend that this may reflect an inability to effectively capture the modest, neurodevelopmental-specific impact of individual variants on biological dysregulation in available post-mortem tissue samples, as well as limitations in the existing autism GWAS data.

Polygenic Risk in Families With Spontaneous Coronary Artery Dissection

Importance

Spontaneous coronary artery dissection (SCAD) is a poorly understood cause of acute coronary syndrome that predominantly affects women. Evidence to date suggests a complex genetic architecture, while a family history is reported for a minority of cases.

Objective

To determine the contribution of rare and common genetic variants to SCAD risk in familial cases, the latter via the comparison of a polygenic risk score (PRS) with those with sporadic SCAD and healthy controls.

Design, Setting, and Participants

This genetic association study analyzed families with SCAD, individuals with sporadic SCAD, and healthy controls. Genotyping was undertaken for all participants. Participants were recruited between 2017 and 2021. A PRS for SCAD was calculated for all participants. The presence of rare variants in genes associated with connective tissue disorders (CTD) was also assessed. Individuals with SCAD were recruited via social media or from a single medical center. A previously published control database of older healthy individuals was used. Data were analyzed from January 2022 to October 2023.

Exposures

PRS for SCAD comprised of 7 single-nucleotide variants.

Main Outcomes and Measures

Disease status (familial SCAD, sporadic SCAD, or healthy control) associated with PRS.

Results

A total of 13 families with SCAD (27 affected and 12 unaffected individuals), 173 individuals with sporadic SCAD, and 1127 healthy controls were included. A total of 188 individuals with SCAD (94.0%) were female, including 25 of 27 with familial SCAD and 163 of 173 with sporadic SCAD; of 12 unaffected individuals from families with SCAD, 6 (50%) were female; and of 1127 healthy controls, 672 (59.6%) were female. Compared with healthy controls, the odds of being an affected family member or having sporadic SCAD was significantly associated with a SCAD PRS (where the odds ratio [OR] represents an increase in odds per 1-SD increase in PRS) (affected family member: OR, 2.14; 95% CI, 1.78-2.50; adjusted P = 1.96 × 10-4; sporadic SCAD: OR, 1.63; 95% CI, 1.37-1.89; adjusted P = 5.69 × 10-4). This association was not seen for unaffected family members (OR, 1.03; 95% CI, 0.46-1.61; adjusted P = .91) compared with controls. Further, those with familial SCAD were overrepresented in the top quintile of the control PRS distribution (OR, 3.70; 95% CI, 2.93-4.47; adjusted P = .001); those with sporadic SCAD showed a similar pattern (OR, 2.51; 95% CI, 1.98-3.04; adjusted P = .001). Affected individuals within a family did not share any rare deleterious variants in CTD-associated genes.

Conclusions and Relevance

Extreme aggregation of common genetic risk appears to play a significant role in familial clustering of SCAD as well as in sporadic case predisposition, although further study is required.

A de novo variant in RERE causes autistic behavior by disrupting related genes and signaling pathway

Autism spectrum disorder (ASD) is a highly variable neurodevelopmental disorder that typically manifests childhood, characterized by a triad of symptoms: impaired social interaction, communication difficulties, and restricted interests with repetitive behaviors. De novo variants in related genes can cause ASD. We present the case of a 6-year-old Chinese boy with autistic behavior, including language communication impairments, intellectual disabilities, stunted development, and irritability in social interactions. Using Sanger sequencing, we confirmed a pathogenic in the RERE gene (NM_012102.4) (c.3732delC, p.Tyr1245Thrfs*12; EX21; Het). Subsequently, we generated an RERE point mutation cell line (ReMut) using CRISPR/Cas9 Targeted Genome Editing. Immunofluorescence was conducted to determine the location of the mutant RERE. RNA-sequencing and mass spectrometry analyses were performed to elucidate the ASD-related genes and signaling pathways disrupted by this variant in RERE. We identified 3790 differentially expressed genes and 684 differentially expressed proteins. The SHH signaling pathway was found to be downregulated, and the Hippo pathway was upregulated in ReMut. Genes implicated in autism, such as CNTNAP2, STX1A, FARP2, and GPC1, were significantly downregulated. Simultaneously, we noted alterations in HDAC1 and HDAC2, which are members of the WHHERE complex, suggesting their role in the pathogenesis of this patient. In conclusion, we report a de novo variant in RERE associated with autistic behavior. The finding that ASD is associated with RERE variants underscore the role of genetic factors in ASD and provides insights regarding the mechanisms underlying RERE variants in disease onset.

Structural models of genome-wide covariance identify multiple common dimensions in autism

Common genetic variation has been associated with multiple phenotypic features in Autism Spectrum Disorder (ASD). However, our knowledge of shared genetic factor structures contributing to this highly heterogeneous phenotypic spectrum is limited. Here, we developed and implemented a structural equation modelling framework to directly model genomic covariance across core and non-core ASD phenotypes, studying autistic individuals of European descent with a case-only design. We identified three independent genetic factors most strongly linked to language performance, behaviour and developmental motor delay, respectively, studying an autism community sample (N = 5331). The three-factorial structure was largely confirmed in independent ASD-simplex families (N = 1946), although we uncovered, in addition, simplex-specific genetic overlap between behaviour and language phenotypes. Multivariate models across cohorts revealed novel associations, including links between language and early mastering of self-feeding. Thus, the common genetic architecture in ASD is multi-dimensional with overarching genetic factors contributing, in combination with ascertainment-specific patterns, to phenotypic heterogeneity.

Pervasive alterations of intra-axonal volume and network organization in young children with a 16p11.2 deletion

Reciprocal Copy Number Variants (CNVs) at the 16p11.2 locus confer high risk for autism spectrum disorder (ASD) and other neurodevelopmental disorders (NDDs). Morphometric MRI studies have revealed large and pervasive volumetric alterations in carriers of a 16p11.2 deletion. However, the specific neuroanatomical mechanisms underlying such alterations, as well as their developmental trajectory, are still poorly understood. Here we explored differences in microstructural brain connectivity between 24 children carrying a 16p11.2 deletion and 66 typically developing (TD) children between 2 and 8 years of age. We found a large pervasive increase of intra-axonal volume widespread over a high number of white matter tracts. Such microstructural alterations in 16p11.2 deletion children were already present at an early age, and led to significant changes in the global efficiency and integration of brain networks mainly associated to language, motricity and socio-emotional behavior, although the widespread pattern made it unlikely to represent direct functional correlates. Our results shed light on the neuroanatomical basis of the previously reported increase of white matter volume, and align well with analogous evidence of altered axonal diameter and synaptic function in 16p11.2 mice models. We provide evidence of a prevalent mechanistic deviation from typical maturation of brain structural connectivity associated with a specific biological risk to develop ASD. Future work is warranted to determine how this deviation contributes to the emergence of symptoms observed in young children diagnosed with ASD and other NDDs.

