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BackgroundWhite matter hyperintensities (WMH), a biomarker of small vessel disease, are often found in Alzheimer’s disease (AD) and their advanced detection and quantification can be beneficial for research and clinical applications. To investigate WMH in large-scale multicenter studies on cognitive impairment and AD, appropriate automated WMH segmentation algorithms are required. This study aimed to compare the performance of segmentation tools and provide information on their application in multicenter research.MethodsWe used a pseudo-randomly selected dataset (n = 50) from the DZNE-multicenter observational Longitudinal Cognitive Impairment and Dementia Study (DELCODE) that included 3D fluid-attenuated inversion recovery (FLAIR) images from participants across the cognitive continuum. Performances of top-rated algorithms for automated WMH segmentation [Brain Intensity Abnormality Classification Algorithm (BIANCA), lesion segmentation toolbox (LST), lesion growth algorithm (LGA), LST lesion prediction algorithm (LPA), pgs, and sysu_media] were compared to manual reference segmentation (RS).ResultsAcross tools, segmentation performance was moderate for global WMH volume and number of detected lesions. After retraining on a DELCODE subset, the deep learning algorithm sysu_media showed the highest performances with an average Dice’s coefficient of 0.702 (±0.109 SD) for volume and a mean F1-score of 0.642 (±0.109 SD) for the number of lesions. The intra-class correlation was excellent for all algorithms (>0.9) but BIANCA (0.835). Performance improved with high WMH burden and varied across brain regions.ConclusionTo conclude, the deep learning algorithm, when retrained, performed well in the multicenter context. Nevertheless, the performance was close to traditional methods. We provide methodological recommendations for future studies using automated WMH segmentation to quantify and assess WMH along the continuum of cognitive impairment and AD dementia.

Introduction: Knowledge about the distribution and frequency of the respective haplotypes on the wildtype and mutant allele is highly relevant in the context of future gene therapy clinical studies in Spinocerebellar Ataxia Type 3, the most common autosomal dominantly inherited ataxia. Single nucleotide polymorphisms associated to the disease-causing gene, ATXN3, have been determined. We wanted to investigate the frequency and regional distribution of two intragenic single nucleotide polymorphisms (SNPs) in a large European SCA3 cohort and their relation to the clinical phenotype., Methods: The genotypes of the two polymorphisms at base pair positions 987 and 1118 of the ATXN3 were determined for their co-localization on the normal and expanded allele, respectively, in 286 SCA3 mutation carriers and 117 healthy controls from 11 European sites., Results: The distribution of genotypes on the expanded allele differed from those of the wildtype allele of SCA3 mutation carriers and of healthy controls, and was mainly influenced by the regional origin. In our cohort, no particular clinical phenotype was associated with any specific haplotype., Conclusions: Our results confirm distinct allocations of SNPs associated to the expanded ATXN3, and accordingly the consideration of allele-specific therapies., Competing Interests: Declarations. Conflicts of interest: The authors declare that they have no competing interests. Ethical approval and consent to participate: The study was approved by the local ethics committees of all participating centers. Informed and written consent was obtained from all study participants at enrollment. Consent for publication: Not applicable., (© 2024. The Author(s).)

Background: Sporadic adult-onset ataxias without known genetic or acquired cause are subdivided into multiple system atrophy of cerebellar type (MSA-C) and sporadic adult-onset ataxia of unknown etiology (SAOA)., Objectives: To study the differential evolution of both conditions including plasma neurofilament light chain (NfL) levels and magnetic resonance imaging (MRI) markers., Methods: SPORTAX is a prospective registry of sporadic ataxia patients with an onset >40 years. Scale for the Assessment and Rating of Ataxia was the primary outcome measure. In subgroups, blood samples were taken and MRIs performed. Plasma NfL was measured via a single molecule assay. Regional brain volumes were automatically measured. To assess signal changes, we defined the pons and middle cerebellar peduncle abnormality score (PMAS). Using mixed-effects models, we analyzed changes on a time scale starting with ataxia onset., Results: Of 404 patients without genetic diagnosis, 130 met criteria of probable MSA-C at baseline and 26 during follow-up suggesting clinical conversion to MSA-C. The remaining 248 were classified as SAOA. At baseline, NfL, cerebellar white matter (CWM) and pons volume, and PMAS separated MSA-C from SAOA. NfL decreased in MSA-C and did not change in SAOA. CWM and pons volume decreased faster, whereas PMAS increased faster in MSA-C. In MSA-C, pons volume had highest sensitivity to change, and PMAS was a predictor of faster progression. Fulfillment of possible MSA criteria, NfL and PMAS were risk factors, CWM and pons volume protective factors for conversion to MSA-C., Conclusions: This study provides detailed information on differential evolution and prognostic relevance of biomarkers in MSA-C and SAOA. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society., (© 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.)

Objective: Neuropsychological impairments are major symptoms of autoimmune limbic encephalitis (LE) epilepsy patients. In LE epilepsy patients with an autoimmune response against intracellular antigens as well as in antibody-negative patients, the antibody findings and magnetic resonance imaging pathology correspond poorly to the clinical features. Here, we evaluated whether T- and B-cells are linked to cognitive impairment in these groups., Methods: In this cross-sectional, observational, case-controlled study, we evaluated 106 patients with adult-onset epilepsies with a suspected autoimmune etiology. We assessed verbal and visual memory, executive function, and mood in relation to the presence or absence of known auto-antibodies, and regarding T- and B-cell activity as indicated by flow cytometry (fluorescence-activated cell sorting = FACS, peripheral blood = PB and cerebrospinal fluid = CSF)., Results: 56% of the patients were antibody-negative. In the other patients, auto-antibodies were directed against intracellular antigens (GAD65, paraneoplastic: 38%), or cellular surface antigens (LGI1/CASPR2/NMDA-R: 6%). Excluding LGI1/CASPR2/NMDA-R, the groups with and without antibodies did not differ in disease features, cognition, or mood. CD4+ T-cells and CD8+ T-cells in blood and CD4+ T-cells in CSF were prominent in the auto-antibody positive group. Regression analyses indicated the role education, drug load, amygdala and/or hippocampal pathology, and CD4+ T-cells play in verbal memory and executive function. Depressed mood revealed no relation to flow cytometry results., Conclusion: Our results indicate a link between T- and B-cell activity and cognition in epilepsy patients with suspected limbic encephalitis, thus suggesting that flow cytometry results can provide an understanding of cognitive impairment in LE patients with autoantibodies against intracellular antigens.