Cut-off value of total adiponectin for managing risk of developing metabolic syndrome in male Japanese workers

Can biomarkers be used to improve diagnosis and prediction of metabolic syndrome in childhood cancer survivors? A systematic review

Childhood cancer survivors (CCS) are at increased risk to develop metabolic syndrome (MetS), diabetes, and cardiovascular disease. Common criteria underestimate adiposity and possibly underdiagnose MetS, particularly after abdominal radiotherapy. A systematic literature review and meta-analysis on the diagnostic and predictive value of nine newer MetS related biomarkers (adiponectin, leptin, uric acid, hsCRP, TNF-alpha, IL-1, IL-6, apolipoprotein B (apoB), and lipoprotein(a) [lp(a)]) in survivors and adult non-cancer survivors was performed by searching PubMed and Embase. Evidence was summarized with GRADE after risk of bias evaluation (QUADAS-2/QUIPS). Eligible studies on promising biomarkers were pooled. We identified 175 general population and five CCS studies. In the general population, valuable predictive biomarkers are uric acid, adiponectin, hsCRP and apoB (high level of evidence), and leptin (moderate level of evidence). Valuable diagnostic biomarkers are hsCRP, adiponectin, uric acid, and leptin (low, low, moderate, and high level of evidence, respectively). Meta-analysis showed OR for hyperuricemia of 2.94 (age-/sex-adjusted), OR per unit uric acid increase of 1.086 (unadjusted), and AUC for hsCRP of 0.71 (unadjusted). Uric acid, adiponectin, hsCRP, leptin, and apoB can be alternative biomarkers in the screening setting for MetS in survivors, to enhance early identification of those at high risk of subsequent complications.

Inflammatory biomarkers and prediction of insulin resistance in Congolese adults

Several studies have shown that low levels of adiponectin (ADP) and high levels of alpha tumor necrosis factor (NFT) increase the risk or severity of many cardiometabolic diseases associated with insulin resistance. The main objective of this study was to evaluate the association between plasma adipokines and IR measured by HOMA-IR. The secondary objective was to determine the biomarker of the potential inflammation to predict IR in Congolese melanoderm subjects residing in Brazzaville. This cross-sectional study was conducted on 234 apparently healthy participants over the age of 18. Socio-demographic and clinical data were collected. Biological data, including the total ADP and NFT dosage, were measured using the ELISA method. Participants were categorized into two groups according to HOMA-IR ≥ 2.5. Univariate and multivariate logistic regression analyses were conducted to identify risk factors for insulin resistance. An optimized model was obtained after the logistic regression. The analysis of the receptor's operating characteristics (OCR) was performed to determine the optimal threshold value and diagnostic characteristics, as well as the area under the curve (ASC). ADP averages were significantly low (11.49 ± 7.61 ng/mL; P < 0.001) while those of TNF were significantly higher (96.03 ± 44.09 pg/mL) in the HOMA-IR group ≥ 2.5. There was a positive and significant correlation (p < 0.05) between BMI, TT, CRPhs, TNF and HOMA-IR. And a negative and significant correlation was noted between ADP and HOMA-IR (r = - 0.39; P < 0.01). Similarly, a negative and significant correlation (p < 0.01) was noted between BMI, TT, TNF, CRPhs and ADP. The optimal threshold value of the total ADP for predicting IR was 17.52 ng/mL with a sensitivity of 89% [IC 95% (0.83-0.95)], 56% specificity [IC 95% (0.47-0.65)] and a CSA of 0.76 [IC 95% (0.69-0.81)]. After logistic regression, the CSA of the optimized model was 0.84 [IC 95% (0.79-0.89)]. ADP can be used as a highly plausible IR prediction biomarker.

