Paul M Ridker

Academisch Medisch Centrum Universiteit van Amsterdam, Amsterdam, North Holland, Netherlands

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Publications (734)8432.79 Total impact

  • [show abstract] [hide abstract]
    ABSTRACT: Vitamin D is involved in blood pressure (BP) regulation. Genetic variations may influence the effect of vitamin D on BP, but data from epidemiologic studies remain inconsistent. We conducted a comprehensive genetic association study in the Women's Genome Health Study (WGHS) with genome-wide genotype data among 23,294 women of European ancestry and in the International Consortium of Blood Pressure (ICBP) with genome-wide meta-analysis results from 69,395 men and women of European ancestry. First, we found none of 5 selected vitamin D-related candidate single nucleotide polymorphisms (SNPs) was associated with systolic BP (SBP) or diastolic BP (DBP). Second, in 61 candidate SNPs involved in vitamin D metabolism and signaling, rs1507023 (in RBFOX1) and rs2296241 (in CYP24A1) showed significant associations with SBP, DBP, mean arterial pressure, or pulse pressure in the WGHS before, but not after, multiple testing corrections. Nominally significant associations in the ICBP were also not significant after corrections. Third, among 24 candidate genes across vitamin D pathway, associations with BP traits that meet gene-wide significance level were found for NCOA3 (rs2235734), RXRA (rs875444), DHCR7 (rs1790370), VDR (rs2544037), and NCOR2 (rs1243733, rs1147289) in the WGHS and NCOR1, TP53BP1, and TYRP1 in the ICBP. However, none of these associations reached significance threshold in both studies. Our study did not replicate previously observed associations of vitamin D-related SNPs with BP. There was suggestive evidence for associations in other vitamin D pathway genes; however, these associations either did not reach the significance threshold or were not replicated.
    American Journal of Hypertension 03/2014; · 3.67 Impact Factor
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    ABSTRACT: The value of measuring levels of glycated hemoglobin (HbA1c) for the prediction of first cardiovascular events is uncertain. To determine whether adding information on HbA1c values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk. Analysis of individual-participant data available from 73 prospective studies involving 294,998 participants without a known history of diabetes mellitus or CVD at the baseline assessment. Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5% to <7.5%), and high (≥7.5%) risk. During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20,840 incident fatal and nonfatal CVD outcomes (13,237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA1c values and CVD risk. The association between HbA1c values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA1c was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (-0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA1c assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels. In a study of individuals without known CVD or diabetes, additional assessment of HbA1c values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk.
    JAMA The Journal of the American Medical Association 03/2014; 311(12):1225-33. · 29.98 Impact Factor
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    ABSTRACT: Blood pressure (BP) is a heritable risk factor for cardiovascular disease. To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP), we genotyped ∼50,000 SNPs in up to 87,736 individuals of European ancestry and combined these in a meta-analysis. We replicated findings in an independent set of 68,368 individuals of European ancestry. Our analyses identified 11 previously undescribed associations in independent loci containing 31 genes including PDE1A, HLA-DQB1, CDK6, PRKAG2, VCL, H19, NUCB2, RELA, HOXC@ complex, FBN1, and NFAT5 at the Bonferroni-corrected array-wide significance threshold (p < 6 × 10(-7)) and confirmed 27 previously reported associations. Bioinformatic analysis of the 11 loci provided support for a putative role in hypertension of several genes, such as CDK6 and NUCB2. Analysis of potential pharmacological targets in databases of small molecules showed that ten of the genes are predicted to be a target for small molecules. In summary, we identified previously unknown loci associated with BP. Our findings extend our understanding of genes involved in BP regulation, which may provide new targets for therapeutic intervention or drug response stratification.
