Introduction to personalized medicine in diabetes mellitus

Managing Diabetic Complications with Alternative Therapeutic Strategies

Diabetes is a chronic metabolic disease affecting millions worldwide. It is characterized by a lack of insulin production or impaired insulin function, leading to elevated blood glucose levels. Conventional treatment methods for diabetes management typically include lifestyle changes and medications. However, alternative therapies have gained attention in recent years, including traditional medicine containing bioactive compounds, supplements like vitamin D and Omega-3 fatty acids, aromatherapy, and homeopathy. Diabetic complications are common in patients with uncontrolled diabetes and can lead to serious health problems, including diabetic retinopathy, impaired wound healing, kidney disease, nerve damage, and cardiovascular disease. Alternative remedies, such as traditional medicine containing bioactive compounds, supplements, and aromatherapy, have been studied for their potential benefits in managing these complications. Traditional medicines like bitter melon, cinnamon, and fenugreek have been shown to have anti-diabetic effects due to their bioactive compounds. Similarly, supplements like vitamin D and Omega-3 fatty acids have been found to improve glycemic control in patients with diabetes. Aromatherapy, which involves the use of essential oils, has also been explored for its potential benefits in diabetes management. Homeopathy, which uses highly diluted substances to stimulate the body's natural healing abilities, has been used to treat diabetes-related symptoms like neuropathy and wounds. Personalized care is essential in natural diabetes management because each person's body and health needs are unique. A holistic approach that addresses the individual's physical, emotional, and spiritual well-being is essential. As research in this field continues to expand, a more comprehensive understanding of diabetes management will lead to improved outcomes for those living with this condition.

Transform diabetes care with precision medicine

Background and Aims

Diabetes is a global concern. This article took a closer look at diabetes and precision medicine.

Methods

A literature search of studies related to the use of precision medicine in diabetes care was conducted in various databases (PubMed, Google Scholar, and Scopus).

Results

Precision medicine encompasses the integration of a wide array of personal data, including clinical, lifestyle, genetic, and various biomarker information. Its goal is to facilitate tailored treatment approaches using contemporary diagnostic and therapeutic techniques that specifically target patients based on their genetic makeup, molecular markers, phenotypic traits, or psychosocial characteristics. This article not only highlights significant advancements but also addresses key challenges, particularly focusing on the technologies that contribute to the realization of personalized and precise diabetes care.

Conclusion

For the successful implementation of precision diabetes medicine, collaboration and coordination among multiple stakeholders are crucial.

Regulated basal and bolus insulin release from glucose-responsive core-shell microspheres based on concanavalin A-sugar affinity

Individual insulin therapy considering the heterogeneity of insulin resistance between patients may bring more benefits than conventional therapy. Therefore, in glucose-responsive insulin delivery systems, more attention should be paid on further regulation of insulin release to meet individual requirements. Our study shows the feasibility of using a photo-crosslinkable shell layer to regulate basal and bolus insulin release from glucose-responsive Con A-polysaccharides network. Core-shell microspheres were fabricated through a two-step high-speed shear-emulsification method. The morphology was observed by SEM and TEM, and the core-shell structure was confirmed by the differences in chemical composition between core-shell and single-layer microspheres obtained from XPS and IR analysis. In vitro insulin release test revealed that the core-shell microspheres with or without light-irradiation could maintain corresponding bolus and basal insulin release in response to different glucose concentration but enable much lower burst release compared with single-layer microspheres without shell. Meanwhile, insulin release rate and amount could be further decreased upon light-irradiation owing to the photo-induced cycloaddition of cinnamate pendant groups of the shell material. The released insulin was proved to remain active according to fluorescence and circular dichroism analysis. The HDF cell viability assessment suggested that the core-shell microspheres possessed no in vitro cytotoxicity.

DMTO: a realistic ontology for standard diabetes mellitus treatment

BACKGROUND

Treatment of type 2 diabetes mellitus (T2DM) is a complex problem. A clinical decision support system (CDSS) based on massive and distributed electronic health record data can facilitate the automation of this process and enhance its accuracy. The most important component of any CDSS is its knowledge base. This knowledge base can be formulated using ontologies. The formal description logic of ontology supports the inference of hidden knowledge. Building a complete, coherent, consistent, interoperable, and sharable ontology is a challenge.

