Objective:To explore the influence of hypercholesterolemia on the risk of chronic kidney disease (CKD) in the middle-aged and elderly population and the gender differences.Methods:The data came from the "Epidemiological Survey of Chronic Kidney Disease among Adults in Urban Communities in Henan Province". The subjects came from 20 communities in Henan Province, aged ≥45 years old. Groups were based on the quartile of total blood cholesterol level and gender. Multivariate logistic regression and Cochran-Armitage trend test were used to analyze the effect of hypercholesterolemia on the risk of CKD and its gender differences.Results:A total of 4 779 subjects were enrolled into the study, with 1 934 males (40.5%) and 2 845 females (59.5%). The age was (61.3±7.7) years old and the blood cholesterol was (5.0±1.0) mmol/L. The prevalence rates of hypercholesterolemia, albuminuria, and reduced estimated glomerular filtration rate (eGFR) were 10.7%(305/2 845), 6.4%(182/2 845) and 2.8%(79/2 845) in females and 12.7%(245/1 934), 6.9%(133/1 934) and 2.3%(45/1 934) in males respectively. Compared with Q1 group, the prevalence of reduced eGFR in females were higher in Q2 and Q4 groups (both P<0.05). Among males, the prevalence of albuminuria and reduced eGFR increased with increasing blood cholesterol quartile (Cochran-Armitage trend test Z=12.231, 8.862, both P<0.001). Multivariate logistic regression analysis showed that hypercholesterolemia was an independent influencing factor for albuminuria and reduced eGFR ( OR=1.49, 95% CI 1.08-2.07, P=0.016 and OR=1.65, 95% CI 1.03-2.65, P=0.037, respectively). In subgroup analysis of different genders, female hypercholesterolemia was an independent influencing factor for albuminuria and reduced eGFR, while male hypercholesterolemia was not an independent influencing factor ( OR=1.54, 95% CI 0.96~2.46, P=0.075; OR=1.89, 95% CI 0.93-3.89, P=0.082, respectively). Further subgroup analysis based on the interquartile range of serum cholesterol levels found that female hypercholesterolemia was an independent influencing factor for reduced eGFR in the Q2 and Q4 groups ( OR=2.35, 95% CI 1.29-7.61, P=0.003; OR=2.51, 95% CI 1.38-8.39, P=0.001). In males, hypercholesterolemia was an independent influencing factor for albuminuria in the Q2, Q3 and Q4 groups ( OR=1.80, 95% CI 1.01-3.41, P=0.047; OR=1.85, 95% CI 1.02-3.35, P=0.044; OR=2.33, 95% CI 1.33-4.33, P=0.002). Conclusions:Hypercholesterolemia is an independent risk factor for CKD in middle-aged and elderly population, and there are gender differences, which provides a new idea for clinical prevention and control of CKD.

Objective: To investigate the risk factors of clinically diagnosed acute kidney injury (AKI) patients progressing to acute kidney disease (AKD). Methods: The clinical data of AKI patients admitted to the First Affiliated Hospital of Zhengzhou University from January 1, 2018 to December 31, 2018 were retrospectively analyzed. According to the outcome of the patients, AKI patients were divided into non-acute kidney disease (NAKD) group and AKD group. Clinical characteristics and laboratory data of two groups were compared. The risk factors of AKD in patients with AKI were analyzed by logistic regression, and then the receiver operating characteristic curve (ROC) was drawn to evaluate the predictive value of these risk factors. Results: A total of 254 patients with AKI were enrolled, and 186 patients developed AKD with an incidence of 73.2%. The incidences of AKD in stage 1, stage 2 and stage 3 of AKI were 20.0%, 46.7% and 83.5% respectively. Multivariate logistic regression analysis showed increased peak serum creatinine (within 7 days after AKI diagnosis) (OR=2.561, 95% CI 1.584-4.140, P<0.001), proteinuria (OR=2.952, 95% CI 1.162-7.500, P=0.023) and increased intact parathyroid hormone (OR=1.757, 95%CI 1.104-2.797, P=0.017) were independent risk factors for progression to AKD in patients with AKI. The ROC showed that increased peak serum creatinine (within 7 days after AKI diagnosis) was an important predictor of AKD in patients with AKI (AUC=0.798, P<0.001). Conclusion Increased peak serum creatinine (within 7 days after AKI diagnosis), proteinuria and increased intact parathyroid hormone are independent risk factors for progression to AKD in patients with AKI, providing new evidences and ideas for clinical preventions and treatments of AKD.

Objective:To investigate the correlation between Piwi-interacting RNA (piRNA) and diabetic nephropathy (DN).Methods:The differential expression profiles of piRNAs in renal tissues of patients with DN (experimental group) and renal tissues adjacent to tumors of patients with renal tumors (control group) were detected by high-throughput sequencing. The biological function of differentially expressed piRNAs was described by gene ontology and Kyoto encyclopedia of genes and genomes enrichment analysis. Real-time fluorescence quantitative PCR was used to detect the serum expression level of target piRNAs in patients with DN. Spearman correlation analysis was used to analyze the correlation between serum target piRNAs and clinical indexes of patients with DN.Results:The results of high throughput sequencing showed that there were 127 differentially expressed piRNAs between DN group and control group, with screening condition of |log 2(fold changes)|≥2 and P<0.05. Among them, there were 99 up-regulated piRNAs and 28 down-regulated piRNAs. The top 5 up-regulated piRNAs were piRNA-hsa-161686, piRNA-hsa-349255, piRNA-hsa-355720, piRNA-hsa-151229 and piRNA-hsa-154959, respectively. The top 5 down-regulated piRNAs were piRNA-hsa-1929960, piRNA-hsa-174194, piRNA-hsa- 148658, piRNA-hsa-172594 and piRNA-hsa-172421, respectively. The PCR verification results of 3 up-regulated genes and 3 down-regulated genes with low P values and high expression levels showed that serum expression level of piRNA-hsa-77976 was significantly down-regulated in patients with DN ( P=0.028), which was consistent with that of sequencing, while the expression levels of other genes were inconsistent with the sequencing results or had no statistical significance. Bioinformatics analysis results predicted that significantly differentially expressed piRNAs might participate in the regulation of DN through Rap1, Ras, PI3K-Akt and axon guiding pathways. The results of correlation analysis showed that the expression level of piRNA-hsa-77976 was negatively correlated with blood urea nitrogen ( r=-0.584, P=0.028), serum creatinine ( r=-0.637, P=0.014), cystatin C ( r=-0.738, P=0.003) and β2 microglobulin ( r=-0.822, P<0.001), and positively correlated with estimated glomerular filtration rate ( r=0.661, P=0.010). Conclusion:The differential expression of piRNA is closely related to DN, and may be used as a new biomarker for the diagnosis and prognosis of DN.