Quantitative electroencephalography parameters as neurophysiological biomarkers of schizophrenia-related deficits: A Phase II substudy of patients treated with iclepertin (BI 425809)

定量脑电图参数作为精神分裂症相关缺陷的神经生理学生物标志物:一项使用 iclepertin (BI 425809) 治疗的患者的 II 期子研究

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Abstract

Patients with schizophrenia experience cognitive impairment related to neural network dysfunction and deficits in sensory processing. These deficits are thought to be caused by N-methyl-D-aspartate receptor hypofunction and can be assessed in patient populations using electroencephalography (EEG). This substudy from a Phase II, randomized, double-blind, placebo-controlled, parallel-group study investigating the safety and efficacy of the novel glycine transporter-1 inhibitor, iclepertin (BI 425809), assessed the potential of EEG parameters as clinically relevant biomarkers of schizophrenia and response to iclepertin treatment. Eligible patients were randomized to once-daily add-on iclepertin (2, 5, 10, or 25 mg), or placebo (1:1:1:1:2 ratio) for 12 weeks. EEG data were recorded from a subgroup of patients (n = 79) at baseline and end of treatment (EoT). EEG parameters of interest were mismatch negativity (MMN), auditory steady-state response (ASSR), and resting state gamma power, and their correlations with clinical assessments. At baseline, MMN and ASSR exhibited consistent correlations with clinical assessments, indicating their potential value as neurophysiological biomarkers of schizophrenia-related deficits. ASSR measures were positively correlated to the MATRICS Consensus Cognitive Battery overall and neurocognitive composite scores; MMN amplitude was positively correlated with Positive and Negative Syndrome Scale scores. However, correlations between change from baseline (CfB) at EoT in clinical assessments, and baseline or CfB at EoT for EEG parameters were modest and inconsistent between dose groups, which might indicate low potential of these EEG parameters as predictive and treatment response biomarkers. Further methodological refinement is needed to establish EEG parameters as useful drug development tools for schizophrenia.

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