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. 2022 Aug 18;54(9):1305–1319. doi: 10.1038/s41588-022-01148-2

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 7 — a, Using a combination of archetypal analysis and canonical correlation analysis, putative autism risk genes were organized into k = 6 archetypes that represent distinct mechanistic (STRING) and phenotypic (HPO) categorizations (neurotransmission, chromatin modification, RNA processing, vesicle-mediated transport, MAPK signaling and migration, and cytoskeleton and mitosis). Genes implicated by our meta-analysis are indicated by their label, with novel genes in red. b, For each of the five novel genes, we identified the five nearest neighbors in the embedding space among the 62 meta-analysis genes. SCAF1, MARK2 and HNRNPUL2 were identified as ‘mixed’ rather than ‘archetypal’ in their probable risk mechanisms. c, To gain further insight into possible risk mechanisms, we calculated the embedding distance to the centroid of these three genes, which was then used as an index variable to perform gene set enrichment analysis. d, A STRING cluster (CL:6549) containing genes related to cell–cell junctions and the gap junction was identified as being highly localized in this region of the embedding space (P = 4.12 × 10⁻¹⁴ by the Kolmogorov–Smirnov test). This may suggest that these genes confer autism risk through dysregulation of processes related to cell adhesion and migration.