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Late-onset multiple system atrophy: Neuropathological features associated with slow disease progression
Misato Ozawa1,2, Rie Saito1, Takuya Konno3,4
1Department of Pathology, Brain Research Institute, Niigata University, Niigata, Japan.
Abstract:
Patients with late-onset (LO) multiple system atrophy (MSA), whose initial symptoms appear at age 75 years or older, are more common than previously assumed, but their clinicopathological characteristics remain unclear. We aimed to clarify the clinicopathological features of LO-MSA. Of 102 patients with autopsy-confirmed MSA, 5 were identified as having LO-MSA and 24 as having usual-age-onset MSA (UO-MSA) with a similar disease duration. On the basis of previous reports, we defined UO-MSA as the appearance of initial symptoms between the ages of 55 and 65 years. We compared the clinical pictures of the two groups and assessed their histopathological features using quantitative and semi-quantitative methods. The investigated features included the severity of degeneration in the striatonigral (StrN) and olivopontocerebellar (OPC) systems, the numbers of neurons in the brainstem autonomic and spinal intermediolateral nuclei, and the density of α-synuclein-immunopositive inclusions in the putamen, inferior olivary nucleus, and ventrolateral medulla (VLM). Most patients with both LO-MSA and UO-MSA exhibited the MSA-olivopontocerebellar atrophy (OPCA) subtype (3/5 and 18/24, respectively). The median disease duration for LO-MSA patients was 5.5 years, which was comparable to that for patients in our cohort who had developed symptoms below 75 years of age. Pathologically, degeneration of the StrN and OPC systems in LO-MSA was less severe than that observed in UO-MSA. Quantitative analysis revealed better preservation of neuron numbers in the brainstem autonomic nuclei in LO-MSA than in UO-MSA, with a significantly higher number of serotonergic neurons in the VLM (p = 0.013). The density of α-synuclein-positive inclusions in the putamen was significantly lower in LO-MSA than in UO-MSA (p < 0.001). Neuronal degeneration in LO-MSA may progress more slowly than in UO-MSA. Accordingly, the prognosis of LO-MSA may not necessarily be less favorable than that of MSA generally, especially with appropriate care.
Insights
Late-onset multiple system atrophy (LO-MSA) shows less severe neurodegeneration and potentially slower progression than usual-age-onset MSA (UO-MSA). This suggests LO-MSA may have a comparable prognosis to general MSA cases with proper care.
Area of Science:
- Neurology
- Pathology
- Geriatrics
Background:
- Late-onset multiple system atrophy (LO-MSA), with symptom onset at age 75+, is more prevalent than previously thought.
- Clinicopathological characteristics of LO-MSA are not well-defined, necessitating further investigation.
Purpose of the Study:
- To elucidate the clinicopathological features of late-onset multiple system atrophy (LO-MSA).
- To compare the clinical and pathological differences between LO-MSA and usual-age-onset MSA (UO-MSA).
Main Methods:
- Compared clinical and histopathological features of 5 LO-MSA patients with 24 UO-MSA patients (similar disease duration).
- Assessed degeneration severity in striatonigral (StrN) and olivopontocerebellar (OPC) systems.
- Quantified neuron numbers in brainstem autonomic nuclei and spinal intermediolateral nuclei.
- Measured α-synuclein inclusion density in the putamen, inferior olivary nucleus, and ventrolateral medulla (VLM).
Main Results:
- Both LO-MSA and UO-MSA predominantly showed the MSA-olivopontocerebellar atrophy (OPCA) subtype.
- LO-MSA exhibited less severe StrN and OPC system degeneration compared to UO-MSA.
- LO-MSA had better preservation of brainstem autonomic neurons, particularly serotonergic neurons in the VLM (p=0.013).
- LO-MSA showed significantly lower α-synuclein inclusion density in the putamen (p<0.001).
Conclusions:
- Neuronal degeneration in LO-MSA appears to progress more slowly than in UO-MSA.
- The prognosis for LO-MSA may not be inherently worse than for MSA overall, especially with adequate medical management.
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