In obesity, elevated fat mass and ectopic fat accumulation are associated with changes in adipokine secretion, which may link obesity to inflammation and the development of insulin resistance. However, relationships among individual adipokines and between adipokines and parameters of obesity, glucose metabolism or inflammation are largely unknown. Serum concentrations of 20 adipokines were measured in 141 Caucasian obese men (n = 67) and women (n = 74) with a wide range of body weight, glycemia and insulin sensitivity. Unbiased, distance-based hierarchical cluster analyses were performed to recognize patterns among adipokines and their relationship with parameters of obesity, glucose metabolism, insulin sensitivity and inflammation. We identified two major adipokine clusters related to either (1) body fat mass and inflammation (leptin, ANGPTL3, DLL1, chemerin, Nampt, resistin) or insulin sensitivity/hyperglycemia, and lipid metabolism (vaspin, clusterin, glypican 4, progranulin, ANGPTL6, GPX3, RBP4, DLK1, SFRP5, BMP7, adiponectin, CTRP3 and 5, omentin). In addition, we found distinct adipokine clusters in subgroups of patients with or without type 2 diabetes (T2D). Logistic regression analyses revealed ANGPTL6, DLK1, Nampt and progranulin as strongest adipokine correlates of T2D in obese individuals. The panel of 20 adipokines predicted T2D compared to a combination of HbA1c, HOMA-IR and fasting plasma glucose with lower sensitivity (78% versus 91%) and specificity (76% versus 94%). Therefore, adipokine patterns may currently not be clinically useful for the diagnosis of metabolic diseases. Whether adipokine patterns are relevant for the predictive assessment of intervention outcomes needs to be further investigated.

Obesity and insulin resistance are hallmarks of the metabolic syndrome, which is associated with low-grade chronic inflammation. Clusterin/apolipoprotein J is an abundant plasma chaperone protein that has recently been suggested as a potential biomarker that reflects the inflammatory process in Alzheimer's disease. In the present study, we investigated anthropometric and clinical factors affecting the plasma levels of clusterin in healthy Korean subjects. We measured fasting plasma clusterin levels in healthy Korean adults (111 men and 93 women) using ELISA kit. We analyzed the relationship between plasma clusterin concentrations and anthropometric and clinical parameters. Fasting plasma clusterin concentrations were higher in overweight and obese subjects than in lean subjects. Correlation analysis revealed that the plasma clusterin levels were positively associated with indices of obesity such as body mass index (BMI), waist circumference and waist-hip ratio and markers of systemic inflammation such as high sensitivity C-reactive protein (hsCRP), uric acid, ferritin and retinol binding protein-4. Multiple linear regression analysis showed that sex, BMI and hsCRP were independent determinants of plasma clusterin levels. Furthermore, plasma clusterin levels showed an upward trend with increasing numbers of metabolic syndrome components. These findings suggest that fasting plasma clusterin levels correlate with the parameters of adiposity and systemic inflammation in healthy adults. Therefore, the circulating clusterin level may be a surrogate marker for obesity-associated systemic inflammation.

The aims of this study were to investigate whether circulating irisin is associated with favorable metabolic parameters and how the association differs according to body composition in humans. A total of 424 subjects (233 men and 191 women), aged 23–73 years (mean age 47.1 years), were enrolled from the Seoul Metro City Diabetes Prevention Program. Body composition was determined using an impedance body composition analyzer, and serum irisin level was measured using a commercial kit. Serum irisin was correlated with favorable metabolic parameters including less obese, lower blood pressure and glucose levels and healthy lipid parameters. The skeletal muscle mass to visceral fat area ratio (SVR) was positively correlated with the serum irisin concentration (r = 0.10, P = 0.04). When the study subjects were divided into tertiles according to their SVR, serum irisin was correlated with favorable metabolic phenotypes in those subjects in the upper tertile. However, there were no such correlations in the lower tertile. In addition, serum irisin was inversely related to pre-diabetes/type 2 diabetes (T2D) independent of other risk factor for T2D and insulin resistance [OR (95 % CI); 0.66 (0.49–0.90), P = 0.009]. The compositions of skeletal muscle and visceral fat play key roles in the association between circulating irisin and a patient’s metabolic phenotype.