    The American Journal of Human Genetics 02/2014; · 11.20 Impact Factor
  • Paul M Ridker, Nancy R Cook
    The Lancet 02/2014; 383(9917):600. · 39.06 Impact Factor
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    ABSTRACT: Large-scale randomized clinical trials have established the efficacy of cholesterol-lowering, blood pressure-lowering, and anti-platelet therapy to prevent cardiovascular diseases. A challenge for clinicians is to apply group-level evidence from these trials to individual patients. Trials typically report a single treatment effect estimate which is the average effect of all participants, comprising patients who respond poorly, intermediately, and well. Clinicians would preferably make patient-tailored treatment decisions. Therefore, one would require an estimate of an individual patient's response to therapy. Although not yet widely recognized, trials contain this type of information. In this paper, we show how available information from landmark trials can be translated to an individual 'treatment score' through the use of multivariable therapeutic prediction models. These models provide an individual estimate of the absolute risk reduction in cardiovascular events given the specific combination of multiple clinical characteristics of a patient under care. Based on this individualized treatment estimate and metrics such as the individual number-needed-to-treat, clinicians together with their patients can decide whether drug treatment or what treatment intensity is worthwhile. Selective treatment of those who can anticipate the greatest benefit and the least harm on an individualized basis could reduce the number of unnecessary treatments and healthcare costs beyond that currently achievable by subgroup analyses based on single patient characteristics.
    European Heart Journal 02/2014; · 14.10 Impact Factor
  • Paul M Ridker, Peter W F Wilson
    JAMA The Journal of the American Medical Association 01/2014; 311(3):306. · 29.98 Impact Factor
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    ABSTRACT: Previously, we showed that sex-specific complete blood count (CBC) risk scores strongly predicted risk of all-cause mortality in multiple sets of general medical patients. This study evaluated the CBC risk score in an independent, well-studied international primary risk population of lower-risk individuals initially free from cardiovascular (CV) disease. Observational secondary analysis of a randomized trial population. The previously derived and validated CBC score was evaluated for association with all-cause mortality among CV disease-free females (n = 6568) and males (n = 10,629) enrolled for up to 5 years in the Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin (JUPITER) trial. Associations of the CBC score with CV mortality and with major CV disease were also tested. The CBC score predicted all-cause mortality, with univariable hazard ratio (HR) 4.83 (95% CI 3.70-6.31) for the third CBC score tertile vs. the first tertile, and HR 2.31 (CI 1.75-3.05) for the second tertile (ptrend < 0.001). The CBC score retained significance after adjustment: HR 1.97 (CI 1.46-2.67) and 1.51 (CI 1.13-2.00) for tertiles 3 and 2 vs. 1, respectively (ptrend < 0.001). The CBC score also predicted CV mortality (ptrend = 0.025) and the primary JUPITER endpoint (ptrend = 0.015). c-statistics for mortality were 0.729 among all, and 0.722 and 0.750 for females and males, respectively. The CBC risk score was strongly associated with all-cause mortality among JUPITER trial participants and had good discrimination. It also predicted CV-specific outcomes. This CBC score may be useful in identifying cardiac disease-free individuals at increased risk of mortality.
    European journal of preventive cardiology. 01/2014;
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    ABSTRACT: To examine the interactions between genetic predisposition and consumption of fried food in relation to body mass index (BMI) and obesity. Prospective cohort study. Health professionals in the United States. 9623 women from the Nurses' Health Study, 6379 men from the Health Professionals Follow-up Study, and a replication cohort of 21 421 women from the Women's Genome Health Study. Repeated measurement of BMI over follow-up. There was an interaction between fried food consumption and a genetic risk score based on 32 BMI-associated variants on BMI in both the Nurses' Health Study and Health Professionals Follow-up Study (P≤0.001 for interaction). Among participants in the highest third of the genetic risk score, the differences in BMI between individuals who consumed fried foods four or more times a week and those who consumed fried foods less than once a week amounted to 1.0 (SE 0.2) in women and 0.7 (SE 0.2) in men, whereas the corresponding differences were 0.5 (SE 0.2) and 0.4 (SE 0.2) in the lowest third of the genetic risk score. The gene-diet interaction was replicated in the Women's Genome Health Study (P<0.001 for interaction). Viewed differently, the genetic association with adiposity was strengthened with higher consumption of fried foods. In the combined three cohorts, the differences in BMI per 10 risk alleles were 1.1 (SE 0.2), 1.6 (SE 0.3), and 2.2 (SE 0.6) for fried food consumption less than once, one to three times, and four or more times a week (P<0.001 for interaction); and the odds ratios (95% confidence intervals) for obesity per 10 risk alleles were 1.61 (1.40 to 1.87), 2.12 (1.73 to 2.59), and 2.72 (2.12 to 3.48) across the three categories of consumption (P=0.002 for interaction). In addition, the variants in or near genes highly expressed or known to act in the central nervous system showed significant interactions with fried food consumption, with the FTO (fat mass and obesity associated) variant showing the strongest result (P<0.001 for interaction). Our findings suggest that consumption of fried food could interact with genetic background in relation to obesity, highlighting the particular importance of reducing fried food consumption in individuals genetically predisposed to obesity.