Whole exome sequencing and polygenic assessment of a Swedish cohort with severe developmental language disorder

Developmental language disorder (DLD) overlaps clinically, genetically, and pathologically with other neurodevelopmental disorders (NDD), corroborating the concept of the NDD continuum. There is a lack of studies to understand the whole genetic spectrum in individuals with DLD. Previously, we recruited 61 probands with severe DLD from 59 families and examined 59 of them and their families using microarray genotyping with a 6.8% diagnostic yield. Herein, we investigated 53 of those probands using whole exome sequencing (WES). Additionally, we used polygenic risk scores (PRS) to understand the within family enrichment of neurodevelopmental difficulties and examine the associations between the results of language-related tests in the probands and language-related PRS. We identified clinically significant variants in four probands, resulting in a 7.5% (4/53) molecular diagnostic yield. Those variants were in PAK2, MED13, PLCB4, and TNRC6B. We also prioritized additional variants for future studies for their role in DLD, including high-impact variants in PARD3 and DIP2C. PRS did not explain the aggregation of neurodevelopmental difficulties in these families. We did not detect significant associations between the language-related tests and language-related PRS. Our results support using WES as the first-tier genetic test for DLD as it can identify monogenic DLD forms. Large-scale sequencing studies for DLD are needed to identify new genes and investigate the polygenic contribution to the condition.

Curation of causal interactions mediated by genes associated with autism accelerates the understanding of gene-phenotype relationships underlying neurodevelopmental disorders

Autism spectrum disorder (ASD) comprises a large group of neurodevelopmental conditions featuring, over a wide range of severity and combinations, a core set of manifestations (restricted sociality, stereotyped behavior and language impairment) alongside various comorbidities. Common and rare variants in several hundreds of genes and regulatory regions have been implicated in the molecular pathogenesis of ASD along a range of causation evidence strength. Despite significant progress in elucidating the impact of few paradigmatic individual loci, such sheer complexity in the genetic architecture underlying ASD as a whole has hampered the identification of convergent actionable hubs hypothesized to relay between the vastness of risk alleles and the core phenotypes. In turn this has limited the development of strategies that can revert or ameliorate this condition, calling for a systems-level approach to probe the cross-talk of cooperating genes in terms of causal interaction networks in order to make convergences experimentally tractable and reveal their clinical actionability. As a first step in this direction, we have captured from the scientific literature information on the causal links between the genes whose variants have been associated with ASD and the whole human proteome. This information has been annotated in a computer readable format in the SIGNOR database and is made freely available in the resource website. To link this information to cell functions and phenotypes, we have developed graph algorithms that estimate the functional distance of any protein in the SIGNOR causal interactome to phenotypes and pathways. The main novelty of our approach resides in the possibility to explore the mechanistic links connecting the suggested gene-phenotype relations.

Rare X-linked variants carry predominantly male risk in autism, Tourette syndrome, and ADHD

Autism spectrum disorder (ASD), Tourette syndrome (TS), and attention-deficit/hyperactivity disorder (ADHD) display strong male sex bias, due to a combination of genetic and biological factors, as well as selective ascertainment. While the hemizygous nature of chromosome X (Chr X) in males has long been postulated as a key point of "male vulnerability", rare genetic variation on this chromosome has not been systematically characterized in large-scale whole exome sequencing studies of "idiopathic" ASD, TS, and ADHD. Here, we take advantage of informative recombinations in simplex ASD families to pinpoint risk-enriched regions on Chr X, within which rare maternally-inherited damaging variants carry substantial risk in males with ASD. We then apply a modified transmission disequilibrium test to 13,052 ASD probands and identify a novel high confidence ASD risk gene at exome-wide significance (MAGEC3). Finally, we observe that rare damaging variants within these risk regions carry similar effect sizes in males with TS or ADHD, further clarifying genetic mechanisms underlying male vulnerability in multiple neurodevelopmental disorders that can be exploited for systematic gene discovery.

Endophenotyping social cognition in the broader autism phenotype

Relatives of individuals with autism spectrum disorder (ASD) may display milder social traits of the broader autism phenotype (BAP) providing potential endophenotypic markers of genetic risk for ASD. We performed a case-control comparison to quantify social cognition and pragmatic language difficulties in the BAP (n = 25 cases; n = 33 controls) using the Faux Pas test (FPT) and the Goldman-Eisler Cartoon task. Using deep phenotyping we then examined patterns of inheritance of social cognition in two large multiplex families and the spectrum of performance in 32 additional families (159 members; n = 51 ASD, n = 87 BAP, n = 21 unaffected). BAP individuals showed significantly poorer FPT performance and reduced verbal fluency with the absence of a compression effect in social discourse compared to controls. In multiplex families, we observed reduced FPT performance in 89% of autistic family members, 63% of BAP relatives and 50% of unaffected relatives. Across all affected families, there was a graded spectrum of difficulties, with ASD individuals showing the most severe FPT difficulties, followed by the BAP and unaffected relatives compared to community controls. We conclude that relatives of probands show an inherited pattern of graded difficulties in social cognition with atypical faux pas detection in social discourse providing a novel candidate endophenotype for ASD.

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

Rare copy number variants (CNVs) and polygenic risk for intelligence (PRS-IQ) both confer risk 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 risk, 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. 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. 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 risk 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. Our findings suggest that cognitive ability itself may not be the factor driving the underlying risk 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.

