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Associations between Tooth Loss and Prognostic Biomarkers and the Risk for 4 5

6 Cardiovascular Events in Patients with Stable Coronary Heart Disease 7

8 Short title: Vedin et al.: Tooth Loss and Biomarkers in CHD

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12 Ola Vedin, MD, PhD1,2, Emil Hagström, MD, PhD1,2, Ollie Östlund, PhD2, Alvaro Avezum, 13

14 MD, PhD3, Andrzej Budaj, MD, PhD4, Marcus D. Flather, MBBS5, Robert A. Harrington, 15 16 MD6, Wolfgang Koenig, MD7-9, Joseph Soffer, MD10, Agneta Siegbahn, MD, PhD2,11, 17 18

Philippe Gabriel Steg, MD12-15, Ralph A. H. Stewart, MD16, Lars Wallentin, MD, PhD1,2, 19 20

Harvey D. White, MB, ChB, DSc16, Claes Held, MD, PhD1,2 on behalf of the STABILITY 21 22

23 Investigators

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27 1Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden;

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29 2Uppsala Clinical Research Center (UCR), Uppsala University, Uppsala, Sweden; 3Dante 30

31 Pazzanese Institute of Cardiology, São Paulo, Brazil; 4Postgraduate Medical School, 32

33 Grochowski Hospital, Warsaw, Poland; 5Norwich Medical School, University of East Anglia 34 35 and Norfolk and Norwich University Hospital, UK; 6Department of Medicine, Stanford 36 37

University, Stanford, CA, USA; 7Department of Internal Medicine II-Cardiology, University 38 39

40 of Ulm Medical Center, Ulm, Germany; 8Deutsches Herzzentrum München, Technische 41

42 Universität München, Munich, Germany; 9DZHK (German Centre for Cardiovascular 43

44 Research), partner site Munich Heart Alliance, Munich, Germany; 10Metabolic Pathways and 45

46 Cardiovascular Therapeutic Area, GlaxoSmithKline, King of Prussia, PA, USA; 47

48 11Department of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, 49 50 Sweden; 12INSERM-Unité 1148, Paris, France; 13Assistance Publique-Hôpitaux de Paris, 51 52 Département Hospitalo-Universitaire FIRE, Hôpital Bichat, Paris, France; 14Université Paris- 53 54

Diderot, Sorbonne-Paris Cité, Paris, France; 15NHLI Imperial College, ICMS, Royal 55

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Brompton Hospital, London, UK; 16Green Lane Cardiovascular Service, Auckland City

Hospital and University of Auckland, Auckland, New Zealand

All authors take responsibility for all aspects of the reliability and freedom from bias of the

data presented and their discussed interpretation.

Address for correspondence: Dr. Ola Vedin; Uppsala Clinical Research Centre/MTC, Dag

Hammarskjölds väg 14B, 752 37, Uppsala, SWEDEN; Tel: + 46 18 6119500;

Fax: +46 18 515570; Email: ola.vedin@ucr.uu.se

ACKNOWLEDGEMENT OF GRANT SUPPORT

The STABILITY study was funded by GlaxoSmithKline. Roche Diagnostics, Rotkreuz,

Switzerland supported the research by providing GDF-15 assay free of charge.

CONFLICTS OF INTEREST

OV: institutional research grant from GlaxoSmithKline; expert committee member and lecture

fees from Boehringer Ingelheim, Fresenius Medicare, Novartis. EH: expert committee

member, lecture fees and institutional research grant from Sanofi; institutional research grant

and lecture fees from Amgen; institutional research grants from AstraZeneca,

GlaxoSmitKline; expert committee member for Ariad and Merck Sharp & Dohme. OÖ:

institutional research grants from GlaxoSmithKline. AA: personal fees from Boehringer

Ingelheim, Bristol-Myers Squibb, Pfizer, Bayer, AstraZeneca. AB: research

grants/investigator’s fees and honoraria for lectures from GlaxoSmithKline, AstraZeneca,

Bristol-Myers Squibb/Pfizer; research grants/investigator’s fees from Sanofi-Aventis,

Boehringer Ingelheim, Novartis, Eisai, Duke Research Institute. MDF: speaker's bureau and

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consultancy fees from AstraZeneca; grants from GlaxoSmithKline, Novartis, Menarini;

honoraria from Eli Lilly. RAH: research grants and consultant/advisory fees from Merck,

The Medicines Company; research grants from AstraZeneca, CSL Behrig, GlaxoSmithKline,

Portola, Regado, Sanofi; consultant/advisory fees from Amgen, Gilead, MyoKardia,

WebMD; stock ownership in Element Science, Scanadu, Signal Path. WK: lecture and

consultancy fees from Novartis, Amgen, AstraZeneca, Servier; lecture fees from Actavis;

consultancy fees from BioInvent, diaDexus, Cerenis, GlaxoSmithKline, The Medicines

