clinical and genetic correlates of circulating angiopoietin-2...

Clinical and genetic correlates of Circulating Angiopoietin-2 and soluble Tie-2 in the Community

Running title: Lieb et al; Correlates of Angiopoietin-2 and soluble Tie-2

Wolfgang Lieb*, MD; Justin Zachariah*, MD; Vanessa Xanthakis, MS; Radwan Safa,

MS; Ming-Huei Chen, PhD; Lisa M. Sullivan, PhD; Martin G. Larson, ScD; Holly M.

Smith, MS; Qiong Yang, PhD; Gary F. Mitchell, MD; Joseph A. Vita, MD; Douglas B.

Sawyer, MD; Ramachandran S. Vasan, MD

Framingham Heart Study, Framingham, MA (WL, JZ, EJB, MGL, RSV); Department of

Cardiology, Children's Hospital Boston, Department of Pediatrics, Harvard Medical

School, Boston, MA (JZ); Cardiovascular Division, Vanderbilt University, Nashville, TN

(HMS, DBS), Cardiovascular Engineering Inc, Norwood, MA (GFM); Departments of

Biostatistics (VX, LMS, QY) and Epidemiology (EJB), Boston University School of

Public Health; Division of Graduate Medical Sciences (RS); Department of Mathematics

(MGL); Department of Neurology (MHC), School of Medicine (EJB, JAV, RSV);

Section of Preventive Medicine and Epidemiology (RSV), Boston University, Boston,

MA

*denotes equal contribution

Address for correspondence: Ramachandran S. Vasan, MD Framingham Heart Study 73 Mount Wayte Ave, Framingham, MA 01702–5803 Tel. 508-935-3450 Fax: 508-626-1262 E-mail: [email protected]

Journal Subject Code: [8] Epidemiology; [129] Angiogenesis; [135] Risk Factors; [96] Mechanism of atherosclerosis/growth factors

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Abstract:

Background. Experimental studies suggest that endothelial growth factors play an

important role in angiogenesis and vascular remodeling. The clinical and genetic

correlates of circulating angiopoietin-2 (Ang-2) and its soluble receptor/regulator Tie-2

(sTie-2) have not been determined in a community-based sample.

Methods and Results. Serum Ang-2 and sTie-2 were assayed in 3778 Framingham

Third Generation cohort participants (mean age 40±9 years, 53% women). Clinical

correlates and heritability of both biomarkers were assessed using generalized estimating

equations and variance-component analyses. Ang-2 levels were higher and sTie-2 levels

lower in women as compared to men. Ang-2 was positively related to age, smoking,

systolic blood pressure (BP), hypertension treatment and diabetes (p<0.05 for all) but was

inversely associated with total cholesterol and diastolic BP (p<0.0001 for both). Soluble

Tie-2 was positively associated with body mass index, diabetes and triglycerides, but

inversely related to age, alcohol consumption and glomerular filtration rate (p<0.05 for

all). Both Ang-2 and sTie-2 were higher in participants with metabolic syndrome

(p<0.005), with stronger associations of Ang-2 with BP traits and of sTie-2 with obesity-

dyslipidemia components. Heritability estimates for Ang-2 and sTie-2 were 27% and

56%, respectively (p<0.0001). A region on chromosome 9 was significantly linked to

circulating sTie-2 levels (LOD score 8.31).

Conclusion. Circulating levels of Ang-2 and sTie-2 are heritable traits that are associated

with cardiovascular (CVD) risk factors including the metabolic syndrome. These

observations are consistent with the notion that angiogenesis and vascular remodeling are

in part determined by genetic influences, and associated with metabolic risk factors.

Keywords: Angiopoietins, vascular remodeling, heritability, metabolic syndrome, CVD risk factors

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Introduction

Vascular remodeling, a process characterized by progressive structural and functional

changes in the vessel wall, is an adaptive response of the vessel to hemodynamic and

biochemical stressors and a precursor of overt cardiovascular disease (CVD).

