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

Comparison of several survey-based algorithms to ascertain type 1 diabetes among US adults with self-reported diabetes

INTRODUCTION

Defining type of diabetes using survey data is challenging, although important, for determining national estimates of diabetes. The purpose of this study was to compare the percentage and characteristics of US adults classified as having type 1 diabetes as defined by several algorithms.

RESEARCH DESIGN AND METHODS

This study included 6331 respondents aged ≥18 years who reported a physician diagnosis of diabetes in the 2016-2017 National Health Interview Survey. Seven algorithms classified type 1 diabetes using various combinations of self-reported diabetes type, age of diagnosis, current and continuous insulin use, and use of oral hypoglycemics.

RESULTS

The percentage of type 1 diabetes among those with diabetes ranged from 3.4% for those defined by age of diagnosis <30 years and continuous insulin use (algorithm 2) to 10.2% for those defined only by continuous insulin use (algorithm 1) and 10.4% for those defined as self-report of type 1 (supplementary algorithm 6). Among those defined by age of diagnosis <30 years and continuous insulin use (algorithm 2), by self-reported type 1 diabetes and continuous insulin use (algorithm 4), and by self-reported type 1 diabetes and current insulin use (algorithm 5), mean body mass index (BMI) (28.6, 27.4, and 28.5 kg/m², respectively) and percentage using oral hypoglycemics (16.1%, 11.1%, and 19.0%, respectively) were lower than for all other algorithms assessed. Among those defined by continuous insulin use alone (algorithm 1), the estimates for mean age and age of diagnosis (54.3 and 30.9 years, respectively) and BMI (30.9 kg/m²) were higher than for other algorithms.

CONCLUSIONS

Estimates of type 1 diabetes using commonly used algorithms in survey data result in varying degrees of prevalence, characteristic distributions, and potential misclassification.

Insights into the Genetic Underpinnings of Endocrine Traits from Large-Scale Genome-Wide Association Studies

Great strides have been made in genetic association studies of endocrine traits and diseases, with hundreds or thousands of variants associated with height, body mass index, bone density, pubertal timing, and diabetes in recent years. The common variants associated with these traits explain up to half of the trait variation owing to genetic factors, and when aggregated into polygenic risk scores, can also impact clinically relevant phenotypes at the tail ends of the trait distributions. However, pediatric studies tend to lag behind, and it is often unclear how adult-associated variants behave across life.

Next steps in the identification of gene targets for type 1 diabetes

The purpose of this review is to provide a view of the future of genomics and other omics approaches in defining the genetic contribution to all stages of risk of type 1 diabetes and the functional impact and clinical implementations of the associated variants. From the recognition nearly 50 years ago that genetics (in the form of HLA) distinguishes risk of type 1 diabetes from type 2 diabetes, advances in technology and sample acquisition through collaboration have identified over 60 loci harbouring SNPs associated with type 1 diabetes risk. Coupled with HLA region genes, these variants account for the majority of the genetic risk (~50% of the total risk); however, relatively few variants are located in coding regions of genes exerting a predicted protein change. The vast majority of genetic risk in type 1 diabetes appears to be attributed to regions of the genome involved in gene regulation, but the target effectors of those genetic variants are not readily identifiable. Although past genetic studies clearly implicated immune-relevant cell types involved in risk, the target organ (the beta cell) was left untouched. Through emergent technologies, using combinations of genetics, gene expression, epigenetics, chromosome conformation and gene editing, novel landscapes of how SNPs regulate genes have emerged. Furthermore, both the immune system and the beta cell and their biological pathways have been implicated in a context-specific manner. The use of variants from immune and beta cell studies distinguish type 1 diabetes from type 2 diabetes and, when they are combined in a genetic risk score, open new avenues for prediction and treatment. Graphical abstract.

Meta-analysis investigating the role of interleukin-6 mediated inflammation in type 2 diabetes

BACKGROUND

Evidence from animal models and observational epidemiology points to a role for chronic inflammation, in which interleukin 6 (IL-6) is a key player, in the pathophysiology of type 2 diabetes (T2D). However, it is unknown whether IL-6 mediated inflammation is implicated in the pathophysiology of T2D.

METHODS

We performed a meta-analysis of 15 prospective studies to investigate associations between IL-6 levels and incident T2D including 5,421 cases and 31,562 non-cases. We also estimated the association of a loss-of-function missense variant (Asp358Ala) in the IL-6 receptor gene (IL6R), previously shown to mimic the effects of IL-6R inhibition, in a large trans-ethnic meta-analysis of six T2D case-control studies including 260,614 cases and 1,350,640 controls.

FINDINGS

In a meta-analysis of 15 prospective studies, higher levels of IL-6 (per log pg/mL) were significantly associated with a higher risk of incident T2D (1·24 95% CI, 1·17, 1·32; P = 1 × 10-12). In a trans-ethnic meta-analysis of 260,614 cases and 1,350,640 controls, the IL6R Asp358Ala missense variant was associated with lower odds of T2D (OR, 0·98; 95% CI, 0·97, 0·99; P = 2 × 10-7). This association was not due to diagnostic misclassification and was consistent across ethnic groups. IL-6 levels mediated up to 5% of the association between higher body mass index and T2D.

INTERPRETATION

Large-scale human prospective and genetic data provide evidence that IL-6 mediated inflammation is implicated in the etiology of T2D but suggest that the impact of this pathway on disease risk in the general population is likely to be small.

FUNDING

The EPICNorfolk study has received funding from the Medical Research Council (MRC) (MR/N003284/1, MC-UU_12015/1 and MC_PC_13048) and Cancer Research UK (C864/A14136). The Fenland Study is funded by the MRC (MC_UU_12015/1 and MC_PC_13046).

Comprehensive epigenetic analysis of m6A modification in the hippocampal injury of diabetic rats

Aim: To study RNA N6-methyladenosine (m6A) modification in the diabetic hippocampus. Methods: Behavioral tests and staining were performed to evaluate the damage to the diabetic hippocampus in model rats. Western blotting was performed to investigate the expression of methylation-related enzymes, and flow cytometry was used to demonstrate HT22 cell apoptosis. M6A and RNA sequencing analyses were conducted to profile m6A-tagged transcripts in the diabetic hippocampus. Results: The rat models of diabetes mellitus suffered from cognitive disorders and hippocampal neuron damage. High glucose levels altered the expression of methylation-related enzymes. A total of 4890 differentially methylated m6A peaks and 63 differentially expressed genes and differentially methylated m6A sites were identified. Conclusion: The findings suggest that m6A modification is altered in the diabetic hippocampus and provide new insight into diabetic hippocampal injury.