Company, Genzyme, Pfizer, Merck Sharpe & Dohme; research grants from Roche

Diagnostics, Abbott, Singulex, Beckmann. JS: employee of and having stock ownership in

GlaxoSmithKline. AS: institutional research grants from AstraZeneca, Boehringer Ingelheim,

Bristol-Myers Squibb/Pfizer, GlaxoSmithKline. PGS: institutional research grants, honoraria

and non-financial support from Sanofi, Servier; honoraria and non-financial support from

AstraZeneca; honoraria from Amarin, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb,

Daiichi-Sankyo, Eli Lilly, Merck Sharp & Dohme, Novartis, Pfizer, Medtronic, Janssen, The

Medicines Company, CSL-Behring, GlaxoSmithKline; stockholder in Aterovax. RAHS:

grants and non-financial support from GlaxoSmithKline. LW: institutional research grant,

consultancy and lecture fees, travel support and honoraria from GlaxoSmithKline;

institutional research grants, consultancy and lecture fees and travel support from

AstraZeneca, Bristol-Myers Squibb/Pfizer, Boehringer Ingelheim; institutional research grant

from Merck, Roche; consultancy fees from Abbott; holds two patents involving GDF-15.

HDW: research grants and advisory board for AstraZenecea; advisory board for The

Medicines Company; research grants from Sanofi Aventis, Eli Lilly and Company, National

Institute of Health, Merck Sharpe & Dohm, GlaxoSmithKline, Omthera Pharmaceuticals,

Pfizer New Zealand, Intarcia Therapeutics Inc, Elsai Inc., DalGen Products and Services,

Daiichi Sankyo Pharma Development. CH: institutional research grant and speaker’s bureau

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from AstraZeneca; institutional research grants from Bristol-Myers Squibb Merck & Co,

GlaxoSmithKline, Roche.

KEYWORDS

Tooth loss, periodontal disease, stable coronary heart disease, biomarkers, risk factors.

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ABSTRACT

BACKGROUND: Underlying mechanisms behind the hypothesized relationship between

periodontal disease (PD) and coronary heart disease (CHD) have been insufficiently

explored. We evaluated associations between self-reported tooth loss, a marker of PD, and

prognostic biomarkers in 15,456 (97%) patients with stable CHD in the global STABILITY

trial.

METHODS AND RESULTS: Baseline blood samples were obtained and patients reported

their number of teeth according to the following tooth loss levels: “26–32 (All)” [lowest

level], “20–25”, “15–19”, “1–14”, and “No Teeth” [highest level]. Linear and Cox regression

models assessed associations between tooth loss levels, biomarker levels and the relationship

between tooth loss levels and outcomes, respectively.

After multivariable adjustment, the relative biomarker increase between the

highest and the lowest tooth loss level was: high-sensitivity C-reactive protein 1.21 (95%

confidence interval, 1.14-1.29), interleukin 6 1.14 (1.10-1.18), lipoprotein-associated

phospholipase A2 activity 1.05 (1.03-1.06), growth differentiation factor 15 1.11 (1.08-1.14),

and N-terminal pro−B-type natriuretic peptide (NT-proBNP) 1.18 (1.11-1.25). No association

was detected for high-sensitivity troponin T 1.02 (0.98-1.05). Some attenuation of the

relationship between tooth loss and outcomes resulted from the addition of biomarkers to the

multivariable analysis, of which NT-proBNP had the biggest impact.

CONCLUSIONS: A graded and independent association between tooth loss and several

prognostic biomarkers was observed, suggesting that tooth loss and its underlying

mechanisms may be involved in multiple pathophysiological pathways also implicated in the

development and prognosis of CHD. The association between tooth loss and cardiovascular

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death and stroke persisted despite comprehensive adjustment including prognostic

biomarkers.

Clinical trial registration: www.clinicaltrials.gov; NCT00799903

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1. INTRODUCTION

There is a growing body of evidence favouring an independent association between oral

health and coronary heart disease (CHD) [1–3]. We have recently reported an association

between tooth loss and cardiovascular (CV) outcomes, but not myocardial infarction (MI), in

a chronic CHD population [4]. In the literature, the hypothesized relationship between dental

disease and CV disease is often attributed to deleterious effects of periodontal disease (PD), a

highly prevalent chronic inflammatory condition ranging from early gingivitis to end-stage

tooth loss, on the atherosclerotic process but the specific mechanistic nature of such a

relationship remains elusive and debated [5].

