Personalized Type 2 Diabetes Management: An Update on Recent Advances and Recommendations

The Effect of Genetic Variants of SLC22A2 (rs662301 and rs315978) on the response to Metformin in type 2 Saudi diabetic patients

PURPOSE

To investigate the allelic and genotypic frequencies of the two genetic variations, NC_000006.12: g.160275887C > T (rs662301) and NC_000006.12:g.160231826 T > C (rs315978), in the SLC22A2 gene among the Saudi population. The primary goal is to elucidate potential associations with these genetic variations and the response to metformin therapy over 6 months to enhance our knowledge of the genetic basis of Type 2 Diabetes Mellitus (T2DM) and its clinical management in the Saudi population.

MATERIALS/METHODS

76 newly diagnosed T2DM patients, aged 30 to 60, of both sexes and Saudi origin, were treated with metformin monotherapy. Blood samples were collected before and after 6 months of therapy,80 healthy individuals were included as controls. Genomic DNA was extracted. Genotyping of the SLC22A2 genetic variations was performed using TaqMan® SNP Genotyping Assays. Binary logistic regression was utilized to evaluate how certain clinical parameters influence T2DM concerning the presence of SLC22A2 gene variants.

RESULTS

Among these patients, 73.3 % were responders, and 26.7 % were non-responders. For these variants, no statistically significant differences in genotype or allele frequencies were observed between responders and non-responders (p = 0.375 and p = 0.384 for rs662301; p = 0.473 and p = 0.481 for rs315978, respectively). For the SLC22A2 variant rs662301, the C/C genotype was significantly associated with increased T2DM risk with age and elevated HbA1c levels. Similarly, rs315978 revealed higher T2DM susceptibility and HbA1c elevation in C/C genotype carriers, specifically with advancing age compared to individuals with C/T and T/T genotypes.

CONCLUSION

The study offers insights into the genetic landscape of T2DM in Saudi Arabia. Despite the absence of significant associations with treatment response, the study suggests potential age-specific associations, this highlights the complexity of the disease. This research underscores the necessity for expanded research, considering diverse populations and genetic factors, to develop personalized treatment approaches. This study serves as a foundation for future investigations into the Saudi population, recognizing the need for a larger sample size.

Rewriting the textbook for pharma: how to adapt and thrive in a digital, personalized and collaborative world

The pharmaceutical industry is undergoing a sweeping transformation, driven by technological innovations, demographic shifts, regulatory changes and consumer expectations. For adaptive players in pharma to excel in this rapidly changing landscape, which will be markedly different from today by 2030 and beyond, they will require a different set of skills, capabilities and mindsets, as well as a willingness to collaborate and co-create value with multiple stakeholders. The industry needs to rewrite the textbook for pharma by embracing and implementing four key dimensions of change: digitalization, personalization, collaboration and innovation. In this article, we will examine how these dimensions of change are reshaping the industry, and provide practical and strategic guidance based on best practices and examples. Specifically, adaptive pharma companies should embrace the use of advanced digital technologies, such as artificial intelligence and machine learning technologies, to streamline processes and solve challenges rapidly. Personalization, both in medicine and patient engagement, will also be key to success in the 'digital revolution', and a collaborative approach involving partnerships with tech start-ups, health-care providers and regulatory bodies will also be essential to create an integrated and responsive health-care ecosystem. Using these ideas for a rewritten textbook for pharma, adaptive players in pharma will evolve to be personalized and digitized health-focused organizations that provide comprehensive solutions which go beyond drugs and devices.

Diabetes mellitus in privately insured autistic adults in the United States

LAY ABSTRACT

Diabetes is a chronic health condition that is challenging to manage. Estimates of how common diabetes is among non-autistic adults are available, but improved estimates for autistic adults are needed. The purpose of this study was to obtain improved diabetes estimates for autistic adults. We analyzed a large private health insurance claims database to estimate how common diabetes was among autistic adults, and how likely autistic adults were to have diabetes compared to non-autistic adults at 5-year age intervals throughout adulthood (e.g. 18-22, 23-27). We found that diabetes was more common among autistic adults than non-autistic adults and that autistic adults were significantly more likely than non-autistic adults to have diabetes throughout most of adulthood. Our findings suggest that autistic adults may be more likely than non-autistic adults to experience diabetes in adulthood. The development of diabetes support services and programs that accommodate autistic adults' individual needs are important for future study to promote positive diabetes outcomes for autistic adults.

Patterns of initial and first-intensifying antidiabetic drug utilization among patients with type 2 diabetes mellitus in Scotland, 2010-2020: A retrospective population-based cohort study

AIM

To evaluate the utilization and prescribing patterns of antidiabetic drugs (ADDs) for patients with type 2 diabetes mellitus (T2DM) at treatment initiation and first intensification.

METHODS

A retrospective cohort study was performed using linked routinely collected data of patients with T2DM who received ADDs between January 2010 and December 2020 in Scotland. The prescribing patterns were quantified using frequency/percentages, absolute/relative change, and trend tests.

