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. 2024 Apr 30:29:e943282.
doi: 10.12659/AOT.943282.

Does Antibiotic Use Increase the Risk of Post-Transplantation Diabetes Mellitus? A Retrospective Study of Renal Transplant Patients

Zhenwei Jiang  1 , Caomei Xu  1 , Huan Hou  2 , Xuping Yang  1 , Minyan Qian  1 , Lian Zuo  1 , Peipei Wang  3 , Qing Qian  1 , Yan Jiang  1 , Nan Hu  1
Affiliations

Does Antibiotic Use Increase the Risk of Post-Transplantation Diabetes Mellitus? A Retrospective Study of Renal Transplant Patients

Zhenwei Jiang et al. Ann Transplant. .

Abstract

BACKGROUND This study aimed to investigate the incidence of post-transplant diabetes mellitus (PTDM) in renal transplant (RT) patients at our center and to explore new risk factors for PTDM. MATERIAL AND METHODS This retrospective study included RT patients from 2010 to 2022. Clinic data on RT patients were obtained from hospital electronic medical records. CYP3A5*3, POR*28, ABCB1 (3435 C>T), and ABCB1 (1236 C>T) were genotyped in RT patients. The associations between age, BMI, concentration of tacrolimus (TAC), polymorphism of genes, antibiotics (eg, penicillins, cephalosporins, oxazolidinones, quinolones), numbers and days of antibiotic use, and PTDM were analyzed. RESULTS In this study, 409 patients with RT were included. The cumulative incidence of PTDM in the first year after RT was 9.05%. The numbers and days of antibiotic use in PTDM patients were significantly higher than those in non-PTDM patients. Multivariate logistic regression analysis identified age (OR=1.047, P=0.014), body mass index (BMI) (OR=1.178, P=0.007), dose-adjusted trough concentration of TAC (TAC C₀/D) at 7 days after RT (OR=1.159, P=0.042), trough concentration of TAC (TAC C₀) at 28 days after RT (OR=1.094, P=0.042), and levofloxacin (OR=5.975, P=0.003) as independent risk factors for PTDM. CONCLUSIONS In addition to age, BMI, and TAC concentration after RT, antibiotic use may be a novel factor affecting PTDM. The use of antibiotics may influence the development of PTDM.

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Conflict of interest statement

Conflict of interest: None declared

Figures

Figure 1
Figure 1. Comparison of TAC C0 and C0/D at different time points after transplantation between PTDM patients and non-PTDM patients
(A) TAC C0 during 1 year of follow-up; (B) TAC C0/D ratio during 1 year of follow-up. Values are expressed as the mean±standard deviation. Quantitative variables were analyzed using the t test.
Figure 2
Figure 2. Influence of CYP3A5*3 polymorphism on TAC C0 and C0/D
TAC C0: TAC trough level; TAC C0/D: TAC dose-adjusted trough level. (A, B) TAC C0 and C0/D over time by CYP3A5*3 genotype. genotype wild-type vs mutant homozygous genotype *: * P<0.05, ** P<0.01, *** P<0.001; wild-type vs mutant heterozygous genotype#: # P<0.05, ## P<0.01, ### P<0.001; mutant heterozygous genotype vs mutant homozygous genotype$: $ P<0.05, $$ P<0.01, $$$ P<0.001. Values are expressed as the mean±standard deviation. The data were analyzed by one-way ANOVA, with post hoc Bonferroni’s or Games-Howell’s multiple comparison tests based on homogeneity of variance.
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