Relative contribution of type 1 and type 2 diabetes loci to the genetic etiology of adult-onset, non-insulin-requiring autoimmune diabetes.

BACKGROUND: In adulthood, autoimmune diabetes can present as non-insulin-requiring diabetes, termed as 'latent autoimmune diabetes in adults' (LADA). In this study, we investigated established type 1 diabetes (T1D) and type 2 diabetes (T2D) genetic loci in a large cohort of LADA cases to assess where LADA is situated relative to these two well-characterized, classic forms of diabetes. METHODS: We tested the association of T1D and T2D GWAS-implicated loci in 978 LADA cases and 1057 non-diabetic controls of European ancestry using a linear mixed model. We then compared the associations of T1D and T2D loci between LADA and T1D and T2D cases, respectively. We quantified the difference in genetic risk between each given disease at each locus, and also calculated genetic risk scores to quantify how genetic liability to T1D and T2D distinguished LADA cases from controls. RESULTS: Overall, our results showed that LADA is genetically more similar to T1D, with the exception of an association at the T2D HNF1A locus. Several T1D loci were associated with LADA, including the major histocompatibility complex region, as well as at PTPN22, SH2B3, and INS. Contrary to previous studies, the key T2D risk allele at TCF7L2 (rs7903146-T) had a significantly lower frequency in LADA cases, suggesting that this locus does not play a role in LADA etiology. When constrained on antibody status, the similarity between LADA and T1D became more apparent; however, the HNF1A and TCF7L2 observations persisted. CONCLUSION: LADA is genetically closer to T1D than T2D, although the genetic load of T1D risk alleles is less than childhood-onset T1D, particularly at the major histocompatibility complex region, potentially accounting for the later disease onset. Our results show that the genetic spectrum of T1D extends into adult-onset diabetes, where it can clinically masquerade as T2D. Furthermore, T2D genetic risk plays a small role in LADA, with a degree of evidence for the HNF1A locus, highlighting the potential for genetic risk scores to contribute towards defining diabetes subtypes.

Substantial reduction in the number of amputations among patients with diabetes: a cohort study over 16 years.

AIMS/HYPOTHESIS: The aim of this study was to describe the trends in rates of amputation among individuals with and without diabetes. METHODS: We studied amputation rates in the County of Funen (approximately 0.5 million residents) during the period 1996-2011. Amputations were identified from the hospital administrative system, diabetes status by linkage with the Danish National Diabetes Register, and mortality and population data by extraction from Statistics Denmark. Amputation rates were analysed using proportional hazard models. We analysed the incidence of the first amputation at each level as well as the incidence of further amputations, subdivided by level of amputation. RESULTS: During the period 1996-2011, a total of 2,832 amputations were performed, of which 1,285 were among patients with diabetes and 1,547 among individuals without diabetes. Relative to persons without diabetes, patients with diabetes had an HR for below-ankle amputations (BAAs) of 14.7 for men and 7.5 for women, and for from-ankle-to-knee amputations (BKAs) of 7.6 and 8.4 for men and women, respectively. For above-knee amputations (AKAs) the numbers were 4.0 for men and 3.7 for women. We found an annual reduction in BAA rates among patients with diabetes of 9.8%, and the annual reduction in BKA for patients with diabetes was 15.1%. CONCLUSIONS/INTERPRETATION: The amputation rate in patients with diabetes is still several-fold higher than in persons without diabetes, but the improvements in diabetes care in recent years have resulted in a steady decline in amputation rates among patients with diabetes from this Danish cohort.

Methods to assess area and volume of wounds - a systematic review.

Wound measurement is important in monitoring the healing process of chronic wounds and in evaluating the effect of treatment. The objective of this systematic review was to evaluate evidence from the literature on accuracy, agreement, reliability and feasibility of wound measurement techniques described since 1994. Studies were identified by searching the electronic databases PubMed, Embase and Cochrane Library. Of the 12 013 studies identified, 43 were included in the review. A total of 30 papers evaluated techniques for measuring wound area and 13 evaluated techniques for measuring wound volume. The six approaches for measuring wound area were simple ruler method (10 papers), mathematical models (5 papers), manual planimetry (10 papers), digital planimetry (16 papers), stereophotogrammetry (2 papers) and digital imaging method (20 papers). Of these studies, 10 evaluated accuracy, 15 agreement, 17 reliability and 25 mentioned feasibility. The number of wounds examined in the studies was highly variable (n = 3-260). Studies evaluating techniques for measuring wound volume included between 1 and 50 wounds and evaluated accuracy (4 studies), agreement (6 studies), reliability (8 studies) and feasibility (12 studies). Digital planimetry and digital imaging were considered the most accurate and reliable methods for area measurement, particularly in larger and irregularly shaped wounds. None of the three-dimensional technologies have so far had a major impact, because of their low accuracy, high cost and complexity in handling the system set-up.

