Developing a Neuroimaging Biomarker for Amyotrophic Lateral Sclerosis: Multi-Center Data Sharing and the Road to a "Global Cohort"

Pathological insights derived from neuroimaging in amyotrophic lateral sclerosis: emerging clinical applications

PURPOSE OF REVIEW

Neuroimaging has been instrumental in shaping current understanding of the pathoanatomical signature of amyotrophic lateral sclerosis (ALS) across clinically well defined patient cohorts. The potential utility of imaging as an objective disease marker, however, remains poorly defined.

RECENT FINDINGS

Increasingly advanced quantitative and computational imaging studies have highlighted emerging clinical applications for neuroimaging as a complementary clinical modality for diagnosis, monitoring, and modelling disease propagation. Multimodal neuroimaging has demonstrated novel approaches for capturing primary motor disease. Extra-motor subcortical dysfunction is increasingly recognized as key modulators of disease propagation.

SUMMARY

The neural signature of cortical and subcortical dysfunction in ALS has been well defined at the population level. Objective metrics of focal primary motor dysfunction are increasingly sensitive and translatable to the individual patient level. Integrity of extra-motor subcortical abnormalities are recognized to represent critical pathways of the ALS disease 'connectome', predicting pathological spread. Neuroimaging plays a pivotal role in capturing upper motor neuron pathology in ALS. Their potential clinical role as objective disease markers for disease classification, longitudinal monitoring, and prognosis in ALS have become increasingly well defined.

Novel approaches to assessing upper motor neuron dysfunction in motor neuron disease/amyotrophic lateral sclerosis: IFCN handbook chapter

Identifying upper motor neuron (UMN) dysfunction is fundamental to the diagnosis and understanding of disease pathogenesis in motor neuron disease (MND). The clinical assessment of UMN dysfunction may be difficult, particularly in the setting of severe muscle weakness. From a physiological perspective, transcranial magnetic stimulation (TMS) techniques provide objective biomarkers of UMN dysfunction in MND and may also be useful to interrogate cortical and network function. Single, paired- and triple pulse TMS techniques have yielded novel diagnostic and prognostic biomarkers in MND, and have provided important pathogenic insights, particularly pertaining to site of disease onset. Cortical hyperexcitability, as heralded by reduced short interval intracortical inhibition (SICI) and increased short interval intracortical facilitation, has been associated with the onset of lower motor neuron degeneration, along with patterns of disease spread, development of specific clinical features such as the split hand phenomenon, and may provide an indication about the rate of disease progression. Additionally, reduction of SICI has emerged as a potential diagnostic aid in MND. The triple stimulation technique (TST) was shown to enhance the diagnostic utility of conventional TMS measures in detecting UMN dysfunction in MND. Separately, sophisticated brain imaging techniques have uncovered novel biomarkers of neurodegeneration that have bene associated with progression. The present review will discuss the utility of TMS and brain neuroimaging derived biomarkers of UMN dysfunction in MND, focusing on recently developed TMS techniques and advanced neuroimaging modalities that interrogate structural and functional integrity of the corticomotoneuronal system, with an emphasis on pathogenic, diagnostic, and prognostic utility.

Diffusion Tensor Imaging in Amyotrophic Lateral Sclerosis: Machine Learning for Biomarker Development

Diffusion tensor imaging (DTI) allows the in vivo imaging of pathological white matter alterations, either with unbiased voxel-wise or hypothesis-guided tract-based analysis. Alterations of diffusion metrics are indicative of the cerebral status of patients with amyotrophic lateral sclerosis (ALS) at the individual level. Using machine learning (ML) models to analyze complex and high-dimensional neuroimaging data sets, new opportunities for DTI-based biomarkers in ALS arise. This review aims to summarize how different ML models based on DTI parameters can be used for supervised diagnostic classifications and to provide individualized patient stratification with unsupervised approaches in ALS. To capture the whole spectrum of neuropathological signatures, DTI might be combined with additional modalities, such as structural T1w 3-D MRI in ML models. To further improve the power of ML in ALS and enable the application of deep learning models, standardized DTI protocols and multi-center collaborations are needed to validate multimodal DTI biomarkers. The application of ML models to multiparametric MRI/multimodal DTI-based data sets will enable a detailed assessment of neuropathological signatures in patients with ALS and the development of novel neuroimaging biomarkers that could be used in the clinical workup.

