METS‐IR, a novel score to evaluate insulin sensitivity, is associated with the urinary albumin–creatinine ratio in Chinese adults: A cross‐sectional REACTION study

The U-shape relationship between insulin resistance-related indexes and chronic kidney disease: a retrospective cohort study from National Health and Nutrition Examination Survey 2007-2016

BACKGROUND

There is ongoing debate on the correlation between chronic kidney disease (CKD) and insulin resistance (IR)-related indices. Our objective was to explore the prognostic ability of IR-related indexes for the prevalence of CKD, as well as the mortality from all causes and cardiovascular disease (CVD) in CKD patients.

METHODS

The data used in this study came from the National Health and Nutrition Examination Survey (NHANES). Binary logistic regression analysis, Cox proportional hazards model, and restricted cubic spline (RCS) were used to analyze the relationship between IR-related indexes, including metabolic score of IR (METS-IR), homeostatic model assessment for IR (HOMA-IR), triglyceride glucose index (TyG), triglyceride glucose-waist-to-height ratio (TyG-WHtR), triglyceride glucose-body mass index (TyG-BMI), with CKD and its all-cause mortality and CVD mortality. Subgroup analysis was performed to test the stability of the results. Finally, the predictive power of IR-related indexes for CKD was tested by the receiver operating characteristic (ROC) curve.

RESULTS

Among the recruited 10,660 participants, 15.42% were CKD patients. All IR-related indexes were found to be nonlinearly correlated to the prevalence of CKD in the study. When the TyG index was higher than 9.05, it was positively associated with CKD (OR: 1.77, 95% CI 1.44-2.18). Moreover, increased TyG-WHtR level was correlated with a greater prevalence of CKD when it was higher than 4.3 (OR: 1.31, 95% CI 1.19-1.45). Other IR-related indexes (METS-IR, HOMA-IR, and TyG-BMI) showed fewer notable correlations with CKD. The association of IR-related indexes and the prevalence of CKD remained consistent in most subgroups (P for interactions > 0.05). TyG-WHtR was also the predictor of all-cause mortality in CKD patients (HR: 1.34, 95% CI 1.14-1.58), while other IR-related indexes were not correlated with the all-cause mortality or CVD mortality in CKD patients (P > 0.05). Otherwise, ROC curves showed that TyG-WHtR had more robust diagnostic efficacy than other IR-related indexes (METS-IR, HOMA-IR, TyG, and TyG-BMI) in predicting CKD (area under the curve: 0.630, 95% CI 0.615-0.644).

CONCLUSIONS

IR-related biomarkers (METS-IR, HOMA-IR, TyG, and TyG-BMI) were positively correlated with the prevalence of CKD. Moreover, TyG-WHtR enhanced CKD and its all-cause mortality prediction. In patients with elevated levels of IR-related indexes, the early detection and intervention of IR may reduce the occurrence of CKD and the prognosis of CKD patients.

Kidney and liver fat accumulation: from imaging to clinical consequences

BACKGROUND

Recent studies indicate that accumulation of adipose tissue in various organs such as liver and kidney may contribute to the pathophysiology of metabolic syndrome. We aim to investigate the association between kidney and liver adipose tissue accumulation, assessed by the magnetic resonance imaging (MRI) proton density fat fraction technique, along with its relation to clinical and biochemical parameters.

METHODS

We included 51 volunteers with phenotypical features of metabolic syndrome (mean age = 34 years, mean body-mass index = 26.4 kg/m2) in our study in which liver and kidney adipose tissue accumulation was assessed via MRI-proton density fat fraction along with multiple other clinical and biochemical parameters such as estimated glomerular filtration rate (eGFR), urine albumin-to-creatinine ratio, serum lipid profile, liver function tests and body-mass index (BMI).

RESULTS

Our results from the univariate linear regression analysis indicate that both the kidney and liver scores were positively correlated with markers such as BMI, urine albumin-to-creatinine ratio, triglycerides (p < 0.001) and negatively correlated with eGFR (p < 0.05). In multivariate analysis, urine albumin-to-creatinine ratio (p < 0.05), triglycerides (p < 0.01), eGFR (p < 0.05) and BMI (p < 0.001) were found to be independently associated with kidney and liver fat accumulation, respectively (R2 = 0.64; R2 = 0.89). There was also a positive correlation between kidney and liver fat accumulation.

CONCLUSION

We have found a significant association between adipose tissue accumulation in liver and kidney and the parameters of metabolic syndrome. Moreover, the presence of a strong association between kidney and liver fat accumulation and kidney function parameters such as urine albumin-to-creatinine ratio and eGFR may be an indicator of the clinical significance of parenchymal fat accumulation.