    BMJ (Clinical research ed.). 01/2014; 348:g1610.
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    ABSTRACT: The length of female reproductive lifespan is associated with multiple adverse outcomes, including breast cancer, cardiovascular disease and infertility. The biological processes that govern the timing of the beginning and end of reproductive life are not well understood. Genetic variants are known to contribute to approximately 50% of the variation in both age at menarche and menopause, but to date the known genes explain <15% of the genetic component. We have used genome-wide association in a bivariate meta-analysis of both traits to identify genes involved in determining reproductive lifespan. We observed significant genetic correlation between the two traits using genome-wide complex trait analysis. However, we found no robust statistical evidence for individual variants with an effect on both traits. A novel association with age at menopause was detected for a variant rs1800932 in the mismatch repair gene MSH6 (P = 1.9 x 10(-9)), which was also associated with altered expression levels of MSH6 mRNA in multiple tissues. This study contributes to the growing evidence that DNA repair processes play a key role in ovarian ageing and could be an important therapeutic target for infertility.
    Hum Mol Genet. 01/2014; 23(9):2490-7.
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    ABSTRACT: Chronic inflammation closely associates with obesity, metabolic syndrome, diabetes mellitus, and atherosclerosis. Evidence indicates that the immunomodulator pentraxin 3 (PTX3) may serve as a biomarker of these cardiometabolic disorders, but whether PTX3 predicts cardiovascular complications is unknown. We examined the association of plasma PTX3 levels with recurrent coronary events via a prospective, nested, case-control design in the CARE trial. Among 4159 patients who had a prior myocardial infarction 3 to 20 months before enrollment and also had total cholesterol levels <240 mg/dL and LDL cholesterol levels between 115 and 175 mg/dL, we measured plasma PTX3 levels at baseline by high-sensitivity ELISA in 413 cases with recurrent myocardial infarction or coronary death during a 5-year follow-up period, and in 366 sex- and age-matched controls. Cases with recurrent coronary events and controls had similar PTX3 levels, and PTX3 did not predict recurrent coronary events - a finding that contrasts with that of C-reactive protein (CRP) and serum amyloid A (SAA) in this cohort. We then associated PTX3 levels with metabolic disorders. Low plasma PTX3 levels correlated with high body-mass index, waist circumference, and triglycerides; and with low HDL cholesterol. Overall, PTX3 levels correlated inversely with the number of metabolic syndrome components. PTX3 levels also correlated inversely with apoCIII and tissue plasminogen activator, but did not associate with CRP. Although the study further links low PTX3 levels with various features associated with metabolic syndrome, the results do not indicate that PTX3 can predict recurrent coronary events among MI survivors.