Ovarian cancer is the leading cause of gynecological cancer-related mortality. The anticancer effect of eupatilin, a family of flavonoids, is known in many cancer types, but it is unclear what mechanism it plays in ovarian cancer. In this study, eupatilin promoted cell death of ovarian cancer cells by activating caspases, cell cycle arrest, reactive oxygen species (ROS) generation, calcium influx, disruption of the endoplasmic reticulum (ER)–mitochondria axis with SERPINB11 inhibition, and downregulation of phosphoinositide 3-kinase (PI3K) and mitogen activated protein kinase (MAPK) pathways. Additionally, eupatilin-reduced SERPINB11 expression enhanced the effect of conventional chemotherapeutic agents against ovarian cancer cell progression. Cotreatment with siSERPINB11 and eupatilin increased calcium-ion-dependent apoptotic activity in ovarian cancer cells. Although there were no significant toxic effects of eupatilin on embryos, eupatilin completely inhibited tumorigenesis in a zebrafish xenograft model. In addition, eupatilin suppressed angiogenesis in zebrafish transgenic models. Collectively, downregulating SERPINB11 with eupatilin against cancer progression may improve therapeutic activity.

Objective: Serum concentrations of retinol-binding protein 4 (RBP4) are elevated in type 2 diabetes and associated with the severity of insulin resistance; however, there are few data about the relationship between urinary RBP4 levels and metabolic parameters. We assessed urinary RBP4 as a new biomarker by establishing its relationship with clinical parameters associated with insulin resistance and urinary albumin excretion.Design and methods: We measured RBP4 in the serum and urine of 689 subjects with diverse glucose tolerance status. We also evaluated the relationship between urinary RBP4 and cardiometabolic risk factors, including insulin resistance, high-sensitivity C-reactive protein (hsCRP), arterial stiffness, and microalbuminuria.Results: Urinary RBP4 levels were higher in insulin-resistant subjects with prediabetes or type 2 diabetes than in subjects with normal glucose tolerance (NGT) (type 2 diabetes>prediabetes>NGT; allP<0.001). Urinary RBP4 correlated strongly with homeostasis model assessments of insulin resistance (HOMA-IR), fasting glucose, triglycerides, blood pressure, hsCRP, arterial stiffness, estimated glomerular filtration rate, and urinary albumin-to-creatinine ratio (allP<0.01). HOMA-IR and arterial stiffness were found to be independent determinants of urinary RBP4 concentration. Furthermore, urinary RBP4 was highly predictive of microalbuminuria (odds ratio 2.6, 95% CI 1.6–4.2), even after adjustment for other metabolic parameters. The area under the ROC curve for urinary RBP4 to detect the presence of microalbuminuria was 0.80±0.02 (95% CI 0.76–0.84) and the cut-off value was 157.01 μg/gCr.Conclusions: Urinary RBP4 concentrations were elevated in patients with dysregulation of glucose metabolism and were related to various cardiometabolic risk factors including insulin resistance, inflammation, and microalbuminuria.

Homeostatic bone remodeling is vital to maintain healthy bone tissue. Although the receptor activator of nuclear factor κB ligand (RANKL)/RANK axis is considered the master regulator of osteoclastogenesis, the underlying mechanisms including cell fusion remain incompletely defined. Here, we introduce a new axis in the formation of MNCs via RANK signaling: the progranulin (PGRN)/PGRN-induced receptor-like gene during osteoclastogenesis (PIRO) axis. When mouse bone marrow-derived macrophages (MBMMs) were stimulated with PGRN in the presence of RANKL, explosive OC formation was observed. PGRN knockdown experiments suggested that endogenous PGRN is an essential component of the RANKL/RANK axis. Our efforts for identifying genes that are induced by PGRN unveiled a remarkably induced (twenty fold) gene named PIRO. Substantial PGRN and PIRO expression was detected 2 days and 3 days, respectively, suggesting their sequential induction. PIRO was predicted to be a five transmembrane domain-containing receptor-like molecule. The tissue distribution of PGRN and PIRO mRNA expression suggested bone marrow cells are the most suitable niche. Mouse and human PIRO are part of a multigene family. Knockdown experiments suggested that PIRO is a direct target for the formation of MNCs by PGRN. PGRN levels were also substantially higher in ovariectomized (OVX) mice than in sham control (SH) mice. These observations suggest that PGRN and PIRO form a new regulatory axis in osteoclastogenesis that is included in RANK signaling in cell fusion and OC resorption of osteoclastogenesis, which may offer a novel therapeutic modality for osteoporosis and other bone-associated diseases.