Background: This study aimed to determine the optimal cutoff values and evaluate the associations of neutrophil to high-density lipoprotein cholesterol ratio (NHR) and lymphocyte to high-density lipoprotein cholesterol ratio (LHR) with metabolic syndrome (MetS), stratified by sex. Methods: A large-scale cross-sectional survey was conducted among 1401 adults from January to April 2018 in six communities in Wanzhai Town, Zhuhai City, on the southern coast of China. Receiver operating characteristics (ROC) analyses and logistic regression analysis were conducted to assess the optimal cutoff and value of NHR and LHR for predicting MetS. Results: Hematological parameters showed the correlation with the occurrence of MetS (red blood cells, hemoglobin, and white blood cells and subtypes). Binomial logistic regression analysis found that LHR (OR: 3.671; 95% CI: 2.385-5.651; p<0.001) and NHR (OR: 1.728; 95% CI: 1.353-2.207; p<0.001) can predict MetS in females, independent of confounding factors. Although LHR (OR: 1.571; 95% CI: 1.001-2.468; p=0.05) and NHR (OR: 1.163; 95% CI: 0.909-1.48; p<0.01) were independent risk factors for MetS in males after adjustment for age, current smoking, current alcohol use, physical activity, educational attainment, waist circumference, systolic pressure, diastolic pressure and hypersensitive C-reactive protein (hs-CRP), when further adjusted for fasting plasma glucose level, LHR and NHR, both lost their independence. ROC curves showed that LHR had the highest AUC for predicting MetS in females and NHR had the highest AUC in males. The cutoff points of LHR and NHR were 1.36 and 2.31 in females, and 1.96 and 3.38 in males. Conclusion: LHR and NHR may become valuable makers and have strong predictive power for predicting MetS, especially in females.

High-density lipoprotein (HDL) particles comprising heterogeneous subclasses of different functions exert anti-inflammatory effects by interacting with immune-response cells. However, the relationship of HDL subclasses with immune-response cells in metabolic unhealth/obesity has not been defined clearly. The purpose of this study was to delineate the relational changes of HDL subclasses with immune cells and inflammatory markers in metabolic unhealth/obesity to understand the role of anti-inflammatory HDL subclasses. A total of 316 participants were classified by metabolic health. HDL subclasses were detected by microfluidic chip electrophoresis. White blood cell (WBC) counts and lymphocytes were assessed using automatic haematology analyser. Levels of high-sensitivity C-reactive protein (hs-CRP) and interleukin 6 (IL-6) were measured. In our study, not only the distribution of HDL subclasses, but also HDL-related structural proteins changed with the deterioration of metabolic disease. Moreover, lymphocytes and inflammation factors significantly gradually increased. The level of HDL2b was negatively associated with WBC, lymphocytes and hs-CRP in multivariable linear regression analysis. In multinomial logistic regression analysis, high levels of HDL3 and low levels of HDL2b increased the probability of having an unfavourable metabolic unhealth/obesity status. We supposed that HDL2b particles may play anti-inflammation by negatively regulating lymphocytes activation. HDL2b may be a therapeutic target for future metabolic disease due to the anti-inflammatory effects.

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Purpose: Diabetic kidney disease (DKD), which is related to inflammation and immune response, is the primary vascular complication of diabetes mellitus and also the leading etiology of end-stage renal disease. Urinary extracellular vesicles (UEVs) are an attractive source for biomarker detection as they involve molecular constituents derived from their parental sections of the nephron. In this study, we aimed to search for a potential biomarker in UEVs for the early diagnosis and prediction of DKD, especially before the emergence of microalbuminuria. Patients and Methods: UEVs were isolated from the urine of healthy subjects, prediabetic, and diabetic patients with varying degrees of kidney damage by ultracentrifugation, and the extracted UEVs were used to measure alpha1-antitrypsin (α1-AT) by Western blot. To explore the function of α1-AT in the inflammatory process leading to DKD, we silenced the expression of α1-AT in renal tubular epithelial cells using cell transfection techniques to assess the differential expression of the inflammatory factors such as MCP-1 and TNF-α using qRT-PCR. Results: There was no expression of α1-AT in the UEVs of either healthy or pre-diabetic subjects. Its expression was significantly increased in the UEVs of diabetic patients with normoalbuminuria (prior to microalbuminuria), which was more sensitive and more stable than other renal indexes to predict DKD. Additionally, the expression of α1-AT in UEVs was gradually upregulated with the aggravation of DKD and the decline of renal function. In vitro, the mRNA expression of MCP-1 and TNF-α was significantly decreased when the generation of α1-AT in tubular epithelial cells was inhibited under high glucose stimulation. Conclusion: Our results suggest that α1-AT derived from UEVs, especially in diabetic patients with normoalbuminuria, might serve as a potential noninvasive biomarker for diagnosis of DKD early in the development of the disease and may predict the future decline of renal function.

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