Pathophysiological information on multiple aspects of etiology and progression

of CV disease is reflected by several biomarkers, many of which also have robust capabilities

of predicting prognosis [6–11]. Thus, associations between markers of PD, biomarkers and

CV outcomes could provide further insights about possible mechanisms connecting PD and

CV disease. However, such existing observations mainly stem from smaller populations and

are limited to selected inflammatory markers such as C-reactive protein and interleukin-6

[12,13], whereas reported associations with other important biomarkers are either scarce or

non-existent.

We evaluated associations between self-reported tooth loss, a marker of oral

disease and PD, and a wide range of prognostic biomarkers, including high-sensitivity

C-reactive protein (hs-CRP), interleukin-6 (IL-6), lipoprotein-associated phospholipase A2

activity (Lp-PLA2), growth differentiation factor 15 (GDF-15), high-sensitivity troponin T

(hs-Troponin T) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) in a large global

CHD population. Further, we assessed the influence of these biomarkers on the ability of

self-reported tooth loss to predict CV outcomes.

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2. METHODS

2.1. Study population

The STabilization of Atherosclerotic plaque By Initiation of darapLadIb TherapY

(STABILITY) study evaluated the efficacy of darapladib, an oral inhibitor of lipoprotein-

associated phospholipase A2 activity (Lp-PLA2) compared to placebo in addition to optimal

medical treatment in 15,828 participants from 39 countries with stable CHD, defined as prior

myocardial infarction (MI), prior coronary revascularization (percutaneous coronary

intervention or coronary artery bypass grafting), or multivessel CHD without

revascularization. At least one additional enrichment criterion was required: age ≥60 years;

diabetes mellitus requiring pharmacotherapy; high-density lipoprotein cholesterol

<1.03mmol/L; current or previous smoker defined as ≥5 cigarettes per day on average;

moderate renal dysfunction (estimated glomerular filtration rate ≥30 and <60mL/min/1.73 m2

or urine albumin:creatinine ratio ≥30mg albumin/g creatinine); or polyvascular disease (co-

existing disease in at least two arterial territories). Patients with an estimated glomerular

filtration rate <30mL/min/1.73 m2 were excluded [14]. After a median follow-up of 3.7 years,

no difference in major adverse cardiovascular events (MACE, i.e. first occurrence of CV

death, myocardial infarction or stroke) was observed for patients randomized to darapladib

compared to placebo [15]. The ethics committees of each participating country approved the

study and all patients provided written informed consent prior to inclusion. The STABILITY

trial was performed in accordance with the Declaration of Helsinki.

2.2. Data collection

At baseline, 15,456 (97%) patients reported their number of teeth according to the following

categories: “26–32 (All teeth)”, “20–25”, “15–19”, “1–14”, and “No Teeth”. For the purposes

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of this report, these categories are termed tooth loss levels with 26-32 teeth corresponding to

the lowest level and no teeth, the highest level.

Blood samples for routine laboratory tests and storage for later analyses were

obtained in all 15,456 patients at baseline and prognostic biomarker analyses were performed

in the majority of patients. Plasma aliquots were stored at -70°C until biochemical analysis.

All routine biochemical and hs-CRP analyses were performed at a central laboratory with

standardized methods (Quest Diagnostics Clinical Laboratories, Inc., Valencia, California,

USA). Plasma concentrations of hs-CRP were analyzed using a particle-enhanced

immunonephelometry assay, CardioPhase© hsCRP, Siemens Healthcare. Plasma

concentrations of high-sensitivity IL-6 were analyzed using an ELISA technique, R&D

Systems Inc., Minneapolis, MN, U.S.A. Lp-PLA2 activity was measured in an automated

enzyme assay system (PLAC® Test for Lp-PLA2 Activity, diaDexus, San Francisco, CA,

USA). The other biomarker assays were performed at the UCR Laboratory at Uppsala

University, Uppsala, Sweden, GDF-15 was measured with the GDF-15 precommercial assay

(Roche Diagnostics, Penzberg, Germany), composed of a monoclonal mouse antibody for

capture and a monoclonal mouse antibody fragment, [F(ab´)2], for detection in a sandwich

assay format. Detection was based on an electrochemiluminiscence immunoassay using a

ruthenium (II) complex label. Levels of hs-Troponin T and NT-proBNP were also determined

by electrochemiluminescence (Roche Diagnostics, Penzberg, Germany). The Cobas

Analytics e601 was used for the Roche immunoassays.

2.3. Statistical analysis

Baseline variables are presented as mean, standard deviation and percentages. Baseline

biomarker levels are presented as median and interquartile range. Baseline biomarker levels

by tooth loss level were compared using the Kruskal-Wallis tests.

