Epidemiology of heart failure in diabetes: a disease in disguise.

Left ventricular diastolic dysfunction (LVDD) without symptoms, and heart failure (HF) with preserved ejection fraction (HFpEF) represent the most common phenotypes of HF in individuals with type 2 diabetes mellitus, and are more common than HF with reduced ejection fraction (HFrEF), HF with mildly reduced ejection fraction (HFmrEF) and left ventricular systolic dysfunction (LVSD) in these individuals. However, diagnostic criteria for HF have changed over the years, resulting in heterogeneity in the prevalence/incidence rates reported in different studies. We aimed to give an overview of the diagnosis and epidemiology of HF in type 2 diabetes, using both a narrative and systematic review approach; we focus narratively on diagnosing (using the 2021 European Society of Cardiology [ESC] guidelines) and screening for HF in type 2 diabetes. We performed an updated (2016-October 2022) systematic review and meta-analysis of studies reporting the prevalence and incidence of HF subtypes in adults ≥18 years with type 2 diabetes, using echocardiographic data. Embase and MEDLINE databases were searched and data were assessed using random-effects meta-analyses, with findings presented as forest plots. From the 5015 studies found, 209 were screened using the full-text article. In total, 57 studies were included, together with 29 studies that were identified in a prior meta-analysis; these studies reported on the prevalence of LVSD (n=25 studies, 24,460 individuals), LVDD (n=65 studies, 25,729 individuals), HFrEF (n=4 studies, 4090 individuals), HFmrEF (n=2 studies, 2442 individuals) and/or HFpEF (n=8 studies, 5292 individuals), and on HF incidence (n=7 studies, 17,935 individuals). Using Hoy et al's risk-of-bias tool, we found that the studies included generally had a high risk of bias. They showed a prevalence of 43% (95% CI 37%, 50%) for LVDD, 17% (95% CI 7%, 35%) for HFpEF, 6% (95% CI 3%, 10%) for LVSD, 7% (95% CI 3%, 15%) for HFrEF, and 12% (95% CI 7%, 22%) for HFmrEF. For LVDD, grade I was found to be most prevalent. Additionally, we reported a higher incidence rate of HFpEF (7% [95% CI 4%, 11%]) than HFrEF 4% [95% CI 3%, 7%]). The evidence is limited by the heterogeneity of the diagnostic criteria over the years. The systematic section of this review provides new insights on the prevalence/incidence of HF in type 2 diabetes, unveiling a large pre-clinical target group with LVDD/HFpEF in which disease progression could be halted by early recognition and treatment.Registration PROSPERO ID CRD42022368035.

Trajectories of clinical characteristics, complications and treatment choices in data-driven subgroups of type 2 diabetes.

AIMS/HYPOTHESIS: This study aimed to explore the added value of subgroups that categorise individuals with type 2 diabetes by k-means clustering for two primary care registries (the Netherlands and Scotland), inspired by Ahlqvist's novel diabetes subgroups and previously analysed by Slieker et al. METHODS: We used two Dutch and Scottish diabetes cohorts (N=3054 and 6145; median follow-up=11.2 and 12.3 years, respectively) and defined five subgroups by k-means clustering with age at baseline, BMI, HbA1c, HDL-cholesterol and C-peptide. We investigated differences between subgroups by trajectories of risk factor values (random intercept models), time to diabetes-related complications (logrank tests and Cox models) and medication patterns (multinomial logistic models). We also compared directly using the clustering indicators as predictors of progression vs the k-means discrete subgroups. Cluster consistency over follow-up was assessed. RESULTS: Subgroups' risk factors were significantly different, and these differences remained generally consistent over follow-up. Among all subgroups, individuals with severe insulin resistance faced a significantly higher risk of myocardial infarction both before (HR 1.65; 95% CI 1.40, 1.94) and after adjusting for age effect (HR 1.72; 95% CI 1.46, 2.02) compared with mild diabetes with high HDL-cholesterol. Individuals with severe insulin-deficient diabetes were most intensively treated, with more than 25% prescribed insulin at 10 years of diagnosis. For severe insulin-deficient diabetes relative to mild diabetes, the relative risks for using insulin relative to no common treatment would be expected to increase by a factor of 3.07 (95% CI 2.73, 3.44), holding other factors constant. Clustering indicators were better predictors of progression variation relative to subgroups, but prediction accuracy may improve after combining both. Clusters were consistent over 8 years with an accuracy ranging from 59% to 72%. CONCLUSIONS/INTERPRETATION: Data-driven subgroup allocations were generally consistent over follow-up and captured significant differences in risk factor trajectories, medication patterns and complication risks. Subgroups serve better as a complement rather than as a basis for compressing clustering indicators.

An omics-based machine learning approach to predict diabetes progression: a RHAPSODY study.