Meta-Analysis of Adiponectin as a Biomarker for the Detection of Metabolic Syndrome

Previous studies revealed the potential significance of circulating adiponectin levels with respect to the diagnosis and prediction of metabolic syndrome, but uncertainty has been noted across different cohorts. Systematic evaluation was performed for diagnostic accuracy and predictivity of adiponectin variation for metabolic syndrome in enrolled studies including 1,248 and 6,020 subjects, respectively. Adiponectin can identify metabolic syndrome with moderate accuracy (area under the curve = 0.81, 95% CI: 0.77–0.84). Heterogeneity analysis revealed that an increasing index of insulin resistance was independently associated with improving the performance of adiponectin upon metabolic syndrome diagnosis (ratio of diagnostic odds ratio = 3.89, 95% CI: 1.13–13.9). In addition, reductions in adiponectin were associated with increasing metabolic syndrome incidence in a linear dose-response manner. The risk of hypoadiponectinemia with metabolic syndrome was especially increased in men (P < 0.05). Further Mendelian randomization analysis identified that the amplified risk could be attributed to increased susceptibility (up to 7%) to insulin resistance compared with women. In conclusion, adiponectin measurement might have potential benefits in the detection of metabolic syndrome. Factors that affect insulin resistance should be considered for adjustment in future assessments.

Uric acid upregulates the adiponectin‑adiponectin receptor 1 pathway in renal proximal tubule epithelial cells

Adiponectin (APN) is a protein hormone that is primarily derived from adipocytes. It can also be secreted by renal cells. Hypoadiponectinemia has been documented in patients with hyperuricemia, however, whether soluble uric acid (SUA) regulates the expression of APN and APN receptor 1 (AdipoR1) in renal proximal tubule epithelial cells (PTECs) remains to be elucidated. The present study investigated the expression of APN and AdipoR1 in cultured PTECs that were exposed to SUA through immunofluorescence and western blot analysis. In addition, Sprague-Dawley rats with oxonic acid-induced hyperuricemia (HUA) with or without febuxostat treatment were employed as an animal model to measure 24 h urine protein, serum creatinine, urea nitrogen, uric acid and homeostasis model assessment of insulin resistance. Renal pathology was evaluated using hematoxylin and eosin and immunohistochemical staining. APN and AdipoR1 expression in the renal cortex were evaluated by western blotting. The results demonstrated that, in PTECs, the expression of APN and AdipoR1 was constant and increased upon SUA exposure. Similar observations were made within the proximal renal tubules of rats, and the oxonic acid-induced increases in APN and AdipoR1 were offset by febuxostat treatment. Furthermore, SUA-treated PTECs exhibited an increase in the expression of NLR family pyrin domain-containing (NLRP) 3, which was dose-dependent. NLRP3 expression was also significantly increased in the renal cortex of HUA rats compared with control and febuxostat-treated rats. In conclusion, SUA enhanced the expression of APN and AdipoR1 in PTECs, which was associated with an increase in NLRP3 expression. The APN-AdipoR1 pathway was demonstrated to have an important role in in vitro and in vivo models of renal proximal tubule inflammatory injury. Therefore, this pathway may be a potential therapy target in urate nephropathy.

Accuracy of plasma interleukin-18 and adiponectin concentrations in predicting metabolic syndrome and cardiometabolic disease risk in middle-age Brazilian men

The aims of this cross-sectional study were to explore the ability of serum interleukin 18 (IL-18) and adiponectin to identify metabolic syndrome (MetS), and to verify their association with an index of central lipid overaccumulation (lipid accumulation product (LAP)) and cardiometabolic risk factors in a population of middle-aged Brazilian men. A group of 218 apparently healthy middle-aged Brazilian men (age, 50.3 ± 4.97 years) underwent anthropometric, clinical, sociodemographic, and standard serum biochemical assessments. LAP was calculated and the study participants were categorized into 3 groups according to serum IL-18 and adiponectin cut-points tertiles to verify the association of these biomarkers with cardiometabolic risk factors. The MetS group had more less active (p = 0.03) and obese (p < 0.01) individuals who exhibited higher IL-18 (p < 0.01) and lower adiponectin (p < 0.01) than did those in the group with no MetS. After adjustments (age, smoking, alcohol consumption, physical activity level, and total body fat), serum IL-18 ≥ 336.4 pg/mL was an independent factor for MetS occurrence and it was directly associated with LAP (≥51.28), central obesity, hypertriglyceridemia, and hypertension (p < 0.05), but not with high-density lipoprotein cholesterol (HDL-C). Serum adiponectin ≥ 7.02 μg/mL was negatively associated with MetS occurrence, LAP, hypertriglyceridemia, and low HDL-C (p < 0.05), but not with central obesity and hypertension. In conclusion, both IL-18 and adiponectin demonstrated the ability to identify MetS in this population, with IL-18 being more accurate. The association of these biomamarkers with LAP and cardiometabolic risk factors highlights its relevance as a diagnostic tool.