Pattern, Trend and Predictors of Adult-Onset Type 1 Diabetes in Uyo, Nigeria

<b><i>Background:</i></b> Unlike what obtains in childhood-onset type 1 diabetes, there remains a paucity of data on adult-onset type 1 diabetes in Nigeria. Hence, the current study aimed to determine the general characteristics of adult-onset type 1 diabetes among subjects (aged ≥18 years) presenting at the University of Uyo Teaching Hospital (UUTH) in Akwa Ibom State, South-south Nigeria. <b><i>Methods:</i></b> A 5-year (2014–2018) retrospective records review of subjects with type 1 diabetes was undertaken, using hospital medical records retrieved from the Department of Health Information Management of UUTH. Diagnosed adult cases of type 1 diabetes were meticulously identified and the relevant data at the point of initial diagnosis were acquired on a specially designed data acquisition template. <b><i>Results:</i></b> A total of 47,357 medical cases were identified of which 362 adults were diagnosed with type I diabetes (mean age 33.12 ± 4.40, range 20–51 years) and the females (<i>n</i> = 204; 56.4%) predominated among those diagnosed. The overall, male gender, and female gender prevalence was 7.4/1,000 (95% confidence interval [CI]: 6.89–7.98), 3.3/1,000 (95% CI: 2.52–4.08), and 4.3/1,000 (95% CI: 3.61–4.99), respectively. The females exhibited the highest trough, peak, annual, and overall prevalence during the study period. The female gender (OR: 2.334; 95% CI: 1.407–3.478; <i>p</i> = 0.010), age ≤30 years (OR: 1.976; 95% CI: 0.875–3.211; <i>p</i> &#x3c; 0.001), urban-dwelling (OR: 3.243; 95% CI: 2.3407.780; &#x3c;0.001), diabetes family history (OR: 1.365; 95% CI: 0.678–2.010; <i>p</i> = 0.033), and the rainy season (OR: 1.129; 95% CI: 0.401–1.910; <i>p</i> &#x3c; 0.001) were independent predictors among the overall adult type 1 diabetics. On gender-segregated analyses, age ≤30 years, urban-dwelling, diabetes family history, and the rainy season remained independent predictors among the male and female adult type 1 diabetics (<i>p</i> &#x3c; 0.05). <b><i>Conclusion:</i></b> The study demonstrated a high burden of type 1 diabetes among adult residents of Uyo, Akwa Ibom State, South-South Nigeria. The predictors of adult type 1 diabetes, identified in the present study, are valuable epidemiologic evidence for the design of type 1 diabetes-targeted preventive programs by various concerned stakeholders.

The clinical consequences of heterogeneity within and between different diabetes types

Advances in molecular methods and the ability to share large population-based datasets are uncovering heterogeneity within diabetes types, and some commonalities between types. Within type 1 diabetes, endotypes have been discovered based on demographic (e.g. age at diagnosis, race/ethnicity), genetic, immunological, histopathological, metabolic and/or clinical course characteristics, with implications for disease prediction, prevention, diagnosis and treatment. In type 2 diabetes, the relative contributions of insulin resistance and beta cell dysfunction are heterogeneous and relate to demographics, genetics and clinical characteristics, with substantial interaction from environmental exposures. Investigators have proposed approaches that vary from simple to complex in combining these data to identify type 2 diabetes clusters relevant to prognosis and treatment. Advances in pharmacogenetics and pharmacodynamics are also improving treatment. Monogenic diabetes is a prime example of how understanding heterogeneity within diabetes types can lead to precision medicine, since phenotype and treatment are affected by which gene is mutated. Heterogeneity also blurs the classic distinctions between diabetes types, and has led to the definition of additional categories, such as latent autoimmune diabetes in adults, type 1.5 diabetes and ketosis-prone diabetes. Furthermore, monogenic diabetes shares many features with type 1 and type 2 diabetes, which make diagnosis difficult. These challenges to the current classification framework in adult and paediatric diabetes require new approaches. The 'palette model' and the 'threshold hypothesis' can be combined to help explain the heterogeneity within and between diabetes types. Leveraging such approaches for therapeutic benefit will be an important next step for precision medicine in diabetes. Graphical abstract.

Biopsychosocial factors associated with a current depressive episode in diabetes: the ELSA-Brasil study

AIMS

Depression is more prevalent in people with diabetes, and is associated with worse diabetes outcomes. Depression in diabetes is more treatment resistant, and as underlying mechanisms are unknown, development of more effective treatment strategies is complicated. A biopsychosocial model may improve our understanding of the pathophysiology, and therewith help improving treatment options.

METHODS

Diabetes was diagnosed according to American Diabetes Association (ADA) criteria and a current depressive episode according to the International Classification of Diseases (ICD-10), based on the Clinical Interview Schedule Revised (CIS-R). From the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), we included 455 participants without diabetes with a current depressive episode and 10 900 without either diabetes or a current depressive episode. Furthermore, 2183 participants had diabetes alone and 106 had both diabetes and a current depressive episode. Variable selection was based on their relationship with depression and/or diabetes. Multinomial multivariate logistic regression was used to determine how the models differed between participants with and without diabetes.

RESULTS

A current depressive episode in diabetes was related to being older and female, having poorer education, financial problems, experiencing discrimination at work, home and school, higher waist circumference, albumin to creatinine ratio and insulin resistance, and the presence of hypertension and cardiovascular disease. In non-diabetes, a current depressive disorder was related to being female, not being black, low income, psychological and social factors, non-current alcohol use, lower HDL cholesterol, higher insulin resistance and the presence of cardiovascular disease.

CONCLUSIONS

A current depressive episode in the presence compared with the absence of diabetes was related more to biological than to psychosocial factors.

Incidence and seasonality of type 1 diabetes: a population-based 3-year cohort study using the National Database in Japan

INTRODUCTION

To investigate the incidence of type 1 diabetes by age group (0-19, 20-39, 40-59, ≥60 years) in Japan and whether there is seasonality in this incidence.

RESEARCH DESIGN AND METHODS

The incidence of type 1 diabetes from September 2014 to August 2017 was estimated using 2013-2018 data from the National Database of Health Insurance Claims and Specific Health Check-ups of Japan. The incidence rate was analyzed using Tango's Index and the self-controlled case series method.

RESULTS

Overall, 10 400 of the 79 175 553 included individuals were diagnosed with type 1 diabetes. The incidence of type 1 diabetes from September 2014 to August 2017 was 4.42/100 000 person-years. The incidence rates for men aged 0-19, 20-39, 40-59, and ≥60 years were 3.94, 5.57, 5.70, and 3.48, respectively. Among women, the incidence rates for the same age ranges were 5.22, 4.83, 4.99, and 3.31, respectively. Tango's index showed that the incidence rate of type 1 diabetes was significantly associated with seasons among those aged 0-19 years. Further, the self-controlled case series method showed a significant interaction between age and season, with the incidence of type 1 diabetes being higher in spring for patients younger than 20 years of age.

CONCLUSIONS

In Japan, men aged 40-59 years and women aged 0-19 years are the groups with the highest incidence of type 1 diabetes. Further, the incidence of younger-onset diabetes in Japan was higher in spring (from March to May).

