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000285923 1001_ $$00009-0000-0602-7122$$aPetit, Emilien$$b0
000285923 245__ $$aPredictive models for ataxia progression and conversion in spinocerebellar ataxia type 1 and 3.
000285923 260__ $$aOxford$$bOxford Univ. Press$$c2026
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000285923 520__ $$aThe 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.
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000285923 650_7 $$2Other$$abiomarkers
000285923 650_7 $$2Other$$abrain MRI
000285923 650_7 $$2Other$$aclinical scales
000285923 650_7 $$2Other$$anatural history study
000285923 650_7 $$2Other$$aspinocerebellar ataxia
000285923 650_7 $$2NLM Chemicals$$aNeurofilament Proteins
000285923 650_7 $$2NLM Chemicals$$aneurofilament protein L
000285923 650_2 $$2MeSH$$aHumans
000285923 650_2 $$2MeSH$$aMale
000285923 650_2 $$2MeSH$$aDisease Progression
000285923 650_2 $$2MeSH$$aFemale
000285923 650_2 $$2MeSH$$aMiddle Aged
000285923 650_2 $$2MeSH$$aAdult
000285923 650_2 $$2MeSH$$aMagnetic Resonance Imaging
000285923 650_2 $$2MeSH$$aMachado-Joseph Disease: diagnostic imaging
000285923 650_2 $$2MeSH$$aSpinocerebellar Ataxias: diagnostic imaging
000285923 650_2 $$2MeSH$$aNeurofilament Proteins: blood
000285923 650_2 $$2MeSH$$aLongitudinal Studies
000285923 650_2 $$2MeSH$$aAged
000285923 7001_ $$aCoarelli, Giulia$$b1
000285923 7001_ $$aMorgan, David$$b2
000285923 7001_ $$aCunha, Paulina$$b3
000285923 7001_ $$aHurmic, Hortense$$b4
000285923 7001_ $$0P:(DE-2719)2811327$$aFaber, Jennifer$$b5
000285923 7001_ $$0P:(DE-2719)9001510$$aGrobe-Einsler, Marcus$$b6$$udzne
000285923 7001_ $$aRezende, Thiago$$b7
000285923 7001_ $$aKuo, Sheng-Han$$b8
000285923 7001_ $$aWilmot, George R$$b9
000285923 7001_ $$aRosenthal, Liana S$$b10
000285923 7001_ $$aSchmahmann, Jeremy D$$b11
000285923 7001_ $$aYacoubian, Talene A$$b12
000285923 7001_ $$aPerlman, Susan L$$b13
000285923 7001_ $$00000-0003-2861-3776$$aGeschwind, Michael D$$b14
000285923 7001_ $$aGomez, Christopher M$$b15
000285923 7001_ $$aHawkins, Trevor$$b16
000285923 7001_ $$aSubramony, S. H.$$b17
000285923 7001_ $$aShakkottai, Vikram G$$b18
000285923 7001_ $$aBushara, Khalaf O$$b19
000285923 7001_ $$aZesiewicz, Theresa A$$b20
000285923 7001_ $$aPulst, Stefan M$$b21
000285923 7001_ $$0P:(DE-HGF)0$$aPark, Young Woo$$b22
000285923 7001_ $$aLenglet, Christophe$$b23
000285923 7001_ $$0P:(DE-2719)2810314$$aKlockgether, Thomas$$b24$$udzne
000285923 7001_ $$aPaulson, Henry L$$b25
000285923 7001_ $$0P:(DE-2719)9000429$$aDurr, Alexandra$$b26
000285923 7001_ $$aÖz, Gülin$$b27
000285923 7001_ $$aAshizawa, Tetsuo$$b28
000285923 7001_ $$00000-0002-2866-4330$$aTezenas du Montcel, Sophie$$b29
000285923 773__ $$0PERI:(DE-600)1474117-9$$a10.1093/brain/awaf408$$gVol. 149, no. 4, p. 1268 - 1277$$n4$$p1268 - 1277$$tBrain$$v149$$x0006-8950$$y2026
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