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UMEÅ UNIVERSITY MEDICAL DISSERTATIONSNew Series No 975 ISSN 0346-6612 ISBN 91-7305-909-9
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From Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
Risk markers for a first myocardial infarction
Anna Margrethe Thøgersen
Umeå 2005
Copyright © 2005 by Anna Margrethe Thøgersen Department of Medicine, Public Health and Clinical Medicine, Umeå University,
Umeå, Sweden
Printed in SwedenPrint & Media, Umeå 2005:2001088
Fortune is not a terminus, but a continuous journey
Chinese proverb
Lykken er ikke en endestation, men en måde at rejse på.
Kinesisk ordsprog
To everybody
CONTENTS
ABSTRACT………………………………………………………………………4
ABBREVIATIONS…………………………………………….…………………5
ORIGINAL PAPERS………………………………………………………...…...6
INTRODUCTION………………………………………………………………...7
AIMS…………………………………………………………………………...…35
MATERIAL AND METHODS…………………………………………….....….36
RESULTS………………………………………………………………....………49
Study I
Study II
Study III
Study IV
DISCUSSION………………………………………………………………......…67
CONCLUSION…………………………………………………………...…..…..82
ACKNOWLEDGMENTS…………………………………………………..….....83
REFERENCES…………………………………………………………….…...…86
ABSTRACT
Risk markers for a first myocardial infarction
Anna Margrethe Thøgersen, Department of Public Health and Clinical Medicine, Umeå University, S-901 85 Umeå, Sweden.
The development of a first myocardial infarction is associated with a large number of contributing factors. Age, male sex, hypertension, smoking, diabetes, body mass index and hypercholesterolemia are considered as established risk factors. The primary aim of the present dissertation was to evaluate whether specific biomarkers could improve the prediction of subjects at risk for a first myocardial infarction when considered in addition to established cardiovascular risk factors. The biomarkers investigated include: tissue plasminogen activator (tPA), plasminogen activator inhibitor-1 (PAI-1), thrombomodulin (TM), von Willebrand factor (VWF), dehydroepiandrosterone sulfate (DHEAS), lipoprotein (a) (Lp(a)), leptin, apolipoproptein A1 (ApoA1), proinsulin, homocysteine and homozygosity for the 5,10-methylenetetrahydrofolate reductase (MTHFR) C>T genotype. A secondary objective was to determine whether a first myocardial infarction leads to increased plasma homocysteine concentrations and whether the association between homocysteine and myocardial infarction was greater at follow-up compared to baseline.
The study population consisted of 36 405 subjects screened and included in the Västerbotten Intervention Program and the Northern Sweden MONICA cohorts between January 1, 1985 and September 30, 1994. A nested incident case-referent study design was used. Seventy eight cases with a first myocardial infarction were identified, and from the same cohort twice as many sex and age matched referents were randomly selected. Moreover, a follow-up health survey (average 8.5 years between surveys) was conducted with 50 cases and 56 matched referents.
High plasma levels of tPA and PAI-1 mass concentration, VWF, proinsulin, leptin and Lp(a) and low plasma levels of ApoA1 were associated with subsequent development of a first myocardial infarction in univariate conditional logistic regression analysis. For PAI-1 and tPA, this relation was found in both men and women. For tPA, but not for PAI-1 and VWF, this association was independent of established risk factors. In women, high plasma concentrations of TM were associated with significant increases in risk of a first myocardial infarction. No predictive values of DHEAS, homocysteine or for the point mutation C677>T in the gene for MTHFR was found regarding the risk of a first myocardial infarction. The summarised importance of haemostatic and metabolic variables (proinsulin, lipids including Lp(a) and leptin) in predicting first myocardial infarction in men, as well as possible interactions among these variables, were studied. High tPA and Lp(a) and low ApoA1 remained significant risk markers in multivariate analysis independent of established risk factors. There were non-significant synergic interactions between high Lp(a) and leptin and tPA respectively, and between high Lp(a) and low ApoA1.
In the follow-up study plasma homocysteine and plasma creatinine increased significantly, and plasma albumin decreased significantly over time. Conditional univariate logistic regression indicated that high homocysteine at follow-up but not at baseline was associated with first myocardial infarction but the relation disappeared in multivariate analyses including plasma creatinine and plasma albumin. High plasma creatinine remained associated with first myocardial infarction at both baseline and follow-up.
In conclusion, the present results support the hypothesis that biomarkers, in addition to the traditional cardiovascular risk factors, carry predictive information on the risk of developing a first myocardial infarction.
Keywords: haemostatis, lipoprotein (a), MTHFR, homocysteine, proinsulin, leptin, apolipoprotein A1, DHEAS, myocardial infarction, risk factors.
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ABBREVIATIONS
ApoA1 apolipoprotein A1
CBS cystationine- -synthase
CI confidence interval
CV coefficient of variation
DHEAS dehydroepiandrosterone sulfate
DNA deoxyribonucleic acid
DBP diastolic blood pressure
EDTA ethylene diamine tetraacetate
ELISA enzyme-linked immunosorbent assay
GP glycoprotein
HDL high density lipoprotein
IL interleukin
LDL low density lipoprotein
Lp(a) lipoprotein (a)
MMP matrix metalloproteinase
MTHFR 5,10-methylenetetrahydrofolate reductase
MONICA Multinational Monitoring of Trends and Determinants in Cardiovascular Diseases
OR odds ratio
PAI-1 plasminogen activator inhibitor-1
SD standard deviation
SBP systolic blood pressure
TAFI thrombin-activatable fibrinolysis inhibitor
tHcy total plasma homocysteine
TNF tumor necrosis factor
TM thrombomodulin
tPA tissue plasminogen activator
uPA plasminogen activator urokinase
VIP Västerbotten Intervention Program
VWF von Willebrand factor
WHO World Health Organisation
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ORIGINAL PAPERS
This thesis is based on the following papers, which will be referred to by their Roman numerals.
Permission is granted to reprint all four papers in the thesis.
I. Thøgersen AM, Jansson JH, Boman K, Nilsson TK, Weinehall L, Huhtasaari F, Hallmans G.
High plasminogen activator inhibitor and tissue plasminogen activator levels in plasma precede a
first acute myocardial infarction in both men and women. Evidence for the fibrinolytic system as
an independent primary risk factor. Circulation 1998; 98: 2241-2247.
II. Thøgersen AM, Nilsson TK, Dahlén G, Jansson JH, Boman K, Huhtasaari F, Hallmans G.
Homozygosity for the C677 T mutation of 5,10-methylenetetrahydrofolate reductase and total
plasma homocyst(e)ine are not associated with greater than normal risk of a first myocardial
infarction in Northern Sweden. Coronary Artery Disease 2001; 12: 85-90.
III. Thøgersen AM, Søderberg S, Jansson J-H, Dahlén G, Boman K, Nilsson TK, Lindahl B,
Weinehall L, Stenlund H, Lundberg V, Johnson O, Ahrén B, Hallmans G. Interactions between
fibrinolysis, lipoproteins and leptin related to a first myocardial infarction. European Journal of
Cardiovascular Prevention and Rehabilitation 2004; 11: 33-40.
IV. Hultdin J, Thøgersen AM, Jansson J-H, Nilsson TK, Weinehall L, Hallmans G. Elevated plasma
homocysteine: cause or consequence of myocardial infarction? Journal of Internal Medicine 2004;
256: 491-498.
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INTRODUCTION
Epidemiology of myocardial infarction in Northern Sweden
Compared with the rest of Sweden, Northern Sweden has been characterized by a high incidence of
cardiovascular disease (1,2), and in an international 10-year comparison (3,4), Northern Sweden is
above the median rates of myocardial infarction for both men and women. The rate for a first
myocardial infarction among men aged 25-64 in Northern Sweden has been 250 per 100,000 during
1985-98, and the corresponding numbers for women have been about 66 per 100,000 in the same
age group (4). Cardiovascular diseases were identified as leading causes of morbidity and mortality
in northen Sweden during the 1970s and early 1980s (5).
Risk factor definition and cohort study
In Last´s Dictionary of Epidemiology (6), a risk factor is defined as “an aspect of personal behavior
or lifestyle, an environmental exposure, or an inborn or inherited characteristic, that, on the basis of
epidemiologic evidence, is known to be associated with health-related condition(s) considered
important to prevent”. This broad and rather loose definition leaves unanswered the issue of causal
role, strength of association, and modifiablility (7). Beck (8) has offered a more specific definition
of a risk factor as “an environmental, behavioral, or biologic factor confirmed by temporal
sequence, usually in longitudinal studies, which if present directly increases the probability of a
disease occurring, and if absent or removed reduces the probability”. Risk factors are part of the
causal chain, or expose the host to the causal chain. Once disease occurs, removal of a risk factor
may not result in a cure. Hill (9) have used different criteria for the probability of clinical causality
of which the most important are 1) temporality – the cause is present before the disease, 2) strength
of the relation – a stronger relationship means a greater probability of causality, 3) plausibility – the
relation has a biological rationale, 4) consistence – the relation is reproducible in different
populations and situations. Hill (9) suggested that the following aspects of an association can be
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considered in attempting to distinguish causal from non-causal associations: (1) strength, (2)
consistency, (3) specificity (4) temporality, (5) biologic gradient, (6) plausibility, (7) coherence, (8)
experimental evidence, and (9) analogy. A risk marker is an attribute or exposure that is associated
with an increased probability of disease, but is not necessarily a causal factor. A risk determinant is
an attribute or exposure that increases the probability of occurrence of disease or other specified
outcome. The relation could be causal, but this has not been proven. A modifiable risk factor is a
determinant that can be modified by intervention, thereby reducing the probability of disease (6).
Biologic interaction should be evaluated as departures from additivity of effect (10).
A cohort study is the analytical method of epidemiologic study in which subsets of a defined
population can be identified who are, have been, or in the future may be exposed or not exposed in
different degrees, to a factor or factors hypothesized to influence the probability of occurrence of a
given disease or other outcome (6). The main feature of cohort study is observation of large
numbers over a long period with comparison of incidence rates in groups that differ in exposure
levels (6). Generally, all the cases that are identified in the cohort are selected and included in a
nested case-referent study (11).
Myocardial infarction pathology: atherosclerotic plaques, platelet activation and the
fibrinolytic pathway
Virtually all-regional myocardial infarctions are caused by thrombosis developing on a culprit
coronary atherosclerotic plaque (12). The very rare exceptions to this are spontaneous coronary
artery dissection, coronary arteritis, coronary emboli, coronary spasm, and compression by
myocardial bridges (12).