Precision medicine in diabetes: a Consensus Report from the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)

The convergence of advances in medical science, human biology, data science and technology has enabled the generation of new insights into the phenotype known as 'diabetes'. Increased knowledge of this condition has emerged from populations around the world, illuminating the differences in how diabetes presents, its variable prevalence and how best practice in treatment varies between populations. In parallel, focus has been placed on the development of tools for the application of precision medicine to numerous conditions. This Consensus Report presents the American Diabetes Association (ADA) Precision Medicine in Diabetes Initiative in partnership with the European Association for the Study of Diabetes (EASD), including its mission, the current state of the field and prospects for the future. Expert opinions are presented on areas of precision diagnostics and precision therapeutics (including prevention and treatment) and key barriers to and opportunities for implementation of precision diabetes medicine, with better care and outcomes around the globe, are highlighted. Cases where precision diagnosis is already feasible and effective (i.e. monogenic forms of diabetes) are presented, while the major hurdles to the global implementation of precision diagnosis of complex forms of diabetes are discussed. The situation is similar for precision therapeutics, in which the appropriate therapy will often change over time owing to the manner in which diabetes evolves within individual patients. This Consensus Report describes a foundation for precision diabetes medicine, while highlighting what remains to be done to realise its potential. This, combined with a subsequent, detailed evidence-based review (due 2022), will provide a roadmap for precision medicine in diabetes that helps improve the quality of life for all those with diabetes.

Genetic Risk Score in Diabetes Associated With Chronic Pancreatitis Versus Type 2 Diabetes Mellitus

Diabetes mellitus (DM) is a complication of chronic pancreatitis (CP). Whether pancreatogenic diabetes associated with CP-DM represents a discrete pathophysiologic entity from type 2 DM (T2DM) remains uncertain. Addressing this question is needed for development of specific measures to manage CP-DM. We approached this question from a unique standpoint, hypothesizing that if CP-DM and T2DM are separate disorders, they should be genetically distinct. To test this hypothesis, we sought to determine whether a genetic risk score (GRS) based on validated single nucleotide polymorphisms for T2DM could distinguish between groups with CP-DM and T2DM.

Circular RNA circPPM1F modulates M1 macrophage activation and pancreatic islet inflammation in type 1 diabetes mellitus

Rationale: Macrophages play critical roles in the pathogenesis of type 1 diabetes mellitus (T1DM). Circular RNAs (circRNAs) are a novel class of endogenous RNAs with covalently closed loop structures, implicated in various disease processes. However, their impact on macrophage activation and T1DM pathogenesis remains elusive. Methods: circRNA expression profiles of peripheral blood mononuclear cells (PBMCs) from T1DM children were determined by whole transcriptome microarray. Bioinformatics, quantitative real-time PCR, Western blot, RNA immunoprecipitation (RIP), cell co-culture, cell proliferation, and cell apoptosis assays were performed to investigate the expression, function, and regulatory mechanisms of circPPM1F in vitro. The regulatory role of circPPM1F in vivo was evaluated in the streptozocin-induced diabetic mouse model. Results: We identified 27 upregulated and 31 downregulated differentially expressed circRNAs in T1DM patients. circPPM1F, a circRNA with unknown function, was dominantly expressed in monocytes and significantly upregulated in T1DM patients. Functionally, circPPM1F promoted lipopolysaccharide (LPS)-induced M1 macrophage activation via enhancement of the NF-κB signaling pathway. Mechanistically, circPPM1F competitively interacted with HuR to impair the translation of protein phosphatase, Mg²⁺/Mn²⁺ dependent 1F (PPM1F), thus alleviating the inhibitory effect of PPM1F on the NF-κB pathway. Moreover, eukaryotic initiation factor 4A-III (EIF4A3) and fused in sarcoma (FUS) coordinately regulated circPPM1F expression during M1 macrophage activation. In addition, circPPM1F could exacerbate pancreas injury in the streptozocin-induced diabetic mice by activation of M1 macrophages in vivo. Conclusions: circPPM1F is a novel positive regulator of M1 macrophage activation through the circPPM1F-HuR-PPM1F-NF-κB axis. Overexpression of circPPM1F could promote pancreatic islet injury by enhancing M1 macrophage activation and circPPM1F may serve as a novel potential therapeutic target for T1DM in children.

Causal relationships between NAFLD, T2D and obesity have implications for disease subphenotyping

BACKGROUND & AIMS

Non-alcoholic fatty liver disease (NAFLD), type 2 diabetes (T2D) and obesity are epidemiologically correlated with each other but the causal inter-relationships between them remain incompletely understood. We aimed to explore the causal relationships between the 3 diseases.

METHODS

Using both UK Biobank and publicly available genome-wide association study data, we performed a 2-sample bidirectional Mendelian randomization analysis to test the causal inter-relationships between NAFLD, T2D, and obesity. Transgenic mice expressing the human PNPLA3-I148M isoforms (TghPNPLA3-I148M) were used as an example to validate causal effects and explore underlying mechanisms.

RESULTS

Genetically driven NAFLD significantly increased the risk of T2D and central obesity but not insulin resistance or generalized obesity, while genetically driven T2D, body mass index and WHRadjBMI causally increased NAFLD risk. The animal study focusing on PNPLA3 corroborated these causal effects: compared to the TghPNPLA3-I148I controls, the TghPNPLA3-I148M mice developed glucose intolerance and increased visceral fat, but maintained normal insulin sensitivity, reduced body weight, and decreased circulating total cholesterol. Mechanistically, the TghPNPLA3-I148M mice demonstrated decreased pancreatic insulin but increased glucagon secretion, which was associated with increased pancreatic inflammation. In addition, transcription of hepatic cholesterol biosynthesis pathway genes was significantly suppressed, while transcription of thermogenic pathway genes was activated in subcutaneous and brown adipose tissues but not in visceral fat in TghPNPLA3-I148M mice.

CONCLUSIONS

Our study suggests that lifelong, genetically driven NAFLD causally promotes T2D with a late-onset type 1-like diabetic subphenotype and central obesity; while genetically driven T2D, obesity, and central obesity all causally increase the risk of NAFLD. This causal relationship revealed new insights into how nature and nurture drive these diseases, providing novel hypotheses for disease subphenotyping.

LAY SUMMARY

Non-alcoholic fatty liver disease, type 2 diabetes and obesity are epidemiologically correlated with each other, but their causal relationships were incompletely understood. Herein, we identified causal relationships between these conditions, which suggest that each of these closely related diseases should be further stratified into subtypes. This is important for accurate diagnosis, prevention and treatment of these diseases.

IgA Nephropathy Genetic Risk Score to Estimate the Prevalence of IgA Nephropathy in UK Biobank

Background

IgA nephropathy (IgAN) is the commonest glomerulonephritis worldwide. Its prevalence is difficult to estimate, as people with mild disease do not commonly receive a biopsy diagnosis. We aimed to generate an IgA nephropathy genetic risk score (IgAN-GRS) and estimate the proportion of people with hematuria who had IgAN in the UK Biobank (UKBB).

Methods

We calculated an IgAN-GRS using 14 single-nucleotide polymorphisms (SNPs) drawn from the largest European Genome-Wide Association Study (GWAS) and validated the IgAN-GRS in 464 biopsy-proven IgAN European cases from the UK Glomerulonephritis DNA Bank (UKGDB) and in 379,767 Europeans in the UKBB. We used the mean of IgAN-GRS to calculate the proportion of potential IgAN in 14,181 with hematuria and other nonspecific renal phenotypes from 379,767 Europeans in the UKBB.