Understanding the biological basis of vascular remodeling is, therefore, critical for

preventing CVD. The endothelium plays a central role in vascular remodeling, in part via

endothelium-derived signaling proteins and receptors that mediate intercellular

communication.1,2 Angiopoietins are an important group of endothelial growth factors

that modulate angiogenesis,3 as well as vascular remodeling.4 While the various

angiopoietins bind to the same endothelial tyrosine kinase receptor, Tie-2 (TEK), they

seem to have distinct, context-dependent biological functions. Binding of angiopoietin-1

(Ang-1) to Tie-2 leads to prolonged endothelial cell survival, maintains the endothelium

in a quiescent state,5 and supports the maturation of new vessels.6 Angiopoietin-2 (Ang-

2), on the other hand, functions as a competitor inhibitor of Ang-1 for Tie-2 binding,2

thereby inhibiting Ang-1/Tie-2 signalling.7 Preformed Ang-2 in the Wiebel Palade bodies

in endothelial cells is readily available for rapid release and primes the endothelium to

respond to stressors. Ang-2 also promotes vascular endothelial growth factor (VEGF)-

induced neovascularization. Recently, a soluble form of the Tie-2 receptor (sTie-2) has

been described.8 SolubleTie-2 downregulates endothelial Ang/Tie-2 signalling by binding

to circulating angiopoietins and reducing the pool of free angiopoietins. Thus, a complex

interplay of Ang-1, Ang-2, Tie-2, sTie-2, VEGF, and other pro- or anti-angiogenic

factors determines progression of angiogenesis and vascular remodeling.

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In smaller clinical studies, altered circulating concentrations of Ang-2 and/or Tie-2

were observed in patients with peripheral artery disease,9 acute coronary syndrome,10 and

heart failure11 and reported to predict incident myocardial infarction.12 Furthermore, level

of these biomarkers were associated with measures of subclinical disease13 and target

organ damage in hypertension.14 While these preliminary data suggest an important role

for angiopoietins along the CVD continuum, the clinical and genetic correlates of Ang-2

and the soluble form of its receptor Tie-2 have not been evaluated in a large community-

based sample. We hypothesize that circulating Ang-2 and Tie-2 are associated with

traditional CVD and metabolic risk factors and with target organ damage (ECG-left

ventricular hypertrophy, LVH); and are heritable traits influenced by select genetic loci.

Methods

In 2002, the Third Generation cohort of the Framingham Heart Study was initiated and a

total of 4,095 participants with at least one parent in the Offspring cohort were included.

The data for the present analyses were obtained at the first examination cycle.15

Participants were comprehensively evaluated, including anthropometric measurements,

biochemical assessment for traditional CVD risk factors, and a medical history and

physical examination by a Heart Study physician. The present analyses included only

Third Generation cohort participants. Overall, 317 participants were excluded for the

following reasons: prevalent CVD (n=66), serum creatinine >2 mg/dl (n=1), missing data

on Ang-2 or Tie-2 (n=126), missing covariates (n=124). After exclusions, 3778

participants remained eligible for the present analyses. Written informed consent was

provided by all participants and the Institutional Review Board at the Boston University

Medical Centre approved the study protocol.

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Biomarker measurement

Blood was drawn in the early morning after a 12 hour fast. Blood samples were

immediately centrifuged and stored at -80 C until biomarkers were assayed. Circulating

concentrations of free Ang-2 and sTie-2 in serum were assayed using commercial assays

(R&D Inc.). The average inter-assay coefficients of variation were 5.7% for Ang-2 and

3.2% for sTie-2. Vascular endothelial growth factor A (VEGF), its soluble receptor sFlt-

1, and hepatocyte growth factor (HGF) were assayed as previously reported.16

Electrocardiography

Presence of electrocardiographically determined left ventricular hypertrophy (LVH) was

determined based on a standard 12-lead ECG when at least one of the following criteria

were fulfilled:17 Precordial RV5 or RV6 + SV1 or SV2 3.5 mV; R wave in AVL >11

mV; R wave in left precordial leads 2.5 mV; S wave in right precordial leads 2.5 mV;

R wave in lead I + S wave in lead III 2.5 mV.

Statistical analyses

Clinical correlates

Ang-2 and sTie-2 were natural-logarithmically transformed to normalize their skewed

distributions. Significant correlates of Ang-2 and sTie-2 (each biomarker considered

separately) were identified using forward stepwise selection procedures (p 0.1 for model

entry), from a set of candidate variables (age, sex, systolic and diastolic blood pressure

[BP], antihypertensive medication, diabetes, total cholesterol, high density lipoprotein

[HDL] cholesterol, triglycerides, smoking, body mass index [BMI], alcohol consumption,