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To determine associations between tooth loss levels and biomarker levels, each

biomarker was modelled as a function of tooth loss level (five levels). All biomarkers were

analyzed on a log-transformed scale using linear models. Geometric mean ratios are presented

with 95% confidence intervals (CI) with the lowest tooth loss level (26-32 teeth) as

reference, and according to three adjustment models. Model 1 adjusted for randomized

treatment. Model 2 adjusted for Model 1 and prior MI, prior coronary revascularization,

multi-vessel CHD, age, sex, geographic region, diabetes mellitus, hypertension, renal

dysfunction, body mass index, smoking (current, former or never), systolic blood pressure

and polyvascular disease. Model 3 adjusted for Model 2 and estimated glomerular filtration

rate (according to The Chronic Kidney Disease Epidemiology Collaboration equation,

replacing significant renal dysfunction) [16], hemoglobin, white blood cells, low-density

lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides. Cox

proportional hazards models were used to calculate hazard ratios for MACE, CV death and

stroke in relation to tooth loss levels, adjusting for biomarkers in addition to a previously

reported multivariable model [4], co-variables of which are also listed in Table 3. In these

models, all biomarkers except Lp-PLA2 activity were added after log-transformation. The

association between tooth loss and MI has previously been found to be absent in this cohort

and was not re-analysed in the present analysis.

A p-value <0.05 was considered statistically significant in all analyses. Analyses were

performed at the Uppsala Clinical Research Center, Uppsala, Sweden using SAS version 9.3

(SAS Institute, Inc., Cary, NC, USA). 587 588

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3. RESULTS

3.1. Baseline characteristics and associations with biomarkers

Patients with higher tooth loss levels were older, were more likely to be female and had a

greater CV risk factor burden, particularly a higher prevalence of smoking, diabetes mellitus,

hypertension and impaired renal function compared to those with lower tooth loss levels

(Table 1). Patients with more tooth loss had progressively higher baseline levels of hs-CRP,

IL-6, Lp-PLA2 activity, GDF-15, hs-Troponin T and NT-proBNP (Table 2). As demonstrated

in Figure 1, higher tooth loss levels were associated with progressively greater relative

increases for all prognostic biomarkers in relation to the lowest tooth less level in Model 1.

After multivariable adjustment the association remained statistically significant for all

biomarkers, except for hs-Troponin T.

3.2. Tooth loss and outcomes

Table 3 demonstrates the association between a one-level increase in tooth loss and the risk

of MACE, CV death and stroke according to the three adjustment models after a median

follow-up of 3.7 years. The data up until Model 2 have been previously presented [4]

showing a relative risk increase of 1.06, 1.17 and 1.14 for MACE, CV death and for stroke,

respectively, for every one-level increase in tooth loss. The subsequent addition of

biomarkers, individually and in groups, only attenuated the results slightly. Nevertheless, the

addition of IL-6 and NT-proBNP rendered the association with MACE non-significant.

Despite adjustment for all biomarkers and other co-variables, the association between tooth

loss and CV death and stroke persisted. 652 653

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4. DISCUSSION

We found that tooth loss, a marker of PD, was associated with higher levels of several CV

biomarkers indicating a potential relationship between tooth loss and several

pathophysiological mechanisms relevant to CV morbidity and mortality, including

inflammation, cellular integrity and myocardial dysfunction [6,7,9,17]. Adjustment for the

biomarkers somewhat attenuated the risk of adverse outcome, signalling a potential relevance

of the pathways they represent in the relationship between tooth loss and increased CV risk.

However, much of the risk increase remained, suggesting that other and presently unknown

mechanisms could be of importance, although confounding cannot be excluded.

The host-mediated inflammatory response to PD constitutes the most

commonly proposed mechanism linking oral disease with CHD and CV disease [18], mainly

based on evidence from smaller studies of moderate associations between various measures

of PD and elevation of inflammatory markers [12,13,19] and studies showing reductions of

CRP and IL-6 levels after PD treatment [20]. This is the first study to corroborate these

findings on a large scale in a global CHD population, including both upstream and

downstream inflammatory markers, with comprehensive adjustment and with tooth loss as

the exposure measure. Moreover, the association with Lp-PLA2 activity, previously only

assessed in small patient populations [21], could represent an additional alternative and

independent inflammatory link [22]. However, our findings could represent a challenge to the

inflammation hypothesis as the highest levels of inflammatory markers were observed among

the edentulous, who are most likely rid of oral substrates for inflammation. This could indicate

that intrinsic factors and not PD explain the inflammatory activity, for instance pro-

inflammatory genetic traits and epigenetic modifications common to both advanced PD and

CHD [23,24]. However, it is also conceivable that many years’ exposure to chronic oral

inflammation could instigate a secondary response in other locations, e.g.

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atherosclerosis in blood vessels, which in turn could promote or maintain an elevated

systemic inflammatory response.