    PLoS ONE 01/2014; 9(4):e94073. · 3.73 Impact Factor
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    ABSTRACT: Recent animal and human studies have demonstrated the importance of RhoA/Rho-associated kinases (ROCKs) pathway in ischemic stroke (IsST). Whether the genetic variation within ROCKs-associated genes modulates IsST risk remains elusive. The association between 66 tag-SNPs (tSNPs) of 3 ROCKs-associated genes (ROCK1, ROCK2 and ARHGEF10) and incident IsST was investigated in 23,294 Caucasian female participants of the prospective Women's Genome Health Study. All were free of known cancer and cardiovascular disease at baseline. During a 15-year follow-up period, 323 participants developed a first ever IsST. Multivariable Cox regression analysis was performed to investigate the relationship between genotypes and IsST risk assuming an additive genetic model. Haplotype-block analysis was also performed. A total of ten tSNPs were associated with IsST risk (three in ARHGEF10, and seven in ROCK1; all p<0.050). Further investigation using the haplotype-block analysis revealed similar significant association of pre-specified haplotypes of ROCK1 with IsST risk (p=0.005). If corroborated in other large prospective studies, the present findings suggest that genetic variation within the ROCKs-associated pathway gene loci examined, in particular, the ROCK1 gene variation may influence IsST risk.
    Clinical Science 12/2013; · 4.86 Impact Factor
  • Samia Mora, Julie E Buring, Paul M Ridker
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    ABSTRACT: LDL cholesterol (LDL-C) is the traditional measure of risk attributable to LDL. Non-HDL-cholesterol (NHDL-C), apolipoprotein B (apoB), and LDL particle number (LDL-P) are alternative measures of LDL-related risk. However, the clinical utility of these measures may only become apparent among individuals for whom levels are inconsistent (discordant) with LDL-C. LDL-C was directly measured, NHDL-C was calculated, apoB was measured with immunoassay, and LDL-P with nuclear magnetic resonance spectroscopy among 27,533 healthy women (median follow-up 17.2 years; 1,070 incident coronary events). Participants were grouped by median LDL-C (121 mg/dL) and each of NHDL-C, apoB, and LDL-P. Discordance was defined as LDL-C ≥median and the alternative measure <median, or vice versa. Despite high LDL-C correlations with NHDL-C, apoB, and LDL-P (r=0.910, 0.785, and 0.692, all p<0.0001), prevalence of LDL-C discordance as defined by median cut-points was 11.6%, 18.9%, and 24.3% for NHDL-C, apoB, and LDL-P, respectively. Among women with LDL-C<median, coronary risk was underestimated for women with discordant (≥median) NHDL-C (age-adjusted hazard ratio 2.92, 95% CI 2.33-3.67), apoB (2.48, 2.01-3.07), or LDL-P (2.32, 1.88-2.85), compared to women with concordant levels. Conversely, among women with LDL-C ≥median, risk was overestimated for women with discordant (<median) NHDL-C (0.40, 0.29-0.57), apoB (0.34, 0.26-0.46), or LDL-P (0.42, 0.33-0.53). After multivariable adjustment for potentially mediating factors including HDL cholesterol and triglycerides, coronary risk remained under or overestimated by ≈20-50% for women with discordant levels. For women with discordant LDL-related measures, coronary risk may be under or overestimated when relying on LDL-C alone. ClinicalTrials.gov. Identifier: NCT00000479.
