Three generation families: Analysis of de novo variants in autism.

De novo variants (DNVs) analysis has proven to be a powerful approach to gene discovery in Autism Spectrum Disorder (ASD), which has not yet been shown in a Brazilian ASD cohort. The relevance of inherited rare variants has also been suggested, particularly in oligogenic models. We hypothesized that three-generation analyses of DNVs could provide new insights into the relevance of de novo and inherited variants across generations. To accomplish this goal, we performed whole-exome sequencing of 33 septet families composed of probands, parents, and grandparents (n = 231 individuals) and compared DNV rates (DNVr) between generations and those from two control cohorts. The DNVr in the probands (DNVr = 1.16) was marginally higher than in parents (DNVr = 0.60; p = 0.054), and in controls (DNVr = 0.68; p = 0.035, congenital heart disorder and DNVr = 0.70; p = 0.047, unaffected ASD siblings from Simons Simplex Collection). Moreover, most of the DNVs were found to have paternal origin in both generations (84.6%). Finally, we observed that 40% (6/15) of the DNVs in parents transmitted for probands are in ASD or ASD candidate genes, representing recently emerged risk variants to ASD in their families and suggest ZNF536, MSL2 and HDAC9 as ASD candidate genes. We did not observe an enrichment of risk variants nor sex bias of transmitted variants in the three generations, that can be due to sample size. These results further reinforce the relevance of de novo variants in ASD.

SCIP: software for efficient clinical interpretation of copy number variants detected by whole-genome sequencing.

Copy number variants (CNVs) represent major etiologic factors in rare genetic diseases. Current clinical CNV interpretation workflows require extensive back-and-forth with multiple tools and databases. This increases complexity and time burden, potentially resulting in missed genetic diagnoses. We present the Suite for CNV Interpretation and Prioritization (SCIP), a software package for the clinical interpretation of CNVs detected by whole-genome sequencing (WGS). The SCIP Visualization Module near-instantaneously displays all information necessary for CNV interpretation (variant quality, population frequency, inheritance pattern, and clinical relevance) on a single page-supported by modules providing variant filtration and prioritization. SCIP was comprehensively evaluated using WGS data from 1027 families with congenital cardiac disease and/or autism spectrum disorder, containing 187 pathogenic or likely pathogenic (P/LP) CNVs identified in previous curations. SCIP was efficient in filtration and prioritization: a median of just two CNVs per case were selected for review, yet it captured all P/LP findings (92.5% of which ranked 1st). SCIP was also able to identify one pathogenic CNV previously missed. SCIP was benchmarked against AnnotSV and a spreadsheet-based manual workflow and performed superiorly than both. In conclusion, SCIP is a novel software package for efficient clinical CNV interpretation, substantially faster and more accurate than previous tools (available at https://github.com/qd29/SCIP , a video tutorial series is available at https://bit.ly/SCIPVideos ).

Genomic architecture of autism from comprehensive whole-genome sequence annotation.

Fully understanding autism spectrum disorder (ASD) genetics requires whole-genome sequencing (WGS). We present the latest release of the Autism Speaks MSSNG resource, which includes WGS data from 5,100 individuals with ASD and 6,212 non-ASD parents and siblings (total n = 11,312). Examining a wide variety of genetic variants in MSSNG and the Simons Simplex Collection (SSC; n = 9,205), we identified ASD-associated rare variants in 718/5,100 individuals with ASD from MSSNG (14.1%) and 350/2,419 from SSC (14.5%). Considering genomic architecture, 52% were nuclear sequence-level variants, 46% were nuclear structural variants (including copy-number variants, inversions, large insertions, uniparental isodisomies, and tandem repeat expansions), and 2% were mitochondrial variants. Our study provides a guidebook for exploring genotype-phenotype correlations in families who carry ASD-associated rare variants and serves as an entry point to the expanded studies required to dissect the etiology in the ∼85% of the ASD population that remain idiopathic.

Genome-wide rare variant score associates with morphological subtypes of autism spectrum disorder.

Defining different genetic subtypes of autism spectrum disorder (ASD) can enable the prediction of developmental outcomes. Based on minor physical and major congenital anomalies, we categorize 325 Canadian children with ASD into dysmorphic and nondysmorphic subgroups. We develop a method for calculating a patient-level, genome-wide rare variant score (GRVS) from whole-genome sequencing (WGS) data. GRVS is a sum of the number of variants in morphology-associated coding and non-coding regions, weighted by their effect sizes. Probands with dysmorphic ASD have a significantly higher GRVS compared to those with nondysmorphic ASD (P = 0.03). Using the polygenic transmission disequilibrium test, we observe an over-transmission of ASD-associated common variants in nondysmorphic ASD probands (P = 2.9 × 10-3). These findings replicate using WGS data from 442 ASD probands with accompanying morphology data from the Simons Simplex Collection. Our results provide support for an alternative genomic classification of ASD subgroups using morphology data, which may inform intervention protocols.