Factorizing polygenic epistasis improves prediction and uncovers biological pathways in complex traits

Epistasis is central in many domains of biology, but it has not yet been proven useful for understanding the etiology of complex traits. This is partly because complex-trait epistasis involves polygenic interactions that are poorly captured in current models. To address this gap, we developed a model called Epistasis Factor Analysis (EFA). EFA assumes that polygenic epistasis can be factorized into interactions between a few epistasis factors (EFs), which represent latent polygenic components of the observed complex trait. The statistical goals of EFA are to improve polygenic prediction and to increase power to detect epistasis, while the biological goal is to unravel genetic effects into more-homogeneous units. We mathematically characterize EFA and use simulations to show that EFA outperforms current epistasis models when its assumptions approximately hold. Applied to predicting yeast growth rates, EFA outperforms the additive model for several traits with large epistasis heritability and uniformly outperforms the standard epistasis model. We replicate these prediction improvements in a second dataset. We then apply EFA to four previously characterized traits in the UK Biobank and find statistically significant epistasis in all four, including two that are robust to scale transformation. Moreover, we find that the inferred EFs partly recover pre-defined biological pathways for two of the traits. Our results demonstrate that more realistic models can identify biologically and statistically meaningful epistasis in complex traits, indicating that epistasis has potential for precision medicine and characterizing the biology underlying GWAS results.

Whole genome analysis of rare deleterious variants adds further evidence to BRSK2 and other risk genes in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with a strong genetic component in which rare variants contribute significantly to risk. We have performed whole genome and/or exome sequencing (WGS and WES) and SNP-array analysis to identify both rare sequence and copy number variants (SNVs and CNVs) in 435 individuals from 116 ASD families. We identified 37 rare potentially damaging de novo SNVs (pdSNVs) in cases (n = 144). Interestingly, two of them (one stop-gain and one missense variant) occurred in the same gene, BRSK2. Moreover, the identification of 9 severe de novo pdSNVs in genes not previously implicated in ASD (RASAL2, RAP1A, IRX5, SLC9A1, AGPAT3, MGAT3, RAB8B, MGAT5B, YME1L1), highlighted novel candidates. Potentially damaging CNVs (pdCNVs) provided support to the involvement of inherited variants in PHF3, NEGR1, TIAM1 and HOMER1 in neurodevelopmental disorders (NDD), although mostly acting as susceptibility factors with incomplete penetrance. Interpretation of identified pdSNVs/pdCNVs according to the ACMG guidelines led to a molecular diagnosis in 19/144 cases, but this figure represents a lower limit and is expected to increase thanks to further clarification of the role of likely pathogenic variants in new ASD/NDD candidates. In conclusion, our study strengthens the role of BRSK2 and other neurodevelopmental genes in ASD risk, highlights novel candidates and contributes to characterize the allelic diversity, mode of inheritance and phenotypic impact of de novo and inherited risk variants in ASD/NDD genes.

Transmit Radiant Individuality to Offspring (TRIO) study: investigating intergenerational transmission effects on brain development

Intergenerational transmission is a crucial aspect of human development. Although prior studies have demonstrated the continuity of psychopathology and maladaptive upbringing environments between parents and offspring, the underlying neurobiological mechanisms remain unclear. We have begun a novel neuroimaging research project, the Transmit Radiant Individuality to Offspring (TRIO) study, which focuses on biological parent-offspring trios. The participants of the TRIO study were Japanese parent-offspring trios consisting of offspring aged 10-40 and their biological mother and father. Structural and functional brain images of all participants were acquired using magnetic resonance imaging (MRI). Saliva samples were collected for DNA analysis. We obtained psychosocial information, such as intelligence, mental health problems, personality traits, and experiences during the developmental period from each parent and offspring in the same manner as much as possible. By April 2023, we completed data acquisition from 174 trios consisting of fathers, mothers, and offspring. The target sample size was 310 trios. However, we plan to conduct genetic and epigenetic analyses, and the sample size is expected to be expanded further while developing this project into a multi-site collaborative study in the future. The TRIO study can challenge the elucidation of the mechanism of intergenerational transmission effects on human development by collecting diverse information from parents and offspring at the molecular, neural, and behavioral levels. Our study provides interdisciplinary insights into how individuals' lives are involved in the construction of the lives of their descendants in the subsequent generation.

Phenotype and genetic analysis of data collected within the first year of NeuroDev

Genetic association studies have made significant contributions to our understanding of the etiology of neurodevelopmental disorders (NDDs). However, these studies rarely focused on the African continent. The NeuroDev Project aims to address this diversity gap through detailed phenotypic and genetic characterization of children with NDDs from Kenya and South Africa. We present results from NeuroDev's first year of data collection, including phenotype data from 206 cases and clinical genetic analyses of 99 parent-child trios. Most cases met criteria for global developmental delay/intellectual disability (GDD/ID, 80.3%). Approximately half of the children with GDD/ID also met criteria for autism. Analysis of exome-sequencing data identified a pathogenic or likely pathogenic variant in 13 (17%) of the 75 cases from South Africa and 9 (38%) of the 24 cases from Kenya. Data from the trio pilot are publicly available, and the NeuroDev Project will continue to develop resources for the global genetics community.

Genetically inferred birthweight, height, and puberty timing and risk of osteosarcoma

INTRODUCTION

Several studies have linked increased risk of osteosarcoma with tall stature, high birthweight, and early puberty, although evidence is inconsistent. We used genetic risk scores (GRS) based on established genetic loci for these traits and evaluated associations between genetically inferred birthweight, height, and puberty timing with osteosarcoma.

METHODS

Using genotype data from two genome-wide association studies, totaling 1039 cases and 2923 controls of European ancestry, association analyses were conducted using logistic regression for each study and meta-analyzed to estimate pooled odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup analyses were conducted by case diagnosis age, metastasis status, tumor location, tumor histology, and presence of a known pathogenic variant in a cancer susceptibility gene.

RESULTS

Genetically inferred higher birthweight was associated with an increased risk of osteosarcoma (OR =1.59, 95% CI 1.07-2.38, P = 0.02). This association was strongest in cases without metastatic disease (OR =2.46, 95% CI 1.44-4.19, P = 9.5 ×10-04). Although there was no overall association between osteosarcoma and genetically inferred taller stature (OR=1.06, 95% CI 0.96-1.17, P = 0.28), the GRS for taller stature was associated with an increased risk of osteosarcoma in 154 cases with a known pathogenic cancer susceptibility gene variant (OR=1.29, 95% CI 1.03-1.63, P = 0.03). There were no significant associations between the GRS for puberty timing and osteosarcoma.

