Multiple studies have identified single-nucleotide polymorphisms (SNPs) that are associated with coronary heart disease (CHD). We examined whether SNPs selected based on predefined criteria will improve CHD risk prediction when added to traditional risk factors (TRFs).
SNPs were selected from the literature based on association with CHD, lack of association with a known CHD risk factor, and successful replication. A genetic risk score (GRS) was constructed based on these SNPs. Cox proportional hazards model was used to calculate CHD risk based on the Atherosclerosis Risk in Communities (ARIC) and Framingham CHD risk scores with and without the GRS.
The GRS was associated with risk for CHD (hazard ratio [HR] = 1.10; 95% confidence interval [CI]: 1.07–1.13). Addition of the GRS to the ARIC risk score significantly improved discrimination, reclassification, and calibration beyond that afforded by TRFs alone in non-Hispanic whites in the ARIC study. The area under the receiver operating characteristic curve (AUC) increased from 0.742 to 0.749 (Δ= 0.007; 95% CI, 0.004–0.013), and the net reclassification index (NRI) was 6.3%. Although the risk estimates for CHD in the Framingham Offspring (HR = 1.12; 95% CI: 1.10–1.14) and Rotterdam (HR = 1.08; 95% CI: 1.02–1.14) Studies were significantly improved by adding the GRS to TRFs, improvements in AUC and NRI were modest.
Addition of a GRS based on direct associations with CHD to TRFs significantly improved discrimination and reclassification in white participants of the ARIC Study, with no significant improvement in the Rotterdam and Framingham Offspring Studies.
Genetics; Risk factors; Coronary disease
Lipoprotein-associated phospholipase A2 (Lp-PLA2) generates proinflammatory and proatherogenic compounds in the arterial vascular wall and is a potential therapeutic target in coronary heart disease (CHD). We searched for genetic loci related to Lp-PLA2 mass or activity by a genome-wide association study as part of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.
Methods and results
In meta-analyses of findings from five population-based studies, comprising 13 664 subjects, variants at two loci (PLA2G7, CETP) were associated with Lp-PLA2 mass. The strongest signal was at rs1805017 in PLA2G7 [P = 2.4 × 10−23, log Lp-PLA2 difference per allele (beta): 0.043]. Variants at six loci were associated with Lp-PLA2 activity (PLA2G7, APOC1, CELSR2, LDL, ZNF259, SCARB1), among which the strongest signals were at rs4420638, near the APOE–APOC1–APOC4–APOC2 cluster [P = 4.9 × 10−30; log Lp-PLA2 difference per allele (beta): −0.054]. There were no significant gene–environment interactions between these eight polymorphisms associated with Lp-PLA2 mass or activity and age, sex, body mass index, or smoking status. Four of the polymorphisms (in APOC1, CELSR2, SCARB1, ZNF259), but not PLA2G7, were significantly associated with CHD in a second study.
Levels of Lp-PLA2 mass and activity were associated with PLA2G7, the gene coding for this protein. Lipoprotein-associated phospholipase A2 activity was also strongly associated with genetic variants related to low-density lipoprotein cholesterol levels.
Genome-wide association; Inflammation; Lipoprotein-associated phospholipase A2
Copy-number variants (CNVs) are a source of genetic variation that increasingly are associated with human disease. However, the role of CNVs in human lifespan is to date unknown. To identify CNVs that influence mortality at old age, we analyzed genome-wide CNV data in 5178 participants of Rotterdam Study (RS1) and positive findings were evaluated in 1714 participants of the second cohort of the Rotterdam Study (RS2) and in 4550 participants of Framingham Heart Study (FHS). First, we assessed the total burden of rare (frequency <1%) and common (frequency >1%) CNVs for association with mortality during follow-up. These analyses were repeated by stratifying CNVs by type and size. Secondly, we assessed individual common CNV regions (CNVR) for association with mortality. We observed that the burden of common but not of rare CNVs influences mortality. A higher burden of large (≥500 kb) common deletions associated with 4% higher mortality [hazard ratio (HR) per CNV 1.04, 95% confidence interval (CI) 1.02–1.07, P = 5.82 × 10−5] in the 11 442 participants of RS1, RS2 and FHS. In the analysis of 312 individual common CNVRs, we identified two regions (11p15.5; 14q21.3) that associated with higher mortality in these cohorts. The 11p15.5 region (combined HR 1.59, 95% CI 1.31–1.93, P = 2.87 × 10−6) encompasses 41 genes, of which some have previously been related to longevity, whereas the 14q21.3 region (combined HR 1.57, 95% CI 1.19–2.07, P = 1.53 × 10−3) does not encompass any genes. In conclusion, the burden of large common deletions, as well as common CNVs in 11p15.5 and 14q21.3 region, associate with higher mortality.
