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Background Cardiovascular disease risk among individuals across different categories of BMI might depend on their metabolic health. It remains unclear to what extent metabolic health status changes over time and whether this affects cardiovascular disease risk. In this study, we aimed to examine the association between metabolic health and its change over time and cardiovascular disease risk across BMI categories. Findings During 2 127 391 person-years of follow-up with a median follow-up of 24 years, we documented 6306 cases of cardiovascular disease including 3304 myocardial infarction cases and 3080 strokes. Cardiovascular disease risk of women with metabolically healthy obesity was increased compared with women with metabolically healthy normal weight (HR 1.39, 95% CI 1.15-1.68), but risk was considerably higher in women with metabolically unhealthy normal weight (2.43, 2.19-2.68), overweight (2.61, 2.36-2.89) and obesity (3.15, 2.83-3.50). The majority of metabolically healthy women converted to unhealthy phenotypes (2555 [84%] of 3027 women with obesity, 22 215 [68%] of 32 882 women with normal-weight after 20 years). Women who maintained metabolically healthy obesity during follow-up were still at a higher cardiovascular disease risk compared with women with stable healthy normal weight (HR 1.57, 1.03-2.38), yet this risk was lower than for initially metabolically healthy women who converted to an unhealthy phenotype (normal-weight 1.90, 1.66-2.17 vs obesity 2.74, 2.30-3.27). Particularly incident diabetes and hypertension increased the risk among women with initial metabolic health. Interpretation Even when metabolic health is maintained during long periods of time, obesity remains a risk factor for cardiovascular disease. However, risks are highest for metabolically unhealthy women across all BMI categories. A large proportion of metabolically healthy women converted to an unhealthy phenotype over time across all BMI categories, which is associated with an increased cardiovascular disease risk. Copyright (C) 2018 Elsevier Ltd. All rights reserved.
Insulin-Like Growth Factor Binding Protein 2 (IGFBP-2) and the Risk of Developing Type 2 Diabetes
(2019)
Recent studies suggest that insulin-like growth factor binding protein 2 (IGFBP-2) may protect against type 2 diabetes, but population-based human studies are scarce. We aimed to investigate the prospective association of circulating IGFBP-2 concentrations and of differential methylation in the IGFBP-2 gene with type 2 diabetes risk.
Objective: Hypertension before and during early pregnancy has been associated with an increased risk of gestational diabetes mellitus (GDM) in retrospective analyses. We aimed to investigate the prospective blood pressure trackings in a population-based cohort of pregnant women, who were stratified according to their metabolic status in early third trimester. Methods: We recorded blood pressure longitudinally during pregnancy in 1230 women from the Odense Child Cohort, Denmark. Fasting glucose and insulin were measured at gestational weeks 28-30. Metabolic status was evaluated according to the WHO 2013 threshold for GDM (GDM-WHO: fasting plasma glucose >= 5.1 mmol/l), insulin and homeostatic model assessment of insulin resistance (HOMA-IR). Relationships between metabolic status in third trimester and blood pressure trajectories were evaluated with adjusted linear mixed models. Trajectory was defined as blood pressure records in pregnancy per 4 weeks interval. Results: Prevalence of GDM-WHO was 40% (498/1230). GDM-WHO was associated with 1.46 (0.22-2.70) mmHg higher SBP and 1.04 (0.07-2.01) mmHg higher DBP trajectories in the overall cohort. The associations were driven by differences in the overweight group, with 3.14 (1.05-5.25) mmHg higher SBP and 1.94 (0.42-3.47) mmHg higher DBP per 4 weeks in women with GDM-WHO compared with women without GDM-WHO. GDM-WHO was not associated with blood pressure in women with normal weight. Blood pressure trajectories were elevated across quartiles of insulin resistance. Conclusion: GDM-WHO is associated with higher blood pressure in pregnancy, and there appears to be a stronger effect in overweight women.
