# Prevalence, Severity, and Progression of Cerebellar Cognitive-Affective Syndrome in Patients With Spinocerebellar Ataxias

Emilien Petit, Daniel López Domínguez, Cecilia Marelli, Sabrina Sayah, Stefan M Pulst, Jennifer Faber, Gulin Oz, Henry L Paulson, Tetsuo Ashizawa, Sophie Tezenas Du Montcel, et al.

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Emilien Petit, Daniel López Domínguez, Cecilia Marelli, Sabrina Sayah, Stefan M Pulst, et al. Prevalence, Severity, and Progression of Cerebellar Cognitive-Affective Syndrome in Patients With Spinocerebellar Ataxias. Neurology, 2025, 105 (5), 10.1212/wnl.0000000000213980. hal-05224235

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Distributed under a Creative Commons CC BY 4.0 - Attribution - International License
1 Prevalence, severity and progression of cerebellar cognitive-

2 affective syndrome in patients with spinocerebellar ataxias

3 Running head: Cognitive dysfunction in spinocerebellar ataxias assessed by the CCAS Scale

4

5 Emilien Petit,¹ Daniel Lopez Dominguez,¹† Cecilia Marelli,²† Sabrina Sayah,¹ Stefan Pulst,³

6 Jennifer Faber,⁴,⁵,⁶ Gulin Oz,⁷ Henry L Paulson,⁸ Tetsuo Ashizawa,⁹ READISCA Consortium,

7 Sophie Tezenas du Montcel,¹ Alexandra Durr,¹ Giulia Coarelli¹

8 †These authors contributed equally to this work.

9

10 ¹Sorbonne Université, Institut du Cerveau - Paris Brain Institute-ICM, Inserm, CNRS, APHP,

11 Hôpital de la Pitié Salpêtrière, Paris, France

12 ²Montpellier University, EPHE, INSERM, Montpellier, France; Expert Center for

13 Neurogenetic Diseases, CHU, Montpellier, France

14 ³Department of Neurology, University of Utah, Salt Lake City, UT 84132, USA

15 ⁴German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany

16 ⁵Center for Neurology, Department of Parkinson, Sleep and Movement Disorders, University

17 Hospital Bonn, 53127, Bonn, Germany

18 ⁶Department of Neuroradiology, University Hospital Bonn, 53127, Bonn, Germany

19 ⁷Center for Magnetic Resonance Research, Department of Radiology, University of

20 Minnesota, Minneapolis, MN, USA

21 ⁸Department of Neurology, University of Michigan, Ann Arbor, MI, USA

22 ⁹Weill Cornell Medicine at Houston Methodist Hospital, Houston, Texas, USA

23 **Corresponding author:** Dr. Giulia Coarelli, Paris Brain Institute, Pitié-Salpêtrière University

24 Hospital, 47 Bd de l'Hôpital, 75646 PARIS Cedex 13, France; giulia.coarelli@icm-

25 institute.org; tel. +33 1 57 27 46 82, fax +33 1 57 27 47 26.
26

27 **Keywords:** Cerebellar Cognitive Affective Syndrome; Polyglutamine Spinocerebellar

28 Ataxias; FGF14/SCA27B, SPG7.

29 Character count for the title: 128; Character count for the running title: 75

30 Total word count of the manuscript: 4467

31 Total word count of the abstract: 350

32 Total number of figures and tables: 6; Number of color figures: 3; Number of tables: 3

33 Number of supplemental tables: 4 (1 in Appendix 2 and 3 in supplementary materials)

34
35 **Abbreviations:**

36

37 CCAS: cerebellar cognitive affective syndrome;

38 CCFS Composite Cerebellar Functional Severity score;

39 CDR: Clinical Dementia Rating;

40 MMSE: Mini Mental State Examination;

41 MOCA: Montreal Cognitive Assessment;

42 NfL: Neurofilament Light chain;

43 PolyQ: Polyglutamine;

44 SARA: Scale for the Assessment and Rating of Ataxia;

45 SCA: Spinocerebellar Ataxia;

46 SPG: Spastic Paraplegia;

47 SPRS: Spastic Paraplegia Rating Scale
**Abstract**

**Background and Objectives:** Cerebellar Cognitive-Affective Syndrome (CCAS) results from cerebellar degeneration, but its prevalence in spinocerebellar ataxias (SCAs) remain underexplored. This study assessed CCAS prevalence, severity, and progression across different SCAs.

**Methods:** We included Polyglutamine (PolyQ) SCAs expansion carriers (ATXN1/SCA1, ATXN2/SCA2, ATXN3/SCA3, and ATXN7/SCA7), patients with FGF14/SCA27B and SPG7, and controls. Cognitive function was assessed with the CCAS scale, and ataxia severity with the Scale for the assessment and rating of ataxia (SARA) and Composite Cerebellar Functional score (CCFS). We correlated CCAS score with ataxia severity, brain MRI, and plasma Neurofilament light chain (NfL) levels. Subtests comparisons among genotypes were adjusted for age, education, and SARA. In PolyQ SCAs carriers, we explored CCAS progression.

**Results:** We included 371 participants: 66 SCA1, 28 SCA2, 158 SCA3, 24 SCA7, 35 SPG7, 17 SCA27B, and 43 controls. SCA27B and SPG7 were older (69.5±9.5 and 57.8±10.6 years) with lower education (11.4±4.2 and 12.7±3.6 years) than PolyQ SCAs (from 40.3±14.0 in SCA7 to 45.9±11.2 years in SCA3, p<0.0001; education ranging from 14.4±3.1 for SCA2 to 15.4±2.8 years for SCA7, p<0.0001). In ataxic patients, definite CCAS was detected in 88% of SCA27B and 71% of SPG7 patients, followed by SCA2 (67%), SCA7 (67%), SCA1 (50%), and SCA3 (41%). Among preataxic PolyQ SCA carriers, CCAS was present in 11% (10/89), similar to controls (11.6%, p=1). However, phonemic fluency showed an early impairment in preataxic SCA1 carriers (11.8±4.5 vs 14.6±3.8, p=0.04).

In PolyQ SCAs, CCAS total raw score correlated with SARA (r=-0.54, p<0.0001), CCFS (r=-0.45; p<0.0001), and plasma NfL levels (r=-0.26, p=0.002). CCAS scores correlated with cerebellar volume in SCA2 (r=0.64, p<0.001). SPG7 patients showed significantly poorer
74 performance in executive function, short-term memory, and abstract reasoning compared to
75 SCA3 and SCA7. In PolyQ SCAs, improvements were observed during the first three years
76 after inclusion (+2.0±0.7 points, p=0.002; +2.6±0.8 points, p=0.0007; +2.7±0.8 p=0.001,
77 respectively). By year 4, the increase was not significant (+0.73±1.16 points, p=0.52).

78 **Discussion:** We observed early cognitive impairment in PolyQ SCAs carriers, correlating
79 with clinical measures, NfL levels, and cerebellum volume. Improvement over three years
80 likely reflects a practice effect, potentially limiting the scale's longitudinal utility.
81 **Introduction**

82 Hereditary cerebellar ataxias are a group of rare, neurodegenerative disorders that primarily
83 affect the cerebellum, with wide clinical and genetic heterogeneity. ¹ Among the dominant
84 forms, the most frequent spinocerebellar ataxias (SCAs) are caused by CAG expansions,
85 encoding polyglutamine (PolyQ) stretches in the corresponding proteins (ATXN1/SCA1,
86 ATXN2/SCA2, ATXN3/SCA3, CACNA1A/SCA6, ATXN7/SCA7 and TPB1S/SCA17). The
87 typical onset is in adulthood, preceded by a long presymptomatic phase.² Additionally, an
88 intronic GAA expansion in FGF14 gene has recently been found responsible for SCA27B,³ a
89 late onset ataxia accounting for about 15% of SCAs.⁴,⁵ Variants in the SPG7 gene, encoding
90 the mitochondrial protein paraplegin, result in SPG7 disease, one of the most common
91 recessive adult-onset spastic ataxia.⁶