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estimated glomerular filtration rate [eGFR]). Then, we used generalized estimating

equations (GEE; using the Compound Symmetry Correlation Matrix) to account for

familial correlation within our sample. In secondary analyses, we replaced each

significant continuous predictor variable (except for age) with a categorical counterpart

frequently used in clinical settings: hypertension (BP 140/90 mmHg or antihypertensive

medication); obesity (BMI 30 kg/m2); abdominal obesity (waist circumference 102 cm

in men or 88 cm in women); low HDL cholesterol (<40 mg/dL in men or <50 mg/dL in

women); high triglycerides ( 150 mg/dL or lipid-lowering medication) and the metabolic

syndrome (defined as the presence of least 3 of the following features: increased waist

circumference [see above]; elevated BP [ 130/85 mmHg, or anti-hypertensive treatment];

hyperglycaemia [fasting glucose 100 mg/dL or treatment for elevated glucose];

hypertriglyceridaemia [ 150 mg/dL or lipid-lowering treatment]; low HDL cholesterol

[as defined above]).18

We evaluated the pair-wise correlations of Ang-2, and sTie-2 with other vascular growth

factors measured in this cohort, i.e., VEGF, sFlt-1 and HGF16 using Pearson’s correlation

coefficients adjusting for age and sex.

Association of biomarker concentrations with ECG-LVH

We related Ang-2 and sTie-2 concentrations to LVH using logistic regression models,

adjusting for age and sex. The multivariable models were additionally adjusted for all

covariates that were significantly related to the respective biomarker (Ang-2 or sTie-2) in

the previous analyses (clinical correlates).

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Genetic correlates

Heritability and Linkage analyses

Variance-component models as implemented in the software package SOLAR were

used to estimate heritabilities for log-biomarker levels using two models; model 1

adjusted for age and sex, while model 2 additionally adjusted for all significant clinical

correlates of the respective biomarker that were identified in the previous analyses

detailed above.

Data from 3768 (10 participants of our sample lacked genotypic data) individuals

belonging 1796 core families (supplemental table 1) which constitute 805 pedigrees

were used for a multipoint linkage analysis for Ang-2 and sTie-2 with the SOLAR

software. The number of core families was larger than the number of pedigrees because

members of some core families were second-degree relatives and therefore represent the

same pedigree. Adjustment was performed for age and sex only (model 1) and

additionally for those covariates that were significantly associated with Ang-2 and sTie-2

in our previous analyses (model 2). The genetic data set included 687 microsatellite

markers. To quantify the evidence for linkage, the logarithm (base 10) of the likelihood

ratio for linkage was calculated.

Results

The clinical and biochemical characteristics of our sample are provided in Table 1.

Our sample was comprised of young–to-middle-aged and included slightly more women

than men. Information about the number of siblings per family is provided in

supplemental Table 1. Circulating concentrations of Ang-2 and sTie-2 were not

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correlated (r=0.004; p=0.3 in age- and sex-adjusted models). Pair-wise age- and sex-

adjusted correlations between Ang-2, sTie-2, VEGF, sFlt-1, and HGF are provided in

supplemental Table 2. Overall, correlations between endothelial biomarker

concentrations were rather low; modest associations were observed between Ang-2 and

HGF and sFlt-1, and between sTie-2 and VEGF and HGF.

Clinical correlates of Angiopoietin-2 and soluble Tie-2

Ang-2 levels were higher in women as compared to men and were positively

associated with age, smoking, antihypertensive medication, systolic BP and diabetes

(Table 2). Inverse associations were observed with diastolic BP and total cholesterol

(Table 2). The multivariable model explained 6.8% of the inter-individual variation in

circulating Ang-2 concentrations. We observed a positive association with hypertension

when we replaced systolic and diastolic BP with the binary variable (ß: 0.054; 95% CI,

0.016 to 0.092; p=0.005). Noting the divergent directions of the associations with systolic

and diastolic BP, we substituted the two measures with pulse pressure and observed a

positive correlation between Ang-2 and pulse pressure (ß: 0.028; 95% CI, 0.008 to 0.037

per 1 SD-increment; p=0.002). Replacing all significant continuous traits that are part of

the definition of the metabolic syndrome, Ang-2 was also positively associated with the

metabolic syndrome as a binary trait (ß: 0.048; 95% CI, 0.015 to 0.082; p=0.0047). Ang-

2 levels were also related to ECG-LVH (prevalence 8.1% in our sample; OR: 1.02; 95%

CI, 1.01 to 1.04; p=0.011 per one-unit increment in log-Ang-2 levels (a 2.72-fold [e1]-

fold increment in Ang-2 in natural units).

