Low frequency oscillations are essential in cognitive function impairment in schizophrenia. While functional connectivity can reveal the synchronization between distant brain regions, the regional abnormalities in task-independent baseline brain activity are less clear, especially in specific frequency bands. Here, we used a regional homogeneity (ReHo) method combined with resting-state functional magnetic resonance imaging to investigate low frequency spontaneous neural activity in the three different frequency bands (slow-5∶0.01–0.027 Hz; slow-4∶0.027–0.08 Hz; and typical band: 0.01–0.08 Hz) in 69 patients with schizophrenia and 62 healthy controls. Compared with controls, schizophrenia patients exhibited decreased ReHo in the precentral gyrus, middle occipital gyrus, and posterior insula, whereas increased ReHo in the medial prefrontal cortex and anterior insula. Significant differences in ReHo between the two bands were found in fusiform gyrus and superior frontal gyrus (slow-4> slow-5), and in basal ganglia, parahippocampus, and dorsal middle prefrontal gyrus (slow-5> slow-4). Importantly, we identified significant interaction between frequency bands and groups in the inferior occipital gyrus and caudate body. This study demonstrates that ReHo changes in schizophrenia are widespread and frequency dependent.

Existing studies have found the relationship between handedness and schizotypy to be inconsistent and had limited generalizability since only highly homogeneous groups have been investigated. This study aimed to examine the relation between handedness and the four schizotypal factors identified from a previous confirmatory factor analysis in a population of high familial loading for schizophrenia. Study subjects consisted of nonpsychotic first-degree relatives (850 parents and 334 siblings) of sib-pairs who were co-affected with schizophrenia. All participants were interviewed with the Diagnostic Interview for Genetic Studies, which contains a section of the modified Structured Interview for Schizotypy, and the Annett handedness questionnaire. Both categorical and continuous indicators for handedness were examined. Non-right handed siblings of schizophrenia patients displayed more positive schizotypal features than their right handed counterparts when the two-way Annett's handedness classification was adopted. No association was found when handedness was treated as continuous. The relationship between handedness and schizotypy was insignificant for parents probably due to the strong social pressure against left-handedness. We concluded that categorical non-right handedness was associated with positive schizotypy in nonpsychotic siblings of schizophrenia patients. The results indicate that an atypical cerebral lateralization underlying non-right handedness may be also a contributing factor to positive schizotypy.

Since brain tissue is not readily accessible, a new focus in search of biomarkers for schizophrenia is blood-based expression profiling of non-protein coding genes such as microRNAs (miRNAs), which regulate gene expression by inhibiting the translation of messenger RNAs. This study aimed to identify potential miRNA signature for schizophrenia by comparing genome-wide miRNA expression profiles in patients with schizophrenia vs. healthy controls. A genome-wide miRNA expression profiling was performed using a Taqman array of 365 human miRNAs in the mononuclear leukocytes of a learning set of 30 cases and 30 controls. The discriminating performance of potential biomarkers was validated in an independent testing set of 60 cases and 30 controls. The expression levels of the miRNA signature were then evaluated for their correlation with the patients' clinical symptoms, neurocognitive performances, and neurophysiological functions. A seven-miRNA signature (hsa-miR-34a, miR-449a, miR-564, miR-432, miR-548d, miR-572 and miR-652) was derived from a supervised classification with internal cross-validation, with an area under the curve (AUC) of receiver operating characteristics of 93%. The putative signature was then validated in the testing set, with an AUC of 85%. Among these miRNAs, miR-34a was differentially expressed between cases and controls in both the learning (P = 0.005) and the testing set (P = 0.002). These miRNAs were differentially correlated with patients' negative symptoms, neurocognitive performance scores, and event-related potentials. The results indicated that the mononuclear leukocyte-based miRNA profiling is a feasible way to identify biomarkers for schizophrenia, and the seven-miRNA signature warrants further investigation.

We previously reported familial aggregation in flush response to niacin skin patch among schizophrenia patients and their nonpsychotic relatives. However, little is known about whether this abnormal skin response is associated with genetic loading for schizophrenia. This study compared the niacin flush response in subjects from families with only one member affected with schizophrenia (simplex families) with those from families having a sib-pair with schizophrenia (multiplex families). Subjects were patients with schizophrenia and their nonpsychotic first-degree relatives from simplex families (176 probands, 260 parents, and 80 siblings) and multiplex families (311 probands, 180 parents, and 52 siblings) as well as 94 healthy controls. Niacin patches of 3 concentrations (0.001M, 0.01M, and 0.1M) were applied to forearm skin, and the flush response was rated at 5, 10, and 15 minutes, respectively, with a 4-point scale. More attenuated flush response to topical niacin was shown in schizophrenia probands and their relatives from multiplex families than in their counterparts from simplex families, and the differentiation was better revealed using 0.1M concentration of niacin than 0.01M or 0.001M. For the highest concentration of 0.1M and the longest time lag of 15 minutes, a subgroup of probands (23%), parents (27%), and siblings (19%) still exhibited nonflush response. Flush response to niacin skin patch is more impaired in schizophrenia patients and their relatives from families with higher genetic loading for schizophrenia, and this finding has implications for future genetic dissection of schizophrenia.

