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. Author manuscript; available in PMC: 2025 Feb 1.
Published in final edited form as: Mov Disord. 2023 Nov 20;39(2):380–390. doi: 10.1002/mds.29670

Frequency of comorbid pathologies and their clinical impact in multiple system atrophy

Hiroaki Sekiya 1, Shunsuke Koga 1, Aya Murakami 1, Michael DeTure 1, Owen A Ross 1, Ryan J Uitti 2, William P Cheshire 2, Zbigniew K Wszolek 2, Dennis W Dickson 1
PMCID: PMC10922743  NIHMSID: NIHMS1944541  PMID: 37986699

Abstract

Background:

Mixed pathology is common at autopsy for a number of age-associated neurodegenerative disorders; however, the frequency of comorbid pathologies in multiple system atrophy (MSA) and their clinical correlations are poorly understood.

Objective:

We determined the frequency of comorbid pathologic processes in autopsy-confirmed MSA and assessed their clinical correlates.

Methods:

This study included 160 neuropathologically established MSA from the Mayo Clinic brain bank. Clinical information, including age at onset or death, clinical subtype, initial symptoms, antemortem clinical diagnosis, and cognitive dysfunction was collected. We assessed comorbid pathologies including Alzheimer’s disease neuropathologic change, Lewy-related pathology, argyrophilic grain disease, age-related tau astrogliopathy, transactive DNA-binding protein 43 pathology, cerebral amyloid angiopathy, and cerebrovascular small vessel disease and examined their clinical impact.

Results:

The majority of MSA patients (62%) had no significant comorbid pathologies. There was a positive correlation between age at onset or death with the number of comorbid pathologies; however, even in the highest quartile group (average age at death 78 ± 6 years), the average number of comorbid pathologies was less than 2. Logistic regression analysis revealed that none of the assessed variables, including sex, age at onset, and the presence or absence of each comorbid pathology, were significantly associated with cognitive dysfunction.

Conclusions:

The majority of MSA patients do not have comorbid pathologies, even in advanced age, indicating that MSA is unique among neurodegenerative disorders in this regard. There was minimal clinical impact of comorbid pathologies in MSA. These findings warrant focusing on alpha-synuclein for the treatment strategy for MSA.

Introduction

Multiple system atrophy (MSA) is an adult-onset neurodegenerative disorder clinically characterized by various degrees of autonomic dysfunction, parkinsonism, and cerebellar ataxia.1, 2 The presence of glial3, 4 and neuronal5, 6 inclusions which consist of α-synuclein is a pathological hallmark of MSA. MSA is categorized as synucleinopathy along with Parkinson’s disease and dementia with Lewy bodies.7, 8 Recently, the misfolding and accumulation of proteins have been considered a cause of neurodegenerative disorders.9, 10 In addition to α-synuclein, the causative proteins include amyloid-beta, tau, and transactive DNA-binding protein 43 (TDP-43). Since many neurodegenerative disorders occur later in life, it is not uncommon to find multiple pathologic processes at autopsy. The frequency of cerebrovascular pathology also increases with age, which may affect the clinical presentation of neurodegenerative disorders.11 Coexisting pathologies have been reported in other neurodegenerative disorders, including dementia with Lewy bodies (DLB), Alzheimer’s disease (AD), and progressive supranuclear palsy (PSP).12–16

Co-existence of PSP with MSA has been reported in several case reports17-19. Uchikado et al. reported one concomitant MSA in 290 PSP18. Silveira-Moriyama et al. also reported one case of PSP and MSA from a brain bank of 120 PSP and 36 MSA19. A few small case series to examine comorbid pathologies in MSA have been reported as well14, 20. Dugger et al. examined comorbid pathologies in parkinsonian disorders including 7 MSA. In their study, AD pathology and argyrophilic grains, cerebral amyloid angiopathy (CAA) were found in 14% (1/7) of MSA patients, respectively20. Robinson et al. reported comorbid pathologies in various neurodegenerative diseases including 26 MSA patients. In their research, 92% of MSA patients had neurofibrillary tangle (NFT), 38% had amyloid-beta, and 4% had TDP-43 pathology14.