AIMS/HYPOTHESIS: People with type 2 diabetes are heterogeneous in their disease trajectory, with some progressing more quickly to insulin initiation than others. Although classical biomarkers such as age, HbA1c and diabetes duration are associated with glycaemic progression, it is unclear how well such variables predict insulin initiation or requirement and whether newly identified markers have added predictive value. METHODS: In two prospective cohort studies as part of IMI-RHAPSODY, we investigated whether clinical variables and three types of molecular markers (metabolites, lipids, proteins) can predict time to insulin requirement using different machine learning approaches (lasso, ridge, GRridge, random forest). Clinical variables included age, sex, HbA1c, HDL-cholesterol and C-peptide. Models were run with unpenalised clinical variables (i.e. always included in the model without weights) or penalised clinical variables, or without clinical variables. Model development was performed in one cohort and the model was applied in a second cohort. Model performance was evaluated using Harrel's C statistic. RESULTS: Of the 585 individuals from the Hoorn Diabetes Care System (DCS) cohort, 69 required insulin during follow-up (1.0-11.4 years); of the 571 individuals in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) cohort, 175 required insulin during follow-up (0.3-11.8 years). Overall, the clinical variables and proteins were selected in the different models most often, followed by the metabolites. The most frequently selected clinical variables were HbA1c (18 of the 36 models, 50%), age (15 models, 41.2%) and C-peptide (15 models, 41.2%). Base models (age, sex, BMI, HbA1c) including only clinical variables performed moderately in both the DCS discovery cohort (C statistic 0.71 [95% CI 0.64, 0.79]) and the GoDARTS replication cohort (C 0.71 [95% CI 0.69, 0.75]). A more extensive model including HDL-cholesterol and C-peptide performed better in both cohorts (DCS, C 0.74 [95% CI 0.67, 0.81]; GoDARTS, C 0.73 [95% CI 0.69, 0.77]). Two proteins, lactadherin and proto-oncogene tyrosine-protein kinase receptor, were most consistently selected and slightly improved model performance. CONCLUSIONS/INTERPRETATION: Using machine learning approaches, we show that insulin requirement risk can be modestly well predicted by predominantly clinical variables. Inclusion of molecular markers improves the prognostic performance beyond that of clinical variables by up to 5%. Such prognostic models could be useful for identifying people with diabetes at high risk of progressing quickly to treatment intensification. DATA AVAILABILITY: Summary statistics of lipidomic, proteomic and metabolomic data are available from a Shiny dashboard at https://rhapdata-app.vital-it.ch .

The yield of routine laboratory examination in osteoporosis evaluation in primary care.

This study evaluated the yield of routine laboratory examination in a large population of older women in primary care. The prevalence of laboratory abnormalities was low and the clinical consequences in follow-up were limited. There was a weak association of laboratory abnormalities with osteoporosis but no association with vertebral fractures and recent fractures. PURPOSE: Most osteoporosis guidelines advice routine laboratory examination. We have investigated the yield of laboratory examinations in facture risk evaluation of elderly women in primary care. METHODS: We assessed the prevalence of laboratory abnormalities and their association with risk factors for fractures, recent fractures, low bone mineral density (BMD), and prevalent vertebral fracture in 8996 women ≥ 65 years of age participating in a primary care fracture risk screening study. In a sample of 2208 of these participants, we also evaluated the medical consequences in the medical records during a follow-up period of ≥ 1 year. RESULTS: Vitamin D deficiency (< 30 nmol/L) was present in 13% and insufficiency (< 50 nmol/L) in 43% of the study sample. The prevalence of other laboratory abnormalities (ESR, calcium, creatinine, FT4) was 4.6% in women with risk factors for fractures, 6.1% in women with low BMD (T-score ≤ - 2.5), 6.0% after a prevalent vertebral fracture, 5.2% after a recent fracture and 2.6% in the absence of important risk factors for fractures. Laboratory abnormalities other than vitamin D were associated with low BMD (OR 1.4, 95%CI 1.1-1.8) but not with prevalent vertebral fractures nor recent fractures. Low BMD was associated with renal failure (OR 2.0, 95%CI 1.3-3.4), vitamin D insufficiency (OR 1.2, 95%CI 1.0-1.3) and deficiency (OR 1.3, 95%CI 1.1-.5). In the follow-up period, 82% of the laboratory abnormalities did not result in a new diagnosis or treatment reported in the medical records. CONCLUSIONS: We identified a low prevalence of laboratory abnormalities in a primary care population of older women and the majority of these findings had no medical consequences.

A meta-analysis of previous falls and subsequent fracture risk in cohort studies.

