Association of DTNBP1 With Schizophrenia: Findings From Two Independent Samples of Han Chinese Population

Objectives: Schizophrenia (SZ) is a complex psychiatric disorder that has a strong genetic basis. Dystrobrevin-binding protein 1 (DTNBP1) is one of the genes thought to be pivotal in regulating the glutamatergic system. Studies have suggested that variations in DTNBP1 confer susceptibility to SZ and clinical symptoms. Here, we performed a two-stage independent verification study to identify polymorphisms of the DTNBP1 gene that might be associated with SZ in the Han Chinese population. Methods: In stage 1, 14 single nucleotide polymorphisms (SNPs) were genotyped in 528 paranoid SZ patients and 528 healthy controls (HCs) using the Illumina GoldenGate assays on a BeadStation 500G Genotyping System. In stage 2, ten SNPs were genotyped in an independent sample of 1,031 SZ patients and 621 HCs using the Illumina 660k Genotyping System. Clinical symptoms were assessed using the Positive and Negative Syndrome Scale. Results: There was a significant association related to allele frequency, and a trend association in relation to genotype between SZ patients and HCs at rs4712253 (p = 0.03 and 0.05, respectively). These associations were not evident following Bonferroni correction (p \u3e 0.05 for both). Haplotype association analysis revealed that only two haplotypes (GAG and GAA; rs16876575-rs9464793-rs4712253) were significantly different between SZ patients and HCs (chi(2) = 4.24, 6.37, p = 0.04 and 0.01, respectively). In addition, in SZ patients there was a significant association in the rs4964793 genotype for positive symptoms, and in the rs1011313 genotype for excitement/hostility symptoms (p = 0.01 and 0.002, respectively). We found a significant association in the baseline symbol digital modalities test (SDMT), forward-digital span (DS), backward-DS, and semantic fluency between SZ patients and HCs (p \u3c 0.05 for all). Finally, the SNP rs1011313 genotypes were associated with SDMT in SZ patients (p = 0.04). Conclusion: This study provides further evidence that SNP rs4712253 of DTNBP1 has a nominal association with SZ in the Han Chinese population. Such a genotype variation may play a role in psychopathology and cognitive function

Clinical Assistant Diagnosis for Electronic Medical Record Based on Convolutional Neural Network

Automatically extracting useful information from electronic medical records along with conducting disease diagnoses is a promising task for both clinical decision support(CDS) and neural language processing(NLP). Most of the existing systems are based on artificially constructed knowledge bases, and then auxiliary diagnosis is done by rule matching. In this study, we present a clinical intelligent decision approach based on Convolutional Neural Networks(CNN), which can automatically extract high-level semantic information of electronic medical records and then perform automatic diagnosis without artificial construction of rules or knowledge bases. We use collected 18,590 copies of the real-world clinical electronic medical records to train and test the proposed model. Experimental results show that the proposed model can achieve 98.67\% accuracy and 96.02\% recall, which strongly supports that using convolutional neural network to automatically learn high-level semantic features of electronic medical records and then conduct assist diagnosis is feasible and effective.Comment: 9 pages, 4 figures, Accepted by Scientific Report