RESULTS

Overall, 145 909 new ADD users were identified, with approximately 91% (N = 132 382) of patients receiving a single ADD at first treatment initiation. Metformin was the most often prescribed monotherapy (N = 118 737, 89.69%). A total of 50 731 patients (39.40%) who were started on metformin (N = 46 730/118 737, 39.36%) or sulphonylurea (SU; N = 4001/10 029, 39.89%) monotherapy had their treatment intensified with one or more additional ADD. Most initial-metformin (45 963/46 730; 98.36%) and initial-SU users (3894/4001; 97.33%) who added further drugs were intensified with single ADDs. SUs (22 197/45 963; 48.29%) were the most common first-intensifying monotherapy after initial metformin use, but these were replaced by sodium-glucose cotransporter-2 (SGLT2) inhibitors in 2019 (SGLT2 inhibitors: 2039/6065, 33.62% vs. SUs: 1924/6065, 31.72%). Metformin was the most frequently added monotherapy to initial SU use (2924/3894, 75.09%). Although the majority of patients received a single ADD, the use of combination therapy significantly increased over time. Nevertheless, there was a significant increasing trend towards prescribing the newer ADD classes (SGLT2 inhibitors, dipeptidyl peptidase-4 inhibitors) as monotherapy or in combination compared with the older ones (SUs, insulin, thiazolidinediones) at both drug initiation and first intensification.

CONCLUSIONS

An overall increasing trend in prescribing the newer ADD classes compared to older ADDs was observed. However, metformin remained the most commonly prescribed first-line ADD, while SGLT2 inhibitors replaced SUs as the most common add-on therapy to initial metformin use in 2019.

Miniature mass spectrometer-based point-of-care assay for quantification of metformin and sitagliptin in human blood and urine

Metformin (MET) and sitagliptin (STG) are widely used as the first-line and long-term oral hypoglycemic agents for managing type 2 diabetes mellitus (T2DM). However, the current lack of convenient and rapid measurement methods poses a challenge for individualized management. This study developed a point-of-care (POC) assay method utilizing a miniature mass spectrometer, enabling rapid and accurate quantification of MET and STG concentrations in human blood and urine. By combining the miniature mass spectrometer with paper spray ionization, this method simplifies the process into three to four steps, requires minimal amounts of bodily fluids (50 μL of blood and 2 μL of urine), and is able to obtain quantification results within approximately 2 min. Stable isotope-labeled internal standards were employed to enhance the accuracy and stability of measurement. The MS/MS responses exhibited good linear relationship with concentration, with relative standard deviations (RSDs) below 25%. It has the potential to provide immediate treatment feedback and decision support for patients and healthcare professionals in clinical practice.

Expert Consensus on Dipeptidyl Peptidase-4 Inhibitor-Based Therapies in the Modern Era of Type 2 Diabetes Mellitus Management in India

India has a high prevalence of type 2 diabetes mellitus (T2DM) with unique clinical characteristics compared to other populations. Despite advancements in diabetes therapy, a significant number of patients in India still experience poor glycemic control and complications. Dipeptidyl peptidase-4 (DPP-4) inhibitors continue to be an important component of T2DM treatment due to their favorable efficacy and tolerability profile. Given the current scenario, there is a need to revisit the role of DPP-4 inhibitors in T2DM management in Indian patients. This consensus paper aims to provide guidance on the utilization of DPP-4 inhibitors in T2DM management from an Indian perspective. A consensus group of 100 experts developed recommendations based on an extensive literature review and discussions. The expert group emphasized the importance of timely glycemic control, combination therapy, and targeting the underlying pathophysiology of T2DM. The combinations of DPP-4 inhibitors with metformin and/or sodium-glucose transport protein-2 inhibitors are rationalized in this paper, considering their complementary mechanisms of action. This paper provides valuable insights for clinicians in optimizing the management of T2DM in the Indian population with the use of DPP-4 inhibitors and proposes an algorithm for selecting DPP-4 inhibitor-based therapies.

Etiologies underlying subtypes of long-standing type 2 diabetes

BACKGROUND

Attempts to subtype, type 2 diabetes (T2D) have mostly focused on newly diagnosed European patients. In this study, our aim was to subtype T2D in a non-white Emirati ethnic population with long-standing disease, using unsupervised soft clustering, based on etiological determinants.

METHODS

The Auto Cluster model in the IBM SPSS Modeler was used to cluster data from 348 Emirati patients with long-standing T2D. Five predictor variables (fasting blood glucose (FBG), fasting serum insulin (FSI), body mass index (BMI), hemoglobin A1c (HbA1c) and age at diagnosis) were used to determine the appropriate number of clusters and their clinical characteristics. Multinomial logistic regression was used to validate clustering results.

RESULTS

Five clusters were identified; the first four matched Ahlqvist et al subgroups: severe insulin-resistant diabetes (SIRD), severe insulin-deficient diabetes (SIDD), mild age-related diabetes (MARD), mild obesity-related diabetes (MOD), and a fifth new subtype of mild early onset diabetes (MEOD). The Modeler algorithm allows for soft assignments, in which a data point can be assigned to multiple clusters with different probabilities. There were 151 patients (43%) with membership in cluster peaks with no overlap. The remaining 197 patients (57%) showed extensive overlap between clusters at the base of distributions.

CONCLUSIONS

Despite the complex picture of long-standing T2D with comorbidities and complications, our study demonstrates the feasibility of identifying subtypes and their underlying causes. While clustering provides valuable insights into the architecture of T2D subtypes, its application to individual patient management would remain limited due to overlapping characteristics. Therefore, integrating simplified, personalized metabolic profiles with clustering holds greater promise for guiding clinical decisions than subtyping alone.