The relationship between self-reported falls and fracture risk was estimated in an international meta-analysis of individual-level data from 46 prospective cohorts. Previous falls were associated with an increased fracture risk in women and men and should be considered as an additional risk factor in the FRAX® algorithm. INTRODUCTION: Previous falls are a well-documented risk factor for subsequent fracture but have not yet been incorporated into the FRAX algorithm. The aim of this study was to evaluate, in an international meta-analysis, the association between previous falls and subsequent fracture risk and its relation to sex, age, duration of follow-up, and bone mineral density (BMD). METHODS: The resource comprised 906,359 women and men (66.9% female) from 46 prospective cohorts. Previous falls were uniformly defined as any fall occurring during the previous year in 43 cohorts; the remaining three cohorts had a different question construct. The association between previous falls and fracture risk (any clinical fracture, osteoporotic fracture, major osteoporotic fracture, and hip fracture) was examined using an extension of the Poisson regression model in each cohort and each sex, followed by random-effects meta-analyses of the weighted beta coefficients. RESULTS: Falls in the past year were reported in 21.4% of individuals. During a follow-up of 9,102,207 person-years, 87,352 fractures occurred of which 19,509 were hip fractures. A previous fall was associated with a significantly increased risk of any clinical fracture both in women (hazard ratio (HR) 1.42, 95% confidence interval (CI) 1.33-1.51) and men (HR 1.53, 95% CI 1.41-1.67). The HRs were of similar magnitude for osteoporotic, major osteoporotic fracture, and hip fracture. Sex significantly modified the association between previous fall and fracture risk, with predictive values being higher in men than in women (e.g., for major osteoporotic fracture, HR 1.53 (95% CI 1.27-1.84) in men vs. HR 1.32 (95% CI 1.20-1.45) in women, P for interaction = 0.013). The HRs associated with previous falls decreased with age in women and with duration of follow-up in men and women for most fracture outcomes. There was no evidence of an interaction between falls and BMD for fracture risk. Subsequent risk for a major osteoporotic fracture increased with each additional previous fall in women and men. CONCLUSIONS: A previous self-reported fall confers an increased risk of fracture that is largely independent of BMD. Previous falls should be considered as an additional risk factor in future iterations of FRAX to improve fracture risk prediction.

Is the association between social jetlag and BMI mediated by lifestyle? A cross-sectional survey study in the Dutch general population.

OBJECTIVE: Social jetlag is a discordance between the social and biological rhythm and is associated with higher HbA1c, higher BMI, and higher odds of obesity. The pathways that could explain these associations are still debated. This study aims to assess the mediating role of several lifestyle factors in the cross-sectional association between social jetlag and BMI. METHODS: We used cross-sectional data from 1784 adults from urban areas in the Netherlands, collected in 2019. Social jetlag (difference in midpoint of sleep between week and weekend nights) was categorized as low(<1 h), moderate(1-2h), and high(>2 h). BMI(kg/m2) was calculated from self-reported height and weight. The association between social jetlag and BMI was assessed using linear regression, adjusted for sex, age, education, and sleep duration and stratified for the effect modifier stress (high vs. low). Mediation analysis was performed for self-reported smoking, physical activity, alcohol consumption, and adherence to a healthy diet. RESULTS: High social jetlag was associated with higher BMI (0.69 kg/m2,95%CI 0.05;1.33). This association was stronger in people with high stress (0.93 kg/m2,95%CI 0.09;1.76). Social jetlag was also associated with higher odds of smoking, lower physical activity, higher alcohol consumption, and lower healthy diet adherence. In people with high stress, these factors mediated 10-15% of the association between social jetlag and BMI. CONCLUSIONS: Social jetlag is associated with higher BMI and this association is stronger in people with high stress. In people with high stress, healthy diet adherence mediated 12% of this association. Other pathways involved in this association should be further investigated.

Cultural competency of GP trainees and GP trainers: a cross-sectional survey study.

OBJECTIVE: To assess the cultural competence (CC) of GP trainees and GP trainers.Design and setting: A cross-sectional survey study was conducted at the GP Training Institute of Amsterdam UMC. SUBJECTS: We included 92 GP trainees and 186 GP trainers. MAIN OUTCOME MEASURES: We measured the three domains of cultural competency: 1) knowledge, 2) culturally competent attitudes and 3) culturally competent skills. Regression models were used to identify factors associated with levels of CC. Participants rated their self-perceived CC at the beginning and end of the survey, and the correlation between self-perceived and measured CC was assessed. RESULTS: Approximately 94% of the GP trainees and 81% of the GP trainers scored low on knowledge; 45% and 42%, respectively, scored low on culturally competent attitudes. The level of culturally competent skills was moderate (54.3%) or low (48.4%) for most GP trainees and GP trainers. The year of residency and the GP training institute were significantly associated with one or more (sub-)domains of CC in GP trainees. Having >10% migrant patients and experience as a GP trainer were positively associated with one or more (sub-) domains of cultural competence in GP trainers. The correlation between measured and self-perceived CC was positive overall but very weak (Spearman correlation coefficient ranging from -0.1-0.3). CONCLUSION: The level of cultural competence was low in both groups, especially in the knowledge scores. Cultural competence increased with experience and exposure to an ethnically diverse patient population. Our study highlights the need for cultural competence training in the GP training curricula.

