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. Author manuscript; available in PMC: 2025 Jul 1.
Published in final edited form as: Ann Neurol. 2024 Apr 5;96(1):99–109. doi: 10.1002/ana.26930

Evaluating the effect of Alzheimer’s disease-related biomarker change in Corticobasal Syndrome and Progressive Supranuclear Palsy

Indira Garcia-Cordero 1, Chloe Anastassiadis 1, Abeer Khoja 2,3, Alonso Morales-Rivero 2,4, Simrika Thapa 1, Anna Vasilevskaya 1, Carly Davenport 1, Vishaal Sumra 1, Blas Couto 5,6,7, Namita Multani 1, Foad Taghdiri 1, Cassandra Anor 1, Karen Misquitta 1, Lawren Vandevrede 8, Hilary Heuer 8, David Tang-Wai 9, Bradford Dickerson 10, Alexander Pantelyat 11, Irene Litvan 12, Bradley Boeve 13, Julio C Rojas 8, Peter Ljubenkov 8, Edward Huey 14, Susan Fox 5,6, Gabor G Kovacs 1,5,6,9, Adam Boxer 8, Anthony Lang 1,5,6,9, M Carmela Tartaglia 1,2,5,9,*; 4-R-Tauopathy Neuroimaging Initiative Consortium, and the Alzheimer’s Disease Neuroimaging Initiative†
PMCID: PMC11249787  NIHMSID: NIHMS1978562  PMID: 38578117

Abstract

Objectives:

To evaluate the effect of Alzheimer’s disease (AD)-related biomarker change on clinical features, brain atrophy and functional connectivity of patients with corticobasal syndrome (CBS) and progressive supranuclear palsy (PSP).

Methods:

Data from patients with a clinical diagnosis of CBS, PSP and AD and healthy controls were obtained from the 4-R-Tauopathy Neuroimaging Initiative 1 and 2, the Alzheimer’s Disease Neuroimaging Initiative and a local cohort from the Toronto Western Hospital. Patients with CBS and PSP were divided into AD-positive (CBS/PSP-AD) and AD-negative (CBS/PSP-noAD) groups based on fluid biomarkers and amyloid PET scans. Cognitive, motor and depression scores, AD fluid biomarkers (cerebrospinal p-tau, t-tau, and amyloid-beta, and plasma ptau-217) and neuroimaging data (amyloid PET, MRI and fMRI) were collected. Clinical features, whole-brain grey matter volume and functional networks connectivity were compared across groups.

Results:

Data were analyzed from 87 CBS/PSP-noAD and 23 CBS/PSP-AD, 18 AD, and 30 healthy controls. CBS/PSP-noAD showed worse performance in comparison to CBS/PSP-AD in the PSPRS [mean(SD): 34.8(15.8) vs 23.3(11.6)] and the UPDRS scores [mean(SD): 34.2(17.0) vs 21.8(13.3)]. CBS/PSP-AD demonstrated atrophy in AD signature areas and brainstem, while CBS/PSP-noAD patients displayed atrophy in frontal and temporal areas, globus pallidus and brainstem compared to healthy controls. The default mode network showed greatest disconnection in CBS/PSP-AD compared with CBS/PSP-no AD and controls. The thalamic network connectivity was most affected in CBS/PSP-noAD.

Interpretation:

AD biomarker positivity may modulate the clinical presentation of CBS/PSP, with evidence of distinctive structural and functional brain changes associated with the AD pathology/co-pathology.

Keywords: CBS, PSP, biomarkers, atrophy, functional connectivity, networks, cognition, motor

1. Introduction

Co-pathology is recognized as a frequent post-mortem finding in neurodegenerative diseases1 and could contribute to heterogeneity of disease presentation and progression. Indeed, in frontotemporal lobar degeneration (FTLD)-related syndromes, a wide spectrum of pathologies can be associated with a particular diagnosis. The use of in vivo biomarkers may facilitate more precise profiling of a syndrome and a better understanding of heterogeneity.

Corticobasal syndrome (CBS) and progressive supranuclear palsy (PSP) are two FTLD syndromes characterized by changes in motor function and cognition2, 3. CBS and PSP can show overlapping symptoms, but also, have their own distinct clinical features and disease progression. Classically, CBS presents with asymmetric rigidity, bradykinesia, dystonia, myoclonus, cortical sensory loss, alien limb phenomenon and language, social and executive impairment2, 4. Patients with PSP often present with the classical Richardson’s syndrome that features postural instability leading to falls and supranuclear gaze palsy, with frequently seen language and executive deficits3, but it has been recognized that many other variants exist3. Neuropsychiatric symptoms, such as depression and apathy, are also frequent in both CBS and PSP5, 6. The overlapping symptomatology between various neurodegenerative diseases and the non-traditional presentations (e.g., the presence of cognitive and executive impairment before the onset of motor symptoms or the lack of the supranuclear gaze palsy) can delay their diagnosis or lead to misdiagnosis.

