Martin G Larson

Boston University, Boston, Massachusetts, United States

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Publications (430)4484.75 Total impact

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    ABSTRACT: AimsNon-invasive measures of cardiac mechanical function may have the potential to serve as markers of risk for heart failure; however, limited data exist regarding clinical correlates and heritability of these measures in the community.Methods and resultsWe used speckle-tracking echocardiography to assess LV strain and synchrony in the Framingham Offspring Study (n = 2816; mean age 67 years, 54% women). In multivariable regression analyses, male gender (vs. female, P < 0.001), higher heart rate (P < 0.0001), and presence of cardiovascular disease (P < 0.001) were associated with worse global peak strains across all planes analysed (longitudinal, transverse, circumferential, and radial). Higher diastolic blood pressure and diabetes were associated with worse longitudinal strain (P < 0.01), and greater body mass index was associated with worse radial strain (P = 0.0004). Overall, however, clinical correlates accounted for only 4–19% of the variation in measures of LV mechanical function. Select measures of LV strain were heritable: longitudinal strain (h2 = 16%, P = 0.002), transverse strain (h2 = 15%, P = 0.006), and circumferential strain (h2 = 30%, P < 0.0001). Furthermore, in a subset of 14437 participants with parental data available, parental heart failure was associated with worse circumferential strain in the offspring free of heart failure (P = 0.01).Conclusions Our investigation in a large community-based sample identified heritablity and clinical correlates of LV mechanical function, and highlighted an association of parental heart failure with worse global circumferential strain in offspring.
    European Journal of Heart Failure 12/2014; · 5.25 Impact Factor
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    ABSTRACT: The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD.
    Nature Genetics 12/2014; · 35.21 Impact Factor
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    ABSTRACT: Whether low diastolic blood pressure (DBP) is a risk factor for recurrent cardiovascular disease (CVD) events in persons with isolated systolic hypertension is controversial. We studied 791 individuals (mean age 75 years, 47% female, mean follow-up time: 8±6 years) with DBP <70 (n=225) versus 70 to 89 mm Hg (n=566) after initial CVD events in the original and offspring cohorts of the Framingham Heart Study. Recurrent CVD events occurred in 153 (68%) participants with lower DBP and 271 (48%) with higher DBP (P<0.0001). Risk of recurrent CVD events in risk factor-adjusted Cox regression was higher in those with DBP <70 mm Hg versus DBP 70 to 89 mm Hg in both treated (hazard ratio, 5.1 [95% confidence interval: 3.8-6.9] P<0.0001) and untreated individuals (hazard ratio, 11.7 [95% confidence interval: 6.5-21.1] P<0.0001; treatment interaction: P=0.71). Individually, coronary heart disease, heart failure, and stroke recurrent events were more likely with DBP <70 mm Hg versus 70 to 89 mm Hg (P<0.0001). To examine for an effect of wide pulse pressure on excess risk associated with low DBP, we defined 4 binary groupings of pulse pressure (≥68 versus <68 mm Hg) and DBP (<70 versus 70-89 mm Hg). CVD incidence rates were higher only in the group with pulse pressure ≥68 and DBP <70 mm Hg (76% versus 46%-54%; P<0.001). Persons with isolated systolic hypertension and prior CVD events have increased risk for recurrent CVD events in the presence of DBP <70 mm Hg versus DBP 70 to 89 mm Hg, whether treated or untreated, supporting wide pulse pressure as an important risk modifier for the adverse effect of low DBP. © 2014 American Heart Association, Inc.
    Hypertension 11/2014; · 6.87 Impact Factor
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    ABSTRACT: -Elevated blood pressure is the leading modifiable risk factor for cardiovascular disease (CVD) and premature death. The blood pressure waveform consists of discrete hemodynamic components, derived from measured central pressure and flow, which may contribute separately to risk for an adverse outcome. However, pressure-flow measures have not been studied in a large, community-based sample. -We used proportional hazards models to examine association of incident CVD with forward pressure wave amplitude, mean arterial pressure, and global reflection coefficient derived from wave separation analysis and echocardiography in 2492 participants (mean age 66 ± 9 years, 56% women) in the Framingham Heart Study. During follow up (0.04 - 6.8 years), 149 participants (6%) had a CVD event. In multivariable models adjusting for age, sex, antihypertensive therapy, body mass index, heart rate, total and high density lipoprotein cholesterol concentrations, smoking, and presence of diabetes, forward pressure wave amplitude (HR=1.40; 95% CI: 1.16, 1.67; P=0.0003) was associated with incident CVD whereas mean arterial pressure (HR=1.10; 95% CI: 0.94, 1.29; P=0.25) and global wave reflection (HR=0.93; 95% CI: 0.78, 1.12; P=0.58) were not. After adding systolic blood pressure and carotid-femoral pulse wave velocity to the model, forward pressure wave amplitude persisted as a correlate of events (HR=1.33; 95% CI, 1.05, 1.68; P=0.02). -Higher forward pressure wave amplitude (a measure of proximal aortic geometry and stiffness) was whereas mean arterial pressure and relative wave reflection (correlates of resistance vessel structure and function) were not associated with increased risk for incident CVD.
