Anti-ApoA-1 IgG serum levels predict worse poststroke outcomes. - Carbone, Federico; Satta, Nathalie; Montecucco, Fabrizio; Virzi, Julien; Burger, Fabienne; Roth, Aline; Roversi, Gloria; Tamborino, Carmine; Casetta, Ilaria; Seraceni, Silva; Trentini, Alessandro; Padroni, Marina; et al. (Eur J Clin Invest, 2016)
BACKGROUND: Autoantibodies to apolipoprotein A-1 (anti-ApoA-1 IgG) were shown to predict major adverse cardiovascular events and promote atherogenesis. However, their potential relationship with clinical disability and ischaemic lesion volume after acute ischaemic stroke (AIS) remains unexplored. MATERIALS AND METHODS: We included n = 76 patients admitted for AIS and we investigated whether baseline serum anti-ApoA-1 IgG levels could predict (i) AIS-induced clinical disability [assessed by the modified Rankin Scale (mRS)], and (ii) AIS-related ischaemic lesion volume [assessed by Computed Tomography (CT)]. We also evaluated the possible pro-apoptotic and pro-necrotic effects of anti-ApoA-1 IgG on human astrocytoma cell line (U251) using flow cytometry. RESULTS: High levels of anti-ApoA-1 IgG were retrieved in 15·8% (12/76) of patients. Increased baseline levels of anti-ApoA-1 IgG were independently correlated with worse mRS [β = 0·364; P = 0·002; adjusted odds ratio (OR): 1·05 (95% CI 1·01-1·09); P = 0·017] and CT-assessed ischaemic lesion volume [β = 0·333; P < 0·001; adjusted OR: 1·06 (95% CI 1·01-1·12); P = 0·048] at 3 months. No difference in baseline clinical, biochemical and radiological characteristics was observed between patients with high vs. low levels of anti-ApoA-1 IgG. Incubating human astrocytoma cells with anti-ApoA-1 IgG dose dependently induced necrosis and apoptosis of U251 cells in vitro. CONCLUSION: Anti-ApoA-1 IgG serum levels at AIS onset are associated with poorer clinical recovery and worse brain lesion volume 3 months after AIS. These observations could be partly explained by the deleterious effect of anti-ApoA-1 IgG on human brain cell survival in vitro and may have clinical implication in the prediction of poor outcome in AIS.