The underlying pathology of CBS includes 4-repeat (4-R) tau associated with FTLD (e.g., corticobasal degeneration or PSP) as well as other pathologies including Alzheimer’s disease (AD) pathology2, 7. In 8 to 24% of the CBS cases the primary pathology is AD8, 9; however, in 35% of the cases, AD is a co-pathology1. The pathological substrate of PSP is almost always 4-R tau; however, AD co-pathology has been reported in 70–80% cases1, 10, 11. Pathologies can generate specific patterns of atrophy and functional network alterations that may impact the clinical presentation and disease progression in neurodegenerative diseases12.

Previous studies have demonstrated inconsistent results in CBS with AD pathology. AD pathology was associated with greater memory impairment13, 14, but also, with similar cognition in comparison to CBS without AD pathology4, 15–17, and with both benign13 or rapid18 disease progression. In contrast, atrophy in temporoparietal areas was consistently found in CBS with AD pathology4, 9, 15, 19, 20. Scarce information is available for PSP with AD co-pathology. One study found no differences in neuropsychological measures and less grey matter volume in the parietal and temporal lobes in a mixed group of CBS and PSP with AD vs non-AD21.

The evidence suggests that alteration of the functional connectivity networks could be a potential marker of underlying pathophysiology and useful for early detection and tracking disease progression in neurodegenerative diseases12. Previous reports in patients with AD showed an association between Aβ and tau accumulation and alterations in the default mode network (DMN)22, 23. Increased DMN connectivity has been reported in CBS24, and both increased and decreased connectivity in PSP24–26. Disconnection of the salience network (SN) has been associated with FTLD12 and PSP25, whereas increased connectivity has been shown in CBS24. Consistent disruptions in the thalamic network (ThN) have been reported in patients with CBS and PSP25–28. However, these studies have not evaluated the AD status and the heterogeneous results could be a consequence of having mixed pathologies within groups.

Fluid and neuroimaging biomarkers may help to improve antemortem diagnosis and contribute to a better characterization of the clinical phenotypes. Abeta1–42, phosphorylated tau (p-tau181) and total tau (t-tau) in cerebrospinal fluid (CSF), plasma phosphorylated tau 217 (p-tau217) and PET scans with 11–labeled Pittsburgh Compound B (11C-PiB) have been suggested as reliable biomarkers of AD pathology29–32.

The aim of this study was to evaluate the effect of AD-related biomarker changes on clinical features, brain atrophy and functional connectivity of patients with clinical diagnosis of CBS and PSP. We expected an AD-like phenotype in patients with CBS/PSP that are positive for AD-related biomarker change (i.e., cognitive impairment and relatively spared motor functions, atrophy in AD signature areas, and alteration in the DMN connectivity) compared to CBS/PSP without AD. In contrast, CBS/PSP without AD would be expected to present with more motor impairment than cognitive deficits, atrophy in subcortical structures and frontal lobe and disconnection of the SN and ThN in comparison to CBS/PSP positive for AD-related biomarker change. We did not expect a significant effect of AD pathology on neuropsychiatric symptoms.

2. Methods

2.1. Participants

One hundred and ten patients with a clinical diagnosis of CBS2 (n = 53) and PSP3, 33 (n = 57), 18 AD34 and 30 healthy controls were included in the analysis. Multicenter clinical, neuroimaging and biofluid biomarker data were collected as part of the ongoing 4-R-Tauopathy Neuroimaging Initiative (4RTNI) 1 and 2, the Alzheimer’s Disease Neuroimaging Initiative (ADNI), which involved 6 different centers across the United States (University of South Carolina, Columbia; Massachusetts General Hospital, Boston; Johns Hopkins University, Baltimore; Washington University, Saint Louis; the University of California, San Diego; University of California, San Francisco) and a local cohort (Toronto Western Hospital, Toronto). The process of recruitment and enrolment in each of these studies has been described elsewhere (ADNI: https://adni.loni.usc.edu/ [see the Supplemental file, section 1.1], 4RTNI-1: http://4rtni-ftldni.ini.usc.edu and 4RTNI-2: https://memory.ucsf.edu/research-trials/research/4rtni-2). The local cohort was recruited in the Memory Clinic and the Rossy PSP program of the Toronto Western Hospital and the University Health Network from 2012 to 202235.

