New Model for Estimation of the Age at Onset in Spinocerebellar Ataxia Type 3

Sensitivity of Advanced Magnetic Resonance Imaging to Progression over Six Months in Early Spinocerebellar Ataxia

BACKGROUND

Clinical trials for upcoming disease-modifying therapies of spinocerebellar ataxias (SCA), a group of rare movement disorders, lack endpoints sensitive to early disease progression, when therapeutics will be most effective. In addition, regulatory agencies emphasize the importance of biological outcomes.

OBJECTIVES

READISCA, a transatlantic clinical trial readiness consortium, investigated whether advanced multimodal magnetic resonance imaging (MRI) detects pathology progression over 6 months in preataxic and early ataxic carriers of SCA mutations.

METHODS

A total of 44 participants (10 SCA1, 25 SCA3, and 9 controls) prospectively underwent 3-T MR scanning at baseline and a median [interquartile range] follow-up of 6.2 [5.9-6.7] months; 44% of SCA participants were preataxic. Blinded analyses of annual changes in structural, diffusion MRI, MR spectroscopy, and the Scale for Assessment and Rating of Ataxia (SARA) were compared between groups using nonparametric testing. Sample sizes were estimated for 6-month interventional trials with 50% to 100% treatment effect size, leveraging existing large cohort data (186 SCA1, 272 SCA3) for the SARA estimate.

RESULTS

Rate of change in microstructural integrity (decrease in fractional anisotropy, increase in diffusivities) in the middle cerebellar peduncle, corona radiata, and superior longitudinal fasciculus significantly differed in SCAs from controls (P < 0.005), with high effect sizes (Cohen's d = 1-2) and moderate-to-high responsiveness (|standardized response mean| = 0.6-0.9) in SCAs. SARA scores did not change, and their rate of change did not differ between groups.

CONCLUSIONS

Diffusion MRI is sensitive to disease progression at very early-stage SCA1 and SCA3 and may provide a >5-fold reduction in sample sizes relative to SARA as endpoint for 6-month-long trials. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

SARA captures disparate progression and responsiveness in spinocerebellar ataxias

BACKGROUND

The Scale for Assessment and Rating of Ataxia (SARA) is a widely used clinical scale to assess cerebellar ataxia but faces some criticisms about the relevancy of all its items.

OBJECTIVES

To prepare for future clinical trials, we analyzed the progression of SARA and its items in several polyQ spinocerebellar ataxias (SCA) from various cohorts.

METHODS

We included data from patients with SCA1, SCA2, SCA3, and SCA6 from four cohorts (EUROSCA, RISCA, CRC-SCA, and SPATAX) for a total of 850 carriers and 3431 observations. Longitudinal progression of the SARA and its items was measured. Cohort, stage and genetic effects were tested. We looked at the respective contribution of each item to the total scale. Sensitivity to change of the scale and the impact of item removal was evaluated by calculating sample sizes needed in various scenarios.

RESULTS

Longitudinal progression was significantly different between cohorts in SCA1, SCA2 and SCA3, the EUROSCA cohort having the fastest progression. Advanced-stage patients were progressing slower in SCA2 and SCA6. Items were not contributing equally to the full scale through ataxia severity: gait, stance, hand movement, and heel-shin contributed the most in the early stage, and finger-chase, nose-finger, and sitting in later stages. Few items drove the sensitivity to the change of SARA, but changes in the scale structure could not improve its sensitivity in all populations.

CONCLUSION

SARA and its item's progression pace showed high heterogeneity across cohorts and SCAs. However, no combinations of items improved the responsiveness in all SCAs or populations taken separately.

Genotype-specific spinal cord damage in spinocerebellar ataxias: an ENIGMA-Ataxia study

BACKGROUND

Spinal cord damage is a feature of many spinocerebellar ataxias (SCAs), but well-powered in vivo studies are lacking and links with disease severity and progression remain unclear. Here we characterise cervical spinal cord morphometric abnormalities in SCA1, SCA2, SCA3 and SCA6 using a large multisite MRI dataset.

METHODS

Upper spinal cord (vertebrae C1-C4) cross-sectional area (CSA) and eccentricity (flattening) were assessed using MRI data from nine sites within the ENIGMA-Ataxia consortium, including 364 people with ataxic SCA, 56 individuals with preataxic SCA and 394 nonataxic controls. Correlations and subgroup analyses within the SCA cohorts were undertaken based on disease duration and ataxia severity.

