Person:

Hofman, Albert

An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In order to assess the improvement of 1000G over HapMap imputation in identifying associated loci, we compared the results of GWA studies of circulating fibrinogen based on the two reference panels. Using both HapMap and 1000G imputation we performed a meta-analysis of 22 studies comprising the same 91,953 individuals. We identified six additional signals using 1000G imputation, while 29 loci were associated using both HapMap and 1000G imputation. One locus identified using HapMap imputation was not significant using 1000G imputation. The genome-wide significance threshold of 5×10−8 is based on the number of independent statistical tests using HapMap imputation, and 1000G imputation may lead to further independent tests that should be corrected for. When using a stricter Bonferroni correction for the 1000G GWA study (P-value < 2.5×10−8), the number of loci significant only using HapMap imputation increased to 4 while the number of loci significant only using 1000G decreased to 5. In conclusion, 1000G imputation enabled the identification of 20% more loci than HapMap imputation, although the advantage of 1000G imputation became less clear when a stricter Bonferroni correction was used. More generally, our results provide insights that are applicable to the implementation of other dense reference panels that are under development.

Background: DNA methylation is a key epigenetic mechanism that is suggested to be associated with blood lipid levels. We aimed to identify CpG sites at which DNA methylation levels are associated with blood levels of triglycerides, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and total cholesterol in 725 participants of the Rotterdam Study, a population-based cohort study. Subsequently, we sought replication in a non-overlapping set of 760 participants. Results: Genome-wide methylation levels were measured in whole blood using the Illumina Methylation 450 array. Associations between lipid levels and DNA methylation beta values were examined using linear mixed-effect models. All models were adjusted for sex, age, smoking, white blood cell proportions, array number, and position on array. A Bonferroni-corrected p value lower than 1.08 × 10−7 was considered statistically significant. Five CpG sites annotated to genes including DHCR24, CPT1A, ABCG1, and SREBF1 were identified and replicated. Four CpG sites were associated with triglycerides, including CpG sites annotated to CPT1A (cg00574958 and cg17058475), ABCG1 (cg06500161), and SREBF1 (cg11024682). Two CpG sites were associated with HDL-C, including ABCG1 (cg06500161) and DHCR24 (cg17901584). No significant associations were observed with LDL-C or total cholesterol. Conclusions: We report an association of HDL-C levels with methylation of a CpG site near DHCR24, a protein-coding gene involved in cholesterol biosynthesis, which has previously been reported to be associated with other metabolic traits. Furthermore, we confirmed previously reported associations of methylation of CpG sites within CPT1A, ABCG1, and SREBF1 and lipids. These results provide insight in the mechanisms that are involved in lipid metabolism. Electronic supplementary material The online version of this article (doi:10.1186/s13148-016-0304-4) contains supplementary material, which is available to authorized users.

MicroRNAs (miRNAs) serve as key post-transcriptional regulators of gene expression. Genetic variation in miRNAs and miRNA-binding sites may affect miRNA function and contribute to disease risk. Here, we investigated the extent to which variants within miRNA-related sequences could constitute a part of the functional variants involved in developing Alzheimer’s disease (AD), using the largest available genome-wide association study of AD. First, among 237 variants in miRNAs, we found rs2291418 in the miR-1229 precursor to be significantly associated with AD (p-value = 6.8 × 10−5, OR = 1.2). Our in-silico analysis and in-vitro miRNA expression experiments demonstrated that the variant’s mutant allele enhances the production of miR-1229-3p. Next, we found miR-1229-3p target genes that are associated with AD and might mediate the miRNA function. We demonstrated that miR-1229-3p directly controls the expression of its top AD-associated target gene (SORL1) using luciferase reporter assays. Additionally, we showed that miR-1229-3p and SORL1 are both expressed in the human brain. Second, among 42,855 variants in miRNA-binding sites, we identified 10 variants (in the 3′ UTR of 9 genes) that are significantly associated with AD, including rs6857 that increases the miR-320e-mediated regulation of PVRL2. Collectively, this study shows that miRNA-related variants are associated with AD and suggests miRNA-dependent regulation of several AD genes.

Estimates of biological age based on DNA methylation patterns, often referred to as “epigenetic age”, “DNAm age”, have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2×10−9), independent of chronological age, even after adjusting for additional risk factors (p<5.4×10−4), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5×10−43). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality.