To our knowledge, no study has comprehensively examined comorbid pathologies of MSA in a large number of cases. Therefore, in the present study, we assessed seven comorbid pathologies including AD neuropathologic change (ADNC), Lewy-related pathology, argyrophilic grain disease, age-related tau astrogliopathy (ARTAG), TDP-43 pathology, CAA, and small vessel disease in a large autopsy series of MSA and investigated their clinical correlates.

Methods

Subjects

Of the 212 consecutive MSA cases in the brain bank between 1998 and 2017, we excluded 52 cases because of inadequate clinical information. The remaining 160 cases had available medical records for systematic review. A subset of the cases was included in previous studies of TDP-43 pathology in MSA21, Lewy-related pathology in MSA22, or chronic traumatic encephalopathy and ARTAG in MSA23. MSA patients were divided into quartiles based on age at onset (AAO) and designated as AAO-Q1, AAO-Q2, AAO-Q3, and AAO-Q4, with 40 cases in each subgroup. Given that age at death (AAD) may affect pathological findings, patients were also divided into quartile subgroups according to AAD (AAD-Q1, AAD-A2, AAD-Q3, and AAD-Q4). We examined the association between AAO and AAD with comorbid pathologies using both the approach of using these quartile subgroups and treating age as a continuous variable.

Brain autopsies were conducted with the consent of the legal next-of-kin or an individual with legal authority to grant permission for autopsy. Most cases were sent from referring pathologists or dieners. A subset of autopsies was performed at Mayo Clinic. In most cases, half of the brain (usually the left side) was fixed for histopathologic studies and the other half was frozen. De-identified studies using autopsy samples are considered exempt from human subject research by the Mayo Clinic Institutional Review Board.

Clinical information

We systematically reviewed available medical records of each case.24 We also abstracted data from brain bank questionnaires filled out by family members or someone with close personal knowledge of the patient. The following clinical information was collected: sex, AAO, AAD, initial symptoms, clinical subtype, antemortem clinical diagnosis, and the presence of cognitive dysfunction. Based on the core clinical features in the MSA Movement Disorder Society criteria2, initial symptoms were categorized as parkinsonism, cerebellar symptoms, urinary retention, urinary incontinence, or neurogenic orthostatic hypotension. We determined whether motor symptoms or autonomic dysfunction presented first. Patients with simultaneous onset of motor symptoms and autonomic dysfunction were classified as simultaneous onset. Clinical subtype was determined based on the predominant motor symptom. MSA-P was defined as a clinical syndrome with predominant parkinsonism, and MSA-C was defined as a clinical syndrome with predominant cerebellar ataxia. Following our previous method25, cognitive dysfunction was considered present if one or more of the following symptoms were diagnosed by a physician: memory loss, forgetfulness, distractibility, word-finding difficulty, difficulty with naming, slowed thinking, bradyphrenia, disorientation, or executive dysfunction. They were also considered present if they were endorsed by family members, most often with information provided with the brain bank questionnaire, as free-form comments or responses to dichotomous questions.

Neuropathological evaluation

All cases underwent a standardized neuropathologic assessment that included histologic evaluation of hematoxylin & eosin stained sections. Immunohistochemistry was performed with a DAKO Autostainer. The following antibodies were used for immunohistochemistry: α-synuclein – NACP (Mayo Clinic rabbit polyclonal, 1:3000, with formic acid pretreatment); phospho-tau – CP13 (mouse monoclonal; 1:1000; from the late Dr. Peter Davies; Feinstein Institute for Medical Research); phosphorylated TDP-43 – pS409/410 (mouse monoclonal, 1:5000, CosmoBio USA, Carlsbad, CA).

The neuropathological diagnosis of MSA required widespread and frequent glial cytoplasmic inclusions, as well as neuronal loss and gliosis in striatonigral or olivopontocerebellar systems, or both.26 The pathological subtype of MSA was determined based on the severity of affected regions; striatonigral degeneration (MSA-SND) had the most severe pathology in the striatonigral regions, olivopontocerebellar atrophy (MSA-OPCA) had the most severe pathology in the olivopontocerebellar regions, and MSA-mixed had equal involvement of striatonigral and olivopontocerebellar regions.