Metabolic alterations precede cardiometabolic disease onset. Here we present ceramide- and dihydroceramide-profiling data from a nested case-cohort (type 2 diabetes [T2D, n = 775]; cardiovascular disease [CVD, n = 551]; random subcohort [n = 1137]) in the prospective EPIC-Potsdam study. We apply the novel NetCoupler-algorithm to link a data-driven (dihydro)ceramide network to T2D and CVD risk. Controlling for confounding by other (dihydro)ceramides, ceramides C18:0 and C22:0 and dihydroceramides C20:0 and C22:2 are associated with higher and ceramide C20:0 and dihydroceramide C26:1 with lower T2D risk. Ceramide C16:0 and dihydroceramide C22:2 are associated with higher CVD risk. Genome-wide association studies and Mendelian randomization analyses support a role of ceramide C22:0 in T2D etiology. Our results also suggest that (dh)ceramides partly mediate the putative adverse effect of high red meat consumption and benefits of coffee consumption on T2D risk. Thus, (dihydro)ceramides may play a critical role in linking genetic predisposition and dietary habits to cardiometabolic disease risk.
Deep lipidomics in human plasma: cardiometabolic disease risk and effect of dietary fat modulation
(2022)
Background: In blood and tissues, dietary and endogenously generated fatty acids (FAs) occur in free form or as part of complex lipid molecules that collectively represent the lipidome of the respective tissue. We assessed associations of plasma lipids derived from high-resolution lipidomics with incident cardiometabolic diseases and subsequently tested if the identified risk-associated lipids were sensitive to dietary fat modification. Methods: The EPIC Potsdam cohort study (European Prospective Investigation into Cancer and Nutrition) comprises 27 548 participants recruited within an age range of 35 to 65 years from the general population around Potsdam, Germany. We generated 2 disease-specific case cohorts on the basis of a fixed random subsample (n=1262) and all respective cohort-wide identified incident primary cardiovascular disease (composite of fatal and nonfatal myocardial infarction and stroke; n=551) and type 2 diabetes (n=775) cases. We estimated the associations of baseline plasma concentrations of 282 class-specific FA abundances (calculated from 940 distinct molecular species across 15 lipid classes) with the outcomes in multivariable-adjusted Cox models. We tested the effect of an isoenergetic dietary fat modification on risk-associated lipids in the DIVAS randomized controlled trial (Dietary Intervention and Vascular Function; n=113). Participants consumed either a diet rich in saturated FAs (control), monounsaturated FAs, or a mixture of monounsaturated and n-6 polyunsaturated FAs for 16 weeks. Results: Sixty-nine lipids associated (false discovery rate<0.05) with at least 1 outcome (both, 8; only cardiovascular disease, 49; only type 2 diabetes, 12). In brief, several monoacylglycerols and FA16:0 and FA18:0 in diacylglycerols were associated with both outcomes; cholesteryl esters, free fatty acids, and sphingolipids were largely cardiovascular disease specific; and several (glycero)phospholipids were type 2 diabetes specific. In addition, 19 risk-associated lipids were affected (false discovery rate<0.05) by the diets rich in unsaturated dietary FAs compared with the saturated fat diet (17 in a direction consistent with a potential beneficial effect on long-term cardiometabolic risk). For example, the monounsaturated FA-rich diet decreased diacylglycerol(FA16:0) by 0.4 (95% CI, 0.5-0.3) SD units and increased triacylglycerol(FA22:1) by 0.5 (95% CI, 0.4-0.7) SD units. Conclusions: We identified several lipids associated with cardiometabolic disease risk. A subset was beneficially altered by a dietary fat intervention that supports the substitution of dietary saturated FAs with unsaturated FAs as a potential tool for primary disease prevention.
Aims/hypothesis
Studies suggest decreased mortality risk among people who are overweight or obese compared with individuals with normal weight in type 2 diabetes (obesity paradox). However, the relationship between body weight or weight change and microvascular vs macrovascular complications of type 2 diabetes remains unresolved. We investigated the association between BMI and BMI change with long-term risk of microvascular and macrovascular complications in type 2 diabetes in a prospective cohort study.