Results

The IgAN-GRS was higher in the IgAN cohort (4.30; 95% confidence interval [95% CI: 4.23–4.38) than in controls (3.98; 3.97–3.98; P < 0.0001). The mean GRS in UKBB participants with hematuria (n = 12,858) was higher (4.04; 4.02–4.06) than UKBB controls (3.98; 3.97–3.98; P < 0.0001) and higher in those with hematuria, hypertension, and microalbuminuria (n = 1323) (4.07; 4.02–4.13) versus (3.98; 3.97–3.98; P = 0.0003). Using the difference in these means, we estimated that IgAN accounted for 19% of noncancer hematuria and 28% with hematuria, hypertension, and microalbuminuria in UKBB.

Conclusions

We used an IgAN-GRS to estimate the prevalence of IgAN contributing to common phenotypes that are not always biopsied. The noninvasive use of polygenic risk in this setting may have further utility to identify likely etiology of nonspecific renal phenotypes in large population cohorts.

Non-parametric Polygenic Risk Prediction via Partitioned GWAS Summary Statistics

In complex trait genetics, the ability to predict phenotype from genotype is the ultimate measure of our understanding of genetic architecture underlying the heritability of a trait. A complete understanding of the genetic basis of a trait should allow for predictive methods with accuracies approaching the trait's heritability. The highly polygenic nature of quantitative traits and most common phenotypes has motivated the development of statistical strategies focused on combining myriad individually non-significant genetic effects. Now that predictive accuracies are improving, there is a growing interest in the practical utility of such methods for predicting risk of common diseases responsive to early therapeutic intervention. However, existing methods require individual-level genotypes or depend on accurately specifying the genetic architecture underlying each disease to be predicted. Here, we propose a polygenic risk prediction method that does not require explicitly modeling any underlying genetic architecture. We start with summary statistics in the form of SNP effect sizes from a large GWAS cohort. We then remove the correlation structure across summary statistics arising due to linkage disequilibrium and apply a piecewise linear interpolation on conditional mean effects. In both simulated and real datasets, this new non-parametric shrinkage (NPS) method can reliably allow for linkage disequilibrium in summary statistics of 5 million dense genome-wide markers and consistently improves prediction accuracy. We show that NPS improves the identification of groups at high risk for breast cancer, type 2 diabetes, inflammatory bowel disease, and coronary heart disease, all of which have available early intervention or prevention treatments.

Precision Medicine in Diabetes: A Consensus Report From the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)

The convergence of advances in medical science, human biology, data science, and technology has enabled the generation of new insights into the phenotype known as "diabetes." Increased knowledge of this condition has emerged from populations around the world, illuminating the differences in how diabetes presents, its variable prevalence, and how best practice in treatment varies between populations. In parallel, focus has been placed on the development of tools for the application of precision medicine to numerous conditions. This Consensus Report presents the American Diabetes Association (ADA) Precision Medicine in Diabetes Initiative in partnership with the European Association for the Study of Diabetes (EASD), including its mission, the current state of the field, and prospects for the future. Expert opinions are presented on areas of precision diagnostics and precision therapeutics (including prevention and treatment), and key barriers to and opportunities for implementation of precision diabetes medicine, with better care and outcomes around the globe, are highlighted. Cases where precision diagnosis is already feasible and effective (i.e., monogenic forms of diabetes) are presented, while the major hurdles to the global implementation of precision diagnosis of complex forms of diabetes are discussed. The situation is similar for precision therapeutics, in which the appropriate therapy will often change over time owing to the manner in which diabetes evolves within individual patients. This Consensus Report describes a foundation for precision diabetes medicine, while highlighting what remains to be done to realize its potential. This, combined with a subsequent, detailed evidence-based review (due 2022), will provide a roadmap for precision medicine in diabetes that helps improve the quality of life for all those with diabetes.

Exploring Diseases/Traits and Blood Proteins Causally Related to Expression of ACE2, the Putative Receptor of SARS-CoV-2: A Mendelian Randomization Analysis Highlights Tentative Relevance of Diabetes-Related Traits

OBJECTIVE

COVID-19 has become a major public health problem. There is good evidence that ACE2 is a receptor for SARS-CoV-2, and high expression of ACE2 may increase susceptibility to infection. We aimed to explore risk factors affecting susceptibility to infection and prioritize drug repositioning candidates, based on Mendelian randomization (MR) studies on ACE2 lung expression.

RESEARCH DESIGN AND METHODS

We conducted a phenome-wide MR study to prioritize diseases/traits and blood proteins causally linked to ACE2 lung expression in GTEx. We also explored drug candidates whose targets overlapped with the top-ranked proteins in MR, as these drugs may alter ACE2 expression and may be clinically relevant.

RESULTS

The most consistent finding was tentative evidence of an association between diabetes-related traits and increased ACE2 expression. Based on one of the largest genome-wide association studies on type 2 diabetes mellitus (T2DM) to date (N = 898,130), T2DM was causally linked to raised ACE2 expression (P = 2.91E-03; MR-IVW). Significant associations (at nominal level; P < 0.05) with ACE2 expression were observed across multiple diabetes data sets and analytic methods for T1DM, T2DM, and related traits including early start of insulin. Other diseases/traits having nominal significant associations with increased expression included inflammatory bowel disease, (estrogen receptor-positive) breast cancer, lung cancer, asthma, smoking, and elevated alanine aminotransferase. We also identified drugs that may target the top-ranked proteins in MR, such as fostamatinib and zinc.

CONCLUSIONS

Our analysis suggested that diabetes and related traits may increase ACE2 expression, which may influence susceptibility to infection (or more severe infection). However, none of these findings withstood rigorous multiple testing corrections (at false discovery rate <0.05). Proteome-wide MR analyses might help uncover mechanisms underlying ACE2 expression and guide drug repositioning. Further studies are required to verify our findings.

Type 1 diabetes genetic risk score is discriminative of diabetes in non-Europeans: evidence from a study in India

Type 1 diabetes (T1D) is a significant problem in Indians and misclassification of T1D and type 2 diabetes (T2D) is a particular problem in young adults in this population due to the high prevalence of early onset T2D at lower BMI. We have previously shown a genetic risk score (GRS) can be used to discriminate T1D from T2D in Europeans. We aimed to test the ability of a T1D GRS to discriminate T1D from T2D and controls in Indians. We studied subjects from Pune, India of Indo-European ancestry; T1D (n = 262 clinically defined, 200 autoantibody positive), T2D (n = 345) and controls (n = 324). We used the 9 SNP T1D GRS generated in Europeans and assessed its ability to discriminate T1D from T2D and controls in Indians. We compared Indians with Europeans from the Wellcome Trust Case Control Consortium study; T1D (n = 1963), T2D (n = 1924) and controls (n = 2938). The T1D GRS was discriminative of T1D from T2D in Indians but slightly less than in Europeans (ROC AUC 0.84 v 0.87, p < 0.0001). HLA SNPs contributed the majority of the discriminative power in Indians. A T1D GRS using SNPs defined in Europeans is discriminative of T1D from T2D and controls in Indians. As with Europeans, the T1D GRS may be useful for classifying diabetes in Indians.

