npj Genomic Medicine

Previous genetic studies in ASD identified hundreds of high-confidence ASD genes enriched with likely deleterious protein-coding de novo mutations (DNMs). Multiple studies also demonstrated that DNMs in the non-coding genome can contribute to ASD risk. However, identification of individual risk genes enriched with noncoding DNMs has remained largely unexplored. We analyzed two datasets with over 5000 ASD families to assess the contribution of noncoding DNMs. We used two methods to assess statistical significance for noncoding DNMs: a point-based test that analyzes sites that are likely functional, and a segment-based test that analyzes 1kb genomic segments with segment-specific background mutation rates. We found that coding and noncoding DNMs in SCA2A are associated with ASD risk. Further application of these approaches on large-scale whole genome sequencing data will aid in identifying additional candidates ASD risk genes.

Autism Spectrum Disorder (ASD) exhibits an [~]4:1 male-to-female sex bias and is characterized by early-onset impairment of social/communication skills, restricted interests, and stereotyped behaviors. Disruption of the Xp22.11 locus has been associated with ASD in males. This locus includes the three-exon PTCHD1 gene, an adjacent multi-isoform long noncoding RNA (lncRNA) named PTCHD1-AS (spanning [~]1Mb), and a poorly characterized single-exon RNA helicase named DDX53 that is intronic to PTCHD1-AS. While the relationship between PTCHD1/PTCHD1-AS and ASD is being studied, the role of DDX53 has not been examined, in part because there is no apparent functional murine orthologue. Through clinical testing, here, we identified 6 males and 1 female with ASD from 6 unrelated families carrying rare, predicted-damaging or loss-of-function variants in DDX53. Then, we examined databases, including the Autism Speaks MSSNG and Simons Foundation Autism Research Initiative, as well as population controls. We identified 24 additional individuals with ASD harboring rare, damaging DDX53 variations, including the same variants detected in two families from the original clinical analysis. In this extended cohort of 31 participants with ASD (28 male, 3 female), we identified 25 mostly maternally-inherited variations in DDX53, including 18 missense changes, 2 truncating variants, 2 in-frame variants, 2 deletions in the 3 UTR and 1 copy number deletion. Our findings in humans support a direct link between DDX53 and ASD, which will be important in clinical genetic testing. These same autism-related findings, coupled with the observation that a functional orthologous gene is not found in mouse, may also influence the design and interpretation of murine-modelling of ASD.

Background and aimsInflammatory bowel disease (IBD) is usually comorbid with psychological disorders. Emerging observational studies have indicated the association between autism spectrum disorder (ASD) and IBD, including Crohns disease (CD) and ulcerative colitis (UC), whereas the causality remains unknown. Our study aimed to explore the causal association between IBD and ASD using bidirectional two-sample Mendelian randomization (MR) design. MethodsSummary-level data from large-scale genome-wide association (GWAS) studies of IBD (International Inflammatory Bowel Disease Genetics Consortium, Ncases=25,042, Ncontrols=34,915) and ASD (Integrative Psychiatric Research-Psychiatric Genomics Consortium, Ncases=18,382, Ncontrols=27,969) were retrieved. Gene variants for IBD and ASD were selected as instrumental variables. MR analyses were performed mainly including the inverse-variance-weighted method with a series of sensitivity tests. ResultsGenetic predisposition to IBD was associated with a high risk of ASD (odds ratio [OR] = 1.03, 95% confidence interval [CI] = 1.01-1.06, P = 0.01; OR [95% CI]: 1.03 [1.01-1.05], P = 0.02 for CD; OR [95% CI]: 1.03 [1.01-1.07], P = 0.04 for UC). In contrast, no causal association was found for the genetic liability to ASD on IBD. ConclusionsOur findings reveal that genetically predicted IBD is causally related to ASD, whereas the causal association of ASD on IBD is not supported. Our study highlights the early screening and surveillance of psychological symptoms, as well as sustaining support for patients with IBD. Further investigations on age-specific groups are warranted.

