Human SHC-transforming protein 1 and its isoforms p66shc: A novel marker for prediabetes

Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers

Type II diabetes mellitus (T2DM) is a rising global health burden due to its rapidly increasing prevalence worldwide, and can result in serious complications. Therefore, it is of utmost importance to identify individuals at risk as early as possible to avoid long-term T2DM complications. In this study, we developed an interpretable machine learning model leveraging baseline levels of biomarkers of oxidative stress (OS), inflammation, and mitochondrial dysfunction (MD) for identifying individuals at risk of developing T2DM. In particular, Isolation Forest (iForest) was applied as an anomaly detection algorithm to address class imbalance. iForest was trained on the control group data to detect cases of high risk for T2DM development as outliers. Two iForest models were trained and evaluated through ten-fold cross-validation, the first on traditional biomarkers (BMI, blood glucose levels (BGL) and triglycerides) alone and the second including the additional aforementioned biomarkers. The second model outperformed the first across all evaluation metrics, particularly for F1 score and recall, which were increased from 0.61 ± 0.05 to 0.81 ± 0.05 and 0.57 ± 0.06 to 0.81 ± 0.08, respectively. The feature importance scores identified a novel combination of biomarkers, including interleukin-10 (IL-10), 8-isoprostane, humanin (HN), and oxidized glutathione (GSSG), which were revealed to be more influential than the traditional biomarkers in the outcome prediction. These results reveal a promising method for simultaneously predicting and understanding the risk of T2DM development and suggest possible pharmacological intervention to address inflammation and OS early in disease progression.

Comparative Analysis of Biomarkers in Type 2 Diabetes Patients With and Without Comorbidities: Insights Into the Role of Hypertension and Cardiovascular Disease

Background

Type 2 diabetes mellitus (T2DM) are 90% of diabetes cases, and its prevalence and incidence, including comorbidities, are rising worldwide. Clinically, diabetes and associated comorbidities are identified by biochemical and physical characteristics including glycemia, glycated hemoglobin (HbA1c), and tests for cardiovascular, eye and kidney disease.

Objectives

Diabetes may have a common etiology based on inflammation and oxidative stress that may provide additional information about disease progression and treatment options. Thus, identifying high-risk individuals can delay or prevent diabetes and its complications.

Design

In patients with or without hypertension and cardiovascular disease, as part of progression from no diabetes to T2DM, this research studied the changes in biomarkers between control and prediabetes, prediabetes to T2DM, and control to T2DM, and classified patients based on first-attendance data. Control patients and patients with hypertension, cardiovascular, and with both hypertension and cardiovascular diseases are 156, 148, 61, and 216, respectively.

Methods

Linear discriminant analysis is used for classification method and feature importance, This study examined the relationship between Humanin and mitochondrial protein (MOTSc), mitochondrial peptides associated with oxidative stress, diabetes progression, and associated complications.

Results

MOTSc, reduced glutathione and glutathione disulfide ratio (GSH/GSSG), interleukin-1β (IL-1β), and 8-isoprostane were significant (P < .05) for the transition from prediabetes to t2dm, highlighting importance of mitochondrial involvement. complement component 5a (c5a) is a biomarker associated with disease progression and comorbidities, gsh gssg, monocyte chemoattractant protein-1 (mcp-1), 8-isoprostane being most important biomarkers.

Conclusions

Comorbidities affect the hypothesized biomarkers as diabetes progresses. Mitochondrial oxidative stress indicators, coagulation, and inflammatory markers help assess diabetes disease development and provide appropriate medications. Future studies will examine longitudinal biomarker evolution.

The p66Shc Redox Protein and the Emerging Complications of Diabetes

Diabetes mellitus is a chronic metabolic disease, the prevalence of which is constantly increasing worldwide. It is often burdened by disabling comorbidities that reduce the quality and expectancy of life of the affected individuals. The traditional complications of diabetes are generally described as macrovascular complications (e.g., coronary heart disease, peripheral arterial disease, and stroke), and microvascular complications (e.g., diabetic kidney disease, retinopathy, and neuropathy). Recently, due to advances in diabetes management and the increased life expectancy of diabetic patients, a strong correlation between diabetes and other pathological conditions (such as liver diseases, cancer, neurodegenerative diseases, cognitive impairments, and sleep disorders) has emerged. Therefore, these comorbidities have been proposed as emerging complications of diabetes. P66Shc is a redox protein that plays a role in oxidative stress, apoptosis, glucose metabolism, and cellular aging. It can be regulated by various stressful stimuli typical of the diabetic milieu and is involved in various types of organ and tissue damage under diabetic conditions. Although its role in the pathogenesis of diabetes remains controversial, there is strong evidence regarding the involvement of p66Shc in the traditional complications of diabetes. In this review, we will summarize the evidence supporting the role of p66Shc in the pathogenesis of diabetes and its complications, focusing for the first time on the emerging complications of diabetes.

Characterization of the internal working-life exposome using minimally and non-invasive sampling methods - a narrative review

During recent years, we are moving away from the 'one exposure, one disease'-approach in occupational settings and towards a more comprehensive approach, taking into account the totality of exposures during a life course by using an exposome approach. Taking an exposome approach however is accompanied by many challenges, one of which, for example, relates to the collection of biological samples. Methods used for sample collection in occupational exposome studies should ideally be minimally invasive, while at the same time sensitive, and enable meaningful repeated sampling in a large population and over a longer time period. This might be hampered in specific situations e.g., people working in remote areas, during pandemics or with flexible work hours. In these situations, using self-sampling techniques might offer a solution. Therefore, our aim was to identify existing self-sampling techniques and to evaluate the applicability of these techniques in an occupational exposome context by conducting a literature review. We here present an overview of current self-sampling methodologies used to characterize the internal exposome. In addition, the use of different biological matrices was evaluated and subdivided based on their level of invasiveness and applicability in an occupational exposome context. In conclusion, this review and the overview of self-sampling techniques presented herein can serve as a guide in the design of future (occupational) exposome studies while circumventing sample collection challenges associated with exposome studies.