Studies of insulin and proinsulin in pancreas and serum support the existence of aetiopathological endotypes of type 1 diabetes associated with age at diagnosis

AIMS/HYPOTHESIS

It is unclear whether type 1 diabetes is a single disease or if endotypes exist. Our aim was to use a unique collection of pancreas samples recovered soon after disease onset to resolve this issue.

METHODS

Immunohistological analysis was used to determine the distribution of proinsulin and insulin in the islets of pancreas samples recovered soon after type 1 diabetes onset (<2 years) from young people diagnosed at age <7 years, 7-12 years and ≥13 years. The patterns were correlated with the insulitis profiles in the inflamed islets of the same groups of individuals. C-peptide levels and the proinsulin:C-peptide ratio were measured in the circulation of a cohort of living patients with longer duration of disease but who were diagnosed in these same age ranges.

RESULTS

Distinct patterns of proinsulin localisation were seen in the islets of people with recent-onset type 1 diabetes, which differed markedly between children diagnosed at <7 years and those diagnosed at ≥13 years. Proinsulin processing was aberrant in most residual insulin-containing islets of the younger group but this was much less evident in the group ≥13 years (p < 0.0001). Among all individuals (including children in the middle [7-12 years] range) aberrant proinsulin processing correlated with the assigned immune cell profiles defined by analysis of the lymphocyte composition of islet infiltrates. C-peptide levels were much lower in individuals diagnosed at <7 years than in those diagnosed at ≥13 years (median <3 pmol/l, IQR <3 to <3 vs 34.5 pmol/l, IQR <3-151; p < 0.0001), while the median proinsulin:C-peptide ratio was increased in those with age of onset <7 years compared with people diagnosed aged ≥13 years (0.18, IQR 0.10-0.31) vs 0.01, IQR 0.009-0.10 pmol/l; p < 0.0001).

CONCLUSIONS/INTERPRETATION

Among those with type 1 diabetes diagnosed under the age of 30 years, there are histologically distinct endotypes that correlate with age at diagnosis. Recognition of such differences should inform the design of future immunotherapeutic interventions designed to arrest disease progression.

Nanotechnology's application in Type 1 diabetes

Type 1 diabetes mellitus (T1D) is an autoimmune disease caused by the immune system attacking islet cells. T1D, with a long prediabetes period, and the incidence of T1D increases with age during childhood and peaks at 10-14 years. And once it gets overt, it requires lifelong insulin replace treatment. Therefore, the diagnosis of early-stage T1D and effective treatments are important for the management of T1D patients. The imaging methods, such as magnetic resonance imaging (MRI) and so on, were applied in diagnosis of the early stage T1D and its development tracking. The addition of nanomaterials, especially in MRI, can improve the quality of T1D imaging for the diagnosis of T1D at early stage and cause less harm to human body. Meantime, among various treatment options, islet transplantation and immunotherapy are promising, effective, and less independent on insulin. The addition of nanotechnology can effectively reduce the attack of the immune system on drugs and cells, making the therapeutic drug more targeted in the body and prolonging the action time between drugs and cells, thus its addition makes these therapy safer and more efficient. In this review, we attempt to summarize the recent advances in the development of nanotechnology advances of T1D including using nanomaterials for the diagnosis and immunological imaging of T1D, protecting the transplanted islet cells from immune system attack, and delivering relevant molecules to targeted immunocytes. This article is categorized under: Diagnostic Tools > in vivo Nanodiagnostics and Imaging Therapeutic Approaches and Drug Discovery > Emerging Technologies Implantable Materials and Surgical Technologies > Nanotechnology in Tissue Repair and Replacement.

Assessing Digital Phenotyping to Enhance Genetic Studies of Human Diseases

Population-scale biobanks that combine genetic data and high-dimensional phenotyping for a large number of participants provide an exciting opportunity to perform genome-wide association studies (GWAS) to identify genetic variants associated with diverse quantitative traits and diseases. A major challenge for GWAS in population biobanks is ascertaining disease cases from heterogeneous data sources such as hospital records, digital questionnaire responses, or interviews. In this study, we use genetic parameters, including genetic correlation, to evaluate whether GWAS performed using cases in the UK Biobank ascertained from hospital records, questionnaire responses, and family history of disease implicate similar disease genetics across a range of effect sizes. We find that hospital record and questionnaire GWAS largely identify similar genetic effects for many complex phenotypes and that combining together both phenotyping methods improves power to detect genetic associations. We also show that family history GWAS using cases ascertained on family history of disease agrees with combined hospital record and questionnaire GWAS and that family history GWAS has better power to detect genetic associations for some phenotypes. Overall, this work demonstrates that digital phenotyping and unstructured phenotype data can be combined with structured data such as hospital records to identify cases for GWAS in biobanks and improve the ability of such studies to identify genetic associations.

Prevalence and incidence of type 1 diabetes in Ireland: a retrospective cross-sectional study using a national pharmacy claims data from 2016

OBJECTIVES

The aim of this study is to estimate the prevalence and incidence of type 1 diabetes in the Irish population using a national pharmacy claims database in the absence of a national diabetes register.

DESIGN

National, population-based, retrospective, cross-sectional study.

SETTING

Community care with data available through the Health Service Executive Pharmacy Claims Reimbursement Scheme from 2011 to 2016.

PARTICIPANTS

Individuals with type 1 diabetes were identified by coprescription of insulin and glucometer test strips without any prolonged course (>12 months) of oral hypoglycaemic agents prior to commencing insulin. Those claiming prescriptions for long-acting insulin only, without any prandial insulin, were excluded from the analysis. Incidence was estimated based on the first claim for insulin in 2016, with no insulin use in the preceding 12 months.

MAIN OUTCOME MEASURES

Prevalence of type 1 diabetes in children (<18 years) and adults (≥18 years); incidence of type 1 diabetes in children (≤14 years) and adolescents and adults (>14 years).

RESULTS

There were 20 081 prevalent cases of type 1 diabetes in 2016. The crude prevalence was 0.42% (95% CI 0.42% to 0.43%). Most prevalent cases (n=17 053, 85%) were in adults with a prevalence of 0.48% (95% CI 0.47% to 0.48%). There were 1527 new cases of type 1 diabetes in 2016, giving an incidence rate of 32 per 100 000 population/year (95% CI 30.5 to 33.7). There was a significant positive linear trend for age, for prevalence (p<0.0001) and incidence (p=0.014). The prevalence and incidence were 1.2-fold and 1.3-fold higher in men than women, respectively. Significant variations in prevalence (p<0.0001) and incidence (p<0.001) between the different geographical regions were observed.

CONCLUSIONS

This study provides epidemiological estimates of type 1 diabetes across age groups in Ireland, with the majority of prevalent cases in adults. Establishing a national diabetes register is essential to enable updated epidemiological estimates of diabetes and for planning of services in Ireland.

