Aberrant migration features in primary skin fibroblasts of Huntington's disease patients hold potential for unraveling disease progression using an image based machine learning tool.

Huntington's disease (HD) is a complex neurodegenerative disorder with considerable heterogeneity in clinical manifestations. While CAG repeat length is a known predictor of disease severity, this heterogeneity suggests the involvement of additional genetic and environmental factors. Previously we revealed that HD primary fibroblasts exhibit unique features, including distinct nuclear morphology and perturbed actin cap, resembling characteristics seen in Hutchinson-Gilford Progeria Syndrome (HGPS). This study establishes a link between actin cap deficiency and cell motility in HD, which correlates with the HD patient disease severity. Here, we examined single-cell motility imaging features in HD primary fibroblasts to explore in depth the relationship between cell migration patterns and their respective HD patients' clinical severity status (premanifest, mild and severe). The single-cell analysis revealed a decline in overall cell motility in correlation with HD severity, being most prominent in severe HD subgroup and HGPS. Moreover, we identified seven distinct spatial clusters of cell migration in all groups, which their proportion varies within each group becoming a significant HD severity classifier between HD subgroups. Next, we investigated the relationship between Lamin B1 expression, serving as nuclear envelope morphology marker, and cell motility finding that changes in Lamin B1 levels are associated with specific motility patterns within HD subgroups. Based on these data we present an accurate machine learning classifier offering comprehensive exploration of cellular migration patterns and disease severity markers for future accurate drug evaluation opening new opportunities for personalized treatment approaches in this challenging disorder.

Perturbed actin cap as a new personalized biomarker in primary fibroblasts of Huntington's disease patients.

Primary fibroblasts from patient's skin biopsies are directly isolated without any alteration in the genome, retaining in culture conditions their endogenous cellular characteristics and biochemical properties. The aim of this study was to identify a distinctive cell phenotype for potential drug evaluation in fibroblasts from Huntington's Disease (HD) patients, using image-based high content analysis. We show that HD fibroblasts have a distinctive nuclear morphology associated with a nuclear actin cap deficiency. This in turn affects cell motility in a similar manner to fibroblasts from Hutchinson-Gilford progeria syndrome (HGPS) patients used as known actin cap deficient cells. Moreover, treatment of the HD cells with either Latrunculin B, used to disrupt actin cap formation, or the antioxidant agent Mitoquinone, used to improve mitochondrial activity, show expected opposite effects on actin cap associated morphological features and cell motility. Deep data analysis allows strong cluster classification within HD cells according to patients' disease severity score which is distinct from HGPS and matching controls supporting that actin cap is a biomarker in HD patients' cells correlated with HD severity status that could be modulated by pharmacological agents as tool for personalized drug evaluation.