TWEAK and monocyte to HDL ratio as a predictor of metabolic syndrome in patients with polycystic ovary syndrome

Association of white blood cell parameters with metabolic syndrome: A systematic review and meta-analysis of 168,000 patients

BACKGROUND

Leukocyte parameters are predicted to be affected in patients with metabolic syndrome (MetS). We conducted a systematic review and meta-analysis to study the association between white blood cell parameters (WBC) in people with and without MetS.

METHODS

PubMed, EMBASE, Scopus and Cochrane Library databases were searched according to the study protocol. The standardized mean difference (SMD) and 95% confidence intervals (CI) of leukocyte markers between individuals with and without MetS were pooled using an inverse variance model. Additionally, a subgroup analysis by sex was performed where possible. Methodological quality assessment was conducted using the Newcastle-Ottawa scale (NOS) for observational studies and the Cochrane Risk of Bias tool 2.0 for Randomized Controlled Trials (RCTs).

RESULTS

Of 6068 articles identified, 63 were eligible for the study. Compared to controls, individuals with MetS showed significantly higher concentrations of total leukocyte count (SMD [95% CI]: 0.60 [0.55-0.65]; P < .00001; I2 = 100%), neutrophil counts (0.32 [0.28-0.37]; P < .00001; I2 = 99%), lymphocyte counts (0.15 [0.07-0.23]; P = .0004; I2 = 100%), basophil counts (0.01 [0.00-0.02]; P = .02; I2 = 98%), monocyte counts (0.05 [0.02-0.09]; P = .003; I2 = 99%), and neutrophil-to-lymphocyte ratio (0.24 [0.15-0.33]; P < .00001; I2 = 98%). There were no significant differences in the eosinophil count (0.02 [-0.01 to 0.05]; P = .19; I2 = 96%) and monocyte-to-lymphocyte ratio (0.06 [-0.05 to 0.17]; P = .27; I2 = 100%) between patients with and without MetS, however, the lymphocyte-to-monocyte ratio (0.52 [-0.81 to -0.23]; P = .0005; I2 = 52%) tended to be significantly lower in patients with MetS.

CONCLUSION

Biomarkers such as total leukocyte count, neutrophil count, lymphocyte count, basophil count, monocyte count and neutrophil-to-lymphocyte ratio are associated with higher levels in patients in MetS and thus can potentially be used for early detection of MetS.

Healthy lifestyles, systemic inflammation and breast cancer risk: a mediation analysis

BACKGROUND

Despite the known association between healthy lifestyles and reduced risk of breast cancer, it remains unclear whether systemic inflammation, as a consequence of unhealthy lifestyles, may mediate the association.

METHODS

A cohort study of 259,435 female participants in the UK Biobank was conducted to estimate hazard ratio (HR) for breast cancer according to 9 inflammation markers using Cox regression models. We further estimated the percentage of total association between healthy lifestyle index (HLI) and breast cancer that is mediated by these inflammation markers.

RESULTS

During 2,738,705 person-years of follow-up, 8,889 cases of breast cancer were diagnosed among 259,435 women in the UK Biobank cohort. Higher level of C-reactive protein (CRP), systemic immune-inflammation index (SII), CRP-to-albumin Ratio (CAR), CRP-to-lymphocyte Ratio (CLR), monocyte-to-HDL-c ratio (MHR), and neutrophil-to-HDL-c ratio (NHR) were associated with increased breast cancer risk, while a higher lymphocyte-to-monocyte ratio (LMR) was associated with a lower risk. The inverse association between HLI and breast cancer was weakly mediated by CRP (8.5%), SII (1.71%), CAR (8.66%), CLR (6.91%), MHR (6.27%), and NHR (7.33%). When considering individual lifestyle factors, CRP and CAR each mediated 16.58% and 17.20%, respectively, of the associations between diet score and breast cancer risk, while the proportion mediated for physical activity and breast cancer were 12.13% and 11.48%, respectively. Furthermore, MHR was found to mediate 13.84% and 12.01% of the associations between BMI, waist circumference, and breast cancer.

CONCLUSION

The association of HLI and breast cancer is weakly mediated by the level of inflammation, particularly by CRP and CAR. Systemic inflammatory status may be an intermediate in the biological pathway of breast cancer development.

Monocyte to High-Density lipoprotein and Apolipoprotein A1 Ratios: Novel Indicators for Metabolic Syndrome in Chinese Newly Diagnosed Type 2 Diabetes

OBJECTIVE

Increasing evidence highlighted that chronic inflammation involved in the development of metabolic syndrome (MetS) and Type 2 diabetes mellitus (T2DM). This prospective study was aimed to assess the association between MetS and novel pro-inflammatory indicators like monocyte-to-high-density lipoprotein and monocyte-to-apolipoprotein A1 ratios (MHR and MAR) in Chinese newly diagnosed T2DM.

METHOD

A total of 605 Chinese newly diagnosed T2DM with complete and available data were enrolled in this study. Demographic and anthropometric information were collected. Laboratory assessments were determined by standard methods. MetS was based on the Chinese Diabetes Society definition. Multiple binomial logistic regression model was used to estimate the independent variables of MHR and MAR for MetS. Receiver operating characteristic (ROC) curve was conducted to assess the optimal cutoff value of MHR and MAR in identifying MetS.