    Circulation 12/2013; · 15.20 Impact Factor
  • Nancy R Cook, Paul M Ridker
    Circulation 12/2013; · 15.20 Impact Factor
  • Paul M Ridker, Nancy R Cook
    The Lancet 11/2013; · 39.06 Impact Factor
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    ABSTRACT: Lipoprotein(a) [Lp(a)] is an LDL-like particle largely independent of known risk factors and predictive of cardiovascular disease (CVD). Statins may offset the risk associated with elevated Lp(a), but it is unknown if Lp(a) is a determinant of residual risk in the setting of low LDL-cholesterol after potent statin therapy. Baseline and on-treatment Lp(a) concentrations were assessed in 9,612 multiethnic JUPITER trial participants before and after random allocation to rosuvastatin 20 mg/day or placebo, with outcomes reported for whites (N=7,746). Lp(a) concentrations (nmol/L) were highest in blacks (median [25(th)-75(th) percentile] 60 [34-100]), then Asians (38 [18-60]), hispanics (24 [11-46]), and whites (23 [10-50]); p<0.001. While the median change in Lp(a) with rosuvastatin and placebo was zero, rosuvastatin nonetheless resulted in a small but statistically significant positive shift in the overall Lp(a) distribution (p<0.0001). Baseline Lp(a) concentrations were associated with incident CVD: adjusted hazard ratio (HR) per 1-SD increment in Ln[Lp(a)] 1.18 (95%CI 1.03 - 1.34; p=0.02). Similarly, on-statin Lp(a) concentrations were associated with residual risk of CVD: adjusted HR 1.27 (95%CI 1.01 - 1.59; p=0.04), which was independent of LDL-cholesterol and other factors. Rosuvastatin significantly reduced incident CVD among participants with baseline Lp(a)≥median (HR 0.62, 0.43-0.90) and Lp(a)<median (HR 0.46, 0.30-0.72), with no evidence of interaction. Similar results were obtained when analyses included non-whites. Among white JUPITER participants treated with potent statin therapy, Lp(a) was a significant determinant of residual risk. The magnitude of relative risk reduction with rosuvastatin was similar among participants with high or low Lp(a). clinicaltrial.gov. Identifier: NCT00239681.
    Circulation 11/2013; · 15.20 Impact Factor
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  • Paul M Ridker
    European Heart Journal 11/2013; · 14.10 Impact Factor
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    ABSTRACT: Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.
    Nature Genetics 10/2013; · 35.21 Impact Factor
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    ABSTRACT: Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P < 5 × 10(-8) for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.
    Nature Genetics 10/2013; · 35.21 Impact Factor
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    ABSTRACT: The association of non-functional variants in CETP with efficacy of statins has been subject of debate. We evaluated whether three functional CETP variants influence statin efficacy. The effect of CETP genotypes on achieved HDL-cholesterol (HDLc), LDL-cholesterol (LDLc) and total cholesterol levels during statin treatment was estimated by meta-analyzing linear regression outcomes of three studies (11,021 individuals). The effect of these SNPs on statin response in protecting against myocardial infarction (MI) was estimated by meta-analysis of statin*SNP interaction terms from logistic regression in five studies (16,570 individuals). The enhancer SNP rs3764261 significantly increased HDLc by 0.02 mmol/L per T allele (p=6E-05), and reduced protection against MI by statins (interaction-OR=1.19 per T allele; p=0.04). Focusing on functional CETP variants, we showed that in carriers of the rs3764261 T variant HDLc increased more during statin treatment, and protection against MI by statins appeared to be reduced, when compared to non-carriers.Clinical Pharmacology & Therapeutics (2013); accepted article preview online 30 September 2013 doi:10.1038/clpt.2013.194.
    Clinical Pharmacology &#38 Therapeutics 09/2013; · 6.85 Impact Factor

Publication Stats

62k Citations
8,432.79 Total Impact Points

Institutions

  • 2012–2013
    • Academisch Medisch Centrum Universiteit van Amsterdam
      • • Academic Medical Center
      • • Department of Cardiology and Cardio-thoracic Surgery
      Amsterdam, North Holland, Netherlands
    • McGill University
      • Department of Epidemiology, Biostatistics and Occupational Health
      Montréal, Quebec, Canada
    • St. Michael's Hospital
      Toronto, Ontario, Canada
    • Soroka Medical Center
      Be'er Sheva`, Southern District, Israel
    • University of Amsterdam
      Amsterdamo, North Holland, Netherlands
  • 2007–2013
    • Beth Israel Deaconess Medical Center