Braak NFT stage27 and Thal amyloid phase28 were assessed by thioflavin S fluorescent microscopy. In this study, the presence of ADNC was determined based on the Mayo Clinic Florida National Institute on Aging-Alzheimer’s Association (NIA-AA) operational criteria29, which were adapted from the NIA-AA criteria30. Briefly, we calculated a composite AD-score using Braak NFT stage and Thal amyloid phase. Patients with Thal phase 0 or Braak NFT 0 were classified as ‘no’, Thal phase 1–2 and Braak NFT I-VI or Thal phase 3–5 and Braak NFT I–II as ‘low’, Thal phase 3 and Braak NFT III–VI or Thal 4–5 and Braak III–IV as ‘intermediate’ and Thal phase 4–5 and Braak NFT V–VI as ‘high’. ADNC was defined as present when the AD-score was classified as intermediate or high. The presence of CAA was assessed with thioflavin S fluorescent microscopy in frontal, temporal, parietal, motor, and visual cortices. The severity of CAA in cortical vessels was assessed on a semi-quantitative scale from 0 (none) to 3 (severe) in each cortex. Argyrophilic grain disease was diagnosed by presence of tau-positive (argyrophilic) grains, oligodendroglial coiled bodies, bush-like astrocytes, balloon neurons, and pretangles in the medial temporal lobe structures.31 ARTAG was defined as thorn-shaped astrocytes (TSA) or granular / fuzzy astrocytes (GFA) in subependymal, subpial, perivascular, gray matter, and white matter.32 Lewy-related pathology, including Lewy bodies and Lewy neurites, was evaluated with α-synuclein immunohistochemistry and staged according to Kosaka33 and McKeith et al.34 Lewy bodies were distinguished from neuronal cytoplasmic inclusions of MSA as well-circumscribed round inclusions in neuronal perikarya visible on hematoxylin & eosin and positive on α-synuclein immunohistochemistry. Lewy neurites were defined as α-synuclein positive neuronal cell processes.35 The presence of TDP-43 pathology was screened in the section including the amygdala, basal forebrain, putamen, globus pallidus, and hypothalamus at the level of the anterior commissure and was considered present if there were neuronal cytoplasmic inclusions, glial cytoplasmic inclusions, dystrophic neurites, fine neurites, neuronal intranuclear inclusions spheroids, or perivascular inclusions.36 Patients with positive TDP-43 pathology in the screening section were also evaluated for TDP-43 pathology in the hippocampus, midbrain, pons, cerebellum, and motor cortex. Small vessel disease was assessed on hematoxylin & eosin stained sections and diagnosed based on the presence of arteriolosclerosis with microinfarcts, microbleeds, or ischemic white matter changes.

The presence of each comorbid pathology and the number of comorbid pathologies were compared in MSA patients with and without cognitive dysfunction.

Genetic information

Genomic DNA was extracted from the frozen cerebellar tissue using the AutoGen 245T platform. APOE genotype was determined based on the two single nucleotide polymorphisms, rs7412 and rs429358, while MAPT H1/H2 haplotype status was defined by the variant rs8070723.

Statistical analysis

Statistical analyses were performed with R 4.2.237 and GraphPad Prism (version 9.2.0, GraphPad Software, La Jolla, CA, USA). A Mann-Whitney rank sum test was used for continuous variables and Fisher exact test was used for categorical variables. Three-group or quartile subgroup comparisons used ordinary one-way analysis of variance with Tukey's post hoc analysis for continuous variables and Kruskal-Wallis test followed by Dunn's post hoc analysis for non-normally distributed continuous variables. For categorical variables, we used Fisher's exact test with Bonferroni adjustment. Correlation between number of comorbid pathologies, Braak NFT stage, Thal amyloid phase, AAO, AAD, and disease duration was examined using Spearman rank order correlation. Multivariate logistic regression analysis was used to identify variables independently correlated with antemortem diagnostic accuracy and the presence of cognitive dysfunction in MSA. Statistical significance was set at a P-value < 0.05.