The immune response involved in each phase of type 2 diabetes (T2D) development might be different. We aimed to identify novel inflammatory markers that predict progression from normoglycemia to pre-diabetes, incident T2D and insulin therapy. We used plasma levels of 26 inflammatory markers in 971 subjects from the Rotterdam Study. Among them 17 are novel and 9 previously studied. Cox regression models were built to perform survival analysis. Main Outcome Measures: During a follow-up of up to 14.7 years (between April 1, 1997, and Jan 1, 2012) 139 cases of pre-diabetes, 110 cases of T2D and 26 cases of insulin initiation were identified. In age and sex adjusted Cox models, IL13 (HR = 0.78), EN-RAGE (1.30), CFH (1.24), IL18 (1.22) and CRP (1.32) were associated with incident pre-diabetes. IL13 (0.62), IL17 (0.75), EN-RAGE (1.25), complement 3 (1.44), IL18 (1.35), TNFRII (1.27), IL1ra (1.24) and CRP (1.64) were associated with incident T2D. In multivariate models, IL13 (0.77), EN-RAGE (1.23) and CRP (1.26) remained associated with pre-diabetes. IL13 (0.67), IL17 (0.76) and CRP (1.32) remained associated with T2D. IL13 (0.55) was the only marker associated with initiation of insulin therapy in diabetics. Various inflammatory markers are associated with progression from normoglycemia to pre-diabetes (IL13, EN-RAGE, CRP), T2D (IL13, IL17, CRP) or insulin therapy start (IL13). Among them, EN-RAGE is a novel inflammatory marker for pre-diabetes, IL17 for incident T2D and IL13 for pre-diabetes, incident T2D and insulin therapy start. Electronic supplementary material The online version of this article (doi:10.1007/s10654-017-0236-0) contains supplementary material, which is available to authorized users.

Background: Whether being metabolically healthy obese (MHO)—defined by the presence of obesity in the absence of metabolic syndrome—is associated with subsequent cardiovascular disease (CVD) remains unclear and may depend on the participants’ age. We examined the association of being MHO with CVD risk in the elderly. Methods and Findings: This study included 5,314 individuals (mean age 68 years) from the prospective population-based Rotterdam Study. We categorized our population in groups according to body mass index (BMI) and presence and absence of metabolic syndrome, and estimated the hazard ratio (HR) and 95% confidence interval (95%CI) for every group by using Cox proportional hazard models. Among 1048 (19.7%) obese individuals we identified 260 (24.8%) MHO subjects. Over 14 years of follow-up there were 861 incident CVD cases. In the multivariable adjusted analysis, we did not observe an increased CVD risk in MHO individuals (HR 1.07, 95%CI 0.75–1.53), compared to normal weight individuals without metabolic syndrome. CVD risk was increased by the presence of metabolic syndrome in normal weight (HR 1.35, 95%CI 1.02–1.80), overweight (HR 1.32, 95%CI 1.09–1.60) and obese (HR 1.33, 95%CI 1.07–1.66) individuals, compared to those with normal weight without metabolic syndrome. In a mediation analysis, 71.3% of the association between BMI and CVD was explained by the presence of metabolic syndrome. Conclusions: In our elderly population, we found that the presence of obesity without metabolic syndrome did not confer a higher CVD risk. However, metabolic syndrome was strongly associated with CVD risk, and was associated with an increased risk in all BMI categories. Therefore, preventive interventions targeting cardiometabolic risk factors could be considered in elderly, regardless of weight status.

Background: The association of thyroid function with risk of type 2 diabetes remains elusive. We aimed to investigate the association of thyroid function with incident diabetes and progression from prediabetes to diabetes in a population-based prospective cohort study. Methods: We included 8452 participants (mean age 65 years) with thyroid function measurement, defined by thyroid-stimulating hormone (TSH) and free thyroxine (FT4), and longitudinal assessment of diabetes incidence. Cox-models were used to investigate the association of TSH and FT4 with diabetes and progression from prediabetes to diabetes. Multivariable models were adjusted for age, sex, high-density lipoprotein cholesterol, and glucose at baseline, amongst others. Results: During a mean follow-up of 7.9 years, 798 diabetes cases occurred. Higher TSH levels were associated with a higher diabetes risk (hazard ratio [HR] 1.13; 95 % confidence interval [CI], 1.08–1.18, per logTSH), even within the reference range of thyroid function (HR 1.24; 95 % CI, 1.06–1.45). Higher FT4 levels were associated with a lower diabetes risk amongst all participants (HR 0.96; 95 % CI, 0.93–0.99, per 1 pmol/L) and in participants within the reference range of thyroid function (HR 0.96; 95 % CI, 0.92–0.99). The risk of progression from prediabetes to diabetes was higher with low-normal thyroid function (HR 1.32; 95 % CI, 1.06–1.64 for TSH and HR 0.91; 95 % CI, 0.86–0.97 for FT4). Absolute risk of developing diabetes type 2 in participants with prediabetes decreased from 35 % to almost 15 % with higher FT4 levels within the normal range. Conclusions: Low and low-normal thyroid function are risk factors for incident diabetes, especially in individuals with prediabetes. Future studies should investigate whether screening for and treatment of (subclinical) hypothyroidism is beneficial in subjects at risk of developing diabetes. Electronic supplementary material The online version of this article (doi:10.1186/s12916-016-0693-4) contains supplementary material, which is available to authorized users.