Twenty-nine 29 patients with PSP from 4RTNI-2 and the local cohort were diagnosed based on the new Movement Disorder Society PSP Diagnostic Criteria3; and 28 patients from 4RTNI-1 were diagnosed using the previous criteria33. This resulted in 53 patients with PSP Richardson’s syndrome (92.8%), and four patients with other PSP clinical variants such as predominant parkinsonism (n = 1, 1.8%), progressive gait freezing (n = 1, 1.8%), corticobasal syndrome (n = 1, 1.8%), and predominant frontal presentation (n = 1, 1.8%).

Patients were included in the analysis if they had at least one of the biomarkers described below, the magnetic resonance imaging (MRI) and the resting-state functional MRI (fMRI). Biomarkers, neuroimaging and clinical assessments data were collected at the same time point.

ADNI and 4RTNI-1 and 2 obtained all IRB approvals and met all ethical standards in the collection of data. The local study was approved by the University Health Network Research Ethics Board and written consent according to the Declaration of Helsinki was obtained from all participants.

2.1.1. Biomarkers and PiB PET collection

Of the 110 patients with CBS/PSP, CSF p-tau, t-tau, and amyloid-beta were measured in 31 patients and plasma p-tau217 was analyzed in 79 patients. Moreover, six CBS/PSP patients had amyloid (11C-PiB) PET scans (see the Supplemental file, section 1.2 and Supplementary Table 1 for a complete detail of each subject biomarker collection).

2.1.2. Clinical assessments

The following tests were administrated: The Montreal Cognitive Assessment (MoCA), the Clinical Dementia Rating (CDR), the Progressive Supranuclear Palsy Rating Scale (PSPRS), the Unified Parkinson Disease Rating Scale (UPDRS), the California Verbal Learning Test (CVLT), the animal verbal fluency test and the Geriatric Depression Scale (GDS).

2.2.3. Neuroimaging acquisition and preprocessing

All patients and healthy controls underwent a MRI to acquire an anatomical scan and fMRI (see Supplementary Table 2 for more details of the acquisition parameters of each site).

T1 images were analyzed using the Freesurfer V6.0 software (http://surfer.nmr.mgh.harvard.edu/) from the Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library. Resting state-fMRI data were preprocessed and analyzed using the CONN toolbox36. For more details in the preprocessing steps, see the Supplemental file, section 1.3 and Supplementary Table 3.

2.2. Study design: AD status definition

CBS and PSP patients were classified into AD positive or negative based on the presence of AD-related biomarker change in CSF, plasma and/or PiB PET. AD positivity was considered if CSF p-tau > 68 pg/ml and Ab1–42 to t-tau index (ATI) < 0.831 and/or plasma p-tau217 > 0.25 pg/ml37. Positivity for 11C-PiB amyloid PET was defined by expert visual read of the created standardized uptake value ratio (SUVR) images38. If any of the biomarkers presented borderline or inconclusive results, the information from the other biomarker was used to determine the AD status. This procedure resulted in 87 CBS/PSP-AD negative (CBS/PSP no-AD) and 23 CBS/PSP AD positive (CBS/PSP-AD). Three patients from 4RTNI-1 and three patients from the local cohort had post-mortem pathology confirmation that agreed with the biomarker classification (see Supplementary Table 1). The examination of the local cohort was performed by an experienced pathologist from the Toronto Western Hospital (G.G.K.).

2.3. Statistical analysis

Age and level of education were compared using ANOVAs; sex, using Pearson’s Chi-squared test; and age at onset symptoms and disease duration, with a two-sample t-test. Clinical rating scales were compared across groups with ANCOVAs (covaried by age). Exploratory comparisons between CBS-AD vs CBS-noAD and PSP-AD vs PSP-noAD were performed using Mann–Whitney U pairwise tests. Percentage of data collection is reported in Table 1.

Table 1.

