My aim is to understand the exact genetic contribution in every patient with Amyotrophic Lateral Sclerosis (ALS), a lethal disease with a life time risk of 0.3% and an urgent unmet therapeutic need. Technological advances have enabled the development of gene-based therapies as soon as causal genetic variants are discovered. Prime example in ALS is the development of gene-based therapies in SOD1 mediated ALS. This treatment illustrates that in principle ALS is a curable disease. I have recently shown a disproportionate large contribution from low-frequency genetic variants in ALS. ALS is not simply a collection of unique rare diseases with a monogenetic cause nor is it a diagnostic continuum with a complex contribution of thousands of small effect factors. ALS is in-between, which I call “simplex”, where in each patient a few, considerably strong genetic factors with or without environmental factors are at play. ALS mutations are characterized by reduced penetrance, variable clinical expressivity, have specific pleiotropic clinical features and interact with environmental factors. These phenomena are unexplained, but provide me with important and new opportunities in order to unravel the clinical, genetic and biological heterogeneity in ALS. I have created new research fields to go an important step beyond the state of the art: Splitting by lumping uses novel machine learning algorithms to reclassify patients using clinical pleiotropic features, environmental factors and blood epigenetic profiles to identify novel ALS mutations. Imaging genomics overlays patterns in ALS-associated brain morphology on MRI with brain gene-expression patterns to find ALS mutations. ALS risk in 3D integrates data on three-dimensional folding of DNA with genetic data to identify causal mutations and mutation-to-mutation interaction.
So the overall objectives are to find novel credible and actionable genetic variants in ALS that are amenable for gene-based therapies.
