Rare Copy Number Variants Research Articles

Rare copy number variant analysis in case-control studies using snp array data: a scalable and automated data analysis pipeline.

Rare copy number variants (CNVs) significantly influence the human genome and may contribute to disease susceptibility. High-throughput SNP genotyping platforms provide data that can be used for CNV detection, but it requires the complex pipelining of bioinformatic tools. Here, we propose a flexible bioinformatic pipeline for rare CNV analysis from human SNP array data. The pipeline consists of two major sub-pipelines: (1) Calling and quality control (QC) analysis, and (2) Rare CNV analysis. It is implemented in Snakemake following a rule-based structure that enables automation and scalability while maintaining flexibility. Our pipeline automates the detection and analysis of rare CNVs. It implements a rigorous CNV quality control, assesses the frequencies of these rare CNVs in patients versus controls, and evaluates the impact of CNVs on specific genes or pathways. We hence aim to provide an efficient yet flexible bioinformatic framework to investigate rare CNVs in biomedical research.

Genome-wide copy number variation association study in anorexia nervosa.

This study represents the first large-scale investigation of rare (<1% population frequency) copy number variants (CNVs) in anorexia nervosa (AN). Large, rare CNVs are reported to be causally associated with anthropometric traits, neurodevelopmental disorders, and schizophrenia, yet their role in the genetic basis of AN is unclear. Using genome-wide association study (GWAS) array data from the Anorexia Nervosa Genetics Initiative (ANGI), which included 7414 AN case and 5044 controls, we investigated the association of 67 well-established syndromic CNVs and 178 pleiotropic disease-risk dosage-sensitive CNVs with AN. To identify novel CNV regions (CNVRs) that increase the risk of AN, we conducted genome-wide association studies with a focus on rare CNV-breakpoints (CNV-GWAS). We found no net enrichment of rare CNVs, either deletions or duplications, in AN, and none of the well-established syndromic or pleiotropic CNVs had a significant association with AN status. However, the CNV-GWAS found 21 nominally associated CNVRs that contribute to AN risk, covering protein-coding genes implicated in synaptic function, metabolic/mitochondrial factors, and lipid characteristics, like the CD36 (7q21.11) gene, which transports long-chain fatty acids into cells. CNVRs intersecting genes previously related to neurodevelopmental traits include deletions of NRXN1 intron 5 (2p16.3), IMMP2L (7q31.1), and PTPRD (9p23). Overall, given that our study is well powered to detect the CNV burden level reported for schizophrenia, we can conclude that rare CNVs have a limited role in the etiology of AN, as reported for bipolar disorder. Our nominal associations for the 21 discovered CNVRs are consistent with AN being a metabo-psychiatric trait, as demonstrated by the common genetic architecture of AN, and we provide association results to allow for replication in future research.

Evaluating the Joint Effects of Recurrent Copy Number Variants and Polygenic Scores on the Risk of Psychiatric Disorders in the iPSYCH2015 Case-Cohort Sample.

The impact of rare recurrent copy number variants (rCNVs) and polygenic background attributed to common variants, on the risk of psychiatric disorders is well-established in separate studies. However, it remains unclear how polygenic background modulates the effect of rCNVs. Using the population-representative iPSYCH2015 case-cohort sample (N=96,599), we investigated the association between absolute risk of psychiatric disorders and carriage of rCNVs and polygenic scores (PGS), as well as the interaction effect between the two on disease risk. Carriers of rCNVs with higher gene constraint scores had an increased absolute risk for autism, ADHD, and schizophrenia, but not depression, whereas an increase in PGS for each respective disorder was associated with higher absolute risk across all four disorders. Similarly, elevated absolute risks were observed with the increase of both PGS and gene constraints of rCNVs except in the case of depression. In contrast to some previous case-control studies, our joint analysis of rCNV groups and PGS revealed no indication of significant interactive effect between these two factors on disease risk. Also, we found no significant interactions of PGS with any of the most common individual rCNVs, except in the case of 16p13.11 duplication, which was found to attenuate the effect of ADHD-PGS on the absolute risk of ADHD. This study advances our understanding of the interplay between rare and common important genetic risk factors for major psychiatric disorders and sheds light on the importance of population-based samples in implementing precision medicine.

