Eva Corpeleijn

Prediction models for risk of developing type 2 diabetes: systematic literature search and independent external validation study

Objective To identify existing prediction models for the risk of development of type 2 diabetes and to externally validate them in a large independent cohort. Data sources Systematic search of English, German, and Dutch literature in PubMed until February 2011 to identify prediction models for diabetes. Design Performance of the models was assessed in terms of discrimination (C statistic) and calibration (calibration plots and Hosmer-Lemeshow test).The validation study was a prospective cohort study, with a case cohort study in a random subcohort. Setting Models were applied to the Dutch cohort of the European Prospective Investigation into Cancer and Nutrition cohort study (EPIC-NL). Participants 38 379 people aged 20-70 with no diabetes at baseline, 2506 of whom made up the random subcohort. Outcome measure Incident type 2 diabetes. Results The review identified 16 studies containing 25 prediction models. We considered 12 models as basic because they were based on variables that can be assessed non-invasively and 13 models as extended because they additionally included conventional biomarkers such as glucose concentration. During a median follow-up of 10.2 years there were 924 cases in the full EPIC-NL cohort and 79 in the random subcohort. The C statistic for the basic models ranged from 0.74 (95% confidence interval 0.73 to 0.75) to 0.84 (0.82 to 0.85) for risk at 7.5 years. For prediction models including biomarkers the C statistic ranged from 0.81 (0.80 to 0.83) to 0.93 (0.92 to 0.94). Most prediction models overestimated the observed risk of diabetes, particularly at higher observed risks. After adjustment for differences in incidence of diabetes, calibration improved considerably. Conclusions Most basic prediction models can identify people at high risk of developing diabetes in a time frame of five to 10 years. Models including biomarkers classified cases slightly better than basic ones. Most models overestimated the actual risk of diabetes. Existing prediction models therefore perform well to identify those at high risk, but cannot sufficiently quantify actual risk of future diabetes.

DNA methylation mediates the effect of maternal smoking during pregnancy on birthweight of the offspring

Background: We examined whether the effect of maternal smoking during pregnancy on birthweight of the offspring was mediated by smoking-induced changes to DNA methylation in cord blood. Methods: First, we used cord blood of 129 Dutch children exposed to maternal smoking vs 126 unexposed to maternal and paternal smoking (53% male) participating in the GECKO Drenthe birth cohort. DNA methylation was measured using the Illumina HumanMethylation450 Beadchip. We performed an epigenome-wide association study for the association between maternal smoking and methylation followed by a mediation analysis of the top signals [false-discovery rate (FDR) < 0.05]. We adjusted both analyses for maternal age, education, pre-pregnancy BMI, offspring’s sex, gestational age and white blood cell composition. Secondly, in 175 exposed and 1248 unexposed newborns from two independent birth cohorts, we replicated and meta-analysed results of eight cytosine-phosphate-guanine (CpG) sites in the GFI1 gene, which showed the most robust mediation. Finally, we performed functional network and enrichment analysis. Results: We found 35 differentially methylated CpGs (FDR < 0.05) in newborns exposed vs unexposed to smoking, of which 23 survived Bonferroni correction (P < 1 × 10-7). These 23 CpGs mapped to eight genes: AHRR, GFI1, MYO1G, CYP1A1, NEUROG1, CNTNAP2, FRMD4A and LRP5. We observed partial confirmation as three of the eight CpGs in GFI1 replicated. These CpGs partly mediated the effect of maternal smoking on birthweight (Sobel P < 0.05) in meta-analysis of GECKO and the two replication cohorts. Differential methylation of these three GFI1 CpGs explained 12–19% of the 202 g lower birthweight in smoking mothers. Functional enrichment analysis pointed towards activation of cell-mediated immunity. Conclusions: Maternal smoking during pregnancy was associated with cord blood methylation differences. We observed a potentially mediating role of methylation in the association between maternal smoking during pregnancy and birthweight of the offspring. Functional network analysis suggested a role in activating the immune system.

