Clustering Inflammatory Markers with Sociodemographic and Clinical Characteristics of Patients with Diabetes Type 2 Can Support Family Physicians' Clinical Reasoning by Reducing Patients' Complexity

Exploring cytokines dynamics: Uncovering therapeutic concepts for metabolic disorders in postmenopausal women- diabetes, metabolic bone diseases, and non-alcohol fatty liver disease

Menopause is an age-related change that persists for around one-third of a woman's life. Menopause increases the risk of metabolic illnesses such as diabetes, osteoporosis (OP), and nonalcoholic fatty liver disease (NAFLD). Immune mediators (pro-inflammatory cytokines), such as interleukin-1 (IL-1), IL-6, IL-17, transforming growth factor (TGF), and tumor necrosis factor (TNF), exacerbate the challenges of a woman undergoing menopause by causing inflammation and contributing to the development of these metabolic diseases in postmenopausal women. Furthermore, studies have shown that anti-inflammatory cytokines such as interleukin-1 receptor antagonists (IL-1Ra), IL-2, and IL-10 have a double-edged effect on diabetes and OP. Likewise, several interferon (IFN) members are double-edged swords in the OP. Therefore, addressing these immune mediators precisely may be an approach to improving the health of postmenopausal women. Hence, considering the significant changes in these cytokines, the present review focuses on the latest findings concerning the molecular mechanisms by which pro- and anti-inflammatory cytokines (interleukins) impact postmenopausal women with diabetes, OP, and NAFLD. Furthermore, we comprehensively discuss the therapeutic approaches that identify cytokines as therapeutic targets, such as hormonal therapy, physical activities, natural inhibitors (drugs), and others. Finally, this review aims to provide valuable insights into the role of cytokines in postmenopausal women's diabetes, OP, and NAFLD. Deeply investigating the mechanisms and therapeutic interventions involved will address the characteristics of immune mediators (cytokines) and improve the management of these illnesses, thereby enhancing the general quality of life and health of the corresponding populations of women.

Cluster analysis of patient characteristics, treatment modalities, renal impairments, and inflammatory markers in diabetes mellitus

Type 2 diabetes mellitus (T2DM) is caused by an interplay of various factors where chronic hyperglycemia and inflammation have central role in its onset and progression. Identifying patient groups with increased inflammation in order to provide more personalized approach has become crucial. We hypothesized that grouping patients into clusters according to their clinical characteristics could identify distinct unique profiles that were previously invisible to the clinical eye. A cross-sectional record-based study was performed at the Primary Health Care Center Podgorica, Montenegro, on 424 T2DM patients aged between 30 and 85. Using hierarchical clustering patients were grouped into four distinct clusters based on 12 clinical variables, including glycemic and other relevant metabolic indicators. Inflammation was assessed through neutrophil-to-lymphocyte (NLR) and platelet to lymphocyte ratio (PLR). Cluster 3 which featured the oldest patients with the longest T2DM duration, highest hypertension rate, poor glycemic control and significant GFR impairment had the highest levels of inflammatory markers. Cluster 4 which featured the youngest patients, with the best glycemic control, the highest GFR had the lowest prevalence of coronary disease, but not the lowest levels of inflammatory markers. Identifying these clusters offers physicians opportunity for more personalized T2DM management, potentially mitigating its associated complications.

Profiling of patients with type 2 diabetes based on medication adherence data

Introduction

Type 2 diabetes mellitus (T2DM) is a complex, chronic disease affecting multiple organs with varying symptoms and comorbidities. Profiling patients helps identify those with unfavorable disease progression, allowing for tailored therapy and addressing special needs. This study aims to uncover different T2DM profiles based on medication intake records and laboratory measurements, with a focus on how individuals with diabetes move through disease phases.

Methods

We use medical records from databases of the last 20 years from the Department of Endocrinology and Diabetology of the University Medical Center in Maribor. Using the standard ATC medication classification system, we created a patient-specific drug profile, created using advanced natural language processing methods combined with data mining and hierarchical clustering.