The Pharmacological Activity of Camellia sinensis (‎L.‎) ‎Kuntze‎ on Metabolic and Endocrine Disorders: A Systematic Review

Tea made from Camellia sinensis leaves is one of the most consumed beverages worldwide. This systematic review aims to update Camellia sinensis pharmacological activity on metabolic and endocrine disorders. Inclusion criteria were preclinical and clinical studies of tea extracts and isolated compounds on osteoporosis, hypertension, diabetes, metabolic syndrome, hypercholesterolemia, and obesity written in English between 2014 and 2019 and published in Pubmed, Science Direct, and Scopus. From a total of 1384 studies, 80 reports met inclusion criteria. Most papers were published in 2015 (29.3%) and 2017 (20.6%), conducted in China (28.75%), US (12.5%), and South Korea (10%) and carried out with extracts (67.5%, especially green tea) and isolated compounds (41.25%, especially epigallocatechin gallate). Most pharmacological studies were in vitro and in vivo studies focused on diabetes and obesity. Clinical trials, although they have demonstrated promising results, are very limited. Future research should be aimed at providing more clinical evidence on less studied pathologies such as osteoporosis, hypertension, and metabolic syndrome. Given the close relationship among all endocrine disorders, it would be of interest to find a standard dose of tea or their bioactive constituents that would be beneficial for all of them.

The cognitive and psychological effects of living with type 1 diabetes: a narrative review

Across the lifespan, type 1 diabetes mellitus has a profound (neuro)psychological impact. In young people, type 1 diabetes can interfere with psychosocial development and hamper school performance. In adulthood, it can interfere with work life, relationships and parenting. A substantial minority of adults with type 1 diabetes experience coping difficulties and high diabetes-related distress. In youth and adulthood, type 1 diabetes is related to mild cognitive decrements as well as affective disorders, such as depression and anxiety. There is limited literature available that explores the interaction between cognitive and psychological comorbidity and underlying mechanisms. The aims of the present narrative review were to summarize the current state of the literature regarding both cognitive and psychological comorbidities in type 1 diabetes across the lifespan, and to explore potential links between the two domains of interest to make suggestions for future research and clinical practice.

Extracellular Vesicles Derived Human-miRNAs Modulate the Immune System in Type 1 Diabetes

Extracellular vesicles with their molecular cargo can modulate target cell response and may affect the pathogenesis of diseases. The extracellular vesicles containing micro-RNAs (miRNAs), which are often studied as disease biomarkers, but rarely as mediators of the disease development. The role of extracellular vesicles derived miRNAs in type 1 diabetes is currently not well established. We observed a fraction of blood plasma extracellular vesicles positive for membrane proteins potentially associated with insulin-producing beta-cells and identified differentially expressed extracellular vesicles derived miRNAs in individuals with type 1 diabetes. These differentially expressed extracellular vesicles derived human miRNAs in participants with type 1 diabetes and participants with Langerhans islets beta-cells destruction showed the ability to activate TLR7/8 signaling cascade and increase activation as well as cytotoxicity of the effector blood immune cells with cytokine and chemokine release. Our results illustrate extracellular vesicles derived human miRNAs as modulators of the immune system in type 1 diabetes autoimmunity, providing potentially new insight into the pathogenesis of the disease, and novel molecular targets for intervention and type 1 diabetes prevention.

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.

Targeting the receptor for advanced glycation end products (RAGE) in type 1 diabetes

Type 1 diabetes (T1D) is one of the most common chronic diseases manifesting in early life, with the prevalence increasing worldwide at a rate of approximately 3% per annum. The prolonged hyperglycaemia characteristic of T1D upregulates the receptor for advanced glycation end products (RAGE) and accelerates the formation of RAGE ligands, including advanced glycation end products, high-mobility group protein B1, S100 calcium-binding proteins, and amyloid-beta. Interestingly, changes in the expression of RAGE and these ligands are evident in patients before the onset of T1D. RAGE signals via various proinflammatory cascades, resulting in the production of reactive oxygen species and cytokines. A large number of proinflammatory ligands that can signal via RAGE have been implicated in several chronic diseases, including T1D. Therefore, it is unsurprising that RAGE has become a potential therapeutic target for the treatment and prevention of disease. In this review, we will explore how RAGE might be targeted to prevent the development of T1D.

A treatment-based algorithm for identification of diabetes type in the National Health and Nutrition Examination Survey

In epidemiology studies, identification of diabetes type (type 1 vs. type 2) among study participants with diabetes is important; however, conventional diabetes type identification approaches that include age at diabetes diagnosis as an initial criterion introduces biases. Using data from the National Health and Nutrition Examination Survey, we have developed a novel algorithm which does not include age at diagnosis to identify participants with self-reported diagnosed diabetes as having type 1 vs. type 2 diabetes.

Methods

A total of 5457 National Health and Nutrition Examination Survey participants between cycles 1999-2000 and 2015-2016 reported that a health professional had diagnosed them as having diabetes at a time other than during pregnancy and had complete information on diabetes-related questions. After developing an algorithm based on information regarding the treatment(s) they received, we classified these participants as having type 1 or type 2 diabetes.

Results

The treatment-based algorithm yielded a 6-94% split for type 1 and type 2 diabetes, which is consistent with reports from the Centers for Disease Control and other resources. Moreover, the demographics and clinical characteristics of the assigned type 1 and type 2 cases were consistent with contemporary epidemiologic findings.

Conclusion

Applying diabetes treatment information from the National Health and Nutrition Examination Survey, as formulated in our treatment-based algorithm, may better identify type 1 and type 2 diabetes cases and thus prevent the specific biases imposed by conventional approaches which include the age of diabetes diagnosis as an initial criterion for diabetes type classification.

Insulin Therapy in Adults with Type 1 Diabetes Mellitus: a Narrative Review

Here, we review insulin management options and strategies in nonpregnant adult patients with type 1 diabetes mellitus (T1DM). Most patients with T1DM should follow a regimen of multiple daily injections of basal/bolus insulin, but those not meeting individual glycemic targets or those with frequent or severe hypoglycemia or pronounced dawn phenomenon should consider continuous subcutaneous insulin infusion. The latter treatment modality could also be an alternative based on patient preferences and availability of reimbursement. Continuous glucose monitoring may improve glycemic control irrespective of treatment regimen. A glycemic target of glycated hemoglobin < 7% (53 mmol/mol) is appropriate for most nonpregnant adults. Basal insulin analogues with a reduced peak profile and an extended duration of action with lower intraindividual variability relative to neutral protamine Hagedorn insulin are preferred. The clinical advantages of basal analogues compared with older basal insulins include reduced injection burden, better efficacy, lower risk of hypoglycemic episodes (especially nocturnal), and reduced weight gain. For prandial glycemic control, any rapid-acting prandial analogue (aspart, glulisine, lispro) is preferred over regular human insulin. Faster-acting insulin aspart is a relatively new option with the advantage of better postprandial glucose coverage. Frequent blood glucose measurements along with patient education on insulin dosing based on carbohydrate counting, premeal blood glucose, and anticipated physical activity is paramount, as is education on the management of blood glucose under different circumstances.Plain Language Summary: Plain language summary is available for this article.

Association between Bioactive Molecules in Breast Milk and Type 1 Diabetes Mellitus

The association between breastfeeding and type 1 diabetes mellitus (T1DM) is controversial. However, several recent studies have established a link between these two factors, necessitating a need to review this subject to raise public awareness. Current research indicates that breast milk contains a variety of bioactive substances including immunoglobulins, oligosaccharides, insulin, lactoferrin, lysozyme, cytokines, epidermal growth factors, leukocytes, nucleotides, beneficial bacteria and vitamins. Such substances strengthen the breastfeeding infant's immune system, both directly, by increasing gut microbiota diversity and attacking harmful bacteria and pro-inflammatory molecules, and indirectly, by increasing thymus performance. Accordingly, a lack of or inadequate breastfeeding may predispose infants to several autoimmune disorders, including T1DM. Nursing mothers and caregivers are therefore advised to follow optimal breastfeeding practices prior to introducing complementary foods.