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Circulating sTie-2 concentrations were higher in men than women and were positively

related to BMI, diabetes and triglycerides. Inverse associations with age, eGFR and

alcohol consumption were noted. The multivariable model explained 3.8% of the

interindividual variation of circulating sTie-2 concentrations. Replacing BMI in the

multivariable model with the following traits revealed positive associations: obesity

(ß:0.046; 95% CI, 0.025 to 0.068; p<0.0001; indicating about 5% [e0.046] higher Tie-2

levels in obese as compared to non-obese participants), waist circumference (ß: 0.016;

95% CI, 0.005 to 0.026; p=0.004), abdominal obesity (ß: 0.029; 95% CI, 0.01 to 0.049;

p= 0.003) and the metabolic syndrome (ß: 0.047; 95% CI, 0.025 to 0.068; p<0.0001).

Soluble Tie-2 concentrations were not significantly associated with

electrocardiographically determined LVH (OR: 1.00 95% CI, .097 to 1.03; p=0.95).

Genetic correlates of Angiopoietin-2 and soluble Tie-2

Heritability estimates were moderate for Ang-2 (27%) and substantial for sTie-2

(56%) in age-and sex-adjusted and in multivariable-adjusted models (Table

3). Multipoint LOD scores from the genome-wide linkage analysis for Ang-2 and sTie-2

levels are displayed in supplemental Figure 1 and 2. After multivariable adjustment, the

highest LOD score for Ang-2 was observed on chromosome 5 (Marker D5S2006) in the

butyrophilin-like 8 gene (LOD score: 2.41), which is below the acceptable threshold for

significant linkage (LOD score of 3). For sTie-2, the linkage peak (LOD score 8.31) was

identified at 60 cM on chromosome 9 with two genotyped markers (GATA5E06 at 58.26

cM and GATA71E08 at 58.27 cM) nearby. The wide linkage region (LOD score >3)

extends from 40 to 72 cM on chromosome 9 and includes the Tie-2 gene as well as a

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number of genes with known or putative functions in cardiovascular physiology (see

discussion). The second linkage peak (LOD score 2.91) was identified at 158 cM on

chromosome 12 with the genotyped marker ATA29A06 at 160.68 cM nearby, which is

close to the TMEM132D (transmembrane protein 132D) gene. However, the peak LOD

score (2.91) was slightly below the accepted threshold for significant linkage.

Discussion

We evaluated clinical and genetic correlates of Ang-2 and the soluble form of its

receptor (sTie-2) in a large community-based sample including almost 4000 individuals.

Principal findings

First, a sexual dimorphism for both biomarker concentrations was observed, with

Ang-2 levels being significantly higher and sTie-2 concentrations significantly lower in

women as compared to men. Relations to age were also opposite in directionality for the

two markers, with Ang-2 increasing with age, but sTie-2 declining with age. Second,

both Ang-2 and sTie-2 were positively related to diabetes and to the presence of the

metabolic syndrome. However, the two biomarkers were associated with different

components of the metabolic syndrome. Ang-2 was more strongly associated with BP

and pulse pressure, whereas sTie-2 was associated with obesity and hypertriglyceridemia,

components of the atherogenic triad. Third, circulating Ang-2 and sTie-2 concentrations

demonstrated moderate (27%) to substantial (56%) heritability, respectively. Finally, we

obtained strong evidence for linkage of a segment on chromosome 9 with sTie-2 levels

(LOD score: 8.31).

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In the context of the literature

Sexual dimorphism in circulating Angiopoieting-2 and Tie-2 concentrations

Gender differences in vascular function have been well described19 and

differences in endothelium derived vascular growth factors between men and women

might be a contributing factor. Sexual dimorphism has been reported for several

endothelium derived growth factors.16,20 Experimental and animal studies support the

notion that sex hormones influence vascular growth factor expression. For example,

estrogen/estradiol has been shown to modulate expression e.g. of Ang-1,21 and VEGF22.

Recent evidence suggest that also sTie-2 and Ang-2 levels were modulated by estrogen.23

In agreement with our observation of higher Ang-2 levels in women (as compared to

men), estrogen induces Ang-2 expression in several tissues.23 Our findings regarding sex-

related differences in distributions of Ang-2 and sTie-2 deserve additional confirmation

and the underlying mechanisms should be elucidated.