In view of the population-specific heterogeneity in reported genetic risk factors for Parkinson's disease (PD), we conducted a genome-wide association study (GWAS) in a large sample of PD cases and controls from the Netherlands. After quality control (QC), a total of 514 799 SNPs genotyped in 772 PD cases and 2024 controls were included in our analyses. Direct replication of SNPs within SNCA and BST1 confirmed these two genes to be associated with PD in the Netherlands (SNCA, rs2736990: P=1.63 × 10−5, OR=1.325 and BST1, rs12502586: P=1.63 × 10−3, OR=1.337). Within SNCA, two independent signals in two different linkage disequilibrium (LD) blocks in the 3′ and 5′ ends of the gene were detected. Besides, post-hoc analysis confirmed GAK/DGKQ, HLA and MAPT as PD risk loci among the Dutch (GAK/DGKQ, rs2242235: P=1.22 × 10−4, OR=1.51; HLA, rs4248166: P=4.39 × 10−5, OR=1.36; and MAPT, rs3785880: P=1.9 × 10−3, OR=1.19).
SNCA; BST1; GAK/DGKQ; HLA; MAPT; PD
Genotype imputation has become an essential tool in the analysis of genome-wide association scans. This technique allows investigators to test association at ungenotyped genetic markers, and to combine results across studies that rely on different genotyping platforms. In addition, imputation is used within long-running studies to reuse genotypes produced across generations of platforms. Typically, genotypes of controls are reused and cases are genotyped on more novel platforms yielding a case–control study that is not matched for genotyping platforms. In this study, we scrutinize such a situation and validate GWAS results by actually retyping top-ranking SNPs with the Sequenom MassArray platform. We discuss the needed quality controls (QCs). In doing so, we report a considerable discrepancy between the results from imputed and retyped data when applying recommended QCs from the literature. These discrepancies appear to be caused by extrapolating differences between arrays by the process of imputation. To avoid false positive results, we recommend that more stringent QCs should be applied. We also advocate reporting the imputation quality measure (RT2) for the post-imputation QCs in publications.
GWAS; imputation; quality control
Age-related macular degeneration (AMD) is a major cause of blindness in older adults and has a genetically complex background. This study examines the potential association between single nucleotide polymorphisms (SNPs) in the glucose transporter 1 (SLC2A1) gene and AMD. SLC2A1 regulates the bioavailability of glucose in the retinal pigment epithelium (RPE), which might influence oxidative stress–mediated AMD pathology.
Twenty-two SNPs spanning the SLC2A1 gene were genotyped in 375 cases and 199 controls from an initial discovery cohort (the Amsterdam-Rotterdam-Netherlands study). Replication testing was performed in The Rotterdam Study (the Netherlands) and study populations from Würzburg (Germany), the Age Related Eye Disease Study (AREDS; United States), Columbia University (United States), and Iowa University (United States). Subsequently, a meta-analysis of SNP association was performed.
In the discovery cohort, significant genotypic association between three SNPs (rs3754219, rs4660687, and rs841853) and AMD was found. Replication in five large independent (Caucasian) cohorts (4,860 cases and 4,004 controls) did not yield consistent association results. The genotype frequencies for these SNPs were significantly different for the controls and/or cases among the six individual populations. Meta-analysis revealed significant heterogeneity of effect between the studies.
No overall association between SLC2A1 SNPs and AMD was demonstrated. Since the genotype frequencies for the three SLC2A1 SNPs were significantly different for the controls and/or cases between the six cohorts, this study corroborates previous evidence that population dependent genetic risk heterogeneity in AMD exists.