Demographics and clinical features

No. (%) with data CBS/PSP-noAD (n = 87: 40 CBS, 47 PSP) CBS/PSP-AD (n = 23: 13 CBS, 10 PSP) AD (n = 18) Healthy controls (n = 30) Statistics
Age (years) 158/158
(100%)		 68.7 (7.9)
40–88		 66.4 (7.3)
54–79		 69.9 (10.3)
55 – 87		 67.3 (6.5)
57–81		 F (3,154) = 0.92;
p = .43
Sex (males/females) 158/158
(100%)		 42/45 12/11 9/9 12/18 X2(3) = 0.94;
p = .81
Education (years) 151/158
(95.6%)		 15.8 (3.6)
2–26		 16.6 (3.0)
12–24		 14.2 (4.8)
5–20		 16.1 (2.1)
12–20		 F (3,147) =1.57;
p =.20
Race (%, No.) 130/158
(82.3%)		 82.5% White (71); 8.1% Asian (7)
2.3% Latino (2); 3.5% Native Hawaiian of Other Pacific Island (3); 1.2% East Indian (1); 1.2% South East Asia (1); 1.2% Black or African American (1)		 95.5% White (21); 4.5 % Black of African American (1) 100% White (11) 85.8% White (12); 7.1% South East Asia (1); 7.1% Asian Indian (1)
Age at symptom onset (years) 107/110
(97.3%)		 63.5 (8.1)
35–83		 61.3 (7.5)
50–75		 - - t (105) = 1.17;
p = .25
Disease duration (years) 107/110
(97.3%)		 5.3 (3.9)
0–25		 5.2 (3.7)
0–17		 - - t (105) = 0.10;
p = .92
MoCA 117/140
(83.6%)		 20.3 (5.7)
5–30		 21.2 (4.6)
10–28		 - 27.8 (2.4)
22–30		 F (2, 113) =17.66;
p < .001a, b
CDR (sum of box score) 115/128
(89.8%)		 3.89 (3.23)
0.00–12.00		 3.80 (2.75)
0.00–11.00		 4.47 (2.22)
1.00–10.00		 - F (2,111) = 0.34; p = .71a
PSPRS (total score) 92/110
(83.6%) 		34.8 (15.8)
9–71 		23.3 (11.6)
10–58 		- - F (1, 89) = 8.91;
p = .004a
UPDRS (total score) 85/110
(77.3%) 		34.2 (17.0)
3–72 		21.8 (13.3)
4–45 		- - F (1, 82) = 6.81;
p = .01a
CVLT (long-delay recall score) 93/110
(84.5%)		 4.9 (2.7)
0–9		 5.2 (2.8)
0–9		 - - F (1, 90) = 0.07;
p = .79a
Categorical fluency (animals) 141/158
(89.2%)		 11.0 (5.2)
0–25		 12.5 (5.1)
6–29		 9.1 (4.8)
0–15		 22.9 (4.4)
15–36		 F (3, 136) = 43.04;
p < .001a, c
GDS 98/158
(62.0%)		 9.9 (6.5)
0–23		 9.7 (6.9)
2–22		 2.3 (2.1)
0–8		 1.1 (2.5)
0–12		 F (3, 93) = 20.20;
p < .001a, d
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Data are express as mean (standard deviation) and below, the minimum and maximum values.

Abbreviations: CBS, corticobasal syndrome; PSP, progressive supranuclear palsy; AD, Alzheimer’s disease; MoCA, Montreal Cognitive Assessment; CDR, Clinical Dementia Rating; PSPRS, Progressive Supranuclear Palsy Rating Scale; UPDRS, Unified Parkinson Disease Rating Scale; CVLT, California Verbal Learning Test; GDS, Geriatric Depression Scale.

a

ANCOVA across groups, covaried by age.

b

Tukey post-hoc tests: Controls > CBS/PSP-noAD (p < .001) and CBS/PSP-AD (p < .001); CBS/PSP-noAD = CBS/PSP-AD (p = .77).

c

Tukey post-hoc tests: Controls > CBS/PSP-noAD (p < .001), CBS/PSP-AD (p < .001) and AD (p < .001); CBS/PSP-noAD = CBS/PSP-AD (p = .62); CBS/PSP-noAD = AD (p = .52); CBS/PSP-AD = AD (p = .17).

d

Tukey post-hoc tests: Controls = AD (p = .89). Controls < CBS/PSP-noAD (p < .001) and CBS/PSP-AD (p < .001); AD < CBS/PSP-noAD (p < .001) and CBS/PSP-noAD (p = .003); CBS/PSP-noAD = CBS/PSP-AD (p = .99).

Atrophy patterns for the patients’ groups were obtained by comparing per-area values of those groups against healthy controls via ANCOVAs (covaried by age, total intracranial volume and scanner type) and Bonferroni correction. In addition, exploratory comparisons of the grey matter volume between CBS-AD vs CBS-noAD and PSP-AD vs PSP-noAD were performed using the same approach.