92 The cerebellum, traditionally linked to motor control, is increasingly recognized for its role in
93 modulating cognition and affect.⁷ Cerebellar Cognitive-Affective Syndrome (CCAS)⁸,⁹ refers
94 to cognitive impairment from cerebellar injury due to various etiologies,¹⁰ affecting executive
95 functions, visuo-spatial skills, verbal memory, language, and neuropsychiatric symptoms,⁷,⁹
96 while sparing consciousness and other cortical functions.⁷,⁸ The potential link between the
97 cerebellum and cognitive dysfunction may be explained by disrupted circuits connecting the
98 cerebellum with the prefrontal, parietal, and limbic cortices.¹⁰ Traditional cognitive screening
99 scales like the Mini-Mental State Examination¹¹ and the Montreal Cognitive Assessment¹²
100 (MoCA) often fail to detect the subtle impairments typical of CCAS,⁹ particularly in the early
101 stages of the disease.¹³ This limitation has recently prompted the development of a new, more
102 sensitive assessment tool, the CCAS scale.⁹

103 Although cognitive profiles have been underexplored in PolyQ SCAs using varied
104 neuropsychological tests,¹³⁻¹⁸ recent studies have shown the potential of the CCAS scale for
105 distinguishing between healthy controls and SCA carriers.<sup>18,19</sup> However, cognitive
106 involvement has been minimally studied in SPG7<sup>20</sup> and never in SCA27B.

107 This study aimed to evaluate cognitive functions using the CCAS scale across the most
108 common subtypes of hereditary ataxia, determine the frequency and severity of CCAS,
109 identify potential genotype-specific cognitive patterns, and explore CCAS correlations with
110 clinical, imaging, and fluid biomarkers. In PolyQ SCAs, the research also investigated the
111 distinction between preataxic and ataxic individuals and longitudinal changes over time.

112 **Materials and methods**

113 **Study population**

114 We included preataxic and ataxic PolyQ SCAs expansion carriers (ATXN1/SCA1,
115 ATXN2/SCA2, ATXN3/SCA3, and ATXN7/SCA7), non-PolyQ ataxic patients (GAA ataxic
116 expansion carriers in FGF14/SCA27B and SPG7 variant carriers), and healthy controls.

117 Participants were enrolled in: i) SPATAX study (NCT00140829) at the Paris Brain Institute
118 (ICM), Pitié-Salpêtrière University Hospital, and the Neurology Department of the
119 Montpellier University Hospital for patients with PolyQ and non-PolyQ spinocerebellar
degenerations; ii) BIOMOV study (NCT05034172) at the Paris Brain Institute (ICM), Pitié-
120 Salpêtrière University Hospital for preataxic and ataxic carriers with PolyQ and non-PolyQ
121 spinocerebellar degenerations; iii) CERMOI study (NCT04288128)¹⁷ at the Paris Brain
122 Institute (ICM), focusing on SCA2 and SCA7 carriers with a SARA score below 15 with a
123 one-year follow-up; and iv) READISCA study (NCT03487367)²¹ conducted at Paris Brain
124 Institute (ICM), 18 US centers, and German Center for Neurodegenerative Diseases in Bonn
125 (List of investigators in Supplementary Materials), focusing on SCA1 and SCA3 carriers with
126 a SARA score less than or equal to 9.5, with a five-year follow-up. We also included controls
127 as part of the READISCA study and consisted of patients' siblings with a confirmed negative
128 genetic test.
129
130 **Clinical assessment**

131 For all participants, the clinical examination included the Scale for the Assessment and Rating
132 of Ataxia (SARA), with preataxic carriers defined by a score below 3 out of 40,²² and a
133 disability stage evaluation ranging from 0 (no functional handicap) to 7 (confined to bed). In
134 PolyQ SCAs carriers, we utilized the Composite Cerebellar Functional Severity score
135 (CCFS).²³ SPG7 patients were assessed also with the Spastic Paraplegia Rating Scale
136 (SPRS).²⁴ Clinical assessments were conducted by a movement disorders specialist.

137 The neuropsychological evaluation was performed with the CCAS scale⁹ in English, German,
138 and French. This scale evaluates 10 items including semantic and phonemic fluency, category
139 switching, digit span forward, digit span backward, cube draw and copy (if needed), verbal
140 recall, similarities, Go/No-go, and an evaluation of neuropsychiatric symptoms with the affect
141 subtest, allowing to classify the cognitive impairment as definite CCAS (3 or more failed
142 subtests), probable CCAS (2 failed subtests), possible CCAS (1 failed subtest), and absent
143 CCAS. At baseline, cognitive function was evaluated using version 1A of the CCAS scale, as
144 it was the only version available. Total raw scores and total fail scores (number of subtests
145 failed) were recorded. Alternative version were used when available at the follow-up visits.

146 **Plasma biomarkers**

147 We collected plasma samples on an EDTA anticoagulant tube, frozen at -80°C, and stored in
148 the local biobank (EU), or BioSEND (biosend.org/) repository (US). Plasma Neurofilament
149 Light chain (NfL) levels were measured in duplicate using an ultrasensitive single-molecule
150 array on the Simoa HD-1 Analyzer (Quanterix), as previously established.²¹

151 **Neuroimaging**

152 For PolyQ SCA carriers, a 3T brain MRI (Siemens Magnetom PrismaFit) was performed
153 concurrently with the first visit (see Supplementary methods).
154

For each participant, cognitive evaluation, biomarker collection, and brain MRI were
performed on the same day.

155

156

## Statistical Analysis

157

Quantitative variables were expressed as mean ± SD and qualitative variables as frequency (%). Comparisons between genotypes were performed using ANOVA, followed by post-hoc pairwise t-tests, with Holm adjustments for multiple comparisons. These comparisons were conducted for all participants pooled, for ataxic participants only, and for non-ataxic participants only (non-ataxic were all PolyQ SCAs). We computed Pearson correlations between CCAS total raw score and results from clinical assessments, cerebellum volume, and plasma NfL concentrations. Correlations were analyzed by genotype, and by group of genotypes (Pooled PolyQ SCAs and Pooled non-PolyQ SCAs).

158

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165

We measured the internal consistency of the scale using the Cronbach's alpha. To check if an item was deteriorating this consistency, we computed the Cronbach's alpha after removing it, and proceeded so for each item. Pearson correlations were computed between each CCAS item and clinical and NfL levels. Correlations with neuroimaging variables were explored in each genotype. We used Holm-adjustment for each clinical and neuroimaging variables (n=27).

166

167

168

169

170

171

To account for genotype differences, we analyzed the differences in CCAS total raw score and each item value between genotypes, adjusting for age, education, and SARA. Pairwise comparisons were performed on the marginal means and Holm adjusted for multiple comparisons.

172

173

174

175

Longitudinal CCAS assessments were available only for PolyQ SCAs participants. The longitudinal progression of the CCAS was clearly non-linear, and the time points were not equally spaced. Therefore, we grouped the visits based on time since inclusion as follows: Group 1 for baseline, Group 2 for 0.5< time ≤ 1.5, Group 3 for 1.5< time ≤ 2.5 years, etc. This

176

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178
allowed us to perform Mixed Models for Repeated Measures, to have a comprehensive model describing the non-linear effects and consider simultaneously the visit number and the time since inclusion. We included controls in the models but separated them from PolyQ SCAs participants. We also looked at the interaction between group and time to describe whether ataxic SCA participants, preataxic SCA participants, and controls progressed differently. We assessed the impact of the version by including it as a covariate in the model, considering only versions A and B due to the small sample size of other versions. We conducted this version analysis on all CCAS items, pooling controls and SCA participants, as we aimed to investigate the inherent practice effect of the scale.

Statistical tests were performed at the conventional two-tailed type I error of 0.05. Data were analyzed using R version 4.2.0.

## Data availability

Individual anonymized participant data and relevant clinical study documents will be available for qualified scientific and medical researchers as necessary for doing legitimate research. To request access to the data and submit a research proposal, please send a request to giulia.coarelli@icm-institute.org and alexandra.durr@icm-institute.org.