In genome-wide association studies (GWAS) of complex traits, single SNP analysis is still the most applied approach. However, the identified SNPs have small effects and provide limited biological insight. A more appropriate approach to interpret GWAS data of complex traits is to analyze the combined effect of a SNP set grouped per pathway or gene region. We used this approach to study the joint effect on human longevity of genetic variation in two candidate pathways, the insulin/insulin-like growth factor (IGF-1) signaling (IIS) pathway and the telomere maintenance (TM) pathway. For the analyses, we used genotyped GWAS data of 403 unrelated nonagenarians from long-lived sibships collected in the Leiden Longevity Study and 1,670 younger population controls. We analyzed 1,021 SNPs in 68 IIS pathway genes and 88 SNPs in 13 TM pathway genes using four self-contained pathway tests (PLINK set-based test, Global test, GRASS and SNP ratio test). Although we observed small differences between the results of the different pathway tests, they showed consistent significant association of the IIS and TM pathway SNP sets with longevity. Analysis of gene SNP sets from these pathways indicates that the association of the IIS pathway is scattered over several genes (AKT1, AKT3, FOXO4, IGF2, INS, PIK3CA, SGK, SGK2, and YWHAG), while the association of the TM pathway seems to be mainly determined by one gene (POT1). In conclusion, this study shows that genetic variation in genes involved in the IIS and TM pathways is associated with human longevity.
Electronic supplementary material
The online version of this article (doi:10.1007/s11357-011-9340-3) contains supplementary material, which is available to authorized users.
Genetics; Aging; Longevity; Gene set analysis; Insulin/IGF-1 signaling; Telomere maintenance
The Rotterdam Study is a prospective cohort study ongoing since 1990 in the city of Rotterdam in The Netherlands. The study targets cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, oncological, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. The findings of the Rotterdam Study have been presented in over a 1,000 research articles and reports (see www.erasmus-epidemiology.nl/rotterdamstudy). This article gives the rationale of the study and its design. It also presents a summary of the major findings and an update of the objectives and methods.
Biomarkers; Cardiovascular diseases; Cohort study; Dermatological diseases; Endocrine diseases; Epidemiologic methods; Genetic epidemiology; Liver diseases; Neurological diseases; Oncology; Ophthalmic diseases; Pharmacoepidemiology; Renal diseases; Psychiatric diseases; Respiratory diseases
Runs of homozygosity (ROH) are extended tracts of adjacent homozygous single nucleotide polymorphisms (SNPs) that are more common in unrelated individuals than previously thought. It has been proposed that estimating ROH on a genome-wide level, by making use of the genome-wide single nucleotide polymorphism (SNP) data, will enable to indentify recessive variants underlying complex traits. Here, we examined ROH larger than 1.5 Mb individually and in combination for association with survival in 5974 participants of the Rotterdam Study. In addition, we assessed the role of overall homozygosity, expressed as a percentage of the autosomal genome that is in ROH longer than 1.5 Mb, on survival during a mean follow-up period of 12 years. None of these measures of homozygosity was associated with survival to old age.
To investigate the association between variants in the complement component 5 (C5) gene and age-related macular degeneration (AMD).
Separate and combined data from three large AMD case-control studies and a prospective population-based study (The Rotterdam Study).
A total of 2599 AMD cases and 3458 ethnically matched controls.
Fifteen single nucleotide polymorphisms (SNPs) spanning the C5 gene were initially genotyped in 375 cases and 199 controls from the Netherlands (The AMRO-NL study population). Replication testing of selected SNPs was performed in the Rotterdam Study (NL) and study populations from Southampton, United Kingdom (UK) and New York, United States (US).
Main Outcome Measures
Early and late stages of prevalent and incident AMD, graded according to (a modification of) the international grading and classification system of AMD.
Significant allelic or genotypic associations between eight C5 SNPs and AMD were found in the AMRO-NL study and this risk appeared independently of CFH Y402H, LOC387715 A69S, age and gender. None of these findings could be confirmed consistently in three replication populations.