RESULTS

This paper introduces the first version of the newly constructed Diabetes Mellitus Treatment Ontology (DMTO) as a basis for shared-semantics, domain-specific, standard, machine-readable, and interoperable knowledge relevant to T2DM treatment. It is a comprehensive ontology and provides the highest coverage and the most complete picture of coded knowledge about T2DM patients' current conditions, previous profiles, and T2DM-related aspects, including complications, symptoms, lab tests, interactions, treatment plan (TP) frameworks, and glucose-related diseases and medications. It adheres to the design principles recommended by the Open Biomedical Ontologies Foundry and is based on ontological realism that follows the principles of the Basic Formal Ontology and the Ontology for General Medical Science. DMTO is implemented under Protégé 5.0 in Web Ontology Language (OWL) 2 format and is publicly available through the National Center for Biomedical Ontology's BioPortal at http://bioportal.bioontology.org/ontologies/DMTO . The current version of DMTO includes more than 10,700 classes, 277 relations, 39,425 annotations, 214 semantic rules, and 62,974 axioms. We provide proof of concept for this approach to modeling TPs.

CONCLUSION

The ontology is able to collect and analyze most features of T2DM as well as customize chronic TPs with the most appropriate drugs, foods, and physical exercises. DMTO is ready to be used as a knowledge base for semantically intelligent and distributed CDSS systems.

Systems and precision medicine approaches to diabetes heterogeneity: a Big Data perspective

Big Data, and in particular Electronic Health Records, provide the medical community with a great opportunity to analyze multiple pathological conditions at an unprecedented depth for many complex diseases, including diabetes. How can we infer on diabetes from large heterogeneous datasets? A possible solution is provided by invoking next-generation computational methods and data analytics tools within systems medicine approaches. By deciphering the multi-faceted complexity of biological systems, the potential of emerging diagnostic tools and therapeutic functions can be ultimately revealed. In diabetes, a multidimensional approach to data analysis is needed to better understand the disease conditions, trajectories and the associated comorbidities. Elucidation of multidimensionality comes from the analysis of factors such as disease phenotypes, marker types, and biological motifs while seeking to make use of multiple levels of information including genetics, omics, clinical data, and environmental and lifestyle factors. Examining the synergy between multiple dimensions represents a challenge. In such regard, the role of Big Data fuels the rise of Precision Medicine by allowing an increasing number of descriptions to be captured from individuals. Thus, data curations and analyses should be designed to deliver highly accurate predicted risk profiles and treatment recommendations. It is important to establish linkages between systems and precision medicine in order to translate their principles into clinical practice. Equivalently, to realize their full potential, the involved multiple dimensions must be able to process information ensuring inter-exchange, reducing ambiguities and redundancies, and ultimately improving health care solutions by introducing clinical decision support systems focused on reclassified phenotypes (or digital biomarkers) and community-driven patient stratifications.

HbA1c variability in type 2 diabetes is associated with the occurrence of new-onset albuminuria within three years

AIMS

To evaluate the association between HbA1c coefficient of variation (HbA1c-CV) and 3-year new-onset albuminuria risk.

METHODS

A retrospective cohort study involving 716 normoalbuminuric type 2 diabetes patients was conducted between 2010 and 2014. HbA1c-CV was used to categorize patients into low, moderate or high variability groups. Multivariate logistic models were constructed and validated. Integrated discrimination (IDI) and net reclassification (NRI) improvement indices were used to quantify the added predictive value of HbA1c-CV.

RESULTS

The mean age of our cohort was 56.1±12.9years with a baseline HbA1c of 8.3±1.3%. Over 3-years of follow-up, 35.2% (n=252) developed albuminuria. An incremental risk of albuminuria was observed with moderate (6.68-13.43%) and high (above 13.44%) HbA1c-CV categories demonstrating adjusted odds ratios of 1.63 (1.12-2.38) and 3.80 (2.10-6.97) for 3-year new-onset albuminuria, respectively. Including HbA1c-CV for 3-year new-onset albuminuria prediction improved model discrimination (IDI: 0.023, NRI: 0.293, p<0.05). The final model had a C-statistic of 0.760±0.018 on validation.

CONCLUSION

HbA1c-CV improves 3-year prediction of new-onset albuminuria. Together with mean HbA1c, baseline urine albumin-to-creatinine ratio and presence of hypertension, accurate 3-year new-onset albuminuria prediction may be possible.

