Basic visual dysfunction allows classification of patients with schizophrenia with exceptional accuracy

• Published in: Schizophrenia research Vol. 159; no. 1; pp. 226 - 233
• Main Authors: González-Hernández, J.A, Pita-Alcorta, C, Padrón, A, Finalé, A, Galán, L, Martínez, E, Díaz-Comas, L, Samper-González, J.A, Lencer, R, Marot, M
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01-10-2014; Elsevier
• Subjects: Adult; Adult and adolescent clinical studies; Biological and medical sciences; Biomarker; EEG; Electroencephalography; Evoked Potentials, Visual - physiology; Female; Humans; Image Processing, Computer-Assisted; LORETA; Magnetic Resonance Imaging; Male; Medical sciences; Photic Stimulation; Psychiatry; Psychology. Psychoanalysis. Psychiatry; Psychopathology. Psychiatry; Psychoses; Reproducibility of Results; ROC Curve; Schizophrenia; Schizophrenia - classification; Schizophrenia - complications; Spectral resolution; VEP; Vision Disorders - diagnosis; Vision Disorders - etiology; Young Adult; VEP; Biomarker; Spectral resolution; LORETA; EEG; Human; Electrophysiology; Biological marker; Schizophrenia; Electroencephalography; Psychosis; Electrodiagnosis; Accuracy; Vision; Classification; Perception
• ISSN: 0920-9964; 1573-2509
• DOI: 10.1016/j.schres.2014.07.052

Abstract Basic visual dysfunctions are commonly reported in schizophrenia; however their value as diagnostic tools remains uncertain. This study reports a novel electrophysiological approach using checkerboard visual evoked potentials (VEP). Sources of spectral resolution VEP-components C1, P1 and N1 were estimated by LORETA, and the band-effects (BSE) on these estimated sources were explored in each subject. BSEs were Z-transformed for each component and relationships with clinical variables were assessed. Clinical effects were evaluated by ROC-curves and predictive values. Forty-eight patients with schizophrenia (SZ) and 55 healthy controls participated in the study. For each of the 48 patients, the three VEP components were localized to both dorsal and ventral brain areas and also deviated from a normal distribution. P1 and N1 deviations were independent of treatment, illness chronicity or gender. Results from LORETA also suggest that deficits in thalamus, posterior cingulum, precuneus, superior parietal and medial occipitotemporal areas were associated with symptom severity. While positive symptoms were more strongly related to sensory processing deficits (P1), negative symptoms were more strongly related to perceptual processing dysfunction (N1). Clinical validation revealed positive and negative predictive values for correctly classifying SZ of 100% and 77%, respectively. Classification in an additional independent sample of 30 SZ corroborated these results. In summary, this novel approach revealed basic visual dysfunctions in all patients with schizophrenia, suggesting these visual dysfunctions represent a promising candidate as a biomarker for schizophrenia.