Although the complement pathway, including C5, plays a crucial role in AMD, and the C5 protein is present in drusen, no consistent significant associations between C5 SNPs and AMD were found in all studies. The implications for genetic screening of AMD are discussed.
Evolutionary theories of aging predict a trade-off between fertility and lifespan, where increased lifespan comes at the cost of reduced fertility. Support for this prediction has been obtained from various sources. However, which genes underlie this relationship is unknown. To assess it, we first analyzed the association of fertility with age at menarche and menopause, and with mortality in 3,575 married female participants of the Rotterdam Study. In addition, we conducted a candidate gene study where 1,664 single nucleotide polymorphisms (SNPs) in 25 candidate genes were analyzed in relation to number of children as a measure of fertility. SNPs that associated with fertility were analyzed for association with mortality. We observed no associations between fertility and age at menarche (p = 0.38) and menopause (p = 0.07). In contrast, fertility was associated with mortality. Women with two to three children had significantly lower mortality (hazard ratio (HR), 0.82; 95% confidence interval (95% CI), 0.69–0.97) compared to women with no children. No such benefit was observed for women with four or more children, who had a similar mortality risk (HR, 0.93; 95% CI, 0.76–1.13) as women with no children. The analysis of candidate genes revealed four genes that influence fertility after correction for multiple testing: CGB/LHB gene cluster (p = 0.0036), FSHR (p = 0.023), FST (p = 0.023), and INHBA (p = 0.021). However, none of the independent SNPs in these genes predicted mortality. In conclusion, women who bear two to three children live longer than those who bear none or many children, but this relationship was not mediated by the candidate genes analyzed in this study.
Electronic supplementary material
The online version of this article (doi:10.1007/s11357-010-9202-4) contains supplementary material, which is available to authorized users.
Fertility; Lifespan; Trade-off; Gene; SNP
SIRT1 has pleiotropic metabolic functions. We investigated whether SIRT1 genetic variation is associated with obesity.
RESEARCH DESIGN AND METHODS
In 6,251 elderly subjects from the prospective, population-based Rotterdam Study, three single nucleotide polymorphisms (SNPs) in the SIRT1 gene were studied in relation to BMI and risk of obesity (BMI ≥30 kg/m2) and prospectively with BMI change after 6.4 years of follow-up. We used cross-sectional data from 2,347 participants from the Erasmus Rucphen Family (ERF) study for replication.
Minor alleles of rs7895833 (G = 20.2%) and rs1467568 (A = 36.8%) were associated with lower BMI in the Rotterdam Study (P = 0.02 and 0.04) and in the replication cohort ERF study (P = 0.03 and 0.008) and in both studies combined (P = 0.002 for both SNPs), with a 0.2–0.4 kg/m2 decrease in BMI per allele copy. Carriers of these alleles had 13–18% decreased risk of obesity (for rs7895833 in the Rotterdam Study: odds ratio 0.79 [95% CI 0.67–0.94], P = 0.007; in the ERF study: 0.93 [0.73–1.19], P = 0.37; and in the studies combined 0.87 [0.77–0.97], P = 0.02; for rs1467568 in the Rotterdam Study: 0.80 [0.68–0.94], P = 0.007; in the ERF study: 0.85 [0.72–0.99], P = 0.04; and in the studies combined: 0.82 [0.73–0.92], P = 0.0009). In the Rotterdam Study, the two variants were also associated with a lower BMI increase during 6.4 years of follow-up (P = 0.01 and 0.08).
Two common variants in SIRT1 are associated with lower BMI in two independent Dutch populations. Carriers of these variants have 13–18% decreased risk of obesity and gain less weight over time. The availability of SIRT1 stimulators makes these findings relevant in light of the growing obesity epidemic.