General practitioner (GP) trainees find cross-cultural consultations stressful due to a self-perceived lack of cultural competence (CC). The level of CC in general practice is as yet unknown.On average, the level of CC was low for the majority of GP trainees and GP trainers, especially for the scores on knowledge.CC increased with experience and exposure to an ethnically diverse patient population.GP trainees and trainers perceived a lack of covered education on various topics related to the care of migrants.Our study highlights the need for cultural competence training in the GP training curricula.

Apolipoprotein-CIII O-Glycosylation Is Associated with Micro- and Macrovascular Complications of Type 2 Diabetes.

Apolipoprotein-CIII (apo-CIII) inhibits the clearance of triglycerides from circulation and is associated with an increased risk of diabetes complications. It exists in four main proteoforms: O-glycosylated variants containing either zero, one, or two sialic acids and a non-glycosylated variant. O-glycosylation may affect the metabolic functions of apo-CIII. We investigated the associations of apo-CIII glycosylation in blood plasma, measured by mass spectrometry of the intact protein, and genetic variants with micro- and macrovascular complications (retinopathy, nephropathy, neuropathy, cardiovascular disease) of type 2 diabetes in a DiaGene study (n = 1571) and the Hoorn DCS cohort (n = 5409). Mono-sialylated apolipoprotein-CIII (apo-CIII1) was associated with a reduced risk of retinopathy (ß = -7.215, 95% CI -11.137 to -3.294) whereas disialylated apolipoprotein-CIII (apo-CIII2) was associated with an increased risk (ß = 5.309, 95% CI 2.279 to 8.339). A variant of the GALNT2-gene (rs4846913), previously linked to lower apo-CIII0a, was associated with a decreased prevalence of retinopathy (OR = 0.739, 95% CI 0.575 to 0.951). Higher apo-CIII1 levels were associated with neuropathy (ß = 7.706, 95% CI 2.317 to 13.095) and lower apo-CIII0a with macrovascular complications (ß = -9.195, 95% CI -15.847 to -2.543). In conclusion, apo-CIII glycosylation was associated with the prevalence of micro- and macrovascular complications of diabetes. Moreover, a variant in the GALNT2-gene was associated with apo-CIII glycosylation and retinopathy, suggesting a causal effect. The findings facilitate a molecular understanding of the pathophysiology of diabetes complications and warrant consideration of apo-CIII glycosylation as a potential target in the prevention of diabetes complications.

Altered blood gene expression in the obesity-related type 2 diabetes cluster may be causally involved in lipid metabolism: a Mendelian randomisation study.

AIMS/HYPOTHESIS: The aim of this study was to identify differentially expressed long non-coding RNAs (lncRNAs) and mRNAs in whole blood of people with type 2 diabetes across five different clusters: severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), mild diabetes (MD) and mild diabetes with high HDL-cholesterol (MDH). This was to increase our understanding of different molecular mechanisms underlying the five putative clusters of type 2 diabetes. METHODS: Participants in the Hoorn Diabetes Care System (DCS) cohort were clustered based on age, BMI, HbA1c, C-peptide and HDL-cholesterol. Whole blood RNA-seq was used to identify differentially expressed lncRNAs and mRNAs in a cluster compared with all others. Differentially expressed genes were validated in the Innovative Medicines Initiative DIabetes REsearCh on patient straTification (IMI DIRECT) study. Expression quantitative trait loci (eQTLs) for differentially expressed RNAs were obtained from a publicly available dataset. To estimate the causal effects of RNAs on traits, a two-sample Mendelian randomisation analysis was performed using public genome-wide association study (GWAS) data. RESULTS: Eleven lncRNAs and 175 mRNAs were differentially expressed in the MOD cluster, the lncRNA AL354696.2 was upregulated in the SIDD cluster and GPR15 mRNA was downregulated in the MDH cluster. mRNAs and lncRNAs that were differentially expressed in the MOD cluster were correlated among each other. Six lncRNAs and 120 mRNAs validated in the IMI DIRECT study. Using two-sample Mendelian randomisation, we found 52 mRNAs to have a causal effect on anthropometric traits (n=23) and lipid metabolism traits (n=10). GPR146 showed a causal effect on plasma HDL-cholesterol levels (p = 2×10-15), without evidence for reverse causality. CONCLUSIONS/INTERPRETATION: Multiple lncRNAs and mRNAs were found to be differentially expressed among clusters and particularly in the MOD cluster. mRNAs in the MOD cluster showed a possible causal effect on anthropometric traits, lipid metabolism traits and blood cell fractions. Together, our results show that individuals in the MOD cluster show aberrant RNA expression of genes that have a suggested causal role on multiple diabetes-relevant traits.

Kidney function measures and cardiovascular outcomes in people with diabetes: the Hoorn Diabetes Care System cohort.