Clinical correlates of Angiopoietin-2

Circulating Ang-2 concentrations displayed highly significant positive associations

with major vascular risk factors, in particular BP and pulse pressure, hypertension,

smoking, and diabetes. The positive association with diabetes is in agreement with two

previous clinical studies.24,25 Increased levels of Ang-2 have been implicated in the

development of diabetic microvascular complications including retinopathy.26 Ang-2 and

VEGF play an important role in the initiation of neovascularization6 and stabilization of

incipient vascular tubes. Ang-2 may have a role in facilitating VEGF-initiated

neovascular sprouting by impairing Ang-1 stabilization and maintenance of existing

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tubes.7 The positive association of Ang-2 levels with BP traits agrees with several

previous studies reporting that in patients with hypertension Ang-2 levels were

elevated,14 correlated with target organ damage14 and predicted the incidence of

myocardial infarction.12 Given that Ang-2 and Ang-1 are competing for the same

endothelial-bound receptor and that Ang-2 thereby inhibits Ang-1/Tie-2 signaling related

vessel stabilization, it is possible that high levels of Ang-2 serve as a surrogate marker for

reduced Ang-1/Tie-2 signaling 2,7 Several potential explanations can be invoked for the

positive relations of Ang-2 to BP. First, dysregulation of vascular endothelial growth

factors, including increased Ang-2 levels, independent of CVD risk factors, might lead to

a paucity of mature small vessels, called microvascular rarefaction, which is a common

finding in patients with hypertension.27 Microvascular rarefaction increases the

transmission of pulsatile load to the microcirculation, which increases the risk of target

organ damage. Second, experimental data suggest that Ang-1 favorably influences

vascular remodeling through anti-inflammatory and antiatherogenic properties,28,29 and

that COMP (cartilage oligomeric matrix protein)-Ang-1, a derivative of Ang-1, prevents

the development of hypertension and associated target organ damage in pre-hypertensive

spontaneously hypertensive rats.30 Therefore, reduced Ang-1/Tie-2 activity could be

causally related to the development of elevated BP. In this context, Ang-2 has also been

reported to be an autocrine regulator of endothelial cell responses to inflammatory

stimuli, with a permissive role for the effects of proinflammatory cytokines.31 A third

possible explanation is that circulating Ang-2 levels are increased in response to BP-

induced vascular damage. Elevated BP and smoking adversely affect vascular

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remodeling, so increased circulating levels of Ang-2 might be an adaptive response to the

increasing burden of CVD risk factors.

The positive association of circulating Ang-2 with smoking is consistent with

experimental studies that demonstrate a pattern of heightened Ang-2 gene expression in

endothelial cells of smokers (compared to non smokers), consistent with heightened

stress-induced senescence of endothelial cells in smokers.32

Our finding of an association between Ang-2 and ECG-determined LVH are consistent

with angiogenesis being necessary for cardiac hypertrophy but are also in good agreement

with recent basic science data suggesting anti-hypertrophic effect of Ang-1 on cardiac myocytes

through binding to integrin receptors.33 As detailed above, increased soluble Ang-2 levels

could serve as a surrogate marker for reduced Ang-1 activity which would explain the

positive association between Ang-2 levels and LVH.

Clinical correlates of sTie-2

Soluble Tie-2 concentrations displayed highly significant associations with the

metabolic syndrome and its components, including diabetes, triglycerides and indices of

body composition including BMI, waist circumference, obesity and abdominal obesity.

These findings are consistent with the results of a small clinical study34 and agree well

with the positive association of other endothelial growth factors, including HGF, with

obesity and the metabolic syndrome.16 Given the strong interdependence of the adipose

tissue and angiogenesis, this positive association between sTie-2, which is the key

endothelial receptor for all angiopoietins,2 and the metabolic syndrome and obesity

(including abdominal obesity) is not surprising. The adipose tissue is well vascularized,35

and the growth of adipose tissue requires the presence of angiogenic factors and their

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receptor. It has indeed been shown in mouse models of obesity that Ang-2 expression

was increased in subcutaneous adipose tissue36 and that inhibitors of angiogenesis

effectively reduced weight and adipose tissue mass.37 On the other hand, the adipose

tissue itself might be a source of angiopoietins and their receptor, because adipose tissue

represents a very active endocrine organ producing a broad array of hormones, including

promoters and inhibitors of angiogenesis.35 It is not clear what the presence of soluble

Tie-2 indicates in this context. While sTie-2 is elaborated by adipose-related cell types in

response to upstream signals and promotes increased adipogenesis, sTie-2 also inhibits

angiogenesis by limiting circulating Ang-1 and Ang-2 from presentation to endothelial