Common variation within the nitric oxide-1 synthase activator protein (NOS1AP) locus is strongly related to QT interval, a sudden cardiac death (SCD) risk factor. A recent report describes common variation in NOS1AP associated with SCD in a US population of European ancestry. The objective of the current study was to obtain additional evidence by investigating the association between NOS1AP variants and SCD in the prospective population-based Rotterdam Study. The study population consisted of 5974 European ancestry subjects, aged 55 years and older, genotyped on Illumina arrays. SCD was defined according to European Society of Cardiology guidelines. Smoking, body mass index, diabetes mellitus, hypertension, heart failure and myocardial infarction were used as covariates in Cox proportional hazard models. Results were combined with reported evidence using inverse-variance weighted meta-analysis. Two hundred and eight (109 witnessed) cases of SCD occurred during a mean follow-up of 10.4 years. Within the Rotterdam Study alone, no significant associations were observed. Upon pooling of results with existing data, we observed strengthening of existing evidence for rs16847549 (US data HR = 1.31, P = 0.0024; Rotterdam Study HR = 1.18, P = 0.16; joint HR = 1.26, P = 0.0011). When the case definition in the Rotterdam Study was restricted to witnessed SCD, association of rs16847549 with SCD became stronger (joint P = 0.00019) and additionally the association between rs12567209 and SCD gained significance (US data HR = 0.57, P = 0.0035; Rotterdam Study HR = 0.69, P = 0.23; joint HR = 0.60, P = 0.0018). In conclusion, this study provided additional evidence for association between genetic variation within NOS1AP and SCD. The mechanism by which this effect is exerted remains to be elucidated.
Age-related macular degeneration (AMD) is the leading cause of irreversible visual loss in the developed countries and is caused by both environmental and genetic factors. A recent study (Tuo et al., PNAS) reported an association between AMD and a single nucleotide polymorphism (SNP) (rs3793784) in the ERCC6 (NM_000124) gene. The risk allele also increased ERCC6 expression. ERCC6 is involved in DNA repair and mutations in ERCC6 cause Cockayne syndrome (CS). Amongst others, photosensitivity and pigmentary retinopathy are hallmarks of CS.
Separate and combined data from three large AMD case-control studies and a prospective population-based study (The Rotterdam Study) were used to analyse the genetic association between ERCC6 and AMD (2682 AMD cases and 3152 controls). We also measured ERCC6 mRNA levels in retinal pigment epithelium (RPE) cells of healthy and early AMD affected human donor eyes. Rs3793784 conferred a small increase in risk for late AMD in the Dutch population (The Rotterdam and AMRO-NL study), but this was not replicated in two non-European studies (AREDS, Columbia University). In addition, the AMRO-NL study revealed no significant association for 9 other variants spanning ERCC6. Finally, we determined that ERCC6 expression in the human RPE did not depend on rs3793784 genotype, but, interestingly, on AMD status: Early AMD-affected donor eyes had a 50% lower ERCC6 expression than healthy donor eyes (P = 0.018).
Our meta-analysis of four Caucasian cohorts does not replicate the reported association between SNPs in ERCC6 and AMD. Nevertheless, our findings on ERCC6 expression in the RPE suggest that ERCC6 may be functionally involved in AMD. Combining our data with those of the literature, we hypothesize that the AMD-related reduced transcriptional activity of ERCC6 may be caused by diverse, small and heterogeneous genetic and/or environmental determinants.
Substrates for the Organic Cation Transporter 1, encoded by the SLC22A1 gene, are metformin, amantadine, pramipexole, and, possibly, levodopa. Recently, we identified that the rs622342 A > C polymorphism is associated with the HbA1c lowering effect in metformin users. In the Rotterdam Study, we associated this polymorphism with higher prescribed doses of all anti-Parkinsonian drugs. Between the first and fifth prescriptions for levodopa, for each minor rs622342 C allele, the prescribed doses were 0.34 defined daily dose higher (95% CI 0.064, 0.62; p = 0.017). The mortality ratio after start of levodopa therapy was 1.47 times higher (95% CI 1.01, 2.13; p = 0.045).
Organic Cation Transporter 1; Anti-Parkinson Agents; Pharmacogenetics; Pharmacoepidemiology
epidemiology; meta-analysis; genetics; genomics
OBJECTIVE— Metformin, an oral glucose-lowering drug, is taken up in hepatocytes by the organic cation transporter (OCT) 1 and in renal epithelium by OCT2. In these cells, the multidrug and toxin extrusion (MATE) 1 protein, encoded by the SLC47A1 gene, is responsible for the excretion of metformin into the bile and urine, respectively. We studied the effect of single nucleotide polymorphisms (SNPs) in the SLC47A1 gene on the A1C-lowering effect of metformin.
