{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T09:13:05Z","timestamp":1785402785918,"version":"3.56.0"},"reference-count":25,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T00:00:00Z","timestamp":1785369600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objectives: Wolfram syndrome is an ultra-rare, progressive multisystem disorder in which endocrine and sensory manifestations coexist with neurological involvement. Quantitative magnetic resonance imaging (MRI) may help characterize central nervous system involvement in this condition; however, evidence derived from small imaging cohorts requires cautious interpretation. This study aimed to examine the relationships between different MRI-derived attributes and neurological symptoms in Wolfram syndrome, with the goal of identifying exploratory imaging patterns that may suggest the involvement of specific neural systems. Methods: We analyzed a Spanish cohort of 45 genetically confirmed patients with Wolfram syndrome. A homogeneous subset of 15 patients with standardized 3-Tesla multimodal MRI and adequate image quality was included in the quantitative imaging analysis. T1-weighted MRI, T2-weighted\/fluid-attenuated inversion recovery (FLAIR) imaging, and diffusion tensor imaging (DTI) were processed using a standardized workflow for brain extraction, anatomical segmentation, cortical reconstruction, and quantitative feature extraction. A total of 172 MRI-derived features were examined in relation to neurological phenotypes, including dysphagia, ataxia, gait instability, and cognitive impairment. Analyses included principal component analysis, exploratory factor analysis, correlation analyses, and symptom-specific group comparisons. Given the small MRI sample size and the high feature-to-subject ratio, all analyses were considered exploratory and hypothesis-generating, and the findings should be interpreted cautiously pending validation in larger, independent cohorts. Results: Multimodal MRI-derived features showed distributed associations with neurological manifestations. The most recurrent exploratory imaging correlates involved the thalamus, lateral geniculate nucleus, cerebellum, brainstem, ventricular system, corpus callosum, posterior cortical regions, and white-matter pathways. FLAIR-derived signal heterogeneity in the thalamus and lateral geniculate nucleus appeared repeatedly across several clinical manifestations. Dysphagia was associated with a distributed pattern involving cortical thinning, thalamic and brainstem volume reduction, reduced cerebellar white-matter integrity, increased FLAIR heterogeneity, and ventricular enlargement. Ataxia and gait instability showed overlapping but partially distinct imaging profiles, whereas cognitive impairment was associated with broader cortical, subcortical, callosal, cerebellar, and ventricular alterations. Conclusions: In this exploratory pilot study, multimodal MRI-derived features showed clinically plausible associations with neurological manifestations in Wolfram syndrome. The findings support a distributed model of neurological involvement affecting cerebello-thalamo-cortical circuits, visual relay structures, brainstem pathways, and long-range white-matter connections. These results should be interpreted as exploratory MRI-derived attributes rather than as validated biomarkers, prognostic indicators, or clinically applicable imaging signatures. Confirmation in future longitudinal, multicenter studies with harmonized imaging protocols and external validation will be required.<\/jats:p>","DOI":"10.3390\/diagnostics16152396","type":"journal-article","created":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T08:09:42Z","timestamp":1785398982000},"page":"2396","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Exploratory Associations Between Multimodal MRI-Derived Features and Neurological Symptoms in Wolfram Syndrome: A Spanish Cohort Pilot Study"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7554-9434","authenticated-orcid":false,"given":"Gema","family":"Esteban-Bueno","sequence":"first","affiliation":[{"name":"UGC La Ca\u00f1ada (Primary Care Management Unit), Almer\u00eda Periphery\u2013Almer\u00eda Health District, Andalusian Health Service (SAS), 04009 Almer\u00eda, Spain"},{"name":"Spanish Association for Research and Support to Wolfram Syndrome, 04120 Almer\u00eda, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lucas","family":"Fern\u00e1ndez-Brillet","sequence":"additional","affiliation":[{"name":"Miscellany Creative SL, 29620 M\u00e1laga, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4758-2832","authenticated-orcid":false,"given":"Juan Luis","family":"Fern\u00e1ndez-Mart\u00ednez","sequence":"additional","affiliation":[{"name":"Group of Inverse Problems, Optimization and Machine Learning, Department of Mathematics, University of Oviedo, 33007 Oviedo, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1458","DOI":"10.1016\/S0140-6736(95)92473-6","article-title":"Neurodegeneration and diabetes: UK nationwide study of Wolfram (DIDMOAD) syndrome","volume":"346","author":"Barrett","year":"1995","journal-title":"Lancet"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1097\/MOP.0b013e328354ccdf","article-title":"Wolfram syndrome 1 and Wolfram syndrome 2","volume":"24","author":"Rigoli","year":"2012","journal-title":"Curr. Opin. Pediatr."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1007\/s11892-015-0702-6","article-title":"Wolfram Syndrome: Diagnosis, Management, and Treatment","volume":"16","author":"Urano","year":"2016","journal-title":"Curr. Diab. Rep."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1007\/s12020-018-1608-2","article-title":"Natural history and clinical characteristics of 50 patients with Wolfram syndrome","volume":"61","year":"2018","journal-title":"Endocrine"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1002\/ana.22160","article-title":"Neurologic features and genotype-phenotype correlation in Wolfram syndrome","volume":"69","author":"Chaussenot","year":"2011","journal-title":"Ann. Neurol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1186\/1750-1172-8-64","article-title":"Phenotypic characteristics of early Wolfram syndrome","volume":"8","author":"Marshall","year":"2013","journal-title":"Orphanet J. Rare Dis."