Associations with biomarkers that reflect other than inflammatory processes

could suggest a relevance of alternative pathophysiological pathways in the tooth loss-CV

disease relationship. The association with GDF-15 for instance, has not been previously

described and could partly reflect a relationship between tooth loss and inflammation but also

other harmful mechanisms [17] of relevance to several cardiac afflictions, including MI and

heart failure, to which GDF-15 has been previously associated [25,26]. An independent

association with cardiac biomarkers could support a more specific link between tooth loss, its

antecedents, and cardiac pathology. This was previously investigated in a small study where

44 patients with clinical evidence of PD had higher levels of troponin and NT-proBNP

compared to controls, however these associations were unadjusted [27]. The association with

NT-proBNP in our study suggests a relationship between tooth loss and baseline cardiac

dysfunction that persisted after adjustment for traditional important heart failure determinants,

including prior MI, hypertension and diabetes. Cross-reactivity between periodontal

and myocardial antigens and chronic toll-like receptor activation have been

suggested as potential mechanisms linking chronic infection, e.g. PD, to heart failure [28].

Furthermore, a recent study demonstrated a greater burden of PD among patients with

advanced HF awaiting heart transplantation compared to controls without HF. However, the

observed differences were attenuated to non-significance after adjustment for markers of oral

hygiene, race and 25- hydroxyvitamin D levels [29]. Overall, data on the role of PD in the

pathophysiology of heart failure is largely lacking but the results from our present study and

other studies are interesting from a hypothesis generating perspective and should be explored

further.

Conversely to the association with NT-proBNP, tooth loss did not appear to be related to

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mechanisms generating elevated levels of troponin [30], which is an interesting finding

concurrent with the absent association between tooth loss and MI in this population [4].

In contrast to the absent MI association we recently reported a significant

association between tooth loss and MACE, CV death and stroke. Although the demonstrated

risk increases were relatively modest between adjacent tooth loss levels, they were more

substantial and likely to be clinically relevant when comparing patients with severe or

complete tooth loss to those with little or no tooth loss, particularly for CV death and stroke

[4]. In the present analysis, we added biomarkers to the previous outcomes model to assess

their influence on the demonstrated relationship between tooth loss and prognosis. Of the

inflammatory markers, IL-6, an upstream marker, attenuated the results the most and

eliminated the MACE association, supporting the hypothesis of inflammation as a mediator in

the PD-CV outcomes relationship further. However, for most of the biomarkers, resulting

attenuations were relatively small. The addition of NT-proBNP had the most pronounced

attenuating effect on the risk of adverse outcome, indicating a prognostic relevance of the

observed relationship between tooth loss and baseline myocardial dysfunction. The fact that a

significant portion of the increased risk for CV death and stroke persisted despite full

adjustment implies that alternate and presently unidentified pathways could be involved. The

observation of stronger associations for CV death and stroke compared to MI further suggests

that such pathways may be other than atherosclerotic and inflammatory, which is also

consistent with the associations to biomarkers reflecting other than primarily inflammatory

mechanisms, including GDF-15 and NT-proBNP. While the additional adjustment for

biomarkers could lead to underestimation of the true influence of tooth loss on prognosis by

removing effects of potential intermediate pathways, it also likely lessens the impact of

residual confounding, which is undoubtedly a considerable obstacle when assessing causality.

Nevertheless, as our findings are purely observational, causality cannot be inferred and they

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may in fact be a product of long-term influence by causal factors common to both tooth loss

and CV disease.

From a prediction perspective and irrespective of causality, the observations

show promise for the potential use of self-reported tooth loss as a prognostication tool in

chronic CHD. Given its ability to predict several important outcomes combined with other

qualities, including its straightforward obtainability and affordability, the clinical predictive

utility of self-reported tooth loss should be explored further.

4.1. Study limitations

Self-reported tooth loss was the sole marker of PD in this analysis and the use of additional

exposure measures, e.g. clinical, could have provided better information regarding the

underlying etiology of tooth loss in the individual subjects. However, the literature generally

exhibits a lack of consistency in the use of PD definitions [5] and PD has been shown to be

the most common cause of tooth loss in older populations [31], although other causes, most

importantly caries, must be acknowledged. Moreover, self-reported tooth loss has been

validated against number of teeth on clinical examination with concurring results [32]. The

cross-sectional multivariable analysis of the association between tooth loss and biomarker

levels did not include markers of socioeconomic status, which could be important

confounders. Finally, the analysis does not specifically disclose the nature of the observed

associations, i.e. whether tooth loss and its underlying mechanisms increases CV risk or vice

versa, or if the two conditions are driven by a common etiology.

4.2. Conclusion

Self-reported tooth loss was associated with progressively higher levels of several prognostic

CV biomarkers suggesting possible involvement of tooth loss-generating mechanisms,

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including PD, in multiple pathophysiological pathways relevant to both CHD development

and prognosis. Adjustment for a wide range of CV risk factors, socioeconomic status and

biomarkers eliminated the association with MACE but the association with CV death and

stroke persisted.

