Morphometric analysis of a large cohort of ALS patient fibroblasts


Translational Research

Poster Number: 42


Csaba Konrad Ph.D


1. Joan & Sanford I. Weill Medical College of Cornell University

Background: Amyotrophic lateral sclerosis (ALS) is the most common adult-onset motor neuron disease hallmarked by rapid loss of upper and lower motor neurons. The vast majority of ALS cases are sporadic (sALS) with no family history; however, genetic studies in the familial forms of the disease have identified over 30 genes encoding proteins with highly diverse functions, suggesting that distinct pathogenic mechanism converge on neuronal death. Diverse pathology in ALS is further supported by studies using genetic animal models and molecular analyses of post-mortem sALS samples. There is an unmet need for biomarkers that could diagnose, subgroup or predict disease phenotype of ALS patients for better treatment and for better design of clinical trials. However biomarker development for sALS has been challenging because the affected neuronal tissue cannot be sampled during life and efforts in the field to discover biochemical markers for sALS have focused on biofluid samples, such as CSF, blood, urine. These samples have clear limitations if functional studies are needed. Living patient derived cells, such as skin fibroblasts may provide functional biomarkers as well as insights into the underlying pathomechanisms. Objectives: In this study we aim to evaluate if morphology of organelles (ER, mitochondria, lysosomes) or ALS relevant proteins (TDP-43, G3BP1, HSP60) in patient fibroblasts can be used to distinguish ALS patients (sporadic or genetic) from controls, or predict disease phenotype in ALS. Furthermore we test if metabolic (galactose as primary substrate), oxidative (arsenite) or physical (heat shock) perturbations reveal defects in stress response of sALS cells under these readouts. To this end we test our large collection of ~400 samples of fibroblasts from sALS patients and age and sex matched controls. Results: We found that fibroblast morphology metrics show slight differences between controls and different types of ALS. We found that ALS and control fibroblasts both respond to the above stresses to an equal extent. Multivariate models based on morphometry of fibroblasts are weak predictors of disease type and clinical phenotype. Conclusions: Although fibroblasts are not affected in ALS they clearly show differences in organellar and cellular protein distributions at baseline and stress. These differences however are not strong enough to develop clinically relevant, high performance biomarkers to predict disease or clinical phenotype.