Towards a Map of Cortical Folding Patterns Genetics
Poster No:
682
Submission Type:
Abstract Submission
Authors:
Antoine Dufournet1, Julien Laval1, Joël Chavas1, Denis Rivière1, Vincent Frouin1, Jean-François Mangin1
Institutions:
1CEA/Neurospin, Paris Saclay, Gif-sur-Yvette, France
First Author:
Co-Author(s):
Introduction:
The human cortex shows complex folding patterns that delimit distinct anatomical and functional regions. These patterns are known to be influenced by genetic factors (Ronan, 2015). While most neuroimaging Genome-Wide Association Studies (GWAS) focus on macroscopic anatomical features such as cortical thickness and subcortical volume, a smaller subset explores morphological measures like depth, length, and opening of folds. However, these approaches may fail to capture the full genetic diversity underlying variations in folding shapes, interruptions, and relative positions corresponding to the notion of folding patterns.
Methods:
In this study, we introduce a new regional approach that combines AI-based latent space modeling with multivariate GWAS to explore the genetic basis of cortical folding patterns. First, we use 42,000 T1-weighted MRI scans from the UK Biobank and apply preprocessing steps using BrainVisa, without performing sulcus recognition. This preprocessing yields a negative cast of the cortex that we call a 'cortical skeleton.' We train a self-supervised model (Laval, 2025) to capture variability in a region of the MNI space centered on the internal frontal sulcus (S.F.int) and the calloso-marginal anterior fissure (F.C.M.ant), following BrainVisa nomenclature. With the trained model, we then map 36,000 UK Biobank participants (mean age: 64.2 years; 47.6% male; white British ancestry) into a 256-dimensional latent space. This latent space is reduced using Principal Component Analysis (PCA) to retain 99.9% of the variance and is then used as a phenotype for the Multivariate Omnibus Statistical Test (MOSTest) (van der Meer, 2020).
Results:
Focusing on this region, we identify 19 genetic loci in the left hemisphere and 25 loci in the right hemisphere (p < 5 × 10-8) (Fig. 1) using the Functional Mapping and Annotation of GWAS (FUMA) pipeline (Watanabe, 2017). Further gene-set analyses with the Multi-marker Analysis of GenoMic Annotation (MAGMA) (de Leeuw, 2015) reveal that these loci harbor genes involved in neurodevelopment, neuronal cell specification, and migration. Each locus is related to a specific direction in the latent space. The phenotypic variation encoded along that direction can be assessed using moving averages performed from the skeletons included in the region of interest. For instance, one locus seems related to the well-known polymorphism associated with the presence or absence of the paracingulate sulcus above the calloso-marginal fissure (Fig. 2).
·Figure 1: Manhattan plot for the right S.F.int F.C.M.ant region
·Figure 2: Moving average on groups of 200 subjects, in the direction indicated by the association with the lead SNP rs12408663 (p=2x10-13)
Conclusions:
Our findings provide a systematic way to explore the genetic basis of cortical folding patterns across all regions of the cortex. This genetic map could provide insight into genetic expression occurring in utero during the early folding process, which is strongly related to neurogenesis chronology.
Genetics:
Genetic Association Studies 1
Genetic Modeling and Analysis Methods
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Cortical Anatomy and Brain Mapping 2
Novel Imaging Acquisition Methods:
Anatomical MRI
Keywords:
Cortex
Modeling
Morphometrics
MRI
Structures
Other - Sulci
1|2Indicates the priority used for review
Abstract Information
By submitting your proposal, you grant permission for the Organization for Human Brain Mapping (OHBM) to distribute your work in any format, including video, audio print and electronic text through OHBM OnDemand, social media channels, the OHBM website, or other electronic publications and media.
The Open Science Special Interest Group (OSSIG) is introducing a reproducibility challenge for OHBM 2025. This new initiative aims to enhance the reproducibility of scientific results and foster collaborations between labs. Teams will consist of a “source” party and a “reproducing” party, and will be evaluated on the success of their replication, the openness of the source work, and additional deliverables. Click here for more information. Propose your OHBM abstract(s) as source work for future OHBM meetings by selecting one of the following options:
Please indicate below if your study was a "resting state" or "task-activation” study.
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Was this research conducted in the United States?
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.
Please indicate which methods were used in your research:
For human MRI, what field strength scanner do you use?
Provide references using APA citation style.
2. de Leeuw, C. A., Mooij, J. M., Heskes, T., & Posthuma, D. (2015). MAGMA: generalized gene-set analysis of GWAS data. PLoS computational biology, 11(4), e1004219.
3. van der Meer, D., Frei, O., Kaufmann, T., Shadrin, A. A., Devor, A., Smeland, O. B., ... & Dale, A. M. (2020). Understanding the genetic determinants of the brain with MOSTest. Nature communications, 11(1), 3512.
4. Ronan, L., & Fletcher, P. C. (2015). From genes to folds: a review of cortical gyrification theory. Brain Structure and Function, 220, 2475-2483.
5. Watanabe, K., Taskesen, E., Van Bochoven, A., & Posthuma, D. (2017). Functional mapping and annotation of genetic associations with FUMA. Nature communications, 8(1), 1826.