RESULTS

Overall, the prevalence of MetS was 60.2%. The correlation analysis showed that MHR and MAR were closely correlated with metabolic risk factors like body mass index, waist circumference, triglycerides, high-density lipoprotein cholesterol, systolic blood pressure, diastolic blood pressure, uric acid, and insulin resistance. MHR and MAR were also significantly associated with higher odds of MetS after adjustment for other confounders, the odds ratios (ORs) (95%CI) were 1.50 (1.14-1.97) and 2.26(1.79-2.87) respectively. Furthermore, MHR and MAR were also seemed to have higher area under the curve (AUC) for MetS than ApoA1 and monocyte alone from the ROC curve analysis (P < 0.05). The AUCs of MHR and MAR identifying MetS were 0.804 (95% CI: 0.768-0.839) and 0.840 (95% CI: 0.806-0.873) respectively (P < 0.001). The optimal cutoff values of MHR and MAR were 3.57 × 10⁸/mmol (sensitivity: 76.1%, specificity: 73.4%) and 3.95 × 10⁸/g (sensitivity: 79.7%, specificity: 84.6%), respectively.

CONCLUSIONS

MHR and MAR were significantly associated with MetS. These two novel pro-inflammatory indicators may be useful markers for MetS in Chinese newly diagnosed T2DM.

Monocyte to high-density lipoprotein cholesterol ratio as an independent risk factor for papillary thyroid carcinoma

Background

Papillary thyroid carcinoma (PTC) is considered to be an inflammatory disease. This study aimed to investigate the association of monocyte to high‐density lipoprotein cholesterol ratio (MHR) with PTC.

Methods

Clinical parameters from 300 patients with PTC and 552 patients with benign thyroid nodule were compared. Serum renal function and liver enzymes, fasting plasma glucose, lipid profile, and blood cell count were measured.

Results

Patients with PTC had a higher MONO (p < 0.001) and MHR (p < 0.001). There was a step‐wise increase in the prevalence of PTC (p = 0.003) with the tertile of MHR. Logistic regression analysis revealed that MHR could be considered an independent risk factor (p < 0.001) in the case‐control study and the cohort study. Pearson correlation analysis and simple linear regression analysis indicated that MHR was positively associated with neutrophil (NEU) and lymphocyte (LYM) count as well as neutrophil‐to‐lymphocyte ratio (NLR). Area under the curve (AUC) was 0.711. The optimal cutoff of MHR was 0.33 × 10⁹/mmol.

Conclusion

This study identifies novel evidence that patients with PTC have a higher MHR. MHR is an independent risk factor for PTC. These findings support the application of MHR to predict, diagnose, and evaluate the occurrence of PTC.

Effect of Central Obesity and Hyperandrogenism on Selected Inflammatory Markers in Patients with PCOS: A WHtR-Matched Case-Control Study

White blood cell counts (WBC), lymphocyte-to-monocyte ratio (LMR), and monocyte-to-high-density lipoprotein cholesterol ratio (MHR) are used as chronic inflammation markers. Polycystic ovary syndrome (PCOS) is a constellation of systemic inflammation linked to central obesity (CO), hyperandrogenism, insulin resistance, and metabolic syndrome. The waist-to-height ratio (WHtR) constitutes a highest-concordance anthropometric CO measure. This study aims to access WBC, LMR, and MHR in PCOS and healthy subjects, with or without CO. Establishing relationships between complete blood count parameters, high-sensitivity C-reactive protein (hsCRP), and hormonal, lipid and glucose metabolism in PCOS. To do this, WBC, LMR, MHR, hsCRP, anthropometric, metabolic, and hormonal data were analyzed from 395 women of reproductive age, with and without, PCOS. Correlations between MHR, and dysmetabolism, hyperandrogenism, and inflammation variables were examined. No differences were found in WBC, LMR, MHR, and hsCRP between PCOS and controls (p > 0.05). PCOS subjects with CO had higher hsCRP, MHR, and WBC, and lower LMR vs. those without CO (p < 0.05). WBC and MHR were also higher in controls with CO vs. without CO (p < 0.001). MHR correlated with anthropometric, metabolic, and endocrine parameters in PCOS. WHtR appeared to strongly predict MHR in PCOS. We conclude that PCOS does not independently influence WBC or MHR when matched for CO. CO and dysmetabolism may modify MHR in PCOS and control groups.

Inflammatory Markers Predicting Pathological Complete Response in Cases with Breast Cancer Treated by Neoadjuvant Chemotherapy

Objective

Response to neoadjuvant chemotherapy (NAC) is predictive for survival times in some patients with breast cancer (BC). The aim of this study is to explore the predictive value of some inflammatory markers including neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), monocyte-to-high density lipoprotein ratio (MHR) and prognostic nutritional index (PNI) in cases with BC treated with NAC.

Materials and Methods

One hundred and ten patients with BC treated with NAC were included in the study. Measurements for NLR, dNLR, MHR and PNI were calculated with available formulas. The value of NLR, dNLR, MHR and PNI in predicting pCR to NAC in BC was analyzed using receiver operating characteristic (ROC) curve analysis. All analyses were performed using the SPSS statistical software package (SPSS statistics 21.0).

Results

Mean NLR values were 2.2±0.8 vs. 2.6±1.3 for pCR (+) and pCR (-) groups (p=0.603). Mean dNLR values were 1.5±0.5 vs. 1.9±0.8 for pCR (+) and pCR (-) groups, respectively and this was statistically significant (p=0.022). Mean MHR values were 15.4±17.2 vs. 13.2±10.1 for pCR (+) and pCR (-) groups (p=0.406). Mean PNI values were 52±5.1 vs. 49±5.8 for pCR (+) and pCR (-) groups, and this was statistically significant (p=0.015). In multiple logistic regression analysis PNI was found to be independent factor for pCR.

Conclusion

In this study pre-treatment dNLR and PNI were found to be predictive for pCR while NLR and MHR were not found to be associated with pCR. PNI and dNLR are simple but useful biomarkers predicting response to NAC.