Compound heterozygous events involving a chromosome deletion and on the remaining allele a functional DNA sequence-level variant can underpin a range of medical conditions. Most large-scale genetic studies do not include a systematic analysis of such compound heterozygous deletion (DelCH) events. We developed three frameworks: i) traditional burden analysis; ii) deletion-matched burden analysis; and iii) transmission disequilibrium test (TDT), to examine the possible contribution of DelCH to clinical presentations, and report results of their implementation in 9,766 families of autistic individuals. Across the three strategies, we observed enrichment of rare DelCH events in autistic individuals at a nominal significance level for individual tests. Collectively, six genes; CFHR4, HSDL1, MYO15A, NEFH, and three olfactory receptor genes; OR1A2, OR4P2, were affected by DelCH events in at least two unrelated autistic individuals (and not in unaffected family members), while the reverse analyses identified no genes (p<2.2 x 10-16). Gene set enrichment analysis of the extended network of candidate genes showing a remarkable convergence to processes related to neurogenesis. Our findings suggest a modest role for DelCH events in ASD. The strategies described here are available via a GitHub repository, allowing the research community to examine the role of DelCH in other genome sequencing cohorts.

Low-frequency variants (LFVs), defined by minor allele frequencies (MAF) of 1-5%, occupy the gap between common and rare variants in both frequency and effect size. The conventional genome-wide association study (GWAS) significance threshold (5x10-) is overly conservative for LFVs, which account for more than 25% of variants in GWAS. This limitation may obscure meaningful associations in highly heritable yet genetically complex disorders such as autism spectrum disorder (ASD). We hypothesize that the scarcity of significant LFVs in ASD GWAS reflects statistical constraints rather than a true lack of association. To address this, we derived a MAF-specific genome-wide significance threshold using linkage disequilibrium-informed simulations applied to ASD GWAS summary statistics, identifying 2.03x10- as optimal. Applying this threshold revealed three novel LFVs mapping to zinc finger proteins (ZNF420, ZNF781) and known ASD-related genes (KMT2E, PRKDC, MCM4). Enrichment analyses suggested their function in nervous system development and gene regulation. Our findings highlight the contribution of LFVs to ASD risk and underscore the importance of frequency-aware association strategies.

ObjectivePublished observational studies have revealed the connection between inflammatory bowel disease (IBD) and neurodegenerative disorders, whereas the causality remains largely unclear. Our study aims to assess the causality and identify the shared genetic architecture between IBD and neurodegenerative disorders. DesignA series of two-sample Mendelian randomization analyses were performed to assess the causality between IBD and neurodegenerative disorders (amyotrophic lateral sclerosis [ALS], Alzheimers disease [AD], Parkinsons disease [PD], and multiple sclerosis [MS]). Shared genetic loci and functional interpretation were further investigated for IBD and ALS. The transcriptomic expressions of shared genes were evaluated in patients with IBD and ALS. ResultsGenetic predisposition to IBD is associated with lower odds of ALS (odds ratio [OR] 0.96, 95% confidence interval [CI] 0.94 to 0.99). In contrast, IBD is not genetically associated with an increased risk of AD, PD, or MS. Four shared genetic loci (rs6571361, rs10136727, rs7154847, and rs447853) were derived, and SCFD1, G2E3, HEATR5A were further identified as novel risk genes with enriched function related to membrane trafficking. G2E3 was differentially expressed and significantly correlated with SCFD1 in patients with IBD or ALS. ConclusionOur study reveals the casually protective role of IBD on ALS, and does not support the causality of IBD on AD, PD, or MS. Our findings indicate possible shared genetic architecture and pathways between IBD and ALS. The altered expressions of shared risk genes might contribute to the susceptibility to IBD and the protective effects for ALS. These results provide insights into the pathogenesis and therapeutics of IBD and neurodegenerative disorders. What is already known on this topicO_LIEmerging evidence has supported the communication between the gastrointestinal tract and central nervous system (the "gut-brain axis"). C_LIO_LIPublished epidemiological studies have revealed the association between inflammatory bowel disease (IBD) and neurodegenerative disorders. C_LIO_LIThe causality remains largely unclear. C_LI What this study addsO_LIGenetic liability to IBD is associated with a decreased risk of amyotrophic lateral sclerosis (ALS), whereas the susceptibility to IBD does not lead to Alzheimers disease, Parkinsons disease, or multiple sclerosis. C_LIO_LIShared genetic loci (rs6571361, rs10136727, rs7154847, and rs447853) and risk genes (SCFD1, G2E3, HEATR5A) are identified in IBD and ALS. C_LIO_LITranscriptomic profiles in patients with IBD or ALS indicate that G2E3 is differentially expressed and significantly correlated with SCFD1. C_LI How this study might affect research, practice or policyO_LIThe findings provide insights into the pathogenesis and therapeutics of IBD and neurodegenerative disorders. C_LIO_LILower expression of G2E3 in IBD might serve as a protective factor to ALS. C_LIO_LIUnsubstantiated concerns among patients with IBD could be alleviated. C_LI