ACKNOWLEDGMENTS

We thank all participants, study personnel and investigators in the STABILITY study. We

also thank Ebba Bergman, Susanna Thörnqvist, and Vendela Roos, Uppsala Clinical

Research Centre, for editorial support.

FUNDING

The STABILITY study was funded by GlaxoSmithKline. Roche Diagnostics, Rotkreuz,

Switzerland supported the research by providing GDF-15 assay free of charge.

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FIGURE LEGENDS

Figure 1 legend. Geometric mean ratio of biomarker levels according to tooth loss level with

the lowest tooth loss level (26-32 teeth) as reference. Included biomarkers are high-sensitivity

C-reactive protein (hs-CRP), interleukin 6 (IL-6), lipoprotein-associated phospholipase A2

activity (Lp-PLA2), growth differentiation factor 15 (GDF-15), high-sensitivity troponin T

(hs-Troponin T), and N-terminal pro−B-type natriuretic peptide (NT-proBNP).

Adjusted for darapladib treatment, prior MI, prior revascularization, multi-vessel coronary

heart disease, age, sex, geographic region, diabetes mellitus, hypertension, body mass index,

smoking (current, former or never), systolic blood pressure, polyvascular disease, estimated

glomerular filtration rate, Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI),

hemoglobin, white blood cells, low-density lipoprotein (LDL) cholesterol, high-density

lipoprotein (HDL) cholesterol, and triglycerides.

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TABLES

Table 1. Demographic and baseline characteristics by tooth loss level

Tooth Loss Level

Lowest Highest

1394

1395

1396

Characteristics All Patients

(n=15456)

26-32 Teeth

(n=3310)

20-25 Teeth

(n=3680)

15-19 Teeth

(n=2167)

1-14 Teeth

(n=3785)

No Teeth

(n=2514)

p-value

1397

1398

1399

1400

Age, years 64.4 +/- 9.3 61.1 +/- 10.0 63.2 +/- 9.2 64.5 +/- 9.0 65.8 +/- 8.5 68.2 +/- 8.0 <0.0001

Sex <0.0001

1401

1402

1403

1404

1405

1406

1407

1408

1409

1410

1411

1412

1413

1414 1415

Female 18.6 13.7 15.1 19.9 21.6 24.9

Smoking status <0.0001

Never smoked 30.8 38.9 32.9 30.0 27.2 22.9

Former smoker 51.2 46.2 50.5 50.4 53.2 56.6

Current smoker 18.0 14.9 16.5 19.6 19.6 20.5

Diabetes 38.8 35.4 37.4 36.6 41.3 43.0 <0.0001

Chronic kidney disease 30.2 23.9 27.3 31.4 32.7 38.0 <0.0001

Prior MI 58.9 55.3 58.1 59.9 62.4 58.7 <0.0001

1416

1417 Prior revascularization 74.9 76.9 75.6 73.5 72.8 75.7 0.0078

1418 1419 24

1420 1421

1422

1423

1442

1424 Education

1425

1426 None 1427

3.6

3.5

2.6

3.1

3.8

5.2

<0.0001

1428 1-8 years 1429

19.2 14.7 15.5 16.8 23.1 27.1

1430 9-12 years 30.7 26.1 29.0 32.5 32.8 34.4

1431

1432 Trade school 18.2 14.5 17.8 19.7 20.7 18.6

1433

1434 College/university 28.3 41.2 35.0 27.9 19.7 14.7

1435

1436 Alcohol consumption/week

<0.0001

1437 None

1438

54.8 53.6 50.1 51.8 57.1 62.1

1439 1-4 drinks 1440

18.9 19.1 20.3 20.2 18.5 16.4

1441 5-14 drinks 15.8 16.3 18.0 16.4 14.9 12.9

1443 ≥15 drinks 10.5 11.0 11.6 11.7 9.5 8.7

1444

1445 Leisure time physical activity 0.0002

1446

1447 Sedentary 32.8 33.3 30.0 30.4 35.1 35.0

1448

1449 Mild exercise 44.6 44.4 45.1 45.5 43.0 45.4

1450 Moderate exercise 22.6 22.3 25.0 24.1 21.8 19.6 1451 1452 LDL cholesterol, mmol/L 2.2 ± 0.9 2.1 ± 0.8 2.2 ± 0.8 2.2 ± 0.8 2.3 ± 0.9 2.2 ± 0.8 <0.0001 1453 1454 HDL cholesterol, mmol/L 1.2 ± 0.3 1.2 ± 0.3 1.2 ± 0.3 1.2 ± 0.3 1.2 ± 0.3 1.2 ± 0.3 <0.0001

