The relationship between adipokines and the onset of type 2 diabetes in middle-aged men: The PRIME study

Plasma Lipocalin-2 and Adiponectin are Affected by Obesity Rather Than Type 2 Diabetes Mellitus per se

PURPOSE

Changes in plasma adipocytokines and inflammatory markers in type 2 DM remain controversial as to whether they are due to obesity or directly associated with the diabetic state. Our objective was to study the effect of obesity and diabetes on plasma lipocalin-2 (LCN2), adiponectin, and interleukin-1β (IL-1β) by comparing their levels in non-diabetic obese subjects and non-obese type 2 DM patients, as well as determining the association of these adipocytokines with metabolic syndrome factors and diabetic parameters.

PATIENTS AND METHODS

In this study, 85 Yemeni male volunteers aged 30-60 years old were enrolled, 25 of whom were healthy subjects with BMI < 25 kg/m² served as control; 30 non-diabetic obese subjects (BMI ≥ 30 kg/m² and FBG < 6.1 mmol/l); and 30 non-obese type 2 DM patients (BMI < 25 kg/m² and FBG > 7 mmol/l).

RESULTS

Lipocalin-2 and adiponectin were significantly (p = 0.043 and p = 0.034) lower in non-diabetic obese subjects by 16.2% and 29.7% with respect to control group, with no effect in the non-obese type 2 DM patients. Moreover, LCN2 was significantly (p = 0.04) lower in the non-diabetic obese subjects by 15.8% as compared with the non-obese type 2 DM patients, with no significant difference in adiponectin levels. In contrast, serum IL-1β was significantly (p = 0.001 and p = 0.003) higher in both non-diabetic obese subjects and the non-obese type 2 DM patients by 76.5% and 67.7% as compared to control group. The significant decrease in both LCN2 and adiponectin and the significant increase in IL-1β in the non-diabetic obese subjects disappeared upon adjustment for waist circumference (WC). In contrast, the significant increase in IL-1β in the non-obese Type 2 DM patients was not affected upon adjustment for WC.

CONCLUSION

Plasma LCN2 and adiponectin were not affected by diabetes per se, suggesting that the observed changes in LCN2 and adiponectin in type 2 DM may be due to obesity rather than the diabetic state, whereas IL-1β levels were affected by both obesity and diabetes.

Temporal Leptin to Determine Cardiovascular and Metabolic Fate throughout the Life

Leptin links peripheral adiposity and the central nervous system (CNS) to regulate cardiometabolic physiology. Within the CNS, leptin receptor-expressing cells are a counterpart to circulating leptin, and leptin receptor-mediated neural networks modulate the output of neuroendocrine and sympathetic nervous activity to balance cardiometabolic homeostasis. Therefore, disrupted CNS leptin signaling is directly implicated in the development of metabolic diseases, such as hypertension, obesity, and type 2 diabetes. Independently, maternal leptin also plays a central role in the development and growth of the infant during gestation. Accumulating evidence points to the dynamic maternal leptin environment as a predictor of cardiometabolic fate in their offspring as it is directly associated with infant metabolic parameters at birth. In postnatal life, the degree of serum leptin is representative of the level of body adiposity/weight, a driving factor for cardiometabolic alterations, and therefore, the levels of blood leptin through the CNS mechanism, in a large part, are a strong determinant for future cardiometabolic fate. The current review focuses on highlighting and discussing recent updates for temporal dissection of leptin-associated programing of future cardiometabolic fate throughout the entire life.

New Insights into Adipokines as Potential Biomarkers for Type-2 Diabetes Mellitus

A large number of studies have been focused on investigating serum biomarkers associated with risk or diagnosis of type-2 diabetes mellitus. In the last decade, promising studies have shown that circulating levels of adipokines could be used as a relevant biomarker for diabetes mellitus progression as well as therapeutic future targets. Here, we discuss the possible use of recently described adipokines, including apelin, omentin-1, resistin, FGF-21, neuregulin-4 and visfatin, as early biomarkers for diabetes. In addition, we also include recent findings of other well known adipokines such as leptin and adiponectin. In conclusion, further studies are needed to clarify the pathophysiological significance and clinical value of these biological factors as potential biomarkers in type-2 diabetes and related dysfunctions.

Secure Communication through MultiAgent System-Based Diabetes Diagnosing and Classification

The main objective of the research is to provide a multi-agent data mining system for diagnosing diabetes. Here, we use multi-agents for diagnosing diabetes such as user agent, connection agent, updation agent, and security agent, in which each agent performs their own task under the coordination of the connection agent. For secure communication, the user symptoms are encrypted with the help of Elliptic Curve Cryptography and Optimal Advanced Encryption Standard. In Optimal Advanced Encryption Standard algorithm, the key values are optimally selected by means of differential evaluation algorithm. After receiving the encrypted data, the suggested method needs to find the diabetes level of the user through multiple kernel support vector machine algorithm. Based on that, the agent prescribes the drugs for the corresponding user. The performance of the proposed technique is evaluated by classification accuracy, sensitivity, specificity, precision, recall, execution time and memory value. The proposed method will be implemented in JAVA platform.

Plasma adiponectin levels and type 2 diabetes risk: a nested case-control study in a Chinese population and an updated meta-analysis

Results from previous prospective studies assessing the relation between adiponectin and type 2 diabetes (T2D) were not entirely consistent, and evidence in Chinese population is scarce. Moreover, the last meta-analysis did not examine the impact of metabolic variables on the adiponectin-T2D association. Therefore, we prospectively evaluated the adiponectin-T2D association among 571 T2D cases and 571 age-sex-matched controls nested within the Singapore Chinese Health Study (SCHS). Furthermore, we conducted an updated meta-analysis by searching prospective studies on Pubmed till September 2016. In the SCHS, the odds ratio of T2D, comparing the highest versus lowest tertile of adiponectin levels, was 0.30 (95% confidence interval: 0.17, 0.55) in the fully-adjusted model. The relation was stronger among heavier participants (body mass index ≥23 kg/m²) compared to their leaner counterparts (P for interaction = 0.041). In a meta-analysis of 34 prospective studies, the pooled relative risk was 0.53 (95% confidence interval: 0.47, 0.61) comparing the extreme tertiles of adiponectin with moderate heterogeneity (I² = 48.7%, P = 0.001). The adiponectin-T2D association remained unchanged after adjusting for inflammation and dyslipidemia markers, but substantially attenuated with adjustment for insulin sensitivity and/or glycaemia markers. Overall evidence indicates that higher adiponectin levels are associated with decreased T2D risk in Chinese and other populations.