Practical Classification Guidelines for Diabetes in patients treated with insulin: a cross-sectional study of the accuracy of diabetes diagnosis

Real-world study of the multimorbidity and health service utilisation among individuals with non-diabetic hyperglycemia and type 2 diabetes mellitus in North West London

INTRODUCTION

The prevalence of non-diabetic hyperglycemia (NDH) and type 2 diabetes mellitus (T2DM) is increasing. While T2DM is recognised to be associated with multimorbidity and early mortality, people with NDH are frequently thought to be devoid of such complications, potentially exposing individuals with NDH to suboptimal care. We therefore used the Discover London Secure Data Environment (SDE) dataset to appreciate the relationship of NDH/T2DM with multimorbidity, healthcare usage, and clinical outcomes.

RESEARCH DESIGN AND METHODS

The dataset was retrospectively analysed between January 1, 2015 and December 31, 2020 to understand the relationship between NDH/T2DM and multimorbidity primary/secondary healthcare usage and clinical outcomes. This was compared with a cohort of individuals with thyroid disease but no NDH/T2DM.

RESULTS

The dataset identified 152,384 and 124,190 adults with NDH and T2DM compared with 11,626 individuals with thyroid disease (control group). Individuals with NDH and individuals with T2DM had a high burden of disease, with only 13.1% of individuals with either NDH or T2DM not found to be suffering from at least one of the disease states of interest. The three most common comorbidities experienced by individuals with NDH were hypertension (41.4%), hypercholesterolemia (37.5%), and obesity (29.8%) compared with retinopathy (68.7%), hypertension (59.4%), and obesity (45.8%) in individuals with T2DM. Comparatively, the most common comorbidities in the control group were depression (30.8%), hypercholesterolemia (24.4%), and hypertension (17.1%). 28 (control group), 12 (NDH), and 16 (T2DM) primary care contacts per individual per year were identified, with 27,881, 282,371, and 314,880 inpatient admissions for the control, NDH, and T2DM cohorts, respectively. Prescription of drugs used to treat T2DM in individuals with NDH and T2DM was 27,772 (18.2%) and 109,361 (88.1%), respectively, accounting for approximately one in five individuals with NDH developing T2DM.

CONCLUSION

Both NDH and T2DM were associated with significant multimorbidity alongside primary and secondary care utilisation. Given the morbidity highlighted with NDH, we highlight the need for earlier detection of NDH, recognition of multimorbidity associated with both NDH and T2DM, as well as the need for the further implementation of interventions to prevent progression to T2DM/multimorbidity.

Prevalence of Adult Type 2 Diabetes Mellitus and Related Complications in Alberta, Canada: A Retrospective, Observational Study Using Administrative Data

OBJECTIVES

Type 2 diabetes mellitus (T2DM) is a prevalent chronic disease and a leading cause of morbidity/mortality in Canada. We evaluated the burden of T2DM in Alberta, Canada, by estimating the 5-year period prevalence of T2DM and rates of comorbidities and complications/conditions after T2DM.

METHODS

We conducted a population-based, retrospective study linking administrative health databases. Individuals with T2DM (≥18 years of age) were identified between 2008-2009 and 2018-2019 using a published algorithm, with follow-up data to March 2020. The 5-year period prevalence was estimated for 2014-2015 to 2018-2019. Individuals with newly identified T2DM, ascertained between 2010-2011 and 2017-2018 with a lookback period between 2008-2009 and 2009-2010 and a minimum 1 year of follow-up data, were evaluated for subsequent cardiovascular, diabetic, renal, and other complication/condition frequencies (%) and rates (per 100 person-years). Complications/conditions were stratified by atherosclerotic cardiovascular disease (ASCVD) status at index and age.

RESULTS

The 5-year period prevalence of T2DM was 11,051 per 100,000 persons, with the highest prevalence in men 65 to <75 years of age. There were 195,102 individuals included in the cohort (mean age 56.7±14.7 years). The most frequently reported complications/conditions (rates per 100 person-years) were acute infection (23.10, 95% confidence interval [CI] 23.00 to 23.30), hypertension (17.30, 95% CI 16.80 to 17.70), and dyslipidemia (12.20, 95% CI 11.90 to 12.40). Individuals who had an ASCVD event/procedure and those ≥75 years of age had higher rates of complications/conditions.

CONCLUSIONS

We found that over half of the individuals had hypertension or infection after T2DM. Also, those with ASCVD had higher rates of complications/conditions. Strategies to mitigate complications/conditions after T2DM are required to reduce the burden of this disease on individuals and health-care systems.

Performance of European prediction models for classification of type 1 and type 2 diabetes in Indians

AIM

We aimed to determine the performance of European prediction models in an Indian population to classify type 1 diabetes(T1D) and type 2 diabetes(T2D).

METHODS

We assessed discrimination and calibration of published models of diabetes classification, using retrospective data from electronic medical records of 83309 participants aged 18-50 years living in India. Diabetes type was defined based on C-peptide measurement and early insulin requirement. Models assessed combinations of clinical measurements: age at diagnosis, body mass index(mean = 26.6 kg/m2), sex(male = 64.9 %), Glutamic acid decarboxylase(GAD) antibody, serum cholesterol, serum triglycerides, and high-density lipoprotein(HDL) cholesterol.

RESULTS

67955 participants met inclusion criteria, of whom 0.8 % had T1D, which was markedly lower than model development cohorts. Model discrimination for clinical features was broadly similar in our Indian cohort compared to the European cohort: area under the receiver operating characteristic curve(AUC ROC) was 0.90 vs. 0.90 respectively, but was lower in the subset of young participants with measured GAD antibodies(n = 2404): and an AUC ROC of 0.87 when clinical features, sex, lipids and GAD antibodies were combined. All models substantially overestimated the likelihood of T1D, reflecting the lower prevalence of T1D in the Indian population. However, good model performance was achieved after recalibration by updating the model intercept and slope.

CONCLUSION

Models for diabetes classification maintain the discrimination of T1D and T2D in this Indian population, where T2D is far more common, but require recalibration to obtain appropriate model probabilities. External validation and recalibration are needed before these tools can be used in non-European populations.

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.

Early autoantibody screening for type 1 diabetes: a Kuwaiti perspective on the advantages of multiplexing chemiluminescent assays

Type 1 diabetes (T1D) incidence has increased globally over the last decades, alongside other autoimmune diseases. Early screening of individuals at risk of developing T1D is vital to facilitate appropriate interventions and improve patient outcomes. This is particularly important to avoid life-threatening diabetic ketoacidosis and hospitalization associated with T1D diagnosis. Additionally, considering that new therapies have been developed for T1D, screening the population and individuals at high risk would be of great benefit. However, adopting such screening approaches may not be feasible due to limitations, such as cost, adaptation of such programs, and sample processing. In this perspective, we explore and highlight the use of multiplexing chemiluminescent assays for T1D screening and emphasize on their advantages in detecting multiple autoantibodies simultaneously, maximizing efficiency, and minimizing sample volume requirements. These assays could be extremely valuable for pediatric populations and large-scale screening initiatives, providing a cost-efficient solution with increased diagnostic accuracy and deeper insights into T1D pathogenesis. Eventually, the adoption of such screening methods can help transform T1D diagnosis, especially in countries with high T1D prevalence, such as Kuwait, which will contribute to the development of novel therapeutic interventions, positively impacting the lives of those affected by T1D and other autoimmune diseases.