## Results

### Clinical and imaging characteristics

#### All participants

371 participants were enrolled between August 2018 and April 2024, including 276 carriers of pathogenic PolyQ-SCAs expansions (89 preataxic) in the ATXN1/SCA1 (n= 66), ATXN2/SCA2 (n= 28), ATXN3/SCA3 (n= 158), and ATXN7/SCA7 (n= 24) genes (Fig. 1). The non-PolyQ group included 17 patients with FGF14/SCA27B and 35 patients with SPG7, along with 43 healthy controls. The education levels were lower in SPG7 (12.7±3.6 years) and
204 SCA27B (11.4±4.2 years) compared to PolyQ SCAs (from SCA2 with 14.4±3.1 years to
205 SCA7 with 15.4±2.8 years, all pairwise *p*< 0.05 except SCA2 vs SPG7) and controls
206 (15.2±2.2 years, all pairwise *p*< 0.01) (Table 1). Brain MRIs were available for 120
207 participants with PolyQ SCA ataxias (25 SCA1, 15 SCA2, 65 SCA3, 15 SCA7).

208 • Ataxic participants

209 Among ataxic patients, the age at examination was significantly different between PolyQ
210 SCAs and SCA27B and SPG7 (all pairwise *p*< 0.001). Patients with SCA27B were the oldest
211 with a mean age at examination of 69.5±9.5 years, followed by SPG7 (57.5±10.3 years),
212 compared to the patients with PolyQ SCAs, whose ages ranged from 38.2±14.8 years for
213 SCA7 to 48.9±10.7 for SCA1. Significant differences were observed in disease duration,
214 ranging from the longest in SPG7 (20.5±8.3 years) and SCA27B (15.8±10.2 years) to the
215 shortest in SCA1 (8.3±6.1 years, *p*< 0.0001). Disability was greater in patients with SPG7,
216 with a mean disability stage of 4.0±1.3, compared to ataxic patients with PolyQ SCAs
217 (ranging from 2.2±1.2 for SCA3 to 2.8±1.3 for SCA7, with all pairwise comparisons *p*<
218 0.001). Patients with SCA27B had intermediate disability values (3.4±1.4). SPG7 had higher
219 SARA score (15.2±6.0) than SCA1, SCA2, and SCA3 (15.2±6.0 vs 9.2±3.7, 11.4±6.3 and
220 8.5±4.7, respectively, *p*<0.001) and between SCA7 and SCA3 (13.0±5.9 vs 8.6±4.7, *p*= 0.02),
221 eTable 1. The SCA2 group showed significantly greater cerebellar atrophy compared to other
222 PolyQ SCAs (6.8±0.7 % eTIV, *n*= 10 for SCA2 vs 8.6±0.8, *n*= 38 for SCA1, 8.6±0.7, *n*= 37
223 for SCA3, and 8.2±1.2, *n*=6for SCA7, all pairwise *p*< 0.001). Additionally, NfL levels were
224 significantly (all *p*< 0.001) increased in all groups compared to controls (4.6±2.3 pg/mL),
225 with the lowest value in the SPG7 group (9.7±2.5 pg/mL), intermediate values in SCA2 and
226 SCA27B groups (16.8±5.8 and 16.9±9.9 pg/mL), and the highest values in SCA1 (22.1±10.3
227 pg/mL), SCA3 (22.6±6.5 pg/mL) and SCA7 (26.2±10.3 pg/mL).

228 • Preataxic participants
The PolyQ SCAs group comprised 89 preataxic carriers (28 SCA1, 7 SCA2, 45 SCA3, and 9 SCA7), with similar age at examination, years of education, clinical scores, and CCAS total raw scores compared to control group (eTable 2). Differences in NfL levels were already evident at the preataxic stage in all PolyQ SCAs compared to controls (4.6±2.3 pg/ml), with values ranging from 11.4±5.5 pg/ml in SCA1 to 15.3±6.4 pg/ml in SCA3 (all pairwise *p*< 0.001, eTable 2). Differences of cerebellar atrophy were also observed in the preataxic groups, with SCA3 showing significantly larger cerebellar volume (9.4±0.6% eTIV, n= 27) compared to SCA2 (7.9±1.2% eTIV, n= 5, *p*= 0.001) and SCA7 (8.5±0.9% eTIV, n= 9, *p*= 0.011).

## Cognitive impairment assessed by CCAS scale

In ataxic patients, definite CCAS was detected in 88% of SCA27B and 71% of SPG7 patients, followed by SCA2 (67%), SCA7 (67%), SCA1 (50%), and SCA3 (41%). CCAS total raw scores were similar among the groups with a difference only detected for SPG7 and SCA27B patients, having lower scores than SCA3 patients (mean of 79.0±15.7 in SPG7 and 76.4±9.5 in SCA27B vs 90.2±15.1 in SCA3, *p*< 0.0001, Fig. 2A, eTable 1) and SCA1 patients (88.8±13.3 vs SCA27B, *p*= 0.037). Among patients with PolyQ SCAs, CCAS total raw scores were comparable (Fig. 2A, eTable 1). In preataxic PolyQ SCA carriers, definite CCAS was found in 3/28 (11%) SCA1, 2/7 (28%) SCA2, 5/45 (11%) SCA3, and none in SCA7, eTable 2. In controls, 5 out of 43 (12%) exhibited definite CCAS. This rate was significantly lower than ataxic patients (*p*< 0.001) but similar to preataxic PolyQ SCAs carriers (*p*= 1). Additionally, among the preataxic carriers (Fig. 2B), the CCAS total raw scores were not different in pairwise comparisons (the lowest *p*-value being 0.09 between preataxic SCA1 with 97.6±11.2 and controls with 104.1±8.5, eTable 2). However, phonemic fluency was significantly lower in SCA1 preataxic carriers compared to controls (11.8±4.5 vs 14.6±3.8, *p*= 0.04 after pairwise adjustment, eTable 2).

## Baseline correlation of CCAS with clinical, imaging, and plasma NfL data
No significant correlation was found between age and the CCAS total raw score in any of the pooled genotype groups (r = -0.11, p= 0.073 in PolyQ SCAs and r= -0.16, p= 0.26 in non-PolyQ SCAs). In PolyQ SCAs and SPG7, we observed a significant positive correlation between the CCAS Total raw score and years of education (r = 0.50, p< 0.001 and r = 0.53, p< 0.002, respectively). This correlation was not found in SCA27B subgroup (r = 0.31, p= 0.33), which had the lowest mean years of education (Table 1). In pooled PolyQ SCAs carriers, we observed a significant negative correlation between the CCAS total raw score and SARA (r = -0.54, p< 0.0001, n= 275). Similar correlations were found for CCFS and disability stage (r = -0.45, p< 0.0001 and r = -0.51, p< 0.0001, respectively, Table 2). For non-PolyQ SCAs, similar trends were observed between the CCAS total raw score and SARA even if not significant (r = -0.45, p= 0.071 in SCA27B, and r = -0.26, p= 0.014 in SPG7 carriers) or disability stage (SPG7 r = -0.31, p= 0.076, SCA27B r = -0.48, p= 0.05). At baseline, in PolyQ SCAs participants, the cognitive impairment (CCAS total score) was weakly correlated with plasma NfL levels (r = -0.26, p= 0.002, n= 226). When considering genotypes separately, this correlation was significant in SCA3 and SCA7 carriers (r= -0.32, p<0.001, n = 122 and r = -0.53, p= 0.008, n= 24, respectively), but not in SCA1 and SCA2 (r = -0.22, p= 0.10 and r = -0.04, p= 0.86). For non-PolyQ SCAs, we found CCAS correlations with plasma NfL levels for SCA27B patients (r = -0.61, p= 0.027, n= 17), but not for SPG7 patients (r = -0.15, p= 0.56, n= 23). Regarding correlations with brain MRI, the CCAS total raw score was highly correlated with cerebellum volume (r = 0.64, p= 0.01) in SCA2. However, for other genotypes and other regions including frontal cortical thicknesses, no correlations were found.

## CCAS subtest analysis

The different CCAS scale subtests presented an acceptable internal consistency in both versions A and B, with a Cronbach alpha = 0.71 [0.68-0.74] for version A and 0.71 [0.59-
0.80] for version B. No item removal increased these values, highlighting the importance of each item in the total score.