CONCLUSION

A genetic propensity to higher birthweight was associated with increased osteosarcoma risk, suggesting that shared genetic factors or biological pathways that affect birthweight may contribute to osteosarcoma pathogenesis.

The contributions of rare inherited and polygenic risk to ASD in multiplex families

Autism spectrum disorder (ASD) has a complex genetic architecture involving contributions from both de novo and inherited variation. Few studies have been designed to address the role of rare inherited variation or its interaction with common polygenic risk in ASD. Here, we performed whole-genome sequencing of the largest cohort of multiplex families to date, consisting of 4,551 individuals in 1,004 families having two or more autistic children. Using this study design, we identify seven previously unrecognized ASD risk genes supported by a majority of rare inherited variants, finding support for a total of 74 genes in our cohort and a total of 152 genes after combined analysis with other studies. Autistic children from multiplex families demonstrate an increased burden of rare inherited protein-truncating variants in known ASD risk genes. We also find that ASD polygenic score (PGS) is overtransmitted from nonautistic parents to autistic children who also harbor rare inherited variants, consistent with combinatorial effects in the offspring, which may explain the reduced penetrance of these rare variants in parents. We also observe that in addition to social dysfunction, language delay is associated with ASD PGS overtransmission. These results are consistent with an additive complex genetic risk architecture of ASD involving rare and common variation and further suggest that language delay is a core biological feature of ASD.

Phenotypic effects of genetic variants associated with autism

While over 100 genes have been associated with autism, little is known about the prevalence of variants affecting them in individuals without a diagnosis of autism. Nor do we fully appreciate the phenotypic diversity beyond the formal autism diagnosis. Based on data from more than 13,000 individuals with autism and 210,000 undiagnosed individuals, we estimated the odds ratios for autism associated to rare loss-of-function (LoF) variants in 185 genes associated with autism, alongside 2,492 genes displaying intolerance to LoF variants. In contrast to autism-centric approaches, we investigated the correlates of these variants in individuals without a diagnosis of autism. We show that these variants are associated with a small but significant decrease in fluid intelligence, qualification level and income and an increase in metrics related to material deprivation. These effects were larger for autism-associated genes than in other LoF-intolerant genes. Using brain imaging data from 21,040 individuals from the UK Biobank, we could not detect significant differences in the overall brain anatomy between LoF carriers and non-carriers. Our results highlight the importance of studying the effect of the genetic variants beyond categorical diagnosis and the need for more research to understand the association between these variants and sociodemographic factors, to best support individuals carrying these variants.

Leveraging family data to design Mendelian randomization that is provably robust to population stratification

Mendelian randomization (MR) has emerged as a powerful approach to leverage genetic instruments to infer causality between pairs of traits in observational studies. However, the results of such studies are susceptible to biases owing to weak instruments, as well as the confounding effects of population stratification and horizontal pleiotropy. Here, we show that family data can be leveraged to design MR tests that are provably robust to confounding from population stratification, assortative mating, and dynastic effects. We show in simulations that our approach, MR-Twin, is robust to confounding from population stratification and is not affected by weak instrument bias, whereas standard MR methods yield inflated false positive rates. We then conduct an exploratory analysis of MR-Twin and other MR methods applied to 121 trait pairs in the UK Biobank data set. Our results suggest that confounding from population stratification can lead to false positives for existing MR methods, whereas MR-Twin is immune to this type of confounding, and that MR-Twin can help assess whether traditional approaches may be inflated owing to confounding from population stratification.

Analysis of convergence of linkage and association studies in autism spectrum disorders

Autism spectrum disorder (ASD) is a clinically and genetically heterogeneous group of pervasive neurodevelopmental disorders with a strong hereditary component. Although genome-wide linkage studies (GWLS) and [genome-wide association studies (GWAS)] have previously identified hundreds of ASD risk gene loci, the results remain inconclusive. In this study, a genomic convergence approach of GWAS and GWLS for ASD was implemented for the first time in order to identify genomic loci supported by both methods. A database with 32 GWLS and five GWAS for ASD was created. Convergence was quantified as the proportion of significant GWAS markers located within linked regions. Convergence was not found to be significantly higher than expected by chance (z-test = 1,177, P = 0,239). Although convergence is supportive of genuine effects, the lack of agreement between GWLS and GWAS is also indicative that these studies are designed to answer different questions and are not equally well suited for deciphering the genetics of complex traits.

Comparing synaptic proteomes across five mouse models for autism reveals converging molecular similarities including deficits in oxidative phosphorylation and Rho GTPase signaling

Specific and effective treatments for autism spectrum disorder (ASD) are lacking due to a poor understanding of disease mechanisms. Here we test the idea that similarities between diverse ASD mouse models are caused by deficits in common molecular pathways at neuronal synapses. To do this, we leverage the availability of multiple genetic models of ASD that exhibit shared synaptic and behavioral deficits and use quantitative mass spectrometry with isobaric tandem mass tagging (TMT) to compare their hippocampal synaptic proteomes. Comparative analyses of mouse models for Fragile X syndrome (Fmr1 knockout), cortical dysplasia focal epilepsy syndrome (Cntnap2 knockout), PTEN hamartoma tumor syndrome (Pten haploinsufficiency), ANKS1B syndrome (Anks1b haploinsufficiency), and idiopathic autism (BTBR+) revealed several common altered cellular and molecular pathways at the synapse, including changes in oxidative phosphorylation, and Rho family small GTPase signaling. Functional validation of one of these aberrant pathways, Rac1 signaling, confirms that the ANKS1B model displays altered Rac1 activity counter to that observed in other models, as predicted by the bioinformatic analyses. Overall similarity analyses reveal clusters of synaptic profiles, which may form the basis for molecular subtypes that explain genetic heterogeneity in ASD despite a common clinical diagnosis. Our results suggest that ASD-linked susceptibility genes ultimately converge on common signaling pathways regulating synaptic function and propose that these points of convergence are key to understanding the pathogenesis of this disorder.