Structural Changes of Cutaneous Immune Cells in Patients With Type 1 Diabetes and Their Relationship With Diabetic Polyneuropathy.

BACKGROUND AND OBJECTIVES: Diabetic polyneuropathy (DPN) is a complication of diabetes characterized by pain or lack of peripheral sensation, but the underlying mechanisms are not yet fully understood. Recent evidence showed increased cutaneous macrophage infiltration in patients with type 2 diabetes and painful DPN, and this study aimed to understand whether the same applies to type 1 diabetes. METHODS: The study included 104 participants: 26 healthy controls and 78 participants with type 1 diabetes (participants without DPN [n = 24], participants with painless DPN [n = 29], and participants with painful DPN [n = 25]). Two immune cells, dermal IBA1+ macrophages and epidermal Langerhans cells (LCs, CD207+), were visualized and quantified using immunohistological labeling and stereological counting methods on skin biopsies from the participants. The IBA1+ macrophage infiltration, LC number density, LC soma cross-sectional area, and LC processes were measured in this study. RESULTS: Significant difference in IBA1+ macrophage expression was seen between the groups (p = 0.003), with lower expression of IBA1 in participants with DPN. No differences in LC morphologies (LC number density, soma cross-sectional area, and process level) were found between the groups (all p > 0.05). In addition, IBA1+ macrophages, but not LCs, correlated with intraepidermal nerve fiber density, Michigan neuropathy symptom inventory, (questionnaire and total score), severity of neuropathy as assessed by the Toronto clinical neuropathy score, and vibration detection threshold in the whole study cohort. DISCUSSION: This study showed expressional differences of cutaneous IBA1+ macrophages but not LC in participants with type 1 diabetes-induced DPN compared with those in controls. The study suggests that a reduction in macrophages may play a role in the development and progression of autoimmune-induced diabetic neuropathy.

Video-based eye tracking performance for computer-assisted diagnostic support of diabetic neuropathy.

Diabetes is currently one of the major public health threats. The essential components for effective treatment of diabetes include early diagnosis and regular monitoring. However, health-care providers are often short of human resources to closely monitor populations at risk. In this work, a video-based eye-tracking method is proposed as a low-cost alternative for detection of diabetic neuropathy. The method is based on the tracking of the eye-trajectories recorded on videos while the subject follows a target on a screen, forcing saccadic movements. Upon extraction of the eye trajectories, representation of the obtained time-series is made with the help of heteroscedastic ARX (H-ARX) models, which capture the dynamics and latency on the subject's response, while features based on the H-ARX model's predictive ability are subsequently used for classification. The methodology is evaluated on a population constituted by 11 control and 20 insulin-treated diabetic individuals suffering from diverse diabetic complications including neuropathy and retinopathy. Results show significant differences on latency and eye movement precision between the populations of control subjects and diabetics, while simultaneously demonstrating that both groups can be classified with an accuracy of 95%. Although this study is limited by the small sample size, the results align with other findings in the literature and encourage further research.

Facial erythema detects diabetic neuropathy using the fusion of machine learning, random matrix theory and self organized criticality.

