RESUMEN
Tacrolimus (TAC) is an immunosuppressant widely used in kidney transplantation. TAC displays considerable interindividual variability in pharmacokinetics (PKs). Genetic and clinical factors play important roles in TAC PKs. We enrolled a total of 251 Chinese renal transplant recipients and conducted a genomewide association study (GWAS), linkage disequilibrium (LD), and one-way analysis of variance (ANOVA) to find genetic variants affecting log-transformed TAC trough blood concentration/dose ratio (log[C0 /D]). In addition, we performed dual luciferase reporter gene assays and multivariate regression models to evaluate the effect of the genetic variants. The GWAS results showed that all 23 genomewide significant single-nucleotide polymorphisms (p < 5 × 10-8 ) were located on chromosome 7, including CYP3A5*3. LD, conditional association analysis, and one-way ANOVA showed that rs75125371 T > C independently influenced TAC log(C0 /D). Dual luciferase reporter gene assays indicated that rs75125371 minor allele (C) was significantly associated with increased normalized luciferase activity than the major allele (T) in the Huh7 cells (p = 1.2 × 10-5 ) and HepaRG cells (p = 0.0097). A model inclusive of age, sex, hematocrit, CYP3A5*3, and rs75125371 explained 37.34% variance in TAC C0 . These results suggest that rs75125371 T > C is a functional and population-specific variant affecting TAC C0 in Chinese renal transplant recipients.
Asunto(s)
Trasplante de Riñón , Tacrolimus , Humanos , Tacrolimus/farmacocinética , Citocromo P-450 CYP3A/genética , Trasplante de Riñón/efectos adversos , Estudio de Asociación del Genoma Completo , Polimorfismo de Nucleótido Simple , China , GenotipoRESUMEN
PURPOSE: In addition to hyperglycemia and hyperlipidemia, obesity and hypertension are important cardiovascular risk factors for coronary heart disease (CHD) in patients with type 2 diabetes mellitus (T2DM). This study aims to explore the interaction of these risk factors. PATIENTS AND METHODS: Data of hospitalized patients with T2DM from 2013 to 2018 were collected. A multivariate logistic regression model was established. Patients with normal weight and blood pressure were recruited as controls. The interaction on the risk of CHD was evaluated by relative excess risk due to interaction (RERI). RESULTS: Among the 30,693 patients with T2DM, 7202 (23.5%) had CHD. In the low weight group, the prevalence of CHD in patients with hypertension was nearly four times higher than that in patients without hypertension (42.7% vs 11.3%, P < 0.01). The OR value of hypertension alone on CHD increased from 1.29 (95% CI 1.06-1.56) in the body mass index (BMI) 30.0-34.9 kg/m2 group to 1.35 (95% CI 1.11-1.62) in the BMI ≤ 18.5 kg/m2 group. Additive interaction was observed between hypertension and BMI in CHD risk, especially in the low weight group (RERI:2.2, 95% CI 0.9-3.5). BMI and CHD risk showed a smile curve relationship. The attributive proportion in the low weight group was higher than that in the severe obesity group, that is, 0.52 (95% CI 0.35-0.69) vs 0.18 (95% CI -0.59 to 0.95). CONCLUSION: Maintaining normal weight and avoiding low weight are particularly important for patients with co-occurring diabetes and hypertension to prevent the risk of CHD.
RESUMEN
The aim of this study was to identify novel genetic variants affecting tacrolimus trough blood concentrations. We analyzed the association between 58 single nucleotide polymorphisms (SNPs) across the CYP3A gene cluster and the log-transformed tacrolimus concentration/dose ratio (log (C0/D)) in 819 renal transplant recipients (Discovery cohort). Multivariate linear regression was used to test for associations between tacrolimus log (C0/D) and clinical factors. Luciferase reporter gene assays were used to evaluate the functions of select SNPs. Associations of putative functional SNPs with log (C0/D) were further tested in 631 renal transplant recipients (Replication cohort). Nine SNPs were significantly associated with tacrolimus log (C0/D) after adjustment for CYP3A5*3 and clinical factors. Dual luciferase reporter assays indicated that the rs4646450 G allele and rs3823812 T allele were significantly associated with increased normalized luciferase activity ratios (p < 0.01). Moreover, CYP3A7*2 was associated with higher TAC log(C0/D) in the group of CYP3A5 expressers. Age, serum creatinine and hematocrit were significantly associated with tacrolimus log (C0/D). CYP3A7*2, rs4646450, and rs3823812 are proposed as functional SNPs affecting tacrolimus trough blood concentrations in Chinese renal transplant recipients. Clinical factors also significantly affect tacrolimus metabolism.
Asunto(s)
Citocromo P-450 CYP3A/genética , Inmunosupresores/farmacocinética , Trasplante de Riñón , Tacrolimus/farmacocinética , Adulto , Envejecimiento/metabolismo , Pueblo Asiatico , Estudios de Cohortes , Creatinina/sangre , Femenino , Variación Genética , Hematócrito , Humanos , Masculino , Persona de Mediana Edad , Polimorfismo de Nucleótido Simple , Receptores de TrasplantesRESUMEN
AIM: To evaluate genetic variants affecting mycophenolic acid (MPA) metabolism in Chinese renal transplant recipients. METHODS: Total 11 SNPs of UGT1A9, UGT1A8, UGT2B7, ABCC2, ABCG2 and SLCO1B3 were genotyped in 408 Chinese renal transplant recipients. Associations between SNPs and MPA concentration/dose ratio (C0/D) were analyzed using different genetic models. Multivariate linear regression was used to analyze associations between log (C0/D) and clinical factors. Results: After adjustment by clinical factors, UGT2B7 rs7662029 was associated with log (C0/D) using a dominant (p = 0.041) and an additive (p = 0.038) model, ABCC2 rs717620 was associated with log (C0/D) using a recessive model (p = 0.019). Using additive model, SNP-SNP interactions were identified (p = 0.002) between ABCC2 rs717620 and UGT1A9 rs2741049, with interactions (p = 0.002) between ABCC2 rs717620 and UGT1A8 rs1042597. Age, albumin and serum creatinine were associated with log (C0/D). CONCLUSION: rs7662029 and rs717620 may affect MPA pharmacokinetics. SNP-SNP interactions and clinical factors may have significant effects on MPA metabolism.