Tie-2 with consequent loss of vessel stabilization signaling. thus, it is unclear if the

positive association of sTie-2 with BMI is due to increased elaboration of the growth

factor by the expanded fat compartment, or if it is in response to the greater need for

angiogenesis as the compartment expands.Tie-2 is expressed in glomerular capillary

endothelial cells.38 In this light, our finding of an inverse association of sTie-2 with eGFR

has intriguing implications on whether impaired angiogenesis could contribute to

impaired renal function, as has been described for certain nephropathies.39 Alternatively,

lower eGFR may be associated with greater Tie-2 expression.40 The association with

alcohol intake is consistent with experimental observations that ethanol increases

angiogenesis via a Tie-2-dependent pathway.41

Genetic correlates of Angiopoietin-2 and sTie-2

We observed that 56% of the variation in circulating sTie-2 concentrations was due to

genetic factors. Ang-2 levels had a moderate heritability of 27%. This is the first study to

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report heritability estimates for circulating Ang-2 and sTie-2 concentrations. These

heritability estimates are in excellent agreement with previous reports about substantial

heritability of circulating levels of other endothelial derived growth factors16 and support

the notion that circulating levels of angiogenic peptides are in part genetically

determined. This concept is further supported by experimental studies reporting that

expression of Ang-1, sTie-2 and other angiogenic biomarkers in response to chronic

hypoxia differed between mouse strains of varied genetic background.42

Multipoint linkage analyses revealed strong evidence for linkage (LOD score 8.31) on

chromosome 9 with circulating sTie-2 concentrations. The linkage peak is relatively

broad and includes the Tie-2 gene, which is the most plausible explanation for this

linkage peak. In addition, several other interesting candidate genes are in the linked

region, including the DDX58 (DEAD box polypeptide 58) gene, also known as retinoid

acid inducible gene 1, that is expressed in macrophages and has been suggested to play a

role in the development of atherosclerotic lesions.43 Furthermore, the NPR2 gene

(encoding atrial natriuretic peptide receptor B precursor) is located in the critical linkage

region. Another interesting gene is the DNAJB5 gene, belonging to the DNAJ/HSP40

protein family, which has recently been implicated in cardiac hypertrophy.44

Strengths and Limitations

The large community-based design, the familial structure of our study (facilitating

heritability and linkage analyses), and the availability of a broad array of carefully

assessed covariates strengthen our analyses. We acknowledge several limitations. Both

biomarkers were measured only once in each individual, which likely led to an

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underestimation of the strength of the associations between biomarker concentrations and

independent variables. The genomic coverage of linkage analyses is not as good as for

genome wide association analyses and therefore, we might have missed some genetic loci

that might be associated with the biomarker concentrations but that were not in strong

linkage disequilibrium with one of the 687 genetic markers we used. The cross-sectional

design precludes any causal inferences. Our sample is young-to-middle-aged, and of

European descent. The generalizability of our results to other age groups or ethnicities is

unknown. Our findings require replication in independent samples and additional

research is warranted to determine whether the observed associations are clinically

meaningful.

Conclusion

Circulating concentrations of soluble Tie-2 and Ang-2 levels were correlated with key

CVD and metabolic risk factors, consistent with the notion that angiopoietins are

involved in vascular remodeling in response to increased CVD risk factor burden. We

also found that a moderate to substantial proportion of the variation in circulating levels

of these proteins is heritable. Our results require confirmation in future studies.

Source(s) of Funding: This work was supported through National Institutes of Health/National Heart, Lung, and Blood Institute Contract N01-HC-25195, 2 K24 HL04334, RO1 HL 077477, (RSV), T32 HL007572 (JZ), and RO1 HL70100 (EJB). Conflict of interest Disclosures: G.F.M. is owner of Cardiovascular Engineering Inc., a company that designs and manufactures devices that measure vascular stiffness.

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kie RRRRRRRRRRRRRRRRRR, , , ,,,, , ,, ,,,,,, DuDuDuDuDuuDuDuDuDuDuDuDuDuDuDuDuDuDuDuuDDuurarararararararararaarararaarararaarandndndndndndnddndndndndndndndndndndndnndn E

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Table 1. Baseline characteristics of our study sample.