AIMS/HYPOTHESIS: Both manifestations of kidney disease in diabetes, reduced eGFR (ml/min per 1.73 m2) and increased urinary albumin/creatinine ratio (UACR, mg/mmol), may increase the risk of specific CVD subtypes in adults with diabetes. METHODS: We assessed the prospective association between annually recorded measures of eGFR and UACR and the occurrence of myocardial infarction (MI), CHD, stroke, heart failure (HF) and cardiovascular mortality in 13,657 individuals with diabetes (53.6% male, age 62.3±12.1 years) from the Hoorn Diabetes Care System cohort, using data obtained between 1998 and 2018. Multivariate time-dependent Cox regression models adjusted for cardiovascular risk factors were used to estimate HRs and 95% CI. Associations of eGFR were adjusted for UACR values and vice versa. Effect modification by sex was investigated for all associations. RESULTS: After a mean follow-up period of 7 years, event rates per 1000 person-years were 3.08 for MI, 3.72 for CHD, 1.12 for HF, 0.84 for stroke and 6.25 for cardiovascular mortality. Mildly reduced eGFR (60-90 ml/min per 1.73 m2) and moderately to severely reduced eGFR (<59 ml/min per 1.73 m2) were associated with higher risks of MI (HR 1.52; 95% CI 1.10, 2.12 and HR 1.69; 95% CI 1.09, 2.64) and CHD (HR 1.67; 95% CI 1.23, 2.26 and HR 2.01; 95% CI 1.34, 3.02) compared with normal eGFR (>90 ml/min per 1.73 m2). Mildly reduced eGFR was associated with a higher risk of stroke (HR 2.53; 95% CI 1.27, 5.03). Moderately increased UACR (3-30 mg/mmol) and severely increased UACR (>30 mg/mmol) were prospectively associated with a higher cardiovascular mortality risk in men and women (HR 1.87; 95% CI 1.41, 2.47 and HR 2.78; 95% CI 1.78, 4.34) compared with normal UACR (<3 mg/mmol). Significant effect modification by sex was observed for the association between UACR and HF. Because there were a limited number of HF events within the category of UACR >30 mg/mmol, categories were combined into UACR <3.0 and >3.0 mg/mmol in the stratified analysis. Women but not men with UACR >3.0 mg/mmol had a significantly higher risk of HF compared with normal UACR (HR 2.79; 95% CI 1.47, 5.28). CONCLUSIONS/INTERPRETATION: This study showed differential and independent prospective associations between manifestations of early kidney damage in diabetes and several CVD subtypes, suggesting that regular monitoring of both kidney function measures may help to identify individuals at higher risk of specific cardiovascular events.

Patient-reported outcomes for people with diabetes: what and how to measure? A narrative review.

Patient-reported outcomes (PROs) are valuable for shared decision making and research. Patient-reported outcome measures (PROMs) are questionnaires used to measure PROs, such as health-related quality of life (HRQL). Although core outcome sets for trials and clinical practice have been developed separately, they, as well as other initiatives, recommend different PROs and PROMs. In research and clinical practice, different PROMs are used (some generic, some disease-specific), which measure many different things. This is a threat to the validity of research and clinical findings in the field of diabetes. In this narrative review, we aim to provide recommendations for the selection of relevant PROs and psychometrically sound PROMs for people with diabetes for use in clinical practice and research. Based on a general conceptual framework of PROs, we suggest that relevant PROs to measure in people with diabetes are: disease-specific symptoms (e.g. worries about hypoglycaemia and diabetes distress), general symptoms (e.g. fatigue and depression), functional status, general health perceptions and overall quality of life. Generic PROMs such as the 36-Item Short Form Health Survey (SF-36), WHO Disability Assessment Schedule (WHODAS 2.0), or Patient-Reported Outcomes Measurement Information System (PROMIS) measures could be considered to measure commonly relevant PROs, supplemented with disease-specific PROMs where needed. However, none of the existing diabetes-specific PROM scales has been sufficiently validated, although the Diabetes Symptom Self-Care Inventory (DSSCI) for measuring diabetes-specific symptoms and the Diabetes Distress Scale (DDS) and Problem Areas in Diabetes (PAID) for measuring distress showed sufficient content validity. Standardisation and use of relevant PROs and psychometrically sound PROMs can help inform people with diabetes about the expected course of disease and treatment, for shared decision making, to monitor outcomes and to improve healthcare. We recommend further validation studies of diabetes-specific PROMs that have sufficient content validity for measuring disease-specific symptoms and consider generic item banks developed based on item response theory for measuring commonly relevant PROs.

Validation of the ARIC prediction model for sudden cardiac death in the European population: The ESCAPE-NET project.

