We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline,... Show moreWe identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression. Show less
Dawed, A.Y.; Yee, S.W.; Zhou, K.X.; Leeuwen, N. van; Zhang, Y.F.; Siddiqui, M.K.; ... ; MetGen Plus DIRECT Consortium 2022
Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity, investigators of a previous study clustered people with diabetes according to five... Show moreType 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity, investigators of a previous study clustered people with diabetes according to five diabetes subtypes. The aim of the current study is to investigate the etiology of these clusters by comparing their molecular signatures. In three independent cohorts, in total 15,940 individuals were clustered based on five clinical characteristics. In a subset, genetic (N = 12,828), metabolomic (N = 2,945), lipidomic (N = 2,593), and proteomic (N = 1,170) data were obtained in plasma. For each data type, each cluster was compared with the other four clusters as the reference. The insulin-resistant cluster showed the most distinct molecular signature, with higher branched-chain amino acid, diacylglycerol, and triacylglycerol levels and aberrant protein levels in plasma were enriched for proteins in the intracellular PI3K/Akt pathway. The obese cluster showed higher levels of cytokines. The mild diabetes cluster with high HDL showed the most beneficial molecular profile with effects opposite of those seen in the insulin-resistant cluster. This study shows that clustering people with type 2 diabetes can identify underlying molecular mechanisms related to pancreatic islets, liver, and adipose tissue metabolism. This provides novel biological insights into the diverse aetiological processes that would not be evident when type 2 diabetes is viewed as a homogeneous disease. Show less
Memarian, E.; Hart, L.M. 't; Slieker, R.C.; Lemmers, R.F.L.; Heijden, A.A. van der; Rutters, F.; ... ; Dotz, V. 2021
Introduction Although associations of total plasma N-glycome (TPNG) with type 2 diabetes have been reported, little is known on the role of TPNG in type 2 diabetes complications, a major cause of... Show moreIntroduction Although associations of total plasma N-glycome (TPNG) with type 2 diabetes have been reported, little is known on the role of TPNG in type 2 diabetes complications, a major cause of type 2 diabetes-related morbidity and mortality. Here, we assessed TPNG in relation to type 2 diabetes complications in subsamples of two Dutch cohorts using mass spectrometry (n=1815 in DiaGene and n=1518 in Hoorn Diabetes Care System).Research design and methods Blood plasma samples and technical replicates were pipetted into 96-well plates in a randomized manner. Peptide:N-glycosidase F (PNGase F) was used to release N-glycans, whereafter sialic acids were derivatized for stabilization and linkage differentiation. After total area normalization, 68 individual glycan compositions were quantified in total and were used to calculate 45 derived traits which reflect structural features of glycosylation. Associations of glycan features with prevalent and incident microvascular or macrovascular complications were tested in logistic and Cox regression in both independent cohorts and the results were meta-analyzed.Results Our results demonstrated similarities between incident and prevalent complications. The strongest association for prevalent cardiovascular disease was a high level of bisection on a group of diantennary glycans (A2FS0B; OR=1.38, p=1.34x10(-11)), while for prevalent nephropathy the increase in 2,6-sialylation on triantennary glycans was most pronounced (A3E; OR=1.28, p=9.70x10(-6)). Several other TPNG features, including fucosylation, galactosylation, and sialylation, firmly demonstrated associations with prevalent and incident complications of type 2 diabetes.Conclusions These findings may provide a glance on how TPNG patterns change before complications emerge, paving the way for future studies on prediction biomarkers and potentially disease mechanisms. Show less
Beulens, J.W.J.; Yauw, J.S.; Elders, P.J.M.; Feenstra, T.; Herings, R.; Slieker, R.C.; ... ; Heijden, A.A. van der 2021