Results

Demographics and clinical characteristics

Table 1 summarizes demographic, clinical, and pathological features of the 160 patients included in this study. Antemortem clinical diagnosis of MSA was made in 102 patients, while MSA was in the clinical differential diagnosis of an additional 30 patients. The diseases listed as differential diagnoses alongside MSA were as follows: PSP in 13 patients, PSP or corticobasal degeneration (CBD) in 3 patients, CBD in 3 patients, Parkinson’s disease in 9 patients, and DLB in 2 patients, respectively. The remaining patients (N=28) had antemortem clinical diagnoses of other disorders, including PSP (15 patients), Parkinson’s disease (8 patients), and DLB (1 patient). Cognitive dysfunction of at least a mild degree at some time during their disease course was noted in 48 patients (30%). Of the 48 cases with cognitive dysfunction, 24 were judged to have cognitive dysfunction based on physician assessment, 19 based on physician assessment and family report, and 5 based solely on family report, respectively.

Table 1.

Demographic, clinical, and pathological features

Features All patients (N = 160)
Female sex 44% (70)
Age at onset (years) 59 ± 9
Age at death (years) 67 ± 8
Disease duration (years) 7 ± 3
Clinical subtype
 MSA-P 79% (126)
 MSA-C 21% (34)
Clinical diagnosis
 MSA 64% (102)
 MSA vs others 19% (30)
 Other than MSA 18% (28)
Cognitive dysfunction 30% (48)
Brain Weight (g) 1220 ± 160
Pathological subtype
 MSA-SND 42% (67)
 MSA-OPCA 17% (27)
 MSA-mixed 41% (66)
Braak NFT stage I (I, II)
Thal amyloid phase 0 (0, 2)
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Data are % (n), mean ± SD, or median (25th, 75th percentile). MSA, multiple system atrophy; P, parkinsonian type; C, cerebellar type, SND, striatonigral degeneration; OPCA, olivopontocerebellar atrophy; NFT, neurofibrillary tangle

Pathological features and comorbid pathologies

The frequency of each comorbid pathology is illustrated graphically in Figure 1A. Among 160 MSA patients, 8% (12/160) had ADNC, 5% (8/160) had Lewy-related pathology, 8% (12/160) had argyrophilic grain disease, 9% (14/160) had ARTAG, 7% (11/160) had TDP-43 pathology, 18% (29/160) had CAA, and 8% (12/160) had small vessel disease.

Figure 1. Comorbid pathologies in total patients.

Figure 1

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(A) The bars demonstrate frequency of each comorbid pathology in MSA. Among comorbid pathologies examined in this study, CAA was most often observed.

(B) The bar graph shows the distribution of the number of comorbid pathologies: 66% of MSA patients had no comorbid pathology, 19% had 1, 12% had 2, 2% had 3, and 1% had 4.

(C) The left bar shows the distribution of patients with each Braak NFT stage and the right bar shows that of Thal amyloid phase.

ADNC, Alzheimer’s disease neuropathologic change; ARTAG, age-related tau astrogliopathy; TDP-43, transactive response DNA binding protein 43 kDa; CAA, cerebral amyloid angiopathy; SVD, small vessel disease; NFT, neurofibrillary tangle

In this study, 62% (99/160) had no significant comorbid pathologies; 21% (34/160) had one, 13% (20/160) had two, 3% (5/160) had three, 1% (1/160) had four, and 1% (1/160) had five comorbid pathologies (Figure 1B). The combinations of comorbid pathologies were diverse, and no obvious tendency was observed (Supporting Information Table S1). Braak NFT stage and Thal amyloid phase are summarized in Figure 1C. The distribution of Braak NFT stage is as follows: 0 in 17%, I in 34%, II in 28%, III in 14%, IV in 4%, V in 3%, and VI in 1%. The distribution of Thal amyloid phase is as follows: 0 in 54%, 1 in 13%, 2 in 12%, 3 in 14%, 4 in 6%, and 5 in 1%. The distribution of AD-score was as follows: none in 59, low in 33%, intermediate in 5%, and high in 3%. The distribution pattern of Lewy-related pathology was brainstem-predominant in 6 patients and transitional in 2 patients. No patients had diffuse distribution of Lewy-related pathology. ARTAG types and distribution were as follows: subpial TSA in the middle frontal gyrus in 5, subpial TSA in the superior temporal gyrus in 3, perivascular TSA in the superior temporal gyrus in 1, perivascular GFA in inferior parietal gyrus in 1, subpial TSA in the posterior hippocampus in 1, subpial TSA in the forebrain in 10, subpial TSA in the amygdala in 5, and subpial TSA in the hypothalamus in 2. TDP-43 pathology distribution in the 11 TDP-43 positive patients was as follows: amygdala only in 6; amygdala and hippocampus in 2; amygdala, hippocampus, and midbrain in 1; basal forebrain, hippocampus, midbrain, and pontine nucleus in 1; amygdala, basal forebrain, hippocampus, midbrain, pontine nucleus, cerebellar white matter, and motor cortex in 1. Among comorbid pathologies examined in this study, CAA was most frequent. Of the 29 patients with CAA observed in cortical vessels, 25 patients had mild (1+) CAA in any of the cortices and 4 patients had moderate (2+) CAA in the occipital cortex. No patients showed severe (3+) CAA in any cortices, and overall CAA severity was mild.