The American Heart Association (AHA) has made a definition of advanced types of atherosclerotic
lesions and a histological classification of atherosclerosis (13). The initial (type I) atherosclerotic
lesion contains enough atherogenic lipoprotein to elicit an increase in macrophages and formation
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of scattered foam cells (13). The changes are more marked in locations of arteries with adaptive
intimal thickening. Type II lesions consist primarily of layers of macrophage foam cells and smooth
muscle with extracellular lipid deposits cells and include lesions grossly designated as fatty streaks
(13). Type III lesions consist of smooth muscle cells surrounded by extracellular lipid deposits. This
extracellular lipid is the immediate precursor of the larger, confluent, and more disruptive core of
extracellular lipid that characterizes type IV lesions (13). In type V lesions the lipid core contains a
thick layer of fibrous connective tissue. Some type V lesions are largely calcified (type Vb), and
some consist mainly of fibrous connective tissue and little or no accumulated lipid or calcium (type
Vc). Type VI lesions have fissure and/or hematoma, and thrombus (13). The lipid core in stage IV
is an extracellular mass of lipid containing cholesterol and its esters, some of which is in crystalline
form (12). The cholesterol ester composition of the atheromatous core is very similar to that of
circulating plasma-LDL, with a high fraction of cholesterol linoleate (14). Oxidized LDL and its
peroxide derivative, lysophosphatidylcholine, stimulate protein kinase C activity, phosphoinositide
turnover, and release of internal calcium. It also impairs endothelial cell replication and
angiogenesis, and induces apoptosis (15). The core is surrounded by numerous macrophages
derived from monocytes which cross the endothelium from the arterial lumen (12). They are highly
activated, producing procoagulant tissue factors and a host of inflammatory cell mediators. The
connective tissue capsule which surrounds this inflammatory mass is predominantly collagen
synthesised by smooth muscle cells (12). The current view of atherosclerosis is that the prime
stimulus for plaque inflammation is the reaction between oxidised LDL and the macrophage (12).
Thrombosis over plaques occurs because of two somewhat different processes. One is caused by an
extension of the process of endothelial denudation, while the second mechanism involves plaque
disruption (12). The fibrous cap is a dynamic structure within which the connective tissue matrix is
constantly being replaced and maintained by the smooth muscle cell (12). The inflammatory
process both reduces collagen synthesis by inhibiting the smooth muscle cell and causes its death by
apoptosis (12). Continued inflammation results in increased numbers of macrophages and
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lymphocytes emigrating from the blood into the lesion (14). Macrophages also produce a wide
range of metalloproteinases capable of degrading all the components of the connective tissue
matrix, including collagen (12). These metalloproteinases are secreted into the tissue in an inactive
form and then activated by plasmin (12). Metalloproteinase production by macrophages is
upregulated by inflammatory cytokines (12). Plaque disruption is therefore now seen as an auto-
destructive phenomenon associated with an enhanced inflammatory activation (12). When the
endothelium is physically disrupted or functionally perturbed, a prothrombotic and proinflammatory
state develops characterised by vasoconstriction, platelet and leukocyte activation and adhesion,
promotion of thrombin formation, coagulation and fibrin deposition at the vascular wall (16). Three
components need to interact to assure hemostasis: the vascular wall, the formed elements of the
blood and the plasmatic clotting and fibrinolytic systems.
The first event is platelet adhesion with a non-platelet surface, followed by platelet activation and
secretion. Adherent platelets release a varity of pro-inflammatory mediators and growth hormones
and have the potential to modify signaling cascades in vascular cells, inducing the expression of
endothelial adhesion receptors and the release of endothelial chemoattractants (17). In this manner
they might regulate the adhesion and infiltration of leukocytes, in particular that of monocytes, into
the vascular wall: a process which is thought to play a key role in acute and chronic inflammation
(17). von Willebrand factor (VWF) is secreted by platelets and facilitates adhesion of platelets to
vascular subendothelium. Also present is VWF that is secreted by the endothelium (17). A smaller
portion of VWF is secreted into the abluminal space where it adheres to collagen, while the
majority of VWF is released into the plasma compartment (17). Secondarily the reaction of the
plasma coagulation system results in fibrin formation (18) (Figure 1). Endothelial cells express
tissue factor procoagulant in response to inflammatory mediators and PAI-1 (19). Clot lysis and
vessel repair begin immediately after the formation of the definitive hemostatic plug (18). The
principal physiologic activators of the fibrinolytic system system, tissue plasminogen activator
(tPA) and plasminogen activator urokinase (uPA), diffuse from endothelial cells and convert
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plasminogen that is adsorbed to the fibrin clot into plasmin (18). Only a small quantity of each
coagulation enzyme is converted to its active form. Blood fluidity is maintained by the flow of
blood, the adsorption of coagulation factors to surfaces and their trapping in the emerging clot.
Multiple inhibitors in plasma also contribute such as antithrombin, protein C and S and tissue factor
pathway inhibitor (18). Protein C is converted to an active protease by thrombin after it is bound to
an endothelial cell protein called thrombomodulin (TM).
The fibrinolytic pathway
The main fibrinolytic components of plasma are plasminogen, t-PA, and urokinase-type
plasminogen activator (uPA) (20). tPA is the major plasminogen activator in plasma and uPA binds
to a cellular uPA receptor and is considered to participate in extravascular proteolysis (21).
Fibrinolysis involves the action of tPA and uPA on plasminogen, to produce plasmin, which in turn
degrades the cross-linked fibrin of a thrombus (22). The major inhibitors of fibrinolysis are PAI-1,
which inhibits tPA, 2-antiplasmin which neutralizes plasmin, and thrombin activatable fibrinolysis
inhibitor (TAFI) (23). In addition, tPA is inactivated by the slow inhibitors C1-inhibitor, 2-
antiplasmin and 2-macroglobulin (24,25). Expression of tPA, uPA, and PAI-1 is increased in the
atherosclerotic plaque, and these factors therefore may affect thrombotic events after plaque rupture
(23). Furthermore, the plasminogen system is involved in activation of matrix metalloproteinases
intimately involved in plaque stability and in tissue remodelling (23). Since fibrinolytic reactions
take place on the surface of the fibrin clot, fibrinolysis is locally restricted and does not become
systemic (20). The overall balance of tPA and PAI-1 in the circulation is such that PAI-1 is in
several-fold excess over tPA, so that most of the tPA circulates as tPA-PAI-1 complex (Figure 2)
(26). The balance can be changed subtly in normal individuals, for instance by the increase in tPA
concentration by virtue of release from endothelial cells in response to exercise or venous occlusion
(26). PAI-1, in particular, is variable within the normal population (26). Both tPA and
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Prothrombin
Extrinsic or Tissue-factor-dependent pathway Thrombomodulin
+ Thrombin
Xa Va Protein C
Protein S
Intrinsic or Activated contact system Protein C
Thrombin
Fibrinmonomer Cross-linked fibrin+
Plasminogen Plasmin
Fibrinogen
active tPA
PAI-1
Platelet
Platelet
von Willebrand factor Endothelial cells
Connective Connective tissue matrix
Lipidcore,LDL,Lp(a)
smooth muscle cell
Macro-phage
Figure 1. A simplified schematic diagram of the hemostatic and the fibrinolytic pathway and coronary artery disease.
PAI-1 show distinct circadian variations (26). In platelet-rich thrombi, PAI-1 provides an important
mechanism for controlling the activity of tPA (20).
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PAI-1 mass concentration
Active PAI-1
tPA/PAI-1 complex Active tPA
tPA mass concentration
PAI-1 PAI-1
tPA
Other
inhibitors
tPA tPA
Figure 2. Schematic presentation of the relation between tPA mass concentration and activity,
PAI-1 mass concentration and activity, and tPA/PAI-1 complex.
Tissue plasminogen activator
tPA is a serine protease synthesized in endothelial cells with gene expression mainly regulated at
the level of transcription (27). The release rate of tPA is subjected to a local regulation and the
systemic levels of tPA may not reflect the local profibrinolytic capacity in terms of availability of
active tPA at the organ level (28). The major determinant of how much active tPA is available in
the vascular bed of an organ, is proportional to the capacity of the endothelium to increase its
secretion of tPA when required (28). Ladenvall et al (29) recently identified a polymorphic Sp1
binding site in an enhancer at the tPA locus (tPA –7,351C/T), which was associated with vascular
tPA release. Subjects homozygous for the –7,351C allele had twice the tPA release rate compared
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to subjects carrying the –7,351T allele. However there was no significant correlation between
zygosity and systemic plasma tPA (29,30). The genes responsible for the genetic regulation of
plasma tPA remained to be determined and neither variation at the PLAT locus located on
chromosome eight nor the PAI-1 –675 4G>5G polymorphism are strong predictors of plasma tPA
levels (27). In healthy subjects, approximately 1/3 of plasma tPA is in an active, free form, and the
remaining part is complex bound (28). During basal conditions tPA is mainly released via a
constitutive secretory pathway, but a substantial amount of tPA can rapidly be released upon
stimulation (regulated release) (31). Substances released from activated platelets and products of the
coagulation process are potent triggers of stimulated tPA release (31). Release of tPA from vessel
wall is also stimulated by heparin, bradykinin, histamin, nicotinic acid, desmopressin, 1-desamino-
8-D-arginine-vasopressin (DDAVP), methacholine, doxazosin ( 1-inhibitor), prostacyclin,
epinephrine, stress, coffee, exercise, venous occlusion and ischemia (28,32,33). Circulating tPA is
cleared by the liver with a half-life of 3-5 minutes and clearance is proportional to liver blood flow
(34,35). Two receptors in the liver for tPA have been identified, the low-density lipoprotein
receptor-related protein and the mannose-dependent receptor (35,36,37). Active tPA is cleared by
both receptors and has a faster clearance than that of tPA/PAI-1 complex (37).
As free active tPA is difficult to measure in plasma (unless blood is collected into anticoagulants
specific for this purpose), most clinical studies have measured circulating tPA mass values (26,38).
tPA mass is mainly a marker of complex formation between tPA and its major plasma inhibitor
PAI-1, rather than a measure of free tPA (Figure 2).
PAI-1
PAI-1 is a glycoprotein that belongs to the serine protease inhibitor superfamily (serpins) (39). It
binds rapidly to tPA and to uPA, forming a stable complex with a ratio of 1:1 that is cleared from
the circulation by hepatic cells (20,39). The active form of PAI-1 is unstable, with a half-life of 30
minutes (20). Vitronectin has been identified as a protein that binds PAI-1 in plasma, stabilizes the
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active form and maintains a distribution between PAI-1 in plasma and in the extracellular matrix
(20, 40).
Although the principal source of plasma PAI-1 is unknown, available evidence indicates that
several cell types, including endothelial and vascular smooth muscle cells, platelets, macrophages,
hepatocytes, spleen cells, fibroblasts, and adipocytes, all have capacity to produce PAI-1 (39,41).
PAI-1 synthesis is stimulated by numerous agents, including thrombin, endotoxin, various
cytokines, Lp(a), insulin, oxidized LDL, and activation of the renin-angiotensin-aldosteron system,
among others (15,41). It is possible that different tissues are responsible for raised plasma PAI-1
depending on the actual condition (26). For instance, the acute-phase elevation of PAI-1 is
associated with hepatic synthesis, but the elevation that correlates with triglyceride levels may
reflect adipose tissue synthesis (26). The very marked elevation seen in sepsis is probably of
endothelial origin (26). Once produced, PAI-1 is generally secreted immediately, some of it binding
to proteins of the extracellular matrix, in particular vitronectin (26). The exposed reactive centre
loop in PAI-1 inserts spontaneously into the body of the molecule, generating a form known as
latent, because it can be re-activated in vitro by denaturation and subsequent refolding (26). This
loop insertion occurs much more slowly in the presence of vitronectin, which therefore stabilizes
PAI-1 activity (26). High local concentrations of PAI-1 mRNA have been demonstrated in
atherosclerotic plaques, in contrast to normal vessel walls, suggesting that local synthesis of PAI-1
in endothelial and smooth muscle cells is increased, as shown in cultured cells stimulated by
cytokines (26). Plasma levels of PAI-1 can be measured either as activity or as immunoreactive
PAI-1 mass. Both measurements require utmost care in blood collection and sample handling
because PAI-1 is a labile molecule (39). In addition, precautions must be taken to avoid release of
PAI-1 from platelets, which contain a large amount of mostly the inactive form (39). The PAI-1
activity assay detects free active PAI-1, whereas the PAI-1 mass assay measures free active PAI-1,
inactive latent PAI-1, and also inactive (complexed with tPA or uPA) PAI-1 (39) (figure 2).