Meta-Analyses Support Previous and Novel Autism Candidate Genes: Outcomes of an Unexplored Brazilian Cohort.

Large genomic databases of neurodevelopmental disorders (NDD) are helpful resources of genomic variations in complex and heterogeneous conditions, as Autism Spectrum Disorder (ASD). We evaluated the role of rare copy number variations (CNVs) and exonic de novo variants, in a molecularly unexplored Brazilian cohort of 30 ASD trios (n = 90), by performing a meta-analysis of our findings in more than 20,000 patients from NDD cohorts. We identified three pathogenic CNVs: two duplications on 1q21 and 17p13, and one deletion on 4q35. CNVs meta-analysis (n = 8,688 cases and n = 3,591 controls) confirmed 1q21 relevance by identifying duplications in other 16 ASD patients. Exome analysis led the identification of seven de novo variants in ASD genes (SFARI list): three loss-of-function pathogenic variants in CUL3, CACNA1H, and SHANK3; one missense pathogenic variant in KCNB1; and three deleterious missense variants in ATP10A, ANKS1B, and DOCK1. From the remaining 12 de novo variants in non-previous ASD genes, we prioritized PRPF8 and RBM14. Meta-analysis (n = 13,754 probands; n = 2,299 controls) identified six and two additional patients with validated de novo variants in PRPF8 and RBM14, respectively. By comparing the de novo variants with a previously established mutational rate model, PRPF8 showed nominal significance before multiple test correction (P = 0.039, P-value adjusted = 0.079, binomial test), suggesting its relevance to ASD. Approximately 60% of our patients presented comorbidities, and the diagnostic yield was estimated in 23% (7/30: three pathogenic CNVs and four pathogenic de novo variants). Our uncharacterized Brazilian cohort with tetra-hybrid ethnic composition was a valuable resource to validate and identify possible novel candidate loci. Autism Res 2020, 13: 199-206. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: We believed that to study an unexplored autistic population, such as the Brazilian, could help to find novel genes for autism. In order to test this idea, with our limited budget, we compared candidate genes obtained from genomic analyses of 30 children and their parents, with those of more than 20,000 individuals from international studies. Happily, we identified a genetic cause in 23% of our patients and suggest a possible novel candidate gene for autism (PRPF8).

A large data resource of genomic copy number variation across neurodevelopmental disorders.

Copy number variations (CNVs) are implicated across many neurodevelopmental disorders (NDDs) and contribute to their shared genetic etiology. Multiple studies have attempted to identify shared etiology among NDDs, but this is the first genome-wide CNV analysis across autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), schizophrenia (SCZ), and obsessive-compulsive disorder (OCD) at once. Using microarray (Affymetrix CytoScan HD), we genotyped 2,691 subjects diagnosed with an NDD (204 SCZ, 1,838 ASD, 427 ADHD and 222 OCD) and 1,769 family members, mainly parents. We identified rare CNVs, defined as those found in <0.1% of 10,851 population control samples. We found clinically relevant CNVs (broadly defined) in 284 (10.5%) of total subjects, including 22 (10.8%) among subjects with SCZ, 209 (11.4%) with ASD, 40 (9.4%) with ADHD, and 13 (5.6%) with OCD. Among all NDD subjects, we identified 17 (0.63%) with aneuploidies and 115 (4.3%) with known genomic disorder variants. We searched further for genes impacted by different CNVs in multiple disorders. Examples of NDD-associated genes linked across more than one disorder (listed in order of occurrence frequency) are NRXN1, SEH1L, LDLRAD4, GNAL, GNG13, MKRN1, DCTN2, KNDC1, PCMTD2, KIF5A, SYNM, and long non-coding RNAs: AK127244 and PTCHD1-AS. We demonstrated that CNVs impacting the same genes could potentially contribute to the etiology of multiple NDDs. The CNVs identified will serve as a useful resource for both research and diagnostic laboratories for prioritization of variants.

Expanding the neurodevelopmental phenotypes of individuals with de novo KMT2A variants.