Targeting endothelial metaflammation to counteract diabesity cardiovascular risk: Current and perspective therapeutic options

The association of obesity and diabetes, termed "diabesity", defines a combination of primarily metabolic disorders with insulin resistance as the underlying common pathophysiology. Cardiovascular disorders associated with diabesity represent the leading cause of morbidity and mortality in the Western world. This makes diabesity, with its rising impacts on both health and economics, one of the most challenging biomedical and social threats of present century. The emerging comprehension of the genes whose alteration confers inter-individual differences on risk factors for diabetes or obesity, together with the potential role of genetically determined variants on mechanisms controlling responsiveness, effectiveness and safety of anti-diabetic therapy underlines the need of additional knowledge on molecular mechanisms involved in the pathophysiology of diabesity. Endothelial cell dysfunction, resulting from the unbalanced production of endothelial-derived vascular mediators, is known to be present at the earliest stages of insulin resistance and obesity, and may precede the clinical diagnosis of diabetes by several years. Once considered as a mere consequence of metabolic abnormalities, it is now clear that endothelial dysfunctional activity may play a pivotal role in the progression of diabesity. In the vicious circle where vascular defects and metabolic disturbances worsen and reinforce each other, a low-grade, chronic, and 'cold' inflammation (metaflammation) has been suggested to serve as the pathophysiological link that binds endothelial and metabolic dysfunctions. In this paradigm, it is important to consider how traditional antidiabetic treatments (specifically addressing metabolic dysregulation) may directly impact on inflammatory processes or cardiovascular function. Indeed, not all drugs currently available to treat diabetes possess the same anti-inflammatory potential, or target endothelial cell function equally. Perspective strategies pointing at reducing metaflammation or directly addressing endothelial dysfunction may disclose beneficial consequences on metabolic regulation. This review focuses on existing and potential new approaches ameliorating endothelial dysfunction and vascular inflammation in the context of diabesity.

Genetic variability of CYP2C9*2 and CYP2C9*3 in seven indigenous groups from Mexico

Aim: CYP2C9 is one of the major drug metabolizing enzymes, however, little is known about polymorphisms in CYP2C9 gene and pharmacological implications in Mexican indigenous populations. Thus, frequencies of CYP2C9*2 and CYP2C9*3 alleles were evaluated in indigenous groups located in northwest (Cora), center (Mazahua and Teenek), south (Chatino and Mixteco) and southeast (Chontal and Maya) regions Mexico. Materials & methods: Allelic discrimination was performed by real-time PCR. Results: CYP2C9*2 allele was found only in Chontal and Maya groups, despite the low contribution of Caucasian component in these populations. CYP2C9*3 allele was present in all populations except in Mazahua, showing a wide genetic variability in the studied populations. Interestingly, we found significant differences between indigenous groups in CYP2C9*3 allele, even in groups located at the same region and belonging to the same linguistic family. Conclusion: These results contribute to laying the pharmacogenetic bases in Mexico, in addition to improving treatment, taking into account the genetic interethnic differences.

The impact of personalized medicine of Type 2 diabetes mellitus in the global health context

Advances in the fields of genomic sciences have given rise to personalized medicine. This new paradigm draws upon a patient's genetic and metabolic makeup in order to tailor diagnostics and treatment. Personalized medicine holds remarkable promises to improve prevention and management of chronic diseases of global relevance, such as Type 2 diabetes mellitus (T2DM). This review article aims at summarizing the evidence from genome-based sciences on T2DM risk and management in different populations and in the Global Health context. Opinions from leading experts in the field were also included. Based on these findings, strengths and weaknesses of personalized approach to T2DM in a global context are delineated. Implications for future research and implementation on that subject are discussed.

eHealth: past and future perspectives

eHealth is an umbrella term incorporating any area that combines healthcare and technology to improve efficiencies and reduce costs. The ultimate goal of eHealth is to rationalize treatment selection to improve patient safety and outcomes. Telemedicine, first used in the 1920s, is the oldest form of eHealth. The introduction of broadband Internet, followed by wireless technologies, has allowed an explosion of mHealth applications within this field. Wearable technologies, such as smartwatches, are now being used for diagnostics and patient monitoring. Challenges remain to develop reusable Clinical Decision Support systems that will streamline the flow of data from clinical laboratories to point of care. This review explores the history of eHealth, and describes some of the remaining integration and implementation challenges.