Rubeosis faciei diabeticorum, caused by microangiopathy and characterized by a chronic facial erythema, is associated with diabetic neuropathy. In clinical practice, facial erythema of patients with diabetes is evaluated based on subjective observations of visible redness, which often goes unnoticed leading to microangiopathic complications. To address this major shortcoming, we designed a contactless, non-invasive diagnostic point-of-care-device (POCD) consisting of a digital camera and a screen. Our solution relies on (1) recording videos of subject's face (2) applying Eulerian video magnification to videos to reveal important subtle color changes in subject's skin that fall outside human visual limits (3) obtaining spatio-temporal tensor expression profile of these variations (4) studying empirical spectral density (ESD) function of the largest eigenvalues of the tensors using random matrix theory (5) quantifying ESD functions by modeling the tails and decay rates using power law in systems exhibiting self-organized-criticality and (6) designing an optimal ensemble of learners to classify subjects into those with diabetic neuropathy and those of a control group. By analyzing a short video, we obtained a sensitivity of 100% in detecting subjects diagnosed with diabetic neuropathy. Our POCD paves the way towards the development of an inexpensive home-based solution for early detection of diabetic neuropathy and its associated complications.

Non-invasive detection of diabetic complications via pattern analysis of temporal facial colour variations.

BACKGROUND AND OBJECTIVE: Diabetes mellitus is a common disorder amounting to 400 million patients worldwide. It is often accompanied by a number of complications, including neuropathy, nephropathy, and cardiovascular diseases. For example, peripheral neuropathy is present among 20-30% of diabetics before the diagnosis is substantiated. For this reason, a reliable detection method for diabetic complications is crucial and attracts a lot of research attention. METHODS: In this paper, we introduce a non-invasive detection framework for patients with diabetic complications that only requires short video recordings of faces from a standard commercial camera. We employed multiple image processing and pattern recognition techniques to process video frames, extract relevant information, and predict the health status. To evaluate our framework, we collected a dataset of 114 video files from diabetic patients, who were diagnosed with diabetes for years and 60 video files from the control group. Extracted features from videos were tested using two conceptually different classifiers. RESULTS: We found that our proposed framework correctly identifies patients with diabetic complications with 92.86% accuracy, 100% sensitivity, and 80% specificity. CONCLUSIONS: Our study brings a novel perspective on diagnosis procedures in this field. We used multiple techniques from image processing, pattern recognition, and machine learning to robustly process video frames and predict the health status of our subjects with high efficiency.

Genetic Discrimination Between LADA and Childhood-Onset Type 1 Diabetes Within the MHC.

OBJECTIVE: The MHC region harbors the strongest loci for latent autoimmune diabetes in adults (LADA); however, the strength of association is likely attenuated compared with that for childhood-onset type 1 diabetes. In this study, we recapitulate independent effects in the MHC class I region in a population with type 1 diabetes and then determine whether such conditioning in LADA yields potential genetic discriminators between the two subtypes within this region. RESEARCH DESIGN AND METHODS: Chromosome 6 was imputed using SNP2HLA, with conditional analysis performed in type 1 diabetes case subjects (n = 1,985) and control subjects (n = 2,219). The same approach was applied to a LADA cohort (n = 1,428) using population-based control subjects (n = 2,850) and in a separate replication cohort (656 type 1 diabetes case, 823 LADA case, and 3,218 control subjects). RESULTS: The strongest associations in the MHC class II region (rs3957146, ß [SE] = 1.44 [0.05]), as well as the independent effect of MHC class I genes, on type 1 diabetes risk, particularly HLA-B*39 (ß [SE] = 1.36 [0.17]), were confirmed. The conditional analysis in LADA versus control subjects showed significant association in the MHC class II region (rs3957146, ß [SE] = 1.14 [0.06]); however, we did not observe significant independent effects of MHC class I alleles in LADA. CONCLUSIONS: In LADA, the independent effects of MHC class I observed in type 1 diabetes were not observed after conditioning on the leading MHC class II associations, suggesting that the MHC class I association may be a genetic discriminator between LADA and childhood-onset type 1 diabetes.

Invisible Color Variations of Facial Erythema: A Novel Early Marker for Diabetic Complications?

AIM: (1) To quantify the invisible variations of facial erythema that occur as the blood flows in and out of the face of diabetic patients, during the blood pulse wave using an innovative image processing method, on videos recorded with a conventional digital camera and (2) to determine whether this "unveiled" facial red coloration and its periodic variations present specific characteristics in diabetic patients different from those in control subjects. METHODS: We video recorded the faces of 20 diabetic patients with peripheral neuropathy, retinopathy, and/or nephropathy and 10 nondiabetic control subjects, using a Canon EOS camera, for 240 s. Only one participant presented visible facial erythema. We applied novel image processing methods to make the facial redness and its variations visible and automatically detected and extracted the redness intensity of eight facial patches, from each frame. We compared average and standard deviations of redness in the two groups using t-tests. RESULTS: Facial redness varies, imperceptibly and periodically, between redder and paler, following the heart pulsation. This variation is consistently and significantly larger in diabetic patients compared to controls (p value < 0.001). CONCLUSIONS: Our study and its results (i.e., larger variations of facial redness with the heartbeats in diabetic patients) are unprecedented. One limitation is the sample size. Confirmation in a larger study would ground the development of a noninvasive cost-effective automatic tool for early detection of diabetic complications, based on measuring invisible redness variations, by image processing of facial videos captured at home with the patient's smartphone.