Women (n=2018) Men (n=1760)

Age, years 40±9 40±9

Systolic BP, mm Hg 113±14 121±12

Diastolic BP, mm Hg 73±9 78±9

Hypertension, % 12 20

Poorly controlled Hypertension, % 2.0 2.8

Well controlled Hypertension, % 5.3 6.2

BMI, kg/m² 25.9±6.0 27.9±4.7

Waist circumference, cm 86.9±15.3 95.5±12.5

Obesity, % 20 25

Abdominal obesity, % 40 34

Current smoker, % 14 16

Alcohol consumption, ounces per

week

3 (0,8) 8 (2,19)

eGFR, ml/min/1.73m² 99±32 100±17

Glucose, mg/dL 92±18 98±16

Diabetes, % 2.3 3.0

Insulin-dependent Diabetes (% of

participants with diabetes)

23 10

UACR, mg/g 4.7 (3.1,8.9) 3.2 (2.2,5.8)

Total cholesterol, mg/dL 185±34 193±37

LDL cholesterol, mg/dL 105±30 120±32

27.9999999999999±4±±±±±±±±±±±±

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HDL cholesterol, mg/dL 61±16 47±12

Triglycerides, mg/dL 80 (59,114) 107 (72,161)

Metabolic Syndrome, % 15 28

Dyslipidemia, % 29 40

Family history of CVD, % 33 33

Angiopoietin-2, ng/mL 2.03 (1.51,2.72) 1.71 (1.34,2.23))

Log-Angiopoietin-2, ng/mL 0.71 (0.41,1.00) 0.54 (0.29,0.80)

Soluble Tie-2, ng/mL 14.35 (12.02,17.42) 15.02 (12.71,18.29)

Log-sTie-2, ng/mL 2.71 (2.54,2.91) 2.66 (2.49,2.86)

BP, blood pressure; HDL, high-density lipoprotein; eGFR, estimated glomerular filtration rate,

BMI, body mass index; eGFR, estimates glomerular filtration rate; UACR, urinary

albumin/creatinine ratio; LDL, low-density lipoprotein; HDL, high-density lipoprotein; . Data are

mean±standard deviation for continuous traits (except for triglycerides, Angiopoietin-2, Tie-2 and

alcohol consumption where median (quartile1, quartile3) are provided) and percentages for

categorical data.

Definitions: poorly controlled hypertension: participants on antihypertensive medication, but with

systolic BP 140 or diastolic BP 90 mmHg; well controlled hypertension: participants on

antihypertensive medication and with a systolic BP <140 and a diastolic BP <90 mmHg; obesity:

body mass index 30 kg/m²); abdominal obesity: waist circumference 89 cm in women and

102 cm in men; dyslipidemia: total cholesterol > 200 mg/dL; smoking: smoking at least on

cigarette per day in the year preceding the examination.

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Table 2. Clinical correlates of Angiopoietin-2 and soluble Tie-2 as determined by linear regression models.

Increase/decrease in log-Biomarker level Percent increase/decrease in biomarker

in natural units 95% confidence interval 95% confidence interval

Angiopoietin-2Estimate Lower Limit Upper Limit Estimate Lower Limit Upper Limit p-value

Age, years 0.019 0.003 0.035 1.92% 0.30% 3.56% 0.02

Men -0.149 -0.178 -0.12 -13.84% -16.31% -11.31% <.0001

Smoking 0.159 0.119 0.198 17.23% 12.64% 21.90% <.0001

Total cholesterol, mg/dL -0.037 -0.051 -0.023 -3.63% -4.97% -2.27% <.0001

Antihypertensive Medication 0.091 0.04 0.142 9.53% 4.08% 15.26% 0.0004

Diastolic blood pressure, mm Hg -0.045 -0.064 -0.025 -4.40% -6.20% -2.47% <.0001

Systolic blood pressure, mm Hg 0.031 0.011 0.051 3.15% 1.11% 5.23% 0.003

Diabetes 0.097 0.001 0.192 10.19% 0.10% 21.17% 0.048

Soluble Tie-2 Age, years -0.045 -0.056 -0.034 -4.40% -5.45% -3.34% <.0001

Men 0.043 0.024 0.062 4.39% 2.43% 6.40% <.0001

Body mass index, kg/m² 0.016 0.006 0.027 1.61% 0.60% 2.74% 0.002

Diabetes 0.102 0.04 0.164 10.74% 4.08% 17.82% 0.001

eGFR, ml/min/1.73m² -0.017 -0.027 -0.007 -1.69% -2.66% -0.70% 0.0005

Alcohol consumption -0.011 -0.023 -0.0004 -1.09% -2.27% -0.04% 0.04

Triglycerides, mg/dL 0.012 0.003 0.021 1.21% 0.30% 2.12% 0.01

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The first three columns describe the estimates (and 95% CI) representing the increase in log-biomarker levels per 1-SD increment in the predictor

variable for continuous traits. For binary traits, estimates indicate increase in log-biomarker levels for presence vs. absence of the trait. For

example, men have 14% lower (e-0.149 =0.86) Ang-2 levels as compared to women, adjusting for all other covariates in the model. In the next three

columns, the % change in biomarker levels in natural units per 1-SD increment in the predictor variable (presence vs. absence of binary traits) is

shown. The multivariable model explained 6.8% and 3.8% of the inter-individual variation in circulating Ang-2 and sTie-2 concentrations,

respectively.