Evaluation of polygenic risk scores to differentiate between type 1 and type 2 diabetes

Polygenic risk scores (PRS) quantify the genetic liability to disease and are calculated using an individual's genotype profile and disease-specific genome-wide association study (GWAS) summary statistics. Type 1 (T1D) and type 2 (T2D) diabetes both are determined in part by genetic loci. Correctly differentiating between types of diabetes is crucial for accurate diagnosis and treatment. PRS have the potential to address possible misclassification of T1D and T2D. Here we evaluated PRS models for T1D and T2D in European genetic ancestry participants from the UK Biobank (UKB) and then in the Michigan Genomics Initiative (MGI). Specifically, we investigated the utility of T1D and T2D PRS to discriminate between T1D, T2D, and controls in unrelated UKB individuals of European ancestry. We derived PRS models using external non-UKB GWAS. The T1D PRS model with the best discrimination between T1D cases and controls (area under the receiver operator curve [AUC] = 0.805) also yielded the best discrimination of T1D from T2D cases in the UKB (AUC = 0.792) and separation in MGI (AUC = 0.686). In contrast, the best T2D model did not discriminate between T1D and T2D cases (AUC = 0.527). Our analysis suggests that a T1D PRS model based on independent single nucleotide polymorphisms may help differentiate between T1D, T2D, and controls in individuals of European genetic ancestry.

Reclassification of type 2 diabetes to type 1 diabetes in Asturias (Spain) between 2011 and 2020

BACKGROUND

Differentiating between type 1 diabetes (T1D) and type 2 diabetes (T2D) can be difficult in adults. The aim of this study was to determine the frequency of diagnostic reclassification from T2D to T1D, the characteristics of the patients and the impact on the management of the disease.

METHODS

Observational and descriptive study including patients diagnosed with T1D in Asturias (Spain) between 2011 and 2020 who had been considered as T2D for at least 12 months.

RESULTS

A total of 205 patients were included, representing 45.3% of those diagnosed with T1D over 30 years of age. Median time of evolution as T2D was 7,8 years. The age was 59.1 ± 12.9 years. BMI was > 25 kg/m² in 46.8% of patients. HbA1c was 9.1 ± 2.1%, 77 ± 22 mmol/mol, and 56.5% were using insulin. Pancreatic antibodies were present in 95.5%, the most frequent being GAD, 82.6%. At 6 months, basal insulin use increased from 46.9 to 86.3%, and HbA1c decreased, 9.2 ± 2.0%vs7.7 ± 1.2%, 77 ± 22vs60 ± 13 mmol/mol; p < 0.0001.

CONCLUSIONS

Diagnosis as T2D in patients with T1D in adults is common. Age, BMI, insulin use and other clinical features are not definitely discriminatory. GAD is the antibody of choice in case of diagnostic suspect. Reclassification has important implications for metabolic control.

The phenotype of type 1 diabetes in sub-Saharan Africa

The phenotype of type 1 diabetes in Africa, especially sub-Saharan Africa, is poorly understood. Most previously conducted studies have suggested that type 1 diabetes may have a different phenotype from the classical form of the disease described in western literature. Making an accurate diagnosis of type 1 diabetes in Africa is challenging, given the predominance of atypical diabetes forms and limited resources. The peak age of onset of type 1 diabetes in sub-Saharan Africa seems to occur after 18-20 years. Multiple studies have reported lower rates of islet autoantibodies ranging from 20 to 60% amongst people with type 1 diabetes in African populations, lower than that reported in other populations. Some studies have reported much higher levels of retained endogenous insulin secretion than in type 1 diabetes elsewhere, with lower rates of type 1 diabetes genetic susceptibility and HLA haplotypes. The HLA DR3 appears to be the most predominant HLA haplotype amongst people with type 1 diabetes in sub-Saharan Africa than the HLA DR4 haplotype. Some type 1 diabetes studies in sub-Saharan Africa have been limited by small sample sizes and diverse methods employed. Robust studies close to diabetes onset are sparse. Large prospective studies with well-standardized methodologies in people at or close to diabetes diagnosis in different population groups will be paramount to provide further insight into the phenotype of type 1 diabetes in sub-Saharan Africa.

2. Classification and Diagnosis of Diabetes: Standards of Care in Diabetes-2023

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, a multidisciplinary 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.

Identifying type 1 and 2 diabetes in research datasets where classification biomarkers are unavailable: assessing the accuracy of published approaches

OBJECTIVES

We aimed to compare the performance of approaches for classifying insulin-treated diabetes within research datasets without measured classification biomarkers, evaluated against two independent biological definitions of diabetes type.

STUDY DESIGN AND SETTING

We compared accuracy of ten reported approaches for classifying insulin-treated diabetes into type 1 (T1D) and type 2 (T2D) diabetes in two cohorts: UK Biobank (UKBB) n = 26,399 and Diabetes Alliance for Research in England (DARE) n = 1,296. The overall performance for classifying T1D and T2D was assessed using: a T1D genetic risk score and genetic stratification method (UKBB); C-peptide measured at >3 years diabetes duration (DARE).

RESULTS

Approaches' accuracy ranged from 71% to 88% (UKBB) and 68% to 88% (DARE). When classifying all participants, combining early insulin requirement with a T1D probability model (incorporating diagnosis age and body image issue [BMI]), and interview-reported diabetes type (UKBB available in only 15%) consistently achieved high accuracy (UKBB 87% and 87% and DARE 85% and 88%, respectively). For identifying T1D with minimal misclassification, models with high thresholds or young diagnosis age (<20 years) had highest performance. Findings were incorporated into an online tool identifying optimum approaches based on variable availability.

CONCLUSION

Models combining continuous features with early insulin requirement are the most accurate methods for classifying insulin-treated diabetes in research datasets without measured classification biomarkers.

Routine Islet Autoantibody Testing in Clinically Diagnosed Adult-Onset Type 1 Diabetes Can Help Identify Misclassification and the Possibility of Successful Insulin Cessation

OBJECTIVE

Recent joint American Diabetes Association and European Association for the Study of Diabetes guidelines recommend routine islet autoantibody testing in all adults newly diagnosed with type 1 diabetes. We aimed to assess the impact of routine islet autoantibody testing in this population.

RESEARCH DESIGN AND METHODS

We prospectively assessed the relationship between islet autoantibody status (GADA, IA-2A, and ZNT8A), clinical and genetic characteristics, and progression (annual change in urine C-peptide-to-creatinine ratio [UCPCR]) in 722 adults (≥18 years old at diagnosis) with clinically diagnosed type 1 diabetes and diabetes duration <12 months. We also evaluated changes in treatment and glycemia over 2 years after informing participants and their clinicians of autoantibody results.

RESULTS

Of 722 participants diagnosed with type 1 diabetes, 24.8% (179) were autoantibody negative. This group had genetic and C-peptide characteristics suggestive of a high prevalence of nonautoimmune diabetes: lower mean type 1 diabetes genetic risk score (islet autoantibody negative vs. positive: 10.85 vs. 13.09 [P < 0.001] [type 2 diabetes 10.12]) and lower annual change in C-peptide (UCPCR), -24% vs. -43% (P < 0.001).After median 24 months of follow-up, treatment change occurred in 36.6% (60 of 164) of autoantibody-negative participants: 22.6% (37 of 164) discontinued insulin, with HbA1c similar to that of participants continuing insulin (57.5 vs. 60.8 mmol/mol [7.4 vs. 7.7%], P = 0.4), and 14.0% (23 of 164) added adjuvant agents to insulin.

CONCLUSIONS

In adult-onset clinically diagnosed type 1 diabetes, negative islet autoantibodies should prompt careful consideration of other diabetes subtypes. When routinely measured, negative antibodies are associated with successful insulin cessation. These findings support recent recommendations for routine islet autoantibody assessment in adult-onset type 1 diabetes.