BACKGROUND: Sudden cardiac death is responsible for 10% to 20% of all deaths in Europe. The current study investigates how well the risk of sudden cardiac death can be predicted. To this end, we validated a previously developed prediction model for sudden cardiac death from the Atherosclerosis Risk in Communities study (USA). METHODS: Data from participants of the Copenhagen City Heart Study (CCHS) (n=9988) was used to externally validate the previously developed prediction model for sudden cardiac death. The model's performance was assessed through discrimination (C-statistic) and calibration by the Hosmer-Lemeshow goodness-of-fit (HL) statistics suited for censored data and visual inspection of calibration plots. Additional validation was performed using data from the Hoorn Study (N=2045), employing the same methods. RESULTS: During ten years of follow-up of CCHS participants (mean age: 58.7 years, 56.2% women), 425 experienced SCD (4.2%). The prediction model showed good discrimination for sudden cardiac death risk (C-statistic: 0.81, 95% CI: 0.79-0.83). Calibration was robust (HL statistic: P=0.8). Visual inspection of the calibration plot showed that the calibration could be improved. Sensitivity was 89.8%, and specificity was 60.6%. The positive and negative predictive values were 10.1% and 99.2%. Model performance was similar in the Hoorn Study (C-statistic: 0.81, 95% CI: 0.77-0.85 and the HL statistic: 1.00). CONCLUSION: Our study showed that the previously developed prediction model in North American adults performs equally well in identifying those at risk for sudden cardiac death in a general North-West European population. However, the positive predictive value is low.

IgG N-glycans are associated with prevalent and incident complications of type 2 diabetes.

AIMS/HYPOTHESIS: Inflammation is important in the development of type 2 diabetes complications. The N-glycosylation of IgG influences its role in inflammation. To date, the association of plasma IgG N-glycosylation with type 2 diabetes complications has not been extensively investigated. We hypothesised that N-glycosylation of IgG may be related to the development of complications of type 2 diabetes. METHODS: In three independent type 2 diabetes cohorts, plasma IgG N-glycosylation was measured using ultra performance liquid chromatography (DiaGene n = 1815, GenodiabMar n = 640) and mass spectrometry (Hoorn Diabetes Care Study n = 1266). We investigated the associations of IgG N-glycosylation (fucosylation, galactosylation, sialylation and bisection) with incident and prevalent nephropathy, retinopathy and macrovascular disease using Cox- and logistic regression, followed by meta-analyses. The models were adjusted for age and sex and additionally for clinical risk factors. RESULTS: IgG galactosylation was negatively associated with prevalent and incident nephropathy and macrovascular disease after adjustment for clinical risk factors. Sialylation was negatively associated with incident diabetic nephropathy after adjustment for clinical risk factors. For incident retinopathy, similar associations were found for galactosylation, adjusted for age and sex. CONCLUSIONS: We showed that IgG N-glycosylation, particularly galactosylation and to a lesser extent sialylation, is associated with a higher prevalence and future development of macro- and microvascular complications of diabetes. These findings indicate the predictive potential of IgG N-glycosylation in diabetes complications and should be analysed further in additional large cohorts to obtain the power to solidify these conclusions.

The association between social jetlag and parameters of metabolic syndrome and type 2 diabetes: a systematic review and meta-analysis.

This study aims to determine the association between social jetlag and parameters of metabolic syndrome and type 2 diabetes (T2D) in a systematic review and meta-analysis. A systematic literature search was conducted in PubMed/Embase/Scopus until May 2022. Included studies described an association between social jetlag and parameters of the metabolic syndrome and/or T2D, were available full text and written in English or Dutch. Data extraction and quality assessment were performed on pre-piloted forms independently by two reviewers. Results were meta-analysed using random-effects analysis. A total of 6,290 titles/abstracts were screened, 176 papers were read full-text, 68 studies were included. Three studies were rated as low quality, 27 were moderate, and 38 were high quality. High quality studies showed that having social jetlag compared to no social jetlag was significantly associated with higher body mass index in 20 studies (0.49 kg/m2 , 95% confidence interval [CI] 0.21-0.77; I2  = 100%), higher waist circumference in seven studies (1.11 cm, 95% CI 0.42-1.80; I2  = 25%), higher systolic blood pressure in 10 studies (0.37 mmHg, 95% CI 0.00-0.74; I2  = 94%) and higher glycated haemoglobin in 12 studies (0.42%, 95% CI 0.12- 0.72; I2  = 100%). No statistically significant associations were found for obesity, abdominal obesity, high- and low-density lipoprotein levels, cholesterol, triglycerides, diastolic blood pressure, hypertension, fasting glucose, homeostatic model assessment for insulin resistance, metabolic syndrome or T2D. Sensitivity analyses did not reduce heterogeneity. Despite substantial heterogeneity, social jetlag is associated with certain parameters of the metabolic syndrome and T2D, but not with prevalent metabolic syndrome or T2D. These findings should be interpreted with caution as the level of evidence is low and mostly based on cross-sectional data. Longitudinal studies are needed to further assess the direction of causality.

Prolongation of the QTc interval is associated with an increased risk of cardiovascular diseases: The Hoorn study.