Lower mortality and cardiovascular event rates in patients with Latent Autoimmune Diabetes In Adults (LADA) as compared with type 2 diabetes and insulin deficient diabetes: A cohort study of 4368 patients.

BACKGROUND: Latent Autoimmune Diabetes in Adults (LADA) is the second most common form of diabetes, but data on its clinical course and prognosis are scarce. We compared long-term risk of mortality and cardiovascular outcomes in patients with LADA, type 2 diabetes mellitus (T2D), and insulin deficient diabetes (IDD). METHODS: We conducted a cohort study of 4368 adults with diabetes referred to the Department of Endocrinology, Odense University Hospital, Denmark, between 1997 and 2012. Data on comorbidity, cardiovascular outcomes and death were obtained from prospective medical databases. We compared adjusted hazard ratios (HRs) of mortality and cardiovascular outcomes for patients with LADA, T2D and IDD, respectively. RESULTS: We included 327 patients with LADA, 3539 with T2D and 502 with IDD. At diagnosis, patients with LADA were older (50 years (IQR 37-59)) than IDD patients (40 years (IQR 28-52)), but younger than patients with T2D (55 years (IQR 45-64)). During a median follow-up period of 6.6 years (IQR 3.4-9.4), patients with IDD had higher mortality than patients with LADA, age- and gender-adjusted HR 2.2 (95% CI, 1.5-3.2). T2D also conferred higher mortality than LADA, HR 1.4 (95% CI, 1.0-1.9). Compared with LADA patients, cardiovascular outcome rates were increased both with IDD, HR 1.2 (95% CI, 0.7-2.0) and T2D, HR 1.2 (95% CI, 0.8-1.8), with the strongest association observed for T2D vs. LADA and acute myocardial infarction HR 1.7 (95% CI, 0.8-3.5). CONCLUSION: LADA seems to be associated with lower mortality and lower risk of cardiovascular events, compared with both T2D and IDD.

First Genome-Wide Association Study of Latent Autoimmune Diabetes in Adults Reveals Novel Insights Linking Immune and Metabolic Diabetes.

OBJECTIVE: Latent autoimmune diabetes in adults (LADA) shares clinical features with both type 1 and type 2 diabetes; however, there is ongoing debate regarding the precise definition of LADA. Understanding its genetic basis is one potential strategy to gain insight into appropriate classification of this diabetes subtype. RESEARCH DESIGN AND METHODS: We performed the first genome-wide association study of LADA in case subjects of European ancestry versus population control subjects (n = 2,634 vs. 5,947) and compared against both case subjects with type 1 diabetes (n = 2,454 vs. 968) and type 2 diabetes (n = 2,779 vs. 10,396). RESULTS: The leading genetic signals were principally shared with type 1 diabetes, although we observed positive genetic correlations genome-wide with both type 1 and type 2 diabetes. Additionally, we observed a novel independent signal at the known type 1 diabetes locus harboring PFKFB3, encoding a regulator of glycolysis and insulin signaling in type 2 diabetes and inflammation and autophagy in autoimmune disease, as well as an attenuation of key type 1-associated HLA haplotype frequencies in LADA, suggesting that these are factors that distinguish childhood-onset type 1 diabetes from adult autoimmune diabetes. CONCLUSIONS: Our results support the need for further investigations of the genetic factors that distinguish forms of autoimmune diabetes as well as more precise classification strategies.

Metabolic risk profiles in diabetes stratified according to age at onset, islet autoimmunity and fasting C-peptide.