Background: Overweight and obesity are associated with increased risk of type 2 diabetes. Limited evidence exists regarding the effect of excess weight on years lived with and without diabetes. We aimed to determine the association of overweight and obesity with the number of years lived with and without diabetes in a middle-aged and elderly population. Methods and Findings: The study included 6,499 individuals (3,656 women) aged 55 y and older from the population-based Rotterdam Study. We developed a multistate life table to calculate life expectancy for individuals who were normal weight, overweight, and obese and the difference in years lived with and without diabetes. For life table calculations, we used prevalence, incidence rate, and hazard ratios (HRs) for three transitions (healthy to diabetes, healthy to death, and diabetes to death), stratifying by body mass index (BMI) at baseline and adjusting for confounders. During a median follow-up of 11.1 y, we observed 697 incident diabetes events and 2,192 overall deaths. Obesity was associated with an increased risk of developing diabetes (HR: 2.13 [p < 0.001] for men and 3.54 [p < 0.001] for women). Overweight and obesity were not associated with mortality in men and women with or without diabetes. Total life expectancy remained unaffected by overweight and obesity. Nevertheless, men with obesity aged 55 y and older lived 2.8 (95% CI −6.1 to −0.1) fewer y without diabetes than normal weight individuals, whereas, for women, the difference between obese and normal weight counterparts was 4.7 (95% CI −9.0 to −0.6) y. Men and women with obesity lived 2.8 (95% CI 0.6 to 6.2) and 5.3 (95% CI 1.6 to 9.3) y longer with diabetes, respectively, compared to their normal weight counterparts. Since the implications of these findings could be limited to middle-aged and older white European populations, our results need confirmation in other populations. Conclusions: Obesity in the middle aged and elderly is associated with a reduction in the number of years lived free of diabetes and an increase in the number of years lived with diabetes. Those extra years lived with morbidity might place a high toll on individuals and health care systems.

Patients with cardiovascular disease (CVD) are a heterogeneous group regarding their body mass index (BMI) levels at the time of diagnosis. To address the heterogeneity of CVD, we examined the trajectories of change in body mass index (BMI) and in other cardio-metabolic risk factors before CVD diagnosis. The study included 6126 participants from the prospective population-based Rotterdam Study, followed over 22 years with clinical examinations every 4 years. Latent class trajectory analysis and mixed-effect models were used to develop trajectories of BMI and other cardio-metabolic risk factors respectively. During follow-up, 1748 participants developed CVD, among whom we identified 3 distinct BMI trajectories. The majority of participants (n = 1534, 87.8 %) had steady BMI levels during follow-up, comprising the “stable weight” group. This group showed decrease in mean high-density lipoprotein (HDL) cholesterol over time. The second group, the “progressive weight gain” group (n = 112, 6.4 %), showed a progressive increase in BMI levels. In this group, mean waist circumference increased, mean HDL cholesterol decreased and mean fasting glucose levels were fluctuating over follow-up. In the third group, the “progressive weight loss” group (n = 102, 5.8 %), BMI levels decreased during follow-up. This group showed a decrease in mean waist circumference and in fasting glucose. In conclusion, the majority of individuals who developed CVD had a stable weight during follow-up, suggesting that BMI alone is not a good indicator for identifying middle-aged and elderly individuals at high risk of CVD. Waist circumference, HDL cholesterol, and glucose trajectories differed between the identified BMI subgroups, further highlighting that CVD is a heterogeneous disease with different pathophysiological pathways. Electronic supplementary material The online version of this article (doi:10.1007/s10654-016-0131-0) contains supplementary material, which is available to authorized users.

Background: Low serum magnesium has been implicated in cardiovascular mortality, but results are conflicting and the pathway is unclear. We studied the association of serum magnesium with coronary heart disease (CHD) mortality and sudden cardiac death (SCD) within the prospective population‐based Rotterdam Study, with adjudicated end points and long‐term follow‐up. Methods and Results: Nine‐thousand eight‐hundred and twenty participants (mean age 65.1 years, 56.8% female) were included with a median follow‐up of 8.7 years. We used multivariable Cox proportional hazard models and found that a 0.1 mmol/L increase in serum magnesium level was associated with a lower risk for CHD mortality (hazard ratio: 0.82, 95% CI 0.70–0.96). Furthermore, we divided serum magnesium in quartiles, with the second and third quartile combined as reference group (0.81–0.88 mmol/L). Low serum magnesium (≤0.80 mmol/L) was associated with an increased risk of CHD mortality (N=431, hazard ratio: 1.36, 95% CI 1.09–1.69) and SCD (N=217, hazard ratio: 1.54, 95% CI 1.12–2.11). Low serum magnesium was associated with accelerated subclinical atherosclerosis (expressed as increased carotid intima‐media thickness: +0.013 mm, 95% CI 0.005–0.020) and increased QT‐interval, mainly through an effect on heart rate (RR‐interval: −7.1 ms, 95% CI −13.5 to −0.8). Additional adjustments for carotid intima‐media thickness and heart rate did not change the associations with CHD mortality and SCD. Conclusions: Low serum magnesium is associated with an increased risk of CHD mortality and SCD. Although low magnesium was associated with both carotid intima‐media thickness and heart rate, this did not explain the relationship between serum magnesium and CHD mortality or SCD. Future studies should focus on why magnesium associates with CHD mortality and SCD and whether intervention reduces these risks.