Results

Our results show a well-structured profile distribution characterizing different age groups of individuals with diabetes. Interestingly, only two main profiles characterize the early 40-50 age group, and the same is true for the last 80+ age group. One of these profiles includes individuals with diabetes with very low use of various medications, while the other profile includes individuals with diabetes with much higher use. The number in both groups is reciprocal. Conversely, the middle-aged groups are characterized by several distinct profiles with a wide range of medications that are associated with the distinct concomitant complications of T2DM. It is intuitive that the number of profiles increases in the later age groups, but it is not obvious why it is reduced later in the 80+ age group. In this context, further studies are needed to evaluate the contributions of a range of factors, such as drug development, drug adoption, and the impact of mortality associated with all T2DM-related diseases, which characterize these middle-aged groups, particularly those aged 55-75.

Conclusion

Our approach aligns with existing studies and can be widely implemented without complex or expensive analyses. Treatment and drug use data are readily available in healthcare facilities worldwide, allowing for profiling insights into individuals with diabetes. Integrating data from other departments, such as cardiology and renal disease, may provide a more sophisticated understanding of T2DM patient profiles.

A Critical Appraisal of the Diagnostic and Prognostic Utility of the Anti-Inflammatory Marker IL-37 in a Clinical Setting: A Case Study of Patients with Diabetes Type 2

BACKGROUND

The role of the cytokine interleukin-37 (IL-37) has been recognized in reversing inflammation-mediated metabolic costs. The aim was to evaluate the clinical utility of this cytokine as a diagnostic and prognostic marker in patients with type 2 diabetes (T2D).

METHODS

We included 170 older (median: 66 years) individuals with T2D (females: 95) and classified as primary care attenders to assess the association of factors that describe patients with plasma IL-37 levels (expressed as quartiles) using multinomial regression models. We determined the diagnostic ability of IL-37 cut-offs to identify diabetes-related complications or patient subgroups by using Receiver Operating Characteristic analysis (c-statistics).

RESULTS

Frailty status was shown to have a suppressive effect on IL-37 circulating levels and a major modifying effect on associations of metabolic and inflammatory factors with IL-37, including the effects of treatments. Situations in which IL-37 reached a clinically significant discriminating ability included the model of IL-37 and C-Reactive Protein in differentiating among diabetic patients with low-normal/high BMI ((<25/≥25 kg/m2), and the model of IL-37 and Thyroid Stimulating Hormone in discriminating between women with/without metabolic syndrome.

CONCLUSIONS

The study has revealed limitations in using classical approaches in determining the diagnostic and prognostic utility of the cytokine IL-37 in patients with T2D and lain a foundation for new methodology approaches.

Cross-Talk between the Cytokine IL-37 and Thyroid Hormones in Modulating Chronic Inflammation Associated with Target Organ Damage in Age-Related Metabolic and Vascular Conditions

Chronic inflammation is considered to be the main mechanism contributing to the development of age-related metabolic and vascular conditions. The phases of chronic inflammation that mediate the progression of target organ damage in these conditions are poorly known, however. In particular, there is a paucity of data on the link between chronic inflammation and metabolic disorders. Based on some of our own results and recent developments in our understanding of age-related inflammation as a whole-body response, we discuss the hypothesis that cross-talk between the cytokine IL-37 and thyroid hormones could be the key regulatory mechanism that justifies the metabolic effects of chronic tissue-related inflammation. The cytokine IL-37 is emerging as a strong natural suppressor of the chronic innate immune response. The effect of this cytokine has been identified in reversing metabolic costs of chronic inflammation. Thyroid hormones are known to regulate energy metabolism. There is a close link between thyroid function and inflammation in elderly individuals. Nonlinear associations between IL-37 and thyroid hormones, considered within the wider clinical context, can improve our understanding of the phases of chronic inflammation that are associated with target organ damage in age-related metabolic and vascular conditions.