For functional connectivity assessment, a seed-based approach was used to investigate network-specific connectivity. Spherical regions of interest (ROIs) of 10 mm-radius were located in the precuneus [MNI coordinates: 0, −56, 28]36 and the right anterior insula [MNI coordinates: 35, 24, 5]12 to generate seed-to-voxel functional connectivity maps of the DMN and the SN, respectively. Two 6 mm – radius ROIs were placed in the thalamus [MNI coordinates: −12, −12, 6 (left); 11, −12, 6 (right)]39 to obtain the ThN. As a control network, we generated the visual network using two ROIs of 10 mm-radius located in the middle occipital gyrus [MNI coordinates: −29, −88, 8 (left); 27, −91, 2 (right)]39. Z-transformed functional connectivity maps were created per seed and individual by performing Pearson correlations between the seed and all the voxels of the brain. Networks were masked using Yeo et al. parcellation40 to evaluate within network connectivity and minimize multi-voxel comparisons. The ThN was the only network that was not masked, as no clear bounds have been reported. Network functional connectivity maps were compared between the four groups via General Linear Model, using ANCOVAs and controlling by age and scanner type. Statistical threshold was set at p<.001, family-wise error (FWE) rate correction at cluster level (p<.05). Values from the resulting clusters were extracted and analyzed using Tukey pairwise post-hoc testing. To explore the association between the functional connectivity networks and the clinical features, we performed Spearman correlations in all CBS and PSP between the DMN connectivity and the MoCA and the CVLT scores; the SN connectivity and GDS scores; and ThN connectivity and UPDRS and PSPRS scores. The reported p values were corrected for multiple comparisons using false discovery rate (FDR) correction.

3. Results

3.1. Demographics and clinical assessments

Results are shown in Table 1 and Supplementary Tables 4 and 5. Age, sex and education were similar across all groups. There were no significant differences in age at symptom onset and disease duration between CBS/PSP-noAD and CBS/PSP-AD; but CBS-AD presented at an earlier age of onset when compared to CBS-noAD. Patients had significant cognitive impairment in comparison to healthy controls, but MoCA scores, CVLT and verbal fluency were similar between CBS/PSP with or without AD. CDR scores did not differ across AD, CBS/PSP-noAD and CBS/PSP-AD. Both the PSPRS and the UPDRS scores were worse in CBS/PSP-noAD in comparison to CBS/PSP-AD. A worse motor performance was obtained for non-AD groups, regardless of the clinical diagnosis (CBS or PSP). The CBS and PSP patients showed higher depression scores than controls and AD patients.

3.2. Imaging results

AD patients displayed atrophy in temporal and parietal areas, and in hippocampus and amygdala, in comparison to healthy controls. The atrophy in CBS/PSP-AD was in the AD signature areas and brainstem. The CBS/PSP-noAD patients displayed atrophy in frontal and temporal areas and in the globus pallidus and brainstem (see Fig 1). We also explored CBS and PSP separately and found that the CBS-AD patients demonstrated atrophy in temporal areas and the hippocampus. In contrast, CBS-noAD patients displayed frontal and brainstem atrophy. In the case of PSP-noAD, patients presented more basal ganglia atrophy when compared to controls than PSP-AD (see Supplementary Table 6 and Supplementary Fig 1).

Fig 1. Atrophy patterns.

Fig 1.

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Grey matter volumes of each patient group were compared against healthy controls. Only areas that survived the Bonferroni correction (p < .05) are plotted. Color bar indicates p values after Bonferroni correction.

Differences were observed in DMN connectivity, with greater disconnection in AD, followed by CBS/PSP-AD and then CBS/PSP-noAD. The SN showed lower insular functional connectivity in both CBS/PSP-AD and CBS/PSP-noAD, in comparison to AD and healthy controls. The ThN showed differences in three clusters: a large cluster in the basal ganglia that displayed lower connectivity in the CBS/PSP-noAD, followed by CBS/PSP-AD; a second cluster in the anterior cingulate cortex that was only affected in CBS/PSP-noAD; and a cluster that covered mostly the cerebellum and some part of the occipital gyrus that displayed hyperconnectivity for both CBS/PSP-AD and CBS/PSP-noAD versus AD and healthy controls. There were no significant clusters for the visual network (see Fig 2).

Fig 2. Functional connectivity results.

Fig 2.

