Spss 25.0 software for windows

All results are presented as means ± standard error of the mean (SEM). Statistical analyses of all data were conducted with SPSS 25.0 software for Windows (SPSS, Inc., Chicago, IL, United States). The normality of the data was analyzed using the Shapiro–Wilk test. If it was a normal distribution, differences among the three groups were assessed by a one-way analysis of variance (ANOVA) throughout the study, and post-hoc tests between all groups were performed using the least significant difference (LSD) test. Otherwise, the Kruskal–Wallis test was used. Body weight was analyzed using a one-way repeated measures ANOVA with group as an independent factor and time as a repeated measure, and the value of p was calculated from the LSD post-hoc test. Paired t-test was used to compare SP before and after CUMS. The significance level for all tests was set at p < 0.05. GraphPad Prism 8.0 was used to visualize the results of statistical analyses.

Statistical analyses were performed using the SPSS 25.0 software for Windows (Chicago, IL, USA). The Shapiro–Wilk test was used to examine whether the variables were normally distributed. The T-test was used to evaluate the initial differences between the two groups and a chi-square (Χ²) test was used for the categorical data. Two-way repeated measures ANOVA with the Bonferroni post-hoc test was used to compare the mean differences within groups and between the two groups. Moreover, the Pearson correlation coefficient was used to assess the correlation between variables at baseline and the end of the study. p-values ≤ 0.05 were considered statistically significant.

The outcome variable was dichotomized as positive versus not positive to identify any risk factors associated with seropositivity. A Chi-square test was used to assess significant differences among the groups. Multiple logistic regression was used to model the odds ratio (OR) and its 95% confidence interval (CI) of being seropositive related to the variables. Significant potential risk factors at p < 0.05 (two-tailed; alpha = 0.05) were then evaluated using stepwise regression to construct a multiple model (Wald test stepwise p-Wald value to enter p < 0.05). The multiple logistic model was developed using a stepwise approach. Backward elimination followed by a forward selection for each variable at a time was performed using a likelihood ratio test at each step with 0.05 (two-tailed; alpha = 0.05) as the significance level for removal or entry. The fit of the models was assessed using the Hosmer and Lemeshow goodness-of-fit test [50 ]. The model was rerun until all remaining variables presented statistically significant values (p < 0.05). All statistical analyses were performed using SPSS^® 25.0 software for Windows.

All data were analyzed using SPSS 25.0 software for Windows (SPSS Inc., Chicago, IL, USA). Differences in demographic and clinical characteristics between rs1360780 CC or T-allele carriers were examined using chi-squared tests for categorical variables and t-tests for continuous variables. Stepwise linear regression analysis was performed to identify the main and interaction effects of the FKBP5 gene and childhood trauma on trait resilience, with potentially confounding factors. Before constructing the regression model, to determine which variables might best predict trait resilience in AUD patients, we first calculated bivariate correlations. To avoid multicollinearity in the regression analysis, only variables that were not significantly correlated with each other were included as independent variables in the regression analysis. Potential associated factors, including the FKBP5 rs1360780 polymorphism, childhood trauma, the interaction between genotype and trauma (gene * trauma), and other demographic variables or clinical characteristics related to AUD, were considered independent variables in the regression models. Additionally, to examine allele-specific associations between FKBP5 DNA methylation levels and trait resilience, partial correlation analysis was conducted according to the genotype groups of FKBP5 rs1360780.