    Circulation 11/2014; · 15.20 Impact Factor
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    ABSTRACT: Heritability measures the proportion of phenotypic variation attributable to genetic factors. In addition to a shared nuclear genetic component, a number of additional variance components, such as spousal correlation, sibship, household and maternal effects, may have strong contributions to inter-individual phenotype variation. In humans, the confounding effects of these components on heritability have not been studied thoroughly. We sought to obtain unbiased heritability estimates for complex traits in the presence of multiple variance components and also to estimate the contributions of these variance components to complex traits. We compared regression and variance component methods to estimate heritability in simulations when additional variance components existed. We then revisited heritability for several traits in Framingham Heart Study (FHS) participants. Using simulations, we found that failure to account for or misclassification of necessary variance components yielded biased heritability estimates. The direction and magnitude of the bias varied depending on a variance structure and an estimation method. Using the best fitted models to account for necessary variance components, we found that heritability estimates for most FHS traits were overestimated, ranging from 4 to 47 %, when we compared models that considered necessary variance components to models that only considered familial relationships. Spousal correlation explained 14-36 % of phenotypic variation in several anthropometric and lifestyle traits. Maternal and sibling effects also contributed to phenotypic variation, ranging from 3 to 5 % and 4 to 7 %, respectively, in several anthropometric and metabolic traits. Our findings may explain, in part, the missing heritability for some traits.
    Human genetics. 11/2014;
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    ABSTRACT: -Knowledge of mitral valve prolapse (MVP) inheritance is based on pedigree observation and M-mode echocardiography. The extent of familial clustering of MVP among unselected individuals in the community based on current, more specific echocardiographic criteria is unknown. In addition, the importance of non-diagnostic MVP morphologies (NDM; first described in large pedigrees) has not been investigated in the general population. We hypothesized that parental MVP and NDM increase the risk of offspring MVP.
    Circulation 10/2014; · 15.20 Impact Factor
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    ABSTRACT: Background Heart failure is an established risk factor for poor outcomes in patients undergoing non-cardiac surgery, yet risk stratification remains a clinical challenge. We developed an index for 30-day mortality risk prediction in this particular group.Methods and resultsAll individuals with heart failure undergoing non-cardiac surgery between October 23 2004 and October 31 2011 were included from Danish administrative registers (n = 16 827). In total, 1787 (10.6%) died within 30 days. In a simple risk score based on the variables from the revised cardiac risk index, plus age, gender, acute surgery, and body mass index category the following variables predicted mortality (points): male gender (1), age 56–65 years (2), age 66–75 years (4), age 76–85 years (5), or age >85 years (7), being underweight (4), normal weight (3), or overweight (1), undergoing acute surgery (5), undergoing high-risk procedures (intra-thoracic, intra-abdominal, or suprainguinal aortic) (3), having renal disease (1), cerebrovascular disease (1), and use of insulin (1). The c-statistic was 0.79 and calibration was good. Mortality risk ranged from <2% for a score <5 to >50% for a score ≥20. Internal validation by bootstrapping (1000 re-samples) provided c-statistic of 0.79. A more complex risk score based on stepwise logistic regression including 24 variables at P < 0.05 performed only slightly better, c-statistic = 0.81, but was limited in use by its complexity.Conclusions For patients with heart failure, this simple index can accurately identify those at low risk for perioperative mortality.
    European Journal of Heart Failure 10/2014; · 5.25 Impact Factor
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    ABSTRACT: Biomarkers of cardiovascular stress have been associated with incident cardiovascular outcomes. Their relations with measures of subclinical atherosclerosis, as assessed by carotid intima-media thickness, have not been well described.