Pathogenic germline variants in the TP53 gene cause Li-Fraumeni syndrome (LFS), a highly penetrant cancer predisposition disorder. Most of these variants arise from single-nucleotide variations (SNVs) in TP53 exons, causing missense mutations. However, some of these SNVs may also alter mRNA splicing, defining spliceogenic single nucleotide variants (SE-SNVs) of uncertain clinical significance. We reassessed previously classified TP53 missense variants for spliceogenic effects using SpliceAI predictions, in vitro minigene assays, and transcriptomic data from TCGA. Genotype-phenotype correlations were evaluated using clinical data from carriers of TP53 germline variants across multiple databases and registries. Among 58 identified SE-SNVs, 40 were missense and 18 synonymous. Experimental validation showed that most induce aberrant splicing events, frequently via cryptic splice site activation, leading to frameshift and premature stop codons. Several missense variants previously classified as having mild or low pathogenicity were found instead to have strong spliceogenic effects and were associated with early-onset cancers typical of LFS, suggesting that splicing alterations may override their protein-coding impact. The frequent SNV c.375G>A leading to the synonymous variant p.T125= shows intermediate severity, likely due to partial retention of normal splicing activity. Our study highlights the underestimated pathogenic potential of SE-SNVs affecting the TP53 gene. These findings underscore the importance of integrating splicing predictions, functional assays, and transcript-level analyses into TP53 variant interpretation to improve risk stratification in LFS.

BackgroundRNA-sequencing is increasingly being used as a complementary tool to DNA sequencing in diagnostics where DNA analysis has been uninformative. RNA-sequencing allows us to identify alternative splicing and aberrant gene expression allowing for improved interpretation of variants of unknown significance (VUS). Additionally, RNA-sequencing provides the opportunity not only to look at the splicing effects of known VUSs but also to scan the transcriptome for abnormal splicing events and expression abnormalities in other relevant genes that may be the cause of a patients phenotype. MethodsUsing RNA from patient blood, we have systematically assessed transcriptomic profiles of 87 patients with suspected Mendelian disorders, 38% of which did not have a candidate sequence variant. Cases with VUSs and known events were assessed first followed by assessment of cases with no VUS. Each VUS was visually inspected using the Integrative Genomics Viewer (IGV) to search for splicing abnormalities. Once aberrant splicing was identified in cases with VUS, multiple open-source alternative splicing tools (MAJIQ, rMATS-turbo, FRASER2 and LeafCutterMD) were used to investigate if they would identify what was observed in IGV. Expression outliers were detected using OUTRIDER. To find diagnoses in cases without a VUS or gene of interest, two separate strategies were used. The first was a genotype to phenotype approach using variant calls obtained from the RNA-sequencing and overlapping those calls with results from splicing tools. The second strategy involved using phenotype information available to filter results from splicing tools. ResultsUsing RNA-sequencing only, we were able to assess 71% of VUSs and detect aberrant splicing in 14/48 patients with a VUS. Furthermore, we identified four new diagnoses by detecting novel aberrant splicing events in patients with no candidate sequence variants from prior genomic DNA testing (n=33) or those in which the candidate VUS did not affect splicing (n=23) and identified one additional diagnosis through detection of skewed X-inactivation. ConclusionWe demonstrate the identification of novel diagnoses using an RNA-sequencing first approach in patients without candidate VUSs. Furthermore, we demonstrate the utility of blood-based RNA analysis in improving diagnostic yields and highlight optimal approaches for such analysis.