Developing services to support the delivery of care to people with early-onset type 2 diabetes

Early-onset type 2 diabetes occurring in childhood or early adulthood carries a significant excess burden of microvascular diabetes complications, cardiovascular disease and premature death, compared to later onset type 2 diabetes along with adverse pregnancy outcomes in women of child-bearing age. National audit data in England reveal that 122,780 individuals under the age of 40 years are currently living with type 2 diabetes, with an over-representation of people from minority ethnicities and those in the most socioeconomically deprived quintiles. A diagnosis of type 2 diabetes earlier in life poses some unique challenges to healthcare providers that are not routinely encountered when type 2 diabetes presents later. These include; (1) the need to ensure correct diabetes classification in an age group that carries a higher probability of other types of diabetes, (2) overcoming difficulties in engaging with individuals who are of working age or in full-time education, (3) appreciating and addressing the lower attainment of diabetes treatment targets and (4) proactively supporting women of child-bearing age to optimise their future pregnancy outcomes through better preparation for pregnancy, including achieving optimum glycaemic control at the time of conception. Meanwhile, approaches to prevent type 2 diabetes in younger age groups are challenged by difficulties in identifying those at highest risk, by poorer attendance at lifestyle interventions to prevent or delay the onset of type 2 diabetes and by attenuation of associated weight loss in those that do attend. In this article, we discuss the importance of recognising and addressing the distinct challenges in delivering healthcare to those with early-onset type 2 diabetes, the greater challenges in preventing type 2 diabetes at younger ages, and key components of strategies that might address these challenges to drive improvements in pregnancy outcomes, microvascular and cardiovascular outcomes.

Diabetes Mellitus: An Overview in Relationship to Charcot Neuroarthropathy

Diabetes mellitus with the lack of glycemic control increases risks for developing comorbidities affecting organ systems responsible for critical function. The development of diabetic neuropathy predisposes patients to the onset of Charcot neuroarthropathy (CN). There is significant complexity with treatment of diabetic-induced CN, which can have an often delayed or missed diagnosis. Supervision and treatment from trained specialists are required to provide care for this multifaceted disease process. It is essential for patients to partner with glucose control, comorbidity prevention and care, as well as lower extremity management. Ultimately, CN can result in significant lower extremity deformity placing patients at risk of limb and life.

Role of Liver Enzymes in the Relationship Between Particulate Matter Exposure and Diabetes Risk: A Longitudinal Cohort Study

CONTEXT

Particulate matter (PM) is an important risk factor for diabetes. However, its underlying mechanisms remain poorly understood. Although liver-derived biological intermediates may play irreplaceable roles in the pathophysiology of diabetes, few studies have explored this in the association between PM and diabetes.

OBJECTIVE

We investigated the role of liver enzymes in mediating the relationship between PM exposure and diabetes.

METHODS

We included a total of 7963 participants from the China Multi-Ethnic Cohort. Residential exposure to PM was assessed using a validated spatial-temporal assessment method. Diabetes was diagnosed according to the criteria from American Diabetes Association. Associations between PM, liver enzyme [including alanine aminotransferase (ALT), aspartate aminotransferase, alkaline phosphatase, and γ-glutamyl transpeptidase (GGT)], and diabetes were estimated using multivariable regression models. The function of liver enzymes in the relationship between PM and diabetes was assessed using mediation analysis.

RESULTS

PM exposure was positively associated with the odds of diabetes, with odds ratios of 1.32 (95% CI 0.83, 2.09), 1.33 (95% CI 1.07, 1.65), and 1.18 (95% CI 1.02, 1.36) for every 10-μg/m3 increment in ≤1 μm (PM1), ≤2.5 μm (PM2.5), and ≤10 μm (PM10) PM, respectively. ALT (4.47%) and GGT (4.78%) exhibited statistically significant mediation effects on the association between PM2.5 and diabetes, and the ALT (4.30%) also had a mediating role on PM10. However, none of the liver enzymes had a significant mediating effect on PM1.

CONCLUSION

The relationship between PM and diabetes is partially mediated by liver enzymes, suggesting that lipid accumulation, oxidative stress, and chronic inflammation in the liver may be involved in its pathogenesis.

The Protective Effects of Neurotrophins and MicroRNA in Diabetic Retinopathy, Nephropathy and Heart Failure via Regulating Endothelial Function

Diabetes mellitus is a common disease affecting more than 537 million adults worldwide. The microvascular complications that occur during the course of the disease are widespread and affect a variety of organ systems in the body. Diabetic retinopathy is one of the most common long-term complications, which include, amongst others, endothelial dysfunction, and thus, alterations in the blood-retinal barrier (BRB). This particularly restrictive physiological barrier is important for maintaining the neuroretina as a privileged site in the body by controlling the inflow and outflow of fluid, nutrients, metabolic end products, ions, and proteins. In addition, people with diabetic retinopathy (DR) have been shown to be at increased risk for systemic vascular complications, including subclinical and clinical stroke, coronary heart disease, heart failure, and nephropathy. DR is, therefore, considered an independent predictor of heart failure. In the present review, the effects of diabetes on the retina, heart, and kidneys are described. In addition, a putative common microRNA signature in diabetic retinopathy, nephropathy, and heart failure is discussed, which may be used in the future as a biomarker to better monitor disease progression. Finally, the use of miRNA, targeted neurotrophin delivery, and nanoparticles as novel therapeutic strategies is highlighted.

Diagnostic Test Accuracy of Urine C-peptide Creatinine Ratio for the Correct Identification of the Type of Diabetes: A Systematic Review

Objective: To examine the accuracy of urine c-peptide creatinine ratio (UCPCR) for identifying the type of diabetes in appropriate clinical settings. Design: Systematic review of test accuracy studies on patients with different forms of diabetes. Data sources: Medline, Embase and Cochrane library databases from 1 January 2000 to 15 November 2020. Eligibility criteria: Studies reporting the use of UCPCR for diagnosing patients with type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM) and monogenic forms of diabetes (categorized as maturity-onset diabetes of the young [MODY]). Study selection and data synthesis: Two reviewers independently assessed articles for inclusion and assessed the methodological quality of the studies using the Quality Assessment of Diagnostic Accuracy Studies-2 tool, with input from a third reviewer to reach consensus when there was a dispute. Meta-analysis was performed with the studies reporting complete data to derive the pooled sensitivity, specificity and diagnostic odds ratio (DOR), and narrative synthesis only for those with incomplete data. Results: Nine studies with 4,488 patients were included in the qualitative synthesis, while only four of these (915 patients) had complete data and were included in the quantitative synthesis. All the studies had moderate risk of bias and applicability concerns. Meta-analysis of three studies (n=130) revealed sensitivity, specificity and DOR of 84.4% (95% confidence interval [CI] 68.1-93.2%), 91.6% (82.8-96.1%) and 59.9 (32.8-106.0), respectively, for diagnosing T1DM using a UCPCR cut-off of <0.2 nmol/mmol. For participants with T2DM (three studies; n=739), UCPCR >0.2 nmol/mmol was associated with sensitivity, specificity and DOR of 92.8% (84.2-96.9%), 81.6% (61.3-92.5%) and 56.9 (31.3-103.5), respectively. For patients with MODY in the appropriate clinical setting, a UCPCR cut-off of >0.2 nmol/mmol showed sensitivity, specificity and DOR of 85.2% (73.1-92.4%), 98.0% (92.4-99.5%) and 281.8 (57.5-1,379.7), respectively. Conclusions: Based on studies with moderate risk of bias and applicability concerns, UCPCR confers moderate to high sensitivity, specificity, and DOR for correctly identifying T1DM, T2DM and monogenic diabetes in appropriate clinical settings. Large multinational studies with multi-ethnic participation among different age groups are necessary before this test can be routinely used in clinical practice. Study registration: Protocol was registered as PROSPERO CRD42017060633.

The Incidence of Adult-Onset Type 1 Diabetes: A Systematic Review From 32 Countries and Regions

BACKGROUND

The epidemiology of adult-onset type 1 diabetes (T1D) incidence is not well-characterized due to the historic focus on T1D as a childhood-onset disease.