RESEARCH DESIGN AND METHODS— We identified all incident metformin users in the Rotterdam Study, a population-based cohort study. Associations between 12 tagging SNPs in the SLC47A1 gene and change in A1C level were analyzed.
RESULTS— One hundred and sixteen incident metformin users were included in the study sample. The rs2289669 G>A SNP was significantly associated with metformin response. For the other SNPs, no associations were found. For each minor A allele at rs2289669, the A1C reduction was 0.30% (95% CI −0.51 to −0.10; P = 0.005) larger. After Bonferroni correction for multiple testing, the P value was 0.045.
CONCLUSIONS— The rs2289669 G>A SNP is associated with a reduction in A1C level, consistent with a reduction in MATE1 transporter activity. These results suggest that the transporter MATE1, encoded by SLC47A1, may have an important role in the pharmacokinetics of metformin, although replication is necessary.
Despite the positive association between body mass index (BMI) and bone mineral density (BMD) and content (BMC), the role of fat distribution in BMD/BMC remains unclear. We examined relationships between BMD/BMC and various measurements of fat distribution and studied the role of BMI, insulin, and adiponectin in these relations. Using a cross-sectional investigation of 2631 participants from the Erasmus Rucphen Family study, we studied associations between BMD (using dual-energy X-ray absorptiometry (DXA]) at the hip, lumbar spine, total body (BMD and BMC), and fat distribution by the waist-to-hip ratio (WHR), waist-to-thigh ratio (WTR), and DXA-based trunk-to-leg fat ratio and android-to-gynoid fat ratio. Analyses were stratified by gender and median age (48.0 years in women and 49.2 years in men) and were performed with and without adjustment for BMI, fasting insulin, and adiponectin. Using linear regression (adjusting for age, height, smoking, and use of alcohol), most relationships between fat distribution and BMD and BMC were positive, except for WTR. After BMI adjustment, most correlations were negative except for trunk-to-leg fat ratio in both genders. No consistent influence of age or menopausal status was found. Insulin and adiponectin levels did not explain either positive or negative associations. In conclusion, positive associations between android fat distribution and BMD/BMC are explained by higher BMI but not by higher insulin and/or lower adiponectin levels. Inverse associations after adjustment for BMI suggest that android fat deposition as measured by the WHR, WTR, and DXA-based android-to-gynoid fat ratio is not beneficial and possibly even deleterious for bone.
Fat distribution; Bone mineral density; Body composition; Android-to-gynoid fat ratio; Waist-to-hip ratio; Insulin; Adiponectin
It is assumed that testosterone is an important regulator of gender-related differences in ventricular repolarization. Therefore, our aim was to study whether serum levels of testosterone are associated with QTc, QT and RR interval variation. Setting: two independent population-based cohort studies. Participants: 445 male participants (≥55 years) from the Rotterdam study cohort and 1,428 male participants from the study of health in Pomerania (SHIP) with an electrocardiogram who were randomly sampled for assessment of serum testosterone at baseline, after exclusion of participants with testosterone altering drugs, QTc prolonging drugs or dig(it)oxin, left ventricular hypertrophy and left and right bundle branch block. Endpoints: length of the QTc, QT and RR intervals. Analysis: linear regression model, adjusted for the two individual studies and a pooled analysis of both studies. The pooled analysis of the Rotterdam study and SHIP showed that the QTc interval gradually decreased among the tertiles (P value for trend 0.024). The third tertile of serum testosterone was associated with a lower QTc interval compared to the first tertile [−3.4 ms (−6.5; −0.3)]. However, the third tertile of serum testosterone was not associated with a lower QT interval compared to the first tertile [−0.7 ms (−3.1; 1.8)]. The RR interval gradually increased among the tertiles (P value for trend 0.002) and the third tertile of serum testosterone showed an increased RR interval compared to the first tertile [33.5 ms (12.2; 54.8)]. In the pooled analysis of two population-based studies, serum testosterone levels were not associated with the QT interval, which could be due to a lack of power. Lower QTc intervals in men with higher serum testosterone levels could be due to the association of serum testosterone with prolongation of the RR interval.