A prominent endophenotype in Autism Spectrum Disorder (ASD) is synaptic plasticity dysfunction, yet the molecular mechanism remains elusive. As a prototype, we investigated the postsynaptic signal transduction network in glutamatergic neurons and integrated transcriptomics to unveil the malfunction of translation control. We devised an innovative and highly dependable pipeline to transform our acquired signal transduction network into a mRNA Signaling-Regulatory Network (mSiReN) and analyze it at the RNA level. We employed Cell-Specific Network Inference via Integer Value Programming and Causal Reasoning (CS-NIVaCaR) to identify core modules and Cell-Specific Probabilistic Contextualization for mRNA Regulatory Networks (CS-ProComReN) to quantitatively reveal activated sub-pathways involving MAPK1, MKNK1, RPS6KA5, and MTOR across different cell types in ASD. The results indicate that specific pivotal molecules, such as EIF4EBP1 and EIF4E, lacking Differential Expression (DE) characteristics and responsible for protein translation with long-term potentiation (LTP) or long-term depression (LTD), are dysregulated. We further uncovered distinct activation patterns causally linked to the EIF4EBP1-EIF4E module in excitatory and inhibitory neurons. Importantly, our work has introduced a methodology for leveraging extensive transcriptomics data to parse the signal transduction network, transforming it into mSiReN, and mapping it back to the protein level. These algorithms can serve as potent tools in systems biology to analyze other omics and regulatory networks. Furthermore, the biomarkers within the activated sub-pathways, revealed by identifying convergent dysregulation, illuminate potential diagnostic and prognostic factors in ASD.

PurposeInconclusive interpretation of pathogenicity of variants is a common problem in Mendelian disease diagnostics. We hypothesized that some variants of unknown significance (VUS) may lead to aberrant pre-mRNA splicing. To address this we have developed a high throughput splicing assay (HTSA) than can be utilized to test the effects of 1000s of variants on exon recognition. Methods2296 reference, control and variant sequences from 380 exons of 89 genes associated with inherited retinal degenerations (IRDs) were cloned as a pool into a split-GFP HTSA construct and expressed in landing pad RCA7 HEK293T cells. Exon inclusion led to disruption of GFP and exon skipping led to GFP reconstitution, enabling to separate GFP+ve and GFP-ve cells by fluorescence activated cell sorting. After deep sequencing-based quantification of studied sequences in each cell pool, exon inclusion index (EII) was determined, where EII = GFP-ve oligo count/total oligo count. ResultsHTSA showed high reproducibility when compared between different biological replicates (tetrachoric correlation coefficient r2 = 0.83). Reference exon sequences showed a high level of exon recognition (median EII = 0.88) which was significantly reduced by mutations to the essential splice sites (donor site variants: median EII=0.06; acceptor site variants: median EII=0.48). Of the 748 studied VUSs, 47 variants led to decreased exon inclusion ({Delta}EII [&le;] -0.3) with 11 variants showing a strong effect ({Delta}EII [&le;] -0,6). Using the HTSA data we were able to provide a likely genetic diagnosis to five IRD cases. ConclusionHTSA offers a robust method to study the effects of VUSs on exon recognition allowing to provide new diagnoses for patients with Mendelian disorders.