RESULTS

Individuals in the ataxic stage of SCA1, SCA2 and SCA3, relative to non-ataxic controls, had significantly reduced CSA and increased eccentricity at all examined levels. CSA showed large effect sizes (d>2.0) and correlated with ataxia severity (r<-0.43) and disease duration (r<-0.21). Eccentricity correlated only with ataxia severity in SCA2 (r=0.28). No significant spinal cord differences were evident in SCA6. In preataxic individuals, CSA was significantly reduced in SCA2 (d=1.6) and SCA3 (d=1.7), and the SCA2 group also showed increased eccentricity (d=1.1) relative to nonataxic controls. Subgroup analyses confirmed that CSA and eccentricity are abnormal in early disease stages in SCA1, SCA2 and SCA3. CSA declined with disease progression in all, whereas eccentricity progressed only in SCA2.

CONCLUSIONS

Spinal cord abnormalities are an early and progressive feature of SCA1, SCA2 and SCA3, but not SCA6, which can be captured using quantitative MRI.

Reconsidering N component of cancer staging for T1-2N0-2M0 small-cell lung cancer: a retrospective study based on multicenter cohort

BACKGROUND

The current nodal (pN) classification still has limitations in stratifying the prognosis of small cell lung cancer (SCLC) patients with pathological classifications T1-2N0-2M0. Thus. This study aimed to develop and validate a modified nodal classification based on a multicenter cohort.

MATERIALS AND METHODS

We collected 1156 SCLC patients with pathological classifications T1-2N0-2M0 from the Surveillance, Epidemiology, and End Results database and a multicenter database in China. The X-tile software was conducted to determine the optimal cutoff points of the number of examined lymph nodes (ELNs) and lymph node ratio (LNR). The Kaplan-Meier method, the Log-rank test, and the Cox regression method were used in this study. We classified patients into three pathological N modification categories, new pN#1 (pN0-#ELNs > 3), new pN#2 (pN0-#ELNs ≤ 3 or pN1-2-#LNR ≤ 0.14), and new pN#3 (N1-2-#LNR > 0.14). The Akaike information criterion (AIC), Bayesian Information Criterion, and Concordance index (C-index) were used to compare the prognostic, predictive ability between the current pN classification and the new pN component.

RESULTS

The new pN classification had a satisfactory effect on survival curves (Log-rank P < 0.001). After adjusting for other confounders, the new pN classification could be an independent prognostic indicator. Besides, the new pN component had a much more accurate predictive ability in the prognostic assessment for SCLC patients of pathological classifications T1-2N0-2M0 compared with the current pN classification in the SEER database (AIC: 4705.544 vs. 4731.775; C-index: 0.654 vs. 0.617, P < 0.001). Those results were validated in the MCDB from China.

CONCLUSIONS

The multicenter cohort developed and validated a modified nodal classification for SCLC patients with pathological category T1-2N0-2M0 after surgery. Besides, we propose that an adequate lymph node dissection is essential; surgeons should perform and consider the situation of ELNs and LNR when they evaluate postoperative prognoses of SCLC patients.

Machine Learning Approach for the Prediction of Age-Specific Probability of SCA3 and DRPLA by Survival Curve Analysis

Background and Objectives

As the number of repeats in the expansion increases, polyglutamine diseases tend to show at a younger age. From this relationship, attempts have been made to predict age at onset by parametric survival analysis. However, a method for a more accurate prediction has been desirable. In this study, we examined 2 methods for survival analysis using machine learning and 6 conventional methods for parametric survival analysis of spinocerebellar ataxia (SCA)3 and dentatorubral-pallidoluysian atrophy (DRPLA).

Methods

We compared the performance of 2 machine learning methods of survival analysis (random survival forest [RSF] and DeepSurv) and 6 methods of parametric survival analysis (Weibull, exponential, Gaussian, logistic, loglogistic, and log Gaussian). Training and evaluation were performed using the leave-one-out cross-validation method, and evaluation criteria included root mean squared error (RMSE), mean absolute error (MAE), and the integrated Brier score. The latter was used as the primary end point, and the survival analysis model yielding the best result was used to predict the asymptomatic probability.