De novo loss-of-function (LoF) variants in the KMT2A gene are associated with Wiedemann-Steiner Syndrome (WSS). Recently, de novo KMT2A variants have been identified in sequencing studies of cohorts of individuals with neurodevelopmental disorders (NDDs). However, most of these studies lack the detailed clinical information required to determine whether those individuals have isolated NDDs or WSS (i.e. syndromic NDDs). We performed thorough clinical and neurodevelopmental phenotyping on six individuals with de novo KMT2A variants. From these data, we found that all six patients met clinical criteria for WSS and we further define the neurodevelopmental phenotypes associated with KMT2A variants and WSS. In particular, we identified a subtype of Autism Spectrum Disorder (ASD) in five individuals, characterized by marked rigid, repetitive and inflexible behaviours, emotional dysregulation, externalizing behaviours, but relative social motivation. To further explore the clinical spectrum associated with KMT2A variants, we also conducted a meta-analysis of individuals with KMT2A variants reported in the published literature. We found that de novo LoF or missense variants in KMT2A were significantly more prevalent than predicted by a previously established statistical model of de novo mutation rate for KMT2A. Our genotype-phenotype findings better define the clinical spectrum associated with KMT2A variants and suggest that individuals with de novo LoF and missense variants likely have a clinically unrecognized diagnosis of WSS, rather than isolated NDD or ASD alone. This highlights the importance of a clinical genetic and neurodevelopmental assessment for individuals with such variants in KMT2A.

Genomic Context Analysis of de Novo STXBP1 Mutations Identifies Evidence of Splice Site DNA-Motif Associated Hotspots.

Mutations within STXBP1 have been associated with a range of neurodevelopmental disorders implicating the pleotropic impact of this gene. Although the frequency of de novo mutations within STXBP1 for selective cohorts with early onset epileptic encephalopathy is more than 1%, there is no evidence for a hotspot within the gene. In this study, we analyzed the genomic context of de novo STXBP1 mutations to examine whether certain motifs indicated a greater risk of mutation. Through a comprehensive context analysis of 136 de novo/rare mutation (SNV/Indels) sites in this gene, strikingly 26.92% of all SNV mutations occurred within 5bp upstream or downstream of a 'GTA' motif (P < 0.0005). This implies a genomic context modulated mutagenesis. Moreover, 51.85% (14 out of 27) of the 'GTA' mutations are splicing compared to 14.70% (20 out of 136) of all reported mutations within STXBP1 We also noted that 11 of these 14 'GTA' associated mutations are de novo in origin. Our analysis provides strong evidence of DNA motif modulated mutagenesis for STXBP1 de novo splicing mutations.

A Comprehensive Workflow for Read Depth-Based Identification of Copy-Number Variation from Whole-Genome Sequence Data.

A remaining hurdle to whole-genome sequencing (WGS) becoming a first-tier genetic test has been accurate detection of copy-number variations (CNVs). Here, we used several datasets to empirically develop a detailed workflow for identifying germline CNVs >1 kb from short-read WGS data using read depth-based algorithms. Our workflow is comprehensive in that it addresses all stages of the CNV-detection process, including DNA library preparation, sequencing, quality control, reference mapping, and computational CNV identification. We used our workflow to detect rare, genic CNVs in individuals with autism spectrum disorder (ASD), and 120/120 such CNVs tested using orthogonal methods were successfully confirmed. We also identified 71 putative genic de novo CNVs in this cohort, which had a confirmation rate of 70%; the remainder were incorrectly identified as de novo due to false positives in the proband (7%) or parental false negatives (23%). In individuals with an ASD diagnosis in which both microarray and WGS experiments were performed, our workflow detected all clinically relevant CNVs identified by microarrays, as well as additional potentially pathogenic CNVs < 20 kb. Thus, CNVs of clinical relevance can be discovered from WGS with a detection rate exceeding microarrays, positioning WGS as a single assay for genetic variation detection.

Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder.

We are performing whole-genome sequencing of families with autism spectrum disorder (ASD) to build a resource (MSSNG) for subcategorizing the phenotypes and underlying genetic factors involved. Here we report sequencing of 5,205 samples from families with ASD, accompanied by clinical information, creating a database accessible on a cloud platform and through a controlled-access internet portal. We found an average of 73.8 de novo single nucleotide variants and 12.6 de novo insertions and deletions or copy number variations per ASD subject. We identified 18 new candidate ASD-risk genes and found that participants bearing mutations in susceptibility genes had significantly lower adaptive ability (P = 6 × 10-4). In 294 of 2,620 (11.2%) of ASD cases, a molecular basis could be determined and 7.2% of these carried copy number variations and/or chromosomal abnormalities, emphasizing the importance of detecting all forms of genetic variation as diagnostic and therapeutic targets in ASD.