Study Baseline Characteristics
Of the 20 patients included (mean age and BMI of 47.05 and 49 respectively), 11 and 9 patients underwent RYGB and SG respectively. Half the patients had T2D. The overall baseline demographics divided by those with and without T2D are displayed in table 1.
Table 1. Baseline Demographics
all listed data are means ± standard deviation unless stated otherwise
Table 2. Effect of surgery by surgical procedure and T2D diagnosis subgroups
┼significant difference between baseline demographics
* p < 0.05 pre- and post-op comparison
Pre-Operative and 3-month Post-Operative Metabolite Comparisons – surgical intervention
At pre-operative baseline there were no significant differences in metabolite concentrations between the two surgical groups. Both surgical interventions led to significant reductions in weight across all subgroups at 3 months post-operation (table 2). HbA1c concentrations were significantly reduced at the 3-month timepoint following RYGB, but not in the VSG group.
RYGB intervention resulted in a significant decrease in kynurenic acid (p= 0.010, BH q = 0.048), xanthurenic acid (p=0.001, BH q=0.017) and tryptophan (p=0.002, BH q=0.017) concentrations. Concentrations of 3-OH kynurenine (p=0.023, BH q=0.082) and quinolinic acid (p=0.043, BH q=0.121) also decreased, however presented BH q values of > 0.05 post control of the FDR. The VSG procedure did not result in any significant changes in metabolite concentrations at the 3-month timepoint (table 3) but post-operative trend changes mirrored those observed in the RYGB group. No significant difference was found in the kynurenine/tryptophan ratio for either the RGYB or VSG groups after surgery.
Table 3. Effect of surgery by surgical procedure subgroup on measured metabolites
q values were generated using the Benjamini and Hochberg method to control the false discovery rate (FDR)
Units of all of metabolites displayed - ng/ml
KTR expressed as a ratio
Pre-Operative and 3-month Post-Operative Metabolite Comparisons – T2D vs ND
At pre-operative baseline, there was a significantly higher concentration of HbA1c in those with T2D which was expected. In addition, serum tryptophan (p=0.005) and xanthurenic acid (p=0.015) concentrations were higher in those with T2D (figure 2), although after controlling for the FDR, BH q values for both metabolites were > 0.05 (q=0.10 and q=0.14 respectively).
Following surgical intervention, Hba1c concentrations were significantly reduced in both the T2D and ND groups, with a greater reduction in the T2D group. In the T2D group, significant reductions in the concertation of xanthurenic acid (p=0.004, BH q=0.030) and tryptophan (p=0.003, BH q=0.030) occurred (Figure 3). No significant metabolite changes were observed in the ND group at the 3-month post-surgery timepoint (table 4). The kynurenine/tryptophan ratio did not significantly change between pre- and post-surgery for either the T2D or the ND group.
Table 4. Effect of surgery by T2D subgroup on measured metabolites
q values were generated using the Benjamini and Hochberg method to control the false discovery rate (FDR)
Units of all of metabolites displayed - ng/ml
KTR expressed as a ratio
Metabolite relationship with clinical measurements – BMI and Hba1c
The serum concentrations of TRP (R=0.57, p=4.2e-5), KYNA (R=0.33, p=0.024) and XA (R=0.57, p=0.001) were found to be positively correlated with the corresponding serum HbA1c concentrations at the time of sampling (Figure 4).
To further examine the effect of surgery on the kynurenine pathway, the correlation coefficient for the change in concentrations for each pathway metabolite with Δ BMI and ΔHbA1c was calculated (Figure 5). Changes in BMI and HbA1c were not found to be significantly correlated with any of the Δ of measured metabolites after controlling for FDR using the BH method. However, there were several strong correlations observed between ΔHba1c and ΔTRP (r=0.56, p=0.011, BH q= 0.074), ΔXA (r=0.76, p=0.029, BH q= 0.109). As well as ΔBMI and ΔKYN (r=0.56, p=0.017, BH q=0.082).
Within the metabolic pathway, ΔTRP showed a positive correlation with the downstream metabolite of ΔKYNA. ΔNeopterin often used a marker of inflammation, was found to be significantly positively correlated with ΔQA (r= 0.66, p=0.002, BH q=0.018) and inversely correlated with ΔKYNA (r=-0.61, p=0.004, BH q=0.037). To further illustrate the extensive correlation relationship between all quantified metabolites, BMI and HbA1c, a correlation network map is presented in figure 6.