We also compared the frequency and number of comorbid pathologies among pathological subtypes of MSA. (Supporting Information Table S2). The frequency of each comorbid pathology and the number of comorbid pathologies did not differ significantly among pathological subtypes.

Correlation between age at onset and comorbid pathologies

We examined the association between AAO and comorbid pathologies using Braak NFT stage, Thal amyloid phase, number of comorbid pathologies, and frequency of each comorbid pathology.

There was a significant positive correlation between AAO and both Braak NFT stage and Thal amyloid phase (Figure 2A; r = 0.42, P < 0.0001 and r = 0.29, P = 0.0002, respectively). Table 2 summarizes the frequency of each comorbid pathology in the quartile subgroups based on AAO. Braak NFT stage was significantly higher in AAO-Q4 than in AAO-Q1 and in AAO-Q2 (Figure 2B; P < 0.0001 and P = 0.0024), while Thal amyloid phase was significantly higher in AAO-Q3 than in AAO-Q1 and AAO-Q2 (Figure 2B; P = 0.0064 and P = 0.0095).

Figure 2. Correlation between comorbid pathologies and age at onset.

Figure 2

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(A) Each graph shows the correlation between AAO and Braak NFT stage, Thal amyloid phase, or the number of comorbid pathologies. There is positive correlation between AAO and Braak NFT stage (r = 0.42), Thal amyloid phase (r = 0.29), and the number of comorbid pathologies (r = 0.45).

(B) The bars show the distribution of Braak NFT stage, Thal amyloid phase, and the number of comorbid pathologies in the quartile subgroups of AAO. The Braak NFT stage is significantly higher in AAO-Q4 than in AAO-Q1 and in AAO-Q2 (P < 0.0001 and P = 0.0024). Thal amyloid phase is significantly higher in AAO-Q3 than in AAO-Q1 and AAO-Q2 (P = 0.0064 and P = 0.0095). The number of comorbid pathologies is significantly higher in AAO-Q4 than in AAO-Q1 and AAO-Q2 (P < 0.0001 and P = 0.0003).

(C) The bars show the frequency of each comorbid pathology in the quartile subgroups of AAO. ADNC is more frequently observed in AAO-Q4 than in AAO-Q1 (P = 0.032).

NFT, neurofibrillary tangle; ADNC, Alzheimer’s disease neuropathologic change; ARTAG, age-related tau astrogliopathy; TDP-43, transactive response DNA binding protein 43 kDa; CAA, cerebral amyloid angiopathy; SVD, small vessel disease; AAO, age at onset

Table 2.

Comorbid pathologies in quartile age-at-onset subgroups

AAO-Q1 AAO-Q2 AAO-Q3 AAO-Q4
Number of comorbid pathologies, median (25th and 75th percentile) 0 (0, 0) 0 (0, 0) 0 (0, 1) 1 (0, 2)
Braak NFT stage, median (25th and 75th percentile) I (0, II) I (I, II) II (I, II) II (I, III)
Thal amyloid phase, median (25th and 75th percentile) 0 (0, 1) 0 (0, 1) 2 (0, 3) 1 (0, 3)
ADNC (%, N) 0% (0) 3% (1) 8% (3) 20% (8)
Lewy-related pathology (%, N) 3% (1) 0% (0) 10% (4) 8% (3)
Argyrophilic grain disease (%, N) 5% (2) 5% (2) 5% (2) 15% (6)
ARTAG (%, N) 3% (1) 5% (2) 5% (2) 23% (9)
TDP-43 (%, N) 3% (1) 5% (2) 5% (2) 15% (6)
CAA (%, N) 8% (3) 13% (5) 25% (10) 30% (12)
Small vessel disease (%, N) 3% (1) 3% (1) 10% (4) 15% (6)
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AAO, age at onset; NFT, neurofibrillary tangle; ADNC, Alzheimer’s disease neuropathologic change; ARTAG, age-related tau astrogliopathy; TDP-43, transactive response DNA binding protein 43 kDa; CAA, cerebral amyloid angiopathy

