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Genetic insights on the mechanisms of human cortical folding

Overview

16 affiliations
  1. Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Bethesda, MD, United States of America
  2. Department of Psychiatry, University of Cambridge, Cambridge, UK
  3. Lifespan Brain Institute, Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, Pennsylvania, United States of America
  4. Marcus Autism Center, Children’s Healthcare of Atlanta, Atlanta, Georgia, United States of America, Emory University School of Medicine, Department of Pediatrics, Atlanta, Georgia, United States of America
  5. Emory University School of Medicine, Department of Pediatrics, Atlanta, Georgia, United States of America
  6. Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States of America
  7. Centre de recherche CHU Sainte-Justine and University of Montreal, Canada
  8. Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California, United States of America
  9. Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, Los Angeles, California, United States of America
  10. Division of Pediatric Endocrinology, Nationwide Children’s Hospital, Ohio State University, Columbus, Ohio, United States of America
  11. Department of Psychological and Brain Sciences, Drexel University, Philadelphia, Pennsylvania, United States of America
  12. Department of Psychiatry, Robert Wood Johnson School of Medicine, Rutgers University, United States of America
  13. Center for Advanced Biotechnology and Medicine, Rutgers University, United States of America
  14. Department of Pediatrics, University of Montreal, Montreal, QC, Canada
  15. Department of Psychology, University of California, Los Angeles, CA, United States of America
  16. School of Academic Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
Dates: published online 9 March 2026
Type: Preprint · Language: English
License: CC0
Identifiers: DOI 10.64898/2026.03.06.709690 · OpenAlex W7135034986
Open access: green, a free copy (OpenAlex)
Status: data only
Categories: genetics / omics (modality), human (organism), cellular / molecular (subfield)
Methods: Statistics, Smoothing, state filtering, decompositions, Machine learning, Connectivity, Preprocessing, Complexity, fMRI & imaging
Topic: Functional Brain Connectivity Studies (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: MQ: Transforming Mental Health (MQF17_24); National Institute for Health Research (NIHR) (NIHR203312)
Citations: not cited yet (Europe PMC); 155 references in the paper

Abstract

The unique and intricate pattern of human cortical folding is rooted in fetal neurodevelopmental processes and can now be comprehensively quantified by new neuroimaging-derived measures of sulcal complexity. Here, we provide the first genetic maps of human sulcal complexity. Beginning with large effects of rare variants, we survey nine different neurogenetic syndromes (n=615), detecting visible changes in sulcal complexity on a shared axis of sulcal change coupled to the prenatal timing of sulcation. Turning to common genetic variants, we use genome-wide association studies of complexity scores for 40 sulci in the UK Biobank (n~29,000) to (i) resolve variable heritability across sulci, (ii) reveal both local and remote shared genetic effects with cortical morphology, and (iii) identify complexity-associated genes and their embedding in brain maps of prenatal gene expression. These reference genetic maps uncover multiple new mechanistic pathways for cortical morphogenesis in health and disease.

Reproduced under the paper's license (CC0), from the paper cited above.

Code

The paper links to its data, not to its authors' code: see the Data section.

The paper's code and data availability statement is in the Data section.

Tracing map

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Data

Datasets cited

Data availability

All genetic maps of rare neurogenetic syndrome or common variant effects on sulcal complexity produced in this study are provided in Supplementary Data and Source Data files. Additionally, genetic correlations with cortical morphometrics, gene summaries of GWAS significant genes, fetal brain transcriptomic module data and related gene set enrichment analysis are all provided in Supplementary Data and Source Data files. Sulcal complexity GWAS summary statistics will be deposited with accession codes made available prior to publication. Raw neuroimaging data for neurogenetic syndromes are available through request and data access agreement from the principal investigators of the projects from the studies they are derived from. UK Biobank imputed genotype data and imaging data can be accessed through application to the UK Biobank (https://www.ukbiobank.ac.uk/use-our-data/apply-for-access/). Sulcal gradients described in Snyder et al.63 were reproduced with the updated sulcal atlas used in the present study, and are also provided in Source Data files. Sulcal emergence data was obtained from Snyder et al.63 Associations with GWAS on area and thickness phenotypes were derived from Shafee et al.121 and from Smith et al.88 (https://open.oxcin.ox.ac.uk/ukbiobank/big40/). Fetal brain transcriptomics were obtained from Ball et al.97 (https://zenodo.org/records/10622337).

Reproduced under the paper's license (CC0), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 30 September 2026: the first record

Recorded: type, language, journal, dates, 18 authors, 2 funders, 146 references.

Cite

This paper

Snyder, W., Shafee, R., Liu, S., Levitis, E., Duan, K., Kumar, K., Schleifer, C. H., Boen, R., Ching, C. R., Han, J. C., Lee, N., Mulle, J. G., Shultz, S., Jacquemont, S., Bearden, C. E., Vértes, P. E., Bullmore, E. T., & Raznahan, A. (2026). Genetic insights on the mechanisms of human cortical folding. bioRxiv (preprint). https://doi.org/10.64898/2026.03.06.709690

BibTeX

@article{snyder2026genetic,
author = {Snyder, William and Shafee, Rebecca and Liu, Siyuan and Levitis, Elizabeth and Duan, Kuaikuai and Kumar, Kuldeep and Schleifer, Charles H and Boen, Rune and Ching, Christopher RK and Han, Joan C. and Lee, Nancy and Mulle, Jennifer G and Shultz, Sarah and Jacquemont, Sébastien and Bearden, Carrie E and Vértes, Petra E and Bullmore, Edward T and Raznahan, Armin},
title = {{Genetic insights on the mechanisms of human cortical folding}},
journal = {bioRxiv (preprint)},
year = {2026},
month = mar,
publisher = {bioRxiv},
issn = {2692-8205},
doi = {10.64898/2026.03.06.709690},
url = {https://doi.org/10.64898/2026.03.06.709690}
}

RIS

TY - JOUR
AU - Snyder, William
AU - Shafee, Rebecca
AU - Liu, Siyuan
AU - Levitis, Elizabeth
AU - Duan, Kuaikuai
AU - Kumar, Kuldeep
AU - Schleifer, Charles H
AU - Boen, Rune
AU - Ching, Christopher RK
AU - Han, Joan C.
AU - Lee, Nancy
AU - Mulle, Jennifer G
AU - Shultz, Sarah
AU - Jacquemont, Sébastien
AU - Bearden, Carrie E
AU - Vértes, Petra E
AU - Bullmore, Edward T
AU - Raznahan, Armin
TI - Genetic insights on the mechanisms of human cortical folding
T2 - bioRxiv (preprint)
J2 - bioRxiv
PY - 2026
DA - 2026/03/09
SN - 2692-8205
PB - bioRxiv
DO - 10.64898/2026.03.06.709690
UR - https://doi.org/10.64898/2026.03.06.709690
LA - en
ER -

CSL-JSON

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