Recent Insights into Glucose-Responsive Concanavalin A-Based Smart Hydrogels for Controlled Insulin Delivery

Many efforts are continuously undertaken to develop glucose-sensitive biomaterials able of controlling glucose levels in the body and self-regulating insulin delivery. Hydrogels that swell or shrink as a function of the environmental free glucose content are suitable systems for monitoring blood glucose, delivering insulin doses adapted to the glucose concentration. In this context, the development of sensors based on reversible binding to glucose molecules represents a continuous challenge. Concanavalin A (Con A) is a bioactive protein isolated from sword bean plants (Canavalia ensiformis) and contains four sugar-binding sites. The high affinity for reversibly and specifically binding glucose and mannose makes Con A as a suitable natural receptor for the development of smart glucose-responsive materials. During the last few years, Con A was used to develop smart materials, such as hydrogels, microgels, nanoparticles and films, for producing glucose biosensors or drug delivery devices. This review is focused on Con A-based materials suitable in the diagnosis and therapeutics of diabetes. A brief outlook on glucose-derived theranostics of cancer is also presented.

Assessing the reliability and validity of the Slovenian version of the Appraisal of Diabetes Scale (ADS-S) in type 2 diabetes patients

Managing type 2 diabetes (T2D) effectively is a considerable challenge. The Appraisal of Diabetes Scale (ADS) has proven valuable in understanding how individuals perceive and cope with their condition. This study aimed to evaluate the psychometric properties of the Slovenian version of ADS (ADS-S). We recruited a sample of 400 adult individuals with T2D from three primary healthcare centers in Slovenia, ensuring an average of 57 cases per individual item. The psychometric evaluation included internal consistency, test-retest reliability, construct validity, and discriminant validity. Confirmatory factor analysis (CFA) was additionally performed to evaluate the fit of one- and two-factor models. After excluding incomplete questionnaires, 389 individuals participated, averaging 72.0±7.5 years, with 196 men and 193 women. ADS-S exhibited acceptable internal consistency (Cronbach's α = 0.70) and strong test-retest reliability (interclass correlation = 0.88, p <0.001). Criterion validity was established through significant correlations between ADS-S score and EQ-5D utility score (r = -0.34, p <0.001), EQ-VAS score (r = -0.38, p <0.001), and HbA1c >7.5% (r = 0.22, p = 0.019). Discriminant validity assessment found no significant correlation between ADS-S score and age, but a significant correlation with female gender (r = 0.17, p = 0.001). CFA results supported a two-factor structure (psychological impact of diabetes and sense of self-control) over a one-factor structure, as indicated by model fit indicators. ADS-S stands as a valid and reliable tool for assessing psychological impact and self-control in Slovenian T2D patients. Future research should explore adding items for capturing secondary appraisal of diabetes and studying the influence of female gender on ADS scores.

Insulin therapy among diabetic patients in rural communities of Sub-Saharan Africa: a perspective review

In this perspective review, we describe a brief background on the status quo of diabetes mellitus-related therapies and glycemic control among patients in rural communities in sub-Saharan Africa. The article discusses insulin therapy as well as the difficulties in obtaining insulin and oral hypoglycemic medications for diabetic patients living in sub-Saharan Africa. We wrap up our discussion with suggestions on solutions and opportunities for future research to tackle this health challenge in these impoverished communities. We conducted a literature search from PubMed and Google Scholar up until August 2023. Key words were used to generate search terms used to retrieve the required information. All types of literature with pertinent information on the current topic were included in the study. Diabetes mellitus is on the rise in sub-Saharan Africa. Several studies have reported poor glycemic control, low screening rates for diabetes mellitus, cigarette smoking, high alcohol consumption, prescription of antidiabetic therapy, and associated costs as contributors to the uptake of antidiabetic treatment. Although there is paucity of data on the extent of insulin therapy uptake and its possible modifiable contributors among the diabetic patients in the region, the anticipated increase in the number of people with diabetes on the continent makes it critical for global leaders to address the research gaps in insulin therapy among rural communities of sub-Saharan Africa, thus reducing the burden of diabetes in these populations.

To What Extent Does Cardiovascular Risk Classification of Patients with Type 2 Diabetes Differ between European Guidelines from 2023, 2021, and 2019? A Cross-Sectional Study

Background and Objectives: Type 2 Diabetes (T2DM) is intricately associated with an increased cardiovascular (CV) risk, highlighting the imperative for tailored intervention in the prevention and management of CV diseases. To assess the CV risk and subsequent interventions in patients with diabetes, the European Society of Cardiology (ESC) has been consistently developing and updating specific guidelines for risk assessment and patient management since 2019. The 2023 risk classification method has significantly changed, introducing a novel probability-based assessment through the implementation of SCORE2-Diabetes instrument. This marks a shift from the risk factor-based classification employed in the 2019 and 2021 methods, representing an innovative approach in risk assessment for individuals with T2DM. This study aims to evaluate the differences in the CV risk classification among hospitalized patients with T2DM using the three proposed methods within the Romanian population, a European population considered to be at very high cardiovascular risk. Materials and Methods: in a consecutive-case, population-based study design, 70 patients hospitalized with T2DM from a European population characterized by very high CV risk were assessed for CV risk using the three proposed methods. The differences between these classifications were subsequently analyzed. Results: In the study group, according to 2023 classification, one patient (1.4%) was classified with moderate CV risk, eight (11.4%) with high cardiovascular risk, and sixty-one (87.2%) with very high cardiovascular risk. A total of 36 patients (51.4%) were classified differently compared to 2021 criteria, the differences being statistically significant (p = 0.047), while 13 (18.6%) were different compared to 2019 criteria, the differences being statistically non-significant (p = 0.731). By comparing the 2021 to the 2019 ESC Guidelines recommendations, 40 patients had a one-step decrease in cardiovascular risk category, from very high to high risk. Conclusions: Most patients included in the analysis were classified as very high CV risk (87.2%). Within a European population characterized by very high CV risk, the SCORE2-Diabetes instrument proves to be a valuable tool, contributing to most step-ups in CV risk classes within the 2023 classification. In a very-high-risk demographic, the 2023 algorithm resulted in different classifications in contrast to the 2021 method but similar classifications observed with the 2019 method.