    Clinical chemistry. 09/2014;
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    ABSTRACT: This study sought to evaluate pattern and clinical correlates of change in left ventricular (LV) geometry over a 4-year period in the community; it also assessed whether the pattern of change in LV geometry over 4 years predicts incident cardiovascular disease (CVD), including myocardial infarction, heart failure, and cardiovascular death, during an additional subsequent follow-up period.
    JACC. Cardiovascular imaging. 08/2014;
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    ABSTRACT: Osteoprotegerin (OPG) is involved in bone homeostasis and tumor cell survival. Circulating OPG levels are also important biomarkers of various clinical traits, such as cancers and atherosclerosis. OPG levels were measured in serum or in plasma. In a meta-analysis of genome-wide association studies in up to 10,336 individuals from European and Asian origin, we discovered that variants >100 Kb upstream of the TNFRSF11B gene encoding OPG and another new locus on chromosome 17q11.2 were significantly associated with OPG variation. We also identified a suggestive locus on chromosome 14q21.2 associated with the trait. Moreover, we estimated that over half of the heritability of OPG levels could be explained by all variants examined in our study. Our findings provide further insight into the genetic regulation of circulating OPG levels.
    Human Molecular Genetics 07/2014; · 7.69 Impact Factor
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    ABSTRACT: CXCL12 encodes stromal cell-derived factor 1 α (SDF-1), which binds to the receptor encoded by CXCR4. Variation at the CXCL12 locus is associated with coronary artery disease and endothelial progenitor cell numbers, whereas variation at the CXCR4 locus is associated with leukocyte telomere length, which has been shown to be associated with coronary artery disease. Therefore, we examined the relationships of plasma SDF-1 levels to cardiovascular disease (CVD)-related outcomes, risk factors, leukocyte telomere length, and endothelial progenitor cells.
    Arteriosclerosis Thrombosis and Vascular Biology 07/2014; · 6.34 Impact Factor
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    ABSTRACT: B-type natriuretic peptide (BNP) and C-reactive protein (CRP) predict atrial fibrillation (AF) risk. However, their risk stratification abilities in the broad community remain uncertain. We sought to improve risk stratification for AF using biomarker information.
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    ABSTRACT: Blood pressure (BP) is a heritable, quantitative trait with intraindividual variability and susceptibility to measurement error. Genetic studies of BP generally use single-visit measurements and thus cannot remove variability occurring over months or years. We leveraged the idea that averaging BP measured across time would improve phenotypic accuracy and thereby increase statistical power to detect genetic associations. We studied systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP) averaged over multiple years in 46,629 individuals of European ancestry. We identified 39 trait-variant associations across 19 independent loci (p < 5 × 10(-8)); five associations (in four loci) uniquely identified by our LTA analyses included those of SBP and MAP at 2p23 (rs1275988, near KCNK3), DBP at 2q11.2 (rs7599598, in FER1L5), and PP at 6p21 (rs10948071, near CRIP3) and 7p13 (rs2949837, near IGFBP3). Replication analyses conducted in cohorts with single-visit BP data showed positive replication of associations and a nominal association (p < 0.05). We estimated a 20% gain in statistical power with long-term average (LTA) as compared to single-visit BP association studies. Using LTA analysis, we identified genetic loci influencing BP. LTA might be one way of increasing the power of genetic associations for continuous traits in extant samples for other phenotypes that are measured serially over time.
    The American Journal of Human Genetics 06/2014; · 11.20 Impact Factor
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    ABSTRACT: Although age-dependent effects on blood pressure (BP) have been reported, they have not been systematically investigated in large-scale genome-wide association studies (GWASs). We leveraged the infrastructure of three well-established consortia (CHARGE, GBPgen, and ICBP) and a nonstandard approach (age stratification and metaregression) to conduct a genome-wide search of common variants with age-dependent effects on systolic (SBP), diastolic (DBP), mean arterial (MAP), and pulse (PP) pressure. In a two-staged design using 99,241 individuals of European ancestry, we identified 20 genome-wide significant (p ≤ 5 × 10(-8)) loci by using joint tests of the SNP main effect and SNP-age interaction. Nine of the significant loci demonstrated nominal evidence of age-dependent effects on BP by tests of the interactions alone. Index SNPs in the EHBP1L1 (DBP and MAP), CASZ1 (SBP and MAP), and GOSR2 (PP) loci exhibited the largest age interactions, with opposite directions of effect in the young versus the old. The changes in the genetic effects over time were small but nonnegligible (up to 1.58 mm Hg over 60 years). The EHBP1L1 locus was discovered through gene-age interactions only in whites but had DBP main effects replicated (p = 8.3 × 10(-4)) in 8,682 Asians from Singapore, indicating potential interethnic heterogeneity. A secondary analysis revealed 22 loci with evidence of age-specific effects (e.g., only in 20 to 29-year-olds). Age can be used to select samples with larger genetic effect sizes and more homogenous phenotypes, which may increase statistical power. Age-dependent effects identified through novel statistical approaches can provide insight into the biology and temporal regulation underlying BP associations.