Given the differences in age, education, and SARA across ataxia subtypes, we examined genotype difference using models adjusted for these variables (Table 3). We observed different performances in some subtests: patients with SPG7 exhibited the worst performances in inhibitory control (Go/No-go subtest, marginal mean [95% CI]: 1.0 [0.7-1.3]) compared with SCA3 (1.5 [1.4-1.7], *p* = 0.021), and SCA7 (1.7 [1.4-2], *p* = 0.016). Additionally, patients with SPG7 had more severe short-term memory impairment (digit span forward) compared with SCA3 (5.5 [5-5.9] vs 6.3 [6.1-6.5], *p* = 0.02), and verbal reasoning impairment (similarities) compared with SCA7 (6.8 [6.4-7.2] vs 7.7 [7.3-8.1], *p* = 0.04) (Table 3). In contrast, in SPG7, the affect subtest was less impaired (5.9 [5.6-6.2]) compared to SCA27B (5.1 [4.6-5.6], *p* = 0.03) and SCA2 participants (5.1 [4.8-5.4], *p* = 0.004), who had the lowest scores. Among the PolyQ SCAs, SCA1 and SCA3 also had less impairment in the affect subtest (5.7 [5.5-5.9], *p* = 0.02 and 5.7 [5.5-5.8], *p* = 0.006) compared to SCA2.

## Longitudinal progression of CCAS in PolyQ SCAs

Longitudinal CCAS scale data were available only for PolyQ SCAs groups (preataxic and ataxic carriers). The CERMOI study provided a 1-year follow-up for 15 SCA2 and 15 SCA7 participants and the READISCA study provided up to 4 years of follow-up for 108 SCA3 carriers, 39 SCA1 carriers, and 43 controls. The number of visits per year decreased over time in READISCA, with 220, 163, 120, 104, and 49 visits available from baseline to 4-year follow-up visit (Fig. 3).

Over the 4-year follow-up, there were no significant differences of CCAS progression between ataxic PolyQ SCAs, preataxic PolyQ SCA, and controls (*p* = 0.14). Therefore, we combined ataxic and preataxic SCAs participants.
One year after the baseline assessment, SCAs participants exhibited a significant increase of +2.0±0.7 points in the CCAS total raw score (p= 0.002), Fig. 2. This improvement was consistent across different subtests, with significant increases in phonemic fluency and verbal recall (+0.92±0.29 points, p= 0.001 and +0.64±0.20 points, p= 0.001, respectively, Fig. 2). A similar pattern was observed at one-year follow-up in controls, with an increase in the CCAS total raw score of +2.4±1.6 points (p= 0.14), and only significant for phonemic fluency (+1.8±0.7 points, p= 0.01) (Fig. 2).

A sustained and significant improvement in the CCAS total raw score was observed at 2-year and 3-year follow-up visits (+2.6±0.8 points, p= 0.0007 and +2.7±0.8 p= 0.001, respectively).
By the 4-year follow-up visit, the increase was no longer significant (+0.73±1.16 points, p= 0.52) (Fig. 2). Controls did not show significant change of the total CCAS score at any timepoint (Fig. 2). At the subtest level, SCA participants showed no significant differences in longitudinal progression compared to controls, except at the 4-year follow-up visit, where SCA participants exhibited a significant deterioration in semantic fluency (-2.6±0.6 points, p= 0.001 compared to baseline, Fig. 2). The item showing the most consistent practice effect was verbal recall, with SCA participants demonstrating significant improvement at each follow-up visit (all p< 0.01, Fig. 2).

Regarding the analysis of the version used during the 4-year follow-up period, 484 visits were assessed by version A and 50 with version B. Across time points, the CCAS total raw scores did not differ between the two versions (with version B +0.57±1.15, p= 0.62). However, participants performed significantly better on the categoric switching item (+1.07±0.45, p= 0.02) and the digit span backward item (+0.59±0.17, p= 0.001) when assessed with version B (eTable 3).

## Discussion
This study presents an analysis of cognitive impairment in a large cohort of spinocerebellar degenerations that result from six different genotypes, using the CCAS scale and examining its correlation with motor scores, plasma NfL, and brain MRI. We tested patients with PolyQ SCAs, and for the first time, included those with the recently described SCA27B and autosomal recessive SPG7 ataxia. Although cognitive impairment is now an increasingly recognized feature of hereditary ataxias,¹³,¹⁹ it has likely been underestimated in the past due to the lack of suitable psychometric tools for detection²⁵ and the predominance of dysarthria.¹⁴

Our findings confirm the presence of CCAS in PolyQ SCAs and underscore its high prevalence in both SCA27B, typically considered as a late-onset, almost pure cerebellar ataxia,⁵ and SPG7, a complex spastic-ataxia caused by mitochondrial dysfunction.²⁶ We observed significant rates of definite CCAS, with 88% in SCA27B and 68% in SPG7, indicating that CCAS is a common feature across different forms of cerebellar ataxias. For SCA7B, cognitive impairment had not yet been clearly reported and was likely underestimated when based solely on clinical judgment.²⁷ In PolyQ SCAs, we detected definite CCAS even in the early stages, as previously suggested for SCA3.¹³ Among the factors influencing CCAS scale performance, our results reveal a significant correlation between the CCAS score and years of education, confirming that educational level plays a role, acting as a protective factor against cognitive impairment.¹⁸ However, the mild but not significant correlation in SCA27B patients, the subgroup with the lowest mean years of education, implies that the overall impact of education on CCAS may not be as strong as initially suggested.¹⁸ Regarding age, we did not find a significant correlation between age and the total raw CCAS score in any of the groups. This result is consistent with a previous study,²⁸ while others have reported a mild correlation,¹³,¹⁸ leaving the nature of this relationship uncertain. The absence or the mild correlation with age may suggest that
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cognitive dysfunction is more closely linked to the neurodegenerative process itself rather
than aging.

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In PolyQ SCAs, we observed a strong correlation between CCAS and motor scores (SARA and CCFS), as previously published.<sup>13,18,29</sup> We confirmed that there is no difference in the frequency of definite CCAS between preataxic PolyQ SCAs carriers and controls;<sup>18</sup> however, the phonemic fluency score was already significantly affected in preataxic SCA1 carriers.

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This suggests that the development of cognitive symptoms starts in the early ataxic phase, closely related to the motor component of the disease.<sup>13,17</sup> It had been proposed that the cognitive and motor symptoms were associated with dysfunction in distinct regions of the cerebellum: the motor and the cognitive cerebellum.<sup>30</sup> The correlation between the CCAS scale and SARA score suggests that both regions may be globally affected simultaneously. In non-PolyQ ataxias, we did not find a correlation between the total CCAS raw score and SARA. This may be due to SARA not fully capturing motor disability in these two groups, as SCA27B is characterized by episodic symptom fluctuations and SPG7 by spasticity, which is better assessed by the SPRS.<sup>24</sup> In patients with SCA27B, we could not rule out the influence of other comorbidities on cognitive performance; for SPG7, the cognitive deficits may be attributed to more widespread mitochondrial involvement.<sup>31</sup>

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NfL levels were significantly correlated with cognitive impairment only in the SCA3 and SCA7 groups. This finding reflects that these two genotypes exhibit the highest NfL levels among the PolyQ SCAs, as previously shown,<sup>32</sup> despite having similar disease duration and severity. This discrepancy raises questions about the SCA2 group, which displays the greatest cerebellar atrophy but has the lowest NfL levels among the PolyQ SCAs. For the first time, we report plasma NfL concentrations in patients with SCA27B and SPG7, revealing low values, with SPG7 not differing from controls, despite the advanced age at sampling and

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disease duration. These results support the hypothesis that NfL levels are associated with the
rate of the neurodegenerative process.<sup>33</sup>

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Although, in PolyQ SCAs, motor and cognitive involvement are closely related, we found a
significant correlation between cerebellar volume and the CCAS total raw score only in SCA2
group. This group showed the most important cerebellar atrophy and the most severe
involvement in the affect item. The lack of correlation between CCAS and cerebellar atrophy
in the other PolyQ SCA subgroups may indicate early subtle impairment in the cerebellum-
frontal circuitry, rather than being solely due to atrophy.<sup>13,20</sup> In SCA3, it is noteworthy that
cerebellum atrophy is milder, with relatively spared cerebellar cortex and more pronounced
involvement of the dentate nucleus.<sup>34,35</sup> Our results likely suggests that cerebellar
degeneration primarily affects the executive functions and linguistic processing in PolyQ-
SCAs<sup>18,19</sup>, and secondarily the modulation of affect and emotions.<sup>17</sup>

