Clinical Profiles and Patterns of Neurodegeneration in Amyotrophic Lateral Sclerosis: A Cluster-Based Approach Based on MR Imaging Metrics

From use of omics to systems biology: Identifying therapeutic targets for amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a heterogeneous progressive neurodegenerative disorder with available treatments such as riluzole and edaravone extending survival by an average of 3-6 months. The lack of highly effective, widely available therapies reflects the complexity of ALS. Omics technologies, including genomics, transcriptomic and proteomics have contributed to the identification of biological pathways dysregulated and targeted by therapeutic strategies in preclinical and clinical trials. Integrating clinical, environmental and neuroimaging information with omics data and applying a systems biology approach can further improve our understanding of the disease with the potential to stratify patients and provide more personalised medicine. This chapter will review the omics technologies that contribute to a systems biology approach and how these components have assisted in identifying therapeutic targets. Current strategies, including the use of genetic screening and biosampling in clinical trials, as well as the future application of additional technological advances, will also be discussed.

Differential cortical gray matter changes in early- and late-onset patients with amyotrophic lateral sclerosis

Age at onset may be an important feature associated with distinct subtypes of amyotrophic lateral sclerosis (ALS). Little is known about the neuropathological mechanism of early-onset ALS (EO-ALS) and late-onset ALS (LO-ALS). Ninety ALS patients were divided into EO-ALS and LO-ALS group, and 128 healthy controls were matched into young controls(YCs) and old controls (OCs). A voxel-based morphometry approach was employed to investigate differences in gray matter volume (GMV). Significant age at onset-by-diagnosis interactions were found in the left parietal operculum, left precentral gyrus, bilateral postcentral gyrus, right occipital gyrus, and right orbitofrontal cortex. Post hoc analysis revealed a significant decrease in GMV in all affected regions of EO-ALS patients compared with YCs, with increased GMV in 5 of the 6 brain regions, except for the right orbitofrontal cortex, in LO-ALS patients compared with OCs. LO-ALS patients had a significantly increased GMV than EO-ALS patients after removing the aging effect. Correspondingly, GMV of the left postcentral gyrus correlated with disease severity in the 2 ALS groups. Our findings suggested that the pathological mechanisms in ALS patients with different ages at onset might differ. These findings provide unique insight into the clinical and biological heterogeneity of the 2 ALS subtypes.

The impact of upper and lower motor neuron burden on diagnostic certainty, and clinical course of spinal-onset amyotrophic lateral sclerosis: a cluster-based approach

BACKGROUND

Upper motor neuron (UMN) and lower motor neuron (LMN) involvement represent the core clinical features of amyotrophic lateral sclerosis (ALS). Several studies divided patients into prevalent UMN and LMN impairment phenotypes to investigate the association between motor systems impairments and ALS clinical course. However, this distinction was somehow heterogeneous and significantly affected the comparability across studies.

AIMS

This study aimed to investigate whether patients spontaneously segregate based on the extent of UMN and LMN involvement without a-priori categorization and to identify potential clinical and prognostic features of different clusters.

METHODS

Eighty-eight consecutive spinal-onset ALS patients were referred to an ALS tertiary center between 2015 and 2022. UMN and LMN burden was assessed with the Penn Upper Motor Neuron scale (PUMNS) and the Devine score, respectively. PUMNS and LMN scores were normalized into 0-1 and analyzed using a two-step cluster analysis and the Euclidean distance measure. The Bayesian Information Criterion was used to determine the cluster number. Demographic and clinical variables were tested for differences among the clusters.

RESULTS

Three distinct clusters emerged at cluster analysis. Patients in "cluster-1" showed moderate UMN and severe LMN involvement, corresponding to the typical ALS phenotype. Patients in "cluster-2" showed mild LMN and severe UMN damage, corresponding to a predominant UMN phenotype, while "cluster-3" patients showed mild UMN and moderate LMN damage, corresponding to a predominant LMN phenotype. Patients in "cluster-1" and "cluster-2" showed a higher prevalence of definite ALS than those in "cluster-3" (61% and 46 vs 9%, p < 0.001). "Cluster-1" patients had a lower median ALSFRS-r score compared to both "cluster-2" and 3 patients (27 vs 40 and 35, < 0.001). "Cluster-1" (HR: 8.5; 95% CI 2.1-35.1 and p = 0.003) and 3 (HR: 3.2; 95% CI 1.1-9.1; p = 0.03) were associated with shorter survival than those in "cluster-2".

CONCLUSIONS

Spinal-onset ALS can be categorized into three groups according to LMN and UMN burden. The UMN burden is related to higher diagnostic certainty and broader disease spread, while LMN involvement is associated with higher disease severity and shorter survival.