    The American Journal of Human Genetics 06/2014; · 11.20 Impact Factor
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    ABSTRACT: Novel biomarkers are being investigated to identify patients with kidney disease. We measured a panel of 13 urinary biomarkers in participants from the Offspring Cohort of the Framingham Heart Study. Using an Affymetrix chip with imputation to 2.5 M single-nucleotide polymorphisms (SNPs), we conducted a GWAS of these biomarkers (n=2640) followed by exonic sequencing and genotyping. Functional studies in zebrafish were used to investigate histologic correlation with renal function. Across all 13 biomarkers, there were 97 significant SNPs at three loci. Lead SNPs at each locus were rs6555820 (P=6.7×10(-49); minor allele frequency [MAF]=0.49) in HAVCR1 (associated with kidney injury molecule-1), rs7565788 (P=2.15×10(-16); MAF=0.22) in LRP2 (associated with trefoil factor 3 [TFF3]), and rs11048230 (P=4.77×10(-8); MAF=0.10) in an intergenic region near RASSF8 (associated with vascular endothelial growth factor). Validation in the CKDGen Consortium (n=67,093) showed that only rs7565788 at LRP2, which encodes megalin, was associated with eGFR (P=0.003). Sequencing of exons 16-72 of LRP2 in 200 unrelated individuals at extremes of urinary TFF3 levels identified 197 variants (152 rare; MAF<0.05), 31 of which (27 rare) were nonsynonymous. In aggregate testing, rare variants were associated with urinary TFF3 levels (P=0.003), and the lead GWAS signal was not explained by these variants. Knockdown of LRP2 in zebrafish did not alter the renal phenotype in static or kidney injury models. In conclusion, this study revealed common variants associated with urinary levels of TFF3, kidney injury molecule-1, and vascular endothelial growth factor and identified a cluster of rare variants independently associated with TFF3.
    Journal of the American Society of Nephrology : JASN. 05/2014;
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    ABSTRACT: Central pressure augmentation is associated with greater backward wave amplitude and shorter transit time and is higher in women for reasons only partially elucidated. Augmentation also is affected by left ventricular function and shapes of the forward and backward waves. The goal of this study was to examine the relative contributions of forward and backward wave morphology to central pressure augmentation in men and women. From noninvasive measurements of central pressure and flow in 7437 participants (4036 women) aged from 19 to 90 years (mean age, 51 years), we calculated several variables: augmentation index, backward wave arrival time, reflection factor, forward wave amplitude, forward wave peak width, and slope of the backward wave upstroke. Linear regression models for augmentation index, adjusted for height and heart rate, demonstrated nonlinear relations with age (age: B=4.6±0.1%; P<0.001; age(2): B=-4.2±0.1%; P<0.001) and higher augmentation in women (B=4.5±0.4%; P<0.001; model R(2)=0.35). Addition of reflection factor and backward wave arrival time improved model fit (R(2)=0.62) and reduced the age coefficients: age (B=2.3±0.1%; P<0.001) and age(2) (B=-2.2±0.1%; P<0.001). Addition of width of forward wave peak, slope of backward wave upstroke, and forward wave amplitude further improved model fit (R(2)=0.75) and attenuated the sex coefficient (B=1.9±0.2%; P<0.001). Thus, shape and amplitude of the forward wave may be important correlates of augmentation index, and part of the sex difference in augmentation index may be explained by forward and backward wave morphology.
    Hypertension 05/2014; · 6.87 Impact Factor
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    ABSTRACT: Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation.