There was also a significant positive correlation between the number of comorbid pathologies and AAO (Figure 2A; r = 0.42, P < 0.0001). The number of comorbid pathologies was significantly higher in AAO-Q4 than in AAO-Q1 and AAO-Q2 (Figure 2B; P < 0.0001 and P = 0.0003).

Regarding each comorbid pathology, ADNC was significantly more frequent in AAO-Q4 than in AAO-Q1 (Figure 2C, 20% vs. 0%; P = 0.032). Although Lewy-related pathology, argyrophilic grain disease, ARTAG, TDP-43, CAA, and small vessel disease tended to increase in frequency as the AAO advanced, the difference did not reach significance.

Correlation between age at death and comorbid pathologies

We considered the possibility that AAD might affect the frequency of comorbid pathologies. There was a significant positive correlation between AAD and Braak NFT stage and Thal amyloid phase (data not shown; r = 0.46, P < 0.0001 and r = 0.28, P = 0.0003, respectively). The frequency of each comorbid pathology in the quartile subgroups based on AAD was examined (Supporting Information Table S3). Braak NFT stage was significantly higher in AAD-Q4 compared to in AAD-Q1 and in AAD-Q2 (P < 0.0001 and P = 0.023). Thal amyloid phase was significantly lower in AAD-Q1 than in AAD-Q3 and AAD-Q4 (P = 0.047 and P = 0.047).

There was also a significant positive correlation between AAD and the number of comorbid pathologies (data not shown; r = 0.46, P < 0.0001). There were significantly more comorbid pathologies in AAD-Q4 than in the other subgroups (P < 0.0001, P = 0.0003, and P = 0.042) and in AAD-Q3 than in AAD-Q1 (P = 0.027).

Regarding each comorbid pathology, ADNC was significantly more frequent in AAD-Q4 compared to in AAD-Q1 and in AAD-Q2 (P= 0.014 and P = 0.014); CAA was significantly more frequent in AAD-Q4 than in AAD-Q1 (P = 0.0018); and small vessel disease was significantly more often observed in AAD-Q4 compared to in AAD-Q2 (P = 0.032).

Clinical impact of comorbid pathologies

We evaluated the clinical impact of comorbid pathologies and their correlations from the following five perspectives: disease duration, clinical subtypes, initial symptoms, accuracy of antemortem diagnosis, and cognitive dysfunction.

We found no significant correlation between disease duration and number of comorbid pathologies. There was also no significant correlation with disease duration for Braak NFT stage and Thal amyloid phase.

Next, we compared the frequency and number of comorbid pathologies between clinical subtypes (MSA-P and MSA-C). There was no significant difference in the frequency of each comorbid pathology. The number of comorbid pathologies also did not differ between MSA-P and MSA-C.

In addition, we examined the correlation between comorbid pathologies and initial symptoms. One patient with aphasia as the initial symptom was excluded from the analysis. Motor symptoms were the initial symptoms in 112 patients, autonomic dysfunction in 32 patients (urinary issues in 22, orthostatic hypotension in 7, and both in 3), and simultaneous onset of motor symptoms and autonomic dysfunction in 15 patients. Although there was no significant difference in the frequency of each comorbid pathology, the number of comorbid pathologies were significantly higher in patients with simultaneous onset of motor symptoms and autonomic dysfunction (median 1) compared to those with motor onset (median 0, P = 0.048) and autonomic onset (median 0, P = 0.03).

The correlation between antemortem diagnostic accuracy and comorbid pathologies was examined. The diagnostic accuracy was significantly lower in patients with comorbid pathologies compared to those without (48% vs. 73%, P = 0.002). There was a significant difference only in the frequency of ADNC, where ADNC was more frequent in patients without correct antemortem clinical diagnosis (14% vs. 4%, P = 0.03). Braak NFT stage was also significantly higher in patients without correct antemortem diagnosis (median II vs. I, P = 0.04). To determine contributing factors to antemortem diagnostic accuracy, we performed multiple logistic regression analysis with the number of comorbid pathologies, presence of ADNC, Braak NFT stage, AAO, and sex. Only AAO significantly contributed, while comorbid pathologies did not show significant correlations.

