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@ARTICLE{Petit:285923,
author = {Petit, Emilien and Coarelli, Giulia and Morgan, David and
Cunha, Paulina and Hurmic, Hortense and Faber, Jennifer and
Grobe-Einsler, Marcus and Rezende, Thiago and Kuo, Sheng-Han
and Wilmot, George R and Rosenthal, Liana S and Schmahmann,
Jeremy D and Yacoubian, Talene A and Perlman, Susan L and
Geschwind, Michael D and Gomez, Christopher M and Hawkins,
Trevor and Subramony, S. H. and Shakkottai, Vikram G and
Bushara, Khalaf O and Zesiewicz, Theresa A and Pulst, Stefan
M and Park, Young Woo and Lenglet, Christophe and
Klockgether, Thomas and Paulson, Henry L and Durr, Alexandra
and Öz, Gülin and Ashizawa, Tetsuo and Tezenas du Montcel,
Sophie},
title = {{P}redictive models for ataxia progression and conversion
in spinocerebellar ataxia type 1 and 3.},
journal = {Brain},
volume = {149},
number = {4},
issn = {0006-8950},
address = {Oxford},
publisher = {Oxford Univ. Press},
reportid = {DZNE-2026-00369},
pages = {1268 - 1277},
year = {2026},
abstract = {The READISCA study aims to prepare for clinical trials in
spinocerebellar ataxia types 1 and 3 (SCA1 and SCA3). Hence,
we searched for predictive variables of ataxia onset
(phenoconversion) and progression. Individuals with SCA1 or
SCA3 and controls were enrolled from 2018 to 2021 in the USA
and Europe. Clinical scores, MRI measures and neurofilament
light chain (NfL) levels were assessed annually for 5 years.
In the pre-ataxic group at baseline, we compared
phenoconverters with non-converters. A Bayesian mixed model
was used to model the longitudinal progression of clinical
scores and NfL levels. The impact of data-driven selected
baseline variables (demographic, clinical and MRI) on the
expected Scale for Assessment and Rating of Ataxia
progression was tested. Forty-three controls, 55 SCA1
carriers and 124 SCA3 carriers were included; a subset of
the cohort (n = 109) had MRI data. Converters from
pre-ataxic to ataxic stages represented 5/22 $(22\%)$ and
12/38 $(32\%)$ for SCA1 and SCA3, respectively. Converters
were more depressed (Patient Health Questionnaire 9: 3.9 ±
2.9 versus 2.3 ± 2.6, P = 0.04), had higher plasma NfL
levels (17.6 ± 5.7 versus 11.1 ± 5.9 pg/ml, P < 0.0001),
more cerebellar white matter atrophy $(1.44\%$ ± $0.12\%$
of total intracranial volume versus $1.54\%$ ± $0.16\%,$ P
= 0.032) and more Inventory of Non-Ataxia Signs signs (1.8
± 1.3 versus 0.7 ± 0.8, P = 0.002). All clinical scores
except Cerebellar Cognitive Affective Syndrome significantly
worsened during the study. NfL levels significantly
increased in non-converters and ataxic SCA3 (1.06 ± 0.33
pg/ml/year, P = 0.002 and 0.57 ± 0.21 pg/ml/year, P = 0.01,
respectively) but not in controls and ataxic SCA1 (0.31 ±
0.26 pg/ml/year, P = 0.24 and 0.26 ± 0.42 pg/ml/year, P =
0.55, respectively). In the best predictive model of Scale
for Assessment and Rating of Ataxia progression after 1 year
(R2 = 0.54), factors linked with faster progression were
higher functional stage (P < 0.001), higher Composite
Cerebellar Functional Score (P = 0.002) and higher total
creatine in cerebellar white matter (P = 0.026). Factors
significantly linked to conversion, namely NfL levels,
depression and lower motor neuron involvement, differ from
those driving disease progression. The NfL levels and lower
motor neuron signs could be used as predictors of
phenoconversion and MRI variables as ataxia progression
predictors. Psychological care should be provided in the
pre-ataxic phase of the disease.},
keywords = {Humans / Male / Disease Progression / Female / Middle Aged
/ Adult / Magnetic Resonance Imaging / Machado-Joseph
Disease: diagnostic imaging / Spinocerebellar Ataxias:
diagnostic imaging / Neurofilament Proteins: blood /
Longitudinal Studies / Aged / biomarkers (Other) / brain MRI
(Other) / clinical scales (Other) / natural history study
(Other) / spinocerebellar ataxia (Other) / Neurofilament
Proteins (NLM Chemicals) / neurofilament protein L (NLM
Chemicals)},
cin = {Clinical Research (Bonn) / Patient Studies (Bonn)},
ddc = {610},
cid = {I:(DE-2719)1011001 / I:(DE-2719)1011101},
pnm = {353 - Clinical and Health Care Research (POF4-353)},
pid = {G:(DE-HGF)POF4-353},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:41150672},
pmc = {pmc:PMC12998449},
doi = {10.1093/brain/awaf408},
url = {https://pub.dzne.de/record/285923},
}