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In our analysis of CCAS subtests, SPG7 showed the most significant impairment in executive
function, short-term memory, and verbal reasoning, with relatively less involvement in
affective and emotional functions. In a previous study that assessed six SPG7 patients using
the CCAS scale and a comprehensive neuropsychological test battery, difficulties were
observed in language, verbal memory, executive function, and emotional regulation.<sup>20</sup>

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However, in our study emotional dysfunction was less pronounced in SPG7 patients
compared to those with SCAs. In fact, the affect subtest was more severely impaired in SCA2
than in other hereditary ataxias. Impairments in affect and social cognition are evident in
patients with Friedreich's ataxia<sup>36</sup> and SCAs,<sup>37-39</sup> even at very early stages,<sup>17</sup> possibly linked
to a dysfunction in the corticocerebellar network.<sup>39-41</sup> In SCA2 patients, the recognition of
anger has been reported to correlate with the volume of specific posterior cerebellar lobules
(lobule VIIIIB, Crus II, and IX) as well as with DTI alterations in the middle cerebellar
peduncle.<sup>40</sup> The affect assessed by the CCAS scale is a qualitative and subjective evaluation

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of the patient's behavior by the rater. This consideration, along with the findings reported above, emphasizes the need for further investigation into social cognition (e.g., theory of mind test), social perception, and social behavior using objective and reliable measures, as well as dynamic assessment tools.<sup>13,29</sup> Impaired social cognition can significantly affect patient's quality of life, making it challenging to maintain relationships, manage their professional life, and can also impact their care and interactions with healthcare providers.

The longitudinal follow-up of cognitive assessment using the CCAS scale in PolyQ SCAs carriers revealed a significant improvement in the CCAS total raw score. The only area of decline observed after four years was semantic fluency. It is well-established that language impairment, particularly in semantic and phonemic fluency, affect SCAs carriers even at preataxic stages<sup>16,19,41,42</sup>, not explained by slower language production.<sup>43</sup> The improvement may be attributed to a practice effect, often observed in longitudinal assessments by MMSE, MoCA, and Clinical Dementia Rating (CDR) Scale, both in healthy controls and in patients with cognitive impairments<sup>44-46</sup>. Moreover, the CCAS scale shares some items with the MoCA scale<sup>12</sup>, that also showed practice effect in patients with mild cognitive impairment (MCI).<sup>47</sup> These findings suggest that the CCAS scale may not be suitable for long-term follow-up, and it is not ideal for use in clinical trials. Changing the version did not reduce this effect, but the sample size of alternative version was small so further investigations on version impact to reduce practice effect are needed. Moreover, the absence of significant worsening over time may be attributed to the slow progression of these spinocerebellar degenerations.

Our study has some limitations. First, there were differences in age at examination, disease duration, and disease severity between PolyQ and non-PolyQ SCAs carriers, making it difficult to draw conclusions about CCAS in the earlier stage of SCA27B and SPG7 diseases. However, this is linked to the different clinical features of these conditions, such as slower disease progression in SPG7 and SCA27B patients and the older age at onset in SCA27B.
Although no correlation was found between age at examination and CCAS score in any group (PolyQ SCAs, non-PolyQ SCAs, and controls), a slight difference between controls and patients with SCA3, SCA27B, and SPG7 should be noted. This difference can be explained by the fact that controls were recruited exclusively from at-risk individuals resulted negative at the genetic test in the READISCA cohort, a study focused on the early stage of ataxia.

Additionally, cognitive impairment was assessed using only the CCAS scale, without a thorough exploration of other cognitive functions. Lastly, brain MRI was conducted only in PolyQ SCAs focusing on volumetry data that were available in all groups. DTI sequences that could have provided insights into cerebello-cortical connectivity in various networks involved in cognition and social functioning were only available for the SCA1 and SCA3 groups in READISCA, limiting sample size for meaningful analyses.<sup>40,41,48</sup>

In conclusion, we observed a high frequency of definite CCAS in patients with different genetic ataxias. In PolyQ-SCAs, significant correlations between CCAS, clinical scores, NfL levels, and cerebellum volume indicate that cognitive dysfunction is a key component of the neurodegenerative process. The CCAS scale proves valuable for detecting cognitive impairment in patients with hereditary ataxia, even in the early stages of the disease.

However, the observed improvement during the follow-up indicates a potential practice effect, which may limit its effectiveness for longitudinal assessment but opening a therapeutic option for cognitive training.

Acknowledgments

We would like to thank all the participants included in this study. We would also like to thank Inserm, which sponsored the NCT04288128 and NCT00140829 studies, Assistance Publique – Hôpitaux de Paris (AP-HP) which sponsored the NCT05034172 and NCT03487367 studies.
451 NCT03487367 was supported by the National Institute of Neurological Disorders and Stroke (NINDS) grant U01 NS104326. The Center for Magnetic Resonance Research is supported by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) grant P41 EB027061, the Institutional Center Cores for Advanced Neuroimaging award P30 NS076408 and S10 OD017974.

456 The READISCA investigators would like to thank all participants for their enduring willingness and interest in this research. We extend gratitude to Diane Hutter, Ann Fishman, Jason Macmore, Brigitte Jacoby, Samantha Pierce, Jessica Magenheim, Anke Ruehling and Hortense Hurmic for study coordination and Chantel Potvin and Erika Espinoza for project management.

461

462 **Study Funding**

463 The READISCA projet was supported by the National Institute of Neurological Disorders and Stroke (NINDS) grant U01 NS104326. The Center for Magnetic Resonance Research is supported by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) grant P41 EB027061, the Institutional Center Cores for Advanced Neuroimaging award P30 NS076408 and S10 OD017974. Research reported in this publication was also supported by an Academic Investment Research Program (AIRP) award at the University of Minnesota and the National Center for Advancing Translational Sciences of the National Institutes of Health Award Number UL1TR000114. A portion of this work was performed in the McKnight Brain Institute of the University of Florida at the National High Magnetic Field Laboratory's Advanced Magnetic Resonance Imaging and Spectroscopy (AMRIS) Facility, which is supported by National Science Foundation Cooperative Agreement DMR-1644779 and the State of Florida and was supported in part by an NIH award, S10 OD021726, for High End
475 Instrumentation. The content is solely the responsibility of the authors and does not
476 necessarily represent the official views of the National Institutes of Health.

477 The CERMOI study was co-funded by Biogen, Cambridge, Massachusetts, US, and Ionis,
478 Carlsbad, California, US.

479

480 **Conflict of interests**

481 S. Tezenas du Montcel declares that her Institution (Paris Brain Institute) receives consulting
482 fees on her behalf from Vico Therapeutics unrelated to the present manuscript. Dr. Öz has
483 consulted for IXICO Technologies Limited, uniQure biopharma B.V., VICO Therapeutics,
484 Servier, Sanofi and UCB Biopharma SRL / Lacerta Therapeutics Inc, serves on the Scientific
485 Advisory Board of BrainSpec Inc. and received research support from Biogen.