1455 1456 eGFR, mL/min/1.73m2

75.8 ± 18.1 78.7 ± 17.8 77.2 ± 17.8 75.3 ± 18.1 74.5 ± 18.2 72.3 ± 18.0 <0.0001

1457 1458 1459 1460 25 1461 1462

1463

1464

1465

1466

1467

1468

1469

1470

1471

1472

1473

1474

1475

1476

1477

1478

1479

1480

1481

1482

1483

1484

1485

1486

1487

1488

1489

1490

1491

1492

1493

1494

1495

1496

1497

1498

1499

1500

1501

1502

1503

Systolic BP, mmHg 131.5 ± 16.6 128.8 ± 16.0 131.3 ± 16.1 131.6 ± 17.0 132.6 ± 16.4 133.4 ± 17.3 <0.0001

Diastolic BP, mmHg 78.7 ± 10.4 78.4 ± 10.2 78.7 ± 10.3 78.8 ± 10.4 79.2 ± 10.3 78.2 ± 10.6 <0.0001

BMI, kg/m2 28.9 ± 5.0 28.5 ± 5.0 29.1 ± 5.1 28.9 ± 5.0 29.0 ± 4.8 29.3 ± 5.2 <0.0001

Data are percentages and mean ± SD

MI, myocardial infarction; LDL, low-density lipoprotein; HDL, high-density lipoprotein; eGFR, estimated glomerular filtration

rate; BP, blood pressure; BMI, body mass index

26

1504

1505

1506

1507

1508

1509 1510

Table 2. Baseline biomarker levels by tooth loss level

Tooth Loss Level

1511 Lowest Highest

1512

1513

1514

1515

1516

1517

Biomarker All Patients

(n=15456)

hs-CRP, mg/L

26-32 Teeth

(n=3310)

20-25 Teeth

(n=3680)

15-19 Teeth

(n=2167)

1-14 Teeth

(n=3785)

No Teeth

(n=2514)

p-value

1518

1519

1520

1521

1522

1523

1524

1525

1526

1527

1528

1529

1530

n

Median (Q1; Q3)

IL-6, pg/mL

n

Median (Q1; Q3)

14076

1.3 (0.6; 3.1)

14263

2.1 (1.4; 3.2)

2977

1.1 (0.5; 2.6)

2974

1.8 (1.3; 2.8)

3389

1.3 (0.6; 2.8)

3400

2.0 (1.4; 2.9)

1972

1.4 (0.7; 3.0)

2007

2.1 (1.4; 3.3)

3467

1.5 (0.7; 3.3)

3545

2.2 (1.5; 3.4)

2271

1.7 (0.8; 4.0) < 0.0001

2337

2.4 (1.7; 3.8) < 0.0001

1531

1532

Lp-PLA2, μmol/min/L

1533

1534

1535

1536

1537

1538

1539

1540

1541

1542

1543

1544

n

Median

(Q1; Q3)

GDF-15,

pg/mL

14155

173 (143; 204)

2960

171 (140; 203)

3366

172 (143; 202)

1984

172 (143; 204)

27

3520

173 (144; 206)

2325

176 (148;

207)

< 0.0001

1545

1546

1547

1548

1549

1550

1557

1558

1559

1560

1561

1562

1563

1564

1565

1566

n

Median (Q1; Q3)

Median (Q1; Q3)

NT-proBNP, ng/L

14237

1254 (915; 1827)

9.3 (6.2; 14.2)

2974

1120 (824; 1615)

8.5 (5.7; 12.7)

3385

1181 (876; 1709)

8.7 (6.0; 13.3)

2011

1225 (907; 1792)

9.4 (6.2; 14.3)

3528

1314 (962; 1888)

9.8 (6.4; 14.8)

2339

1486 (1069; 2172)

10.4 (6.9; 16.2)

< 0.0001

< 0.0001

1567

1568

1569

1570

1571

1572

1573

1574

1575

1576

1577

1578

1579

1580

1581

1582

1583

1584

1585

n 14181 2960 3392 2003 3505 2321

Median (Q1; Q3) 173 (83; 377) 132 (64; 278) 152 (72; 328) 177 (88; 392) 202 (97; 450) 224 (108; 493) < 0.0001

1551 1552 1553 hs-Troponin T, ng/L

1554 1555 n 14147 2952 3386 1996 3497 2316

1556

hs-CRP, high-sensitivity C-reactive protein; IL-6, interleukin 6; Lp-PLA2

, lipoprotein-associated phospholipase A2

activity; hs-Troponin T, high-sensitivity troponin

T;