Germline copy number variants and endometrial cancer risk.

Known risk loci for endometrial cancer explain approximately one third of familial endometrial cancer. However, the association of germline copy number variants (CNVs) with endometrial cancer risk remains relatively unknown. We conducted a genome-wide analysis of rare CNVs overlapping gene regions in 4115 endometrial cancer cases and 17,818 controls to identify functionally relevant variants associated with disease. We identified a 1.22-fold greater number of CNVs in DNA samples from cases compared to DNA samples from controls (p = 4.4 × 10-63). Under three models of putative CNV impact (deletion, duplication, and loss of function), genome-wide association studies identified 141 candidate gene loci associated (p < 0.01) with endometrial cancer risk. Pathway analysis of the candidate loci revealed an enrichment of genes involved in the 16p11.2 proximal deletion syndrome, driven by a large recurrent deletion (chr16:29,595,483-30,159,693) identified in 0.15% of endometrial cancer cases and 0.02% of control participants. Together, these data provide evidence that rare copy number variants have a role in endometrial cancer susceptibility and that the proximal 16p11.2 BP4-BP5 region contains 25 candidate risk gene(s) that warrant further analysis to better understand their role in human disease.

Phenotypic complexities of rare heterozygous neurexin-1 deletions.

Given the large number of genes significantly associated with risk for neuropsychiatric disorders, a critical unanswered question is the extent to which diverse mutations --sometimes impacting the same gene-- will require tailored therapeutic strategies. Here we consider this in the context of rare neuropsychiatric disorder-associated copy number variants (2p16.3) resulting in heterozygous deletions in NRXN1 , a pre-synaptic cell adhesion protein that serves as a critical synaptic organizer in the brain. Complex patterns of NRXN1 alternative splicing are fundamental to establishing diverse neurocircuitry, vary between the cell types of the brain, and are differentially impacted by unique (non-recurrent) deletions. We contrast the cell-type-specific impact of patient-specific mutations in NRXN1 using human induced pluripotent stem cells, finding that perturbations in NRXN1 splicing result in divergent cell-type-specific synaptic outcomes. Via distinct loss-of-function (LOF) and gain-of-function (GOF) mechanisms, NRXN1 +/- deletions cause decreased synaptic activity in glutamatergic neurons, yet increased synaptic activity in GABAergic neurons. Reciprocal isogenic manipulations causally demonstrate that aberrant splicing drives these changes in synaptic activity. For NRXN1 deletions, and perhaps more broadly, precision medicine will require stratifying patients based on whether their gene mutations act through LOF or GOF mechanisms, in order to achieve individualized restoration of NRXN1 isoform repertoires by increasing wildtype, or ablating mutant isoforms. Given the increasing number of mutations predicted to engender both LOF and GOF mechanisms in brain disorders, our findings add nuance to future considerations of precision medicine.

A burden of rare copy number variants in obsessive-compulsive disorder.

Current genetic research on obsessive-compulsive disorder (OCD) supports contributions to risk specifically from common single nucleotide variants (SNVs), along with rare coding SNVs and small insertion-deletions (indels). The contribution to OCD risk from rare copy number variants (CNVs), however, has not been formally assessed at a similar scale. Here we describe an analysis of rare CNVs called from genotype array data in 2248 deeply phenotyped OCD cases and 3608 unaffected controls from Sweden and Norway. Cases carry an elevated burden of CNVs ≥30 kb in size (OR = 1.12, P = 1.77 × 10-3). The excess rate of these CNVs in cases versus controls was around 0.07 (95% CI 0.02-0.11, P = 2.58 × 10-3). This signal was largely driven by CNVs overlapping protein-coding regions (OR = 1.19, P = 3.08 × 10-4), particularly deletions impacting loss-of-function intolerant genes (pLI >0.995, OR = 4.12, P = 2.54 × 10-5). We did not identify any specific locus where CNV burden was associated with OCD case status at genome-wide significance, but we noted non-random recurrence of CNV deletions in cases (permutation P = 2.60 × 10-3). In cases where sufficient clinical data were available (n = 1612) we found that carriers of neurodevelopmental duplications were more likely to have comorbid autism (P < 0.001), and that carriers of deletions overlapping neurodevelopmental genes had lower treatment response (P = 0.02). The results demonstrate a contribution of rare CNVs to OCD risk, and suggest that studies of rare coding variation in OCD would have increased power to identify risk genes if this class of variation were incorporated into formal tests.