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von Willebrand factor
Mature VWF is a multimeric glycoprotein composed of identical disulfide-linked subunits (42).
Plasma concentrations of VWF have a wide range, from 50 to 200% of normal. The two storage
organelles found in the cells that synthesize VWF are the Weibel-Palade body in endothelial cells
and the -granule in megakaryocytes and platelets (42). In megakaryocytes, only the regulated
pathway of VWF secretion is effectively operative in vivo. Thus, the VWF circulating in plasma is
essentially all of endothelial cell origin, as platelets release their -granule content only when
activated (42). The VWF secreted from endothelial cells, through either the constitutive or the
regulated pathway, is directed towards both the lumen and the subendothelial matrix (42).
Circulating VWF is cleared by the liver with a half-life of approximately 12 to 18 hours (43, 44).
Secretion is stimulated by a variety of agents, including histamine, thrombin and fibrin (45).
Vascular injury or stress increases VWF synthesis and VWF can fluctuate considerably in acute-
phase inflammatory responses (23,46,47). The VWF levels tend to increase with age and VWF
concentrations are also increased in patients with hypertension, diabetes, inflammatory vascular
disease, peripheral artery disease, exercise, pregnancy, malignancy, liver disease ande
hyperthyroidism (43,48-50).
Plasma VWF has three major activities: (1) mediating platelet adhesion to damaged arterial walls,
(2) mediating platelet aggregation at high shear stress, and (3) binding and stabilizing factor VIIIc
(23). Platelets adhere to VWF through IIb/IIIa glycoprotein receptors, which are usually available
for binding only after platelet activation (43). By serving as the carrier for factor VIII, VWF may
also coordinate formation of the fibrin (and platelet)- rich thrombus at the site of endothelial cell
injury. VWF may mediate initial platelet adhesion to the subendothelium by linking to specific
platelet membrane receptors (glycoprotein Ib-IX complex) and to constituents of subendothelial
connective tissue. Through multiple functional domains, each VWF subunit has binding sites for
collagen, heparin, glycoprotein (GP) Ib, GPIIb/IIIa and factor VIII (43).
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Thrombomodulin
Thrombomodulin is an endothelial cell surface receptor for thrombin that functions as an
anticoagulant by greatly accelerating thrombin-induced activation of protein C (51) (Figure 1). The
activity of activated protein C is enhanced by its co-factor protein S, which is synthesized by
endothelial cells, among other cell types (15). Binding of thrombin to thrombomodulin also
dampens the enzyme´s ability to activate platelets, factor V, factor XIII, and fibrinogen and
promotes endothelial cell fibrinolytic activity (15). Thrombomodulin also inhibits prothrombinase
activity indirectly by binding factor Xa (15). Binding of thrombin to thrombomodulin accelerates its
capacity to activate a protein known as thrombin-activatable fibrinolysis inhibitor (TAFI or
procarboxypeptidase B) (15,52). TAFI cleaves when activated by basic carboxyterminal residues
within fibrin and other proteins. This results in the loss of plasminogen/plasmin and tPA binding
sites on fibrin resulting in retarded fibrinolysis (15). Thus, through the regulated expression of
thrombomodulin, endothelial cells also serve as a potent template to decrease the rate of
intravascular fibrinolysis (15). Thrombomodulin has also been found to exhibit anti-inflammatory
properties. In part, this is mediated by protein C activation, but thrombin activation of endothelial
cells contributes to a variety of inflammatory events. This includes the expression of P selectin on
the endothelial cell surface and the formation of the neutrophil agonist, platelet-activating factor.
The ability of thrombomodulin to block these activities has an indirect antiinflammatory effect
(52,53). Various inflammatory cytokines downregulate thrombomodulin gene transcription and
accelerate thrombomodulin internalization, while at the same time promoting tissue factor
expression and shedding of endothelial cell protein C from the endothelium (15,52). Inflammation
leading to downregulation of thrombomodulin, decrease in TAFI activation and increased
complement activation could work together to injure the vessel wall and expose coagulant
phospholipid surfaces (53). A soluble, truncated form of thrombomodulin circulates in plasma, but
its significance is unknown (51).
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Dehydroepiandrosterone sulfate (DHEAS)
Dehydroepiandrosterone (DHEA) and its sulphated form (DHEAS) are produced in the adrenal
cortex and are converted to androgens and oestrogens in peripheral tissues (54). DHEAS
concentration is 100- to 500-fold higher than that of testosterone and 1000 to 10 000 times greater
than that of estradiol (55). DHEA and DHEAS, however, do not possess intrinsic estrogenic or
androgenic activity (55). DHEAS binds strongly to albumin (56). These inactive precursor steroids
are converted into active androgens and estrogens in peripheral target tissues, a process that
depends on the specific expression of the steroidogenic enzymes in each of these tissues (55). In
epidemiological studies, concentrations of DHEAS rather than DHEA have been used, as DHEAS
has been shown to have a longer half-time and little diurnal variation (57). DHEA inhibition of
mammalian glucose 6-phosphate dehydrogenase, which is the entry point into the pentose
phosphate pathway, might provide a plausible biological site of action for the various stages at
which DHEA might interfere with the atherogenic process (57,58). It may affect adherence of
platelets and macrophages, the release of chemoattractants and growth factors, the proliferation of
cellular elements or the uptake of cholesterol into the atheroma (57). DHEA may also reduce local
free radical generation by macrophages (57). In 1996, Beer et al (59) reported that 2 weeks of oral
DHEA administration reduces plasma PAI-1 and tPA mass concentration in men, however the
precise physiological functions of DHEAS are uncertain.
Lp(a)
Lp(a) is a complex serum lipoprotein composed of a LDL particle linked by its surface
apolipoprotein (apo) B-100 via a disulfide bond to an unique and highly polymorphic glycoprotein,
apo(a) (60). Apo(a) shares extensive structural homology with plasminogen, and consists of a non-
functional serine protease domain, a variable number of multiple repeats of kringle IV, and a single
copy of kringle V (51). The variable number of kringle IV repeats is due to varying number of
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copies within the apo(a) gene, and results in at least 35 different molecular weight isoforms (51).
Plasma Lp(a) levels are largely genetically determined (61), and vary inversely with apo(a) isoform
size. Levels increase in patients with renal disease (51). The presence of multiple interleukin-6
responsive elements may explain the transient increase in Lp(a) levels observed during acute
inflammatory states (62). In contrast to plasma LDL levels, Lp(a) levels are unaffected by diet,
physical activity, and most lipid-lowering agents (51). On the other hand, estrogen replacement
therapy and high-dose niacin can lower plasma Lp(a) levels (51). Lp(a) competes for the binding of
plasminogen to endothelial cells, which may contribute to the prothrombotic effects of this
lipoprotein (15). Lp(a) has been implicated in the regulation of PAI-1 expression in endothelial
cells, and shown to inhibit endothelial surface fibrinolysis, to attenuate plasminogen binding to
platelets, to be a possible attractant of macrophages in the atheromatous plaque, to be associated
with smooth muscle cell proliferation and to bind to plaque matrix components (63). Lp(a)
accumulates in atherosclerotic lesions, but it is not found in normal vessels (64). Lp(a) binds avidly
to the extracellular matrix and, once trapped, becomes susceptible to modifications by oxidative
processes and by the action of lipolytic and proteolytic enzymes (64). Hence, Lp(a) lipoprotein may
acquire a pathogenic profile on entering the arterial wall as a consequence of modifications effected
by factors operating in the inflammatory milieu of the atheromatous vessel (64).
Apolipoprotein A1
Apolipoprotein A1 is the major constituent of high density lipoprotein (HDL) and mediates efflux
of cholesterol from the peripheral cell membranes (65). In addition, ApoA1 activates lecithin-
cholesterol acetyl transferase, a key enzyme in the reverse transport of cholesterol from peripheral
tissues to the liver (65). ApoA1 concentration is mainly determined by genetic factors (65). Because
of the close association between apolipoproteins and serum lipids, measurement of ApoA1 has been
proposed as an important factor in predicting the risk of cardiovascular disease (65).
19
Homocysteine
Homocysteine is a sulfhydryl amino acid derived from the metabolic conversion of the essential
amino acid methionine (15,66 and Figure 3). The entry point of the pathway is the transport of
dietary methionine derived from protein food sources into the cellular space (67). It exists both in
free and protein-bound forms and is oxidized in plasma to the disulfides homocysteine-
homocysteine (homocystine) and homocysteine-cysteine (mixed disulfide). Free and protein-bound
homocysteine and its disulfides are globally referred to as total homocysteine (tHcy) or
homocyst(e)ine (66). About 70-80% of plasma homocysteine is bound to albumin, 20-30% is
oxidized to disulfides, and only approximately 1% is present as free homocysteine (66). The
intracellular metabolism of homocysteine occurs through enzymatic pathways that are dependent on
vitamins as cofactors or cosubstrates (Figure 3). There are two pathways of remethylation of
homocysteine to methionine and one pathway of trans-sulfuration to cysteine. In the remethylation
pathway catalyzed by methionine synthase, cobalamin acts as a cofactor and the methyl group is
donated by 5-methyl-tetrahydrofolate, the major form of folate in plasma, derived from the
reduction of 5,10-methylenetetrahydrofolate by methylenetetrahydrofolate reductase (MTHFR). In
the other remethylation pathway, which is active mainly in the liver, betaine is the methyl donor and
the reaction is catalyzed by betaine-homocysteine methyltransferase. In the trans-sulfuration
pathway, homocysteine is transformed by cystationine- -synthase (CBS) to cystathionine, with
pyridoxal-5`-phosphate, a vitamin B6 derivate, acting as a cofactor. Vitamin B6 is also necessary for
transformation of cystathionine to cysteine and alpha-ketobutyric acid (66). There are several
inherited disorders that lead to hyperhomocysteinemia (67). The most common is the 5-
methylenetetrahydrofolate reductase (MTHFR) polymorphism due to a point mutation on
chromosome 1, where folate-deficient individuals will develop hyperhomocysteinemia (67).