NT-

proB

NP,

N-

termi

nal

pro−

B-

type

natri

uretic peptide; GDF-15, growth differentiation factor 15

28

1586

1587

1588

1589

1590

1591

1592

Table 3. Risk of major adverse cardiac events (MACE), cardiovascular (CV) death and stroke for one increase in tooth loss level after

adjustment for risk factors and biomarkers

1593

1594

1595

1596

1597

1598

Adjustment MACE

(HR [95% CI])

p-value CV death

(HR [95% CI])

p-value Stroke

(HR [95% CI])

p-value

1599

1600

1601

1602

1603

1604

1605

1606

1607

1608

1609

1610

1611

1612

1613

1614

1615

1616

1617

1618

1619

1620

1621

1622

1623

1624

1625

1626 Model 1

Model 2

Model 2 + hs-

CRP

Model 2 + IL-6

1.16

(1.12-

1.20)

1.06

(1.02-

1.10)

1.05

(1.00-

1.09)

1.04

(1.00-

1.09)

<0.0001

0.0041

0.0404

0.0581

1.30 (1.23-1.37)

<0.0001

1.17 (1.10-1.24)

<0.0001

1.16 (1.08-1.23)

<0.0001

1.14 (1.07-1.22)

<0.0001

1.22 (1.23-1.32)

1.14 (1.04-1.25)

1.14 (1.04-1.23)

1.12 (1.02-1.23)

Model 2 + Lp-PLA2 1.06 (1.01-1.10) 0.0091 1.16 (1.09-1.24) <0.0001 1.14 (1.04-1.26) 0.0057

Model 2 + GDF-15

1.05 (1.01-1.10)

0.0273

1.15 (1.08-1.23) <0.0001

1.12 (1.02-1.23)

0.0188

29

<

0

.

0

0

0

1

0

.

0

0

6

2

0

.

0

0

6

5

0

.

0

2

2

4

1627

1628

1629

1630

1631

1632

1633

1634

1635

1636

1637

1638

1639

1640

1641

1642

Model 2 + hs-Troponin T, NT-proBNP

1.03 (0.99-1.07)

0.1893

1.12 (1.05-1.19)

0.0006

1.10 (1.00-1.21)

0.0488

1643

1644

1645

1646

1647

HR, hazard ratio; CI, confidence interval; Model 1 is adjusted for study treatment only. Model 2 is adjusted for model 1 and age, systolic blood pressure, diastolic blood

pressure, BMI, LDL cholesterol, HDL cholesterol, history of diabetes, prior MI, sex, smoking status, waist hip ratio, eGFR, family history of coronary heart disease, alcohol

consumption, years of education, level of physical activity and country income level. Abbreviations as in Tables 1 and 2.

Model 2 + hs-CRP, IL-6, Lp-PLA2, 1.04 (0.99-1.08) 0.0973 1.13 (1.05-1.20) 0.0005 1.13 (1.03-1.25) 0.0146

GDF-15

Model 2 + hs-CRP, IL-6, Lp-PLA2,

GDF-15, hs-Troponin T, NT-proBNP

1.02 (0.98-1.07)

0.3335

1.10 (1.03-1.18)

0.0046

1.11 (1.00-1.23)

0.0406

1648 1649

1650

1651

1652

1653

1654

1655

1656

1657

1658

1659

1660

1661

1662

1663

1664

1665 30 1666 1667

1668

1669

1670

1671

1672

1673

1674

1675

1676

1677

1678

1679

1680

1681

1682

1683

1684

1685

1686

1687

1688

1689

1690

1691

1692

1693

1694

1695

1696

1697

1698

1699

1700

1701

1702

1703

1704

1705

1706

1707

1708

1709

1710

1711

1712

1713

1714

1715

1716

1717

1718

1719

1720

1721

1722

1723

1724

1725 31

1726

Biomarker

and tooth Mean (95%

loss level ratio Cl) P-value

0.9 0.95 1 1.05 1.1 1.15 1.2 1.25 1.3

• •

•

Author Agreement Form – International Journal of Cardiology

Manuscript Title: Associations between Tooth Loss and Prognostic Biomarkers and the Risk for

Cardiovascular Events in Patients with Stable Coronary Heart Disease

List of all Authors: Ola Vedin, MD, PhD; Emil Hagström, MD, PhD; Ollie Östlund, PhD; Alvaro

Avezum, MD, PhD; Andrzej Budaj, MD, PhD; Marcus D. Flather, MBBS; Robert A.

Harrington, MD; Wolfgang Koenig, MD; Joseph Soffer, MD; Agneta Siegbahn, MD, PhD;

Philippe Gabriel Steg, MD; Ralph A. H. Stewart, MD; Lars Wallentin, MD, PhD; Harvey D.

White, MB, ChB, DSc; Claes Held, MD, PhD.

Corresponding Author: Ola Vedin

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of the data and its interpretation, and agree to its submission to the International Journal of

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International Journal of Cardiology family of journals. Int. J. Cardiol. 170 (2014) 253-254

DOI:10.1016/j.ijcard.2013.11).

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