Family-based analysis of the contribution of rare and common genetic variants to school performance in schizophrenia

Impaired cognition in schizophrenia is associated with worse functional outcomes. While genetic factors are known to contribute to variation in cognition in schizophrenia, few rare coding variants with strong effects have been identified, and the relative effects from de novo, inherited and non-transmitted alleles are unknown. We used array and exome sequencing data from 656 proband-parent trios to examine the contribution of common and rare variants to school performance, and by implication cognitive function, in schizophrenia. Parental transmission of common alleles contributing to higher educational attainment (p value = 0.00015; OR = 2.63) and intelligence (p value = 0.00009; OR = 2.80), but not to schizophrenia, were associated with higher proband school performance. No significant effects were seen for non-transmitted parental common alleles. Probands with lower school performance were enriched for damaging de novo coding variants in genes associated with developmental disorders (DD) (p value = 0.00026; OR = 11.6). Damaging, ultra-rare coding variants in DD genes that were transmitted or non-transmitted from parents, had no effects on school performance. Among probands with lower school performance, those with damaging de novo coding variants in DD genes had a higher rate of comorbid mild intellectual disability (p value = 0.0002; OR = 15.6). Overall, we provide evidence for rare and common genetic contributions to school performance in schizophrenia. The strong effects for damaging de novo coding variants in DD genes provide further evidence that cognitive impairment in schizophrenia has a shared aetiology with developmental disorders. Furthermore, we report no evidence in this sample that non-transmitted parental common alleles for cognitive traits contributed to school performance in schizophrenia via indirect effects on the environment.

Identifying rare genetic variants in 21 highly multiplex autism families: the role of diagnosis and autistic traits

Autism is a highly heritable, heterogeneous, neurodevelopmental condition. Large-scale genetic studies, predominantly focussing on simplex families and clinical diagnoses of autism have identified hundreds of genes associated with autism. Yet, the contribution of these classes of genes to multiplex families and autistic traits still warrants investigation. Here, we conducted whole-genome sequencing of 21 highly multiplex autism families, with at least three autistic individuals in each family, to prioritise genes associated with autism. Using a combination of both autistic traits and clinical diagnosis of autism, we identify rare variants in genes associated with autism, and related neurodevelopmental conditions in multiple families. We identify a modest excess of these variants in autistic individuals compared to individuals without an autism diagnosis. Finally, we identify a convergence of the genes identified in molecular pathways related to development and neurogenesis. In sum, our analysis provides initial evidence to demonstrate the value of integrating autism diagnosis and autistic traits to prioritise genes.

Exploring potential impacts of pregnancy-related maternal immune activation and extracellular vesicles on immune alterations observed in autism spectrum disorder

Autism Spectrum Disorder (ASD) is a set of neurodevelopmental disorders usually observed in early life, with impacts on behavioral and social skills. Incidence of ASD has been dramatically increasing worldwide, possibly due to increase in awareness/diagnosis as well as to genetic and environmental triggers. Currently, it is estimated that ∼1% of the world population presents ASD symptoms. In addition to its genetic background, environmental and immune-related factors also influence the ASD etiology. In this context, maternal immune activation (MIA) has recently been suggested as a component potentially involved in ASD development. In addition, extracellular vesicles (EVs) are abundant at the maternal-fetal interface and are actively involved in the immunoregulation required for a healthy pregnancy. Considering that alterations in concentration and content of EVs have also been associated with ASD, this article raises a debate about the potential roles of EVs in the processes surrounding MIA. This represents the major differential of the present review compared to other ASD studies. To support the suggested correlations and hypotheses, findings regarding the roles of EVs during pregnancy and potential influences on ASD are discussed, along with a review and update concerning the participation of infections, cytokine unbalances, overweight and obesity, maternal anti-fetal brain antibodies, maternal fever, gestational diabetes, preeclampsia, labor type and microbiota unbalances in MIA and ASD.

Assessment of vulnerability dimensions considering Family History and environmental interplay in Autism Spectrum Disorder

BACKGROUND

Despite previous studies have recently shown Autism Spectrum Disorders (ASD) as having a strong genetics background, over a minimum environmental background, no study up to date has investigated the interplay between genetics and environment.

METHODS

We have collected data regarding Family History (FH) and Environmental Factors (EF) from 2,141 individuals with ASD and their caretakers throughout Brazil, based on an online questionnaire. Most of the ASD individuals were males (81%) and the average age was 02 years minimum for males and females, and the maximum age was 41 years for males and 54 for females. People from all states in Brazil have answered the questionnaire. Genetic inheritance was obtained based on the declared FH of Psychiatric and Neurological diagnosis. As for EF, exposure to risk factors during pregnancy was considered, like infections, diabetes, drugs/chemicals exposure, socioeconomic, and psychological factors. Respondents were invited to answer the questionnaire in lectures given throughout Brazil, and by the social networks of the NGO "The Tooth Fairy Project". A Multiple Correspondence Analysis (MCA) was conducted to search vulnerability dimensions, and a Cluster Analysis was conducted to classify and identify the subgroups.

RESULTS

Regarding EF, social and psychological exposures contributed to the first two dimensions. Concerning FH, the first dimension represented psychiatric FH, while the second represented neurological FH. When analyzed together, EF and FH contributed to two new dimensions: 1. psychiatric FH, and 2. a psychosocial component. Using Cluster Analysis, it was not possible to isolate subgroups by genetic vulnerability or environmental exposure. Instead, a gradient of psychiatric FH with similar contributions of EF was observed.

CONCLUSION

In this study, it was not possible to isolate groups of patients that correspond to only one component, but rather a continuum with different compositions of genetic and environmental interplay.

Candidate biomarkers from the integration of methylation and gene expression in discordant autistic sibling pairs

While the genetics of autism spectrum disorders (ASD) has been intensively studied, resulting in the identification of over 100 putative risk genes, the epigenetics of ASD has received less attention, and results have been inconsistent across studies. We aimed to investigate the contribution of DNA methylation (DNAm) to the risk of ASD and identify candidate biomarkers arising from the interaction of epigenetic mechanisms with genotype, gene expression, and cellular proportions. We performed DNAm differential analysis using whole blood samples from 75 discordant sibling pairs of the Italian Autism Network collection and estimated their cellular composition. We studied the correlation between DNAm and gene expression accounting for the potential effects of different genotypes on DNAm. We showed that the proportion of NK cells was significantly reduced in ASD siblings suggesting an imbalance in their immune system. We identified differentially methylated regions (DMRs) involved in neurogenesis and synaptic organization. Among candidate loci for ASD, we detected a DMR mapping to CLEC11A (neighboring SHANK1) where DNAm and gene expression were significantly and negatively correlated, independently from genotype effects. As reported in previous studies, we confirmed the involvement of immune functions in the pathophysiology of ASD. Notwithstanding the complexity of the disorder, suitable biomarkers such as CLEC11A and its neighbor SHANK1 can be discovered using integrative analyses even with peripheral tissues.