Low Physical Activity and Risk of Cardiovascular and All-Cause Mortality in Renal Transplant Recipients

BACKGROUND AND OBJECTIVES Low physical activity (PA) is a risk factor for mortality in the general population. This is largely unexplored in renal transplant recipients (RTRs). We studied whether PA is associated with cardiovascular and all-cause mortality in a prospective cohort of RTR. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS Between 2001 and 2003, 540 RTRs were studied (age, 51 ± 12 years; 54% male). PA was assessed using validated questionnaires (Tecumseh Occupational Activity Questionnaire and the Minnesota Leisure Time Physical Activity Questionnaire). Cardiovascular and all-cause mortality were recorded until August 2007. RESULTS Independent of age, PA was inversely associated with metabolic syndrome, history of cardiovascular disease, fasting insulin, and triglyceride concentration, and positively associated with kidney function and 24-hour urinary creatinine excretion (i.e., muscle mass). During follow-up for 5.3 years (range, 4.7 to 5.7 years), 81 RTRs died, with 37 cardiovascular deaths. Cardiovascular mortality was 11.7, 7.2, and 1.7%, respectively, according to gender-stratified tertiles of PA (P=0.001). All-cause mortality was 24.4, 15.0, and 5.6% according to these tertiles (P<0.001). In Cox regression analyses, adjustment for potential confounders including history of cardiovascular disease, muscle mass, and traditional risk factors for cardiovascular disease did not materially change these associations. CONCLUSIONS Low PA is strongly associated with increased risk for cardiovascular and all-cause mortality in RTRs. Intervention studies are necessary to investigate whether PA improves long-term survival after renal transplantation.

Does physical activity modify the risk of obesity for type 2 diabetes: a review of epidemiological data

Obesity and physical inactivity are both risk factors for type 2 diabetes. Since they are strongly associated, it has been suggested that they might interact. In this study, we summarized the evidence on this interaction by conducting a systematic review. Two types of interaction have been discerned, statistical and biological interaction, which could give different results. Therefore, we calculated both types of interaction for the studies in our review. Cohort studies, published between 1999 and 2008, that investigated the effects of obesity and physical activity on the risk of type 2 diabetes were included. We calculated both biological and statistical interaction in these studies. Eight studies were included of which five were suitable to calculate interaction. All studies showed positive biological interaction, meaning that the joint effect was more than the sum of the individual effects. However, there was inconsistent statistical interaction; in some studies the joint effect was more than the product of the individual effects, in other studies it was less. The results show that obesity and physical inactivity interact on an additive scale. This means that prevention of either obesity or physical inactivity, not only reduces the risk of diabetes by taking away the independent effect of this factor, but also by preventing the cases that were caused by the interaction between both factors. Furthermore, this review clearly showed that results can differ depending on what method is used to assess interaction.

Results of a Multidisciplinary Treatment Program in 3-Year-Old to 5-Year-Old Overweight or Obese Children: A Randomized Controlled Clinical Trial

OBJECTIVE To assess the effects of a multidisciplinary intervention program for 3-year-old to 5-year-old overweight and obese children compared with a usual-care program. DESIGN Randomized controlled clinical trial conducted from October 2006 to March 2008. SETTING Groningen Expert Center for Kids with Obesity at Beatrix Childrens Hospital, University Medical Center Groningen. PARTICIPANTS Seventy-five children (29 overweight, 46 obese) aged 3 to 5 years. INTERVENTION A multidisciplinary intervention program vs a usual-care program. Anthropometry was performed and body composition was determined by bioelectrical impedance analysis and ultrasonography at the start and end of the 16-week program and 12 months after starting the intervention. MAIN OUTCOME MEASURES The actual weight reduction, change in body mass index (BMI, calculated as weight in kilograms divided by height in meters squared), BMI z score, body fat percentage, and visceral fat in the multidisciplinary intervention group compared with a usual-care group. RESULTS At the end of the treatment program, children in the multidisciplinary intervention group showed a greater decrease in BMI, BMI z score, and waist circumference z score compared with children in the usual-care group. At 12 months, children in the intervention group showed greater decreases in BMI, BMI z score, waist circumference, and waist circumference z score compared with children in the usual-care group. Visceral fat showed a trend toward a higher decrease. CONCLUSIONS A multidisciplinary intervention program in 3-year-old to 5-year-old overweight and obese children had beneficial effects on anthropometry and body composition. The positive effects were still present 12 months after the start of the intervention. TRIAL REGISTRATION isrctn.org Identifier: ISRCTN47185691.

The effects of lifestyle interventions on (long-term) weight management, cardiometabolic risk and depressive symptoms in people with psychotic disorders: a meta-analysis.