Methods
We studied participants with incident type 2 diabetes from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort, who were free of cancer, cardiovascular disease and microvascular disease at diagnosis (n = 1083). Pre-diagnosis BMI and relative annual change between pre- and post-diagnosis BMI were evaluated in multivariable-adjusted Cox models.
Results
There were 85 macrovascular (myocardial infarction and stroke) and 347 microvascular events (kidney disease, neuropathy and retinopathy) over a median follow-up of 10.8 years. Median pre-diagnosis BMI was 29.9 kg/m(2) (IQR 27.4-33.2), and the median relative annual BMI change was -0.4% (IQR -2.1 to 0.9). Higher pre-diagnosis BMI was positively associated with total microvascular complications (multivariable-adjusted HR per 5 kg/m(2) [95% CI]: 1.21 [1.07, 1.36], kidney disease 1.39 [1.21, 1.60] and neuropathy 1.12 [0.96, 1.31]) but not with macrovascular complications (HR 1.05 [95% CI 0.81, 1.36]). Analyses according to BMI categories corroborated these findings. Effect modification was not evident by sex, smoking status or age groups. In analyses according to BMI change categories, BMI loss of more than 1% indicated a decreased risk of total microvascular complications (HR 0.62 [95% CI 0.47, 0.80]), kidney disease (HR 0.57 [95% CI 0.40, 0.81]) and neuropathy (HR 0.73 [95% CI 0.52, 1.03]), compared with participants with a stable BMI; no clear association was observed for macrovascular complications (HR 1.04 [95% CI 0.62, 1.74]). The associations between BMI gain compared with stable BMI and diabetes-related vascular complications were less apparent. Associations were consistent across strata of sex, age, pre-diagnosis BMI or medication but appeared to be stronger among never-smokers compared with current or former smokers.
Conclusions/interpretation
Among people with incident type 2 diabetes, pre-diagnosis BMI was positively associated with microvascular complications, while a reduced risk was observed with weight loss when compared with stable weight. The relationships with macrovascular disease were less clear.
Aims/hypothesis This study aimed to evaluate associations of height as well as components of height (sitting height and leg length) with risk of type 2 diabetes and to explore to what extent associations are explainable by liver fat and cardiometabolic risk markers. Methods A case-cohort study within the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study comprising 26,437 participants who provided blood samples was designed. We randomly selected a subcohort of 2500 individuals (2029 diabetes-free at baseline and with anamnestic, anthropometrical and metabolic data for analysis). Of the 820 incident diabetes cases identified in the full cohort during 7 years of follow-up, 698 remained for analyses after similar exclusions. Results After adjustment for age, potential lifestyle confounders, education and waist circumference, greater height was related to lower diabetes risk (HR per 10 cm, men 0.59 [95% CI 0.47, 0.75] and women 0.67 [0.51, 0.88], respectively). Leg length was related to lower risk among men and women, but only among men if adjusted for total height. Adjustment for liver fat and triacylglycerols, adiponectin and C-reactive protein substantially attenuated associations between height and diabetes risk, particularly among women. Conclusions/interpretation We observed inverse associations between height and risk of type 2 diabetes, which was largely related to leg length among men. The inverse associations may be partly driven by lower liver fat content and a more favourable cardiometabolic profile.
The Net Reclassification Improvement (NRI) has become a popular metric for evaluating improvement in disease prediction models through the past years. The concept is relatively straightforward but usage and interpretation has been different across studies. While no thresholds exist for evaluating the degree of improvement, many studies have relied solely on the significance of the NRI estimate. However, recent studies recommend that statistical testing with the NRI should be avoided. We propose using confidence ellipses around the estimated values of event and non-event NRIs which might provide the best measure of variability around the point estimates. Our developments are illustrated using practical examples from EPIC-Potsdam study.