Schizophrenia is a kind of neurodevelopmental brain disease with genetic background.Cognitive impairment has always been concerned as the core symptom of schizophrenia, and genetic factors play an important role in the cognitive impairment process of schizophrenia.This paper intends to explore the relationship between various neurotransmitter systems and neurodevelopmental related genes and cognitive impairment in schizophrenia. With " schizophrenia" " cognitive" and " genetic" " dopamine" " glutamate" " serotonin" " norepinephrine" " acetylcholine" " neurodevelopmental" " genome-wide association studies" as key words, the author searched the English and Chinese literatures published from January 2001 to October 2019 in several databases, such as Pubmed, ScienceDirect, CNKI academic journal database, Wanfang academic journal database, and selected the literature that was in line with the review topic after a large number of readings.Meanwhile, the author applied the literature tracing method to search the references of the literature that had been reviewed. Finally, 29 related literatures were included, and it was found that cognitive impairment in schizophrenia is related to multiple neurotransmitter system genes and neurodevelopmental genes, and these genes have different mechanisms of action in the process of cognitive impairment. The occurrence and development of cognitive impairment in schizophrenia involve multiple gene effects. The genetic study of neurotransmitter system and neurodevelopmental level is helpful to explore the pathological mechanism of cognitive impairment in schizophrenia.Future research should focus on how the pathogenesis/candidate genes of schizophrenia affect the neurotransmitter system and neurodevelopmental circuits, and further elucidate the mechanism of genetic factors in the development of cognitive impairment in schizophrenia.

Objective:To observe the correlation between blood cell-related inflammatory markers and diabetic retinopathy (DR).Methods:A cross-sectional study. From June 2020 to February 2022, the phase Ⅰ data of Beichen Eye Study in Tianjin Medical University Eye Hospital were included in the study. The research contents included questionnaires, routine systemic and ocular examinations, and laboratory blood cell-related indicators including mean platelet volume (MPV), platelet distribution width (PDW), neutrophils, and lymphocytes were performed. Neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR) were calculated. The diagnosis and classification of DR referred to the international clinical classification standard of DR. Monocular or binocular DR was defined as DR patients. Participants were categorized into different groups based on whether they had diabetes and whether they had DR. The groups included the no-diabetes group, the diabetes without DR group, and the DR group. The Kruskal-Wallis H test was used for the comparison of quantitative data among multiple groups. Wilcoxon test was used for comparison between the two groups. The χ2 test was used to compare the categorical variables between groups. The variables was adjusted step by step, an unadjusted univariate model was built and the different parameters of the model Ⅰ, Ⅱ, Ⅲ were adjusted. The correlation between MPV, PDW, NLR, PLR, and DR in different models was analyzed by logistic regression. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic efficacy of different NLR models for DR. Results:A total of 3 328 subjects were recruited. Among them, 1 121 (33.68 %, 1 121/3 328) were males and 2 207 (66.32 %, 2 207/3 328) were females. The median age of the included participants was 61.84 (6.05) years. The no-diabetes group, the diabetes without DR group, and the DR group were 2 679, 476, and 173, respectively. There was no significant difference in MPV and PLR among the three groups ( H=5.98, 1.94; P=0.051, 0.379). However, compared with no-diabetes group and the diabetes without DR group, PDW and NLR in the DR group showed an upward trend. In model Ⅲ with completely adjusted related factors, NLR was an independent risk factor for DR in no-diabetes group and DR group [odds ratio ( OR)=1.440, 95% confidence interval ( CI) 1.087-1.920, P=0.041], diabetes without DR group and DR group [ OR=1.990, 95% CI 1.440-2.749, P<0.001]. The results of ROC curve analysis showed that the diagnostic efficiency of NLR model Ⅲ was the highest, the area under the curve was 0.751 (95% CI 0.706-0.796, P<0.001), the optimal cutoff value was 0.390, and the sensitivity and specificity were 74.3% and 64.8%, respectively. Conclusions:The NLR of the DR group is significantly higher than that of the no-diabetes group and diabetes without DR group. NLR is an independent risk factor for DR.