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ORIGINAL RESEARCH article

Front. Neurosci.

Sec. Brain Imaging Methods

Volume 19 - 2025 | doi: 10.3389/fnins.2025.1639871

This article is part of the Research TopicAdvances in brain diseases: leveraging multimodal data and artificial intelligence for diagnosis, prognosis, and treatmentView all 7 articles

Multimodal neuroimaging of Col4a1-mutant mice models of Gould Syndrome

Provisionally accepted
  • 1Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, United States
  • 2Department of Ophthalmology, University of California, San Francisco, San Francisco, United States

The final, formatted version of the article will be published soon.

ABSTRACT (217 words) Cerebral small vessel disease (cSVD) is a leading cause of stroke and vascular contributions to cognitive impairment and dementia (VCID). Studying monogenic cSVD can reveal pathways that are dysfunctional in common forms of the disease and may represent therapeutic targets. Mutations in collagen type IV alpha 1 (COL4A1) and alpha 2 (COL4A2) cause highly penetrant cSVD as part of a multisystem disorder referred to as Gould syndrome, which comprises a constellation of cerebrovascular conditions including porencephaly, early-onset stroke, leukoencephalopathy, and intracerebral hemorrhage (ICH). Col4a1 and Col4a2 mutant mice faithfully capture the pathophysiological hallmarks of Gould syndrome and thus provide an experimentally tractable platform to investigate the correlation between allelic heterogeneity and phenotypic variability using magnetic resonance imaging (MRI) as a radiological assessment of cSVD. In this study, we used five different Col4a1 mutant mouse strains that mimic the clinical spectrum of cerebrovascular manifestations observed in Gould syndrome. These strains were characterized using multimodal MRI at 14.1 Tesla. We show that multimodal MRI successfully identified typical cSVD lesions and reveal heterogeneous expressivity in a Col4a1 murine allelic series in terms of lesion prevalence, size, and number. Importantly, using these standards, we identified brain regions most vulnerable to cSVD lesions in Gould syndrome models, highlighting the capability of our imaging modalities in early detection and diagnosis of cSVD-related pathologies.

Keywords: MRI, Gould Syndrome, Collagen, Co4a1, Vascular Dementia, CSVd

Received: 02 Jun 2025; Accepted: 01 Oct 2025.

Copyright: © 2025 Gao, Wang, Labelle-Dumais, Gould and Chaumeil. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Douglas B Gould, douglas.gould@ucsf.edu
Myriam M Chaumeil, myriam.chaumeil@nvision-imaging.com

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