Copy number variations in RNF216 and postsynaptic membrane-associated genes are associated with bipolar disorder: a case-control study in the Japanese population.

Bipolar disorder (BD) is a common psychiatric disorder characterized by alterations between manic/hypomanic and depressive states. Rare pathogenic copy number variations (CNVs) that overlap with exons of synaptic genes have been associated with BD. However, no study has comprehensively explored CNVs in synaptic genes associated with BD. Here, we evaluated the relationship between BD and rare CNVs that overlap with synaptic genes, not limited to exons, in the Japanese population. Using array comparative genome hybridization, we detected CNVs in 1839 patients with BD and 2760 controls. We used the Synaptic Gene Ontology database to identify rare CNVs that overlap with synaptic genes. Using gene-based analysis, we compared their frequencies between the BD and control groups. We also searched for synaptic gene sets related to BD. The significance level was set to a false discovery rate of 10%. The RNF216 gene was significantly associated with BD (odds ratio, 4.51 [95% confidence interval, 1.66-14.89], false discovery rate < 10%). The BD-associated CNV that corresponded with RNF216 also partially overlapped with the minimal critical region of the 7p22.1 microduplication syndrome. The integral component of the postsynaptic membrane (Gene Ontology:0099055) was significantly associated with BD. The CNV overlapping with the intron region of GRM5 in this gene set showed a nominal significant association between cases and controls (P < 0.05). We provide evidence that CNVs in RNF216 and postsynaptic membrane-related genes confer a risk of BD, contributing to a better understanding of the pathogenesis of BD.

Polygenic scores stratify neurodevelopmental copy number variant carrier cognitive outcomes in the UK Biobank

Rare copy-number variants associated with neurodevelopmental conditions (ND-CNVs) exhibit variable expressivity of clinical, physical, behavioural outcomes. Findings from clinically ascertained cohorts suggest this variability may be partly due to additional genetic variation. Here, we assessed the impact of polygenic scores (PGS) and rare variants on ND-CNV carrier fluid intelligence (FI) scores in the UK Biobank. Greater PGS for cognition (PSCog) and educational attainment (PSEA) is associated with increased FI scores in all ND-CNVs (n = 1317), 15q11.2 del. (n = 543), and 16p13.11 dup. carriers (n = 275). No association of rare variants associated with intellectual disability, autism, or putatively loss-of-function, brain-expressed genes was found. Positive predictive values in the first deciles of PScog and PSEA showed a two- to five-fold increase in the rate of low FI scores compared to baseline rates. These findings demonstrate that PGS can stratify ND-CNV carrier cognitive outcomes in a population-based cohort.

Hearing problems in humans and mouse models with rare copy number variants associated with schizophrenia: a scoping review protocol

Background Hearing loss is a risk factor for developing auditory hallucinations and other psychosis symptoms. To date, very little research has investigated hearing loss in individuals with a high genetic risk of developing schizophrenia and other types of psychosis. 13 copy number variant (CNV) loci are robustly associated with an increased risk of schizophrenia. Of these, microdeletions at 22q11.2 often lead to some hearing loss, and mouse models of this CNV display impaired auditory functioning. We hypothesise that hearing impairment is an understudied mechanism that contributes to the formation of psychosis symptoms in individuals at high genetic risk. This scoping review will explore whether the 13 schizophrenia-associated CNVs are related to hearing problems, including peripheral hearing loss and other auditory problems, in humans and related mouse models. Methods Our scoping review will follow guidelines provided by the Joanna Briggs Institute and the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews. A systematic search will be completed using PubMed (MEDLINE), Embase, PsychINFO, and Cochrane Library databases, as well as other sources to identify relevant grey literature. Search terms will include all commonly used synonyms for hearing loss and problems with auditory perception, and both human and mouse studies that describe relevant CNVs will be included. Search lists will be screened by two authors independently, according to eligibility criteria, and data will be extracted and summarised using a narrative approach, and meta-analysis methods will be used if possible. Conclusions To our knowledge, this will be the first scoping review to explore auditory functioning across all CNVs that confer high schizophrenia risk. Looking ahead, if hearing problems are a clinical feature in these groups (including humans and related mouse models), they may serve as useful genetic models for future mechanistic studies.