    Molecular Genetics and Metabolism 05/2014; · 2.83 Impact Factor
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    ABSTRACT: Galectin 3 (Gal-3) is a potential mediator of cardiac fibrosis, and Gal-3 concentrations predict incident heart failure. The same mechanisms that lead to cardiac fibrosis in heart failure may influence development of atrial fibrosis and atrial fibrillation (AF). We examined the association of Gal-3 and incident AF in the community. Plasma Gal-3 concentrations were measured in 3,306 participants of the Framingham Offspring cohort who attended the sixth examination cycle (1995-1998, mean age 58 years, 54% women). Cox proportional hazards regression models were used to assess the association of baseline Gal-3 concentrations and incident AF. Over a median follow-up period of 10 years, 250 participants developed incident AF. Crude incidence rates of AF by increasing sex-specific Gal-3 quartiles were 3.7%, 5.9%, 9.1%, and 11.5% (log-rank test P < .0001). In age- and sex-adjusted analyses, each 1-SD increase in loge-Gal-3 was associated with a 19% increased hazard of incident AF (hazard ratio 1.19, 95% CI 1.05-1.36, P = .009). This association was not significant after adjustment for traditional clinical AF risk factors (hazard ratio 1.12, 95% CI 0.98-1.28, P = .10). Higher circulating Gal-3 concentrations were associated with increased risk of developing AF over the subsequent 10 years in age- and sex-adjusted analyses but not after accounting for other traditional clinical AF risk factors. Our results do not support a role for Gal-3 in AF risk prediction. Further studies are needed to evaluate whether Gal-3 plays a role in the development of AF substrate similar to HF.
    American heart journal 05/2014; 167(5):729-734.e1. · 4.65 Impact Factor
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    ABSTRACT: To examine the relation of endothelial microparticles (EMPs) with cardiometabolic risk in the community. Circulating EMPs are small membrane vesicles released after endothelial cell injury. Endothelial microparticles are reportedly increased among individuals with a high burden of cardiovascular risk factors. However, prior investigations have been limited to small, highly selected samples. We studied 844 individuals without a history of cardiovascular disease in the Framingham Offspring cohort (mean age 66 ± 9 years, 57% women). We used standardized flow cytometry methods to identify and quantify circulating CD144+ and CD31+/CD41- EMPs. We then used multivariable regression analyses to investigate the relations of EMP phenotypes with cardiovascular and metabolic risk factors. In multivariable analyses, the following cardiovascular risk factors were associated with one or more of the circulating EMP populations: hypertension (P = 0.025 for CD144+,), elevated triglycerides (P = 0.002 for CD144+, P < 0.0001 for CD31+/CD41-), and metabolic syndrome (P < 0.0001 for CD144+,). Overall, each tertile increase in the Framingham risk score corresponded to a 9% increase in log-CD31+/CD41- EMPs (P = 0.022). Furthermore, the presence of hypertriglyceridaemic waist status was associated with 38% higher levels of CD144+ EMPs (P < 0.0001) and 46% higher levels of CD31+/CD41- EMPs (P < 0.0001). In a large community-based sample, circulating EMP levels were associated with the presence of cardiometabolic risk factors, particularly dyslipidaemia. These data underscore the potential influence of high-risk metabolic profiles on endothelial integrity.
    European Heart Journal 04/2014; · 14.72 Impact Factor
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    ABSTRACT: Incorporation of novel plasma protein biomarkers may improve current models for prediction of atherosclerotic cardiovascular disease (ASCVD) risk. We used discovery mass spectrometry (MS) to determine plasma concentrations of 861 proteins in 135 myocardial infarction (MI) cases and 135 matched controls. Then, we measured 59 markers by targeted MS in 336 ASCVD case-control pairs. Associations with MI or ASCVD were tested in single-marker and multiple-marker analyses adjusted for established ASCVD risk factors. Twelve single markers from discovery MS were associated with MI incidence (at P<0.01), adjusting for clinical risk factors. Seven proteins in aggregate (cyclophilin A, CD5 antigen-like, cell-surface glycoprotein MUC18, collagen-α 1 [XVIII] chain, salivary α-amylase 1, C-reactive protein, and multimerin-2) were highly associated with MI (P<0.0001) and significantly improved its prediction compared with a model with clinical risk factors alone (C-statistic of 0.71 versus 0.84). Through targeted MS, 12 single proteins were predictors of ASCVD (at P<0.05) after adjusting for established risk factors. In multiple-marker analyses, 4 proteins in combination (α-1-acid glycoprotein 1, paraoxonase 1, tetranectin, and CD5 antigen-like) predicted incident ASCVD (P<0.0001) and moderately improved the C-statistic from the model with clinical covariates alone (C-statistic of 0.69 versus 0.73). Proteomics profiling identified single- and multiple-marker protein panels that are associated with new-onset ASCVD and may lead to a better understanding of underlying disease mechanisms. Our findings include many novel protein biomarkers that, if externally validated, may improve risk assessment for MI and ASCVD.
