Genomic landscape of rare variants in a Chinese autism cohort and discovery of novel risk genes.

Genetic Heterogeneity in Autism Spectrum Disorder: Diagnostic Yield, Recurrent Genes, and Rare Variant-Phenotype Associations from Whole-Exome Sequencing

Autism spectrum disorder (ASD) is genetically heterogeneous, involving rare and common variants that disrupt neurodevelopmental pathways. To explore this complexity, we performed whole-exome sequencing in children with ASD. Clinical phenotypes were systematically recorded, and severity was classified according to DSM-5 criteria. Variants were interpreted using ACMG guidelines, with recurrence analysis to identify genes shared across individuals and cohort enrichment testing against gnomAD. To examine genotype-phenotype relationships, we applied SKAT/SKAT-O across 16 phenotypes after covariate adjustment. Among 25 included individuals, pathogenic or likely pathogenic variants were found in 9, yielding a diagnostic yield of 36%. These involved genes linked to neurodevelopmental, epileptic, metabolic, and syndromic disorders. Recurrence analysis identified 586 genes present in at least two individuals, with PABPC1, GTF2I, PCLO, PKD1, and EP400 being the most frequent. SKAT/SKAT-O revealed the strongest burden associations for motor delay, aggressive behavior, mutism, anxiety, unresponsiveness to spoken voice, digestive disorder, and sleep disturbances, with limited overlap across phenotypes. Several recurrent genes also showed phenotype-specific associations. Overall, this integrative WES study provides clinically actionable diagnoses, highlights recurrent genes, and uncovers phenotype-specific signals, supporting convergent pathways with gene-level heterogeneity.

Rare variation illuminates the distinct and pleiotropic genetic architecture of autism across neuropsychiatric traits

This study finds that rare variants across hundreds of genes contribute to autism with variable phenotypic outcomes, and clusters them based on association evidence from large-scale studies of developmental disorders, schizophrenia, bipolar disorder, and epilepsy.

Contribution of Copy Number Variants and Cumulative Genetic Load to Autism Spectrum Disorders: Integrative Insights from Chromosomal Microarray Analysis

Increased CNV burden, in both number and cumulative genomic size, co-occurred more frequently in individuals with severe phenotypes, including ASD with intellectual disability, epilepsy, and broader NDDs, reflecting a real-world clinical setting rather than a prospectively recruited research cohort.

Genome-wide assessment of rare protein-coding variants identifies associations with non-syndromic cleft lip/palate.

Nonsyndromic cleft lip and palate (NSCLP) is a complex, multifactorial condition for which only about 25% of the genetic contribution has been identified. Although more than 60 genetic loci have been associated with NSCLP, a large portion of its heritability remains unexplained. Rare variants-often with stronger functional effects-are believed to account for some of this missing genetic risk. In this study, short-read whole-genome sequencing data from 786 NSCLP cases and 2149 controls were analyzed to identify genes enriched for rare protein-coding variants. Gene-based association testing, meta-analysis, functional prioritization, and effect-size estimation revealed several novel NSCLP candidate genes and confirmed associations with previously reported genes. The four novel candidate genes with the strongest association evidence were SCT, MALRD1, GPR156, and MYOCOS, all with p-values < 10⁻⁴. Replication of known genes was most robust for ARHGAP29, FGF8, SKI, and TP63. Pathway analyses showed significant enrichment of these genes in neuroactive ligand-receptor interactions, MAPK signaling, and other signal transduction pathways. Precise estimates of the risks conferred by the identified rare variants showed a substantial increase in NSCLP risk, with odds ratio point estimates between 2 and 4. These results provide strong support for a polygenic inheritance model in NSCLP, in which certain genes contribute varying levels of risk.

Estimating the contribution of coding mutations to autism

De novo mutations in protein-coding regions are strongly associated with autism, and family-based sequencing studies have identified numerous genes that harbor excess mutations in probands. However, the aggregate contribution of this class of variation to autism remains unclear. Here, we model the distribution of de novo autosomal coding variant effect sizes in 38,680 autism trios to estimate fundamental features of de novo genetic architecture. We find that damaging de novo single-nucleotide variants and frameshift indels explain 3.4% (95% CI: 2.1% - 4.7%) of autism variance on the observed scale. Approximately 7.0% (95% CI: 5.6% - 8.4%) of cases carry a large-effect mutation (rate ratio > 5), and most such mutations are incompletely penetrant. Although hundreds of genes make some nonzero contribution, 50% of mutational variance on the autosomes is explained by just 15 genes. De novo enrichments vary across cohorts with different ascertainment strategies; making projections for future trio studies, we show that many large-effect genes remain to be found.

Higher frequencies of CNV deletions in bipolar disorder among Chinese Population.