Wszołek, Zbigniew K.

Introduction Parkinson's disease (PD) and Dementia with Lewy Bodies (DLB) are progressive neurodegenerative disorders characterized by alpha-synuclein pathology. As current therapies largely target symptoms, there is a clear need for disease-modifying treatments. Emerging evidence links these disorders to glucose metabolism dysregulation, suggesting antidiabetic agents may hold therapeutic potential. Methods This was a prospective, randomized, double-blind pilot study involving 12 subjects with PD or DLB to evaluate the tolerability and preliminary effects of a dipeptidyl peptidase 4 (DPP4) inhibitor (sitagliptin 100 mg) vs. sodium glucose like transporter 2 (SGLT2) inhibitor (dapagliflozin 10 mg) over a 4-week period, compared to a placebo. We assessed changes in Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scores, cognitive function, and autonomic biomarkers. Both sitagliptin and dapagliflozin were well-tolerated, with no adverse events. While no significant changes were observed in cognitive scores, a significant difference was found in the change from baseline for MDS-UPDRS part 1 ( P = 0.008), part 2 ( P = 0.020), and total scores ( P = 0.047) when comparing the three groups. Discussion The dapagliflozin group showed more favorable trends in MDS-UPDRS scores. Limitations include small study size and duration as well as all participants had PD except one subject in the DPP4 inhibitor group with DLB. This pilot study suggests that these inhibitors are safe in PD and DLB patients. The preliminary findings, particularly the trends in the dapagliflozin group, provide a basis for larger-scale, long-term studies to confirm these potential symptomatic benefits and explore disease-modifying effects. Clinical trial registration https://clinicaltrials.gov/study/NCT06263673 , identifier: NCT06263673.

Abstract Background Progressive supranuclear palsy (PSP) is a tauopathy for which there is limited understanding of epidemiological risk factors. Objective The objective of this study was to identify premorbid nonmedical and medical risk factors for PSP diagnosis in a large prospective population‐based cohort. Methods We performed a matched nested case–control study using the UK Biobank (UKB) cohort consisting of >500,000 adults aged 37 to 73 years. PSP diagnoses were identified from 2007 to censor date (August 2025) and matched 1:10 by age and sex to control subjects without parkinsonism or dementia diagnoses. We derived risk factors using an iterative logistic regression approach. Results There were 240 incident PSP diagnoses in the UKB. In the fully adjusted model, premorbid depression (odds ratio [OR], 3.22; 95% confidence interval [CI], 2.30–4.50; P < 0.001), delirium (OR, 6.76; 95% CI, 4.08–11.19; P < 0.001), and functional gastrointestinal disorders (OR, 1.91; 95% CI, 1.39–2.63; P < 0.001) were associated with increased risk. Heavy alcohol consumption was associated with higher risk compared with moderate consumption (OR, 1.65; 95% CI: 1.21–2.26; P = 0.0017). Body mass index (BMI) and alcohol consumption had nonlinear risk profiles. Cancer diagnosis was inversely associated with PSP (OR, 0.56; 95% CI, 0.40–0.79; P < 0.001). Depression and delirium diagnoses remained significant 5 to 10 years before diagnosis. Conclusions In this large prospective cohort, PSP was associated with premorbid lifestyle practices and neuropsychiatric diagnoses years before diagnosis. This suggests a long premotor phase and highlights opportunities for earlier diagnosis and further mechanistic investigation. The inverse association with cancer mirrors the relationship seen in other neurodegenerative conditions and may point toward shared mechanisms. © 2026 International Parkinson and Movement Disorder Society.

Objective Pre‐mortem diagnosis of parkinsonism is often challenging due to atypical presentations, overlapping syndromes, and co‐pathologies. This study aimed to develop a machine learning‐based algorithm predicting neuropathology in parkinsonism using chronological clinical presentations, which has previously been underexplored. Methods Clinical information was automatically abstracted from medical records of the Mayo Clinic Brain Bank using fine‐tuned Generative Pre‐trained Transformer 4 models. Patients who developed parkinsonism within 3 years of disease onset were included. Six machine learning models were trained with age, sex, family history, and 197 clinical presentations paired with onset information to predict neuropathologic diagnoses, including co‐pathologies. Results Among 7,825 donors, 949 met inclusion criteria, representing 9 neuropathologic categories: Lewy body disease (LBD; n = 128), LBD with Alzheimer's disease (AD; n = 136), progressive supranuclear palsy (PSP; n = 303), PSP with AD (n = 56), PSP with LBD (n = 27), multiple system atrophy (MSA; n = 120), corticobasal degeneration (CBD; n = 99), AD (n = 43), and frontotemporal lobar degeneration (FTLD; n = 37). The CatBoost algorithm achieved an area under the receiver operating characteristic curve of 0.83 across the 9 diagnostic categories at 3 years after onset. Important predictors included age at onset, restricted eye movement, and tremor. The model remained robust to incomplete data, requiring only 23 of 200 parameters for reliable predictions with an area under the curve of 0.80. The algorithm was implemented into a user‐friendly program providing diagnostic probabilities with visualizations of parameter contributions. Interpretation This neuropathology‐confirmed diagnostic algorithm provides a cost‐effective and interpretable screening tool for parkinsonism, bridging biomarker testing and molecular‐targeted therapies. ANN NEUROL 2026;99:1405–1414