    Arteriosclerosis Thrombosis and Vascular Biology 02/2014; · 6.34 Impact Factor

Publication Stats

35k Citations
4,484.75 Total Impact Points


  • 2005–2014
    • Boston University
      • • Department of Medicine
      • • Department of Biostatistics
      Boston, Massachusetts, United States
    • National Institute of Allergy and Infectious Diseases
      Maryland, United States
  • 1993–2014
    • National Heart, Lung, and Blood Institute
      • Division of Cardiovascular Sciences (DCVS)
      Maryland, United States
  • 2013
    • University of Minnesota Duluth
      Duluth, Minnesota, United States
  • 2006–2013
    • Partners HealthCare
      Boston, Massachusetts, United States
    • Harvard University
      • Department of Society, Human Development, and Health
      Boston, MA, United States
    • Massachusetts Institute of Technology
      Cambridge, Massachusetts, United States
  • 2003–2013
    • Whitaker Wellness Institute
      Newport Beach, California, United States
  • 2002–2013
    • Massachusetts General Hospital
      • • Center for Regenerative Medicine
      • • Division of Cardiology
      • • Division of Nephrology
      • • Center for Human Genetic Research
      • • Department of Medicine
      Boston, MA, United States
  • 2012
    • Scuola Superiore Sant'Anna
      Pisa, Tuscany, Italy
    • University of Sioux Falls
      Sioux Falls, South Dakota, United States
  • 2006–2012
    • Harvard Medical School
      • Department of Medicine
      Boston, Massachusetts, United States
  • 2011
    • Tufts University
      • Tufts Center for Conservation Medicine
      Medford, MA, United States
    • National University Health System
  • 2008–2011
    • University of Massachusetts Boston
      Boston, Massachusetts, United States
    • Tufts Medical Center
      Boston, Massachusetts, United States
    • Johns Hopkins University
      • Welch Center for Prevention, Epidemiology, and Clinical Research
      Baltimore, MD, United States
    • University of Massachusetts Medical School
      Worcester, Massachusetts, United States
  • 2010
    • University of Texas Health Science Center at Houston
      • Human Genetics Center
      Houston, TX, United States
    • University of Washington Seattle
      • Department of Epidemiology
      Seattle, WA, United States
    • Erasmus MC
      • Department of Epidemiology
      Rotterdam, South Holland, Netherlands
  • 2008–2010
    • University of Toronto
      • Institute for Clinical Evaluative Sciences
      Toronto, Ontario, Canada
  • 1997–2009
    • University of California, Irvine
      • Department of Medicine
      Irvine, California, United States
  • 1994–2008
    • Beth Israel Deaconess Medical Center
      • • Division of Cardiovascular Medicine
      • • Department of Medicine
      Boston, MA, United States
    • Lahey Hospital and Medical Center
      Burlington, Massachusetts, United States
  • 1996–2007
    • Brigham and Women's Hospital
      • Department of Medicine
      Boston, MA, United States
  • 2004–2006
    • Northwestern University
      • Department of Preventive Medicine
      Evanston, IL, United States
    • Technion - Israel Institute of Technology
      H̱efa, Haifa District, Israel
  • 2003–2006
    • Beverly Hospital, Boston MA
      Beverly, Massachusetts, United States
  • 1999–2004
    • National Institutes of Health
      Maryland, United States
  • 1996–1997
    • Kansai Medical University
      Moriguchi, Ōsaka, Japan
  • 1994–1996
    • Cleveland Clinic
      • Department of Cardiology
      Cleveland, OH, United States
  • 1995
    • Beth Israel Medical Center
      • Department of Medicine
      New York City, New York, United States
    • Yale-New Haven Hospital
      New Haven, Connecticut, United States