Schizophrenia is a complex genetic disease and characterized by affective, cognitive, neuromorphological, and molecular abnormalities that may have a neurodevelopmental origin. MicroRNAs (miRNAs) are critical to neurodevelopment and adult neuronal processes by modulating the activity of multiple genes within biological networks. MiR-137 as a brain-enriched microRNA, plays important roles in regulating embryonic neural stem cells (NSCs) fate determination, neuronal proliferation and differentiation, and synaptic maturation. Its dysregulation causes changes in the gene expression regulation network of the nervous system, thus inducing mental disorders. Recently, miR-137 has been confirmed as a gene related to schizophrenia susceptibility. In the following review, we summarize the expression pattern, epigenetic regulation and functions of miR-137. A more complete picture of the miR-137, which is dysregulated in psychiatric illness, may improve our understanding of the molecular mechanisms underlying schizophrenia.

Objective: It is suggested that estrogen receptors (ERs) might be associated with the disproportionate vulnerability of women to depressive episodes. Several variants in ER-alpha (ERα) and ER-beta (ERβ) have been linked to depression, but the results were not consistent. Hence, we conducted a meta-analysis to evaluate the association between ERα/ERβ and depression in a cohort of women.Methods: A comprehensive literature search was performed in public databases. The genetic association between polymorphisms in Erα/ERβ and depression risk in a cohort of women was evaluated by odds ratios (ORs) and 95% confidence intervals (CIs). Cochran’s Q test and the I² index were used to evaluate heterogeneity.Results: In total, 10 studies and 4 SNPs (rs2234693, rs9340799, rs4986938, rs1256049) were included in our meta-analysis. rs2234693 genotype was significantly associated with the risk of depression in women by dominant model (CC + CT vs TT, OR = 1.30, 95% CI: 1.09–1.55, p = 0.0031), recessive model (CC vs CT + TT, OR = 1.64, 95% CI: 1.00–2.67, p = 0.0478), additive model (CC vs TT, OR = 1.93, 95% CI: 1.12–3.35, p = 0.0189) and allelic model (C vs T, OR = 1.24, 95% CI: 1.10–1.39, p = 0.0003). For rs9340799, the frequencies of risk genotypes according to the dominant (GG + GA vs AA, OR = 1.47, 95% CI = 1.10–1.98, p = 0.0096, I² = 0%, p = 0.43) and allelic (G vs A, OR = 1.33, 95% CI: 1.04–1.69, p = 0.0236, I² = 0%, p = 0.39) models were significantly lower in women with depression than in controls within the Asian subgroup. For rs1256049, risk genotypes were significantly more frequent in depressed subjects than in controls under the dominant model (AA+ GA vs GG, OR = 1.62, 95% CI: 1.19–2.21, p = 0.0024) and the allelic model (A vs G, OR = 1.35, 95% CI: 1.07–1.72, p = 0.012) after sensitivity analysis by omitting one study which induce the heterogeneity.Conclusions: The current meta-analysis is the first and most comprehensive investigation of the association between ERs and depression in women, and the findings support the concept that ERs participate in the etiology of sex heterogeneity in depression.

Background and aims: Clinical diagnosis of gambling disorder (GD) remains challenging due to the heterogeneity in symptoms and a lack of consistency in the proposed neural mechanisms. Effective classification of GD may depend on neural representations of either risky decision-making or reward processing. Methods: To address these challenges, we recruited more than 100 individuals with GD and matched healthy controls, utilizing event-related fMRI during a novel risky decision-making task to elicit neural representations of risky decision-making and reward processing. Results: During the decision phase, there was no significant difference observed between the two groups even when a very liberal threshold was used. During reward processing, the GD group exhibited significantly increased activation in the right inferior frontal gyrus, right anterior insula, and bilateral posterior cingulate cortex in the risky reward condition compared with the healthy controls. A notable neural activation characteristic was the distinct response between risk-win and risk-loss conditions in reward processing, particularly in the right inferior frontal gyrus in the GD group. The classification for GD using the neural representation of reward yielded an area under the curve of 0.75 (±0.11 SD). Discussion and conclusion: These findings integrate biological and behavioral perspectives to provide new insights into the reward processes underlying GD. These findings highlight specific neural representations associated with GD and suggest potential biomarkers for diagnostic evaluation in GD.