Abstract Background XK disease is a multisystem neurodegenerative disorder caused by mutations in the XK gene that codes for the lipid scramblase XK. Objective The aim was to describe the lipidomic spectrum in postmortem brain tissue from XK patients. Methods We measured the levels of 593 lipid species in the caudate nucleus (CN), putamen, and dorsolateral prefrontal cortex (DLPFC) from postmortem tissues of 5 XK patients and 6 controls. Results In XK patients, we observed increased levels of triacylglycerol, monoacylglycerol, phosphatidylserine, and ceramide in the CN. Acylated phosphatidylglycerol levels were reduced in both the CN and putamen. Acyl carnitine, dihydrosphingomyelin, and monosialodihexosylganglioside were reduced, whereas N ‐acyl phosphatidylethanolamine was increased in the DLPFC. N ‐Acyl serine was reduced in all three regions. Conclusions Our findings provide initial evidence of abnormal sphingolipid and phospholipid concentrations in the brains of XK patients and may provide insights into mechanisms of neurodegeneration in this disease. © 2026 International Parkinson and Movement Disorder Society.

Objective This longitudinal study evaluated the long-term efficacy and safety of hematopoietic stem cell transplantation (HSCT) in slowing the progression of CSF1R-related disorder (CSF1R-RD).Methods Six symptomatic patients (mean follow-up, 6.6 years) were compared with six matched, untreated controls. The CSF1R Clinical Severity Score (CCSS), Montreal Cognitive Assessment, and Sundal radiological score were used for evaluation.Results Post-HSCT clinical progression slowed significantly from 14.1 to 3.7 CCSS/year, compared with 15.2 CCSS/year in the control group (p<0.01). Cognitive decline was substantially reduced (-1.5 points/year vs. -7.6 points/year), and radiological deterioration slowed (0.4 per year vs. 3.9 per year). Notably, during the observation period, all HSCT patients survived, whereas 50% of the patients in the control group died. No serious transplant-related complications were observed.Conclusion HSCT is a potent disease-modifying therapy for CSF1R-RD that drastically improves survival and slows deterioration. These findings underscore the necessity of early intervention during the symptomatic phase to maximize the preservation of quality of life for affected individuals.

Abstract The human X chromosome accounts for ∼5% of the genome. Despite its size, the role of X-chromosomal variants in human diseases is not well understood, mainly due to its distinct inheritance pattern and the frequent omission of sex chromosomes from genome-wide association studies. This study used whole-genome sequencing data from 888 multiple system atrophy (MSA) cases and 7128 controls to perform an X-chromosome-wide common variant association study. Our analyses revealed two sex-differential risk loci: one located at Xq28, associated with increased risk for MSA in females [index variant: rs4898389, odds ratio (OR) = 1.69, 95% confidence interval (CI) = 1.40–2.03, P-value = 2.43 × 10⁻⁸], and another at Xp22.2 within the TBL1X gene, identified in males (index variant: rs6638956, OR = 1.48, 95%CI = 1.26–1.73, P-value = 9.92 × 10⁻⁷). In the Xq28 locus, colocalization analyses pointed to FAM3A and PLXNA3 as genes of interest. These findings emphasize the vital role of sex-differential genetic factors in the pathogenesis of MSA.

Objectives Multiple system atrophy (MSA) is classified into parkinsonian (MSA‐P) and cerebellar (MSA‐C) phenotypes based on predominant motor features, with corresponding pathological classifications of striatonigral (SN) degeneration and olivopontocerebellar (OPC) atrophy; however, disease progression patterns remain poorly understood. We aimed to identify novel MSA subtypes based on neuronal loss patterns using unsupervised machine learning. Methods We applied the Subtype and Stage Inference (SuStaIn) algorithm to analyze neuronal loss patterns in 167 autopsy‐confirmed MSA. Neuronal loss was semi‐quantitatively assessed in 5 brain regions: putamen, substantia nigra, pontine nucleus, inferior olivary nucleus, and cerebellar Purkinje cells. Obtained subtypes were validated by clinicopathological information. Results Three distinct subtypes were identified: SN‐early subtype (54% [86/160]) with initial SN neuronal loss, OPC‐early subtype (28% [44/160]) with early OPC involvement, and SN‐OPC‐synchronous subtype (19% [30/160]) with concurrent early neuronal loss in both systems. These subtypes corresponded well with clinical phenotypes. The SN‐OPC‐synchronous subtype exhibited significantly shorter survival (median 6.2 years vs 6.9 and 7.4 years in SN‐early and OPC‐early subtypes; p = 0.0049), more frequent rapid progression (57% vs 24% and 41% in SN‐early and OPC‐early subtypes; p = 0.0048), and more frequent early falls (70% vs 36% and 50% in SN‐early and OPC‐early subtypes; p = 0.0039). Immunohistochemical validation confirmed extensive α‐synuclein pathology in both SN and OPC systems in the SN‐OPC‐synchronous subtype. Interpretation The SN‐OPC‐synchronous subtype provides insights into α‐synuclein propagation mechanisms, suggesting multiple initial seeding sites rather than unidirectional spread. This computational approach uncovered disease heterogeneity undetectable by conventional methods, potentially benefiting clinical trials through patient stratification. ANN NEUROL 2026;99:989–1000