The contribution of copy number variants to psychiatric symptoms and cognitive ability

Copy number variants (CNVs) are deletions and duplications of DNA sequence. The most frequently studied CNVs, which are described in this review, are recurrent CNVs that occur in the same locations on the genome. These CNVs have been strongly implicated in neurodevelopmental disorders, namely autism spectrum disorder (ASD), intellectual disability (ID), and developmental delay (DD), but also in schizophrenia. More recent work has also shown that CNVs increase risk for other psychiatric disorders, namely, depression, bipolar disorder, and post-traumatic stress disorder. Many of the same CNVs are implicated across all of these disorders, and these neuropsychiatric CNVs are also associated with cognitive ability in the general population, as well as with structural and functional brain alterations. Neuropsychiatric CNVs also show incomplete penetrance, such that carriers do not always develop any psychiatric disorder, and may show only mild symptoms, if any. Variable expressivity, whereby the same CNVs are associated with many different phenotypes of varied severity, also points to highly complex mechanisms underlying disease risk in CNV carriers. Comprehensive and longitudinal phenotyping studies of individual CNVs have provided initial insights into these mechanisms. However, more work is needed to estimate and predict the effect of non-recurrent, ultra-rare CNVs, which also contribute to psychiatric and cognitive outcomes. Moreover, delineating the broader phenotypic landscape of neuropsychiatric CNVs in both clinical and general population cohorts may also offer important mechanistic insights.

Accurate and Efficient Estimation of Local Heritability using Summary Statistics and LD Matrix

Existing SNP-heritability estimation methods that leverage GWAS summary statistics produce estimators that are less efficient than the restricted maximum likelihood (REML) estimator using individual-level data under linear mixed models (LMMs). Increasing the precision of a heritability estimator is particularly important for regional analyses, as local genetic variances tend to be small. We introduce a new estimator for local heritability, "HEELS", which attains comparable statistical efficiency as REML (\emph{i.e.} relative efficiency greater than 92%) but only requires summary-level statistics -- Z-scores from the marginal association tests plus the empirical LD matrix. HEELS significantly improves the statistical efficiency of the existing summary-statistics-based heritability estimators-- for instance, HEELS produces heritability estimates that are more than 3-fold and 7-times less variable than GRE and LDSC, respectively. Moreover, we introduce a unified framework to evaluate and compare the performance of different LD approximation strategies. We propose representing the empirical LD as the sum of a low-rank matrix and a banded matrix. This approximation not only reduces the storage and memory cost of using the LD matrix, but also improves the computational efficiency of the HEELS estimation. We demonstrate the statistical efficiency of HEELS and the advantages of our proposed LD approximation strategies both in simulations and through empirical analyses of the UK Biobank data.

Analysis of common genetic variation across targets of microRNAs dysregulated both in ASD and epilepsy reveals negative correlation

Genetic overlap involving rare disrupting mutations may contribute to high comorbidity rates between autism spectrum disorders and epilepsy. Despite their polygenic nature, genome-wide association studies have not reported a significant contribution of common genetic variation to comorbidity between both conditions. Analysis of common genetic variation affecting specific shared pathways such as miRNA dysregulation could help to elucidate the polygenic mechanisms underlying comorbidity between autism spectrum disorders and epilepsy. We evaluated here the role of common predisposing variation to autism spectrum disorders and epilepsy across target genes of 14 miRNAs selected through bibliographic research as being dysregulated in both disorders. We considered 4,581 target genes from various in silico sources. We described negative genetic correlation between autism spectrum disorders and epilepsy across variants located within target genes of the 14 miRNAs selected (p = 0.0228). Moreover, polygenic transmission disequilibrium test on an independent cohort of autism spectrum disorders trios (N = 233) revealed an under-transmission of autism spectrum disorders predisposing alleles within miRNAs’ target genes across autism spectrum disorders trios without comorbid epilepsy, thus reinforcing the negative relationship at the common genetic variation between both traits. Our study provides evidence of a negative relationship between autism spectrum disorders and epilepsy at the common genetic variation level that becomes more evident when focusing on the miRNA regulatory networks, which contrasts with observed clinical comorbidity and results from rare variation studies. Our findings may help to conceptualize the genetic heterogeneity and the comorbidity with epilepsy in autism spectrum disorders.

Protein interaction studies in human induced neurons indicate convergent biology underlying autism spectrum disorders

Autism spectrum disorders (ASDs) have been linked to genes with enriched expression in the brain, but it is unclear how these genes converge into cell-type-specific networks. We built a protein-protein interaction network for 13 ASD-associated genes in human excitatory neurons derived from induced pluripotent stem cells (iPSCs). The network contains newly reported interactions and is enriched for genetic and transcriptional perturbations observed in individuals with ASDs. We leveraged the network data to show that the ASD-linked brain-specific isoform of ANK2 is important for its interactions with synaptic proteins and to characterize a PTEN-AKAP8L interaction that influences neuronal growth. The IGF2BP1-3 complex emerged as a convergent point in the network that may regulate a transcriptional circuit of ASD-associated genes. Our findings showcase cell-type-specific interactomes as a framework to complement genetic and transcriptomic data and illustrate how both individual and convergent interactions can lead to biological insights into ASDs.

