Data-driven subtype classification of patients with early-stage multiple system atrophy

Data-Driven Subtypes of Multiple System Atrophy and Their Implications for Prognosis

Background

While multiple system atrophy (MSA) presents with high heterogeneous motor and nonmotor symptoms, the associations between clinical phenotypes and prognosis are unclear.

Objective

We aimed to evaluate clinical phenotypes of MSA using data-driven approach and measure the impact of phenotypes on survival and bedbound status.

Methods

193 MSA patients were recruited from Xuanwu Hospital Capital Medical University, whose history, motor and non-motor symptoms were examined using cluster analysis. Ninety-five participants were followed-up via telephone after a mean of 31.87 months. We employed Kaplan- Meier analysis to examine survival and performed Cox and logistic regression analyses to identify factors associated with survival and bedbound status.

Results

We identified four clinical profiles of MSA: cerebellar symptom-dominant, sleep and mood disorder-dominant, rigid akinetic-dominant, and malignant diffuse. The overall median survival was 7.75 years (95% CI 7.19-8.31). After adjusting for years from symptom onset to diagnosis, age and sex, patients in the malignant diffuse and rigid akinetic-dominant clusters had greater risk of death than sleep and mood disorder-dominant cluster. Furthermore, patients in the malignant diffuse and rigid akinetic-dominant clusters had higher risk of being bedbound than cerebellar symptom-dominant cluster.

Conclusions

The malignant diffuse and sleep and mood disorder-dominant were identified besides the two classical subtypes, parkinsonism, and cerebellar symptom-variant. Patients with rigid-akinetic motor profiles have a worse prognosis than cerebellar symptom-dominant profiles in general. Diffuse symptoms, especially postural instability, and cognitive alterations at diagnosis, indicate rapid functional loss and disease progression. The different profiles and prognoses might indicate varied underlying pathological mechanisms.

Identifying and verifying Huntington's disease subtypes: Clinical features, neuroimaging, and cytokine changes

AIMS

Huntington's disease (HD) is a progressive neurodegenerative disorder with heterogeneous clinical manifestations. Identifying distinct clinical clusters and their relevant biomarkers could elucidate the underlying disease pathophysiology.

METHODS

Following the Enroll-HD program initiated in 2018.09, we have recruited 104 HD patients (including 21 premanifest) and 31 health controls at Beijing Tiantan Hospital. Principal components analysis and k-means cluster analysis were performed to determine HD clusters. Chi-square test, one-way ANOVA, and covariance were used to identify features among these clusters. Furthermore, plasma cytokines levels and brain structural imaging were used as biomarkers to delineate the clinical features of each cluster.

RESULTS

Three clusters were identified. Cluster 1 demonstrated the most severe motor and nonmotor symptoms except for chorea, the lowest whole brain volume, the plasma levels of IL-2 were higher and significantly associated with cluster 1. Cluster 2 was characterized with the most severe chorea and the largest pallidum volume. Cluster 3 had the most benign motor symptoms but moderate psychiatric problems.

CONCLUSION

We have identified three HD clusters via clinical manifestations with distinct biomarkers. Our data shed light on better understanding about the pathophysiology of HD.

Heterogeneity of Multiple System Atrophy: An Update

Multiple system atrophy (MSA) is a fatal, rapidly progressing neurodegenerative disease of uncertain etiology, clinically characterized by various combinations of Levodopa unresponsive parkinsonism, cerebellar, autonomic and motor dysfunctions. The morphological hallmark of this α-synucleinopathy is the deposition of aberrant α-synuclein in both glia, mainly oligodendroglia (glial cytoplasmic inclusions /GCIs/) and neurons, associated with glioneuronal degeneration of the striatonigral, olivopontocerebellar and many other neuronal systems. Typical phenotypes are MSA with predominant parkinsonism (MSA-P) and a cerebellar variant (MSA-C) with olivocerebellar atrophy. However, MSA can present with a wider range of clinical and pathological features than previously thought. In addition to rare combined or “mixed” MSA, there is a broad spectrum of atypical MSA variants, such as those with a different age at onset and disease duration, “minimal change” or prodromal forms, MSA variants with Lewy body disease or severe hippocampal pathology, rare forms with an unusual tau pathology or spinal myoclonus, an increasing number of MSA cases with cognitive impairment/dementia, rare familial forms, and questionable conjugal MSA. These variants that do not fit into the current classification of MSA are a major challenge for the diagnosis of this unique proteinopathy. Although the clinical diagnostic accuracy and differential diagnosis of MSA have improved by using combined biomarkers, its distinction from clinically similar extrapyramidal disorders with other pathologies and etiologies may be difficult. These aspects should be taken into consideration when revising the current diagnostic criteria. This appears important given that disease-modifying treatment strategies for this hitherto incurable disorder are under investigation.