Progress towards understanding risk factor mechanisms in the development of autism spectrum disorders.

Autism spectrum disorders (ASD) are a heterogenous set of syndromes characterised by social impairment and cognitive symptoms. Currently, there are limited treatment options available to help people with ASD manage their symptoms. Understanding the biological mechanisms that result in ASD diagnosis and symptomatology is an essential step in developing new interventional strategies. Human genetic studies have identified common gene variants of small effect and rare risk genes and copy number variants (CNVs) that substantially increase the risk of developing ASD. Reverse translational studies using rodent models based on these genetic variants provide new insight into the biological basis of ASD. Here we review recent findings from three ASD associated CNV mouse models (16p11.2, 2p16.3 and 22q11.2 deletion) that show behavioural and cognitive phenotypes relevant to ASD. These models have identified disturbed excitation-inhibition neurotransmitter balance, evidenced by dysfunctional glutamate and GABA signalling, as a key aetiological mechanism. These models also provide emerging evidence for serotoninergic neurotransmitter system dysfunction, although more work is needed to clarify the nature of this. At the brain network level, prefrontal cortex (PFC) dysfunctional connectivity is also evident across these models, supporting disturbed PFC function as a key nexus in ASD aetiology. Overall, published data highlight the utility and valuable insight gained into ASD aetiology from preclinical CNV mouse models. These have identified key aetiological mechanisms that represent putative novel therapeutic targets for the treatment of ASD symptoms, making them useful translational models for future drug discovery, development and validation.

Unusual Maternal and Fetal Findings With Cell-Free DNA Screening.

With advances in prenatal cell-free DNA (cfDNA) technology, the information available with cfDNA continues to expand beyond the common fetal aneuploidies such as trisomies 21, 18, and 13. Due to the admixture of maternal and fetal/placental DNA, prenatal cfDNA remains a screening test with the possibility of false-positive and false-negative results. This review aims to summarize unusual incidental maternal and fetal genomic abnormalities detectable by cfDNA and to provide anticipatory guidance regarding management. Of 140 articles identified with keywords such as "incidental" and "discordant" cfDNA, 55 original research articles, review articles, case series, and societal guidelines were reviewed. Prenatal cfDNA may incidentally identify a spectrum of maternal genomic abnormalities such as malignancy, mosaicism, and copy number variants. When discordant with fetal diagnosis, these cases require additional investigation with maternal genetic testing and follow-up evaluation. Such incidental fetal/placental abnormalities may include rare autosomal trisomies, uniparental disomy, and triploidy. Further evaluation of fetal/placental abnormalities can be pursued with a combination of ultrasound and prenatal diagnosis with chorionic villous sampling and/or amniocentesis. Societal guidelines do not currently recommend cfDNA screening for rare autosomal trisomies, microdeletions, or copy number variants, and some experts suggest that sex chromosome screening should be opted in after counseling. Knowledge about possible incidental findings with prenatal cfDNA is needed to inform pretest and posttest counseling with appropriate follow-up evaluation. As cfDNA technology has advanced to include genome-wide findings, it is important for clinicians, genetic counselors, and societal guidelines to acknowledge the spectrum of possible results outside of the traditional and sex chromosome aneuploidies.