Fully understanding the genetic factors involved in Autism Spectrum Disorder (ASD) requires whole-genome sequencing (WGS), which theoretically allows the detection of all types of genetic variants. With the aim of generating an unprecedented resource for resolving the genomic architecture underlying ASD, we analyzed genome sequences and phenotypic data from 5,100 individuals with ASD and 6,212 additional parents and siblings (total n=11,312) in the Autism Speaks MSSNG Project, as well as additional individuals from other WGS cohorts. WGS data and autism phenotyping were based on high-quality short-read sequencing (>30x coverage) and clinically accepted diagnostic measures for ASD, respectively. For initial discovery of ASD-associated genes, we used exonic sequence-level variants from MSSNG as well as whole-exome sequencing-based ASD data from SPARK and the Autism Sequencing Consortium (>18,000 trios plus additional cases and controls), identifying 135 ASD-associated protein-coding genes with false discovery rate <10%. Combined with ASD-associated genes curated from the literature, this list was used to guide the interpretation of all other variant types in WGS data from MSSNG and the Simons Simplex Collection (SSC; n=9,205). We identified ASD-associated rare variants in 789/5,100 individuals with ASD from MSSNG (15%) and 421/2,419 from SSC (17%). Considering the genomic architecture, 57% of ASD-associated rare variants were nuclear sequence-level variants, 41% were nuclear structural variants (SVs) (mainly copy number variants, but also including inversions, large insertions, uniparental isodisomies, and tandem repeat expansions), and 2% were mitochondrial variants. Several of the ASD-associated SVs would have been difficult to detect without WGS, including an inversion disrupting SCN2A and a nuclear mitochondrial insertion impacting SYNGAP1. Polygenic risk scores did not differ between children with ASD in multiplex families versus simplex, and rare, damaging recessive events were significantly depleted in multiplex families, collectively suggesting that rare, dominant variation plays a predominant role in multiplex ASD. Our study provides a guidebook for exploring genotype-phenotype correlations in the 15-20% of ASD families who carry ASD-associated rare variants, as well as an entry point to the larger and more diverse studies that will be required to dissect the etiology in the >80% of the ASD population that remains idiopathic. All data resulting from this study are available to the medical genomics research community in an open but protected manner.

The past decade has seen remarkable progress in identifying genes that, when impacted by deleterious coding variation, confer high risk for autism spectrum disorder (ASD), intellectual disability, and other developmental disorders. However, most underlying gene discovery efforts have focused on individuals of European ancestry, limiting insights into genetic risks across diverse populations. To help address this, the Genomics of Autism in Latin American Ancestries Consortium (GALA) was formed, presenting here the largest sequencing study of ASD in Latin American individuals (n>15,000). We identified 35 genome-wide significant (FDR < 0.05) ASD risk genes, with substantial overlap with findings from European cohorts, and highly constrained genes showing consistent signal across populations. The results provide support for emerging (e.g., MARK2, YWHAG, PACS1, RERE, SPEN, GSE1, GLS, TNPO3, ANKRD17) and established ASD genes, and for the utility of genetic testing approaches for deleterious variants in diverse populations, while also demonstrating the ongoing need for more inclusive genetic research and testing. We conclude that the biology of ASD is universal and not impacted to any detectable degree by ancestry. Autism Sequencing Consortium (ASC)Branko Aleksic, Mykyta Artomov, Mafalda Barbosa, Elisa Benetti, Catalina Betancur, Monica Biscaldi-Schafer, Anders D. Borglum, Harrison Brand, Alfredo Brusco, Joseph D. Buxbaum, Gabriele Campos, Simona Cardaropoli, Diana Carli, Angel Carracedo, Marcus C. Y. Chan, Andreas G. Chiocchetti, Brian H. Y. Chung, Brett Collins, Ryan L. Collins, Edwin H. Cook, Hilary Coon, Claudia I. S. Costa, Michael L. Cuccaro, David J. Cutler, Mark J. Daly, Silvia De Rubeis, Bernie Devlin, Ryan N. Doan, Enrico Domenici, Shan Dong, Chiara Fallerini, Magdalena Fernandez, Montserrat Fernandez-Prieto, Giovanni Battista Ferrero, Eugenio Ferro, Jennifer Foss Feig, Christine M. Freitag, Jack M. Fu, Liliana Galeano, J. Jay Gargus, Sherif Gerges, Elisa Giorgio, Ana Cristina Girardi, Stephen Guter, Emily Hansen-Kiss, Erina Hara, Danielle Halpern, Gail E. Herman, Luis C. Hernandez, Irva Hertz-Picciotto, David M. Hougaard, Christina M. Hultman, Suma Jacob, Miia Kaartinen, Lambertus Klei, Alexander Kolevzon, Itaru Kushima, Maria C. Lattig, So Lun Lee, Terho Lehtimaki, Lindsay Liang, Carla Lintas, Alicia Ljungdahl, Andrea del Pilar Lopez, Caterina Lo Rizzo, Yunin Ludena, Patricia Maciel, Behrang Mahjani, Nell Maltman, Marianna Manara, Dara S. Manoach, Dalia Marquez, Gal Meiri, Idan Menashe, Judith Miller, Nancy Minshew, Matthew Mosconi, Marina Natividad Avila, Rachel Nguyen, Norio Ozaki, Aarno Palotie, Mara Parellada, Maria Rita Passos-Bueno, Lisa Pavinato, Katherine P. Pena, Minshi Peng, Margaret Pericak-Vance, Antonio M. Persico, Isaac N. Pessah, Thariana Pichardo, Kaija Puura, Abraham Reichenberg, Alessandra Renieri, Kathryn Roeder, Catherine Sancimino, Stephan J. Sanders, Sven Sandin, F. Kyle Satterstrom, Stephen W. Scherer, Sabine Schlitt, Rebecca J. Schmidt, Lauren Schmitt, Katja Schneider-Momm, Paige M. Siper, Laura Sloofman, Moyra Smith, Renee Soufer, Christine R. Stevens, P[a]l Suren, James S. Sutcliffe, John A. Sweeney, Michael E. Talkowski, Flora Tassone, Karoline Teufel, Elisabetta Trabetti, Slavica Trajkova, Maria del Pilar Trelles, Brie Wamsley, Jaqueline Y. T. Wang, Lauren A. Weiss, Mullin H. C. Yu, Ryan Yuen, Jessica Zweifach.

