Association between neutrophil-to-lymphocyte ratio and diabetic kidney disease in type 2 diabetes mellitus patients: a cross-sectional study.

Li X ，Wang L ，Liu M ，Zhou H ，Xu H ... -  《Frontiers in Endocrinology》

Systemic immune-inflammation index is associated with diabetic kidney disease in Type 2 diabetes mellitus patients: Evidence from NHANES 2011-2018.

Diabetic kidney disease (DKD) is the most common chronic kidney disease (CKD) and has the highest prevalence of end-stage kidney disease (ESKD) globally, owing mostly to the rise in Type 2 diabetes mellitus (T2DM) correlated with obesity. Current research suggested that the immune response and inflammation may play a role in the pathophysiology of T2DM. The systemic immune-inflammation index (SII) is a novel and integrated inflammatory biomarker that has not yet been linked to DKD. We aimed to identify the potential relationship between SII and DKD. In the National Health and Nutrition Examination Survey (NHANES) between 2011 and 2018, the current cross-sectional study was conducted among adults with T2DM. SII was calculated as the platelet count × neutrophil count/lymphocyte count. DKD was diagnosed with impaired glomerular filtration rate (< 60 mL/min/1.73 m2 assessed by using the Chronic Kidney Disease Epidemiology Collaboration algorithm), albuminuria (urine albumin to creatinine ratio ≥ 30 mg/g), or both in T2DM patients. To investigate the independent association between SII and DKD, weighted univariate and multivariable logistic regression analyses and subgroup analyses were performed. The study involved 3937 patients in total, of whom 1510 (38.4%) had DKD for the diagnosis. After adjustment for covariates, multivariable logistic regression revealed that a high SII level was associated with increased likelihood of DKD (OR = 1.42, 95% CI: 1.10-1.83, P = 0.01). Subgroup analyses and interaction tests revealed that age, gender, estimated glomerular filtration rate (eGFR), urine albumin-to-creatinine ratio (ACR), body mass index (BMI), hypertension, hyperlipidemia, anti-inflammation therapy (yes or no), metformin use (yes or no), and insulin use (yes or no) had no significant dependence on this positive relationship (all p for interaction >0.05). Our results indicate that the higher SII level is associated with DKD in T2DM patients. The SII could be a cost-effective and straightforward approach to detecting DKD. This needs to be verified in further prospective investigations.

Guo W ，Song Y ，Sun Y ，Du H ，Cai Y ，You Q ，Fu H ，Shao L ... -  《Frontiers in Endocrinology》

Association between systemic inflammation response index and chronic kidney disease: a population-based study.

Our objective was to explore the potential link between systemic inflammation response index (SIRI) and chronic kidney disease (CKD). The data used in this study came from the National Health and Nutrition Examination Survey (NHANES), which gathers data between 1999 and 2020. CKD was diagnosed based on the low estimated glomerular filtration rate (eGFR) of less than 60 mL/min/1.73 m2 or albuminuria (urinary albumin-to-creatinine ratio (ACR) of more than 30 mg/g). Using generalized additive models and weighted multivariable logistic regression, the independent relationships between SIRI and other inflammatory biomarkers (systemic immune-inflammation index (SII), monocyte/high-density lipoprotein ratio (MHR), neutrophil/high-density lipoprotein ratio (NHR), platelet/high-density lipoprotein ratio (PHR), and lymphocyte/high-density lipoprotein ratio (LHR)) with CKD, albuminuria, and low-eGFR were examined. Among the recruited 41,089 participants, males accounted for 49.77% of the total. Low-eGFR, albuminuria, and CKD were prevalent in 8.30%, 12.16%, and 17.68% of people, respectively. SIRI and CKD were shown to be positively correlated in the study (OR = 1.24; 95% CI: 1.19, 1.30). Furthermore, a nonlinear correlation was discovered between SIRI and CKD. SIRI and CKD are both positively correlated on the two sides of the breakpoint (SIRI = 2.04). Moreover, increased SIRI levels were associated with greater prevalences of low-eGFR and albuminuria (albuminuria: OR = 1.27; 95% CI: 1.21, 1.32; low-eGFR: OR = 1.11; 95% CI: 1.05, 1.18). ROC analysis demonstrated that, compared to other inflammatory indices (SII, NHR, LHR, MHR, and PHR), SIRI exhibited superior discriminative ability and accuracy in predicting CKD, albuminuria, and low-eGFR. When predicting CKD, albuminuria, and low-eGFR, SIRI may show up as a superior inflammatory biomarker when compared to other inflammatory biomarkers (SII, NHR, LHR, MHR, and PHR). American adults with elevated levels of SIRI, SII, NHR, MHR, and PHR should be attentive to the potential risks to their kidney health.