486

487 **Supplementary material**

488 Supplementary material is available online.

489
<table><thead><tr><td>Name</td><td>Location</td><td>Role</td><td>Contribution</td></tr></thead><tbody><tr><td>Claire Ewenczyk MD, PhD</td><td>Sorbonne Université, Paris Brain Institute (ICM), Assistance Publique des Hôpitaux de Paris (APHP), France</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Anna Heinzmann, MD</td><td>Sorbonne Université, Paris Brain Institute (ICM), Assistance Publique des Hôpitaux de Paris (APHP), France</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Pauline Lallemant, MD, PhD</td><td>Sorbonne Université, Paris Brain Institute (ICM), Assistance Publique des Hôpitaux de Paris (APHP), France</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Solveig Heide MD,</td><td>Sorbonne Université, Paris Brain Institute (ICM), Assistance Publique des Hôpitaux de Paris (APHP), France</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Perrine Charles MD, PhD</td><td>Sorbonne Université, Paris Brain Institute (ICM), Assistance Publique des Hôpitaux de Paris (APHP), France</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Paulina Cunha MD</td><td>Sorbonne Université, Paris Brain Institute (ICM), Assistance Publique des Hôpitaux de Paris (APHP), France</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Hortense Hurmic MsC</td><td>Sorbonne Université, Paris Brain Institute (ICM), Assistance Publique des Hôpitaux de Paris (APHP), France</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Thomas Klockgether, MD, PhD</td><td>German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany</td><td>Principal Investigator</td><td></td></tr><tr><td>Marcus Grobe-Einsler MD,</td><td>German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Demet Oender MD</td><td>German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Okka Kimmich MD</td><td>German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Nina Roy PhD</td><td>German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Ilaria Giordano</td><td>German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Veronika Purrer</td><td>German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Carolin Miklitz</td><td>German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Cornelia McCormick</td><td>German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Titilayo, Olubajo, MD</td><td>Weill Cornell Medicine at Houston Methodist Hospital, Houston, Texas, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Matthew Burns MD, PhD</td><td>University of Florida, Gainesville, FL, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Trevor Hawkins, MD</td><td>University of Colorado, Boulder, CO, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Khalaf, Bushara, MD</td><td>Department of Neurology, University of</td><td>Site Investigator</td><td>Data collection</td></tr></tbody></table>
<table><tr><td></td><td>Minnesota, Minneapolis, MN, USA.</td><td></td><td></td></tr><tr><td>Susan, Perlman, MD</td><td>Department of Neurology, University of California, Los Angeles, Los Angeles, CA, USA.</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>SH Subramony, MD</td><td>Department of Neurology and McKnight Brain Institute, University of Florida, Gainesville, FL, USA.</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>David Morgan, MD, PhD</td><td>Michigan State University, Dept. Translational Neuroscience, Grand Rapids</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Brianna Jackman, MS</td><td>Department of Neurology, University of Michigan, Ann Arbor, MI, USA.</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Lauren Seeberger, MD</td><td>University of Colorado, Boulder, CO, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Drew Scott Kern, MD</td><td>University of Colorado, Boulder, CO, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>George Wilmot, MD, PhD</td><td>Emory University, Atlanta, GA, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Laura Scorr, MD</td><td>Emory University, Atlanta, GA, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Liana Rosenthal MD, PhD</td><td>Johns Hopkins University, Baltimore, MD, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Chiadi Onyike, MD</td><td>Johns Hopkins University, Baltimore, MD, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Michael Geschwind, MD, PhD</td><td>University of California, San Francisco, CA, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Alexandra Nelson, MD, PhD</td><td>University of California, San Francisco, CA, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Cameron Dietiker, MD</td><td>University of California, San Francisco, CA, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Armen Moughamian, MD, PhD</td><td>University of California, San Francisco, CA, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Sheng-Han Kuo, MD</td><td>Columbia University</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Vikram Shakkottai, MD, PhD</td><td>University of Michigan</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Christopher Gomez, MD, PhD</td><td>University of Chicago, Chicago, IL, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Mahesh Padmanaban, MD</td><td>University of Chicago, Chicago, IL, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Talene Yacoubian, MD, PhD</td><td>Univ of Alabama-Birmingham</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Marissa Dean, MD</td><td>Univ of Alabama-Birmingham</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Jeremy Schmahmann, MD, PhD</td><td>Mass General Hospital (Harvard)</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Peggy C. Nopoulos,</td><td>University of Iowa</td><td>Site Investigator</td><td>Data collection</td></tr></table>
<table><tr><td>MD</td><td></td><td></td><td></td></tr><tr><td>Annie Killoran, MD</td><td>University of Iowa</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Puneet Opal, MD, PhD</td><td>Northwestern University, Evanston, IL, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Theresa Zesiewicz, MD</td><td>University of South Florida</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Sharon Sha, MD</td><td>Stanford University, Stanford, CA, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Veronica Santini, MD</td><td>Stanford University, Stanford, CA, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Jacinda Sampson, MD</td><td>Stanford University, Stanford, CA, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Peter Morrison, DO</td><td>University of Rochester, Rochester, NY, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Erika Augustine, MD</td><td>University of Rochester, Rochester, NY, USA</td><td>Site Investigator</td><td>Data collection</td></tr><tr><td>Alex Paciorkowski, MD</td><td>University of Rochester, Rochester, NY, USA</td><td>Site Investigator</td><td>Data collection</td></tr></table>
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616

617
618 **Figure legends**

619 **Figure 1: Number of patients in each ataxia group.**

620 **Figure 2: Distribution of the CCAS total raw scores among controls, PolyQ SCAs**
**carriers, SCA27B patients, and SPG7 patients.**

622 **Panel A:** The figure shows all participants for each group. The p-value are the unadjusted t-test p-values between each groups and controls. **Panel B:** Comparison between controls and preataxic PolyQ SCAs carriers (SARA < 3 out of 40). The p-value are the unadjusted t-test p-values between each groups and controls.

626

627

628 **Figure 3: Longitudinal progression of cognitive impairment assessed by CCAS.**

629 Longitudinal progression of CCAS total raw score and all CCAS item, estimated by linear
630 mixed effect models in PolyQ SCAs carriers over 4 years (baseline or Visit 1, and subsequent
631 visit 2, 3, 4 and 5).

632 Each point represents the estimate of visit year's effect on the score with its 95% confidence
633 interval for controls (blue) and SCA (red) participants. If the confidence interval does not
634 overlap with the baseline value (dashed line), the effect of the visit year is statistically
635 significant. The bottom-right panel shows the number of observations at each visit and for
636 each group.