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A. Seed-to-voxel analyses resulted in different clusters for each network across groups [p < .001, FWE correction at cluster level (p < .05)]. The centers of the cluster for the networks are: DMN: −60, −18, −14 (left middle temporal gyrus), SN: −36, 10, 4 (left insula); ThN: −26, −4, 6 (left putamen); 0, 38, 10 (left anterior cingulate cortex); and 44, −78, −16 (right inferior occipital gyrus). B. Tukey pairwise post-hoc testing of the values extracted from the resulting clusters. P values of each significant comparison are displayed over the bars. DMN= default mode network; SN=salience network; ThN = subcortical (thalamic) network; L=left.

Finally, in all CBS and PSP patients, disconnection of the SN was associated with higher GDS scores. Lower ThN-basal ganglia connectivity was associated with higher PSPRS and UPDRS scores, and higher ThN-cerebellum connectivity was associated with higher UPDRS scores. No other significant correlations were found (see Table 2).

Table 2.

Spearman correlations results

Network connectivity Clinical assessment Statistics
DMN MoCA r = 0.03; p = .80
CVLT r = 0.01; p = .92
SN GDS r = −0.32; p = .04
ThN-basal ganglia PSPRS r = −0.42; p < .001
UPDRS r = −0.35; p = .004
ThN-cerebellum PSPRS r = 0.21; p = .09
UPDRS r = 0.30; p = .02
ThN-cortex PSPRS r = −0.17; p = .15
UPDRS r = −0.05; p = .80
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Abbreviations: DMN, default mode network; SN, salience network; ThN, thalamic network; MoCA, Montreal Cognitive Assessment; CVLT, California Verbal Learning Test (long-delay recall score); GDS, Geriatric Depression Scale; PSPRS, Progressive Supranuclear Palsy Rating Scale (total score); UPDRS, Unified Parkinson Disease Rating Scale (total score); r is the Spearman rank correleation coefficient; p values are FDR corrected.

4. Discussion

We identified the effects of AD-related biomarker change on clinical features, brain atrophy and functional connectivity networks in patients with CBS and PSP. The presence of AD-related biomarker change did not affect global cognition, verbal memory or depression in CBS/PSP cases. CBS/PSP-AD patients demonstrated less motor symptomatology, an AD-like atrophy pattern and disconnection of the DMN, in comparison to CBS/PSP-noAD. The SN and the ThN were also differentially affected based on the presence of AD pathology/co-pathology. Our results provide strong evidence that AD-related biomarker changes could intricately influence the clinical manifestation of CBS and PSP. Furthermore, they enhance our understanding of the mechanisms contributing to the heterogeneity observed in neurodegenerative diseases. Finally, these results underscore the promising potential of precision medicine treatments targeting AD specifically in CBS/PSP cases with AD-related biomarker changes indicative of concurrent AD pathology2, 7. The use of AD-related biomarker stratification may enhance precision in the design of clinical trials, aiding in the identification of individuals with CBS and PSP who may benefit not only from anti-tau drugs but also from therapeutics targeting AD pathology.

The CBS-AD group demonstrated an earlier age of onset in comparison to CBS-noAD in keeping with previous findings9, 15, 16. A recent neuropathological study showed that the Braak stage is associated with age at onset in corticobasal degeneration11, suggesting a relationship between the amount of pathology and manifestation of symptoms. Early onset of symptoms may delineate a clinical phenotype in CBS as it is associated with more cortical atrophy and rapid progression of the disease18, 41. Age at symptom onset was not significantly different between PSP-noAD versus PSP-AD. This is in agreement with a previous report, which shows no influence of AD co-pathology on age of onset in PSP10.

Non-AD groups showed worse motor performance, whether CBS and PSP groups were analyzed together or separately. The worse motor performance could be caused by greater damage in the basal ganglia, brainstem, thalamus, or the cerebellum as a consequence of the 4-R-tauopathy in CBS/PSP-noAD9, 11. Supporting this idea, we found that those areas displayed more atrophy or lower functional connectivity in the CBS/PSP-noAD compared to the CBS/PSP-AD group. We posit that the additional AD pathology may result in patients presenting earlier, with less severity and slower progression related to their underlying 4R-tau pathology and therefore the motor symptoms are less severe for the same duration of disease. There were no differences in cognition between CBS/PSP-noAD and CBS/PSP-AD, and neither when CBS and PSP were considered separately. Based on the hippocampal and temporal lobe atrophy and the AD pathology of the CBS/PSP-AD group, we would have expected a more amnestic profile compared to CBS/PSP-noAD but this was not the case. The literature is ambiguous in relation with cognitive symptoms, finding similar4, 15–17, 21 and different13, 14 performances between CBS/PSP-noAD and CBS/PSP-AD. The studies that found differences13, 14 had small sample size and the CBS-AD patients seemed to be more advanced compared to the other groups as they presented lower scores in all cognitive tests. The literature4, 15–17, 21 and our results suggest that neuropsychological measures may not be helpful in differentiating between AD and non-AD groups16 and highlighting the importance of using biomarkers to detect AD neuropathological changes.