Background5 untranslated regions (5UTRs) are essential modulators of protein translation. Predicting the impact of 5UTR variants is challenging and typically not performed in routine diagnostics. Here, we present a combined approach of a comprehensive prioritization strategy and subsequent functional assays to evaluate 5UTR variation in two large cohorts of patients with inherited retinal diseases (IRDs). MethodsWe performed an isoform-level re-analysis of retinal RNA-seq data to identify the protein-coding transcripts of 378 IRD genes with highest expression in retina. We evaluated the coverage of these 5UTRs by different whole exome sequencing (WES) capture kits. The selected 5UTRs were analyzed in whole genome sequencing (WGS) and WES data from IRD sub-cohorts from the 100,000 Genomes Project (n = 2,417 WGS) and an in-house database (n = 1,682 WES), respectively. Identified variants were annotated for 5UTR-relevant features and classified into 7 distinct categories based on their predicted functional consequence. We developed a variant prioritization strategy by integrating population frequency, specific criteria for each category, and family and phenotypic data. A selection of candidate variants underwent functional validation using diverse experimental approaches. ResultsIsoform-level re-quantification of retinal gene expression revealed 76 IRD genes with a non-canonical retina-enriched isoform, of which 20 display a fully distinct 5UTR compared to that of their canonical isoform. Depending on the probe-design 3-20% of IRD genes have 5UTRs fully captured by WES. After analyzing these regions in both IRD cohorts we prioritized 11 (likely) pathogenic variants in 10 genes (ARL3, MERTK, NDP, NMNAT1, NPHP4, PAX6, PRPF31, PRPF4, RDH12, RD3), of which 8 were novel. Functional analyses further supported the pathogenicity of 2 variants. The MERTK:c.-125G>A variant, overlapping a transcriptional start site, was shown to significantly reduce both luciferase mRNA levels and activity. The RDH12:c.-123C>T variant was found in cis with the reported hypomorphic RDH12:c.701G>A (p.Arg234His) variant in 11 patients. This 5UTR variant, predicted to introduce an upstream open reading frame, was shown to result in reduced RDH12 protein but unaltered mRNA levels. ConclusionsThis study demonstrates the importance of 5UTR variants implicated in IRDs and provides a systematic approach for 5UTR annotation and validation that is applicable to other inherited diseases.