Older Adult Self-Efficacy Study of Mobile Phone Diabetes Management

The purpose of this study was to evaluate participant self-efficacy and use of a mobile phone diabetes health intervention for older adults during a 4-week period. Participants included seven adults (mean age, 70.3 years) with type 2 diabetes cared for by community-based primary care physicians. Participants entered blood glucose data into a mobile phone and personalized patient Internet Web portal. Based on blood glucose values, participants received automatic messages and educational information to self-manage their diabetes. Study measures included prior mobile phone/Internet use, the Stanford Self-Efficacy for Diabetes Scale, the Stanford Energy/Fatigue Scale, the Short Form-36, the Patient Health Questionnaire-9 (depression), the Patient Reported Diabetes Symptom Scale, the Diabetes Stages of Change measure, and a summary of mobile system use. Participants had high self-efficacy and high readiness and confidence in their ability to monitor changes to control their diabetes. Participants demonstrated ability to use the mobile intervention and communicate with diabetes educators.

A Concept Analysis of Personalized Health Care in Nursing

PURPOSE

The purpose of the study is to identify the concept of personalized health care in nursing and to address future direction in person-centered nursing care.

BACKGROUND

Personalized health care has attracted increased attention in the twenty-first century. As more and more preclinical studies are focusing on cost-effective and patient-centered care, there also has been an identified need for a personalized health care in nursing. Yet the term lacks clear definition and interests among healthcare professionals.

REVIEW METHODS

Rodgers' strategy for concept analysis was used in this analysis. A literature review for 1960-2014 was conducted for the following keywords: nursing care, personalized, and health care.

RESULTS

The analysis demonstrates that personalized health care in nursing is an intangible asset, including explicit attributes (interprofessional collaboration and individualized care approach) and implicit attributes (managing personal vulnerabilities: molecular-based health information and self-health-seeking behaviors). The result of this analysis provides a guide for further conceptual and empirical research and clinical practice in the personalized healthcare era.

CONCLUSION

This concept analysis represents an effort to describe the attributes of a concept regarded as representing an important feature of nursing care and to promote discourse that will enhance maturation of the concept into one that is established with clearly delineated characteristics.

Diabetic retinopathy: variations in patient therapeutic outcomes and pharmacogenomics

Diabetes and its microvascular complications in patients poses a significant challenge and constitutes a major health problem. When it comes to manifestations in the eye, each case of diabetic retinopathy (DR) is unique, in terms of the phenotype, genotype, and, more importantly, the therapeutic response. It is therefore important to identify factors that distinguish one patient from another. Personalized therapy in DR is a new trend aimed at achieving maximum therapeutic response in patients by identifying genotypic and phenotypic factors that may result in less than optimal response to conventional therapy, and consequently, lead to poorer outcome. With advances in the identification of these genetic markers, such as gene polymorphisms and human leucocyte antigen associations, as well as development of drugs that can target their effects, the future of personalized medicine in DR is promising. In this comprehensive review, data from various studies have been analyzed to present what has been achieved in the field of pharmacogenomics thus far. An insight into future research is also provided.

Diabetes management in the real world and the impact of adherence to guideline recommendations

OBJECTIVE

To evaluate diabetes management in the real world, examining adherence to the American Diabetic Association (ADA) guidelines on frequency of glycated hemoglobin A1c (A1C) testing and antidiabetic treatment modifications in patients with type 2 diabetes and measuring the impact of adherence to the guidelines for achieving an A1C target <7%.

RESEARCH DESIGN AND METHODS

Retrospective analyses of claims data were conducted in three groups of patients aged ≥18 years with at least two diagnoses of type 2 diabetes in a large US health insurance claims database between January 2009 and December 2011 and with A1C ≥7% (≥53 mmol/mol). Descriptive analyses were performed on adherence to A1C testing frequency and adherence to antidiabetic treatment modification. Pearson's chi-square test and logistic regression were conducted to estimate the odds ratios.

RESULTS

Of 42,837 patients evaluated for adherence to the ADA guideline for A1C testing frequency, only 7% were fully adherent for 1 year. Analysis of 95,330 patients for adherence to antidiabetic treatment modification revealed that drug therapy was modified in accordance with ADA guidelines for 39% of patients. Among 1337 treatment-naive patients meeting the selection criteria, only 3% met both testing frequency and treatment modification guidelines; the odds of achieving the A1C target of <7% were approximately five-fold higher in patients who met both guidelines versus those who did not (odds ratio 5.29; P < 0.0001).

CONCLUSIONS

This study, based on real-world data from a large type 2 diabetes patient population, demonstrated that adherence to ADA guidelines for A1C testing frequency and drug treatment modifications was extremely low. Achievement of glycemic control (A1C <7%) was significantly associated with adherence to both A1C testing frequency and antidiabetic treatment modification guidelines. Limitations of this study include the retrospective nature, lack of important patient clinical information, and issues with incomplete source data.