Cystathionine -synthase deficiency (homocystinuria), methionine synthase deficiency, and
MTHFR enzyme deficiency are rare autosomal recessive disorders that are associated with
20
hyperhomocysteinemia and vascular thrombosis (67). Moderate elevations of plasma tHcy levels
are not found in all subjects with genetic defects causing a 50% reduction of the corresponding
enzyme activities, indicating that their phenotypic expression can be influenced by other factors
(66). Major determinants of plasma homocysteine levels include diet (vitamin B12, B6 and folate
intake) and renal function (68,69). The plasma levels of homocysteine increase with age, are lower
in fertile women than in men and increase after menopause (66,69). Other, less well established
determinants of hyperhomocysteinemia are cigarette smoking, hypercholesterolemia, lack of
physical exercise, coffee and alcohol consumption (66). Drugs interfering with the metabolism of
folate (e.g. methotrexate and various anticonvulsants), cobolamin (e.g. nitrous oxide), and of
vitamin B6 (e.g.theophylline), can cause moderate hyperhomocysteinemia (66). Estrogens,
tamoxifen, penicillamine and acetylcysteine reduce plasma homocysteine levels (66). An enzyme
immunoassay has become commercially available, which allows homocysteine measurements in
non-specialized clinical laboratories (70).
The adverse effects of homocysteine include vascular endothelial injury, smooth muscle
proliferation, oxidation of low-density lipoprotein cholesterol, and induction of a prothrombotic
vascular endothelial microenvironment (71,72). Homocysteine has growth-promoting and collagen
production-stimulating effects on vascular smooth muscle cells and inhibitory effects on endothelial
cell growth (73-75). Homocysteine induces oxidative stress and activates matrix metalloproteinases
(76). Homocysteine alters the normal antithrombotic phenotype of the endothelium by enhancing
the activities of factor XII and factor V and depressing the activation of protein C (72).
Homocysteine also inhibits the expression of tissue factor, and suppresses the expression of heparan
sulfate by the endothelium (72). Homocysteine has been shown to reduce binding sites for tPA in
cultured endothelial cells and reduce tPA activity by as much as 60% (77). In vitro data report a
decrease in fibrinolytic activity in the presence of homocysteine due to increased binding of Lp(a)
to fibrin and stimulation of PAI-1 production in endothelial cells (78,79); in cultured cells, however,
homocysteine does not alter the secretion of PAI-1 (79). In vitro, homocysteine inhibits cell surface
21
expression of thrombomodulin (80). There are several possible biologic mechanisms whereby an
elevated homocysteine level might exert a deleterious effect on vascular function. Homocysteine
may have pro-oxidant effects, it can diminish nitric oxide-mediated vasodilatation, and it may
promote thrombosis or impede fibrinolysis (69). Less frequently discussed is the possibility that
elevated homocysteine may also diminish adenosine formation (81): adenosine being an important
cardiac vasodilator as well as a vasoconstrictor in the renal vascular bed (82).
The mechanism(s) by which hyperhomocysteinemia might contribute to atherogenesis and
thrombogenesis are incompletely understood. Recently, Jakubowski (83) proposed a mechanism of
cellular damage mediated by homocysteine that could lead to cardiovascular disease. Homocysteine
thiolactone, one of homocysteine´s metabolites, is chemically reactive and acylates free amino
groups of lysine residues, resulting in protein modification and cellular damage. Homocysteinylated
proteins loose their biologic activity, and homocysteine-thiolactone is known to be toxic to
endothelial cells, factors that may be involved in the early development of atherosclerosis. This
mechanism is very specific, because homocysteine-thiolactone can be produced only from
homocysteine, and does not require concentrations higher than the physiologic concentrations of
homocysteine (83).
22
Remethylation Remethylation
Methionine
THF Dimethylglycine
AdoMet
R
RCH3
Methylene-THF B12
AdoHcy
Methyl-THF Betaine Betaine
MS
Homocysteine
BHMT
MTHFR
Serine
CBSB6
Cystathionine
-cystathionaseB6
Cysteine
Trans-sulfuration
Figure 3. Schematic representation of homocysteine metabolism. THF: tetrahydrofolate; MTHFR: methylenetetrahydrofolate reductase; MS: methionine synthase; AdoMet: S-adenosylmethionine;AdoHcy: S-adenosylhomocysteine; BHMT: Betaine homocysteine methyltransferase; CBS: cystathionine- -synthase; B12: vitamin B12; B6: vitamin B6. Adapted from Reference 66 with permission.
23
MTHFR
5,10-methylenetetrahydrofolate reductase (MTHFR) is a folate-dependent enzyme and is essential
for the remethylation of homocysteine (84) (Figure 3). In 1988, Kang et al (85) described a
thermolabile variant of MTHFR that is associated with decreased enzyme activity and mildly
elevated plasma homocysteine levels. The responsible mutation in the MTHFR gene, a cytosine (C)
thymine (T) substitution at base pair 677 leading to the exchange of an alanine to a valine, was
identified by Frosst et al in 1995 (86). A modification of the effect of this mutation by plasma levels
of folate has been described, indicating that an increased level of total plasma homocysteine (tHcy)
as a consequence of the mutation occurs only if plasma levels of folate are low (87). Brattstrøm et al
(68) reported from a meta-analysis of 23 studies that the prevalence of the TT genotype varied
between 5.4% and 16% in the different groups of control subjects and between 6.5% and 29.7% in
the different groups of patients. In the meta-analysis by Klerk et al (88) the TT genotype varied
between 3.2 % and 30.2 % (mean 10.2 %) among control subjects.
The metabolic syndrome
There are 6 major components of the metabolic syndrome: abdominal obesity, atherogenic
dyslipidemia, elevated blood pressure, insulin resistance ± glucose intolerance, a proinflammatory
state, and a prothrombotic state (89) or low fibrinolytic activity (90). In addition, research shows
that other components not routinely measured commonly aggregate with the major components:
elevated apolipoprotein B, small LDL particles, elevated C-reactive protein, and variation in
coagulation factors (eg, elevated PAI-1, VWF and fibrinogen) (89,91). At least 3 organizations have
recommended clinical criteria for the diagnosis of the metabolic syndrome; the World Health
Organization (WHO), the American Association of Clinical Endocrinologists (AACE) and The
National Cholesterol Education Program´s Adult treatment Panel III (ATP III) (92). The clinical
criteria proposed by ATP III are abdominal obesity, elevated triglycerides, low HDL cholesterol,
24
high blood pressure and high fasting glucose (89). When 3 of 5 of the characteristics are present, a
diagnosis of metabolic syndrome can be made (92). Explicit demonstration of insulin resistance is
not required for diagnosis: however most persons meeting ATP III criteria will be insulin resistant
(92). Insulin resistance was defined as 1 of the following: type 2 diabetes, impaired fasting glucose
(IFG), impaired glucose tolerance (IGT), or for those with normal fasting glucose values (<110
mg/dL or < 6.1 mmol/L), a glucose uptake below the lowest quartile for background population
under hyperinsulinemic, euglycemic conditions. The conference on the definition of the metabolic
syndrome identified 3 potential etiologic categories: (1) obesity and disorders of adipose tissue, (2)
insulin resistance, and (3) a constellation of independent factors (eg, molecules of hepatic, vascular,
and immunologic origin) that mediate specific components of the syndrome (89). Adipose tissue is
recognized as a source of several molecules that are potentially pathogenic: excess non-esterified
fatty acids, cytokines (tumor necrosis factor- ), resistin, adiponectin, leptin, and PAI-1 (89).
Visceral adipose tissue may be particularly active in producing several of these factors (89).
However, the mechanisms underlying the association between abdominal obesity (particularly
visceral obesity) and the metabolic syndrome are not fully understoood and likely are complex (89).
The second pathogenic category, insulin resistance, is widely believed to be at the heart of the
metabolic syndrome, even though there is as yet little clinical trial evidence that a reduction in
insulin resistance will substantially improve any of the components of the metabolic syndrome
other than glucose intolerance (89). Thus, the mechanistic link between insulin resistance and most
of the components of the metabolic syndrome remains unclear (89). Although insulin resistance is
strongly associated with atherogenic dyslipidemia and a proinflammatory state, it is less tightly
associated with hypertension and the prothrombotic state (89). Much of the heterogeneity in the
manifestation of the metabolic syndrome may therefore be due to the fact that many of the
component factors are regulated independently of insulin resistance (89). Lipoprotein metabolism is
regulated by genetic factors as well as by diet composition, and both can worsen atherogenic
dyslipidemia (89). Blood pressure regulation is similar complex and affected by dietary factors,
25
physical activity, and renal/adrenal organ function (89). Other important modifiers also influence
clinical expression of the metabolic syndrome. For example, physical inactivity promotes the
development of obesity and modifies muscle insulin sensitivity (89). Aging is commonly
accompanied by a loss of muscle mass and by an increase in body fat, particularly accumulation of
fat in the abdomen; both changes can increase insulin resistance (89). Moreover, recent studies
suggest that aging is accompanied by specific defects in fatty acid oxidation in muscle, also
enhancing insulin resistance (89). Men with the metabolic syndrome are at increased risk for
coronary heart disease (93).
Insulin and proinsulin
Insulin, which is produced by cells in pancreatic islets of Langerhans, consists of 51 amino acids
contained within two peptide chains: an A chain with 21 amino acids and a B chain with 30 amino
acids (94 and Figure 4). A precursor molecule, preproinsulin, is produced in the endoplasmic
reticulum and cleaved by microsomal enzymes to yield proinsulin almost immediately after its
synthesis. Proinsulin is transported to the Golgi apparatus, where packaging into clathrin-coated
secretory granules takes place. Proinsulin consists of a single chain of 86 amino acids containing 3
disulphide bridges, and includes the A and B chains of the insulin molecule plus a connecting
segment of 35 amino acids. Maturation of the secretory granules is associated with loss of the
clathrin coating and conversion of proinsulin to insulin and C-peptide by proteolytic cleavage. Two
endoproteases, proconvertase 2 and 3, cleave proinsulin at the AC and BC junctions. Further
processing by carboxypeptidase H results in the removal of the two pairs of dibasic amino acids
located at the two cleaved junctions to give the des forms of partially processed proinsulin, as
shown in Figure 4 (94). C-peptide and insulin are produced when enzymatic cleavage is complete at
both junctions. As a small amount of proinsulin produced by the pancreas escapes cleavage partially
or totally, normal mature secretory granules contain insulin and C-peptide in equimolar quantities,
plus 2 to 6 % of intact and split proinsulins (94). Approximately 50 % of insulin is removed in a
26
Figure 4. Processing of pro-insulin to insulin and C-peptide.
Adapted from D. Chevenne et al (94) with permission.
27
single pass through the liver, while proinsulin is mainly eliminated by the kidneys (94). Therefore,
the half-live for proinsulin is longer (90 min versus 3-5 min for insulin) (94). This allows
proinsulins to accumulate in the blood where they account for 15-20 % of the total amount of
insulin and proinsulins in the basal state (94), whereas in noninsulin dependent diabetes mellitus
circulating proinsulin is known to be disproportionately elevated compared to insulin (95,96).
As proinsulin conversion has a preferred sequential route, with cleavage at the BC junction
occurring first, the two major proinsulins in plasma are intact proinsulin and des 31,32 proinsulin,
far exceeding other barely detectable 65,66 products (94). Proinsulins have 5-10 % of the
bioactivity of insulin (94).