Geriatric Depression Scale scores were not distinct between CBS/PSP-noAD and CBS/PSP-AD; but both groups presented higher scores than AD, consistent with depression being a common comorbidity in 4R-tauopathies5, 6. Although there is evidence of depression being associated with higher neurofibrillary tangles Braak staging42, our results also suggest that there is no interaction between tau and AD pathology within the CBS/PSP cohort that would increase depression. Further studies are required to explore neuropsychiatric symptoms, particularly, in frontal CBS and PSP variants that could be easily misdiagnosed with primary psychiatric disorders.

Atrophy in CBS/PSP-AD was in AD signature areas and differed from CBS/PSP-noAD supporting neuroanatomical selectivity for AD pathology4, 9, 15, 19, 20. The grey matter volume loss in temporo-parietal areas has been proposed as a marker of AD pathology, independent of clinical diagnosis20. In CBS/PSP-noAD, the atrophy was in frontal areas, basal ganglia and midbrain, as expected in FTLD with 4R-tau4, 9.

Regarding functional connectivity, the DMN was most disconnected in AD, as expected22, 23, followed by CBS/PSP-AD and then CBS/PSP-noAD, suggesting a specific network vulnerability to AD pathology12. The DMN is associated with memory and cognitive decline43 and can be affected in CBS and PSP patients24–26. However, we did not find associations between the DMN connectivity and global cognition or memory scores. There may be an interaction between the DMN and other networks, like the executive-control network, contributing to impaired cognition in CBS and PSP, indicating that it is not solely attributed to DMN connectivity changes. We found that the SN was equally affected in CBS/PSP-AD and CBS/PSP-noAD. Confirmed neuropathological cases of FTLD demonstrate atrophy and accumulation of FTLD-associated pathological inclusions in areas that are hubs of SN44. In our case, it is likely that the 4-R tauopathy is associated with the SN disconnection in both groups, despite the presence of AD pathology/co-pathology in only a subset. The association between higher depression scores and the SN disconnection supports its role in emotional processing45.

In the ThN we found functional connectivity alterations among three axes: the cortex, basal ganglia, and cerebellum. Disconnection in thalamus-basal ganglia and thalamus-cortex was observed in CBS/PSP-noAD versus the other groups. Hyperconnection of the thalamus-cerebellum was found in both CBS/PSP-noAD and CBS/PSP-AD. Lower connectivity between the thalamus and the basal ganglia and higher connectivity between the thalamus and the cerebellum were associated with motor impairments. These results replicate previous functional connectivity findings in CBS and PSP25, 27, 28. In particular, the cortico-subcortical disconnection in CBS/PSP-noAD may be related to the neuropathological inclusions in corticobasal degeneration46 and PSP47. We speculate that the cortico-subcortical axis is affected by the 4R-tau pathology and alters the functional connectivity of the other two axes, causing the altered thalamus hypo/hyperconnectivity with the basal ganglia and cerebellum and affecting motor performance. It is important to clarify that hyperconnectivity has been reported as a result of neurodegeneration and as a compensatory mechanism to maintain a “functional” network48. These results provide insights into the pathophysiological mechanism of motor deficits in CBS and PSP. Finally, it should be noted that CBS and PSP groups displayed a similar distribution of connectivity values in all networks, indicating that the results are not biased by diagnosis.