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

Genome wide association studies contributed to a better understanding of the etiology of inflammatory bowel disease (IBD). While over 240 genetic associations with IBD have since been identified, functional follow-up studies are still in their infancy with the overall pathogenesis of IBD remaining unsolved. E.g., a functional understanding of the genetic association between the human leukocyte antigen (HLA) region and ulcerative colitis (UC) - one subtypes of IBD - is still lacking. Here, we analyzed whether an autoimmune reaction involving the HLA class II proteins HLA-DQ and -DR, both being strongly associated with UC, could be a disease trigger or driver. To this end, genotype data derived from whole exome sequencing and genome-wide SNP array data of 863 German UC patients as well as 4,185 healthy controls were analyzed. Association analyses identified novel variants in the NOD2 and SNX20 genes to be linked with UC and confirmed known HLA allele associations. Employing the genetic data, we generated patient-specific self-immunopeptidomes and in silico predicted HLA-peptide binding. Peptidome-wide association analyses of peptide binding preferences in a set of candidate proteins yielded significant associations with 234 specific peptides. Interestingly, none of those peptides showed a differential presence in case and control samples. The disease-associated candidate peptides predicted to be presented by risk HLA proteins contained predominantly aromatic amino acids. In contrast, protective HLA proteins were predicted to bind peptides enriched in acidic amino acids. In summary, we present a proof-of-concept immunogenetic analysis that contributes to a better understanding of the HLA in UC.

Several studies have demonstrated the value of large-scale human exome and genome data analysis, to maximise gene discovery in rare diseases. Using this approach, we have analysed the exomes of 4,747 cases and 52,881 controls, to identify single genes and digenic interactions which confer a substantial risk of congenital heart disease (CHD). We identified both rare loss-of-function and missense coding variants in ten genes which reached genome-wide significance (Bonferroni adjusted P < 0.05) and an additional four genes with a significant association at a false discovery rate (FDR) threshold of 5%. We highlight distinct genetic contributions to syndromic and non-syndromic CHD at both single gene and digenic level, by independently analysing probands from these two groups. In addition, by integrative analysis of exome data with single-cell transcriptomics data from human embryonic hearts, we identified cardiac-specific cells as well as putative biological processes underlying the pathogenesis of CHD. In summary, our findings strengthen the association of known CHD genes, and have identified additional novel disease genes and digenic interactions contributing to the aetiology of CHD.

BackgroundAutism spectrum disorder (ASD) is a neurodevelopmental disorder that affects about 1 in 36 children in the United States, imposing enormous economic and socioemotional burden on families and communities. Genetic studies of ASD have identified de novo copy number variants (CNVs) and point mutations that contribute significantly to the genetic architecture, but the majority of these studies were conducted in populations unsuited for detecting autosomal recessive (AR) inheritance. However, several ASD studies in consanguineous populations point towards AR as an under-appreciated source of ASD variants. MethodsWe used whole exome sequencing to look for rare variants for ASD in 115 proband-mother-father trios from populations with high rates of consanguinity, namely Pakistan, Iran, and Saudi Arabia. Consanguinity was assessed through microarray genotyping. ResultsWe report 84 candidate disease-predisposing single nucleotide variants and indels, with 58% biallelic, 25% autosomal dominant/de novo, and the rest X-linked, in 39 trios. 52% of the variants were loss of function (LoF) or putative LoF (pLoF), and 47% nonsynonymous. We found an enrichment of biallelic variants, both in sixteen genes previously reported for AR ASD and/or intellectual disability (ID) and 32 previously unreported AR candidate genes (including DAGLA, ENPP6, FAXDC2, ILDR2, KSR2, PKD1L1, SCN10A, SHH, and SLC36A1). We also identified eight candidate biallelic exonic loss CNVs. ConclusionsThe significant enrichment for biallelic variants among individuals with high Froh coefficients, compared with low Froh, either in known or candidate AR genes, confirms that genetic architecture for ASD among consanguineous populations is different to non-consanguineous populations. Assessment of consanguinity may assist in the genetic diagnostic process for ASD.