637

638
<table><caption>Table 1: Baseline characteristics of all participants.</caption><thead><tr><th></th><th>Controls (n=43)</th><th>SCA1 (n=66)</th><th>SCA2 (n=28)</th><th>SCA3 (n=158)</th><th>SCA7 (n=24)</th><th>SPG7 (n=35)</th><th>SCA27B (n=17)</th><th>p-value</th></tr></thead><tbody><tr><td>Age (y)</td><td>38.7±9.5<sup>b,f,g</sup></td><td>44.6±10.8<sup>f,g</sup></td><td>42.7±13.5<sup>f,g</sup></td><td>45.9±11.2<sup>a,f,g</sup></td><td>40.3±14.0<sup>f,g</sup></td><td>57.8±10.6<sup>a,b,c,d,e</sup></td><td>69.5±9.5<sup>a,b,c,d,e,f</sup></td><td>&lt;0.0001</td></tr><tr><td>Education (y)</td><td>15.2±2.2<sup>f,g</sup></td><td>14.6±2.5<sup>f,g</sup></td><td>14.4±3.1<sup>g</sup></td><td>14.5±2.4<sup>f,g</sup></td><td>15.4±2.8<sup>f,g</sup></td><td>12.7±3.6<sup>a,b,c,d,e</sup></td><td>11.4±4.2<sup>a,b,c,d,e</sup></td><td>&lt;0.0001</td></tr><tr><td>CAG repeat expansion</td><td>n=29</td><td>n=42</td><td>n=24</td><td>n=102</td><td>n=19</td><td>n=30</td><td>n=12</td><td></td></tr><tr><td>Disability scale (max. value 7)</td><td>0.1±0.3<sup>b,c,d,e,f,g</sup></td><td>1.5±1.2<sup>a,f,g</sup></td><td>1.9±1.6<sup>a,f,g</sup></td><td>1.7±1.3<sup>a,f,g</sup></td><td>1.7±1.7<sup>a,f,g</sup></td><td>3.9±1.4<sup>a,b,c,d,e</sup></td><td>3.4±1.4<sup>a,b,c,d,e</sup></td><td>&lt;0.0001</td></tr><tr><td>SARA (max. value 40)</td><td>0.7±1.1<sup>b,c,d,e,f,g</sup></td><td>5.8±4.9<sup>a,f,g</sup></td><td>8.8±7.1<sup>a,f</sup></td><td>6.4±5.2<sup>a,f,g</sup></td><td>8.4±7.6<sup>a,f</sup></td><td>14.8±6.3<sup>a,b,c,d,e</sup></td><td>11.3±5.3<sup>a,b,d</sup></td><td>&lt;0.0001</td></tr><tr><td>CCFS (normal 0.85±0.05)</td><td>0.883±0.061<sup>b,d</sup></td><td>0.944±0.10</td><td>0.913±0.06</td><td>0.933±0.09</td><td>0.929±0.14</td><td></td><td></td><td>0.0277</td></tr><tr><td>SPRS (max. value 52)</td><td></td><td></td><td></td><td></td><td></td><td>17.5±7.2 (n=16)</td><td></td><td></td></tr><tr><td>Plasma NfL (pg/ml)</td><td>4.6±2.3<sup>b,c,d,e,g</sup></td><td>17.8±10.2<sup>a,f</sup></td><td>15.5±5.5<sup>a,d</sup></td><td>20.4±7.3<sup>a,c,f</sup></td><td>21.8±10.5<sup>a,f</sup></td><td>10.4±3.4<sup>b,d,e</sup></td><td>16.9±9.9<sup>a</sup></td><td>&lt;0.0001</td></tr><tr><td>Disease duration</td><td>n=38</td><td>n=54</td><td>n=26</td><td>n=122</td><td>n=17</td><td>n=17</td><td>n=13</td><td></td></tr><tr><td>Age of onset</td><td>n=36</td><td>n=18</td><td>n=18</td><td>n=108</td><td>n=15</td><td>n=6</td><td>n=15</td><td>&lt;0.0001</td></tr><tr><td>Estimated time to onset</td><td>n=64<sup>d</sup></td><td>n=64<sup>d</sup></td><td>n=64<sup>d</sup></td><td>n=64<sup>d</sup></td><td>n=64<sup>d</sup></td><td>n=64<sup>d</sup></td><td>n=64<sup>d</sup></td><td>0.0151</td></tr><tr><td>Cerebellum total (% ICV)</td><td>n=25</td><td>n=25</td><td>n=25</td><td>n=25</td><td>n=25</td><td>n=25</td><td>n=25</td><td>&lt;0.0001</td></tr><tr><td>Preataxic carriers</td><td>28 (42.4%)</td><td>7 (25%)</td><td>45 (28.7%)</td><td>9 (37.5%)</td><td>1 (3.1%)</td><td>0 (0%)</td><td>0 (0%)</td><td>0.0002</td></tr><tr><td>CCAS total raw score (max. value 120)</td><td>104.1±8.5<sup>b,c,d,e,f,g</sup></td><td>92.2±13.2<sup>a,f,g</sup></td><td>87.6±13.9<sup>a</sup></td><td>93.6±15<sup>a,f,g</sup></td><td>93.5±13.3<sup>a,f,g</sup></td><td>78.9±16.3<sup>a,b,d,e</sup></td><td>76.4±9.5<sup>a,b,d,e</sup></td><td>&lt;0.0001</td></tr><tr><td>Definitive CCAS</td><td>5 (11.6%)</td><td>22 (33.3%)</td><td>16 (57.1%)</td><td>51 (32.3%)</td><td>10 (41.7%)</td><td>24 (68.6%)</td><td>15 (88.2%)</td><td>&lt;0.0001</td></tr><tr><td>Semantic fluency</td><td>23.0±3.2<sup>b,c,d,e,f,g</sup></td><td>19.3±5.3<sup>a,g</sup></td><td>18.3±4.7<sup>a</sup></td><td>19.7±5.1<sup>a,f,g</sup></td><td>18.7±5.2<sup>a</sup></td><td>16.4±5.6<sup>a,d</sup></td><td>15.1±4.2<sup>a,b,d</sup></td><td>&lt;0.0001</td></tr><tr><td>Phonemic fluency</td><td>14.6±3.8<sup>b,c,d,e,f,g</sup></td><td>11.6±4.4<sup>a,f,g</sup></td><td>9.6±3.7<sup>a</sup></td><td>11.6±4.7<sup>a,f,g</sup></td><td>12.4±4.3<sup>f,g</sup></td><td>8.9±4.4<sup>a,b,c,d,e</sup></td><td>7.7±3.3<sup>a,b,d,e</sup></td><td>&lt;0.0001</td></tr><tr><td>Categoric switching</td><td>13.3±2.3<sup>c,d,f,g</sup></td><td>11.4±3.2<sup>f</sup></td><td>10.8±3.5<sup>a</sup></td><td>11.2±3.5<sup>a,f</sup></td><td>11.9±3.1<sup>f</sup></td><td>9.2±3.7<sup>a,b,c,d,e</sup></td><td>8.9±2.6<sup>a</sup></td><td>&lt;0.0001</td></tr><tr><td>Digit span forward</td><td>6.6±1.2<sup>b,f</sup></td><td>5.9±1.3<sup>a,f</sup></td><td>6.0±1.0<sup>f</sup></td><td>6.2±1.3<sup>f</sup></td><td>5.9±0.9</td><td>5.1±1.1<sup>a,b,c,d</sup></td><td>5.8±0.9</td><td>&lt;0.0001</td></tr><tr><td>Digit span backward</td><td>4.6±1.3<sup>f,g</sup></td><td>4.0±1.2</td><td>3.9±1.1</td><td>4.1±1.2<sup>f</sup></td><td>4.2±1.1</td><td>3.3±0.9<sup>a,d</sup></td><td>3.5±0.7<sup>a</sup></td><td>0.0003</td></tr><tr><td>Cube</td><td>14.0±1.7<sup>f</sup></td><td>13.3±3.4</td><td>13.5±2.3</td><td>14.0±1.9<sup>f</sup></td><td>13.1±2.8</td><td>12.2±4.0<sup>a,d</sup></td><td>13.6±2.1</td><td>0.0101</td></tr><tr><td>Verbal recall</td><td>13.1±2.2<sup>f,g</sup></td><td>12.5±2.9<sup>f,g</sup></td><td>11.8±3.4</td><td>12.3±2.9<sup>g</sup></td><td>12.6±3<sup>g</sup></td><td>10.7±3.3<sup>a,b</sup></td><td>9.4±2.5<sup>a,b,d,e</sup></td><td>&lt;0.0001</td></tr><tr><td>Similarities</td><td>7.4±0.8</td><td>7.3±0.8</td><td>7.2±1.1</td><td>7.3±1.0</td><td>7.7±0.5<sup>f</sup></td><td>6.8±1.5<sup>e</sup></td><td>7.1±0.9</td><td>0.0367</td></tr><tr><td>Go/No-go</td><td>1.7±0.6<sup>b,f,g</sup></td><td>1.3±0.8<sup>a,f,g</sup></td><td>1.4±0.7<sup>g</sup></td><td>1.6±0.6<sup>f,g</sup></td><td>1.5±0.7<sup>f,g</sup></td><td>0.9±0.9<sup>a,b,c,d,e</sup></td><td>0.7±0.8<sup>a,b,c,d,e</sup></td><td>&lt;0.0001</td></tr><tr><td>Affect</td><td>5.8±1.0<sup>c,g</sup></td><td>5.8±0.4<sup>c,g</sup></td><td>5.1±1.1<sup>a,b,d</sup></td><td>5.8±0.7<sup>c,g</sup></td><td>5.5±0.8</td><td>5.3±1.1</td><td>4.7±1.2<sup>a,b,d</sup></td><td>&lt;0.0001</td></tr></tbody></table>

