The effect of psychosis associated CACNA1C,and its epistasis with ZNF804A,on brain function

CACNA1C‐rs1006737 and ZNF804A‐rs1344706 polymorphisms are among the most robustly associated with schizophrenia (SCZ) and bipolar disorder (BD), and recently with brain phenotypes. As these patients show abnormal verbal fluency (VF) and related brain activation, we asked whether the latter was affected by these polymorphisms (alone and in interaction)—to better understand how they might induce risk. We recently reported effects on functional VF‐related (for ZNF804A‐rs1344706) and structural (for both) connectivity. We genotyped and fMRI‐scanned 54 SCZ, 40 BD and 80 controls during VF. With SPM, we assessed the main effect of CACNA1C‐rs1006737, and its interaction with ZNF804A‐rs1344706, and their interaction with diagnosis, on regional brain activation and functional connectivity (psychophysiological interactions—PPI). Using public data, we reported effects of CACNA1C‐rs1006737 and diagnosis on brain expression. The CACNA1C‐rs1006737 risk allele was associated with increased activation, particularly in the bilateral prefronto‐temporal cortex and thalamus; decreased PPI, especially in the left temporal cortex; and gene expression in white matter and the cerebellum. We also found unprecedented evidence for epistasis (interaction between genetic polymorphisms) in the caudate nucleus, thalamus, and cingulate and temporal cortical activation; and CACNA1C up‐regulation in SCZ and BD parietal cortices. Some effects were dependent on BD/SCZ diagnosis. All imaging results were whole‐brain, voxel‐wise, and familywise‐error corrected. Our results support evidence implicating CACNA1C and ZNF804A in BD and SCZ, adding novel imaging evidence in clinical populations, and of epistasis—which needs further replication. Further scrutiny of the inherent neurobiological mechanisms may disclose their potential as putative drug targets.     

Characteristics of brain connectivity during verbal fluency test: Convolutional neural network for functional near-infrared spectroscopy analysis

Human connectome describes the complicated connection matrix of nervous system among human brain. It also possesses high potential of assisting doctors to monitor the brain injuries and recoveries in patients. In order to unravel the enigma of neuron connections and functions, previous research has strived to dig out the relations between neurons and brain regions. Verbal fluency test (VFT) is a general neuropsychological test, which has been used in functional connectivity investigations. In this study, we employed convolutional neural network (CNN) on a brain hemoglobin concentration changes (ΔHB) map obtained during VFT to investigate the connections of activated brain areas and different mental status. Our results show that feature of functional connectivity can be identified accurately with the employment of CNN on ΔHB mapping, which is beneficial to improve the understanding of brain functional connections.