In the present study, 30% (48/160) of patients had cognitive dysfunction. Therefore, we divided the patients into two groups according to the presence or absence of cognitive dysfunction. Braak NFT stage and Thal amyloid phase, number of comorbid pathologies did not significantly differ between the two groups (Figure 3A). Among comorbid pathologies, only ADNC was more frequent in MSA patients with cognitive dysfunction compared to those without (Figure 3B; 15% vs. 4%; P = 0.04). We conducted a logistic regression analysis to examine potential factors contributing to cognitive dysfunction in MSA. The variables included sex, AAO, Braak NFT stage, Thal amyloid phase, and the presence or absence of each comorbid pathology. None of the variables were significantly associated with cognitive dysfunction in MSA.

Figure 3. Correlation between comorbid pathologies and cognitive dysfunction.

Figure 3

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(A) The bars show the distribution of Braak NFT stage, Thal amyloid phase, and the number of comorbid pathologies in patients with and without cognitive dysfunction. No significant difference is observed.

(B) The bars show the frequency of each comorbid pathology in patients with and without cognitive dysfunction. ADNC is more frequent in patients with cognitive dysfunction compared to those without (P = 0.044).

NFT, neurofibrillary tangle; CDF, cognitive dysfunction; ADNC, Alzheimer’s disease neuropathologic change; ARTAG, age-related tau astrogliopathy; TDP-43, transactive response DNA binding protein 43 kDa; CAA, cerebral amyloid angiopathy; SVD, small vessel disease

Correlation between genetic information and comorbid pathologies

APOE genotype and MAPT haplotype data were available in 145 and 146 of cases, respectively, when frozen tissue was available. We examined Braak NFT stage, Thal amyloid phase, number of comorbid pathologies, and the frequency of each comorbid pathology in APOE genotypes and MAPT haplotypes. There were significant differences between APOE genotypes with Thal amyloid phase and the frequency of CAA (Supporting Information Table S4), and no significant differences between MAPT haplotypes (Supporting Information Table S5).

Discussion

In this series of autopsy-confirmed MSA, a small subset of cases (38%) had comorbid pathologies. This contrasts with more frequent comorbid pathologies in other neurodegenerative disorders, such as Lewy body disease (92%),14 AD (79%)15 and PSP (68%).16 The frequency of MSA without significant comorbid pathologies was similar to that recently reported by Robinson et al.38 who found it in 65% of MSA cases. The average AAD of MSA patients is younger than in other common neurodegenerative diseases, which may contribute to lower frequency of comorbid pathologies. On the other hand, the number of comorbid pathologies was small in our series even for patients over 75 years of AAD. The reason that other proteinopathies and vascular lesions tend to be less frequent in MSA is unknown.

In the present study, the impact of comorbid pathologies on the clinical features of MSA was limited. With advanced age of symptomatic disease onset and death, the number of comorbid pathologies, Braak NFT stage and Thal amyloid phase tended to increase, but even in the oldest age group, they were infrequent. Furthermore, they did not affect disease duration or clinical phenotype. An increase in comorbid pathologies did not lead to shorter disease duration in MSA. Additionally, even with a longer disease duration, MSA did not induce other pathologies.

The antemortem diagnostic accuracy of MSA was significantly lower in patients with any comorbid pathologies. A previous study reported that higher Braak stage lowered the diagnostic accuracy in dementia with Lewy bodies39. In the present study, ADNC and higher Braak stage correlated with lower diagnostic accuracy, but these associations were not confirmed in the multiple logistic regression analysis. Only AAO significantly contributed to the lower diagnostic accuracy. Therefore, the involvement of comorbid pathologies in diagnostic accuracy was considered limited.