PURPOSE

We assess the incidence of adult-onset (≥20 years) T1D, by country, from available data.

DATA SOURCES

A systematic review of MEDLINE, Embase, and the gray literature, through 11 May 2021, was undertaken.

STUDY SELECTION

We included all population-based studies reporting on adult-onset T1D incidence and published from 1990 onward in English.

DATA EXTRACTION

With the search we identified 1,374 references of which 46 were included for data extraction. Estimates of annual T1D incidence were allocated into broad age categories (20-39, 40-59, ≥60, or ≥20 years) as appropriate.

DATA SYNTHESIS

Overall, we observed the following patterns: 1) there is a paucity of data, particularly in low- and middle-income countries; 2) the incidence of adult-onset T1D is lowest in Asian and highest in Nordic countries; 3) adult-onset T1D is higher in men versus women; 4) it is unclear whether adult-onset T1D incidence declines with increasing age; and 5) it is unclear whether incidence of adult-onset T1D has changed over time.

LIMITATIONS

Results are generalizable to high-income countries, and misclassification of diabetes type cannot be ruled out.

CONCLUSIONS

From available data, this systematic review suggests that the incidence of T1D in adulthood is substantial and highlights the pressing need to better distinguish T1D from T2D in adults so that we may better assess and respond to the true burden of T1D in adults.

Recent Updates to Clinical Practice Guidelines for Diabetes Mellitus

Guidelines for the management of patients with diabetes have become an important part of clinical practice that improve the quality of care and help establish evidence-based medicine in this field. With rapidly accumulating evidence on various aspects of diabetes care, including landmark clinical trials of treatment agents and newer technologies, timely updates of the guidelines capture the most current state of the field and present a consensus. As a leading academic society, the Korean Diabetes Association publishes practice guidelines biennially and the American Diabetes Association does so annually. In this review, we summarize the key changes suggested in the most recent guidelines. Some of the important updates include treatment algorithms emphasizing comorbid conditions such as atherosclerotic cardiovascular disease, heart failure, and chronic kidney disease in the selection of anti-diabetic agents; wider application of continuous glucose monitoring (CGM), insulin pump technologies and indices derived from CGM such as time in range; more active screening of subjects at high-risk of diabetes; and more detailed individualization in diabetes care. Although there are both similarities and differences among guidelines and some uncertainty remains, these updates provide a good approach for many clinical practitioners who are battling with diabetes.

Non-coding RNAs in diabetes mellitus and diabetic cardiovascular disease

More than 10% of the world's population already suffers from varying degrees of diabetes mellitus (DM), but there is still no cure for the disease. Cardiovascular disease (CVD) is one of the most common and dangerous of the many health complications that can be brought on by DM, and has become the leading cause of death in people with diabetes. While research on DM and associated CVD is advancing, the specific mechanisms of their development are still unclear. Given the threat of DM and CVD to humans, the search for new predictive markers and therapeutic ideas is imminent. Non-coding RNAs (ncRNAs) have been a popular subject of research in recent years. Although they do not encode proteins, they play an important role in living organisms, and they can cause disease when their expression is abnormal. Numerous studies have observed aberrant ncRNAs in patients with DM complications, suggesting that they may play an important role in the development of DM and CVD and could potentially act as biomarkers for diagnosis. There is additional evidence that treatment with existing drugs for DM, such as metformin, alters ncRNA expression levels, suggesting that regulation of ncRNA expression may be a key mechanism in future DM treatment. In this review, we assess the role of ncRNAs in the development of DM and CVD, as well as the evidence for ncRNAs as potential therapeutic targets, and make use of bioinformatics to analyze differential ncRNAs with potential functions in DM.

Antiplatelet and Antithrombotic Therapy in Type I Diabetes Mellitus: Update on Current Data

Diabetes mellitus type 1 (T1DM) is an autoimmune disease characterized by a markedly elevated cardiovascular (CV) risk due to premature atherosclerosis. Previous studies have shown that intense glycemic control reduces the incidence of CV disease. Antiplatelet therapy is considered to be a very important therapy for secondary prevention of recurrent atherothrombotic events in patients with DM, while it may be considered for primary prevention in individuals with T1DM with additional CV risk factors. The aim of the present review is to summarize existing literature data regarding the thrombotic risk in T1DM patients and discuss current treatment strategies.

2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2022

The American Diabetes Association (ADA) "Standards of Medical 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, a multidisciplinary expert committee (https://doi.org/10.2337/dc22-SPPC), 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, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc22-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Replacing insulin with immunotherapy: Time for a paradigm change in Type 1 diabetes

For almost a hundred years, the management of Type 1 diabetes has not advanced beyond insulin replacement. However, insulin does not provide satisfactory glycaemic control in the majority of individuals and there remains a major unmet need for novel treatments for Type 1 diabetes. Immunomodulation to preserve beta-cell function offers the prospect of making treatment with insulin easier and/or preventing the need for insulin, particularly when it comes to novel low-risk immunotherapies. Led by the concept that the best insulin-producing cell is a patient's own beta-cell, the Type 1 diabetes scientific community has a challenging task ahead-to fundamentally change the management of this devastating disease by using low-risk immunotherapy to preserve endogenous beta-cell function and make metabolic control substantially easier. In that way, insulin and/or beta-cell replacement (stem cell or transplantation) should in the future be considered rescue therapies reserved for delayed presentations.

The management of type 1 diabetes in adults. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)

The American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) convened a writing group to develop a consensus statement on the management of type 1 diabetes in adults. The writing group has considered the rapid development of new treatments and technologies and addressed the following topics: diagnosis, aims of management, schedule of care, diabetes self-management education and support, glucose monitoring, insulin therapy, hypoglycaemia, behavioural considerations, psychosocial care, diabetic ketoacidosis, pancreas and islet transplantation, adjunctive therapies, special populations, inpatient management and future perspectives. Although we discuss the schedule for follow-up examinations and testing, we have not included the evaluation and treatment of the chronic microvascular and macrovascular complications of diabetes as these are well-reviewed and discussed elsewhere. The writing group was aware of both national and international guidance on type 1 diabetes and did not seek to replicate this but rather aimed to highlight the major areas that healthcare professionals should consider when managing adults with type 1 diabetes. Though evidence-based where possible, the recommendations in the report represent the consensus opinion of the authors. Graphical abstract.

The Management of Type 1 Diabetes in Adults. A Consensus Report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)

The American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) convened a writing group to develop a consensus statement on the management of type 1 diabetes in adults. The writing group has considered the rapid development of new treatments and technologies and addressed the following topics: diagnosis, aims of management, schedule of care, diabetes self-management education and support, glucose monitoring, insulin therapy, hypoglycemia, behavioral considerations, psychosocial care, diabetic ketoacidosis, pancreas and islet transplantation, adjunctive therapies, special populations, inpatient management, and future perspectives. Although we discuss the schedule for follow-up examinations and testing, we have not included the evaluation and treatment of the chronic microvascular and macrovascular complications of diabetes as these are well-reviewed and discussed elsewhere. The writing group was aware of both national and international guidance on type 1 diabetes and did not seek to replicate this but rather aimed to highlight the major areas that health care professionals should consider when managing adults with type 1 diabetes. Though evidence-based where possible, the recommendations in the report represent the consensus opinion of the authors.

Does myopia decrease the risk of diabetic retinopathy in both type-1 and type-2 diabetes mellitus?

Purpose

To study the relationship between the severity of myopia and the severity of diabetic retinopathy (DR) in individuals with type 1 or type 2 diabetes mellitus (DM).