BACKGROUND/OBJECTIVE: Prolonged heart rate-corrected QT interval (QTc) on the electrocardiogram (ECG) is maybe associated with the occurrence of cardiovascular diseases (CVD), but the evidence is inconsistent. Therefore, we investigated whether baseline prolongation of the QTc interval is associated with CVD morbidity and mortality and its subtypes and whether glucose tolerance modifies this association in a population-based cohort study with a mean follow-up of 10.8 years. METHODS: We analyzed a glucose tolerance stratified sample (N = 487) from the longitudinal population-based Hoorn Study cohort (age 64 ± 7 years, 48% female). Cox regression was used to investigate the association between sex-specific baseline QTc quartiles and CVD morbidity and mortality. The risk was also estimated per 10 ms increase in QTc. All analyses were adjusted for age, sex, smoking status, systolic blood pressure, prevalent CVD, glucose tolerance status, hypertension and total cholesterol. In addition, stratified analyses were conducted for glucose tolerance status. RESULTS: During a mean follow-up of 10.8 years, 351 CVD events were observed. The adjusted hazard ratios (95% CI) for each 10 ms increase in QTc interval were 1.06 (95% CI: 1.02-1.10) for CVD, 1.06 (95% CI: 0.97-1.15) for acute myocardial infarction, 1.07 (95% CI: 1.01-1.13) for stroke, 1.12 (95% CI: 1.06-1.19) for heart failure, 1.04 (95% CI: 0.96-1.12) for peripheral arterial disease and 1.01 (95% CI:0.95-1.08) for coronary heart disease. Glucose tolerance status did not modify the association (P > 0.2). CONCLUSION/INTERPRETATION: Prolongation of the QTc interval is associated with morbidity and mortality due to general CVD. Glucose tolerance status did not modify these associations.

Apolipoprotein-CIII O-Glycosylation, a Link between GALNT2 and Plasma Lipids.

Apolipoprotein-CIII (apo-CIII) is involved in triglyceride-rich lipoprotein metabolism and linked to beta-cell damage, insulin resistance, and cardiovascular disease. Apo-CIII exists in four main proteoforms: non-glycosylated (apo-CIII0a), and glycosylated apo-CIII with zero, one, or two sialic acids (apo-CIII0c, apo-CIII1 and apo-CIII2). Our objective is to determine how apo-CIII glycosylation affects lipid traits and type 2 diabetes prevalence, and to investigate the genetic basis of these relations with a genome-wide association study (GWAS) on apo-CIII glycosylation. We conducted GWAS on the four apo-CIII proteoforms in the DiaGene study in people with and without type 2 diabetes (n = 2318). We investigated the relations of the identified genetic loci and apo-CIII glycosylation with lipids and type 2 diabetes. The associations of the genetic variants with lipids were replicated in the Diabetes Care System (n = 5409). Rs4846913-A, in the GALNT2-gene, was associated with decreased apo-CIII0a. This variant was associated with increased high-density lipoprotein cholesterol and decreased triglycerides, while high apo-CIII0a was associated with raised high-density lipoprotein-cholesterol and triglycerides. Rs67086575-G, located in the IFT172-gene, was associated with decreased apo-CIII2 and with hypertriglyceridemia. In line, apo-CIII2 was associated with low triglycerides. On a genome-wide scale, we confirmed that the GALNT2-gene plays a major role i O-glycosylation of apolipoprotein-CIII, with subsequent associations with lipid parameters. We newly identified the IFT172/NRBP1 region, in the literature previously associated with hypertriglyceridemia, as involved in apolipoprotein-CIII sialylation and hypertriglyceridemia. These results link genomics, glycosylation, and lipid metabolism, and represent a key step towards unravelling the importance of O-glycosylation in health and disease.

The role of mental disorders in precision medicine for diabetes: a narrative review.

This narrative review aims to examine the value of addressing mental disorders as part of the care of people with type 1 and type 2 diabetes in terms of four components of precision medicine. First, we review the empirical literature on the role of common mental disorders in the development and outcomes of diabetes (precision prevention and prognostics). We then review interventions that can address mental disorders in individuals with diabetes or at risk of diabetes (precision treatment) and highlight recent studies that have used novel methods to individualise interventions, in person and through applications, based on mental disorders. Additionally, we discuss the use of detailed assessment of mental disorders using, for example, mobile health technologies (precision monitoring). Finally, we discuss future directions in research and practice and challenges to addressing mental disorders as a factor in precision medicine for diabetes. This review shows that several mental disorders are associated with a higher risk of type 2 diabetes and its complications, while there is suggestive evidence indicating that treating some mental disorders could contribute to the prevention of diabetes and improve diabetes outcomes. Using technologically enabled solutions to identify mental disorders could help individuals who stand to benefit from particular treatments. However, there are considerable gaps in knowledge and several challenges to be met before we can stratify treatment recommendations based on mental disorders. Overall, this review demonstrates that addressing mental disorders as a facet of precision medicine could have considerable value for routine diabetes care and has the potential to improve diabetes outcomes.

