(Dis)entangling ALS

Abstract

The aim of this thesis is to investigate neurodegeneration in amyotrophic lateral sclerosis (ALS) from the presymptomatic phase through symptom onset, disease progression, and ultimately death, employing an integrative approach to enhance both understanding and treatment of the disease. ALS is caused by both genetic and environmental/lifestyle factors. By integratively assessing these factors in a large, population-based ALS case-control study, we identified distinct cross-sectional and longitudinal patterns of lifestyle factors between cases and controls during the presymptomatic phase, with further distinctions observed depending on the C9orf72 genotype. The analysis also provided evidence supporting a potential causal effect of smoking and alcohol consumption on ALS development. To investigate the earliest cerebral changes, we studied asymptomatic C9orf72 mutation carriers using magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging (MRSI). Our findings demonstrated cortical thinning and reduced brain volumes that precede symptom onset. Additionally, metabolic abnormalities, including glutamate dysfunction and alterations in glycogen metabolism, were detected in these carriers, indicating that pathological processes begin well before clinical symptoms appear. The study further explores the propagation of ALS pathology through white matter tracts, emphasizing the selective vulnerability of motor neurons and other brain regions. Brain resilience and susceptibility appear to be linked to its network properties, with ALS progression related to reduced network integration. Using advanced imaging techniques and a Louvain-like algorithm, we identified three distinct ALS subgroups – pure motor, frontotemporal, and a newly identified cingulate, parietal and temporal (CPT) group – each exhibiting unique patterns of brain involvement and associations with clinical characteristics. Genotype and phenotype are associated with the heterogeneity of brain involvement in ALS. Patients with different cognitive and behavioural symptoms display different degrees of grey and white matter degeneration, with the most severe damage occurring within the first 13 months after symptom onset. Using MRSI, we observed alterations in glutamatergic, energy, and phospholipid metabolism in ALS patients without the C9orf72 mutation. These biomarkers could be valuable for future subgroup identification, patient selection in clinical trials, and in vivo target engagement studies. We identified similar patterns of cortical thinning in patients with a C9orf72 mutation and a subgroup of patients without this mutation, which could indicate shared disease mechanisms. Subcortical grey matter is affected in ALS, and hippocampal involvement is detectable early in the disease course. The thesis concludes by addressing disease progression and survival. It introduces the ENCALS survival prediction model, which has undergone extensive external validation and assists clinicians in counselling patients with individualized survival predictions. The model's practical application is demonstrated through its use with a notable ALS patient, Stephen Hawking, highlighting its potential in real-world scenarios. Furthermore, the model improves the design of clinical trials by reducing patient heterogeneity, thereby increasing the likelihood of detecting treatment effects. Ultimately, this research aims to facilitate the development of more effective, personalized treatments for ALS.