5. Limitations

Our study has some limitations. Firstly, patients were diagnosed based on clinical criteria and without post-mortem confirmation. Despite this, there is a huge amount of evidence that AD-related biomarkers are accurate to detect AD pathology in FTLD patients41 and that the biomarkers correlate with post-mortem diagnosis30, 32. Our results were also supported by the atrophy patterns that matched the expected AD pathology. We merged CBS and PSP due to their shared classification as 4-R tauopathies, their potential overlap in clinical symptoms, and to increase the sample size. While recognizing the existence of potential clinical distinctions between CBS-AD with AD as the primary pathology and CBS-AD with AD as co-pathology, our study showed consistent replication of all clinical characteristic analyses in the CBS and PSP subgroups, except for age at symptom onset, which was younger for CBS-AD, as compared to CBS-noAD. This observation suggests a potential divergence between AD as the primary pathology versus co-pathology and that younger CBS patients may be more likely to have AD as a primary pathology16. Additionally, genetic analysis was not performed in this study, preventing the determination of whether any of the CBS participants carried progranulin mutations—a prevalent mutation in CBS (48%)49 that is associated with TDP-43 neuropathology50. Including genetic carriers with CBS and AD pathology would facilitate the identification of distinct clinical criteria in CBS-AD as a primary pathology compared with AD as co-pathology. The sample was selected based on the availability of biomarkers and neuroimaging. In our study, 24% percent of the CBS patients were AD positive, similar to previous studies that found around 20%−30% of AD positivity using CSF in CBS17, 51. In PSP, we found a higher AD positivity: 17% in our sample versus 5–10% reported elsewhere51, 52 (although sample sizes were smaller in those studies). We combined CSF, plasma and PiB PET imaging to divide the groups into AD positive and negative. Both CSF and plasma biomarkers have good sensitivity and specificity to detect AD pathology29, 32, 53, and plasma p-tau217 performs similar to CSF AD biomarkers and PiB PET imaging53. We acknowledge that we are introducing a new source of variability by using different types of biomarkers, but this approach allowed us to increase the sample size and potentiate the statistical power. In addition, the combination of different biomarker modalities has previously been used to classify AD patients (ATN framework54). Further longitudinal studies are needed to show whether the disease progression is affected by AD-related biomarker change and if the functional connectivity networks are useful for tracking those changes over time.

6. Conclusion

We found that AD-related biomarker change may influence clinical features, cortical atrophy, and functional connectivity networks. CBS and PSP are syndromes with clinicopathological heterogeneity, and multi-domain approaches that include neuroimaging and biofluid biomarkers may bring more accurate clinical characterization, better clinicopathological correlations, and exposition of avenues of targeted therapies including anti-amyloid drugs or cholinesterase inhibitors in CBS or PSP patients with AD-related biomarker change.

Supplementary Material

Supinfo

What is the current knowledge on the topic?

Co-pathologies may contribute to presentation and progression heterogeneity of the disease. There is a high prevalence of Alzheimer’s disease (AD) pathology/co-pathology in corticobasal syndrome (CBS) and progressive supranuclear palsy (PSP).

What question did this study address?

Is there an effect of AD-related biomarker change on clinical features, brain atrophy and functional connectivity of patients with CBS and PSP?

What does this study add to our knowledge?

We identified a strong influence of AD-related biomarker change on clinical features, brain atrophy and functional connectivity networks in patients with CBS and PSP.

How might this potentially impact on the practice of neurology?

Employing a stratification based on changes in AD-related biomarkers could enhance the characterization of syndromes. This approach may lead to more precise clinical trial designs, helping identify individuals with CBS and PSP patients who could potentially benefit from therapeutics targeting AD pathology.

Acknowledgments

The authors thank all patients and caregivers for their participation in this research. IGC is funded by the Clinical Research Training Scholarship in FTD from the Holloway Family Fund of The Association for Frontotemporal Degeneration, the Bob Burros Family Memorial Fund of the American Brain Foundation and the American Academy of Neurology. JCR is funded by the NIH/NIA K23AG59888 and AlzOut. This work was supported by Canadian Institutes of Health Research (CIHR) and the Alzheimer’s Society of Canada.

Data collection and sharing for this project was funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.;Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.;Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.

Potential conflict of interest:

JCR: Site PI for clinical trials sponsored by Eli Lilly and Eisai. Consulting fees from Roon. No other disclosures were reported.

Data availability:

ADNI and 4RTNI-1 and 2 data are available after approval of proposal. For more information, please visit https://adni.loni.usc.edu/ (ADNI), http://4rtni-ftldni.ini.usc.edu (4RTNI-1) and https://memory.ucsf.edu/research-trials/research/4rtni-2 (4RTNI-2). Local data are available upon reasonable request to corresponding author (Dr. M. C. Tartaglia, carmela.tartaglia@uhn.ca).

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supinfo
NIHMS1978562-supplement-Supinfo.docx (522.6KB, docx)

Data Availability Statement

ADNI and 4RTNI-1 and 2 data are available after approval of proposal. For more information, please visit https://adni.loni.usc.edu/ (ADNI), http://4rtni-ftldni.ini.usc.edu (4RTNI-1) and https://memory.ucsf.edu/research-trials/research/4rtni-2 (4RTNI-2). Local data are available upon reasonable request to corresponding author (Dr. M. C. Tartaglia, carmela.tartaglia@uhn.ca).

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