      • • Division of General Medicine and Primary Care
      • • Cardiovascular Epidemiology Research Unit
      Boston, MA, United States
    • Schepens Eye Research Institute
      Boston, Massachusetts, United States
    • Boston Medical Center
      Boston, Massachusetts, United States
  • 2001–2013
    • University of Massachusetts Boston
      Boston, Massachusetts, United States
    • Concordia University–Ann Arbor
      Ann Arbor, Michigan, United States
  • 2000–2013
    • Partners HealthCare
      Boston, Massachusetts, United States
    • University of California, San Francisco
      • Division of Cardiology
      San Francisco, CA, United States
  • 1991–2013
    • Brigham and Women's Hospital
      • • Department of Medicine
      • • Center for Brain Mind Medicine
      • • Division of Preventive Medicine
      • • Division of Cardiovascular Medicine
      Boston, MA, United States
  • 1990–2013
    • Harvard Medical School
      • Department of Medicine
      Boston, Massachusetts, United States
  • 2005–2012
    • Harvard University
      • • Department of Nutrition
      • • Department of Epidemiology
      Cambridge, Massachusetts, United States
    • University of California, Los Angeles
      • Department of Epidemiology
      Los Angeles, CA, United States
    • University of Toronto
      • Division of Cardiac Surgery
      Toronto, Ontario, Canada
  • 2011
    • Memorial Sloan-Kettering Cancer Center
      New York City, New York, United States
    • Vanderbilt University
      • Division of Cardiovascular Medicine
      Nashville, MI, United States
    • University of Alberta
      Edmonton, Alberta, Canada
    • University Medical Center Utrecht
      • Julius Center for Health Sciences and Primary Care
      Utrecht, Utrecht, Netherlands
    • Universitätsspital Basel
      Bâle, Basel-City, Switzerland
    • University of Texas Southwestern Medical Center
      • Department of Internal Medicine
      Dallas, TX, United States
    • AstraZeneca
      Tukholma, Stockholm, Sweden
  • 2009–2011
    • University of Cambridge
      • Department of Public Health and Primary Care
      Cambridge, ENG, United Kingdom
    • Albert Einstein College of Medicine
      New York City, New York, United States
  • 2008–2011
    • University of Texas Medical School
      • Department of Internal Medicine
      Houston, TX, United States
    • Alpert Medical School - Brown University
      • Department of Family Medicine
      Providence, RI, United States
    • Erasmus MC
      Rotterdam, South Holland, Netherlands
    • Karolinska Institutet
      • Institutionen för medicin, Huddinge
      Solna, Stockholm, Sweden
    • Celera
      Alameda, California, United States
  • 2007–2011
    • Northwestern University
      • • Department of Medicine
      • • Department of Preventive Medicine
      Evanston, IL, United States
  • 2010
    • McMaster University
      • Department of Pathology and Molecular Medicine
      Hamilton, Ontario, Canada
    • Duke University Medical Center
      • Division of Cardiology
      Durham, NC, United States
    • National Heart, Lung, and Blood Institute
      Maryland, United States
    • University Hospital Regensburg
      Ratisbon, Bavaria, Germany
    • Universität Ulm
      • Clinic of Internal Medicine II
      Ulm, Baden-Wuerttemberg, Germany
    • University of Michigan
      • Department of Biostatistics
      Ann Arbor, MI, United States
    • University of Chicago
      Chicago, Illinois, United States
  • 2009–2010
    • Broad Institute of MIT and Harvard
      Cambridge, Massachusetts, United States
    • Johns Hopkins University
      • Department of Epidemiology
      Baltimore, MD, United States
    • University of Notre Dame
      South Bend, Indiana, United States
  • 2005–2010
    • University of California, San Diego
      • Department of Family and Preventive Medicine
      San Diego, CA, United States
  • 2001–2010
    • Beverly Hospital, Boston MA
      Beverly, Massachusetts, United States
  • 2006
    • University of Vermont
      • Department of Medicine
      Burlington, VT, United States
  • 2004–2005
    • University of Pittsburgh
      • Department of Epidemiology
      Pittsburgh, PA, United States
    • Texas Heart Institute
      Houston, Texas, United States
  • 2003
    • Mater Misericordiae University Hospital
      Dublin, Leinster, Ireland
  • 2001–2003
    • Boston Children's Hospital
      • Department of Laboratory Medicine
      Boston, MA, United States
  • 2002
    • St. Vincent's Hospital Sydney
      Sydney, New South Wales, Australia
  • 1999
    • Massachusetts Department of Public Health
      Boston, Massachusetts, United States