Distinct two different ages associated with clinical profiles of acute onset type 1 diabetes in Chinese patients

BACKGROUND

There are abundant variations in the phenotypes and genetics of type 1 diabetes (T1D) patients across different races. This study aimed to assess differences between juvenile acute onset (JAO) and adult acute onset in Chinese T1D patients.

METHODS

Seven hundred and fifty-one acute onset T1D patients were divided into two groups by the patient onset age as follows: the juvenile acute onset group (≤20 years, JAO group) and the adult acute onset group (>20 years, AAO group). Clinical characteristics, islet autoantibodies, and HLA class II haplotypes and genotypes were compared between these two groups.

RESULTS

In comparison with AAO patients, JAO patients had significantly lower relative weights and lower triglyceride levels (P < .001, P < .01, respectively) but higher frequency of ketoacidosis (P < .001), higher daily insulin dosage (P_c  < .001), higher HbA1_c (P_c  < .05), and higher HDL-cholesterol levels (P_c  < .01). The JAO group showed a higher prevalence of IA-2A, ZnT8A, and multiple autoantibodies than that in the AAO group (P < .001, P < .01, P < .001, respectively). Haplotypes for DRB1*0301-DQA1*03-DQB1*0201, DR3, DR4, DR9, and DR3/DR9 genotypes are highly associated with JAO susceptibility, whereas only DR3 and DR9 genotypes confer risk for AAO. In the JAO group but not the AAO group, DR3 is related to ZnT8A, and DR3/DR9 is related to IA-2A and multiple autoantibodies.

CONCLUSIONS

These observations suggest that JAO patients markedly differ from AAO patients in their clinical manifestations and genetics in the Chinese T1D population. Notably, the DR3/DR9 genotype can facilitate the appearance of IA-2A or multiple autoantibodies in JAO patients.

New Frontiers in the Treatment of Type 1 Diabetes

Type 1 diabetes is an autoimmune disease caused by the immune-mediated destruction of pancreatic β cells that results in lifelong absolute insulin deficiency. For nearly a century, insulin replacement has been the only therapy for most people living with this disease. Recent advances in technology and our understanding of β cell development, glucose metabolism, and the underlying immune pathogenesis of the disease have led to innovative therapeutic and preventative approaches. A paradigm shift in immunotherapy development toward the targeting of islet-specific immune pathways involved in tolerance has driven the development of therapies that may allow for the prevention or reversal of this disease while avoiding toxicities associated with historical approaches that were broadly immunosuppressive. In this review, we discuss successes, failures, and emerging pharmacological therapies for type 1 diabetes that are changing how we approach this disease, from improving glycemic control to developing the "holy grail" of disease prevention.

The Challenges of Identifying Environmental Determinants of Type 1 Diabetes: In Search of the Holy Grail

Type 1 diabetes is the result of autoimmune-mediated destruction and inflammation of the insulin-producing β-cells of the pancreas. The excess morbidity and mortality from its complications coupled with its increasing incidence emphasize the importance to better understand the etiology of this condition. It has a strong genetic component, but a genetic predisposition is not the sole contributor to disease development as only 30% to 50% of identical twins both develop the disease. In addition, there are multiple lines of evidence to support that environmental factors contribute to the pathogenesis of type 1 diabetes. Environmental risk factors that have been proposed include infections, dietary factors, air pollution, vaccines, location of residence, childhood obesity, family environment and stress. Researchers have conducted many observational studies to identify and characterize these potential environmental factors, but findings have been inconsistent or inconclusive. Many studies have had inherent methodological issues in recruitment, participation, defining cases and exposures, and/or data analysis which may limit the interpretability of findings. Identifying and addressing these limitations may allow for greatly needed advances in our understanding of type 1 diabetes. As such, the purpose of this article is to review and discuss the limitations of observational studies that aim to determine environmental risk factors for type 1 diabetes and propose recommendations to overcome them.

Childhood Pancreatitis and Risk for Incident Diabetes in Adulthood

OBJECTIVE

The relationship between acute pancreatitis and incident diabetes is unclear. We assessed whether a resolved single event of acute pancreatitis in childhood was associated with incident diabetes in adulthood.

RESEARCH DESIGN AND METHODS

A nationwide, population-based study of 1,802,110 Israeli adolescents (mean age 17.4 years [range 16-20]) who were examined before compulsory military service between 1979 and 2008 and whose data were linked to the Israeli National Diabetes Registry (INDR). Resolved pancreatitis was defined as a history of a single event of acute pancreatitis with normal pancreatic function at enrollment. Logistic regression analysis was applied.

RESULTS

Incident diabetes developed in 4.6% of subjects with resolved pancreatitis (13 of 281; none of these cases were identified as type 1 diabetes) and 2.5% among the unexposed group (44,463 of 1,801,716). Resolved acute pancreatitis was associated with incident diabetes with an odds ratio (OR) of 2.23 (95% CI 1.25-3.98) with adjustment for age, sex, and birth year. Findings persisted after further adjustments for baseline BMI and sociodemographic confounders (OR 2.10 [95% CI 1.15-3.84]). Childhood pancreatitis was associated with a diagnosis of diabetes at a younger age, with 92% of diabetes case subjects diagnosed before 40 years of age compared with 47% in the unexposed group (P = 0.002). The association accentuated when the study sample was limited to individuals of unimpaired health or normal BMI at baseline.

CONCLUSIONS

A history of acute pancreatitis in childhood with normal pancreatic function in late adolescence is a risk factor for incident type 2 diabetes, especially at young adulthood.

13. Children and Adolescents: 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, a multidisciplinary expert committee (https://doi.org/10.2337/dc20-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/dc20-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Genetic Risk Scores for Diabetes Diagnosis and Precision Medicine

During the last decade, there have been substantial advances in the identification and characterization of DNA sequence variants associated with individual predisposition to type 1 and type 2 diabetes. As well as providing insights into the molecular, cellular, and physiological mechanisms involved in disease pathogenesis, these risk variants, when combined into a polygenic score, capture information on individual patterns of disease predisposition that have the potential to influence clinical management. In this review, we describe the various opportunities that polygenic scores provide: to predict diabetes risk, to support differential diagnosis, and to understand phenotypic and clinical heterogeneity. We also describe the challenges that will need to be overcome if this potential is to be fully realized.

The Genetic Contribution to Type 1 Diabetes

PURPOSE OF REVIEW

To provide an updated summary of discoveries made to date resulting from genome-wide association study (GWAS) and sequencing studies, and to discuss the latest loci added to the growing repertoire of genetic signals predisposing to type 1 diabetes (T1D).

