2.4. Statistical Analysis
All statistical analyses were performed using Stata (version 15.0) or R (version 4.1.0). The baseline characteristics, including baseline demographic factors and fasting blood parameters of the study participants (n = 28), were presented as mean (standard deviation) or number (%). We then depicted the gut mycobiome dynamics and profiles over the three intervention sets at both group and individual levels. Due to the n-of-1 design of the trial, we are also interested to see the gut mycobiome dynamics over time for each participant. At the individual level, we described the gut fungal genera detected among ≥50% of the sampling points of each participant. In the following statistical analysis, we only conducted a group-level comparison to achieve the aim of the present study (i.e., to investigate the overall effect of dietary macronutrient distributions on gut mycobiome).Among the 28 participants who completed the trial, we compared the gut fungal alpha diversity before and after each intervention by paired Wilcoxon–Mann–Whitney test. The Bray–Curtis dissimilarity matrix was calculated based on the composition at the genus level using the Next, we used the paired Wilcoxon–Mann–Whitney test to compare the mean differences in fungal genera before and after the dietary interventions (HC or LC dietary intervention). Gut fungal genera present in less than 5% of the stool samples were not considered for statistical analysis. All In our exploratory analysis, we examined the association of the above diet-related gut fungi with postprandial glycemic responses under different dietary interventions (either the HC or LC diet) by using linear mixed-effect models accounting for repeated measures (multiple time points per participant): dependent variable ~ (intercept) + independent variable + age + sex + BMI + (1| subject). Gut fungal genera were included as fixed effects, and the subject ID was adjusted as a random effect. CGM data were tested for normality using the Shapiro–Wilk test and log-transformed where applicable. We averaged the gut mycobiome compositions before and after the diet interventions as well as the postprandial glycemic features at the corresponding study set for the subsequent correlation analysis. All CGM metrics were standardized to allow comparison across metrics. The model included five CGM metrics obtained by mean values from three HC and three LC diets separately as the dependent variables (MBG, MPG, AUC