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.

Integrating Genome Sequencing and Untargeted Metabolomics in Monozygotic Twins with a Rare Complex Neurological Disorder.

Multi-omics approaches, which integrate genomics, transcriptomics, proteomics, and metabolomics, have emerged as powerful tools in the diagnosis of rare diseases. We used untargeted metabolomics and whole-genome sequencing (WGS) to gain a more comprehensive understanding of a rare disease with a complex presentation affecting female twins from a consanguineous family. The sisters presented with polymicrogyria, a Dandy-Walker malformation, respiratory distress, and multiorgan dysfunctions. Through WGS, we identified two rare homozygous variants in both subjects, a pathogenic variant in ADGRG1(p.Arg565Trp) and a novel variant in CNTNAP1(p.Glu910Val). These genes have been previously associated with autosomal recessive polymicrogyria and hypomyelinating neuropathy with/without contractures, respectively. The twins exhibited symptoms that overlapped with both of these conditions. The results of the untargeted metabolomics analysis revealed significant metabolic perturbations relating to neurodevelopmental abnormalities, kidney dysfunction, and microbiome. The significant metabolites belong to essential pathways such as lipids and amino acid metabolism. The identification of variants in two genes, combined with the support of metabolic perturbation, demonstrates the rarity and complexity of this phenotype and provides valuable insights into its underlying mechanisms.

Deciphering metabolomics and lipidomics landscape in zebrafish hypertrophic cardiomyopathy model.

To elucidate the lipidomic and metabolomic alterations associated with hypertrophic cardiomyopathy (HCM) pathogenesis, we utilized cmybpc3-/- zebrafish model. Fatty acid profiling revealed variability of 10 fatty acids profiles, with heterozygous (HT) and homozygous (HM) groups exhibiting distinct patterns. Hierarchical cluster analysis and multivariate analyses demonstrated a clear separation of HM from HT and control (CO) groups related to cardiac remodeling. Lipidomic profiling identified 257 annotated lipids, with two significantly dysregulated between CO and HT, and 59 between HM and CO. Acylcarnitines and phosphatidylcholines were identified as key contributors to group differentiation, suggesting a shift in energy source. Untargeted metabolomics revealed 110 and 53 significantly dysregulated metabolites. Pathway enrichment analysis highlighted perturbations in multiple metabolic pathways in the HM group, including nicotinate, nicotinamide, purine, glyoxylate, dicarboxylate, glycerophospholipid, pyrimidine, and amino acid metabolism. Our study provides comprehensive insights into the lipidomic and metabolomic unique signatures associated with cmybpc3-/- induced HCM in zebrafish. The identified biomarkers and dysregulated pathways shed light on the metabolic perturbations underlying HCM pathology, offering potential targets for further investigation and potential new therapeutic interventions.

Comprehensive whole-genome sequence analyses provide insights into the genomic architecture of cerebral palsy.

We performed whole-genome sequencing (WGS) in 327 children with cerebral palsy (CP) and their biological parents. We classified 37 of 327 (11.3%) children as having pathogenic/likely pathogenic (P/LP) variants and 58 of 327 (17.7%) as having variants of uncertain significance. Multiple classes of P/LP variants included single-nucleotide variants (SNVs)/indels (6.7%), copy number variations (3.4%) and mitochondrial mutations (1.5%). The COL4A1 gene had the most P/LP SNVs. We also analyzed two pediatric control cohorts (n = 203 trios and n = 89 sib-pair families) to provide a baseline for de novo mutation rates and genetic burden analyses, the latter of which demonstrated associations between de novo deleterious variants and genes related to the nervous system. An enrichment analysis revealed previously undescribed plausible candidate CP genes (SMOC1, KDM5B, BCL11A and CYP51A1). A multifactorial CP risk profile and substantial presence of P/LP variants combine to support WGS in the diagnostic work-up across all CP and related phenotypes.

Genomic architecture of autism spectrum disorder in Qatar: The BARAKA-Qatar Study.

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by impaired social and communication skills, restricted interests, and repetitive behaviors. The prevalence of ASD among children in Qatar was recently estimated to be 1.1%, though the genetic architecture underlying ASD both in Qatar and the greater Middle East has been largely unexplored. Here, we describe the first genomic data release from the BARAKA-Qatar Study-a nationwide program building a broadly consented biorepository of individuals with ASD and their families available for sample and data sharing and multi-omics research. METHODS: In this first release, we present a comprehensive analysis of whole-genome sequencing (WGS) data of the first 100 families (372 individuals), investigating the genetic architecture, including single-nucleotide variants (SNVs), copy number variants (CNVs), tandem repeat expansions (TREs), as well as mitochondrial DNA variants (mtDNA) segregating with ASD in local families. RESULTS: Overall, we identify potentially pathogenic variants in known genes or regions in 27 out of 100 families (27%), of which 11 variants (40.7%) were classified as pathogenic or likely-pathogenic based on American College of Medical Genetics (ACMG) guidelines. Dominant variants, including de novo and inherited, contributed to 15 (55.6%) of these families, consisting of SNVs/indels (66.7%), CNVs (13.3%), TREs (13.3%), and mtDNA variants (6.7%). Moreover, homozygous variants were found in 7 families (25.9%), with a sixfold increase in homozygous burden in consanguineous versus non-consanguineous families (13.6% and 1.8%, respectively). Furthermore, 28 novel ASD candidate genes were identified in 20 families, 23 of which had recurrent hits in MSSNG and SSC cohorts. CONCLUSIONS: This study illustrates the value of ASD studies in under-represented populations and the importance of WGS as a comprehensive tool for establishing a molecular diagnosis for families with ASD. Moreover, it uncovers a significant role for recessive variation in ASD architecture in consanguineous settings and provides a unique resource of Middle Eastern genomes for future research to the global ASD community.