Aims/hypothesis Approximately 25% of people with type 2 diabetes experience a foot ulcer and their risk of amputation is 10-20 times higher than that of people without type 2 diabetes. Prognostic... Show moreAims/hypothesis Approximately 25% of people with type 2 diabetes experience a foot ulcer and their risk of amputation is 10-20 times higher than that of people without type 2 diabetes. Prognostic models can aid in targeted monitoring but an overview of their performance is lacking. This study aimed to systematically review prognostic models for the risk of foot ulcer or amputation and quantify their predictive performance in an independent cohort.Methods A systematic review identified studies developing prognostic models for foot ulcer or amputation over minimal 1 year follow-up applicable to people with type 2 diabetes. After data extraction and risk of bias assessment (both in duplicate), selected models were externally validated in a prospective cohort with a 5 year follow-up in terms of discrimination (C statistics) and calibration (calibration plots).Results We identified 21 studies with 34 models predicting polyneuropathy, foot ulcer or amputation. Eleven models were validated in 7624 participants, of whom 485 developed an ulcer and 70 underwent amputation. The models for foot ulcer showed C statistics (95% CI) ranging from 0.54 (0.54, 0.54) to 0.81 (0.75, 0.86) and models for amputation showed C statistics (95% CI) ranging from 0.63 (0.55, 0.71) to 0.86 (0.78, 0.94). Most models underestimated the ulcer or amputation risk in the highest risk quintiles. Three models performed well to predict a combined endpoint of amputation and foot ulcer (C statistics >0.75).Conclusions/interpretation Thirty-four prognostic models for the risk of foot ulcer or amputation were identified. Although the performance of the models varied considerably, three models performed well to predict foot ulcer or amputation and may be applicable to clinical practice. Show less
Pagano, E.; Konings, S.R.A.; Cuonzo, D. di; Rosato, R.; Bruno, G.; Heijden, A.A. van der; ... ; Feenstra, T.L. 2021
Aim To externally validate the UK Prospective Diabetes Study Outcomes Model version 2 (UKPDS-OM2) by comparing the predicted and observed outcomes in two European population-based cohorts of people... Show moreAim To externally validate the UK Prospective Diabetes Study Outcomes Model version 2 (UKPDS-OM2) by comparing the predicted and observed outcomes in two European population-based cohorts of people with type 2 diabetes.Materials and methods We used data from the Casale Monferrato Survey (CMS; n = 1931) and a subgroup of the Hoorn Diabetes Care System (DCS) cohort (n = 5188). The following outcomes were analysed: all-cause mortality, myocardial infarction (MI), ischaemic heart disease (IHD), stroke, and congestive heart failure (CHF). Model performance was assessed by comparing predictions with observed cumulative incidences in each cohort during follow-up.Results All-cause mortality was overestimated by the UKPDS-OM2 in both the cohorts, with a bias of 0.05 in the CMS and 0.12 in the DCS at 10 years of follow-up. For MI, predictions were consistently higher than observed incidence over the entire follow-up in both cohorts (10 years bias 0.07 for CMS and 0.10 for DCS). The model performed well for stroke and IHD outcomes in both cohorts. CHF incidence was predicted well for the DCS (5 years bias -0.001), but underestimated for the CMS cohort.Conclusions The UKPDS-OM2 consistently overpredicted the risk of mortality and MI in both cohorts during follow-up. Period effects may partially explain the differences. Results indicate that transferability is not satisfactory for all outcomes, and new or adjusted risk equations may be needed before applying the model to the Italian or Dutch settings. Show less
Introduction Early recognition of individuals with increased risk of sudden cardiac arrest (SCA) remains challenging. SCA research so far has used data from cardiologist care, but missed most SCA... Show moreIntroduction Early recognition of individuals with increased risk of sudden cardiac arrest (SCA) remains challenging. SCA research so far has used data from cardiologist care, but missed most SCA victims, since they were only in general practitioner (GP) care prior to SCA. Studying individuals with type 2 diabetes (T2D) in GP care may help solve this problem, as they have increased risk for SCA, and rich clinical datasets, since they regularly visit their GP for check-up measurements. This information can be further enriched with extensive genetic and metabolic information. Aim To describe the study protocol of the REcognition of Sudden Cardiac arrest vUlnErability in Diabetes (RESCUED) project, which aims at identifying clinical, genetic and metabolic factors contributing to SCA risk in individuals with T2D, and to develop a prognostic model for the risk of SCA. Methods The RESCUED project combines data from dedicated SCA and T2D cohorts, and GP data, from the same region in the Netherlands. Clinical data, genetic data (common and rare variant analysis) and metabolic data (metabolomics) will be analysed (using classical analysis techniques and machine learning methods) and combined into a prognostic model for risk of SCA. Conclusion The RESCUED project is designed to increase our ability at early recognition of elevated SCA risk through an innovative strategy of focusing on GP data and a multidimensional methodology including clinical, genetic and metabolic analyses. Show less
Extracellular matrix protein turnover may play an important role in left atrial (LA) remodelling. The aim is to investigate the associations between matrix metalloproteinase (MMPs), tissue... Show moreExtracellular matrix protein turnover may play an important role in left atrial (LA) remodelling. The aim is to investigate the associations between matrix metalloproteinase (MMPs), tissue inhibitor of metalloproteinase (TIMP-1) and LA volume index (LAVI) and if these associations are independent of TIMP-1 levels. Participants from The Hoorn Study, a population-based cohort study (n= 674), underwent echocardiography. Serum MMPs (i.e., MMP-1, MMP-2, MMP-3, MMP-9, and MMP-10) and TIMP-1 levels were measured with ELISA. Multiple linear regression analyses were used. MMP-1 levels were not associated with LAVI. Higher MMP-2 levels were associated with larger LAVI (regression coefficient per SD increase in MMP (95% CI); 0.03 (0.01; 0.05). Higher MMP-3 and MMP-9 levels were associated with smaller LAVI; -0.04 (-0.07; -0.01) and -0.04 (-0.06; -0.02) respectively. Only in women were higher MMP-10 levels associated with larger LAVI; 0.04 (0.00; 0.07,p-interaction 0.04). Additionally, only in women were higher TIMP-1 levels associated with smaller LAVI; -0.05 (-0.09; -0.01,p-interaction 0.03). The associations between MMPs and LAVI were independent of TIMP-1 levels. In conclusion, serum MMPs are associated with LAVI, independent of CVD risk factors and TIMP-1 levels. In addition, these associations differ according to sex and within MMP subgroups. This shows that the role of MMPs in LA remodelling is complex. Show less
Context: There is a need for novel biomarkers and better understanding of the pathophysiology of diabetic kidney disease.Objective: To investigate associations between plasma metabolites and kidney... Show moreContext: There is a need for novel biomarkers and better understanding of the pathophysiology of diabetic kidney disease.Objective: To investigate associations between plasma metabolites and kidney function in people with type 2 diabetes (T2D).Design: 3089 samples from individuals with T2D, collected between 1999 and 2015, from 5 independent Dutch cohort studies were included. Up to 7 years follow-up was available in 1100 individuals from 2 of the cohorts.Main outcome measures: Plasma metabolites (n = 149) were measured by nuclear magnetic resonance spectroscopy. Associations between metabolites and estimated glomerular filtration rate (eGFR), urinary albumin-to-creatinine ratio (UACR), and eGFR slopes were investigated in each study followed by random effect meta-analysis. Adjustments included traditional cardiovascular risk factors and correction for multiple testing.Results: In total, 125 metabolites were significantly associated (P-FDR = 1.5x10(-32) - 0.046; beta = -11.98-2.17) with eGFR. Inverse associations with eGFR were demonstrated for branched-chain and aromatic amino acids (AAAs), glycoprotein acetyls, triglycerides (TGs), lipids in very low-density lipoproteins (VLDL) subclasses, and fatty acids (P-FDR < 0.03). We observed positive associations with cholesterol and phospholipids in high-density lipoproteins (HDL) and apolipoprotein A1 (P-FDR < 0.05). Albeit some metabolites were associated with UACR levels (P < 0.05), significance was lost after correction for multiple testing. Tyrosine and HDL-related metabolites were positively associated with eGFR slopes before adjustment for multiple testing (P-Tyr = 0.003; P-HDLrelated < 0.05), but not after.Conclusions: This study identified metabolites associated with impaired kidney function in T2D, implying involvement of lipid and amino acid metabolism in the pathogenesis. Whether these processes precede or are consequences of renal impairment needs further investigation. Show less