39P Search for rare copy number variants associated with hereditary breast cancer in Finnish case-control cohorts

39P Search for rare copy number variants associated with hereditary breast cancer in Finnish case-control cohorts

Whole genome sequencing study of identical twins discordant for psychosis

Monozygotic (MZ) twins are often thought to have identical genomes, but recent work has shown that early post-zygotic events can result in a spectrum of DNA variants that are different between MZ twins. Such variants may explain phenotypic discordance and contribute to disease etiology. Here we performed whole genome sequencing in 17 pairs of MZ twins discordant for a psychotic disorder (schizophrenia, schizoaffective disorder or bipolar disorder). We examined various classes of rare variants that are discordant within a twin pair. We identified four genes harboring rare, predicted deleterious missense variants that were private to an affected individual in the cohort. Variants in FOXN1 and FLOT2 would have been categorized as damaging from recent schizophrenia and bipolar exome sequencing studies. Additionally, we identified four rare genic copy number variants (CNVs) private to an affected sample, two of which overlapped genes that have shown evidence for association with schizophrenia or bipolar disorder. One such CNV was a 3q29 duplication previously implicated in autism and developmental delay. We have performed the largest MZ twin study for discordant psychotic phenotypes to date. These findings warrant further investigation using other analytical approaches.

CLINICAL AND COGNITIVE PHENOTYPING OF COPY NUMBER VARIANTS PATHOGENIC FOR NEURODEVELOPMENTAL DISORDERS FROM A MULTI-ANCESTRY BIOBANK.

Rare copy number variants (CNVs) are pathogenic for neurodevelopmental disorders (NDDs) and effect neurocognitive impairment. In aggregate, NDD CNVs may present in up to 2% of population cohorts with implications for neuropsychiatric disease risk and cognitive health. However, analyses of NDD CNVs in biobanks or population cohorts have been hindered by limited clinical or cognitive phenotypes, and a lack of ancestral diversity. In the current proof-of-concept study, NDD CNV carriers were recontacted from BioMe, a multi-ancestry biobank derived from the Mount Sinai healthcare system, to enable 'deep phenotyping' beyond electronic health record outcomes. From BioMe biobank, 892 adult participants were recontacted, including 335 harboring NDD CNVs, 217 with schizophrenia and 340 neurotypical controls as comparators. Clinical and cognitive assessments were administered to each recruited participant. Seventy-three participants completed study assessments (mean age=48.8 years; 66% female; 36% African, 26% European, 34% Hispanic), or 8% of the recontacted subset, including 30 NDD CNV carriers across 15 loci. Among NDD CNV carriers, assessments indicated 40% with mood and anxiety disorders, 30% with learning disorders, and 13% with a history of special education. NDD CNV carriers were significantly cognitively impaired compared to controls on digit span backwards (Beta=-1.76, FDR=0.04) and digit span sequencing (Beta=-2.01, FDR=0.04). Feasibility of "recall-by-genotype" from a multi-ancestry biobank was established for NDD CNV carriers, along with comparator groups. The current study corroborated past reports of NDD CNVs effects of cognitive impairment, while elucidating clinical phenotypes for recalled individuals. Future "recall-by-genotype" studies may further facilitate clinical characterization of disease-relevant genomic variants.

Association of copy number variation in X chromosome-linked PNPLA4 with heterotaxy and congenital heart disease.

Heterotaxy (HTX) is a thoracoabdominal organ anomaly syndrome and commonly accompanied by congenital heart disease (CHD). The aim of this study was to analyze rare copy number variations (CNVs) in a HTX/CHD cohort and to examine the potential mechanisms contributing to HTX/CHD. Chromosome microarray analysis was used to identify rare CNVs in a cohort of 120 unrelated HTX/CHD patients, and available samples from parents were used to confirm the inheritance pattern. Potential candidate genes in CNVs region were prioritized via the DECIPHER database, and PNPLA4 was identified as the leading candidate gene. To validate, we generated PNPLA4 -overexpressing human induced pluripotent stem cell lines as well as pnpla4 -overexpressing zebrafish model, followed by a series of transcriptomic, biochemical and cellular analyses. Seventeen rare CNVs were identified in 15 of the 120 HTX/CHD patients (12.5%). Xp22.31 duplication was one of the inherited CNVs identified in this HTX/CHD cohort, and PNPLA4 in the Xp22.31 was a candidate gene associated with HTX/CHD. PNPLA4 is expressed in the lateral plate mesoderm, which is known to be critical for left/right embryonic patterning as well as cardiomyocyte differentiation, and in the neural crest cell lineage. Through a series of in vivo and in vitro analyses at the molecular and cellular levels, we revealed that the biological function of PNPLA4 is importantly involved in the primary cilia formation and function via its regulation of energy metabolism and mitochondria-mediated ATP production. Our findings demonstrated a significant association between CNVs and HTX/CHD. Our data strongly suggested that an increased genetic dose of PNPLA4 due to Xp22.31 duplication is a disease-causing risk factor for HTX/CHD.