Methods

This retrospective study was conducted using data from electronic medical records from a multicentric eyecare network located in various geographic regions of India. Individuals with type 1 or type 2 DM were classified according to their refractive status. Severe nonproliferative DR (NPDR), PDR, or presence of clinically significant macular edema (CSME) with any type of DR was considered as vision-threatening diabetic retinopathy (VTDR).

Results

A total of 472 individuals with type-1 DM (mean age 41 ± 10 years) and 9341 individuals with type-2 DM (52 ± 9 years) were enrolled. Individuals with a hyperopic refractive error had a significant positive association with the diagnosis of VTDR (odds ratio (OR) 1.26; 95%CI 1.04-1.51, P = 0.01) and moderate nonproliferative DR (OR 1.27; 95%CI 1.02-1.59, P = 0.03) in type-2 DM; however, no significant association was found in type-1 DM. After adjusting for age, gender, anisometropia, and duration of diabetes, the presence of high myopia (< - 6 D) reduced the risk of VTDR in type 2 DM (OR 0.18; 95% CI 0.04-0.77, P = 0.02), but no association was found in type 1 DM. Mild and moderate myopia had no significant association with any forms of DR in both type-1 and type-2 DM.

Conclusion

Hyperopic refractive error was found to increase the risk of VTDR in persons with type 2 DM. High-myopic refractive error is protective for VTDR in type 2 DM, but not in type-1 DM.

Impact of routine clinic measurement of serum C-peptide in people with a clinician-diagnosis of type 1 diabetes

AIMS/HYPOTHESIS

The aim of this study was to determine the impact of the routine use of serum C-peptide in an out-patient clinic setting on individuals with a clinician-diagnosis of type 1 diabetes.

METHODS

In this single-centre study, individuals with type 1 diabetes of at least 3 years duration were offered random serum C-peptide testing at routine clinic review. A C-peptide ≥200 pmol/L prompted further evaluation of the individual using a diagnostic algorithm that included measurement of islet cell antibodies and genetic testing. Where appropriate, a trial of anti-diabetic co-therapies was considered.

RESULTS

Serum C-peptide testing was performed in 859 individuals (90% of the eligible cohort), of whom 114 (13.2%) had C-peptide ≥200 pmol/L. The cause of diabetes was reclassified in 58 individuals (6.8% of the tested cohort). The majority of reclassifications were to type 2 diabetes (44 individuals; 5.1%), with a smaller proportion of monogenic diabetes (14 individuals; 1.6%). Overall, 13 individuals (1.5%) successfully discontinued insulin, while a further 16 individuals (1.9%) had improved glycaemic control following the addition of co-therapies. The estimated total cost of the testing programme was £23,262 (~€26,053), that is, £27 (~€30) per individual tested. In current terms, the cost of prior insulin therapy in the individuals with monogenic diabetes who successfully stopped insulin was approximately £57,000 (~€64,000).

CONCLUSIONS/INTERPRETATION

Serum C-peptide testing can easily be incorporated into an out-patient clinic setting and could be a cost-effective intervention. C-peptide testing should be strongly considered in individuals with a clinician-diagnosis of type 1 diabetes of at least 3 years duration.

When Inappropriate Use of Insulin is Dangerous: The Utility of C-Peptide Assay in the Era of Cardioprotective Antidiabetic Drugs

INTRODUCTION

New antidiabetic drugs have simplified treatment regimens in patients with type-2 diabetes (T2D). More importantly, they have proven to reduce cardiovascular risk by lowering insulin-resistance, blood pressure and body weight, in addition to avoiding inappropriate insulin therapy, responsible for hypoglycemic episodes and weight gain. In this context, accurate assessment of the metabolic status of T2D patients becomes essential. The C-peptide assay is a simple but often overlooked test that can provide a fundamental contribution to the correct disease classification and optimal therapeutic management of diabetic patients.

CLINICAL CASE

We report the case of a 72-year-old patient, treated with insulin for 26 years after a diagnosis of type-1 diabetes (T1D), resulting in inadequate glycemia control and a severe evolution of cardiovascular complications. After an accurate evaluation of the clinical history, phenotype and laboratory data, including the determination of C-peptide serum levels, a diagnosis was made of T2D not T1D. Considering the patient's very high cardiovascular risk and dysmetabolic profile, insulin therapy was discontinued and more appropriate therapy with dulaglutide and metformin was instituted. These overall therapeutic modifications yielded remarkable clinical advantages in terms of the glycometabolic profile, weight reduction, abdominal circumference and body mass index decrease, as well as a better quality of life, with complete resolution of the dangerous hypoglycemic episodes.

CONCLUSION

In the era of new cardioprotective antidiabetic drugs, we believe the importance of the C-peptide assay should be re-evaluated in order to avoid misdiagnosis and to improve the therapeutic approach to T2D.

2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2021

The American Diabetes Association (ADA) "Standards of Medical 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, a multidisciplinary expert committee (https://doi.org/10.2337/dc21-SPPC), 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, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc21-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Modified Cornell electrocardiographic criteria in the assessment of left ventricular hypertrophy geometry of patients with essential hypertension

To evaluate the value of modified Cornell electrocardiographic criteria in the assessment of left ventricular hypertrophy (LVH) for patients with essential hypertension. A total of 381 patients with essential hypertension diagnosed in our hospital were selected. Using the left ventricle (LV) geometric patterns classified by the American Society of Echocardiography (ASE), we examined the distribution of the modified Cornell criteria of Ravl + S_D (the deepest S wave in 12‐lead ECG) in different geometric patterns and analyzed the correlation of modified Cornell criteria with changes in the LV geometric patterns using multiple linear regression analysis. The distribution of modified Cornell criteria, Sokolow‐Lyon criteria (RV5/V6 + SV1), and Cornell criteria (Ravl + SV3) in gender‐specific hypertensive geometric patterns were significantly different (P ≤ .01 for all). The voltage of Ravl + S_D in male patients showed an increase trend in the normal geometry (NG), concentric remodeling (CR), concentric hypertrophy (CH), and eccentric hypertrophy (EH) groups, and this increase trend was significantly in the unadjusted model and the adjusted model. The voltages of Ravl + SV3 and RV5/V6 + SV1 of male patients in CR, CH and RH groups showed a gradual increase trend, but the increase trend in CR group has no statistical significance compared to that in NG group (P ≥ .05). The voltages of Ravl + S_D, RV5/V6 + SV1, and Ravl + SV3 in female patients in CR, CH and EH groups showed a trend of increase after decrease in the adjusted model. In conclusion, the modified Cornell criteria could dynamically reflect left ventricular hypertensive geometry of male patients.

Systematic Review of Polygenic Risk Scores for Type 1 and Type 2 Diabetes

Recent studies have led to considerable advances in the identification of genetic variants associated with type 1 and type 2 diabetes. An approach for converting genetic data into a predictive measure of disease susceptibility is to add the risk effects of loci into a polygenic risk score. In order to summarize the recent findings, we conducted a systematic review of studies comparing the accuracy of polygenic risk scores developed during the last two decades. We selected 15 risk scores from three databases (Scopus, Web of Science and PubMed) enrolled in this systematic review. We identified three polygenic risk scores that discriminate between type 1 diabetes patients and healthy people, one that discriminate between type 1 and type 2 diabetes, two that discriminate between type 1 and monogenic diabetes and nine polygenic risk scores that discriminate between type 2 diabetes patients and healthy people. Prediction accuracy of polygenic risk scores was assessed by comparing the area under the curve. The actual benefits, potential obstacles and possible solutions for the implementation of polygenic risk scores in clinical practice were also discussed. Develop strategies to establish the clinical validity of polygenic risk scores by creating a framework for the interpretation of findings and their translation into actual evidence, are the way to demonstrate their utility in medical practice.