The Role of G Protein-Coupled Receptors and Receptor Kinases in Pancreatic β-Cell Function and Diabetes

Type 2 diabetes (T2D) mellitus has emerged as a major global health concern that has accelerated in recent years due to poor diet and lifestyle. Afflicted individuals have high blood glucose levels that stem from the inability of the pancreas to make enough insulin to meet demand. Although medication can help to maintain normal blood glucose levels in individuals with chronic disease, many of these medicines are outdated, have severe side effects, and often become less efficacious over time, necessitating the need for insulin therapy. G protein-coupled receptors (GPCRs) regulate many physiologic processes, including blood glucose levels. In pancreatic β cells, GPCRs regulate β-cell growth, apoptosis, and insulin secretion, which are all critical in maintaining sufficient β-cell mass and insulin output to ensure euglycemia. In recent years, new insights into the signaling of incretin receptors and other GPCRs have underscored the potential of these receptors as desirable targets in the treatment of diabetes. The signaling of these receptors is modulated by GPCR kinases (GRKs) that phosphorylate agonist-activated GPCRs, marking the receptor for arrestin binding and internalization. Interestingly, genome-wide association studies using diabetic patient cohorts link the GRKs and arrestins with T2D. Moreover, recent reports show that GRKs and arrestins expressed in the β cell serve a critical role in the regulation of β-cell function, including β-cell growth and insulin secretion in both GPCR-dependent and -independent pathways. In this review, we describe recent insights into GPCR signaling and the importance of GRK function in modulating β-cell physiology. SIGNIFICANCE STATEMENT: Pancreatic β cells contain a diverse array of G protein-coupled receptors (GPCRs) that have been shown to improve β-cell function and survival, yet only a handful have been successfully targeted in the treatment of diabetes. This review discusses recent advances in our understanding of β-cell GPCR pharmacology and regulation by GPCR kinases while also highlighting the necessity of investigating islet-enriched GPCRs that have largely been unexplored to unveil novel treatment strategies.

2. Diagnosis and Classification of Diabetes: Standards of Care in Diabetes-2024

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Exploring the progress of artificial intelligence in managing type 2 diabetes mellitus: a comprehensive review of present innovations and anticipated challenges ahead

A significant worldwide health issue, Type 2 Diabetes Mellitus (T2DM) calls for creative solutions. This in-depth review examines the growing severity of T2DM and the requirement for individualized management approaches. It explores the use of artificial intelligence (AI) in the treatment of diabetes, highlighting its potential for diagnosis, customized treatment plans, and patient self-management. The paper highlights the roles played by AI applications such as expert systems, machine learning algorithms, and deep learning approaches in the identification of retinopathy, the interpretation of clinical guidelines, and prediction models. Examined are difficulties with individualized diabetes treatment, including complex technological issues and patient involvement. The review highlights the revolutionary potential of AI in the management of diabetes and calls for a balanced strategy in which AI supports clinical knowledge. It is crucial to pay attention to ethical issues, data privacy, and joint research initiatives.

Bromocriptine and Colesevelam Hydrochloride: Novel Therapies for Type II Diabetes Mellitus

The increasing prevalence of type II diabetes mellitus (T2DM) is a worldwide healthcare concern. Over the years, our understanding of T2DM has grown considerably in uncovering the pathophysiology of the disease and, in turn, understanding how improved treatment methods can be used to slow disease progression. Some long-term complications that are responsible for most T2DM mortalities include cardiovascular disease, neurological decline, and renal failure. In treating T2DM, it is important that not only glycemic control be obtained but also control of associated complications. Bromocriptine and colesevelam hydrochloride have both been approved by the Food and Drug Administration (FDA) to treat T2DM but are not readily used in practice. These medications are known to treat glycemic dysregulation via unconventional mechanisms, which might contribute to their potential to provide protection against common diabetic complications such as cardiovascular disease. In order to ensure that these overlooked medications become more readily used, it is vital that more research be performed to further elucidate their efficacy in a clinical setting. Future studies should continue to provide clinicians a better understanding of the role these medications have on the treatment of T2DM such as their ability to be used in combination with other commonly used T2DM medications or as monotherapies.

Validation of the hypoglycemia awareness questionnaire to assess hypoglycemia awareness in patients with type 2 diabetes treated with insulin

AIMS

Given the implications of impaired hypoglycemia awareness in patients with type 2 diabetes (T2D), it is necessary to identify reliable and valid instruments for its measurement. The Hypoglycemia Awareness Questionnaire (HypoA-Q) measures impaired awareness, symptom severity, and symptom frequency. The present study evaluated the HypoA-Q validity for assessing awareness of hypoglycemia in patients with T2D treated with insulin.