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1503","DOI":"10.2337\/dc10-1937","article-title":"Diabetes and neurodegeneration in Wolfram syndrome: A multicenter study of phenotype and genotype","volume":"34","author":"Rohayem","year":"2011","journal-title":"Diabetes Care"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1038\/gim.2012.180","article-title":"Genotypic classification of patients with Wolfram syndrome: Insights into the natural history of the disease and correlation with phenotype","volume":"15","author":"Nunes","year":"2013","journal-title":"Genet. Med."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1038\/2441","article-title":"A gene encoding a transmembrane protein is mutated in patients with diabetes mellitus and optic atrophy (Wolfram syndrome)","volume":"20","author":"Inoue","year":"1998","journal-title":"Nat. Genet."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2021","DOI":"10.1093\/hmg\/7.13.2021","article-title":"Diabetes insipidus, diabetes mellitus, optic atrophy and deafness (DIDMOAD) caused by mutations in a novel gene (wolframin) coding for a predicted transmembrane protein","volume":"7","author":"Strom","year":"1998","journal-title":"Hum. Mol. Genet."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1086\/520961","article-title":"A homozygous mutation in a novel zinc-finger protein, ERIS, is responsible for Wolfram syndrome 2","volume":"81","author":"Amr","year":"2007","journal-title":"Am. J. Hum. Genet."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"K\u00f5ks, S. (2023). Genomics of Wolfram Syndrome 1 (WFS1). Biomolecules, 13.","DOI":"10.3390\/biom13091346"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1007\/s40618-024-02495-z","article-title":"SID\/SIEDP expert consensus on optimizing clinical strategies for early detection and management of Wolfram syndrome","volume":"48","author":"Frontino","year":"2025","journal-title":"J. Endocrinol. Investig."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Hershey, T., Lugar, H.M., Shimony, J.S., Rutlin, J., Koller, J.M., Perantie, D.C., Paciorkowski, A.R., Eisenstein, S.A., Permutt, M.A., and the Washington University Wolfram Study Group Early Brain Vulnerability in Wolfram Syndrome (2012). Early brain vulnerability in Wolfram syndrome. PLoS ONE, 7.","DOI":"10.1371\/journal.pone.0040604"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"21167","DOI":"10.1038\/srep21167","article-title":"Neuroimaging evidence of deficient axon myelination in Wolfram syndrome","volume":"6","author":"Lugar","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"e000081","DOI":"10.1136\/bmjophth-2017-000081","article-title":"Visual pathway function and structure in Wolfram syndrome: Patient age, variation and progression","volume":"3","author":"Hoekel","year":"2018","journal-title":"BMJ Open Ophthalmol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"6010","DOI":"10.1038\/s41598-019-42447-9","article-title":"Evidence for altered neurodevelopment and neurodegeneration in Wolfram syndrome using longitudinal morphometry","volume":"9","author":"Lugar","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1186\/s13023-019-1260-9","article-title":"Developmental hypomyelination in Wolfram syndrome: New insights from neuroimaging and gene expression analyses","volume":"14","author":"Samara","year":"2019","journal-title":"Orphanet J. Rare Dis."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2364","DOI":"10.3174\/ajnr.A6831","article-title":"Longitudinal assessment of neuroradiologic features in Wolfram syndrome","volume":"41","author":"Samara","year":"2020","journal-title":"Am. J. Neuroradiol."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Simo, J., Lugar, H.M., Miller, E., Wilf-Yarkoni, A., Goldberg, Y., Kocaa\u011fa, A., Ito, S., Cocozza, S., Frontino, G., and Baldoli, C. (2025). Expanding the spectrum of white matter abnormalities in Wolfram syndrome: A retrospective review. Front. Neurol., 16.","DOI":"10.3389\/fneur.2025.1623314"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/S0006-3495(94)80775-1","article-title":"MR diffusion tensor spectroscopy and imaging","volume":"66","author":"Basser","year":"1994","journal-title":"Biophys. J."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1148\/radiol.2015151169","article-title":"Radiomics: Images are more than pictures, they are data","volume":"278","author":"Gillies","year":"2016","journal-title":"Radiology"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1148\/radiol.2020191145","article-title":"The Image Biomarker Standardization Initiative: Standardized quantitative radiomics for high-throughput image-based phenotyping","volume":"295","author":"Zwanenburg","year":"2020","journal-title":"Radiology"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"e778","DOI":"10.1002\/mco2.778","article-title":"Machine learning-based radiomics in neurodegenerative and cerebrovascular disease","volume":"5","author":"Shi","year":"2024","journal-title":"MedComm"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"13112","DOI":"10.1038\/s41598-025-97552-9","article-title":"A multimodal MRI-based machine learning framework for classifying cognitive impairment in cerebral small vessel disease","volume":"15","author":"Lin","year":"2025","journal-title":"Sci. Rep."}],"container-title":["Diagnostics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-4418\/16\/15\/2396\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T08:29:04Z","timestamp":1785400144000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-4418\/16\/15\/2396"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,30]]},"references-count":25,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2026,8]]}},"alternative-id":["diagnostics16152396"],"URL":"https:\/\/doi.org\/10.3390\/diagnostics16152396","relation":{},"ISSN":["2075-4418"],"issn-type":[{"value":"2075-4418","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,30]]}}}