Aims The aim of this study was to estimate the effects of lifestyle interventions on bodyweight and other cardiometabolic risk factors in people with psychotic disorders. Additionally, the long-term effects on body weight and the effects on depressive symptoms were examined. Material and Methods We searched four databases for randomized controlled trials (RCTs) that compared lifestyle interventions to control conditions in patients with psychotic disorders. Lifestyle interventions were aimed at weight loss or weight gain prevention, and the study outcomes included bodyweight or metabolic parameters. Results The search resulted in 25 RCTs -only 4 were considered high quality- showing an overall effect of lifestyle interventions on bodyweight (effect size (ES) = −0.63, p<0.0001). Lifestyle interventions were effective in both weight loss (ES = −0.52, p<0.0001) and weight-gain-prevention (ES = −0.84, p = 0.0002). There were significant long-term effects, two to six months post-intervention, for both weight-gain-prevention interventions (ES = −0.85, p = 0.0002) and weight loss studies (ES = −0.46, p = 0.02). Up to ten studies reported on cardiometabolic risk factors and showed that lifestyle interventions led to significant improvements in waist circumference, triglycerides, fasting glucose and insulin. No significant effects were found for blood pressure and cholesterol levels. Four studies reported on depressive symptoms and showed a significant effect (ES = −0.95, p = 0.05). Conclusion Lifestyle interventions are effective in treating and preventing obesity, and in reducing cardiometabolic risk factors. However, the quality of the studies leaves much to be desired.

Role of HDL Cholesterol and Estimates of HDL Particle Composition in Future Development of Type 2 Diabetes in the General Population: The PREVEND Study

BACKGROUND AND AIMS High-density lipoproteins (HDLs) may directly stimulate β-cell function and glucose metabolism. We determined the relationships of fasting high-density lipoprotein cholesterol (HDL-C), plasma apolipoprotein (apo) A-I and apoA-II, and HDL-C-to-apoA-I and HDL-C-to-apoA-II ratios, as estimates of HDL particle composition, with incident type 2 diabetes mellitus. METHODS A prospective study was carried out in the Prevention of Renal and Vascular End-Stage Disease (PREVEND) cohort after exclusion of subjects with diabetes at baseline (n = 6820; age, 28-75 years). The association of HDL-related variables with incident type 2 diabetes was determined by multivariate logistic regression analyses. RESULTS After a median follow-up of 7.7 years, 394 incident cases of type 2 diabetes mellitus were ascertained (5.8%). After adjustment for age, sex, family history of diabetes, body mass index, hypertension, alcohol, and smoking, odd ratios (ORs) for diabetes were 0.55 (95% confidence interval [CI], 0.47-0.64; P < .001), 0.81 (0.71-0.93; P = .002), 0.02 (0.01-0.06; P < .001), and 0.03 (0.01-0.060; P < .001) per 1-SD increase in HDL-C and apoA-I and in the HDL-C-to-apoA-I and the HDL-C-to-apoA-II ratios, respectively. In contrast, apoA-II was not related to incident diabetes (OR = 1.02; 95% CI, 0.90-1.16; P=0.71). The relationships of HDL-C and the ratios of HDL-C to apoA-I and HDL-C to apoA-II remained significant after further adjustment for baseline glucose and triglycerides (OR(HDL) = 0.74 [95% CI, 0.61-0.88], OR(HDL/APO A-I) = 0.14 [0.04-0.44], and OR(HDL/APOA-II) = 0.12 [0.04-0.36]; all P ≤ .001). CONCLUSIONS Higher HDL-C, as well as higher HDL-C-to-apoA-I and HDL-C-to-apoA-II ratios are strongly and independently related to a lower risk of future type 2 diabetes.

Bilirubin as a potential causal factor in type 2 diabetes risk: a Mendelian randomization study