METHODS

The questionnaire was administered to 406 patients diagnosed with T2D on insulin treatment at four centers in Bogotá, Colombia. The internal structure of the questionnaire was analyzed using exploratory and confirmatory factor analyses, internal consistency and test-retest reliability were evaluated, and criterion validity was rated by assessing its correlation with the Clarke scale.

RESULTS

Factor analysis identified an empirical structure of four domains that adequately represented the construct. Cronbach's alpha and McDonald's Omega coefficients yielded values between 0.75 and 0.79 for the impaired awareness scale. Lin and intraclass correlation coefficients were 0.86 and 0.85, respectively. The correlation between the impaired awareness subscale and Clarke scale was 0.654, and differences were found between patients with good and poor awareness of hypoglycemia.

CONCLUSIONS

The HypoA-Q is a valid and reliable tool for measuring the awareness of hypoglycemia in patients with T2D who are treated with insulin.

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.

3D printing combined with biopredictive dissolution and PBPK/PD modeling optimization and personalization of pharmacotherapy: Are we there yet?

Precision medicine requires selecting the appropriate dosage regimen for a patient using the right drug, at the right time. Model-Informed Precision Dosing (MIPD) is a concept suggesting utilization of model-based prediction methods for optimizing the treatment benefit-harm balance, based on individual characteristics of the patient, disease, treatment method, and other factors. Here, we discuss a theoretical workflow comprising several elements, beginning from the physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models, through 3D printed tablets with the model proposed dose, information range and flow, and the patient themselves. We also describe each of these elements, and the connection between them, highlighting challenges and potential obstacles.

Understanding Type 2 Diabetes Mellitus Risk Parameters through Intermittent Fasting: A Machine Learning Approach

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by elevated blood glucose levels. Despite the availability of pharmacological treatments, dietary plans, and exercise regimens, T2DM remains a significant global cause of mortality. As a result, there is an increasing interest in exploring lifestyle interventions, such as intermittent fasting (IF). This study aims to identify underlying patterns and principles for effectively improving T2DM risk parameters through IF. By analyzing data from multiple randomized clinical trials investigating various IF interventions in humans, a machine learning algorithm was employed to develop a personalized recommendation system. This system offers guidance tailored to pre-diabetic and diabetic individuals, suggesting the most suitable IF interventions to improve T2DM risk parameters. With a success rate of 95%, this recommendation system provides highly individualized advice, optimizing the benefits of IF for diverse population subgroups. The outcomes of this study lead us to conclude that weight is a crucial feature for females, while age plays a determining role for males in reducing glucose levels in blood. By revealing patterns in diabetes risk parameters among individuals, this study not only offers practical guidance but also sheds light on the underlying mechanisms of T2DM, contributing to a deeper understanding of this complex metabolic disorder.

Bexagliflozin, a sodium-glucose cotransporter 2 (SGLT2) inhibitor, for improvement of glycemia in type 2 diabetes mellitus: a systematic review and meta-analysis

OBJECTIVES

This study assessed the clinical safety and efficacy of bexagliflozin, a sodium-glucose cotransporter 2(SGLT2) inhibitor, in managing glycemia among patients with type 2 diabetes mellitus (T2DM).

AREAS COVERED

We examined RCTs with T2DM comparing the clinical effectiveness and safety of 20 mg once daily oral dose of bexagliflozin with placebo for managing glycemia till 28 May 2023, published on databases like ClinicalTrials.gov, PubMed, Embase, and Cochrane Library. Furthermore, reduction of body weight, fasting plasma sugarr(FPG), systolic blood pressure (SBP) and the percentage of individuals who achieved glycated hemoglobin (HbA1c) of < 7% from baseline were also evaluated. The Review Manager 5 was utilized to investigate the retrieved data.

EXPERT OPINION

We involved eight RCTs. Bexagliflozin was significantly superior in reducing HbA1c[least squares mean difference(LSMD) = -0.45,95% confidence interval (CI =-0.55 to -0.34,p < 0.00001], FPG [LSMD= -1.37, 95%CI =-1.73 to -1.00, p < 0.00001], body weight (LSMD= -1.77, 95%CI =-2.44 to-1.10, p < 0.00001), and SBP(LSMD= -4.11,95%CI = -6.18 to -2.03,p = 0.0001) in comparison to placebo. The safety outcomes of bexagliflozin were consistent with the placebo arm. This study concluded that bexagliflozin seems to be a promising oral anti-diabetic drug for enhancing glycemic management in adult patients with T2DM.

Algae-Derived Natural Products in Diabetes and Its Complications-Current Advances and Future Prospects

Diabetes poses a significant global health challenge, necessitating innovative therapeutic strategies. Natural products and their derivatives have emerged as promising candidates for diabetes management due to their diverse compositions and pharmacological effects. Algae, in particular, have garnered attention for their potential as a source of bioactive compounds with anti-diabetic properties. This review offers a comprehensive overview of algae-derived natural products for diabetes management, highlighting recent developments and future prospects. It underscores the pivotal role of natural products in diabetes care and delves into the diversity of algae, their bioactive constituents, and underlying mechanisms of efficacy. Noteworthy algal derivatives with substantial potential are briefly elucidated, along with their specific contributions to addressing distinct aspects of diabetes. The challenges and limitations inherent in utilizing algae for therapeutic interventions are examined, accompanied by strategic recommendations for optimizing their effectiveness. By addressing these considerations, this review aims to chart a course for future research in refining algae-based approaches. Leveraging the multifaceted pharmacological activities and chemical components of algae holds significant promise in the pursuit of novel antidiabetic treatments. Through continued research and the fine-tuning of algae-based interventions, the global diabetes burden could be mitigated, ultimately leading to enhanced patient outcomes.