Li X ，Cui L ，Xu H 《Frontiers in Endocrinology》

[Association Between the Aggregate Index of Systemic Inflammation and Albuminuria: A Cross-Sectional Study of National Health and Nutrition Examination Survey 2007-2018].

Prior studies have established a connection between albuminuria and various inflammatory reactions, highlighting that an increase in C-reactive protein by 1 mg/L increases the likelihood of albuminuria by 2%. Recent investigations indicate a positive correlation between the systemic immune-inflammation index (SII) and increased urinary protein excretion. In addition, elevated levels of the systemic inflammatory response index (SIRI) also correlate with a higher prevalence of albuminuria. The aggregate index of systemic inflammation (AISI) offers a more comprehensive indicator of inflammation, providing an extensive assessment of systemic inflammatory status compared to SII and SIRI. Yet, the specific relationship between AISI and albuminuria remains unclear. This study aims to explore this association in U.S. adults. We analyzed data from the National Health and Nutrition Examination Survey (NHANES) for 2007-2018, excluding pregnant women and individuals under 18. Cases with missing data on AISI, urinary albumin concentration, and other covariates were also excluded. AISI was computed using the formula: AISI=(platelet count×neutrophil count×monocyte count)/lymphocyte count. Albuminuria was defined as the urinary albumin-to-creatinine ratio exceeding 30 mg/g. Continuous variables were presented in the form of the mean±standard error, and categorical variables in percentages. We utilized weighted t-tests and chi-square tests for baseline comparisons. We applied weighted multivariable logistic regression and generalized additive models (GAM) to explore the association between AISI and albuminuria and to assess potential nonlinear relationships. The study included 32273 participants, with an average age of (46.75±0.24) years old. The cohort comprised 48.73% males and 51.27% females. The prevalence of albuminuria was 9.64%. The average logarithmic value of log2AISI was 7.95±0.01, and were categorized into tertiles as follows: Quartile 1 (Q1) (4.94 to 7.49), Q2 (7.49 to 8.29), and Q3 (8.29 to 10.85). As log2AISI increased, so did the prevalence of hypertension, diabetes, congestive heart failure, and albuminuria, all showing statistically significant increases (P<0.001). Similarly, the use of antihypertensive, lipid-lowering, and hypoglycemic drugs was also more prevalent (P<0.001). Statistically significant differences were observed across the three groups concerning age, race and ethnicity, formal education, alcohol consumption, smoking status, systolic and diastolic blood pressures, body mass index, estimated glomerular filtration rate, HbA1c, alanine aminotransferase, aspartate aminotransferase, albumin, creatinine, uric acid, and high-density lipoprotein cholesterol (P<0.05). However, no significant differences were noted in the total cholesterol or the sex ratios among the groups. The association between log2AISI and albuminuria was assessed using weighted multivariable logistic regression, and the detailed results are presented in Table 2. In model 1, without adjusting for covariates, each unit increase in log2AISI was associated with a 32% increase in the risk of albuminuria (odds ratio [OR]=1.32, 95% confidence interval [CI]: 1.27-1.38, P<0.001). Model 2 was adjusted for age, gender, race, and education level, and showed a similar trend, with each unit increase in log2AISI associated with a 31% increased risk (OR=1.31, 95% CI: 1.26-1.37, P<0.001). Model 3, which was further adjusted for all covariates, revealed that each unit increase in log2AISI was associated with a 20% increase in the risk of albuminuria (OR=1.20, 95% CI: 1.15-1.26, P<0.001). The study also transformed log2AISI from a continuous to a categorical variable for analysis. Compared with Q1, the risk of albuminuria in Q3, after adjusting for all covariates, significantly increased (OR=1.37, 95% CI: 1.22-1.55, P<0.001). Q2 also demonstrated a higher risk compared with Q1 (OR=1.13, 95% CI: 1.06-1.36, P=0.004). The trend test indicated a dose-effect relationship between increasing log2AISI and the rising risk of albuminuria. GAM revealed a nonlinear relationship between log2AISI and albuminuria, with distinct trends noted between sexes. Segmented regression based on turning points showed significant effects among women, although the slope difference between the segments was not significant. In men, a significant threshold effect was observed; below the log2AISI of 7.25, increases in log2AISI did not enhance the risk of albuminuria, but above this threshold, the risk significantly increased. As part of a sensitivity analysis, weighted multivariable logistic regression was performed by changing the outcome variable to macroalbuminuria and adjusting for all covariates. The analysis showed that for every unit increase in log2AISI, the risk of developing macroalbuminuria increased by 31% (OR=1.31, 95% CI: 1.15-1.49, P<0.001). Compared with Q1, the risk of albuminuria in Q3 increased by 69% (OR=1.69, 95% CI: 1.27-2.25, P<0.001), and in Q2, it increased by 40% (OR=1.40, 95% CI: 1.03-1.92, P=0.030). Subgroup analysis and interaction results showed that the positive association between AISI and proteinuria risk was stronger in men than in women. Similarly, the association was stronger in people with hypertension compared with those with normal blood pressure, and higher in overweight people compared with those of normal weight. Furthermore, smokers and drinkers showed a stronger positive association between AISI and the risk of proteinuria than non-smokers and non-drinkers do. These results suggest that sex, blood pressure, body mass index, smoking, and alcohol consumption interact with AISI to influence the risk of proteinuria. There is a robust positive association between AISI and increased risks of albuminuria in US adults. As log2AISI increases, so does the risk of albuminuria. However, further validation of this conclusion through large-scale prospective studies is warranted.

