Chih‐Min Liu

Schizophrenia has been associated with abnormal task-related brain activation in sensory and motor regions as well as social cognition network. Recently, two studies investigated temporal correlation between resting-state functional magnetic resonance imaging (R-fMRI) low-frequency oscillations (LFOs) in schizophrenia but reported mixed results. This may be due to the different frequency bands used in these studies. Here we utilized R-fMRI to measure the amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF) in 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. We showed that there were significant differences in ALFF/fALFF between the two bands (slow-5 and slow-4) in regions including basal ganglia, midbrain, and ventromedial prefrontal cortex. Importantly, we also identified significant interaction between frequency bands and groups in inferior occipital gyrus, precuneus, and thalamus. The results suggest that the abnormalities of LFOs in schizophrenia is dependent on the frequency band and suggest that future studies should take the different frequency bands into account when measure intrinsic brain activity.

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.

In order to evaluate the linkage of schizophrenia to loci at chromosome 15q, we genotyped six microsatellite markers at chromosome 15q11-14 in 52 Taiwanese schizophrenic families. Two phenotype models (narrow: DSM-IV schizophrenia only; and broad: including schizophrenia, schizoaffective, and other nonaffective psychotic disorders) were used to define the disease phenotype. Maximum nonparametric linkage scores (NPL scores) of 3.33 (P = 0.0003) and 2.96 (P = 0.0008) were obtained at the marker D15S976 under broad and narrow models, respectively. Positive linkage results were also observed at the marker D15S1360, previously reported to have significant linkage to a neurophysiological deficit of schizophrenia, with NPL scores of 2.71 (P = 0.003) and 2.78 (P = 0.002) under broad and narrow models, respectively. The results provide suggestive linkage evidence of schizophrenia to loci at chromosome 15q13-14 in an ethnically distinct Taiwanese sample.