Multiple system atrophy: cure and care.

[Multiple system atrophy].

From clinical phenotypes to molecular precision: multimodal biomarkers for progressive supranuclear palsy

It is concluded that the shift from clinical-only diagnostic criteria to a biomarker-enabled molecular framework is the necessary catalyst for developing effective disease-modifying therapies for PSP and related 4R-tauopathies.

Clinicopathologic mismatch in young-onset parkinsonism: Multiple system atrophy masquerading as a neurotransmitter synthesis disorder.

BACKGROUND Multiple system atrophy (MSA) is a progressive adult-onset synucleinopathy that remains difficult to diagnose clinically, particularly in younger patients and during early disease stages. Brainstem nuclei degeneration resulting in reduced monoamines in cerebrospinal fluid (CSF) analysis may further complicate diagnostic interpretation. OBJECTIVES To describe a clinicopathologic case of early-onset MSA found to have decreased CSF monoamines suggestive of a primary neurotransmitter synthesis disorder. MATERIALS AND METHODS Clinical records, neuroimaging findings, CSF neurotransmitter analysis, and postmortem neuropathologic examination were reviewed. RESULTS A 41-year-old woman developed rapidly progressive parkinsonism, dystonia, dysphagia, and speech impairment. Broad CSF analysis was significant for reduced homovanillic acid (HVA), 5-hydroxyindoleacetic acid (5-HIAA), and tetrahydrobiopterin, raising concern for a monoamine synthesis defect and prompting treatment for sepiapterin reductase deficiency (SRD). Despite directed therapy, neurologic decline continued. Postmortem examination demonstrated neuropathologic findings consistent with MSA, parkinsonian subtype (MSA-P). Early cortical and allocortical amyloid-β deposition corresponding to Thal phase 2 was also identified. No additional proteinopathies were present. CONCLUSION Degeneration of dopaminergic and serotonergic nuclei in MSA can reduce CSF monoamine metabolite levels and mimic disorders of neurotransmitter biosynthesis despite correlation with tetrahydrobiopterin levels. This case highlights a potential diagnostic pitfall when interpreting CSF neurotransmitter studies in adults with parkinsonism.

FRONTOTEMPORAL DEMENTIA - COMPREHENSIVE INSIGHTS INTO PATHOGENESIS, DIAGNOSIS, AND INNOVATIVE TREATMENTS

Frontotemporal dementia (FTD) is a clinically and genetically diverse group of neurodegenerative disorders predominantly affecting the frontal and anterior temporal lobes, leading to progressive changes in behavior, language, and executive function. FTD is the most common cause of young-onset dementia and third overall among degenerative dementias, with a prevalence of 15–22 per 100,000 and an incidence of 2.7–4.1 per 100,000. The core clinical syndromes include the behavioral variant (bvFTD), semantic and nonfluent primary progressive aphasias (svPPA, nfvPPA), and overlap with motor disorders such as progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS). Genetic mutations, especially C9orf72, GRN, and MAPT, are responsible for most familial cases and involve proteinopathies with TDP-43, tau, and FUS proteins. Biomarkers (e.g., neurofilament light chain, progranulin) and neuroimaging are used to improve detection and differentiate subtypes, although reliable biomarkers are lacking. Management is largely supportive, with a combination of non-pharmacological therapies (e.g., exercise, speech and occupational strategies, behavioral tactics, caregiver education) and pharmacotherapy for neuropsychiatric symptoms. Clinical trials explore gene therapies and disease-modifying drugs, indicating a move towards personalized medicine. Despite major advances, obstacles persist for early detection and effective therapies, underlining the need for sustained multidisciplinary research in FTD. 

Predicting disease progression in progressive cerebellar ataxias: integrating clinical, imaging, fluid, genetic, and digital biomarkers

Progressive cerebellar ataxias, including the polyglutamine spinocerebellar ataxias (SCA1, SCA2, SCA3, and SCA6), Friedreich ataxia, and the autosomal recessive and sporadic forms, are rare, clinically heterogeneous neurodegenerative disorders. Disease-modifying therapies, notably antisense oligonucleotides and the approved compound omaveloxolone, are now entering or reaching the clinic, which makes reliable prediction of disease progression a central obstacle to trial success. Rarity, slow and variable decline, and a quantifiable premanifest window together demand sensitive, validated tools to forecast who will progress, how fast, and when symptoms begin. This review synthesizes evidence across five complementary biomarker domains, clinical, imaging, fluid, genetic, and digital, and judges their readiness for forecasting onset and progression. Clinical scales such as SARA capture genotype-specific trajectories but lose sensitivity at the extremes of the disease course. Volumetric, microstructural, and spectroscopic MRI and blood neurofilament light chain change before ataxia onset and predict subsequent decline, whereas repeat length and genetic modifiers set prior risk. Wearable-sensor gait and balance metrics detect change earlier than clinical scales and sharply reduce required sample sizes. We argue that no single modality satisfies every context of use, and that stage-specific, multimodal composites, integrated through harmonized international cohorts and machine learning, offer the most credible path to prognostic enrichment and to shorter, adequately powered, and preventive trials.

Plasma neurofilament light for early differentiation of multiple system atrophy from Parkinson disease

Summary Background Early differentiation of multiple system atrophy (MSA) from Parkinson's disease (PD) remains difficult, particularly within two years of symptom onset, when diagnostic uncertainty has major implications for prognosis, referral, and trial enrolment. Because MSA is rare, previous biomarker studies have often been limited by relatively small samples and restricted multicentre validation. We aimed to determine the diagnostic performance of plasma neurofilament light chain (NfL) for differentiating MSA from PD and to assess the incremental value of glial fibrillary acidic protein (GFAP), total tau (t-tau), and phosphorylated tau at threonine 217 (p-tau217). Methods In this multicentre cross-sectional diagnostic study, participants were enrolled from five movement-disorder referral centres in China between Jan 1, 2018, and June 30, 2024, and were divided by enrolment period into discovery and temporally separated validation datasets. Plasma NfL, GFAP, t-tau, and p-tau217 were measured using light-initiated chemiluminescence assays. Group comparisons used age- and sex-adjusted models, and discrimination was assessed using receiver-operating-characteristic analysis with sensitivity, specificity, predictive values, and robustness analyses. Findings The analysis included 2408 participants: 782 (32.5%) with PD, 796 (33.1%) with MSA, and 830 (34.5%) healthy controls. NfL was the best single biomarker for differentiating MSA from PD in the discovery dataset (AUC 0.920, 95% CI 0.903–0.936). The discovery-derived cutoff of 41.3 pg/mL yielded sensitivity of 90.5% and specificity of 83.4% in the discovery dataset, and sensitivity of 86.7% and specificity of 85.5% in the validation dataset (AUC 0.924, 95% CI 0.898–0.948). In the early-stage subgroup, NfL retained strong performance (AUC 0.943, 95% CI 0.915–0.966). Integrated multimarker models provided limited incremental discrimination over NfL alone. Interpretation Plasma NfL may support the differentiation between clinically diagnosed MSA and PD, including early in the disease course. The limited added value of multimarker panels supports a simpler and more immediately translatable NfL-first strategy for diagnostically uncertain parkinsonism. Funding National Natural Science Foundation of China; the Capital's Fund for Health Improvement and Research; Beijing Natural Science Foundation; Beijing Municipal Science and Technology Commission; Beijing Neurosurgical Institute; Beijing Traditional Chinese Medicine Science and Technology Development Fund.