Serum testosterone; Ventricular repolarization; QTc interval; RR interval
OBJECTIVE—Prediction of type 2 diabetes based on genetic testing might improve identification of high-risk subjects. Genome-wide association (GWA) studies identified multiple new genetic variants that associate with type 2 diabetes. The predictive value of genetic testing for prediction of type 2 diabetes in the general population is unclear.
RESEARCH DESIGN AND METHODS—We investigated 18 polymorphisms from recent GWA studies on type 2 diabetes in the Rotterdam Study, a prospective, population-based study among homogeneous Caucasian individuals of 55 years and older (genotyped subjects, n = 6,544; prevalent cases, n = 686; incident cases during follow-up, n = 601; mean follow-up 10.6 years). The predictive value of these polymorphisms was examined alone and in addition to clinical characteristics using logistic and Cox regression analyses. The discriminative accuracy of the prediction models was assessed by the area under the receiver operating characteristic curves (AUCs).
RESULTS—Of the 18 polymorphisms, the ADAMTS9, CDKAL1, CDKN2A/B-rs1412829, FTO, IGF2BP2, JAZF1, SLC30A8, TCF7L2, and WFS1 variants were associated with type 2 diabetes risk in our population. The AUC was 0.60 (95% CI 0.57–0.63) for prediction based on the genetic polymorphisms; 0.66 (0.63–0.68) for age, sex, and BMI; and 0.68 (0.66–0.71) for the genetic polymorphisms and clinical characteristics combined.
CONCLUSIONS—We showed that 9 of 18 well-established genetic risk variants were associated with type 2 diabetes in a population-based study. Combining genetic variants has low predictive value for future type 2 diabetes at a population-based level. The genetic polymorphisms only marginally improved the prediction of type 2 diabetes beyond clinical characteristics.
The Rotterdam Study is a prospective cohort study ongoing since 1990 in the city of Rotterdam in The Netherlands. The study targets cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. The findings of the Rotterdam Study have been presented in close to a 1,000 research articles and reports (see www.epib.nl/rotterdamstudy). This article gives the rationale of the study and its design. It also presents a summary of the major findings and an update of the objectives and methods.
Biomarkers; Cardiovascular diseases; Cohort study; Endocrine diseases; Epidemiologic methods; Genetic epidemiology; Liver diseases; Neurological diseases; Ophthalmic diseases; Pharmacoepidemiology; Psychiatric diseases; Respiratory diseases
Summary: The current fast growth of genome-wide association studies (GWAS) combined with now common computationally expensive imputation requires the online access of large user groups to high-performance computing resources capable of analyzing rapidly and efficiently millions of genetic markers for ten thousands of individuals. Here, we present a web-based interface—called GRIMP—to run publicly available genetic software for extremely large GWAS on scalable super-computing grid infrastructures. This is of major importance for the enlargement of GWAS with the availability of whole-genome sequence data from the 1000 Genomes Project and for future whole-population efforts.
Contact: firstname.lastname@example.org; email@example.com
Osteoporosis is a bone disease leading to an increased fracture risk. It is considered a complex multifactorial genetic disorder with interaction of environmental and genetic factors. As a candidate gene for osteoporosis, we studied vitamin D binding protein (DBP, or group-specific component, Gc), which binds to and transports vitamin D to target tissues to maintain calcium homeostasis through the vitamin D endocrine system. DBP can also be converted to DBP-macrophage activating factor (DBP-MAF), which mediates bone resorption by directly activating osteoclasts. We summarized the genetic linkage structure of the DBP gene. We genotyped two single-nucleotide polymorphisms (SNPs, rs7041 = Glu416Asp and rs4588 = Thr420Lys) in 6,181 elderly Caucasians and investigated interactions of the DBP genotype with vitamin D receptor (VDR) genotype and dietary calcium intake in relation to fracture risk. Haplotypes of the DBP SNPs correspond to protein variations referred to as Gc1s (haplotype 1), Gc2 (haplotype 2), and Gc1f (haplotype3). In a subgroup of 1,312 subjects, DBP genotype was found to be associated with increased and decreased serum 25-(OH)D3 for haplotype 1 (P = 3 × 10−4) and haplotype 2 (P = 3 × 10−6), respectively. Similar associations were observed for 1,25-(OH)2D3. The DBP genotype was not significantly associated with fracture risk in the entire study population. Yet, we observed interaction between DBP and VDR haplotypes in determining fracture risk. In the DBP haplotype 1-carrier group, subjects of homozygous VDR block 5-haplotype 1 had 33% increased fracture risk compared to noncarriers (P = 0.005). In a subgroup with dietary calcium intake <1.09 g/day, the hazard ratio (95% confidence interval) for fracture risk of DBP hap1-homozygote versus noncarrier was 1.47 (1.06–2.05). All associations were independent of age and gender. Our study demonstrated that the genetic effect of the DBP gene on fracture risk appears only in combination with other genetic and environmental risk factors for bone metabolism.