Insulin is the master regulator of glucose and lipid metabolism (97,98). Insulin increases the uptake
of glucose in muscle and fat and inhibits hepatic glucose production, thus serving as the primary
regulator of blood glucose concentration (97,98). Insulin also stimulates cell growth and
differentation, and promotes the storage of substrates in fat, liver and muscle by stimulating
lipogenesis, glycogen and protein synthesis, and inhibiting lipolysis, glycogenolysis and protein
breakdown (98). Insulin has recently been shown to exert an anti-inflammatory effect on human
aortic endothelial cells in vitro and mononuclear cells in humans in vivo (99). These effects were
reflected in the suppression of the expression of intercellular adhesion molecule-1 and monocyte
chemoattractant protein-1 and in the intranuclear binding activity of nuclear factor- B (which
induces the transcription of proinflammatory genes like TNF- and IL-6) in human aortic
endothelial cells, with a concomitant fall in plasma concentration of PAI-1 (99). Moreover, insulin
has the ability to induce the release of nitric oxide (NO) and to enhance the expression of
constitutive nitric oxide synthase (NOS) (100). The ability of insulin to induce an acute release of
nitric oxide from endothelial cells and to increase the expression of nitric oxide synthase in these
cells is associated with an acute vasodilatory effect (100). Two other proinflammatory transcription
factors, activator protein-1 and early growth response gene-1 (Egr-1), were also suppressed, along
with their respectively regulated genes, matrix metalloproteinase (MMP)-2, MMP-9, and tissue
28
factor (99). Thus, the action of insulin may not only be anti-inflammatory in general; it may be
particularly relevant to atherosclerotic plaque rupture in which MMPs play an important role: in the
initiation of thrombosis, in which tissue factor is a major trigger; and fibrinolysis, which is inhibited
by PAI-1 (99).
Leptin
Leptin circulates as a 16-kDa protein and is partially bound to plasma proteins (101). An additional
pool of leptin is bound to tissue-binding sites and is likely to contribute to the maintenance of
steady-state plasma leptin levels (101). Leptin is synthesized mainly by white adipose tissue, but
also in placenta, ovary, gastric fundic mucosa, skeletal muscle, bone marrow and mammary
epithelium, and is cleared by the kidneys (101,102). Structural analysis indicates that leptin is
similar to cytokines (101,102). The long form leptin receptor is present in hypothalamic regions,
whereas the short leptin receptor isoforms are expressed in choriod plexus, vascular endothelium,
platelets, macrophages, lymphocytes and peripheral tissues, such as kidney, liver, heart, lung, small
intestine, pancreas, adrenal gland, spleen, skeletal muscle and gonads (101,102,103). Leptin inhibits
appetite and weight gain by decreasing orexigenic and increasing anorexigenic peptide expression
in the hypothalamus (101). Plasma leptin levels correlate with fat stores and respond to changes in
energy balance (101). Leptin levels are regulated by insulin, glucocorticoids, testosterone,
oestrogens, endotoxin, cytokines, insulin-like growth factor-1 (IGF-1), growth hormone,
somatostatin, catecholamines, alcohol and smoking (102). Furthermore, it has been shown that
leptin is related to platelet aggregation (104), PAI-1 production (105), endothelial nitric oxide
release (106), vascular calcification (107), angiogenesis (102) and stimulates free fatty acid
oxidation (102). In lean persons, roughly 50% of leptin is present in the bound form, whereas
mostly free leptin is present in the circulation of obese people (103). Hyperleptinemia is thought to
be indicative of leptin resistance, which may play a role in the development of obesity (101). Leptin
29
levels increase acutely during inflammation and regulate T-cell responses, polarizing T-helper cells
towards a T-helper 1 phenotype (108). Thus increased leptin production, during obesity, may exert
a proinflammatory influence (108).
Overview of prospective studies
tPA
A meta-analysis on all seven available prospective cohort studies in general populations of tPA and
risk of myocardial infarction (2119 cases and 8832 controls in total) showed a combined odds ratio
of 2.18 (1.77-2.69) in the top third versus those in the bottom third of baseline tPA values after
adjustment for age and sex only, and this fell to 1.47 (1.19-1.81) after further adjustment for
smoking, blood pressure, blood lipids and body mass index (38). The mean weighted age at entry
was 54 years and mean weighted follow-up was 8 years (38). All studies used enzyme-linked
immunoassays, and all used plasma samples.
PAI-1
A meta-analysis of the five previous prospective studies of PAI including our own study (109 - 112)
involved a total of 833 coronary heart disease cases and 3122 controls (38). They had a mean
weighted age at entry of 58 years and mean weighted follow-up of 5 years. One study measured
latent and free, active PAI-1 (112), two measured PAI-1 mass (109 and our study I), one used
chromogenic assay of PAI-1 activity (110), and one did not specify the assay method used (111).
There was no significant heterogeneity among the five seperate studies, and a combined analysis
yielded an odds ratio of 0.98 (0.53-1.81) in individuals in the top third versus those in the bottom
third of baseline PAI-1 values (38).
30
von Willebrand Factor
Danesh et al (47) has updated an earlier meta-analysis of prospective studies of VWF (which adds
2445 cases of coronary heart disease to the previous total of 1524 cases) and found an odds ratio of
1.23 (95 percent confidence interval, 1.14 to 1.33), which is propably weaker than the previous
estimate of about 1.5 (95 percent confidence interval, 1.1 to 2.0) (46). In the recently published
PRIME study (113) including 296 cases and 563 controls, VWF was an independent risk factor for
fatal and nonfatal myocardial infarction. Individuals with plasma VWF levels in the highest quartile
showed a 3.04-fold increase in the risk of fatal and nonfatal myocardial infarction compared with
those in the lowest quartile (95% CI, 1.59 to 5.80) after adjustment for body mass index, total
cholesterol, HDL cholesterol, systolic blood pressure, smoking, alcohol, and diabetes. After further
adjustment for inflammatory variables (fibrinogen, C-reactive protein, tumor necrosis factor – and
interleukin –6) the odds ratio in the highest quartile increased to 3.40 (95% CI, 1.65 – 7.02).
Thrombomodulin
The ARIC study including 258 cases and 753 controls found a strong inverse association of soluble
thrombomodulin with incident coronary heart disease where rate ratio of the highest quintile of
soluble thrombomodulin compared with the lowest quintile was 0.29 (96% CI 0.15-0.57) after
adjustment for age, sex, etnic origin, study center, smoking, systolic blood pressure, total
cholesterol, HDL cholesterol, triglycerides, diabetes, and body mass index (114). However, in the
prospective PRIME study (113) there was no association between plasma thrombomodulin and
coronary heart disease.
Dehydroepiandrosterone sulfate (DHEAS)
Several prospective studies have examined the relationship between DHEAS levels and
cardiovascular disease, but results have been inconsistent and conflicting, generating much debate
and controversy on this issue (55 - 57,115,116).
31
Apolipoprotein A1
A number of prospective studies have shown the value of plasma ApoA1 in predicting coronary
heart disease (65,117-120).
Lp(a)
Prospective studies of Lp(a) as a cardiovascular risk factor have yielded conflicting results, but a
meta-analysis including 18 prospective cohort studies (4044 cases) showed that the relative risk of
coronary heart disease comparing top and bottom thirds of baseline measurements was 1.7
(p<0.0001), without significant heterogeneity (121). The interpretation of these data is however
complicated by the different methodologies used in measuring plasma Lp(a) and the lack of
standardization (122).
Insulin
A meta-analysis of 17 studies on hyperinsulinemia and risk of cardiovascular disease (1639 cases)
resulted in an estimated summary relative risk of 1.18 (95% CI 1.08 to 1.29) (123). The relationship
between hyperinsulinemia and cardiovascular disease was modified by ethnic background (stronger
longitudinal relationship in white than in non white populations) and by type of insulin assay
involved (123).
Proinsulin
Three prospective studies have found proinsulin to be an independent predictor of coronary heart
disease (124-126). Dunder et al (124) included 251 men cases and 1108 men control men during
28.7 years follow-up and found a hazard ratio of 1.46 (95% CI 1.20 – 1.76) for development of fatal
and nonfatal myocardial infarction. Zethelius et al (125) included a population based cohort of 874
men with a follow-up of 27 years. Intact proinsulin was an independent predictor of coronary heart
32
disease mortality with hazard ratio 1.31 (95% CI 1.12 to 1.53). Yudkin et al (126) reported that the
sum of proinsulin-like molecules predicted the incidence of coronary heart disease with a
standardised odds ratio 1.54 (95 % CI 1.07 to 2.20) after adjustment for age and body mass index in
a cohort of 1181 non-diabetic men 50-64 years old during 10-14 years follow-up.
Leptin
Only limited prospective data are available for leptin as a cardiovascular risk factor (127,128). In
our previous report (129), in which we used other sets of variables and statistical models, leptin was
found to be an independent risk marker for a first myocardial infarction. Couillard et al. (127) found
in a group of 86 non-diabetic men matched for age, body mass index, smoking, and alcohol intake,
that hyperleptinemia was not an independent risk factor for ischemic heart disease, defined as effort
angina, coronary insufficiency, nonfatal myocardial infarction, or coronary death. In the larger
prospective WOSCOP study (128) including 377 men cases, was plasma leptin a risk factor for
coronary heart disease independent of body mass index, age, lipids, systolic blood pressure, and
fasting glucose.
Homocysteine
Wald et al (130) reported on 16 prospective studies including 3144 cases with death from ischaemic
heart disease or non-fatal myocardial infarction a summary odds ratio of 1.23 (95% CI 1.14 to 1.32)
for a 5 µmol/L increase in serum homocysteine, adjusted for age, sex, smoking, cholesterol
concentration, and blood pressure. An individual patient data meta-analysis of observational studies
of tHcy up to January 1999 and cardiovascular disease by the Homocysteine Studies Collaboration
(131) reported on 12 prospective studies including 1968 cases with nonfatal or fatal myocardial
infarction or occlusive coronary artery disease. After adjustment for age, sex, smoking, total
cholesterol levels, systolic blood pressure and regression dilution in the prospective studies, a 25%
lower usual (corrected dilution bias) homocysteine level (about 3 µmol/L) was associated with an
33
11% (OR 0.89; 95% CI 0.83-0.96) lower risk of ischemic heart disease. However the variation in
the level of control for confounding factors in the studies included in these reviews raises the
possibility that the combined relative risk estimates from these meta-analyses may not be reliable.
O´Leary et al (132) also concluded that failure to adjust for creatinine in meta-analysis of
homocysteine and cardiovascular disease could result in an overestimate of risk.
MTHFR
Klerk et al (88) conducted a meta-analysis of individual participant data from all observational case-
control studies (retrospective or nested case-control) with data on the MTHFR 677 C>T genotype
and coronary heart disease as an endpoint. Data were obtained from 40 (34 published and 6
unpublished) observational studies, involving a total of 11162 cases and 12758 controls. Individuals
with the MTHFR 677 C>T genotype had a 16% (OR 1.16; 95% CI 1.05 to 1.28) higher risk of
coronary heart disease compared with individuals with the CC genotype. There was a significant
heterogeneity between the results obtained in European populations, compared with the North
American populations, which might largely be explained by interaction between MTHFR 677 C>T
polymorphism and folate status (88). There was also significant heterogeneity between the pooled
estimates of prospective and retrospective studies. The pooled OR for coronary heart disease for the
TT genotype compared with the CC genotype was 0.86 (95% CI 0.67 to 1.10) for prospective
studies (5 studies involving 1288 cases and 1749 controls), and 1.21 (95% CI 1.10 to 1.33) for
retrospective studies (35 studies involving 9874 cases and 11009 controls).