Cortical and subcortical grey matter atrophy in Amyotrophic Lateral Sclerosis correlates with measures of disease accumulation independent of disease aggressiveness

There is a growing demand for reliable biomarkers to monitor disease progression in Amyotrophic Lateral Sclerosis (ALS) that also take the heterogeneity of ALS into account. In this study, we explored the association between Magnetic Resonance Imaging (MRI)-derived measures of cortical thickness (CT) and subcortical grey matter (GM) volume with D50 model parameters. T1-weighted MRI images of 72 Healthy Controls (HC) and 100 patients with ALS were analyzed using Surface-based Morphometry for cortical structures and Voxel-based Morphometry for subcortical Region-Of-Interest analyses using the Computational Anatomy Toolbox (CAT12). In Inter-group contrasts, these parameters were compared between patients and HC. Further, the D50 model was used to conduct subgroup-analyses, dividing patients by a) Phase of disease covered at the time of MRI-scan and b) individual overall disease aggressiveness. Finally, correlations between GM and D50 model-derived parameters were examined. Inter-group analyses revealed ALS-related cortical thinning compared to HC located mainly in frontotemporal regions and a decrease in GM volume in the left hippocampus and amygdala. A comparison of patients in different phases showed further cortical and subcortical GM atrophy along with disease progression. Correspondingly, regression analyses identified negative correlations between cortical thickness and individual disease covered. However, there were no differences in CT and subcortical GM between patients with low and high disease aggressiveness. By application of the D50 model, we identified correlations between cortical and subcortical GM atrophy and ALS-related functional disability, but not with disease aggressiveness. This qualifies CT and subcortical GM volume as biomarkers representing individual disease covered to monitor therapeutic interventions in ALS.

Brain activity is contingent on neuropsychological function in a functional magnetic resonance imaging study of verbal working memory in amyotrophic lateral sclerosis

BACKGROUND AND PURPOSE

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease that causes progressive degeneration of neurons in motor and non-motor brain regions, affecting multiple cognitive domains such as memory. A functional magnetic resonance imaging (fMRI) study was performed to explore working memory function in ALS.

METHODS

To contribute to the growing research field that employs structural and functional neuroimaging to investigate the effect of ALS on different working memory components, the localization and intensity of alterations in neural activity was explored using fMRI. Being the first study to specifically address verbal working memory via fMRI in the context of ALS, the verbal n-back task with 0-back and 2-back conditions was employed.

RESULTS

Despite ALS patients showing unimpaired accuracies (p = 0.724) and reaction times (p = 0.0785), there was significantly increased brain activity of frontotemporal and parietal regions in the 2-back minus 0-back contrast in patients compared to controls (using nonparametric statistics with 5000 permutations and a T threshold of 2.5).

DISCUSSION

Increased brain activity of the frontotemporal and parietal regions during working memory performance was largely associated with better neuropsychological function within the ALS group, suggesting a compensatory effect during working memory execution. This study therefore adds to the current knowledge on neural correlates of working memory in ALS and contributes to a more nuanced understanding of hyperactivity during cognitive processes in fMRI studies of ALS.