Circulating bilirubin, a natural antioxidant, is associated with decreased risk of type 2 diabetes (T2D), but the nature of the relationship remains unknown. We performed Mendelian randomization in a prospective cohort of 3,381 participants free of diabetes at baseline (age 28–75 years; women 52.6%). We used rs6742078 located in the uridine diphosphate–glucuronosyltransferase locus as an instrumental variable (IV) to study a potential causal effect of serum total bilirubin level on T2D risk. T2D developed in a total of 210 participants (6.2%) during a median follow-up period of 7.8 years. In adjusted analyses, rs6742078, which explained 19.5% of bilirubin variation, was strongly associated with total bilirubin (a 0.68-SD increase in bilirubin levels per T allele; P < 1 × 10−122) and was also associated with T2D risk (odds ratio [OR] 0.69 [95% CI 0.54–0.90]; P = 0.006). Per 1-SD increase in log-transformed bilirubin levels, we observed a 25% (OR 0.75 [95% CI 0.62–0.92]; P = 0.004) lower risk of T2D. In Mendelian randomization analysis, the causal risk reduction for T2D was estimated to be 42% (causal OR for IV estimation per 1-SD increase in log-transformed bilirubin 0.58 [95% CI 0.39–0.84]; P = 0.005), which was comparable to the observational estimate (Durbin-Wu-Hausman χ2 test, P for difference = 0.19). These novel results provide evidence that an elevated bilirubin level is causally associated with the risk of T2D and support its role as a protective determinant.

Physical Activity, Adiposity, and Diabetes Risk in Middle-Aged and Older Chinese Population The Guangzhou Biobank Cohort Study

OBJECTIVE Physical activity may modify the association of adiposity with type 2 diabetes. We investigated the independent and joint association of adiposity and physical activity with fasting plasma glucose, impaired fasting glucose, and type 2 diabetes in a Chinese population. RESEARCH DESIGN AND METHODS Middle-aged and older Chinese (n = 28,946, ≥50 years, 72.4%women) from the Guangzhou Biobank Cohort Study were examined in 2003–2008. Multivariable regression was used in a cross-sectional analysis. RESULTS BMI, waist circumference, and waist-to-hip ratio (WHR) were positively associated with type 2 diabetes after multiple adjustment, most strongly for WHR with odds ratio (OR) of 3.99 (95% CI 3.60–4.42) for highest compared with lowest tertile. Lack of moderate-to-vigorous physical activity, but not walking, was associated with diabetes with an OR of 1.29 (1.17–1.41). The association of moderate-to-vigorous activity with fasting glucose varied with WHR tertiles (P = 0.01 for interaction). Within the high WHR tertile, participants who had a lack of moderate-to-vigorous activity had an OR of 3.87 (3.22–4.65) for diabetes, whereas those who were active had an OR of 2.94 (2.41–3.59). CONCLUSIONS In this population, WHR was a better measure of adiposity-related diabetes risk than BMI or waist circumference. Higher moderate-to-vigorous activity was associated with lower diabetes risk, especially in abdominally obese individuals.

Waist-to-height ratio, waist circumference and BMI as indicators of percentage fat mass and cardiometabolic risk factors in children aged 3–7 years

OBJECTIVE To assess whether waist-to-height-ratio (WHtR) is a better estimate of body fat percentage (BF%) and a better indicator of cardiometabolic risk factors than BMI or waist circumference (WC) in young children. METHODS WHtR, WC and BMI were measured by trained staff according to standardized procedures. (2)H2O and (2)H2(18)O isotope dilution were used to assess BF% in 61 children (3-7 years) from the general population, and bioelectrical impedance (Horlick equation) was used to assess BF% in 75 overweight/obese children (3-5 years). Cardiometabolic risk factors, including diastolic and systolic blood pressure, HOMA2-IR, leptin, adiponectin, triglycerides, total cholesterol, HDL- and LDL-cholesterol, TNFα and IL-6 were determined in the overweight/obese children. RESULTS In the children from the general population, after adjustments for age and gender, BMI had the highest explained variance for BF% compared to WC and WHtR (R(2) = 0.32, 0.31 and 0.23, respectively). In the overweight/obese children, BMI and WC had a higher explained variance for BF% compared to WHtR (R(2) = 0.68, 0.70 and 0.50, respectively). In the overweight/obese children, WHtR, WC and BMI were all significantly positively correlated with systolic blood pressure (r = 0.23, 0.30, 0.36, respectively), HOMA2-IR (r = 0.53, 0.62, 0.63, respectively), leptin (r = 0.70, 0.77, 0.78, respectively) and triglycerides (r = 0.33, 0.36, 0.24, respectively), but not consistently with other parameters. CONCLUSION In young children, WHtR is not superior to WC or BMI in estimating BF%, nor is WHtR better correlated with cardiometabolic risk factors than WC or BMI in overweight/obese children. These data do not support the use of WHtR in young children.