Inflammation, oxidative stress and mitochondrial dysfunction in the progression of type II diabetes mellitus with coexisting hypertension

Introduction

Type II diabetes mellitus (T2DM) is a metabolic disorder that poses a serious health concern worldwide due to its rising prevalence. Hypertension (HT) is a frequent comorbidity of T2DM, with the co-occurrence of both conditions increasing the risk of diabetes-associated complications. Inflammation and oxidative stress (OS) have been identified as leading factors in the development and progression of both T2DM and HT. However, OS and inflammation processes associated with these two comorbidities are not fully understood. This study aimed to explore changes in the levels of plasma and urinary inflammatory and OS biomarkers, along with mitochondrial OS biomarkers connected to mitochondrial dysfunction (MitD). These markers may provide a more comprehensive perspective associated with disease progression from no diabetes, and prediabetes, to T2DM coexisting with HT in a cohort of patients attending a diabetes health clinic in Australia.

Methods

Three-hundred and eighty-four participants were divided into four groups according to disease status: 210 healthy controls, 55 prediabetic patients, 32 T2DM, and 87 patients with T2DM and HT (T2DM+HT). Kruskal-Wallis and χ2 tests were conducted between the four groups to detect significant differences for numerical and categorical variables, respectively.

Results and discussion

For the transition from prediabetes to T2DM, interleukin-10 (IL-10), C-reactive protein (CRP), 8-hydroxy-2'-deoxyguanosine (8-OHdG), humanin (HN), and p66^Shc were the most discriminatory biomarkers, generally displaying elevated levels of inflammation and OS in T2DM, in addition to disrupted mitochondrial function as revealed by p66^Shc and HN. Disease progression from T2DM to T2DM+HT indicated lower levels of inflammation and OS as revealed through IL-10, interleukin-6 (IL-6), interleukin-1β (IL-1β), 8-OHdG and oxidized glutathione (GSSG) levels, most likely due to antihypertensive medication use in the T2DM +HT patient group. The results also indicated better mitochondrial function in this group as shown through higher HN and lower p66^Shc levels, which can also be attributed to medication use. However, monocyte chemoattractant protein-1 (MCP-1) levels appeared to be independent of medication, providing an effective biomarker even in the presence of medication use. The results of this study suggest that a more comprehensive review of inflammation and OS biomarkers is more effective in discriminating between the stages of T2DM progression in the presence or absence of HT. Our results further indicate the usefulness of medication use, especially with respect to the known involvement of inflammation and OS in disease progression, highlighting specific biomarkers during disease progression and therefore allowing a more targeted individualized treatment plan.

The Role of p66Shc in Diabetes: A Comprehensive Review from Bench to Bedside

It is well-documented that diabetes is an inflammatory and oxidative disease, with an escalating global burden. Still, there is no definite treatment for diabetes or even prevention of its harmful complications. Therefore, understanding the molecular pathways associated with diabetes might help in finding a solution. p66Shc is a member of Shc family proteins, and it is considered as an oxidative stress sensor and regulator in cells. There are inconsistent data about the role of p66Shc in inducing diabetes, but accumulating evidence supports its role in the pathogenesis of diabetes-related complications, including macro and microangiopathies. There is growing hope that by understanding and targeting molecular pathways involved in this network, prevention of diabetes or its complications would be achievable. This review provides an overview about the role of p66Shc in the development of diabetes and its complications.

Immunoaffinity Capillary Electrophoresis in the Era of Proteoforms, Liquid Biopsy and Preventive Medicine: A Potential Impact in the Diagnosis and Monitoring of Disease Progression

Over the years, multiple biomarkers have been used to aid in disease screening, diagnosis, prognosis, and response to therapy. As of late, protein biomarkers are gaining strength in their role for early disease diagnosis and prognosis in part due to the advancements in identification and characterization of a distinct functional pool of proteins known as proteoforms. Proteoforms are defined as all of the different molecular forms of a protein derived from a single gene caused by genetic variations, alternative spliced RNA transcripts and post-translational modifications. Monitoring the structural changes of each proteoform of a particular protein is essential to elucidate the complex molecular mechanisms that guide the course of disease. Clinical proteomics therefore holds the potential to offer further insight into disease pathology, progression, and prevention. Nevertheless, more technologically advanced diagnostic methods are needed to improve the reliability and clinical applicability of proteomics in preventive medicine. In this manuscript, we review the use of immunoaffinity capillary electrophoresis (IACE) as an emerging powerful diagnostic tool to isolate, separate, detect and characterize proteoform biomarkers obtained from liquid biopsy. IACE is an affinity capture-separation technology capable of isolating, concentrating and analyzing a wide range of biomarkers present in biological fluids. Isolation and concentration of target analytes is accomplished through binding to one or more biorecognition affinity ligands immobilized to a solid support, while separation and analysis are achieved by high-resolution capillary electrophoresis (CE) coupled to one or more detectors. IACE has the potential to generate rapid results with significant accuracy, leading to reliability and reproducibility in diagnosing and monitoring disease. Additionally, IACE has the capability of monitoring the efficacy of therapeutic agents by quantifying companion and complementary protein biomarkers. With advancements in telemedicine and artificial intelligence, the implementation of proteoform biomarker detection and analysis may significantly improve our capacity to identify medical conditions early and intervene in ways that improve health outcomes for individuals and populations.