Identifying subgroups of patients with type 2 diabetes based on real-world traditional chinese medicine electronic medical records

Introduction: Type 2 diabetes (T2D) is a multifactorial complex chronic disease with a high prevalence worldwide, and Type 2 diabetes patients with different comorbidities often present multiple phenotypes in the clinic. Thus, there is a pressing need to improve understanding of the complexity of the clinical Type 2 diabetes population to help identify more accurate disease subtypes for personalized treatment. Methods: Here, utilizing the traditional Chinese medicine (TCM) clinical electronic medical records (EMRs) of 2137 Type 2 diabetes inpatients, we followed a heterogeneous medical record network (HEMnet) framework to construct heterogeneous medical record networks by integrating the clinical features from the electronic medical records, molecular interaction networks and domain knowledge. Results: Of the 2137 Type 2 diabetes patients, 1347 were male (63.03%), and 790 were female (36.97%). Using the HEMnet method, we obtained eight non-overlapping patient subgroups. For example, in H3, Poria, Astragali Radix, Glycyrrhizae Radix et Rhizoma, Cinnamomi Ramulus, and Liriopes Radix were identified as significant botanical drugs. Cardiovascular diseases (CVDs) were found to be significant comorbidities. Furthermore, enrichment analysis showed that there were six overlapping pathways and eight overlapping Gene Ontology terms among the herbs, comorbidities, and Type 2 diabetes in H3. Discussion: Our results demonstrate that identification of the Type 2 diabetes subgroup based on the HEMnet method can provide important guidance for the clinical use of herbal prescriptions and that this method can be used for other complex diseases.

Predicting mechanisms of action at genetic loci associated with discordant effects on type 2 diabetes and abdominal fat accumulation

Obesity is a major risk factor for cardiovascular disease, stroke, and type 2 diabetes (T2D). Excessive accumulation of fat in the abdomen further increases T2D risk. Abdominal obesity is measured by calculating the ratio of waist-to-hip circumference adjusted for the body-mass index (WHRadjBMI), a trait with a significant genetic inheritance. Genetic loci associated with WHRadjBMI identified in genome-wide association studies are predicted to act through adipose tissues, but many of the exact molecular mechanisms underlying fat distribution and its consequences for T2D risk are poorly understood. Further, mechanisms that uncouple the genetic inheritance of abdominal obesity from T2D risk have not yet been described. Here we utilize multi-omic data to predict mechanisms of action at loci associated with discordant effects on abdominal obesity and T2D risk. We find six genetic signals in five loci associated with protection from T2D but also with increased abdominal obesity. We predict the tissues of action at these discordant loci and the likely effector Genes (eGenes) at three discordant loci, from which we predict significant involvement of adipose biology. We then evaluate the relationship between adipose gene expression of eGenes with adipogenesis, obesity, and diabetic physiological phenotypes. By integrating these analyses with prior literature, we propose models that resolve the discordant associations at two of the five loci. While experimental validation is required to validate predictions, these hypotheses provide potential mechanisms underlying T2D risk stratification within abdominal obesity.

Human Digital Twin for Personalized Elderly Type 2 Diabetes Management

Managing Elderly type 2 diabetes (E-T2D) is challenging due to geriatric conditions (e.g., co-morbidity, multiple drug intake, etc.), and personalization becomes paramount for precision medicine. This paper presents a human digital twin (HDT) framework to manage E-T2D that exploits various patient-specific data and builds a suite of models exploiting the data for prediction and management to personalize diabetes treatment in E-T2D patients. These models include mathematical and deep-learning ones that capture different patient aspects. Consequently, the HDT virtualizes the patient from different viewpoints using an HDT that mimics the patient and has interfaces to update the virtual models simultaneously from measurements. Using these models the HDT obtains deeper insights about the patient. Further, an adaptive patient model fusing this information and a learning-based model predictive control (LB-MPC) algorithm are proposed. The geriatric conditions are captured as model parameters and constraints while solving the LB-MPC to personalize the insulin infusion for E-T2D management. The HDT is deployed on and illustrated with 15 patients using clinical trials and simulations. Our results show that HDT helps improve the time-in-range from 3–75% to 86–97% and reduces insulin infusion by 14–29%.

Adherence to Oral Antidiabetic Drugs in Patients with Type 2 Diabetes: Systematic Review and Meta-Analysis

Poor adherence to oral antidiabetic drugs (OADs) in patients with type 2 diabetes (T2D) can lead to therapy failure and risk of complications. The aim of this study was to produce an adherence proportion to OADs and estimate the association between good adherence and good glycemic control in patients with T2D. We searched in MEDLINE, Scopus, and CENTRAL databases to find observational studies on therapeutic adherence in OAD users. We calculated the proportion of adherent patients to the total number of participants for each study and pooled study-specific adherence proportions using random effect models with Freeman-Tukey transformation. We also calculated the odds ratio (OR) of having good glycemic control and good adherence and pooled study-specific OR with the generic inverse variance method. A total of 156 studies (10,041,928 patients) were included in the systematic review and meta-analysis. The pooled proportion of adherent patients was 54% (95% confidence interval, CI: 51-58%). We observed a significant association between good glycemic control and good adherence (OR: 1.33; 95% CI: 1.17-1.51). This study demonstrated that adherence to OADs in patients with T2D is sub-optimal. Improving therapeutic adherence through health-promoting programs and prescription of personalized therapies could be an effective strategy to reduce the risk of complications.