Results

Among the models examined, the RSF and DeepSurv machine learning methods had a higher prediction accuracy than the parametric methods of survival analysis. For both SCA3 and DRPLA, RSF had a higher accuracy than DeepSurv for the assessment of RMSE (SCA3: 7.37, DRPLA: 10.78), MAE (SCA3: 5.52, DRPLA: 8.17), and the integrated Brier score (SCA3: 0.05, DRPLA: 0.077). Using RSF, we determined the age-specific probability distribution of age at onset based on CAG repeat size and current age.

Discussion

In this study, we have demonstrated the superiority of machine learning methods for predicting age at onset of SCA3 and DRPLA using survival analysis. Such accurate prediction of onset will be useful for genetic counseling of carriers and for devising methods to verify the effects of interventions for unaffected individuals.

Baseline Clinical and Blood Biomarkers in Patients With Preataxic and Early-Stage Disease Spinocerebellar Ataxia 1 and 3

BACKGROUND AND OBJECTIVES

In spinocerebellar ataxia, ataxia onset can be preceded by mild clinical manifestation, cerebellar and/or brainstem alterations, or biomarker modifications. READISCA is a prospective, longitudinal observational study of patients with spinocerebellar ataxia type 1 (SCA1) and 3 (SCA3) to provide essential markers for therapeutic interventions. We looked for clinical, imaging, or biological markers that are present at an early stage of the disease.

METHODS

We enrolled carriers of a pathologic ATXN1 or ATXN3 expansion and controls from 18 US and 2 European ataxia referral centers. Clinical, cognitive, quantitative motor, neuropsychological measures and plasma neurofilament light chain (NfL) measurements were compared between expansion carriers with and without ataxia and controls.

RESULTS

We enrolled 200 participants: 45 carriers of a pathologic ATXN1 expansion (31 patients with ataxia [median Scale for the Assessment and Rating of Ataxia: 9; 7-10] and 14 expansion carriers without ataxia [1; 0-2]) and 116 carriers of a pathologic ATXN3 expansion (80 patients with ataxia [7; 6-9] and 36 expansion carriers without ataxia [1; 0-2]). In addition, we enrolled 39 controls who did not carry a pathologic expansion in ATXN1 or ATXN3. Plasma NfL levels were significantly higher in expansion carriers without ataxia than controls, despite similar mean age (controls: 5.7 pg/mL, SCA1: 18.0 pg/mL [p < 0.0001], SCA3: 19.8 pg/mL [p < 0.0001]). Expansion carriers without ataxia differed from controls by significantly more upper motor signs (SCA1 p = 0.0003, SCA3 p = 0.003) and by the presence of sensor impairment and diplopia in SCA3 (p = 0.0448 and 0.0445, respectively). Functional scales, fatigue and depression scores, swallowing difficulties, and cognitive impairment were worse in expansion carriers with ataxia than those without ataxia. Ataxic SCA3 participants showed extrapyramidal signs, urinary dysfunction, and lower motor neuron signs significantly more often than expansion carriers without ataxia.

DISCUSSION

READISCA showed the feasibility of harmonized data acquisition in a multinational network. NfL alterations, early sensory ataxia, and corticospinal signs were quantifiable between preataxic participants and controls. Patients with ataxia differed in many parameters from controls and expansion carriers without ataxia, with a graded increase of abnormal measures from control to preataxic to ataxic cohorts.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov NCT03487367.

Clinically Meaningful Magnetic Resonance Endpoints Sensitive to Preataxic Spinocerebellar Ataxia Types 1 and 3

OBJECTIVE

This study was undertaken to identify magnetic resonance (MR) metrics that are most sensitive to early changes in the brain in spinocerebellar ataxia type 1 (SCA1) and type 3 (SCA3) using an advanced multimodal MR imaging (MRI) protocol in the multisite trial setting.

METHODS

SCA1 or SCA3 mutation carriers and controls (n = 107) underwent MR scanning in the US-European READISCA study to obtain structural, diffusion MRI, and MR spectroscopy data using an advanced protocol at 3T. Morphometric, microstructural, and neurochemical metrics were analyzed blinded to diagnosis and compared between preataxic SCA (n = 11 SCA1, n = 28 SCA3), ataxic SCA (n = 14 SCA1, n = 37 SCA3), and control (n = 17) groups using nonparametric testing accounting for multiple comparisons. MR metrics that were most sensitive to preataxic abnormalities were identified using receiver operating characteristic (ROC) analyses.