While the frequency of ADNC was higher in MSA patients with cognitive dysfunction compared to those without, ADNC was found in only 15% of MSA patients with cognitive dysfunction. The median Braak NFT stage and Thal amyloid phase were both 1 in MSA patients with cognitive dysfunction, suggesting that cognitive dysfunction in MSA is unlikely driven by ADNC. Patients with cognitive dysfunction tended to have more comorbid pathologies, but the difference was not significant. Indeed, the median number of comorbid pathologies was 0 for both those with and without cognitive dysfunction. A previous study of 48 autopsy-confirmed MSA patients showed that Lewy-related pathology was not associated with cognitive dysfunction, but there was a high prevalence of AD pathology in MSA patients with cognitive dysfunction.40 To address the association between comorbid pathologies and cognitive dysfunction, we performed a logistic regression analysis and identified no significant contributing pathology for cognitive dysfunction, suggesting that comorbid pathologies are unlikely to be drivers of cognitive dysfunction in MSA. In terms of MSA pathology itself, previous studies have compared the burden of α-synuclein in oligodendroglia and neurons in MSA patients with and without cognitive dysfunction, yielding varying results depending upon the brain regions evaluated.5, 25, 40-42 These studies primarily focused on later-stage α-synuclein aggregates; however, recently, the toxicity and widespread distribution of α-synuclein oligomers, early-stage α-synuclein aggregates, have been highlighted in Parkinson’s disease and MSA.6, 43-47 Notably, a recent report demonstrated higher levels of α-synuclein oligomers in the hippocampus of MSA patients with memory impairment.48 Taken together, it is suggested that cognitive dysfunction in MSA may be due to the MSA pathology itself, rather than to comorbid pathologies. These findings suggest that α-synuclein, including early aggregates, may be a target for future MSA treatment.

A limitation of the present study is that it was a retrospective study of an autopsy cohort. Patients did not undergo systematic, standardized antemortem clinical evaluations, and mild cognitive dysfunction may be underestimated. Conversely, in cases with pronounced motor or autonomic impairments, which may hinder effective communication, there is a possibility of an overestimation of cognitive dysfunction. Nonetheless, this study represents the largest autopsy series assessing frequency of comorbid pathologies of MSA, and their clinical contribution.

Conclusion

The present study demonstrates that most MSA patients do not have comorbid pathologies and that the clinical impact of comorbid pathologies in those who have it is limited. Given that MSA appears to be a disease driven by a single factor (i.e. pathological α-synuclein), it is reasonable that α-synuclein should be the primary focus of disease modifying therapies.

Supplementary Material

Supinfo

Acknowledgement

We would like to express our sincere gratitude to patients and their families for their agreement to brain donation. We also thank Virginia Phillips (Mayo Clinic, Jacksonville) for histological support and Monica Castanedes-Casey (Mayo Clinic, Jacksonville) for immunohistochemistry support.

Funding:

HS reports fellowships from the Japanese Society of Neurology, the Cell Science Research Foundation, and the Uehara Memorial Foundation. He is partially supported by the American Parkinson Disease Association Research Grant and the Multiple System Atrophy Coalition Research Grant; SK is partially supported by the State of Florida Ed and Ethel Moore Alzheimer’s Disease Research Program, Mayo Clinic Alzheimer’s Disease Research Center Research Grant, and CurePSP Research Grant; AM reports fellowships from the Japanese Society of Neurology; ZKW is partially supported by the NIH/NIA and NIH/NINDS (1U19AG063911, FAIN: U19AG063911), Mayo Clinic Center for Regenerative Medicine, the gifts from the Donald G. and Jodi P. Heeringa Family, the Haworth Family Professorship in Neurodegenerative Diseases fund, and The Albertson Parkinson’s Research Foundation. He serves as PI or Co-PI on Biohaven Pharmaceuticals, Inc. (BHV4157-206), Neuraly, Inc. (NLY01-PD-1), and Vigil Neuroscience, Inc. (VGL101-01.002, VGL101-01.201, PET tracer development protocol, Csf1r biomarker and repository project, and ultra-high field MRI in the diagnosis and management of CSF1R-related adult-onset leukoencephalopathy with axonal spheroids and pigmented glia) projects/grants. He serves as Co-PI of the Mayo Clinic APDA Center for Advanced Research and as an external advisory board member for the Vigil Neuroscience, Inc., and as a consultant on neurodegenerative medical research for Eli Lilli & Company.

Footnotes

Conflict of Interest: There are no conflicts of interest to declare.

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