RECENT FINDINGS

Genetic studies have identified over 60 loci associated with T1D susceptibility. GWAS alone does not specifically inform on underlying mechanisms, but in combination with other sequencing and omics-data, advances are being made in our understanding of T1D genetic etiology and pathogenesis. Current knowledge indicates that genetic variation operating in both pancreatic β cells and in immune cells is central in mediating T1D risk. One of the main challenges is to determine how these recently discovered GWAS-implicated variants affect the expression and function of gene products. Once we understand the mechanism of action for disease-causing variants, we will be well placed to apply targeted genomic approaches to impede the premature activation of the immune system in an effort to ultimately prevent the onset of T1D.

The heterogeneous pathogenesis of type 1 diabetes mellitus

Type 1 diabetes mellitus (T1DM) results from the destruction of pancreatic β-cells that is mediated by the immune system. Multiple genetic and environmental factors found in variable combinations in individual patients are involved in the development of T1DM. Genetic risk is defined by the presence of particular allele combinations, which in the major susceptibility locus (the HLA region) affect T cell recognition and tolerance to foreign and autologous molecules. Multiple other loci also regulate and affect features of specific immune responses and modify the vulnerability of β-cells to inflammatory mediators. Compared with the genetic factors, environmental factors that affect the development of T1DM are less well characterized but contact with particular microorganisms is emerging as an important factor. Certain infections might affect immune regulation, and the role of commensal microorganisms, such as the gut microbiota, are important in the education of the developing immune system. Some evidence also suggests that nutritional factors are important. Multiple islet-specific autoantibodies are found in the circulation from a few weeks to up to 20 years before the onset of clinical disease and this prediabetic phase provides a potential opportunity to manipulate the islet-specific immune response to prevent or postpone β-cell loss. The latest developments in understanding the heterogeneity of T1DM and characterization of major disease subtypes might help in the development of preventive treatments.

Risk factors for prevalent diabetic retinopathy and proliferative diabetic retinopathy in type 1 diabetes

PURPOSE

Age at diagnosis of type 1 diabetes (DM1) has been implied as an important factor associated with the development of the microvascular complications. Our aim was to identify factors associated with prevalent diabetic retinopathy (DR) and proliferative diabetic retinopathy (PDR) in DM1 people with early and late-onset.

METHODS

We reviewed medical records from all DM1 people from the reference area of a tertiary center (about 340,000 persons). Univariate and multivariate logistic regression were used to assess the relationship between potential risk factors (sociodemographic, diabetes-related, co-morbidities, and laboratory parameters) and prevalent DR/PDR. We performed an analysis comparing patients diagnosed before (early-onset) and after (late-onset) 18 years of age.

RESULTS

We included 140 patients in early-onset DM1 group and 169 in late-onset DM1 group. Longer duration of diabetes and HbA1c remained associated with prevalent DR in both groups after adjusting for potential risk factors. Nephropathy was associated with prevalent DR in the late-onset group but not in the early-onset group. Peripheral neuropathy remained associated with prevalent PDR when modeled together in the multivariate model. High BMI demonstrated a significative association with PDR in early but not in the late-onset DM1 group.

CONCLUSIONS

Although previous reports suggest that age at DM1 diagnosis may have a role in DR prevalence, the risk factors for DR in early and late-onset DM1 were similar for both groups. Duration of disease and lifelong metabolic control were the major predictors for DR in both groups. Nephropathy was associated with DR in patients with late-onset disease. Neuropathy was associated with PDR occurrence in both groups. BMI was associated with PDR early-onset DM1 group.

Ability of verbal autopsy data to detect deaths due to uncontrolled hyperglycaemia: testing existing methods and development and validation of a novel weighted score

OBJECTIVES

Verbal autopsy (VA) is a useful tool to ascertain cause of death where no other mechanisms exist. We aimed to assess the utility of VA data to ascertain deaths due to uncontrolled hyperglycaemia and to develop a weighted score (WS) to specifically identify cases. Cases were identified by a study or site physician with training in diabetes. These diagnoses were also compared with diagnoses produced by a standard computer algorithm (InterVA-4).

SETTING

This study was done using VA data from the Health and Demographic Survey sites in Agincourt in rural South Africa. Validation of the WS was done using VA data from Karonga in Malawi.

PARTICIPANTS

All deaths from ages 1 to 49 years between 1992 and 2015 and between 2002 and 2016 from Agincourt and Karonga, respectively. There were 8699 relevant deaths in Agincourt and 1663 in Karonga.

RESULTS

Of the Agincourt deaths, there were 77 study physician classified cases and 58 computer algorithm classified cases. Agreement between study physician classified cases and computer algorithm classified cases was poor (Cohen's kappa 0.14). Our WS produced a receiver operator curve with area under the curve of 0.952 (95% CI 0.920 to 0.985). However, positive predictive value (PPV) was below 50% when the WS was applied to the development set and the score was dominated by the necessity for a premortem diagnosis of diabetes. Independent validation showed the WS performed reasonably against site physician classified cases with sensitivity of 86%, specificity of 99%, PPV of 60% and negative predictive value of 99%.

CONCLUSION

Our results suggest that widely used VA methodologies may be missing deaths due to uncontrolled hyperglycaemia. Our WS may offer improved ability to detect deaths due to uncontrolled hyperglycaemia in large populations studies where no other means exist.

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.

What Have Slow Progressors Taught Us About T1D-Mind the Gap!

PURPOSE OF REVIEW

Progression rate from islet autoimmunity to clinical diabetes is unpredictable. In this review, we focus on an intriguing group of slow progressors who have high-risk islet autoantibody profiles but some remain diabetes free for decades.

RECENT FINDINGS

Birth cohort studies show that islet autoimmunity presents early in life and approximately 70% of individuals with multiple islet autoantibodies develop clinical symptoms of diabetes within 10 years. Some "at risk" individuals however progress very slowly. Recent genetic studies confirm that approximately half of type 1 diabetes (T1D) is diagnosed in adulthood. This creates a conundrum; slow progressors cannot account for the number of cases diagnosed in the adult population. There is a large "gap" in our understanding of the pathogenesis of adult onset T1D and a need for longitudinal studies to determine whether there are "at risk" adults in the general population; some of whom are rapid and some slow adult progressors.

Socio-economic inequalities in diabetes prevalence in the Kingdom of Saudi Arabia

BACKGROUND

Rising prevalence of non-communicable diseases, including diabetes in the Middle East, is a major public health concern of the 21st century. However, there is a paucity of literature to understand and measure socio-economic inequalities in diabetes prevalence in this region, including the Kingdom of Saudi Arabia (KSA).

METHODS

This study investigated socio-economic inequalities in diabetes prevalence in the KSA using data from the Saudi Arabia Health Interview Survey. Concentration curve, concentration index, and multivariate logistic regression were used to measure and examine income- and education-related inequalities in diabetes prevalence.

RESULTS

The results showed significant socio-economic inequalities in the prevalence of diabetes through analysing a nationally representative sample of the KSA population. Diabetes prevalence was concentrated among the poor and among people with less education. In addition, education-related inequality was higher than income-related inequality.

CONCLUSIONS

The findings of this study are important for policymakers to combat both the increasing prevalence of and socio-economic inequalities in diabetes. The government should promote health education programmes and increase the level of public awareness of diabetes management, especially among the lower educated population in the KSA.