RESULTS

Atrophy and microstructural damage in the brainstem and cerebellar peduncles and neurochemical abnormalities in the pons were prominent in both preataxic groups, when patients did not differ from controls clinically. MR metrics were strongly associated with ataxia symptoms, activities of daily living, and estimated ataxia duration. A neurochemical measure was the most sensitive metric to preataxic changes in SCA1 (ROC area under the curve [AUC] = 0.95), and a microstructural metric was the most sensitive metric to preataxic changes in SCA3 (AUC = 0.92).

INTERPRETATION

Changes in cerebellar afferent and efferent pathways underlie the earliest symptoms of both SCAs. MR metrics collected with a harmonized advanced protocol in the multisite trial setting allow detection of disease effects in individuals before ataxia onset with potential clinical trial utility for subject stratification. ANN NEUROL 2023;93:686-701.

Circulating biomarker-based risk stratifications individualize arch repair strategy of acute Type A aortic dissection via the XGBoosting algorithm

Aims

The incremental usefulness of circulating biomarkers from different pathological pathways for predicting mortality has not been evaluated in acute Type A aortic dissection (ATAAD) patients. We aim to develop a risk prediction model and investigate the impact of arch repair strategy on mortality based on distinct risk stratifications.

Methods and results

A total of 3771 ATAAD patients who underwent aortic surgery retrospectively included were randomly divided into training and testing cohorts at a ratio of 7:3 for the development and validation of the risk model based on multiple circulating biomarkers and conventional clinical factors. Extreme gradient boosting was used to generate the risk models. Subgroup analyses were performed by risk stratifications (low vs. middle-high risk) and arch repair strategies (proximal vs. extensive arch repair). Addition of multiple biomarkers to a model with conventional factors fitted an ABC risk model consisting of platelet-leucocyte ratio, mean arterial pressure, albumin, age, creatinine, creatine kinase-MB, haemoglobin, lactate, left ventricular end-diastolic dimension, urea nitrogen, and aspartate aminotransferase, with adequate discrimination ability {area under the receiver operating characteristic curve (AUROC): 0.930 [95% confidence interval (CI) 0.906-0.954] and 0.954, 95% CI (0.930-0.977) in the derivation and validation cohort, respectively}. Compared with proximal arch repair, the extensive repair was associated with similar mortality risk among patients at low risk [odds ratio (OR) 1.838, 95% CI (0.559-6.038); P = 0.316], but associated with higher mortality risk among patients at middle-high risk [OR 2.007, 95% CI (1.460-2.757); P < 0.0001].

Conclusion

In ATAAD patients, the simultaneous addition of circulating biomarkers of inflammatory, cardiac, hepatic, renal, and metabolic abnormalities substantially improved risk stratification and individualized arch repair strategy.

Explainable artificial intelligence based on feature optimization for age at onset prediction of spinocerebellar ataxia type 3

Existing treatments can only delay the progression of spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD) after onset, so the prediction of the age at onset (AAO) can facilitate early intervention and follow-up to improve treatment efficacy. The objective of this study was to develop an explainable artificial intelligence (XAI) based on feature optimization to provide an interpretable and more accurate AAO prediction. A total of 1,008 affected SCA3/MJD subjects from mainland China were analyzed. The expanded cytosine-adenine-guanine (CAG) trinucleotide repeats of 10 polyQ-related genes were genotyped and included in related models as potential AAO modifiers. The performance of 4 feature optimization methods and 10 machine learning (ML) algorithms were compared, followed by building the XAI based on the SHapley Additive exPlanations (SHAP). The model constructed with an artificial neural network (ANN) and feature optimization of Crossing-Correlation-StepSVM performed best and achieved a coefficient of determination (R2) of 0.653 and mean absolute error (MAE), root mean square error (RMSE), and median absolute error (MedianAE) of 4.544, 6.090, and 3.236 years, respectively. The XAI explained the predicted results, which suggests that the factors affecting the AAO were complex and associated with gene interactions. An XAI based on feature optimization can improve the accuracy of AAO prediction and provide interpretable and personalized prediction.