Disease aggressiveness signatures of amyotrophic lateral sclerosis in white matter tracts revealed by the D50 disease progression model

Numerous neuroimaging studies in amyotrophic lateral sclerosis (ALS) have reported links between structural changes and clinical data; however phenotypic and disease course heterogeneity have occluded robust associations. The present study used the novel D50 model, which distinguishes between disease accumulation and aggressiveness, to probe correlations with measures of diffusion tensor imaging (DTI). DTI scans of 145 ALS patients and 69 controls were analyzed using tract‐based‐spatial‐statistics of fractional anisotropy (FA), mean‐ (MD), radial (RD), and axial diffusivity (AD) maps. Intergroup contrasts were calculated between patients and controls, and between ALS subgroups: based on (a) the individual disease covered (Phase I vs. II) or b) patients' disease aggressiveness (D50 value). Regression analyses were used to probe correlations with model‐derived parameters. Case–control comparisons revealed widespread ALS‐related white matter pathology with decreased FA and increased MD/RD. These affected pathways showed also correlations with the accumulated disease for increased MD/RD, driven by the subgroup of Phase I patients. No significant differences were noted between patients in Phase I and II for any of the contrasts. Patients with high disease aggressiveness (D50 < 30 months) displayed increased AD/MD in bifrontal and biparietal pathways, which was corroborated by significant voxel‐wise regressions with D50. Application of the D50 model revealed associations between DTI measures and ALS pathology in Phase I, representing individual disease accumulation early in disease. Patients' overall disease aggressiveness correlated robustly with the extent of DTI changes. We recommend the D50 model for studies developing/validating neuroimaging or other biomarkers for ALS.

Applying the D50 disease progression model to gray and white matter pathology in amyotrophic lateral sclerosis

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The D50 disease progression model well characterized a cross-sectional ALS cohort.

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VBM reveled ALS-related widespread gray and white matter density decreases.

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A spread of structural alterations occurs along with D50 model derived disease phases.

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White-matter alterations were associated with higher disease aggressiveness.

Therapeutic management and research in Amyotrophic Laterals Sclerosis (ALS) have been limited by the substantial heterogeneity in progression and anatomical spread that are endemic of the disease. Neuroimaging biomarkers represent powerful additions to the current monitoring repertoire but have yielded inconsistent associations with clinical scores like the ALS functional rating scale. The D50 disease progression model was developed to address limitations with clinical indices and the difficulty obtaining longitudinal data in ALS. It yields overall disease aggressiveness as time taken to reach halved functionality (D50); individual disease covered in distinct phases; and calculated functional state and calculated functional loss as acute descriptors of local disease activity. It greatly reduces the noise of the ALS functional rating scale and allows the comparison of highly heterogeneous disease and progression subtypes. In this study, we performed Voxel-Based Morphometry for 85 patients with ALS (60.1 ± 11.5 years, 36 female) and 62 healthy controls. Group-wise comparisons were performed separately for gray matter and white matter using ANCOVA testing with threshold-free cluster enhancement. ALS-related widespread gray and white matter density decreases were observed in the bilateral frontal and temporal lobes (p < 0.001, family-wise error corrected). We observed a progressive spread of structural alterations along the D50-derived phases, that were primarily located in frontal, temporal and occipital gray matter areas, as well as in supratentorial neuronal projections (p < 0.001 family-wise error corrected). ALS patients with higher overall disease aggressiveness (D50 < 30 months) showed a distinct pattern of supratentorial white matter density decreases relative to patients with lower aggressiveness; no significant differences were observed for gray matter density (p < 0.001 family-wise error corrected).

The application of the D50 disease progression model separates measures of disease aggressiveness from disease accumulation. It revealed a strong correlation between disease phases and in-vivo measures of cerebral structural integrity. This study underscores the proposed corticofugal spread of cerebral pathology in ALS. We recommend application of the D50 model in studies linking clinical data with neuroimaging correlates.

Are Circulating Cytokines Reliable Biomarkers for Amyotrophic Lateral Sclerosis?

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that has no effective treatment. The lack of any specific biomarker that can help in the diagnosis or prognosis of ALS has made the identification of biomarkers an urgent challenge. Multiple panels have shown alterations in levels of numerous cytokines in ALS, supporting the contribution of neuroinflammation to the progressive motor neuron loss. However, none of them is fully sensitive and specific enough to become a universal biomarker for ALS. This review gathers the numerous circulating cytokines that have been found dysregulated in both ALS animal models and patients. Particularly, it highlights the opposing results found in the literature to date, and points out another potential application of inflammatory cytokines as therapeutic targets.