Preferred Conversation Topics with Respect to Treatment Decisions Among Individuals with Type 2 Diabetes

PURPOSE

Greater knowledge of individuals' needs and preferences can enhance shared decision-making, which is associated with improved quality of decisions and increased satisfaction. This study aimed to identify and prioritize the attributes (ie conversation topics) that individuals with type 2 diabetes find it most important to discuss with their healthcare provider regarding treatment decisions.

PATIENTS AND METHODS

First, small group interviews were organized with adults with type 2 diabetes (N=8) treated in primary care to identify the attributes that they find important to discuss regarding treatment decisions. A five-step nominal group technique was applied during the interviews. An object best-worst scaling (BWS) survey was subsequently distributed to individuals with self-reported diabetes participating in the Dutch Health Care Consumer Panel of the Netherlands Institute for Health Services Research (N=600) to determine the relative importance score (RIS) of the identified attributes. A higher RIS indicates a higher level of perceived importance. Subgroup and latent class analyses were performed to explore whether individuals' demographic and disease characteristics influenced their attribute preferences.

RESULTS

A total of 21 attributes were identified during three small group interviews with individuals with type 2 diabetes. Respondents in the BWS survey (N=285) viewed "quality of life" (RIS=11.97), "clinical outcomes" (RIS=10.40), "long-term diabetes complications" (RIS=9.83) and "short-term adverse medication" (RIS=7.72) as the most important in the decision-making process for the treatment of type 2 diabetes. Some differences in attribute preferences were identified according to demographic and disease characteristics.

CONCLUSION

In general, individuals with type 2 diabetes not only want to discuss the biological effects of treatments, but also the impact of treatment on their quality of life. Healthcare providers should be aware that attributes are viewed differently by different individuals. This emphasizes the need for tailor-made healthcare decisions, which means eliciting and responding to individual preferences in the decision-making process.

A series of patients with hospital-acquired diabetic ketoacidosis (HADKA): a descriptive analysis

BACKGROUND

Hospital-acquired diabetic ketoacidosis (HADKA) can complicate hospital admission in people with type 1 diabetes (T1D) and type 2 diabetes (T2D). We aimed to determine the characteristics of such patients and the reasons for HADKA.

METHODS

A retrospective analysis of patients referred to diabetes services with HADKA at Morriston Hospital between January 2016 and January 2022 was undertaken. Patients that were included were admitted without diabetic ketoacidosis (DKA), were aged 18 years and over, and who subsequently developed DKA in hospital.

RESULTS

Twenty-five patients were included with a mean age of 65.2 years; nine (32.0%) were men, 13 (52.0%) had T1D and 12 (48.0%) had T2D. Patients had a mean pre-admission glycated haemoglobin of 84.7 mmol/mol, and 17 (68.0%) were insulin-treated. Most were admitted under medicine (n=14; 56.0%) and the remainder under surgery (n=11; 44.0%). More common reasons for HADKA were erroneous insulin administration (n=9; 36.0%), infection (n=7; 28.0%) and surgery (n=5; 20.0%). Five (20.0%) patients required intensive care admission, and the mean length of hospital stay was 42.6 days (range 2-173). Three (12.0%) patients died during the hospital admission.

CONCLUSION

HADKA was identified in a significant number of patients at our hospital and was associated with significant mortality. Earlier recognition of ketonaemia and associated medication use may prevent HADKA and improve outcomes.

Genetics of Type 2 Diabetes: Past, Present, and Future

Diabetes has reached epidemic proportions worldwide. Currently, approximately 537 million adults (20–79 years) have diabetes, and the total number of people with diabetes is continuously increasing. Diabetes includes several subtypes. About 80% of all cases of diabetes are type 2 diabetes (T2D). T2D is a polygenic disease with an inheritance ranging from 30 to 70%. Genetic and environment/lifestyle factors, especially obesity and sedentary lifestyle, increase the risk of T2D. In this review, we discuss how studies on the genetics of diabetes started, how they expanded when genome-wide association studies and exome and whole-genome sequencing became available, and the current challenges in genetic studies of diabetes. T2D is heterogeneous with respect to clinical presentation, disease course, and response to treatment, and has several subgroups which differ in pathophysiology and risk of micro- and macrovascular complications. Currently, genetic studies of T2D focus on these subgroups to find the best diagnoses and treatments for these patients according to the principles of precision medicine.