34
AIMS
The general aims of the present dissertation were:
- To evaluate whether the biomarkers: tPA, PAI-1, VWF, TM, DHEAS, ApoA1,
homocysteine and MTHFR could improve the prediction of subjects at increased risk for a
first myocardial infarction in addition to established cardiovascular risk factors (I-II).
- To investigate the summarised importance of haemostatic and metabolic variables (insulin,
lipids including lipoprotein (a) (Lp(a)) and leptin) in predicting first myocardial infarction,
and to explore potential synergistic interactions among these variables (III).
- To test the hypothesis that a first myocardial infarction leads to increased plasma
homocysteine concentrations and that the association between homocysteine and myocardial
infarction is greater at follow-up compared to baseline (IV).
35
MATERIAL AND METHODS
Study population
When Northern Sweden applied for membership in the WHO MONICA study in 1984, the high
prevalence of cardiovascular disease in the region had become a great concern in the population as
well as among policy makers and healthcare providers (5). A Västerbotten County Council task
force was selected, representing both preventive medicine and public health, in order to advise in
the planning and implementation process of a coming community-oriented cardiovascular disease
prevention programme. In early 1985 both the monitoring Northern Sweden MONICA Project and
the preventive Västerbotten Intervention Program (VIP) was launched (133). The VIP health survey
was designed to fit the MONICA criteria so that it would be possible to refer to MONICA data
when evaluating the community intervention programme (134).
The Västerbotten Intervention Program
In the Västerbotten Intervention Program (VIP) intended for health promotion of the population in
the county of Västerbotten (approx. 254,000 inhabitants), all men and women were invited to a
health survey at their local primary health care center the year they became 30, 40, 50, and 60 years
of age (135). Between January 1, 1985 and September 30, 1994, 31 680 persons participated in the
VIP health surveys. Selection bias in the VIP study was examined in 1992 and 1993 (136,137).
During those two years a total of 24 870 eligible persons were at the appropriate ages (30, 40, 50,
60 years). Of those, 14 188 took part in the health survey (57%). In order to get information about
age, employment, education level and socio-economic group of the non-participants of the VIP
survey, a record linkage was made between the data from all invited and the 1990 population and
housing census. Overall, the differences were small between participants and non-participants, with
marginal differences in socio-economic groups and educational levels. However, the youngest
group (30 years) and the unemployed were less prone to participate (46.0% and 42.5% participants,
respectively). To estimate the overall risk factor status among the VIP participants, a comparison
36
was made against a reference population. In the 1990 and 1994 MONICA surveys a random sample
of Västerbotten County population (aged 25-64 years) was screened. The participation rate was
more than 75%. Data from the two MONICA surveys were pooled and used as a reference group
for risk factor comparison. There were no significant differences between VIP and MONICA
participants in mean BMI and smoking status. The mean level of total cholesterol was lower among
the VIP participants. However, the MONICA participants had lower blood pressure (except for
diastolic blood pressure in men) (136,137).
The WHO MONICA study
The WHO MONICA Study started in the beginning of the 1980s in 26 countries (138). The
objective of the study was to measure trends in cardiovascular mortality and disease (3,138). To
allow comparison of rates between different populations, data collection should be done with
uniform diagnostic criteria and quality assurance procedures. The Northern Sweden MONICA
Study started 1985 in Västerbotten and Norrbotten counties, with a total population of 510 000 (291
000 aged 25-64 years) (136). Population surveys for cardiovascular risk factors were performed in
1986, 1990, 1994 and 1999. At each survey, a random sample (stratified for age and sex) of 2000
individuals aged 25-64 years was invited and more than 75% participated. Between January 1, 1985
and September 30, 1994, 4725 participated in three MONICA screening surveys.
Baseline examination
Baseline examination for cardiovascular risk factors was performed in the VIP and MONICA
surveys and included measurement of blood pressure, height, weight and cholesterol. Participants in
both surveys were requested to donate blood samples to be stored at the Northern Sweden Medical
Research Bank for future research purposes. More than 90% donated blood samples. Participants
were also asked to fill in a questionnaire with items on social background, lifestyle factors including
37
diet, smoking habits, medical history and intake of drugs among other. Informed consent was
collected from the start of the project and all projects were reviewed and approved by the local
research ethics committee (135).
Case definition and exclusion
A diagnosis of myocardial infarction was confirmed if the event met World Health Organisation
MONICA criteria, definition 1 (3) (for relevant section of MONICA Manual see URL:
www.ktl.fi/publications/monica/manual/part4/iv-1.htm). A definite myocardial infarction meets
one of the following criteria: definite serial ECG progression (defined by the Minnesota criteria) or
at least one cardiac enzyme level more than twice the upper limit of normal in the local laboratory
either with typical symptoms and abnormal ECG or with an ECG progression labelled probable and
atypical symptoms. For fatal myocardial infarctions we also accepted diagnoses based on
necropsies and on deaths confirmed by records as being due to coronary heart disease (ICD-9 411-
414). Silent myocardial infarctions found on routine examination were not included, as they could
not be assigned an accurate date of occurrence.
Case findings are based on reports from hospitals and general practitioners and on screening of
hospital discharge registers and all death certificates. Annually, computer-based lists of discharge
diagnoses from acute-care hospitals and nursing homes are screened for additional cases (138).
Only cases with a first definite myocardial infarction and no known cancer were included.
Accordingly, cases were excluded if they had been registered for a previous myocardial infarction
or stroke according to the MONICA registry or cancer according to the regional cancer registry. If
the questionnaires or patient records revealed information of a possible prior stroke, myocardial
infarction or cancer, the diagnosis was validated and if appropriate, the case was excluded.
38
Referent definition and exclusion
Two referents were randomly selected amongst the participants in the VIP or MONICA surveys
who had donated a blood sample to the Northern Sweden Medical Research Bank. They were
matched for sex, age (± 2 years), date of health survey (± 1 year), type of survey (VIP or MONICA)
and geographical region (same screening center). Referents were excluded if they had died or had
moved out of the MONICA region before September 30, 1994, if they had reported a prior
myocardial infarction or stroke according to the Northern Sweden MONICA Incidence Registry or
on the survey questionnaire, or if myocardial infarction or stroke might have occurred before the
health survey and could not definitely be excluded based on the case record (139).
Case and referent finding
All cases and referents were collected from the VIP and MONICA study base and fulfilled the
inclusion and exclusion criteria stated above. Two referents were identified and matched to each
case according to the principles described (see Figure 5 for a schematic overview).
Study I - III
According to the VIP health surveys and the three MONICA screening surveys during January 1
1985 and September 30, 1994, a total of 243 myocardial infarction cases were reported in the
MONICA incidence registry (139) (Figure 5). Ninety-two fulfilled the following two criteria: 1)
The cases were registered in the Northern Sweden MONICA Incidence registry during the period of
January 1, 1985 to September 30, 1994, and 2) The cases participated in the VIP or MONICA
health surveys prior to the myocardial infarction event, and on those occasions had donated blood
samples to the Northern Sweden Medical Research Bank. Individuals were excluded if they had a
cancer diagnosis according to the regional cancer registry or if the blood sample was inadequate for
analysis. For study I, 78 cases remained after exclusion. 156 matched referents were identified.
39
In study II the presence of the mutation C677>T in the MTHFR was determined for 69 of the 78
cases of myocardial and 129 of their referents, from which DNA for analysis was available.
In study III women were excluded due to few cases and because of significantly different leptin and
Lp(a) levels compared to men. Consequently, study III comprised of 62 men cases and 124 men
referents.
Study IV
This is a follow-up study of the 78 participants developing a first myocardial infarction and their
referents. The first health surveys for the participants in the present study occurred between April
1988 and November 1993, and the follow-up examinations were performed between July 1997 and
February 2001. The time interval between the two screening episodes had a mean of 8.4 1.8 years
(SD) for cases and 8.7 1.7 years (SD) for referents (unpaired t-test: p=0.5). Fifty cases had their
fasting total plasma homocysteine level repeated at follow-up. Of the 28 cases not participating in
the follow-up survey, 24 had died in the interim, 1 had severe dementia, 1 had terminal cancer, 1
had relocated outside the catchment area and 1 was lost to follow-up. Cases were matched with one
referent subject for age (± 2 years), sex, date (± 1 year), type (MONICA or VIP) of health survey,
and geographical region. Three cases had no matching control subjects in the follow-up
examination, and 7 cases had two matching referent subjects. Two additional referent subjects were
used without corresponding cases. Thus, for the conditional logistic regression analysis, 40 cases
with one referent and 7 cases with two referents were included in study IV.
40
Measurements of body mass index and blood pressure
Subjects were weighted without shoes in light indoor clothing. Height was measured without shoes.
Body mass index (BMI) was calculated as (weight in kg)/(height in m2). In the MONICA project
blood pressure was measured twice in every person after a five-minute rest with the subject in the
sitting position using the random zero method (Hawksley Gelman Ltd, Lancing UK) (140). The
mean value of the two measurements was used in the present study. In the VIP survey, blood
pressure was measured after 5 minutes rest in recumbent position. An adjustment was made to the
sitting posture based on comparison between sitting and recumbent position in 1850 subjects from
the VIP health survey (139)
41
Initialinclusion
Cases:- MI in MONICA registry Jan 1, 1985- Sep 30 1994
- Blood sample in the Northern Sweden Medical Bank
92
Referents: - 2 randomly selected referents/case, matched for sex, age (±2years) - No MI according to MONICA Jan 1, 1985 – Sep 30, 1994 - Blood sample in the Northern Sweden Medical Bank
Exclusion
Cases:
- MI according toMONICA, but inaddition, previous MIbefore Jan 1, 1985.
- Cancer according to theNational Cancer Register
- Missing blood samples
Referents:
- Dead before Sep 30, 1994- Cancer according to the regional
cancer registry- Moved out from the province
before Sep 30, 1994- If statement of “prior MI” in
survey questionnaire or if, frompatient file, a MI/stroke beforesurvey not could be excluded
- 6
- 6
- 2
86
80
78 156 Cases Referents
Study base: All participants in the Västerbotten Intervention Program or the Northern Sweden MONICA surveys
Figure 5. Adapted from reference 139 with permission.
42
Estimations of smoking status, presence of diabetes and hypertension
This information was obtained from the self-reported questionnaire answered at the health
screening. Smokers were defined as those who reported smoking cigarettes, cigars, or pipe on a
daily basis. Non-smokers were those who reported occasional smoking or never had smoked (139).
Presence or absence of diabetes was based on the self-reported data. Reported hypertension was
defined as having ever received information from a physician or nurse about having high blood
pressure. Anti-hypertensive medication was defined as treatment with blood pressure lowering
drugs within 14 days prior to screening. Hypertension was defined as systolic blood pressure 160
mmHg and/or diastolic blood pressure 95 mmHg and/or reported use of antihypertensive
medication during a period of 14 days before the health survey.