OBJECTIVE: Islet autoimmunity, age at onset and time to insulin treatment are often used to define subgroups of diabetes. However, the latter criterion is not clinical useful. Here, we examined whether an unbiased stratification of diabetes according to age at onset, fasting C-peptide and GAD autoantibodies (GADab) defines groups with differences in glycaemic control and markers of cardiometabolic risk. DESIGN AND METHODS: A cohort of 4374 adults with relatively newly diagnosed diabetes referred to a Danish hospital during 1997-2012 was stratified according to age at onset above or below 30 years, fasting C-peptide above or below 300 pmol/l (CPEPhigh or CPEPlow), and presence or absence of GADab (GADpos or GADneg). HbA1c, BMI, blood pressure (BP), lipid profile, alanine aminotransferase (ALT) and creatinine were evaluated. RESULTS: GADab were present in 13% of the cohort. Age at onset was not associated with major differences between groups. Patients with insulin deficient diabetes (CPEPlow; n = 503) had higher HbA1c but otherwise lower cardiometabolic risk (lower BMI, BP, LDL, triacylglycerol, and ALT, and higher HDL) than both patients with latent autoimmune diabetes of adults (LADA defined as GADposCPEPhigh; n = 327) and patients with type 2 diabetes (GADnegCPEPhigh; n = 3544). Patients with LADA defined an intermediate group with higher HbA1c but otherwise lower cardiometabolic risk than patients with type 2 diabetes. CONCLUSIONS: Our results demonstrate that fasting C-peptide and GADab status, but not age at onset, define groups of patients with diabetes with clinically relevant differences in glycaemic control and cardiometabolic risk.

[More research is needed in telemedicine for well-defined patient groups]. / Behov for mere forskning i telemedicin til veldefinerede patientgrupper.

The Whole Systems Demonstrator (WSD), a cluster randomized trial of effects of telehealth, was initiated in 2008 including 3.230 patients from 179 general practices. The objective of this review is to summarize the results from WSD based on publications made so far. Results from five publications show that telehealth reduces mortality (odds ratio 0.54) during 12 months. The use of secondary care is reduced, however, when including costs of telehealth, the total costs are higher for

A Randomized Controlled Trial Comparing Telemedical and Standard Outpatient Monitoring of Diabetic Foot Ulcers.

OBJECTIVE: The role of telemedical monitoring in diabetic foot ulcer care is still uncertain. Our aim was to compare telemedical and standard outpatient monitoring in the care of patients with diabetic foot ulcers in a randomized controlled trial. RESEARCH DESIGN AND METHODS: Of the 736 screened individuals with diabetic foot ulcers, 401 met the eligibility criteria and were randomized between October 2010 and November 2014. The per-protocol telemedical monitoring consisted of two consultations in the patient's own home and one consultation at the outpatient clinic. Standard practice consisted of three outpatient clinic visits. The three-visit cycle was repeated until study end point. The study end points were defined as complete ulcer healing, amputation, or death. RESULTS: One hundred ninety-three individuals were randomized to telemedical monitoring and 181 to standard care. Demographics were similar in both groups. A cause-specific Cox proportional hazards model showed no difference in individuals monitored through telemedicine regarding wound healing (hazard ratio 1.11 [95% CI 0.87, 1.42], P = 0.42) or amputation (0.87 [0.54, 1.42], P = 0.59). We found a higher mortality incidence in the telemedical monitoring group compared with the standard outpatient monitoring group (8.68 [6.93, 10.88], P = 0.0001). CONCLUSIONS: The findings of no significant difference regarding amputation and healing between telemedical and standard outpatient monitoring seem promising; however, for telemedical monitoring, a higher mortality throws into question the role of telemedicine in monitoring diabetic foot ulcers. Further studies are needed to investigate effects of telemedicine on mortality and other clinical outcomes and to identify patient subgroups that may have a poorer outcome through telemedical monitoring.

[More research is needed in telemedicine for well-defined patient groups].

The Whole Systems Demonstrator (WSD), a cluster randomized trial of effects of telehealth, was initiated in 2008 including 3.230 patients from 179 general practices. The objective of this review is to summarize the results from WSD based on publications made so far. Results from five publications show that telehealth reduces mortality (odds ratio 0.54) during 12 months. The use of secondary care is reduced, however, when including costs of telehealth, the total costs are higher for patients using telehealth. Many questions regarding differences between patient groups and the mechanism behind the effects remain unanswered.