DBP; VDR; Haplotype; Calcium intake; Fracture
Most common age-related diseases such as osteoporosis, have strong genetic influences and therefore intense efforts are ongoing to identify the underlying genetic variants. Knowledge of these variants can help in understanding the disease process and might benefit development of interventions and diagnostics. Association studies have now become the standard approach to uncover the genetic effects of common variants. Yet, in all fields of complex disease genetics – including osteoporosis – progress in identifying these genetic factors has been hampered by often controversial results. Because of the complicated genetic architecture of the diseases and the small effect size for each individual risk alleles, this is mostly due to low statistical power and limitations of analytical methods. It is now recognised that association analysis followed by replication and prospective multi-centred meta-analysis is currently the best way forward to identify genetic markers for complex traits, such as osteoporosis. To accomplish this, large (global) collaborative consortia have been established that have large collections of DNA samples from subjects with a certain phenotype and that use standardized methodology and definitions, to quantify by meta-analysis the subtle effects of the responsible gene variants. The GENOMOS consortium has played such a role in the field of osteoporosis and has initially identified and refuted associations of well known candidate genes. This consortium is now expected to play an important role in validation of risk alleles coming from Genome Wide Association Studies (GWAS) for osteoporosis, some of which have just been published. Together with genetic studies on more rare syndromes, the GWA approach in combination with the GENOMOS consortium, is likely to help in clarifying the genetic architecture of complex bone traits such as BMD, and – eventually – in understanding the genetics of clinically relevant endpoints in osteoporosis, i.e., fracture risk. Such genetic insights will be useful in understanding biology and are likely to also find applications in clinical practice.
genetic, osteoporosis, polymorphisms, GWAS.
Arterial stiffness normally increases with age and has been established as a precursor of cardiovascular disease. Interleukin-6 is a pleiotropic inflammatory cytokine with an important role in the inflammatory cascade, such as up-regulation of C-reactive protein (CRP). The interleukin-6 –174-G/C promoter polymorphism appears to influence levels of inflammatory markers, which have been shown to be associated with arterial stiffness. We studied the association of this polymorphism with levels of interleukin-6 and CRP and with arterial stiffness. The study (n = 3849) was embedded in the Rotterdam Study, a prospective, population-based study. Analyses on the association between the –174-G/C polymorphism and pulse wave velocity, distensibility coefficient, and pulse pressure were performed using analyses of variance. Analyses on the levels of inflammatory markers and arterial stiffness were performed using linear regression analyses. Analyses were adjusted for age, sex, mean arterial pressure, heart rate, known cardiovascular risk factors, and atherosclerosis. We found pulse wave velocity to be 0.35 m/s higher for CC-homozygotes vs. wildtype GG-homozygotes (p = 0.018) with evidence for an allele-dose effect (p trend = 0.013), and a similar pattern for pulse pressure (p trend = 0.041). No apparent consistent association with the distensibility coefficient was found. CRP levels were associated with pulse wave velocity (p = 0.007). In conclusion, the interleukin-6 –174 G/C polymorphism is associated with increased arterial stiffness and pulse pressure.
IL-6; CRP; arterial stiffness; pulse wave velocity; distensibility coefficient; pulse pressure