Aims/hypothesis The aims of this study were to identify all published prognostic models predicting retinopathy risk applicable to people with type 2 diabetes, to assess their quality and accuracy,... Show moreAims/hypothesis The aims of this study were to identify all published prognostic models predicting retinopathy risk applicable to people with type 2 diabetes, to assess their quality and accuracy, and to validate their predictive accuracy in a head-to-head comparison using an independent type 2 diabetes cohort. Methods A systematic search was performed in PubMed and Embase in December 2019. Studies that met the following criteria were included: (1) the model was applicable in type 2 diabetes; (2) the outcome was retinopathy; and (3) follow-up was more than 1 year. Screening, data extraction (using the checklist for critical appraisal and data extraction for systemic reviews of prediction modelling studies [CHARMS]) and risk of bias assessment (by prediction model risk of bias assessment tool [PROBAST]) were performed independently by two reviewers. Selected models were externally validated in the large Hoorn Diabetes Care System (DCS) cohort in the Netherlands. Retinopathy risk was calculated using baseline data and compared with retinopathy incidence over 5 years. Calibration after intercept adjustment and discrimination (Harrell's C statistic) were assessed. Results Twelve studies were included in the systematic review, reporting on 16 models. Outcomes ranged from referable retinopathy to blindness. Discrimination was reported in seven studies with C statistics ranging from 0.55 (95% CI 0.54, 0.56) to 0.84 (95% CI 0.78, 0.88). Five studies reported on calibration. Eight models could be compared head-to-head in the DCS cohort (N = 10,715). Most of the models underestimated retinopathy risk. Validating the models against different severities of retinopathy, C statistics ranged from 0.51 (95% CI 0.49, 0.53) to 0.89 (95% CI 0.88, 0.91). Conclusions/interpretation Several prognostic models can accurately predict retinopathy risk in a population-based type 2 diabetes cohort. Most of the models include easy-to-measure predictors enhancing their applicability. Tailoring retinopathy screening frequency based on accurate risk predictions may increase the efficiency and cost-effectiveness of diabetic retinopathy care. Registration PROSPERO registration ID CRD42018089122 Show less
OBJECTIVEProgression to insulin therapy in clinically diagnosed type 2 diabetes is highly variable. GAD65 autoantibodies (GADA) are associated with faster progression, but their predictive value is... Show moreOBJECTIVEProgression to insulin therapy in clinically diagnosed type 2 diabetes is highly variable. GAD65 autoantibodies (GADA) are associated with faster progression, but their predictive value is limited. We aimed to determine if a type 1 diabetes genetic risk score (T1D GRS) could predict rapid progression to insulin treatment over and above GADA testing.RESEARCH DESIGN AND METHODSWe examined the relationship between T1D GRS, GADA (negative or positive), and rapid insulin requirement (within 5 years) using Kaplan-Meier survival analysis and Cox regression in 8,608 participants with clinical type 2 diabetes (onset >35 years and treated without insulin for 6 months). T1D GRS was both analyzed continuously (as standardized scores) and categorized based on previously reported centiles of a population with type 1 diabetes (<5th [low], 5th-50th [medium], and >50th [high]).RESULTSIn GADA-positive participants (3.3%), those with higher T1D GRS progressed to insulin more quickly: probability of insulin requirement at 5 years (95% CI): 47.9% (35.0%, 62.78%) (high T1D GRS) vs. 27.6% (20.5%, 36.5%) (medium T1D GRS) vs. 17.6% (11.2%, 27.2%) (low T1D GRS); P = 0.001. In contrast, T1D GRS did not predict rapid insulin requirement in GADA-negative participants (P = 0.4). In Cox regression analysis with adjustment for age of diagnosis, BMI, and cohort, T1D GRS was independently associated with time to insulin only in the presence of GADA: hazard ratio per SD increase was 1.48 (1.15, 1.90); P = 0.002.CONCLUSIONSA T1D GRS alters the clinical implications of a positive GADA test in patients with clinical type 2 diabetes and is independent of and additive to clinical features. Show less
