Self-supervised representations of cortical folding are established as a powerful phenotype for the genetic study of neurodevelopment through multivariate genome-wide association studies (GWAS).
This study uses Multimodal Surface Matching with Hierarchical Templates (MSM-HT), a hierarchical surface registration, to parse cortical folding patterns into a representative family of distinct anatomical templates, offering a robust framework to generalise the uncovered cortical folding motifs across datasets and dev...
You-Rong Guo, Mohamed A. Suliman, L. Williams et al.· Nature Communications· 0 citations
This work presents the first genome-wide association study (GWAS) of subcortical LBA, estimated using a deep neural network applied to T1-weighted MRI scans from 41,957 cognitively normal participants in the UK Biobank, and identifies 14 significant single-nucleotide polymorphisms across nine independent loci.
Nicholas J. Kim, Ayati Mishra, Jeremy S Yu et al.· GeroScience· 0 citations
Genetic prediction of complex phenotypes typically relies on additive linear models, which scale well but cannot capture non-additive effects or deeply integrate molecular and clinical data. Domain-specific neural networks have driven advances in images, text, and other modalities, but genome-scale neural networks rema...
J. Upmeier zu Belzen, L. Arnoldt, N. Hollmann et al.· medRxiv· 0 citations
Video masked-autoencoder training identified new associated loci beyond those detected using supervised phenotypes at matched sample size, which shared genetic architecture selectively with cardiac-conduction traits and were localised to cardiac structures within the imaged field of view.
These findings demonstrate that aberrant cortical folding in schizophrenia is constrained by network topology and molecular architecture, and establishes sulcal morphology as a mechanistically grounded biomarker that may help differentiate the neurodevelopmental trajectories of psychiatric disorders.
J. González-Peñas, H. Schnack, Carmen Rueda Hernández et al.· Biological Psychiatry· 0 citations
Overall, this work identifies a conserved transcriptional axis that links cortical architecture to developmental timing and organizes the heterogeneous cortical effects of autism-associated mutations.