VH1-69 germline encoded antibodies directed towards ADAMTS13 in patients with acquired thrombotic thrombocytopenic purpura

BACKGROUND: Autoantibodies directed towards ADAMTS13 are present in the majority of patients with acquired thrombotic thrombocytopenic purpura (TTP). Analysis of a set of antibodies derived from two patients with acquired TTP revealed frequent use of the VH1-69 heavy chain gene segment for the assembly of anti-ADAMTS13 antibodies. OBJECTIVE: We explored the ability of two VH1-69 germline gene-encoded antibodies to inhibit the von Willebrand factor (VWF)-processing activity of ADAMTS13 under different experimental conditions. Furthermore, the presence of VH1-69 encoded anti-ADAMTS13 antibodies in 40 patients with acquired TTP was monitored using monoclonal antibody G8, which specifically reacts with an idiotype expressed on VH1-69 encoded antibodies. METHODS AND RESULTS: Binding of the two VH1-69 encoded monoclonal antibodies was dependent on the presence of the spacer domain. Both antibodies inhibited ADAMTS13 activity under static conditions, as measured by cleavage of FRETS-VWF73 substrate and cleavage of VWF multimers. The recombinant antibodies were also capable of inhibiting the processing of UL-VWF strings on the surface of endothelial cells. G8-reactive antibodies directed towards ADAMTS13 were present in plasma of all patients containing anti ADAMTS13 antibodies. CONCLUSIONS: These results suggest that VH1-69 derived antibodies directed towards ADAMTS13 develop in the majority of patients with acquired TTP.

Autoantibodies directed against bactericidal/permeability-increasing protein in patients with cystic fibrosis: association with microbial respiratory tract colonization

BACKGROUND: Cystic fibrosis (CF) is associated with the appearance of serum autoantibodies directed against bactericidal/permeability-increasing protein (BPI). OBJECTIVES: To determine the age-specific seroprevalence rates of anti-BPI-IgG and IgA in a population of patients with CF and to correlate anti-BPI antibody concentrations with microbial respiratory tract colonization and pulmonary function variables at the time of serum sampling and 6 years thereafter. METHODS: Determination of BPI antibodies of the IgG and IgA isotypes using a commercial enzyme-linked immunosorbent assay in sera of a CF serum bank of 1992; correlation of anti-BPI antibody concentrations with age, clinical score, pulmonary function variables in 1992 and 1998, total serum immunoglobulin isotype concentrations and respiratory tract colonization with Pseudomonas aeruginosa and Aspergillus spp. RESULTS: Seventy-one patients (age in 1992, 14.1 +/- 7.5 years) were studied. Reactivities for anti-BPI-IgG and IgA were found in 28 (39%) and 26 (37%) patients, respectively. The seroprevalence of anti-BPI-IgA, but not IgG, increased significantly with age. P. aeruginosa colonization was associated with elevated concentrations of anti-BPI-IgG (P = 0.003) and IgA (P = 0.037). There were significant negative correlations between pulmonary function variables (vital capacity, forced expiratory volume in 1 s) in 1992 and 1998, respectively, and concentrations of anti-BPI-IgG or IgA in a multiple regression analysis. Anti-BPI-IgG, but not IgA, remained significantly associated with P. aeruginosa colonization (P = 0.006) and with reduced vital capacity (P = 0.01) in 1998 after correction for total serum isotype concentration. CONCLUSIONS: Anti-BPI-IgG are strongly associated with concurrent P. aeruginosa colonization and with long term restrictive pulmonary function abnormalities.

Parameter-free extraction of the functional network topology from intracranial EEG recordings: a time-resolved study of graph properties in focal onset seizures

Rationale: Focal onset epileptic seizures are due to abnormal interactions between distributed brain areas. By estimating the cross-correlation matrix of multi-site intra-cerebral EEG recordings (iEEG), one can quantify these interactions. To assess the topology of the underlying functional network, the binary connectivity matrix has to be derived from the cross-correlation matrix by use of a threshold. Classically, a unique threshold is used that constrains the topology [1]. Our method aims to set the threshold in a data-driven way by separating genuine from random cross-correlation. We compare our approach to the fixed threshold method and study the dynamics of the functional topology. Methods: We investigate the iEEG of patients suffering from focal onset seizures who underwent evaluation for the possibility of surgery. The equal-time cross-correlation matrices are evaluated using a sliding time window. We then compare 3 approaches assessing the corresponding binary networks. For each time window: * Our parameter-free method derives from the cross-correlation strength matrix (CCS)[2]. It aims at disentangling genuine from random correlations (due to finite length and varying frequency content of the signals). In practice, a threshold is evaluated for each pair of channels independently, in a data-driven way. * The fixed mean degree (FMD) uses a unique threshold on the whole connectivity matrix so as to ensure a user defined mean degree. * The varying mean degree (VMD) uses the mean degree of the CCS network to set a unique threshold for the entire connectivity matrix. * Finally, the connectivity (c), connectedness (given by k, the number of disconnected sub-networks), mean global and local efficiencies (Eg, El, resp.) are computed from FMD, CCS, VMD, and their corresponding random and lattice networks. Results: Compared to FMD and VMD, CCS networks present: *topologies that are different in terms of c, k, Eg and El. *from the pre-ictal to the ictal and then post-ictal period, topological features time courses that are more stable within a period, and more contrasted from one period to the next. For CCS, pre-ictal connectivity is low, increases to a high level during the seizure, then decreases at offset. k shows a ‘‘U-curve’’ underlining the synchronization of all electrodes during the seizure. Eg and El time courses fluctuate between the corresponding random and lattice networks values in a reproducible manner. Conclusions: The definition of a data-driven threshold provides new insights into the topology of the epileptic functional networks.