Deep-embedded clustering by relevant scales and genome-wide association study in autism - Fumihiko Ueno; Ippei Takahashi; Hisashi Ohseto; Tomomi Onuma; Akira Narita; Taku Obara; Mami Ishikuro; Keiko Murakami; Aoi Noda; Fumiko Matsuzaki; Hirohito Metoki; Gen Tamiya; et al. (PLoS ONE, 2025)
Autism spectrum disorder (ASD) presents with heterogeneous phenotypic and genetic characteristics. Despite investigation into the molecular mechanisms underlying ASD, its etiology remains elusive. In our previous investigation within the Simons Simplex Collection (SSC), we noted increased signals through a genome-wide association study (GWAS) by clustering patients with ASD and reducing the sample size. This study seeks to validate our previous study in a different population, the Simons Foundation Powering Autism Research for Knowledge (SPARK) population, while probing further into the genetic architecture of ASD. We examined data from 2,079 white male subjects and 875 unaffected SPARK siblings. Our methodology encompassed cluster analyses, followed by traditional GWAS and cluster-based GWAS (cGWAS). No significant associations were observed in the conventional GWAS when comparing all patients with all controls. However, in the cGWAS, by comparing patients clustered by phenotypes with controls, we identified 27 chromosomal loci meeting the criteria of p < 5.0 × 10 ⁻ 8 . Remarkably, several of these loci were situated within or in proximity to genes previously implicated as candidates for ASD. Nonetheless, our previous study of the SSC population did not fully replicate the SPARK population. The absence of reproducibility suggests the possibility of false positives within the cGWAS results due to potential technical factors. However, the emergence of multiple signals post-clustering and the association of numerous identified gene regions with ASD and related disorders provide supporting evidence for the validity of cGWAS outcomes.