2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2020

The American Diabetes Association (ADA) "Standards of Medical 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 (https://doi.org/10.2337/dc20-SPPC), a multidisciplinary 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, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc20-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Development and validation of multivariable clinical diagnostic models to identify type 1 diabetes requiring rapid insulin therapy in adults aged 18-50 years

OBJECTIVE

To develop and validate multivariable clinical diagnostic models to assist distinguishing between type 1 and type 2 diabetes in adults aged 18-50.

DESIGN

Multivariable logistic regression analysis was used to develop classification models integrating five pre-specified predictor variables, including clinical features (age of diagnosis, body mass index) and clinical biomarkers (GADA and Islet Antigen 2 islet autoantibodies, Type 1 Diabetes Genetic Risk Score), to identify type 1 diabetes with rapid insulin requirement using data from existing cohorts.

SETTING

UK cohorts recruited from primary and secondary care.

PARTICIPANTS

1352 (model development) and 582 (external validation) participants diagnosed with diabetes between the age of 18 and 50 years of white European origin.

MAIN OUTCOME MEASURES

Type 1 diabetes was defined by rapid insulin requirement (within 3 years of diagnosis) and severe endogenous insulin deficiency (C-peptide <200 pmol/L). Type 2 diabetes was defined by either a lack of rapid insulin requirement or, where insulin treated within 3 years, retained endogenous insulin secretion (C-peptide >600 pmol/L at ≥5 years diabetes duration). Model performance was assessed using area under the receiver operating characteristic curve (ROC AUC), and internal and external validation.

RESULTS

Type 1 diabetes was present in 13% of participants in the development cohort. All five predictor variables were discriminative and independent predictors of type 1 diabetes (p<0.001 for all) with individual ROC AUC ranging from 0.82 to 0.85. Model performance was high: ROC AUC range 0.90 (95% CI 0.88 to 0.93) (clinical features only) to 0.97 (95% CI 0.96 to 0.98) (all predictors) with low prediction error. Results were consistent in external validation (clinical features and GADA ROC AUC 0.93 (0.90 to 0.96)).

CONCLUSIONS

Clinical diagnostic models integrating clinical features with biomarkers have high accuracy for identifying type 1 diabetes with rapid insulin requirement, and could assist clinicians and researchers in accurately identifying patients with type 1 diabetes.

MALDI-TOF mass spectrometry-based quantification of C-peptide in diabetes patients

BACKGROUND

Serum C-peptide concentrations reflect insulin secretion and beta cell function and can be used to diagnose and distinguish type-1 and type-2 diabetes. C-peptide is a more accurate indicator of insulin status than direct insulin measurement for monitoring patients with diabetes. However, the current methods available for C-peptide quantification exhibit poor reproducibility, are costly, and require highly trained laboratory personnel. Here, we have developed and evaluated a matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS)-based assay to standardize C-peptide measurements, providing highly accurate and comparable results across testing systems and laboratories.

METHODS

C-peptide from human serum was enriched using antibody-conjugated magnetic beads. The eluted isolates were further modified with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) to enhance the ionization of naturally acidic C-peptide. After desalting with ZipTips, the samples were subjected to MALDI-TOF MS analysis. Recombinant human C-peptide was used to develop the assay, and a heavy isotope labeled human C-peptide was used as an internal standard for quantification.

RESULTS

The MALDI-TOF MS method was validated in accordance with the restrictions of the device, with a limit of quantitation of 25 pmol/L. A correlation between the MAL-DI-TOF MS assay and a reference method was conducted using patient samples. The resulting regression revealed good agreement.

CONCLUSIONS

A simple, high-throughput, cost effective and quantitative MALDI-TOF MS C-peptide assay has been successfully developed and validated in clinical serum samples.

Use of human islets to understand islet biology and diabetes: progress, challenges and suggestions

Over the last two decades, improved access to human islets and the development of human islet distribution networks have enabled the use of millions of human islets in hundreds of scientific research projects, leading to a dramatic increase in our understanding of human islet biology. Here we discuss recent scientific advances as well as methodological and experimental challenges that impact human islet quality, experimental outcomes and the reporting of human islets used in scientific publications. In a survey of over 200 scientific publications with human islet experimentation, we found that the reporting of critical information was quite variable, sometimes obscure, and often failed to adequately outline the experiments and results using human islets. As the complexity of human islet research grows, we propose that members of the human islet research ecosystem work together to develop procedures and approaches for accessible and transparent collecting and reporting of crucial human islet characteristics and, through this, enhance collaboration, reproducibility and rigour, leading to further advances in our understanding of human islet biology.

Development and Standardization of an Improved Type 1 Diabetes Genetic Risk Score for Use in Newborn Screening and Incident Diagnosis

OBJECTIVE

Previously generated genetic risk scores (GRSs) for type 1 diabetes (T1D) have not captured all known information at non-HLA loci or, particularly, at HLA risk loci. We aimed to more completely incorporate HLA alleles, their interactions, and recently discovered non-HLA loci into an improved T1D GRS (termed the "T1D GRS2") to better discriminate diabetes subtypes and to predict T1D in newborn screening studies.

RESEARCH DESIGN AND METHODS

In 6,481 case and 9,247 control subjects from the Type 1 Diabetes Genetics Consortium, we analyzed variants associated with T1D both in the HLA region and across the genome. We modeled interactions between variants marking strongly associated HLA haplotypes and generated odds ratios to create the improved GRS, the T1D GRS2. We validated our findings in UK Biobank. We assessed the impact of the T1D GRS2 in newborn screening and diabetes classification and sought to provide a framework for comparison with previous scores.

RESULTS

The T1D GRS2 used 67 single nucleotide polymorphisms (SNPs) and accounted for interactions between 18 HLA DR-DQ haplotype combinations. The T1D GRS2 was highly discriminative for all T1D (area under the curve [AUC] 0.92; P < 0.0001 vs. older scores) and even more discriminative for early-onset T1D (AUC 0.96). In simulated newborn screening, the T1D GRS2 was nearly twice as efficient as HLA genotyping alone and 50% better than current genetic scores in general population T1D prediction.

CONCLUSIONS

An improved T1D GRS, the T1D GRS2, is highly useful for classifying adult incident diabetes type and improving newborn screening. Given the cost-effectiveness of SNP genotyping, this approach has great clinical and research potential in T1D.

REMISSION OF LONGSTANDING INSULIN-TREATED DIABETES MELLITUS FOLLOWING SURGICAL RESECTION OF PHEOCHROMOCYTOMA

Objective

To describe the case of a woman with a longstanding misdiagnosis of type 1 diabetes mellitus (T1DM), in whom diabetes remission was achieved following surgical resection of adrenal pheochromocytoma.

Methods

We present a case report with accompanying biochemical, histologic, and genetic investigation results.

Results

We report the case of a 57-year-old woman with a 13-year history of apparent T1DM, and her presentation with intermittent exertional nausea. An abdominal ultrasound scan identified a rounded heterogeneous mass measuring 120 × 110 × 104 mm superior to her left kidney. Plasma metanephrine levels were markedly elevated with normetaneprhine at 17,856 pmol/L (reference range is 120 to 1,180 pmol/L), metanephrine >25,000 pmol/L (reference range is 80 to 510 pmol/L), 3-methoxytyramine at 1,393 pmol/L (reference range is 0 to 180 pmol/L). The mass demonstrated marked uptake on an iodine-123-meta-iodobenzylguanidine scan. The patient's hypertension was managed with phenoxybenzamine, and she underwent adrenalectomy. Following surgery, she was able to discontinue all diabetes medications and has maintained a hemoglobin A1c value <48 mmol/mol for over 12 months.

Conclusion

The case illustrates that remission of T1DM is possible even after prolonged insulin treatment upon surgical resection of pheochromocytoma. It highlights the potential benefits of reevaluating the diagnostic classification of T1DM in the light of new clinical information.