UBE3A and transsynaptic complex NRXN1-CBLN1-GluD1 in a hypothalamic VMHvl-arcuate feedback circuit regulates aggression

The circuit origins of aggression in autism spectrum disorder remain undefined. Here we report Tac1-expressing glutamatergic neurons in ventrolateral division of ventromedial hypothalamus (VMHvl) drive intermale aggression. Aggression is increased due to increases of Ube3a gene dosage in the VMHvl neurons when modeling autism due to maternal 15q11-13 triplication. Targeted deletion of increased Ube3a copies in VMHvl reverses the elevated aggression adult mice. VMHvl neurons form excitatory synapses onto hypothalamic arcuate nucleus AgRP/NPY neurons through a NRXN1-CBLN1-GluD1 transsynaptic complex and UBE3A impairs this synapse by decreasing Cbln1 gene expression. Exciting AgRP/NPY arcuate neurons leads to feedback inhibition of VMHvl neurons and inhibits aggression. Asymptomatic increases of UBE3A synergize with a heterozygous deficiency of presynaptic Nrxn1 or postsynaptic Grid1 (both ASD genes) to increase aggression. Targeted deletions of Grid1 in arcuate AgRP neurons impairs the VMHvl to AgRP/NPY neuron excitatory synapses while increasing aggression. Chemogenetic/optogenetic activation of arcuate AgRP/NPY neurons inhibits VMHvl neurons and represses aggression. These data reveal that multiple autism genes converge to regulate the VMHvl-arcuate AgRP/NPY glutamatergic synapse. The hypothalamic circuitry implicated by these data suggest impaired excitation of AgRP/NPY feedback inhibitory neurons may explain the increased aggression behavior found in genetic forms of autism.

Translating precision medicine for autism spectrum disorder: A pressing need

Autism spectrum disorder (ASD) is a heterogenous group of neurodevelopmental disorders (NDDs) with a high unmet medical need. Currently, ASD is diagnosed according to behavior-based criteria that overlook clinical and genomic heterogeneity, thus repeatedly resulting in failed clinical trials. Here, we summarize the scientific evidence pointing to the pressing need to create a precision medicine framework for ASD and other NDDs. We discuss the role of omics and systems biology to characterize more homogeneous disease subtypes with different underlying pathophysiological mechanisms and to determine corresponding tailored treatments. Finally, we provide recent initiatives towards tackling the complexity in NDDs for precision medicine and cost-effective drug discovery.

Interpreting population and family-based genome-wide association studies in the presence of confounding

A central aim of genome-wide association studies (GWASs) is to estimate direct genetic effects: the causal effects on an individual's phenotype of the alleles that they carry. However, estimates of direct effects can be subject to genetic and environmental confounding, and can also absorb the 'indirect' genetic effects of relatives' genotypes. Recently, an important development in controlling for these confounds has been the use of within-family GWASs, which, because of the randomness of Mendelian segregation within pedigrees, are often interpreted as producing unbiased estimates of direct effects. Here, we present a general theoretical analysis of the influence of confounding in standard population-based and within-family GWASs. We show that, contrary to common interpretation, family-based estimates of direct effects can be biased by genetic confounding. In humans, such biases will often be small per-locus, but can be compounded when effect size estimates are used in polygenic scores. We illustrate the influence of genetic confounding on population- and family-based estimates of direct effects using models of assortative mating, population stratification, and stabilizing selection on GWAS traits. We further show how family-based estimates of indirect genetic effects, based on comparisons of parentally transmitted and untransmitted alleles, can suffer substantial genetic confounding. In addition to known biases that can arise in family-based GWASs when interactions between family members are ignored, we show that biases can also arise from gene-by-environment (G×E) interactions when parental genotypes are not distributed identically across interacting environmental and genetic backgrounds. We conclude that, while family-based studies have placed GWAS estimation on a more rigorous footing, they carry subtle issues of interpretation that arise from confounding and interactions.

Mouse population genetics phenocopies heterogeneity of human Chd8 haploinsufficiency

Preclinical models of neurodevelopmental disorders typically use single inbred mouse strains, which fail to capture the genetic diversity and symptom heterogeneity that is common clinically. We tested whether modeling genetic background diversity in mouse genetic reference panels would recapitulate population and individual differences in responses to a syndromic mutation in the high-confidence autism risk gene, CHD8. We measured clinically relevant phenotypes in >1,000 mice from 33 strains, including brain and body weights and cognition, activity, anxiety, and social behaviors, using 5 behavioral assays: cued fear conditioning, open field tests in dark and bright light, direct social interaction, and social dominance. Trait disruptions mimicked those seen clinically, with robust strain and sex differences. Some strains exhibited large effect-size trait disruptions, sometimes in opposite directions, and-remarkably-others expressed resilience. Therefore, systematically introducing genetic diversity into models of neurodevelopmental disorders provides a better framework for discovering individual differences in symptom etiologies.

Sex-Related Changes in the Clinical, Genetic, Electrophysiological, Connectivity, and Molecular Presentations of ASD: A Comparison between Human and Animal Models of ASD with Reference to Our Data

The etiology of autism spectrum disorder (ASD) is genetic, environmental, and epigenetic. In addition to sex differences in the prevalence of ASD, which is 3-4 times more common in males, there are also distinct clinical, molecular, electrophysiological, and pathophysiological differences between sexes. In human, males with ASD have more externalizing problems (i.e., attention-deficit hyperactivity disorder), more severe communication and social problems, as well as repetitive movements. Females with ASD generally exhibit fewer severe communication problems, less repetitive and stereotyped behavior, but more internalizing problems, such as depression and anxiety. Females need a higher load of genetic changes related to ASD compared to males. There are also sex differences in brain structure, connectivity, and electrophysiology. Genetic or non-genetic experimental animal models of ASD-like behavior, when studied for sex differences, showed some neurobehavioral and electrophysiological differences between male and female animals depending on the specific model. We previously carried out studies on behavioral and molecular differences between male and female mice treated with valproic acid, either prenatally or early postnatally, that exhibited ASD-like behavior and found distinct differences between the sexes, the female mice performing better on tests measuring social interaction and undergoing changes in the expression of more genes in the brain compared to males. Interestingly, co-administration of S-adenosylmethionine alleviated the ASD-like behavioral symptoms and the gene-expression changes to the same extent in both sexes. The mechanisms underlying the sex differences are not yet fully understood.

Rationale, Design, and the Baseline Characteristics of the RHDGen (The Genetics of Rheumatic Heart Disease) Network Study†

BACKGROUND

The genetics of rheumatic heart disease (RHDGen) Network was developed to assist the discovery and validation of genetic variations and biomarkers of risk for rheumatic heart disease (RHD) in continental Africans, as a part of the global fight to control and eradicate rheumatic fever/RHD. Thus, we describe the rationale and design of the RHDGen study, comprising participants from 8 African countries.