Background

Implicit learning was reported to be intact in schizophrenia using artificial grammar learning. However, emerging evidence indicates that artificial grammar learning is not a unitary process. The authors used dual coding stimuli and schizophrenia clinical symptom dimensions to re-evaluate the effect of schizophrenia on various components of artificial grammar learning.

Methods

Letter string and color pattern artificial grammar learning performances were compared between 63 schizophrenic patients and 27 comparison subjects. Four symptom dimensions derived from a Chinese Positive and Negative Symptom Scale ratings were correlated with patients' artificial grammar implicit learning performances along the two stimulus dimensions. Patients' explicit memory performances were assessed by verbal paired associates and visual reproduction subtests of the Wechsler Memory Scales Revised Version to provide a contrast to their implicit memory function.

Results

Schizophrenia severely hindered color pattern artificial grammar learning while the disease affected lexical string artificial grammar learning to a lesser degree after correcting the influences from age, education and the performance of explicit memory function of both verbal and visual modalities. Both learning performances correlated significantly with the severity of patients' schizophrenic clinical symptom dimensions that reflect poor abstract thinking, disorganized thinking, and stereotyped thinking.

Conclusion

The results of this study suggested that schizophrenia affects various mechanisms of artificial grammar learning differently. Implicit learning, knowledge acquisition in the absence of conscious awareness, is not entirely intact in patients with schizophrenia. Schizophrenia affects implicit learning through an impairment of the ability of making abstractions from rules and at least in part decreasing the capacity for perceptual learning.

Objectives

Endophenotypes in schizophrenia research is a contemporary approach to studying this heterogeneous mental illness, and several candidate neurophysiological markers (e.g. P50 sensory gating) and neuropsychological tests (e.g. Continuous Performance Test (CPT) and Wisconsin Card Sorting Test (WCST)) have been proposed. However, the clinical utility of a single marker appears to be limited. In the present study, we aimed to construct a diagnostic model incorporating P50 sensory gating with other neuropsychological tests in order to improve the clinical utility.

Methods

We recruited clinically stable outpatients meeting DSM-IV criteria of schizophrenia and age- and gender-matched healthy controls. Participants underwent P50 sensory gating experimental sessions and batteries of neuropsychological tests, including CPT, WCST and Wechsler Adult Intelligence Scale Third Edition (WAIS-III).

Results

A total of 106 schizophrenia patients and 74 healthy controls were enrolled. Compared with healthy controls, the patient group had significantly a larger S2 amplitude, and thus poorer P50 gating ratio (gating ratio = S2/S1). In addition, schizophrenia patients had a poorer performance on neuropsychological tests. We then developed a diagnostic model by using multivariable logistic regression analysis to differentiate patients from healthy controls. The final model included the following covariates: abnormal P50 gating (defined as P50 gating ratio >0.4), three subscales derived from the WAIS-III (Arithmetic, Block Design, and Performance IQ), sensitivity index from CPT and smoking status. This model had an adequate accuracy (concordant percentage = 90.4%; c-statistic = 0.904; Hosmer-Lemeshow Goodness-of-Fit Test, p = 0.64>0.05).

Conclusion

To the best of our knowledge, this is the largest study to date using P50 sensory gating in subjects of Chinese ethnicity and the first to use P50 sensory gating along with other neuropsychological tests to develop a diagnostic model for schizophrenia. Further research to validate the predictive accuracy of this model by applying it on other samples is warranted.

Background

Schizophrenia is a heterogeneous disorder with diverse presentations. The current and the proposed DSM-V diagnostic system remains phenomenologically based, despite the fact that several neurobiological and neuropsychological markers have been identified. A multivariate approach has better diagnostic utility than a single marker method. In this study, the mismatch negativity (MMN) deficit of schizophrenia was first replicated in a Han Chinese population, and then the MMN was combined with several neuropsychological measurements to differentiate schizophrenia patients from healthy subjects.

Methodology/Principal Findings

120 schizophrenia patients and 76 healthy controls were recruited. Each subject received examinations for duration MMN, Continuous Performance Test, Wisconsin Card Sorting Test, and Wechsler Adult Intelligence Scale Third Edition (WAIS-III). The MMN was compared between cases and controls, and important covariates were investigated. Schizophrenia patients had significantly reduced MMN amplitudes, and MMN decreased with increasing age in both patient and control groups. None of the neuropsychological indices correlated with MMN. Predictive multivariate logistic regression models using the MMN and neuropsychological measurements as predictors were developed. Four predictors, including MMN at electrode FCz and three scores from the WAIS-III (Arithmetic, Block Design, and Performance IQ) were retained in the final predictive model. The model performed well in differentiating patients from healthy subjects (percentage of concordant pairs: 90.5%).

Conclusions/Significance

MMN deficits were found in Han Chinese schizophrenia patients. The multivariate approach combining biomarkers from different modalities such as electrophysiology and neuropsychology had a better diagnostic utility.