Genetics of Monogenic Diabetes: Present Clinical Challenges

PURPOSE OF REVIEW

Monogenic forms of diabetes have specific treatments that differ from the standard care provided for type 1 and type 2 diabetes, making the appropriate diagnosis essential. In this review, we discuss current clinical challenges that remain, including improving case-finding strategies, particularly those that have transethnic applicability, and understanding the interpretation of genetic variants as pathogenic, with clinically meaningful impacts.

RECENT FINDINGS

Biomarker approaches to the stratification for genetic testing now appear to be most effective in identifying cases of monogenic diabetes, and use of genetic risk scores may also prove useful. However, applicability in all ethnic groups is lacking. Challenges remain in the classification of genes as diabetes-causing and the interpretation of genetic variants at the clinical interface. Since the discovery that genetic defects can cause neonatal or young-onset diabetes, multiple causal genes have been identified and there have been many advances in strategies to detect genetic forms of diabetes and their treatments. Approaches learnt from monogenic diabetes are now being translated to polygenic diabetes.

Clinical presentation of newly diagnosed diabetes patients in a rural district hospital in Eastern Uganda

Background

Our objective was to describe the clinical presentation of new diabetes patients in a rural hospital, to enhance clinical detection in low resource settings.

Methods

A case series assessment of 103 new diabetes patients consecutively enrolled at Iganga Hospital in rural Eastern Uganda was conducted. All underwent a basic clinical assessment through the clinic's routine procedures. Following diagnosis, variables pertinent to the study (symptoms, blood pressure, anthropometry, and blood glucose) were secondarily abstracted from their clinical records.

Results

Fiftty two percent of new diabetes patients were female. The mean age was 49 years (SD=14.4). Two clinical symptoms were present in almost all new patients: Frequent urination (100%) and frequent thirst (79%). Moderately occurring symptoms (i.e. 25–50% of patients) included blurred vision, frequent eating and frequent sweating. The mean duration of symptoms was 1.4 years; 48% had high blood pressure while 46% were overweight. Random blood sugar was normal for 25% of patients. The majority (71%) were classified as having ‘moderate illness' at diagnosis. Severe illness was significantly lower among patients aged 40 or older compared to younger patients (OR 0.1; 95% CI 0.03–0.35).

Conclusion

Out-patients aged 40–65 years should be prioritised for early diabetes diagnosis and associated risk factors in this setting.

Type 1 diabetes

Type 1 diabetes is a chronic autoimmune disease characterised by insulin deficiency and resultant hyperglycaemia. Knowledge of type 1 diabetes has rapidly increased over the past 25 years, resulting in a broad understanding about many aspects of the disease, including its genetics, epidemiology, immune and β-cell phenotypes, and disease burden. Interventions to preserve β cells have been tested, and several methods to improve clinical disease management have been assessed. However, wide gaps still exist in our understanding of type 1 diabetes and our ability to standardise clinical care and decrease disease-associated complications and burden. This Seminar gives an overview of the current understanding of the disease and potential future directions for research and care.

Clinical and research uses of genetic risk scores in type 1 diabetes

Type 1 diabetes (T1D) is a chronic disease of high blood glucose caused by autoimmune destruction of pancreatic beta cells eventually resulting in severe insulin deficiency. T1D has a significant heritable risk. Genetic associations found are particularly strong in the HLA class II region but T1D is a polygenic disease associated with over 60 loci across the genome. Polygenic risk scores are one method of summing these genetic risk elements as a single continuous variable. This review discusses the clinical and research utility of genetic risk scores in T1D particularly in disease prediction and progression. We also explore creative uses of genetic risk scores in big data and the limitations of using a genetic risk score. The increase in publically available genetic data and rapid fall in costs of genotyping mean that a T1D genetic risk score (T1D GRS) is likely to prove useful for disease prediction, discrimination, investigation of unusual cohorts, and investigation of biology in large datasets where genetic data are available.

Are we missing hypoglycaemia? Elderly patients with insulin-treated diabetes present to primary care frequently with non-specific symptoms associated with hypoglycaemia

INTRODUCTION

We assessed if patients with known hypoglycaemia present on other occasions with non-specific symptoms associated with (but not diagnosed as) hypoglycaemia, potentially representing missed hypoglycaemia.

METHODS

335 primary care records (5/2/12-4/2/13) from patients aged >65 (79 on insulin, 85 on sulphonylureas, 121 on metformin only, 50 without diabetes) were assessed for hypoglycaemia episodes and consultations with non-specific symptoms, "hypo clues".

RESULTS

27/79(34%) insulin-treated patients had >1 documented hypoglycaemia episode, compared to 4/85(5%) sulphonylurea-treated patients, 2/121(2%) metformin-only treated patients, and none without diabetes, p<0.001. "Hypo clue" consultations were common: 1.37 consultations/patient/year in insulin-treated patients, 0.98/patient/year in sulphonylurea-treated, 0.97/patient/year in metformin only-treated, and 0.78/patient/year in non-diabetic patients, p=0.34. In insulin-treated patients with documented hypoglycaemia, 20/27(74%) attended on another occasion with a "hypo clue" symptom, compared to 21/52(40%) of those without hypoglycaemia, p=0.008. No significant difference in the other treatment groups. Nausea, falls and unsteadiness were the most discriminatory symptoms: 7/33(21%) with hypoglycaemia attended on another occasion with nausea compared to 14/302(5%) without hypoglycaemia, p=0.002; 10/33(30%) vs 36/302(12%) with falls, p=0.007; and 5/33(15%) vs 13/302(4%) with unsteadiness, p=0.023.

CONCLUSIONS

Non-specific symptoms are common in those >65 years. In insulin-treated patients at high hypoglycaemia risk, nausea, falls and unsteadiness should prompt consideration of hypoglycaemia.

Frequency and phenotype of type 1 diabetes in the first six decades of life: a cross-sectional, genetically stratified survival analysis from UK Biobank

BACKGROUND

Type 1 diabetes is typically considered a disease of children and young adults. Genetic susceptibility to young-onset type 1 diabetes is well defined and does not predispose to type 2 diabetes. It is not known how frequently genetic susceptibility to type 1 diabetes leads to a diagnosis of diabetes after age 30 years. We aimed to investigate the frequency and phenotype of type 1 diabetes resulting from high genetic susceptibility in the first six decades of life.

METHODS

In this cross-sectional analysis, we used a type 1 diabetes genetic risk score based on 29 common variants to identify individuals of white European descent in UK Biobank in the half of the population with high or low genetic susceptibility to type 1 diabetes. We used Kaplan-Meier analysis to evaluate the number of cases of diabetes in both groups in the first six decades of life. We genetically defined type 1 diabetes as the additional cases of diabetes that occurred in the high genetic susceptibility group compared with the low genetic susceptibility group. All remaining cases were defined as type 2 diabetes. We assessed the clinical characteristics of the groups with genetically defined type 1 or type 2 diabetes.

FINDINGS

13 250 (3·5%) of 379 511 white European individuals in UK Biobank had developed diabetes in the first six decades of life. 1286 more cases of diabetes were in the half of the population with high genetic susceptibility to type 1 diabetes than in the half of the population with low genetic susceptibility. These genetically defined cases of type 1 diabetes were distributed across all ages of diagnosis; 537 (42%) were in individuals diagnosed when aged 31-60 years, representing 4% (537/12 233) of all diabetes cases diagnosed after age 30 years. The clinical characteristics of the group diagnosed with type 1 diabetes when aged 31-60 years were similar to the clinical characteristics of the group diagnosed with type 1 diabetes when aged 30 years or younger. For individuals diagnosed with diabetes when aged 31-60 years, the clinical characteristics of type 1 diabetes differed from those of type 2 diabetes: they had a lower BMI (27·4 kg/m2 [95% CI 26·7-28·0] vs 32·4 kg/m2 [32·2-32·5]; p<0·0001), were more likely to use insulin in the first year after diagnosis (89% [476/537] vs 6% [648/11 696]; p<0·0001), and were more likely to have diabetic ketoacidosis (11% [61/537] vs 0·3% [30/11 696]; p<0·0001).