Autism spectrum disorder (ASD) is a highly heritable and highly heterogeneous neuropsychiatric condition whose cause is still unknown because there are no recurrent genes found among diagnosed individuals. One of the most common functional properties of the many reported risk-genes for autism is "chromatin modification" but it is not known how this biological process relates to neurodevelopment and autism. We recently reported frequent, recurrent genomic structural variants (SVs) in two cohorts of individuals with autism that were identified using non-Mendelian inheritance (NMI) patterns in family trios. The genes harboring the SVs participate in neurodevelopment, glutamate signaling, and chromatin modification, confirming previous reports and providing greater detail for these processes in ASD. The majority of these ASD-associated SVs (ASD-SV) were found in non-coding regions of the genome and were enriched for expression quantitative trait loci (eQTL) suggesting that gene dysregulation results from these genomic disruptions rather than alteration of proteins. Here, we intersect the ASD-SV from our earlier work with different gene regulatory and epigenetic multiomic layers to understand how they may function to produce autism. Our results indicate that the core of ASD resides in the dysregulation of a process called RNA-induced Initiation of Transcriptional gene Silencing (RITS) that is meant to maintain heterochromatin and produces SVs in the genes within these chromosomal regions, resulting in alterations in brain development. This finally links reported ASD-risk genes involved in chromatin remodeling with neurodevelopment. In addition, it may explain the role of de novo mutations in ASD and provide a framework for more accurate diagnostics and endophenotypes.

Intestinal obstruction, a prevalent and serious condition, necessitates deeper understanding of its genetic architecture. This study rigorously employed two-sample Mendelian randomization to dissect the causal influence of gene expression on intestinal obstruction risk, leveraging comprehensive summary-level data from eQTLGen and FinnGen GWAS. To enhance causal inference, Summary-data-based Mendelian Randomization was integrated, utilizing GTEx eQTL data to specifically assess tissue-relevant gene expression. Our multi-pronged analyses provide compelling genetic evidence supporting causal roles for genetically predicted expression of CHRNB2 and MIAT in intestinal obstruction. Specifically, increased genetically proxied CHRNB2 expression was associated with a protective effect, while higher genetically proxied MIAT expression suggested an elevated susceptibility to intestinal obstruction. Colocalization analysis, alongside HEIDI heterogeneity testing within the SMR framework, further bolstered the robustness of these findings by distinguishing causality from linkage disequilibrium. These convergent results offer novel mechanistic insights into intestinal obstruction pathogenesis, positioning CHRNB2 and MIAT as promising therapeutic targets for both prevention and treatment strategies. Future research is crucial to validate these findings across diverse ancestries and to fully elucidate the intricate biological mechanisms underpinning these gene-disease associations.

BackgroundAutism spectrum disorder (ASD) is a lifelong neurodevelopmental condition characterised by social and behavioural challenges. It is highly heritable, with estimates ranging from 40-90% and a liability-scale heritability of 0.924, underscoring the role of genetic variants in its pathogenesis. Limited studies from India hinder an accurate assessment of the countrys true ASD genetic spectrum. AimTo investigate the genetic spectrum in an Indian control dataset, providing baseline variant frequency data to facilitate interpretation of disease-associated variants in the Indian population. MethodsWe compiled a strongly ASD-linked gene panel from the SFARI and ClinGen databases, followed by the extraction of gene-associated variants from the IndiGenomes dataset. A stepwise analysis pipeline was implemented, including variant annotation, filtering for minor allele frequency (MAF < 5%), prediction of deleteriousness using REVEL (>0.75), and loss-of-function prediction with LoFTEE (high confidence). Variants were then classified according to ACMG-AMP guidelines. ResultsWe identified 1,531,327 variants from 517 ASD panel genes (MAF < 5%) spanning [~]88 Mb of genomic regions. ACMG-AMP interpretation was performed for prioritised 298 missense variants (REVEL > 0.75) and 537 LoF variants (LoFTEE; high confidence). Missense and LoF variants contributed 37% and 63% of the filtered data, respectively. Fifty-five variants from 28 genes were classified as pathogenic/likely pathogenic, while 10 variants in 6 genes showed significantly higher MAF (p < 0.05; Fishers exact test). Carrier numbers were estimated for autosomal recessive inheritance models. ConclusionThis study provides a comprehensive spectrum of ASD-related genetic variants in the Indian population, offering valuable insights for ASD diagnosis, genetic interpretation, and understanding of underlying molecular mechanisms.