Blood sampling
The 20 ml whole blood sample was taken after four hours of fasting (20%) or on the morning after
overnight fasting (80%) in the VIP and MONICA cohorts. Subjects in the MONICA surveys, in
addition, had been instructed not to use tobacco and to avoid strenuous physical activity before the
examination. The blood sample is divided into 10 subsamples consisting of six plasma, two
leucocyte (buffy coat) and two erythrocyte samples, each containing 1.5 ml (135). Plasma was
obtained by centrifugation at 1500g for 15 minutes, aliquoted, and was initially stored frozen at -
20° C and then transferred to -80° C at the Medical Biobank at Umeå University Hospital until
analysis. In some instances, samples were stored at -20˚ C for up to 1 week and then transferred to -
80˚ C. Venous blood samples for hemostatic assays, DHEAS, insulin variables, apolipoprotein A1,
apolipoprotein B, Lp(a), leptin, homocysteine, MTHFR, creatinine and albumin were drawn, with a
minimum of stasis in sitting position, into evacuated glass tubes (Venoject) containing 1/100
volume of 0.5 mmol/L EDTA. The organization of the bank includes specially trained staff and an
organization of standardized transport, storage, and security facilities. For DNA handling a
43
specialized laboratory were established (135). Blood specimens from cases and referents were
analyzed in triplets of one case and two referents, the position was varied at random within each
triplet to avoid systemic bias and interassay variability. The investigators and laboratory staff had
no knowledge of case and referent status.
Measurement of serum cholesterol,
In the VIP survey serum cholesterol was measured by enzymatic methods using Reflotron bench-
top analyzers (Boehringer Mannheim GmbH Diagnostica, Germany) at each health survey center at
the time for the screening. The mean interassay coefficient of variation (CV) was 2.6%. An
enzymatic method (CHOD-PAP, Boehringer Mannheim GmbH Diagnostica, Germany) performed
at Umeå University hospital was used in the MONICA survey. To evaluate the two methods 180
subjects were analyzed with both benchtop analyzer and the enzymatic method. The mean value for
each method differed by 0.04 mmol/L and the correlation coefficient between the methods was
0.90. Total cholesterol values were adjusted based on these results, using the enzymatic method as
standard (137).
Laboratory procedures
Measurement of fibrinolytic factors
The mass concentration of tPA and PAI-1 in plasma were determined with an ELISA (25). Reagent
kits (Imulyse) were purchased from Biopool AB. For tPA mass concentration, the CV at 8 µg/L was
9.5% in our hands (n = 34) and 10% according to the manufacturer. For PAI-1 mass concentration,
the CV is 9% according to the manufacturer.
Measurement of von Willebrand factor, soluble thrombomodulin and DHEAS
44
VWF was measured with an ELISA (141) by use of reagents purchased from DAKO. The values
are expressed as percent of the value obtained in a pool of normal subjects (n = 20). For VWF, the
CV at a level of 138% was 11.7% in our hands (n = 41). TM was measured with an ELISA method
(142) purchased from STAGO, France. The interassay CV was below 8.6% (143). Plasma DHEAS
was measured directly in diluted plasma with a radioimmunoassay with an antiserum obtained from
Endocrine Sciences and raised against DHEA-SO4-17-oxime-BSA. 7-3H-DHEAS was used as a
tracer, and free and bound radioactivities were separated by means of ammonium sulfate
precipitation.
Measurement of apolipoprotein A-1, apolipoprotein B, Lp(a) and leptin
Apolipoprotein A1 was measured at a hospital laboratory with a commercial radioimmunoassay
research kit (RIA-100, KABI Pharmacia, Uppsala, Sweden). The interassay CV was 5.7%
according to the manufacturer. Apolipoprotein B was determined with our own enzyme-linked
immunosorbent assay (ELISA) (144). The interassay CV was 6.8%. The results correlated well
(0.97) with those of a previously used commercial radioimmunoassay method (RIA-100, Kabi
Pharmacia, Uppsala, Sweden). Lipoprotein(a) was measured by the specific protein(a) content with
our own ELISA technique (144). A catching monospecific polyclonal (a) antibody was used. The
results were identical (r = 0.98) whether a detecting monospecific antibody against Apo(a) or
against Apo B-100 was used. The mean interassay CV was 6.6% and 7.7% at Lp(a) concentrations
of 40 mg L-1 and 300 mg L-1, respectively. Leptin analysis was performed using a double-antibody
RIA with rabbit antihuman leptin antibodies, 125I-labelled human leptin as tracer, and human leptin
as standard (Linco Res., St Louis, MO, USA) (129). Interassay CV was 1.9% at low levels (< 5ng
mL-1) and 3.2% at high levels (10 – 15 ng mL-1).
45
Measurement of insulin, proinsulin and specific insulin
Insulin was measured using a microparticle enzyme immunoassay (MEIA) (Abbott Laboratories,
IL, USA) (129). The CV was 6.7% at the level of 7.9 mU L –1. The insulin assay measures total
immunoreactive insulin, which is comprised primarily of proinsulin and its conversion
intermediates.
The proinsulin level was measured using a highly sensitive two-site sandwich ELISA (145,146).
The assay is based on two monoclonal antibodies, a mouse anti-human C-peptide antibody (PEP-
001) and a mouse anti-human insulin antibody (HUI-001). The detection limit in human serum is
0.25 pmol/L. There was no cross-reactivity with human insulin and human C-peptide. However, the
four major proinsulin conversion intermediates reacted in various proportions of 65% to 99%. The
specific insulin level was measured in a similar manner using another sensitive two-site sandwich
ELISA (147). The assay is based on one monoclonal antibody with its epitope near the C-terminal
end of the B-chain (OXI-005) and one monoclonal antibody with its epitope centered around the A-
chain loop (HUI-018). The detection limit is 5.0 pmol/L. The specificity of the assay excludes intact
proinsulin, split(32-33), and des(31.32) proinsulin. There was a cross-reactivity with the less
frequently occuring split(65-66) proinsulin (30%) and des(64,65) proinsulin (63%).
Measurement of homocysteine, creatinine and albumin
In study II total plasma homocysteine was measured by high-pressure liquid chromatography using
electrochemical detection. The preparation of samples included reduction of disulfide bonds with
dithiothreitol and deproteinization with trichloracetic acid. In the concentration range 10-50 µmol/L
the interassay CV was 3.6%. In study IV total plasma homocysteine was measured using a
fluorescence polarization immunoassay on an IMx (Abbott Laboratories, Abbott Park, Il, USA)
(148). Inter- and intraassay coefficients of variation (CV) were 1.31 % and 1.42 % at a mean plasma
homocysteine level of 12.8 mol/L, and 2.10 % and 1.00 %, respectively at a mean plasma
46
homocysteine level of 25.7 mol/L. Plasma creatinine and plasma albumin concentrations were
determined using the Vitros DT60 II dry chemistry system (Ortho-Clinical Diagnostics, NJ, USA).
Genotyping
DNA was extracted according to a method published by Ma et al (149) after lysis of cells,
deproteinization with perchlorate, and extraction with chloroform and resin, using the Nucleon
DNA extraction kit (Nucleon Biosciences, Coatbridge, UK). The DNA samples were subjected to
amplification by the polymerase chain reaction, and restriction enzyme HinfI was used to identify
those with the point mutation C677>T in the gene for MTHFR, as described by Frostt et al (86).
Statistics
Mean values and standard deviations (SD) or frequencies for baseline cardiovascular risk factors
were calculated for cases and referents by unpaired t tests, Fisher´s exact test and chi-square tests as
appropriate (Study I - IV). Prevalences of alleles and genotype among cases and referents were
counted and compared by chi-square test with Hardy-Weinberg prediction (150) (Study II). Possible
relations between study variables were explored by Spearman or Pearson correlation analysis
(Study II, III). To test the relation between increasing levels of risk factors and the risk of
myocardial infarction, the sample was categorized into quartiles, tertiles or dichotomized by the
distribution of the referent values, or based on clinically relevant levels (Study I, II, III). A chi-
square test for trends was employed to assess relationships between different levels of the respective
variables and risk of myocardial infarction (Study I, II, III). Conditional logistic regression analysis
was used when estimating odds ratios (OR) and 95% confidence interval (CI) (Study I-IV) to
account for the matching variables and potential confounding factors simultaneously (151). Missing
values for categorical variables were treated as a separate category (omitted from tables) in the
analysis (Study I-IV). In the conditional logistic regression analysis Apo B was excluded as a
traditional risk factor due to high correlation with serum cholesterol (r=0.74) (Study I, III). Based
47
on the results of the Spearman correlation analysis and the univariate logistic regression analysis,
the variable hypertension replaced systolic and diastolic blood pressure, and proinsulin replaced
insulin and specific insulin, in the multivariate conditional logistic regression analysis (Study I, III,
IV). The presence of interaction was assessed by conditional logistic regression between high and
low plasma levels of tPA, ApoAI, Lp(a), leptin and proinsulin in relation to the risk of a first
myocardial infarction (Study III). Cut-off values were selected according to the distribution of the
referent values, and missing values were considered unexposed and thus assigned to the lower
category for tPA, PAI-1, VWF, TM, Lp(a), leptin and proinsulin, and the higher category for
ApoA1 and DHEAS (Study I, III). The empirical criterion of interaction is a departure from
additivity of effects of each of the risk determinants (152). Synergy index scores (SI) were therefore
calculated, which give the ratio of the combined effects to the sum of the effects of two risk factors
(153). The mathematical formula is as follows: SI = (OR ”high-high”-1)/(OR ”high-low” + OR
”low-high” – 2). A Synergy index score exceeding 1.0 indicates the presence of synergistic
interaction. All calculations were performed using the SPSS statistical program (Chicago, Il, USA)
version 6.1 (Study I-III) and version 11.0 (study IV) and STATA (College Station, TX, USA)
version 5.0 (Study III) and 7.0 on a Macintosh computer (Study III) and the EGRET software
package (SERC, Seattle, Wasington, USA) (Study I-IV). With a total of 78 cases and 156 referents,
it is estimated that for a statistical power of 80%, OR > 3.0 will be significant at the 5% level when
exposure prevalence is 10% and OR > 2.3 will be significant at the 5% levels when exposure
prevalence is 30% (Study I). With a total of 69 cases and 129 referents and a 5% prevalence of the
MTHFR mutation, for a statistical power of 80%, odds ratios above 4.3 for +/+ versus –/– and
above 2.4 for +/– versus –/– would be significant at the 5% level (Study II). With a total of 50 cases
and 56 referents, it was estimated that for a statistical power of 80%, a difference in total plasma
homocysteine concentration of 1.5 mol/L between the two groups at the first and the second
examination would be significant at the 5% level (study IV).
48
RESULTS
Study I
In this study, haemostatic factors (PAI-1, tPA, VWF and TM) and DHEAS were investigated as
predictors for a first myocardial infarction. Acute myocardial infarction events for the 78 cases
occurred on average 18 months after their participation in the health survey (median, 15 months).