Harmonization of the definition of sudden cardiac death in longitudinal cohorts of the European Sudden Cardiac Arrest network - towards Prevention, Education, and New Effective Treatments (ESCAPE-NET) consortium.

BACKGROUND: The burden of sudden cardiac death (SCD) in the general population is substantial and SCD frequently occurs among people with few or no known risk factors for cardiac disease. Reported incidences of SCD vary due to differences in definitions and methodology between cohorts. This study aimed to develop a method for adjudicating SCD cases in research settings and to describe uniform case definitions of SCD in an international consortium harmonizing multiple longitudinal study cohorts. METHODS: The harmonized SCD definitions include both case definitions using data from multiple sources (eg, autopsy reports, medical history, eyewitnesses) as well as a method using only information from registers (eg, cause of death registers, ICD-10 codes). Validation of the register-based method was done within the consortium using the multiple sources definition as gold standard and presenting sensitivity, specificity, accuracy and positive predictive value. RESULTS: Consensus definitions of "definite," "possible" and "probable" SCD for longitudinal study cohorts were reached. The definitions are based on a stratified approach to reflect the level of certainty of diagnosis and degree of information. The definitions can be applied to both multisource and register-based methods. Validation of the method using register-information in a cohort comprising 1335 cases yielded a sensitivity of 74%, specificity of 88%, accuracy of 86%, and positive predictive value of 54%. CONCLUSIONS: This study demonstrated that a harmonization of SCD classification across different methodological approaches is feasible. The developed classification can be used to study SCD in longitudinal cohorts and to merge cohorts with different levels of information.

The longitudinal association between chronic stress and (visceral) obesity over seven years in the general population: The Hoorn Studies.

BACKGROUND: We aimed to study the mediating role of diet quality, physical activity, smoking, and alcohol intake in the association of stressful life events with visceral obesity over a seven-year period and assessed effect modification by sex and SES. METHODS: In total, 2416 participants with a mean age of 56.1 (±7.3) years, of which 51.4% were women, and 12.5% had a lower educational level from the Hoorn studies were followed for seven years. Stress was measured with a 'Serious Life Events' questionnaire, which was summed into a total score (range zero to ten events) and stratified to account for nonlinearity. Changes in visceral obesity were assessed by changes in BMI (kg/m2) and waist circumference (cm) in seven years. We used the product of coefficient approach to assess mediation of the following lifestyle factors: diet, physical activity, smoking, and alcohol intake. We analyzed associations between stressful life events and change in BMI and waist circumference with linear regression models. RESULTS: Within the low education group, we observed a significant association between ≥3 stressful life events and a change in BMI (0.60 kg/m2 (CI: 0.05, 1.14)) and waist circumference (2.23 cm (CI: 0.19, 4.48)), compared to experiencing no events. For both BMI and waist circumference, no significant associations were observed when experiencing 1 or 2 events. In the moderate to high education group, we observed only statistically significant associations for waist circumference when experiencing ≥3 stressful life events (0.86 cm (CI: 0.05, 1.41)) and not for the other event groups. Our mediation analyses showed that the proportion mediated by smoking was 13.2%, while the other lifestyle factors showed no mediating effect. CONCLUSIONS: Multiple stressful life events are associated with an increase in waist circumference and BMI in those with lower education. Smoking might play a mediating role in this association.

Diagnostic value of echocardiographic markers for diastolic dysfunction and heart failure with preserved ejection fraction.

This study aimed to evaluate the diagnostic performance of echocardiographic markers of heart failure with preserved ejection fraction (HFpEF) and left ventricular diastolic dysfunction (LVDD) in comparison with the gold standard of cardiac catheterization. Diagnosing HFpEF is challenging, as symptoms are non-specific and often absent at rest. A clear need exists for sensitive echocardiographic markers to diagnose HFpEF. We systematically searched for studies testing the diagnostic value of novel echocardiographic markers for HFpEF and LVDD. Two investigators independently reviewed the studies and assessed the risk of bias. Results were meta-analysed when four or more studies reported a similar diagnostic measure. Of 353 studies, 20 fulfilled the eligibility criteria. The risk of bias was high especially in the patients' selection domain. The highest diagnostic performance was demonstrated by a multivariable model combining echocardiographic, clinical and arterial function markers with an area under the curve of 0.95 (95% CI, 0.89-0.98). A meta-analysis of four studies indicated a reasonable diagnostic performance for left atrial strain with an AUC of 0.83 (0.70-0.95), a specificity of 93% (95% CI, 90-97%) and a sensitivity of 77% (95% CI, 59-96%). Moreover, the addition of exercise E/e' improved the sensitivity of HFpEF diagnostic algorithms up to 90%, compared with 60 and 34% of guidelines alone. Despite the heterogeneity of the included studies, this review supported the current multivariable-based approach for the diagnosis of HFpEF and LVDD and showed a potential diagnostic role for exercise echocardiography and left atrial strain. Larger well-designed studies are needed to evaluate the incremental value of novel diagnostic tools to current diagnostic algorithms.