Age at examination and Education are expressed in years (y), NfL concentrations in pg/mL.
Abbreviations: CCAS: Cerebellar Cognitive Affective Syndrome; CCFS: Composite Cerebellar Functional Severity score; ICV: Intracranial Volume; NfL: Neurofilament Light chain; SARA: Scale for the Assessment and Rating of Ataxia; y: years. Data are expressed as mean ± Standard deviation
646 (sample size in case of missing data), or frequency (percent). Significant pairwise comparisons are
647 shown as a,b,c,d,e,f,g for Controls, SCA1, SCA2, SCA3, SCA7, SPG7, and SCA27B respectively.
648
<table><caption>Table 2: Correlations between CCAS total score and demographic, clinical variables, MRI volumetry, and plasma NfL levels.</caption><thead><tr><th></th><th>Controls<br>(n=43)</th><th>SCA1<br>(n=66)</th><th>SCA2<br>(n=28)</th><th>SCA3<br>(n=158)</th><th>SCA7<br>(n=24)</th><th>Pooled<br>PolyQ<br>SCAs<br>(n=276)</th><th>SPG7<br>(n=35)</th><th>SCA27B<br>(n=17)</th><th>Pooled<br>non-<br>PolyQ<br>SCAs<br>(n=52)</th></tr></thead><tbody><tr><td>Education<br>(y)</td><td>0.34<br>(n=29)</td><td>0.45**<br>(n=42)</td><td>0.57**<br>(n=24)</td><td>0.52***<br>(n=102)</td><td>0.52*<br>(n=19)</td><td>0.50***<br>(n=187)</td><td>0.53**<br>(n=30)</td><td>0.31<br>(n=12)</td><td>0.47**<br>(n=42)</td></tr><tr><td>Age (y)</td><td>-0.04<br>(n=43)</td><td>-0.29*<br>(n=66)</td><td>-0.17<br>(n=28)</td><td>-0.12<br>(n=158)</td><td>0.32<br>(n=24)</td><td>-0.11<br>(n=276)</td><td>-0.15<br>(n=35)</td><td>-0.10<br>(n=17)</td><td>-0.16<br>(n=52)</td></tr><tr><td>Disease<br>duration (y)</td><td></td><td>-0.07<br>(n=36)</td><td>-0.38<br>(n=18)</td><td>-0.18<br>(n=108)</td><td>-0.58*<br>(n=15)</td><td>-0.20**<br>(n=177)</td><td>-0.34<br>(n=16)</td><td>-0.33<br>(n=17)</td><td>-0.24<br>(n=33)</td></tr><tr><td>Estimated<br>time to onset<br>(y)</td><td></td><td>-0.31*<br>(n=64)</td><td>-0.67***<br>(n=27)</td><td>-0.36***<br>(n=154)</td><td>-0.49*<br>(n=24)</td><td>-0.37***<br>(n=269)</td><td></td><td></td><td></td></tr><tr><td>Disability<br>stage</td><td>-0.01<br>(n=43)</td><td>-0.30*<br>(n=66)</td><td>-0.66***<br>(n=26)</td><td>-0.54***<br>(n=158)</td><td>-0.68***<br>(n=23)</td><td>-0.51***<br>(n=273)</td><td>-0.31<br>(n=34)</td><td>-0.48*<br>(n=17)</td><td>-0.32*<br>(n=51)</td></tr><tr><td>SARA</td><td>-0.21<br>(n=43)</td><td>-0.43**<br>(n=66)</td><td>-0.69***<br>(n=28)</td><td>-0.54***<br>(n=157)</td><td>-0.66***<br>(n=24)</td><td>-0.54***<br>(n=275)</td><td>-0.26<br>(n=32)</td><td>-0.45<br>(n=17)</td><td>-0.26<br>(n=49)</td></tr><tr><td>CCFS</td><td>-0.09<br>(n=39)</td><td>-0.17<br>(n=44)</td><td>-0.70**<br>(n=15)</td><td>-0.50***<br>(n=109)</td><td>-0.82***<br>(n=14)</td><td>-0.45***<br>(n=182)</td><td></td><td></td><td></td></tr><tr><td>NfL (pg/ml)</td><td>-0.01<br>(n=38)</td><td>-0.22<br>(n=54)</td><td>-0.04<br>(n=26)</td><td>-0.32***<br>(n=122)</td><td>-0.53**<br>(n=24)</td><td>-0.26***<br>(n=226)</td><td>-0.15<br>(n=17)</td><td>-0.61*<br>(n=13)</td><td>-0.43*<br>(n=30)</td></tr><tr><td>Cerebellum<br>volume</td><td></td><td>-0.16<br>(n=25)</td><td>0.64*<br>(n=15)</td><td>0.08<br>(n=65)</td><td>0.23<br>(n=15)</td><td>0.17<br>(n=120)</td><td></td><td></td><td></td></tr></tbody></table>

Pearson correlation coefficient were computed. Age at examination and Education level are expressed in years (y), NfL concentrations in pg/mL.

*p<0.05; **p<0.01; ***p<0.001

Abbreviations: CCAS: Cerebellar Cognitive Affective Syndrome; CCFS: Composite Cerebellar Functional Severity score; NfL: Neurofilament Light chain; SARA: Scale for the Assessment and Rating of Ataxia; y: years.
<table><caption>Table 3. CCAS comparisons for each subgroup, adjusted for SARA, education, and age.</caption><thead><tr><th>Variable</th><th>SCA1</th><th>SCA2</th><th>SCA3</th><th>SCA7</th><th>SPG7</th></tr></thead><tbody><tr><td>CCAS total</td><td>89.9 [86.6-93.2]</td><td>90.0 [85.6-94.4]</td><td>93.8 [91.6-95.9]</td><td>93.5 [88.5-98.5]</td><td>89.9 [85.3-94.4]</td></tr><tr><td>Semantic fluency</td><td>18.2 [16.9-19.5]</td><td>19.1 [17.3-20.8]</td><td>19.8 [18.9-20.7]</td><td>18.6 [16.7-20.6]</td><td>19.6 [17.8-21.4]</td></tr><tr><td>Phonemic fluency</td><td>10.8 [9.6-12]</td><td>10.1 [8.5-11.8]</td><td>11.5 [10.7-12.3]</td><td>12.2 [10.4-14]</td><td>10.8 [9.1-12.4]</td></tr><tr><td>Categoric switching</td><td>10.9 [10-11.9]</td><td>11.2 [9.9-12.4]</td><td>11.4 [10.7-12]</td><td>12 [10.5-13.4]</td><td>11.4 [10.1-12.7]</td></tr><tr><td>Digit span forward</td><td>5.9 [5.6-6.2]</td><td>6.1 [5.6-6.5]</td><td>6.3 [6.1-6.5]<sup>e</sup></td><td>6.0 [5.5-6.5]</td><td>5.5 [5-5.9]<sup>e</sup></td></tr><tr><td>Digit span backward</td><td>4.0 [3.7-4.3]</td><td>3.9 [3.4-4.3]</td><td>4.1 [3.8-4.3]</td><td>4.1 [3.7-4.6]</td><td>4.1 [3.6-4.5]</td></tr><tr><td>Cube</td><td>13.4 [12.7-14.1]</td><td>14 [13.1-14.9]</td><td>13.8 [13.4-14.3]</td><td>13.7 [12.6-14.7]</td><td>13.4 [12.5-14.4]</td></tr><tr><td>Verbal recall</td><td>12.7 [11.9-13.6]</td><td>11.7 [10.6-12.8]</td><td>12.4 [11.9-12.9]</td><td>11.9 [10.6-13.1]</td><td>11.7 [10.5-12.8]</td></tr><tr><td>Similarities</td><td>7.4 [7.1-7.6]</td><td>7.5 [7.1-7.8]</td><td>7.5 [7.3-7.6]</td><td>7.7 [7.3-8.1]<sup>e</sup></td><td>6.8 [6.4-7.2]<sup>d</sup></td></tr><tr><td>Go/no-go</td><td>1.2 [1-1.4]</td><td>1.4 [1.1-1.6]</td><td>1.5 [1.4-1.7]<sup>e</sup></td><td>1.7 [1.4-2]<sup>e</sup></td><td>1.0 [0.7-1.3]<sup>c,d</sup></td></tr><tr><td>Affect</td><td>5.7 [5.5-5.9]<sup>b</sup></td><td>5.1 [4.8-5.4]<sup>a,c,e</sup></td><td>5.7 [5.5-5.8]<sup>b</sup></td><td>5.5 [5.2-5.9]</td><td>5.9 [5.6-6.2]<sup>b</sup></td></tr></tbody></table>

Abbreviations: CCAS: Cerebellar Cognitive Affective Syndrome. Each value is the estimated marginal mean [95% CI] for the item considered and for each genotype in the adjusted model, i.e. the mean value if all covariables are set at the mean of the population. Significant differences in the pairwise comparisons are shown as <sup>a,b,c,d,e,f</sup> for SCA1, SCA2, SCA3, SCA7, SPG7, and SCA27B respectively