*Alcohol consumption in ounces per week.


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Table 3. Heritability estimates for Angiopoietin-2 and soluble Tie-2

Biomarker Model Heritability 95% CI p-value

Angiopoietin-2 Age- and sex-adjusted 0.28 (0.21,0.35) 3.9x10-17

multivariable-adjusted 0.27 (0.19,0.34) 1.7x10-16

Soluble Tie-2 Age- and sex-adjusted 0.55 (0.47,0.62) 1.2x10-57

multivariable-adjusted 0.56 (0.48,0.63) 5.2x10-59

Multivariable-adjusted models adjusted for those covariates that were significantly

related to Angiopoietin-2 and Tie-2, respectively in Table 2.

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B. Sawyer and Ramachandran S. VasanSullivan, Martin G. Larson, Holly M. Smith, Qiong Yang, Gary F. Mitchell, Joseph A. Vita, Douglas

Wolfgang Lieb, Justin Zachariah, Vanessa Xanthakis, Radwan Safa, Ming-Huei Chen, Lisa M.Community

Clinical and Genetic Correlates of Circulating Angiopoietin-2 and Soluble Tie-2 in the

Print ISSN: 1942-325X. Online ISSN: 1942-3268 Copyright © 2010 American Heart Association, Inc. All rights reserved.

TX 75231is published by the American Heart Association, 7272 Greenville Avenue, Dallas,Circulation: Cardiovascular Genetics

published online March 26, 2010;Circ Cardiovasc Genet.

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1

SUPPLEMENTAL MATERIAL

Supplemental Table 1. Number of siblings per family in the study sample

Supplemental Table 2. Correlation matrix for natural‐logarithmically transformed circulating

concentrations of angiopoietin‐2 (Ang‐2), its soluble receptor sTie‐2, vascular endothelial growth factor A

(VEGF), its receptor sFlt‐1 and hepatocyte growth factor (HGF)

Supplemental Figure 1. Multipoint Logarithm of the odds (LOD) score (y‐axis) from the genome wide

linkage analysis for Ang‐2. X‐axis: Chromosomal position. Analyses were adjusted for all significant

correlates of Ang‐2 (Table 2).

Supplemental Figure 2. Multipoint Logarithm of the odds (LOD) score (y‐axis) from the genome wide

linkage analysis for sTie‐2 levels. X‐axis: Chromosomal position. Analyses were adjusted for all significant

correlates of sTie‐2 (Table 2).

2

Supplemental Table 1. Number of siblings per family in the study sample

Participants with xx siblings in the study n Subtotal n

0 712 712

1 559 1118

2 306 918

3 130 520

4 48 240

5 23 138

6 14 98

7 2 16

8 2 18

Total n 3778

“0” siblings indicates families with 1 Third Generation participant

3

Supplemental Table 2. Correlation matrix for natural‐logarithmically transformed circulating concentrations of angiopoietin‐2 (Ang‐2), its soluble receptor sTie‐2, vascular endothelial growth factor A (VEGF), its receptor sFlt‐1 and hepatocyte growth factor (HGF)

Log‐Ang‐2 Log‐sTie‐2 Log‐VEGF Log‐HGF Log‐sFlt‐1

correlation coefficient





Log‐Ang‐2 1 0.00396 ‐0.01787 0.07306** 0.06765** Log‐sTie‐2 0.00396 1 ‐0.0451* 0.05893* 0.01379 Log‐VEGF ‐0.01787 ‐0.0451* 1 0.18206** 0.02498 Log‐HGF 0.07306** 0.05893* 0.18206** 1 0.13398** Log‐sFlt‐1 0.06765** 0.01379 0.02498 0.13398** 1

**p<0.0001

*p<0.01

ln_Ang2: multivariable adjusted

Chromosome

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ln_Tie2: multivariable adjusted

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clinical and genetic correlates of circulating angiopoietin-2...

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