METHODS

RHDGen screened potential participants using echocardiography, thereafter enrolling RHD cases and ethnically-matched controls for whom case characteristics were documented. Biological samples were collected for conducting genetic analyses, including a discovery case-control genome-wide association study (GWAS) and a replication trio family study. Additional biological samples were also collected, and processed, for the measurement of biomarker analytes and the biomarker analyses are underway.

RESULTS

Participants were enrolled into RHDGen between December 2012 and March 2018. For GWAS, 2548 RHD cases and 2261 controls (3301 women [69%]; mean age [SD], 37 [16.3] years) were available. RHD cases were predominantly Black (66%), Admixed (24%), and other ethnicities (10%). Among RHD cases, 34% were asymptomatic, 26% had prior valve surgery, and 23% had atrial fibrillation. The trio family replication arm included 116 RHD trio probands and 232 parents.

CONCLUSIONS

RHDGen presents a rare opportunity to identify relevant patterns of genetic factors and biomarkers in Africans that may be associated with differential RHD risk. Furthermore, the RHDGen Network provides a platform for further work on fully elucidating the causes and mechanisms associated with RHD susceptibility and development.

New insights from the last decade of research in psychiatric genetics: discoveries, challenges and clinical implications

Psychiatric genetics has made substantial progress in the last decade, providing new insights into the genetic etiology of psychiatric disorders, and paving the way for precision psychiatry, in which individual genetic profiles may be used to personalize risk assessment and inform clinical decision-making. Long recognized to be heritable, recent evidence shows that psychiatric disorders are influenced by thousands of genetic variants acting together. Most of these variants are commonly occurring, meaning that every individual has a genetic risk to each psychiatric disorder, from low to high. A series of large-scale genetic studies have discovered an increasing number of common and rare genetic variants robustly associated with major psychiatric disorders. The most convincing biological interpretation of the genetic findings implicates altered synaptic function in autism spectrum disorder and schizophrenia. However, the mechanistic understanding is still incomplete. In line with their extensive clinical and epidemiological overlap, psychiatric disorders appear to exist on genetic continua and share a large degree of genetic risk with one another. This provides further support to the notion that current psychiatric diagnoses do not represent distinct pathogenic entities, which may inform ongoing attempts to reconceptualize psychiatric nosology. Psychiatric disorders also share genetic influences with a range of behavioral and somatic traits and diseases, including brain structures, cognitive function, immunological phenotypes and cardiovascular disease, suggesting shared genetic etiology of potential clinical importance. Current polygenic risk score tools, which predict individual genetic susceptibility to illness, do not yet provide clinically actionable information. However, their precision is likely to improve in the coming years, and they may eventually become part of clinical practice, stressing the need to educate clinicians and patients about their potential use and misuse. This review discusses key recent insights from psychiatric genetics and their possible clinical applications, and suggests future directions.

Leveraging family data to design Mendelian Randomization that is provably robust to population stratification

Mendelian Randomization (MR) has emerged as a powerful approach to leverage genetic instruments to infer causality between pairs of traits in observational studies. However, the results of such studies are susceptible to biases due to weak instruments as well as the confounding effects of population stratification and horizontal pleiotropy. Here, we show that family data can be leveraged to design MR tests that are provably robust to confounding from population stratification, assortative mating, and dynastic effects. We demonstrate in simulations that our approach, MR-Twin, is robust to confounding from population stratification and is not affected by weak instrument bias, while standard MR methods yield inflated false positive rates. We applied MR-Twin to 121 trait pairs in the UK Biobank dataset and found that MR-Twin identifies likely causal trait pairs and does not identify trait pairs that are unlikely to be causal. Our results suggest that confounding from population stratification can lead to false positives for existing MR methods, while MR-Twin is immune to this type of confounding.

Interactions of genetic risks for autism and the broad autism phenotypes

Background

Common polygenic risk and de novo variants (DNVs) capture a small proportion of autism spectrum disorder (ASD) liability, and ASD phenotypic heterogeneity remains difficult to explain. Integrating multiple genetic factors contribute to clarifying the risk and clinical presentation of ASD.

Methods

In our study, we investigated the individual and combined effects of polygenic risk, damaging DNVs (including those in ASD risk genes), and sex among 2,591 ASD simplex families in the Simons Simplex Collection. We also explored the interactions among these factors, along with the broad autism phenotypes of ASD probands and their unaffected siblings. Finally, we combined the effects of polygenic risk, damaging DNVs in ASD risk genes, and sex to explain the total liability of ASD phenotypic spectrum.

Results

Our findings revealed that both polygenic risk and damaging DNVs contribute to an increased risk for ASD, with females exhibiting higher genetic burdens than males. ASD probands that carry damaging DNVs in ASD risk genes showed reduced polygenic risk. The effects of polygenic risk and damaging DNVs on autism broad phenotypes were inconsistent; probands with higher polygenic risk exhibited improvement in some behaviors, such as adaptive/cognitive behaviors, while those with damaging DNVs exhibited more severe phenotypes. Siblings with higher polygenic risk and damaging DNVs tended to have higher scores on broader autism phenotypes. Females exhibited more severe cognitive and behavioral problems compared to males among both ASD probands and siblings. The combination of polygenic risk, damaging DNVs in ASD risk genes, and sex explained 1-4% of the total liability of adaptive/cognitive behavior measurements.

Conclusion

Our study revealed that the risk for ASD and the autism broad phenotypes likely arises from a combination of common polygenic risk, damaging DNVs (including those in ASD risk genes), and sex.

Oxytocin Exposure in Labor and its Relationship with Cognitive Impairment and the Genetic Architecture of Autism

Whether there is a relationship between oxytocin (OXT) use in labor and the risk of autism (ASD), and the nature of such relationship, is unclear. By integrating genetic and clinical data in a sample of 176 ASD participants, we tested the hypothesis that OXT is a marker for abnormal prenatal development which leads to impairments in the process of labor. OXT-exposed ASD had more obstetric complications (P = 0.031), earlier onset of symptoms (P = 0.027), poorer cognitive development (P = 0.011), higher mutation burden across neurodevelopment genes (P = 0.020; OR = 5.33) and lower transmission of polygenic risk for ASD (P = 0.0319), than non-exposed ASD. OXT seems to constitute a risk indicator rather than a risk factor for ASD, which is relevant for diagnostic and genetic counselling.