INTERPRETATION

Genetic susceptibility to type 1 diabetes results in non-obesity-related, insulin-dependent diabetes, which presents throughout the first six decades of life. Our results highlight the difficulty of identifying type 1 diabetes after age 30 years because of the increasing background prevalence of type 2 diabetes. Failure to diagnose late-onset type 1 diabetes can have serious consequences because these patients rapidly develop insulin dependency.

FUNDING

Wellcome Trust and Diabetes UK.

Future Roadmaps for Precision Medicine Applied to Diabetes: Rising to the Challenge of Heterogeneity

Precision medicine, the concept that specific treatments can be targeted to groups of individuals with specific genetic, cellular, or molecular features, is a key aspect of modern healthcare, and its use is rapidly expanding. In diabetes, the application of precision medicine has been demonstrated in monogenic disease, where sulphonylureas are used to treat patients with neonatal diabetes due to mutations in ATP-dependent potassium (K_ATP) channel genes. However, diabetes is highly heterogeneous, both between and within polygenic and monogenic subtypes. Making the correct diagnosis and using the correct treatment from diagnosis can be challenging for clinicians, but it is crucial to prevent long-term morbidity and mortality. To facilitate precision medicine in diabetes, research is needed to develop a better understanding of disease heterogeneity and its impact on potential treatments for specific subtypes. Animal models have been used in diabetes research, but they are not translatable to humans in the majority of cases. Advances in molecular genetics and functional laboratory techniques and availability and sharing of large population data provide exciting opportunities for human studies. This review will map the key elements of future diabetes research in humans and its potential for clinical translation to promote precision medicine in all diabetes subtypes.

Random non-fasting C-peptide testing can identify patients with insulin-treated type 2 diabetes at high risk of hypoglycaemia

AIMS/HYPOTHESIS

The aim of this study was to determine whether random non-fasting C-peptide (rCP) measurement can be used to assess hypoglycaemia risk in insulin-treated type 2 diabetes.

METHODS

We compared continuous glucose monitoring-assessed SD of blood glucose and hypoglycaemia duration in 17 patients with insulin-treated type 2 diabetes and severe insulin deficiency (rCP < 200 pmol/l) and 17 matched insulin-treated control patients with type 2 diabetes but who had preserved endogenous insulin (rCP > 600 pmol/l). We then assessed the relationship between rCP and questionnaire-based measures of hypoglycaemia in 256 patients with insulin-treated type 2 diabetes and a comparison group of 209 individuals with type 1 diabetes.

RESULTS

Continuous glucose monitoring (CGM)-assessed glucose variability and hypoglycaemia was greater in individuals with rCP < 200 pmol/l despite similar mean glucose. In those with low vs high C-peptide, SD of glucose was 4.2 (95% CI 3.7, 4.6) vs 3.0 (2.6, 3.4) mmol/l (p < 0.001). In the low-C-peptide vs high-C-peptide group, the proportion of individuals experiencing sustained hypoglycaemia ≤ 4 mmol/l was 94% vs 41% (p < 0.001), the mean rate of hypoglycaemia was 5.5 (4.4, 6.7) vs 2.1 (1.4, 2.9) episodes per person per week (p = 0.004) and the mean duration was 630 (619, 643) vs 223 (216, 230) min per person per week (p = 0.01). Hypoglycaemia ≤ 3 mmol/l was infrequent in individuals with preserved C-peptide (1.8 [1.2, 2.6] episodes per person per week vs 0.4 [0.1, 0.8] episodes per person per week for low vs high C-peptide, p = 0.04) and only occurred at night. In a population-based cohort with insulin-treated type 2 diabetes, self-reported hypoglycaemia was twice as frequent in those with rCP < 200 pmol/l (OR 2.0, p < 0.001) and the rate of episodes resulting in loss of consciousness or seizure was five times higher (OR 5.0, p = 0.001). The relationship between self-reported hypoglycaemia and C-peptide was similar in individuals with type 1 and type 2 diabetes.

CONCLUSIONS/INTERPRETATION

Low rCP is associated with increased glucose variability and hypoglycaemia in patients with insulin-treated type 2 diabetes and represents a practical, stable and inexpensive biomarker for assessment of hypoglycaemia risk.

Clinical features of childhood diabetes mellitus focusing on latent autoimmune diabetes

PURPOSE

This study was designed to evaluate the clinical characteristics of childhood diabetes mellitus (DM) according to its classification as well as the clinical course of latent autoimmune diabetes (LAD) that initially showed noninsulin dependence despite autoantibody positivity.

METHODS

A total of 91 subjects diagnosed between 2001 and 2015 were enrolled in the study. They were classified into 3 groups: type 1 DM, LAD, and type 2 DM. Clinical features and laboratory findings were compared among groups.

RESULTS

Among 91 subjects, type 1 DM, LAD, and type 2 DM were 51 (56.0%), 7 (7.7%), and 33 (36.3%), respectively. In LAD, age at diagnosis and BMI Z-scores were higher, as compared with those in type 1 DM. Initial serum c-peptide levels were higher in LAD than those in type 1 DM, but lower than those in type 2 DM. In LAD, the mean follow-up duration was 4.56 years, and 43% of the patients ultimately required intensive insulin treatment with dosage of > 0.5 U/kg/day. HbA1C and serum c-peptide levels at the time of intensive insulin treatment were 9.43±0.93% and 1.37±1.36 ng/mL, respectively. Recent serum c-peptide/glucose ratio was lower in the group requiring intensive insulin treatment than the group without intensive insulin treatment, with P-value of 0.057 (0.003±0.005 vs. 0.071±0.086).

CONCLUSION

Initial autoantibody evaluation is useful for classification and management. Close monitoring of the patients with LAD is important due to the expected need for intensive insulin treatment within several years.

Is diabetes mellitus correctly registered and classified in primary care? A population-based study in Catalonia, Spain

OBJECTIVE

To assess the prevalence of miscoding, misclassification, misdiagnosis and under-registration of diabetes mellitus (DM) in primary health care in Catalonia (Spain), and to explore use of automated algorithms to identify them.

METHODS

In this cross-sectional, retrospective study using an anonymized electronic general practice database, data were collected from patients or users with a diabetes-related code or from patients with no DM or prediabetes code but treated with antidiabetic drugs (unregistered DM). Decision algorithms were designed to classify the true diagnosis of type 1 DM (T1DM), type 2 DM (T2DM), and undetermined DM (UDM), and to classify unregistered DM patients treated with antidiabetic drugs.

RESULTS

Data were collected from a total of 376,278 subjects with a DM ICD-10 code, and from 8707 patients with no DM or prediabetes code but treated with antidiabetic drugs. After application of the algorithms, 13.9% of patients with T1DM were identified as misclassified, and were probably T2DM; 80.9% of patients with UDM were reclassified as T2DM, and 19.1% of them were misdiagnosed as DM when they probably had prediabetes. The overall prevalence of miscoding (multiple codes or UDM) was 2.2%. Finally, 55.2% of subjects with unregistered DM were classified as prediabetes, 35.7% as T2DM, 8.5% as UDM treated with insulin, and 0.6% as T1DM.

CONCLUSIONS

The prevalence of inappropriate codification or classification and under-registration of DM is relevant in primary care. Implementation of algorithms could automatically flag cases that need review and would substantially decrease the risk of inappropriate registration or coding.