By Vijay Kumar MalesuReviewed by Susha Cheriyedath, M.Sc.Jun 18 2024 In a recent study published in the journal Science Advances, researchers in the United States used 3D transport-based morphometry to identify and visualize brain changes linked to 16p11.2 genetic copy number variation , enhancing prediction accuracy and advancing precision medicine in autism.
About the study In the present study, subjects were recruited from the Simons VIP project, reviewed by the Johns Hopkins Institutional Review Board, and acknowledged as exempt as subjects were deidentified from a preexisting database. Participants were referred by clinical genetic centers, testing laboratories, web-based networks, and self-referral. Screening and medical record reviews were conducted by Geisinger and Emory University, with 16p11.
T1-weighted magnetization-prepared gradient-echo image images were collected using standardized protocols. Preprocessing involved excluding non-brain tissues, segmenting gray and white matter, and normalizing brain size. The 3D TBM technique, based on optimal mass transport, transformed images to identify and visualize tissue patterns linked to 16p11.2 CNV, combined with machine learning for automated discovery and visualization.
Related StoriesThe study utilized T1-weighted MPRAGE images from the Simons VIP dataset. Images were coregistered and segmented into gray and white matter tissues using Statistical Parametric Mapping software. After normalizing tissue mass, TBM transformed each image into the transport domain relative to a reference image, generating transport maps that were analyzed.
Genetic cohorts were highly separable in the transport domain using penalized linear discriminant analysis for white and gray matter. Genetic cohorts were more separable based on white matter distribution, with direction 1 showing a dose-dependent influence of 16p11.2 CNV on brain structure. Classification performance on the test set using 10-fold cross-validation showed 94.6% accuracy for white matter and 88.5% for gray matter.