Challenges in Multi-Task Learning for fMRI-Based Diagnosis: Benefits for Psychiatric Conditions and CNVs Would Likely Require Thousands of Patients

Abstract There is a growing interest in using machine learning (ML) models to perform automatic diagnosis of psychiatric conditions; however, generalising the prediction of ML models to completely independent data can lead to sharp decrease in performance. Patients with different psychiatric diagnoses have traditionally been studied independently, yet there is a growing recognition of neuroimaging signatures shared across them as well as rare genetic copy number variants (CNVs). In this work, we assess the potential of multi-task learning (MTL) to improve accuracy by characterising multiple related conditions with a single model, making use of information shared across diagnostic categories and exposing the model to a larger and more diverse dataset. As a proof of concept, we first established the efficacy of MTL in a context where there is clearly information shared across tasks: the same target (age or sex) is predicted at different sites of data collection in a large fMRI dataset compiled from multiple studies. MTL generally led to substantial gains relative to independent prediction at each site. Performing scaling experiments on the UK Biobank, we observed that performance was highly dependent on sample size: for large sample sizes (N&amp;gt;6000) sex prediction was better using MTL across three sites (N=K per site) than prediction at a single site (N=3K), but for small samples (N&amp;lt;500) MTL was actually detrimental for age prediction. We then used established machine learning methods to benchmark the diagnostic accuracy of each of the 7 CNVs (N=19-103) and 4 psychiatric conditions (N=44-472) independently, replicating the accuracy previously reported in the literature on psychiatric conditions. We observed that MTL hurt performance when applied across the full set of diagnoses, and complementary analyses failed to identify pairs of conditions which would benefit from MTL. Taken together, our results show that if a successful multi-task diagnostic model of psychiatric conditions were to be developed with resting-state fMRI, it would likely require datasets with thousands of patients across different diagnoses.

Identification of novel driver risk genes in CNV loci associated with neurodevelopmental disorders

Copy number variants (CNVs) are genome-wide structural variations involving the duplication or deletion of large nucleotide sequences. While these types of variations can be commonly found in humans, large and rare CNVs are known to contribute to the development of various neurodevelopmental disorders (NDDs), including autism spectrum disorder (ASD). Nevertheless, given that these NDD-risk CNVs cover broad regions of the genome, it is particularly challenging to pinpoint the critical gene(s) responsible for the manifestation of the phenotype. In this study, we performed a meta-analysis of CNV data from 11,614 patients with NDDs and 4,031 controls from SFARI database to identify 41 NDD-risk CNV loci, including 24 novel regions. We also found evidence for dosage-sensitive genes within these regions being significantly enriched for known NDD-risk genes and pathways. In addition, a significant proportion of these genes was found to i) converge in protein-protein interaction networks; ii) be among most expressed genes in the brain across all developmental stages; and iii) be hit by deletions that are significantly over-transmitted to individuals with ASD within multiplex ASD families from the iHART cohort. Finally, we conducted a burden analysis using 4,281 NDD cases from Decipher and iHART cohorts, and 2,504 neurotypical controls from 1,000 Genomes and iHART, that resulted in the validation of the association of 162 dosage sensitive genes driving risk for NDDs, including 22 novel NDD-risk genes. Importantly, most NDD-risk CNV loci entail multiple NDD-risk genes in agreement with a polygenic model associated with the majority of NDD cases.

The Impact of Rare Copy Number Variants on Real-World Functional Outcomes in Individuals With Psychosis

The Impact of Rare Copy Number Variants on Real-World Functional Outcomes in Individuals With Psychosis

The Role of Rare Copy Number Variants in the Functional Outcomes of Individuals With Neurodevelopmental Conditions

The Role of Rare Copy Number Variants in the Functional Outcomes of Individuals With Neurodevelopmental Conditions

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 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. 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 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. 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.