Sun L ，Huo X ，Jia S ，Chen X ... -  《-》

Association between monocyte-to-lymphocyte ratio and prostate cancer in the U.S. population: a population-based study.

Monocyte-to-lymphocyte ratio (MLR) is a convenient and noninvasive inflammatory biomarker, and inflammation has been reported to be associated with prostate cancer (PCa). Our objective was to ascertain any possible correlation between PCa and MLR. We utilized data from the 1999-2020 cycles of the National Health and Nutrition Examination Survey (NHANES) regarding MLR and PCa. The independent associations of MLR and other inflammatory biomarkers (platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), system inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI)) with PCa was investigated using weighted multivariate logistic regression and generalized additive models. Receiver operating characteristic (ROC) curves were conducted to evaluate and contrast their diagnostic capabilities. The analysis we conducted comprised 25,367 persons in total. The mean MLR was 0.31 ± 0.14. The prevalence of PCa was 3.1%. A positive association was found between MLR and PCa (OR = 2.28; 95% CI: 1.44, 3.62). According to the interaction tests, age, body mass index (BMI), hypertension, diabetes, and smoking status did not significantly impact the relationship between MLR and PCa (all p for interaction >0.05). ROC analysis showed that MLR had a stronger discriminative ability and accuracy in predicting PCa than other inflammatory biomarkers (NLR, SII, AISI, PLR, and SIRI). MLR might be better than other inflammatory biomarkers (NLR, SIRI, AISI, PLR, and SII) in predicting PCa. American adults who have elevated levels of MLR, NLR, PLR, SII, and AISI should be aware that they have a greater risk of PCa.

Wang L ，Li X ，Liu M ，Zhou H ，Shao J ... -  《Frontiers in Cell and Developmental Biology》