Evaluation of Subclinical Vascular Disease in Diabetic Kidney Disease: A Tool for Personalization of Management of a High-Risk Population

Background: Patients with diabetic kidney disease (DKD) are at increased risk for cardiovascular events but traditional risk factors do not fully explain this association. Evaluation of subclinical vascular disease might improve risk stratification and management of these patients. The aim of the study was to compare the prevalence of markers of arterial stiffness, carotid atherosclerosis and peripheral arterial disease between patients with DKD and patients with type 2 diabetes mellitus (T2DM) and preserved kidney function. Methods: We prospectively enrolled patients with DKD and age- and gender-matched patients with T2DM but without DKD (estimated glomerular filtration rate < and ≥60 mL/min/1.73 m2, respectively). The presence of arterial stiffness was evaluated by measuring pulse wave velocity (PWV), augmentation index (AIx), AIx adjusted to a heart rate of 75 beats/min (AIx@75) and central systolic, diastolic, pulse and mean blood pressure. The presence of carotid atherosclerosis was evaluated by measuring carotid stenosis, carotid intima-media thickness and maximal plaque thickness. The presence of PAD was evaluated with the measurement of ankle-brachial index (ABI). Results: Forty patients with T2DM were included in the study (mean age 71.6 ± 8.9 years). The prevalence of cardiovascular risk factors was similar in patients with and without DKD. PWV was higher in the former (9.8 ± 5.5 and 6.6 ± 4.4 m/s, respectively; p < 0.05) and carotid stenosis of the left carotid artery was also greater in patients with DKD (36.5 ± 12.6 and 22.1 ± 17.2%, respectively; p < 0.05). Other markers of arterial stiffness and carotid atherosclerosis and ABI did not differ between patients with DKD and those without DKD. Conclusions: Patients with DKD appear to have more pronounced arterial stiffness and carotid atherosclerosis than patients with T2DM and preserved kidney function despite the similar prevalence of traditional cardiovascular risk factors in the two groups. Therefore, evaluating the presence of subclinical vascular disease in these patients could be a useful tool for the personalization of their management.

Clinical Parameters Affecting the Therapeutic Efficacy of SGLT-2—Comparative Effectiveness and Safety of Dapagliflozin and Empagliflozin in Patients with Type 2 Diabetes

(1) Background. We aimed to assess long-term efficacy and safety in inadequately controlled type 2 diabetes (T2DM) of two SGLT-2 inhibitors: empagliflozin (Empa) and dapagliflozin (Dapa), combined with metformin, other oral antidiabetics or insulin, according to the protocols in Romania. (2) Methods. The data of 100 patients treated for T2DM with associated dyslipidemia and/or cardiovascular diseases at the University Hospital and Consultmed Medical Center in Iasi were retrospectively reviewed (2017–2021). In total, 48 patients had received dapagliflozin (10 mg with oral antidiabetics or insulin) and 52 patients received empagliflozin (10 mg /25 mg with oral antidiabetics). (3) Results. In both groups, the lowering of BMI was significant: Dapa group (32.04 ± 4.49 vs. 31.40 ± 4.18 kg/m²; p = 0.006), and Empa group (34.16 ± 5.08 vs. 33.17 ± 4.99 kg/m²; p = 0.002). Blood sugar average levels decreased significantly (170 vs. 136 mg/dL; p = 0.001 for Dapa; 163 vs. 140 mg/dL; p = 0.002 for Empa) and also average levels of HbA1c (7.90% vs. 7.51%; p = 0,01 for Dapa; 7.72% vs. 7.35%; p = 0.004 for Empa). (4) Conclusions. Better results in all variables were observed in younger male patients with a shorter duration of diabetes and threshold BMI levels of 34.1, treated with SGLT2, and more significantly with Empa.

HTR1A Gene Polymorphism in Type 2 Diabetes Mellitus Comorbid with Major Depressive Disorder in a Chinese Population

Background

Major depressive disorder is a frequent mental illness, which is common in patients with type 2 diabetes. Type 2 diabetes comorbid with depression has a worse prognosis. There are multiple risk factors for depression, and genetic studies have shown that gene polymorphism may play an important role in the pathogenesis of depression.

Methods

A total of 874 patients with type 2 diabetes were recruited for this study and divided into two groups: depressive group (DDM group, n = 234) and non-depressive group (NDDM group, n = 640). HTR1A gene polymorphisms (rs6295, rs878567, rs1800044) genotyping work was performed using a custom by design 48-Plex SNPscanTM Kit.

Results

The rs6295, rs878567, and rs1800044 SNPs were not associated with type 2 diabetes comorbid with depression. Female sex, age, and FBG level increased the risk of depression in patients with type 2 diabetes.

Conclusion

HTR1A rs6295, rs878567, and rs1800044 SNPs polymorphism is not associated with type 2 diabetes comorbid with depression. Rather, female sex, age, and FBG level are risk factors for depression among patients with type 2 diabetes. Larger studies are needed to further confirm our findings.

The Importance of Patient and Family Engagement, the Needs for Self-Monitoring of Blood Glucose (SMBG) - Our Perspectives Learned Through a Story of SMBG Assistive Devices Made by a Husband of the Patient with Diabetes

Despite some negative reports regarding the need for the self-monitoring of blood glucose (SMBG), including the issue of cost-effectiveness, there are still many users, and in diabetes treatment, which is largely dependent on the patient's self-care, SMBG remains an important tool in establishing such self-care habits, with several reports supporting this notion. In addition, devices are needed to assist in SMBG for patients with diabetes who have difficulty performing SMBG, such as the elderly or those with visual impairment. In current diabetes care, it is reported that patient-centered care that respects the preferences, needs, and values of individual patients and personalized care that consider the characteristics and comorbidities of each patient are important. Through a case study of a patient with diabetes who had difficulty performing SMBG due to visual impairment, we learned of the needs of SMBG and its assistive devices and the importance of patient and family engagement with emphasis on patient-centered and personalized care. We herein report what we learned through this case in the form of perspectives. Through this report, we hope that medical professionals involved in diabetes care will learn of the importance and needs of these issues and apply them to their actual clinical practice.