Baseline characteristics for the 16 women and 62 men who developed a myocardial infarction and
for the matched controls are shown in Table 1
Table 1. Mean Baseline Characteristics for Patients and Referent Subjects by Use of an Unpaired tTest and Fisher's Exact Test for Comparison
Men Women
Patients Referents P Patients Referents P
Age, y 54.7 54.5 NS 55.1 55.1 NS
Smokers, % 46.4 29.9 0.041 30.8 19.4 NS
Diabetes, % 5.2 0.8 NS 20.0 0 0.034
History of hypertension, % 43.1 30.3 NS 53.3 12.5 0.009
BMI, kg/m2 27.1 25.9 0.031 28.7 24.5 0.006
Cholesterol, mmol/L 6.60 6.37 NS 7.33 6.47 0.051
ApoA1, mg/L 1054 1135 0.002 1109 1232 0.029
DBP, mm Hg 89.6 86.9 NS 87.9 83.3 NS
SBP, mm Hg 142.0 138.3 NS 148.4 132.9 0.01
tPA, µg/L 12.2 9.3 <0.001 13.3 8.3 <0.001
PAI-1, µg/L 15.1 11.4 0.041 17.3 10.0 0.015
VWF, % of normal 142 131 NS 162 134 0.044
TM, µg/L 45.5 40.0 NS 28.6 29.9 NS
DHEAS, µmol/L 4.03 4.30 NS 2.88 2.61 NS
DBP indicates diastolic blood pressure; SBP, systolic blood pressure.
49
Established cardiovascular risk factors such as smoking, hypertension, and diabetes were more
common in the cases, as were higher mean levels of body mass index, systolic and diastolic blood
pressures, and serum cholesterol concentrations, but lower mean concentrations of ApoA1.
Moreover, in the group with myocardial infarction, the mass concentrations of PAI-1, tPA, and
VWF were significantly higher, whereas TM and DHEAS did not differ compared with the
reference group.
Data for the total study population and the probability value for the test for trends across the
stratification are shown in Tables 2 and 3. High plasma levels of PAI-1, tPA, and VWF mass
concentrations, obesity and high levels of cholesterol were all associated with significant increases
in the risk of myocardial infarction. High levels of ApoA1 were associated with a markedly reduced
risk, whereas only nonsignificant trends for increased risk were seen for high levels of TM and low
levels of DHEAS.
50
Table 2. Relative Risk of Myocardial Infarction From a Matched Analysis of 78 Case-Referent Triplets With Conditional Logistic Regression and Adjustment for Traditional Risk Factors
Relative Risk Matched forAge and Sex (95% CI)
P for Trend*
Relative Risk for Model Including Diabetes, Smoking, Hypertension, BMI, Cholesterol, ApoA1, and tPA
(95% CI)
No history of diabetes
1.00 0.002 1.00
History of diabetes 12.74 (1.52–106.6) † 7.90 (0.45–139.5)
Nonsmoker 1.00 0.021 1.00
Daily smoker 2.07 (1.12–3.82) † 1.98 (0.90–4.35)
Normotensive 1.00 0.013 1.00
Hypertensive 2.31 (1.23–4.33) † 1.71 (0.73–3.98)
BMI 26.9 kg/m2 1.00 0.043 1.00
BMI 27–29.9 kg/m2 1.26 (0.65–2.42) 0.68 (0.27–1.73)
BMI 30 kg/m2 2.23 (1.03–4.83) † 0.43 (0.12–1.47)
Cholesterol <6.5 mmol/L
1.00 0.002 1.00
Cholesterol 6.5–7.79 mmol/L
1.47 (0.78–2.78) 1.79 (0.79–4.02)
Cholesterol 7.8mmol/L
3.19 (1.47–6.89) † 5.66 (1.95–16.47) †
ApoA1 1047 mg/L 1.00 <0.001 1.00
ApoA1 1048–1148 mg/L
0.46 (0.22–0.97) † 0.35 (0.14–0.91) †
ApoA1 1149–1266 mg/L
0.29 (0.12–0.67) † 0.33 (0.11–0.96) †
ApoA1 1267 mg/L 0.21 (0.09–0.51) † 0.16 (0.05–0.50) †
* 2 test. † Significant relation.
51
Table 3. Relative Risk of Myocardial Infarction From a Matched Analysis of 78 Case-Referent Triplets With Conditional Logistic Regression and Adjustment for Traditional Risk Factors
Relative RiskMatched for Age and
Sex (95% CI) P for Trend*
Relative Risk for Model Including Diabetes, Smoking,
Hypertension, BMI, Cholesterol, ApoA1, and 1 of
the Variables Shown (95% CI)
tPA 6.0 µg/L 1.00 <0.001 1.00
tPA 6.1–8.4 µg/L 1.04 (0.42–2.59) 1.08 (0.37–3.16)
tPA 8.5–11.6 µg/L 1.79 (0.73–4.37) 1.32 (0.45–3.90)
tPA 11.7 µg/L 5.89 (2.38–14.57) † 5.42 (1.75–16.79) †
PAI-1 5.8 µg/L 1.00 0.002 1.00
PAI-1 5.9–7.9 µg/L 1.25 (0.50–3.13) 0.96 (0.34–2.73)
PAI-1 8.0–13.5 µg/L 2.37 (0.98–5.72) 1.77 (0.58–5.89)
PAI-1 13.6 µg/L 3.35 (1.38–8.14) † 1.83 (0.57–5.89)
VWF 102% 1.00 0.045 1.00
VWF 103–124% 1.49 (0.66–3.38) 1.40 (0.50–3.94)
VWF 125–154% 1.57 (0.69–3.57) 1.37 (0.50–3.76)
VWF 155% 2.39 (1.05–5.44) † 2.58 (0.87–7.63)
TM 26.7 µg/L 1.00 0.682 1.00
TM 26.8–36.9 µg/L 1.24 (0.57–2.73) 0.87 (0.32–2.35)
TM 37.0–45.2 µg/L 1.14 (0.50–2.63) 0.79 (0.27–2.29)
TM 45.3 µg/L 1.30 (0.53–3.16) 1.04 (0.35–3.05)
DHEAS 2.9 µmol/L 1.00 0.688 1.00
DHEAS 3.0–4.9 µmol/L 1.11 (0.58–2.15) 1.30 (0.55–3.10)
DHEAS 5.0 µmol/L 0.82 (0.38–1.77) 0.55 (0.20–3.10)
* 2 test. † Significant relations.
To visually illustrate the strength of these relationships, the ORs through quartiles 1 through 4 of the
distributions of mass concentrations of tPA, PAI-1, and VWF are shown in the Figure 6.
52
Figure 6. Relative risk of myocardial infarction in all subjects for quartiles 1 through 4 of massconcentrations in plasma of t-PA, PAI-1, and VWF.
Subgroup analysis on men showed that higher levels of cholesterol and mass concentrations of tPA
and PAI-1 and lower levels of apoA-I were associated with significant increases in the risk of
myocardial infarction, whereas no significant trend was found for BMI, VWF, TM, or DHEAS
(data not shown).
Variables for women were only dichotomized because of the small number of cases. In women,
high levels of TM and mass concentrations of tPA and PAI-1 and low levels of ApoA1 were
associated with significant increases in the risk of myocardial infarction (Table 4).
53
Table 4. Subgroup Analyses on 16 Women With First Myocardial Infarction and 32 Age- and Sex-Matched Referent Subjects on Relative Risk of Myocardial Infarction With Conditional Logistic Regression
Cut-off Level OR 95% CI
tPA mass concentration, µg/L 8.10 8.42 1.06–67.13
PAI-1 mass concentration,µg/L
7.30 10.00 1.23–81.47
VWF, % 126 3.42 0.68–17.15
TM, µg/L 23 5.62 1.14–27.79
ApoA1, mg/L 1232 0.19 0.04–0.92
Cut-off level was defined as the median level in the 32 female referent subjects.
In multivariate conditional logistic regression analysis on all cases of both sexes, when all the
traditional atherosclerotic risk factors available in this study were simultaneously controlled for, the
relative risk in the highest quartile of tPA mass concentration was only slightly reduced to 5.42
(95% CI, 1.75 to 16.79) compared with 5.89 (95% CI, 2.38 to 14.57) in univariate analysis (Table
3). Low levels of ApoA1 and high cholesterol levels also remained significantly associated with
myocardial infarction in this analysis with tPA (Table 2). When PAI-1, VWF, TM, and DHEAS
were included in the same multivariate analysis together with the established risk factors diabetes,
smoking, hypertension, body mass index, cholesterol, and ApoA1, the significant associations of
these former variables to myocardial infarction disappeared.
Subgroup analysis on men showed a significant association of tPA and diabetes, smoking,
hypertension, BMI, cholesterol, and ApoA1 in multivariate conditional logistic regression, whereas
no significant association could be shown when PAI-1, VWF, TM, or DHEAS was included in the
model (data not shown). Multivariate subgroup analysis on women was not done because the
statistical power was too small owing to the limited number of women.
54
Study II
In this study, the prevalences of the three possible genotypes of the C 677>T mutation of MTHFR,
namely –/– (no mutation), +/+ (both alleles have the mutation) and +/–, and plasma concentration of
total homocysteine were investigated as predictors of a first myocardial infarction. Prevalences of
genotypes did not deviate from the Hardy–Weinberg equilibrium for referent subjects ( 2 = 0.31, P
> 0.05), cases ( 2 = 0.63, P > 0.05), and the subjects overall ( 2 = 0.78, P > 0.05). The T prevalence
was greater for cases than referents (0.30 versus 0.25) but not significantly. The expected
prevalance of the TT mutation was 6.25%. There was no statistically significant difference between
cases and referents for any of these combinations. Neither were odds ratios for the +/– and +/+
groups significantly higher (Table 5).
Cases Referents Odds ratio Confidence interval (95%)
MTHFR /
MTHFR /+
MTHFR +/+
Prevalence of alleles
–
+
Total plasma homocysteine
First quartile ( 9.66 µmol/L)
Second quartile (9.67-11.43 µmol/L)
Third quartile (11.44-13.58 µmol/L)
Fourth Quartile ( 13.59 µmol/L)
32 (46)
32 (46)
5(7)
0.70
0.30
19
18
15
24
71 (55)
51(40)
7(5)
0.75
0.25
36
36
38
37
1.00
1.4
1.7
1.00
0.9
0.8
1.2
0.7-2.6
0.5-6.3
0.4-2.2
0.4-1.7
0.5-2.7
Table 5. Distributions of 5,10-methylenetetrahydrofolate reductase (MTHFR) genotype and level of
total plasma homocyst(e)ine for case subjects with myocardial infarction and age-matched and sex-
matched referents. Values are expressed as numbers (percentages). MTHFR, P -value for trend
0.249; total plasma homocysteine, P -value for trend 0.700. Conditional logistic regression was
used for comparisons.
Mean concentrations of homocysteine did not differ between the group with myocardial infarction
and the reference group and between men and women.
55
In Figure 7 we show the relative distributions of homocysteine for cases and controls. The
prevalence of hyperhomocysteinemia, whether defined as homocysteine >15.8 µmol/l (154), or the
95th (homocysteine >18.65 µmol/l) or the 90th (homocysteine >15.65 µmol/l) percentile of
concentration of homocysteine of the distribution for referents, corresponding to 16% of cases and
9.6% of referent subjects, 2.6% of cases and 4.8% of referent subjects, and 17.1% of cases and
10.9% of referent subjects, respectively, did not differ significantly between cases and referent
subjects. Univariate conditional logistic regression analysis of the quartiles for homocysteine
showed that there was no association with risk of myocardial infarction (Table 5).
Figure 7. Relative distribution of total plasma homocyst(e)ine (TPH) among cases and controls besides one control individual with a TPH of 55.13 µmol/l.
We observed no association between MTHFR genotype and homocysteine (Table 6) even after
stratification by age, for which 60% of the study population were aged more than 58 years.
56
Homocysteine was positively associated with age (r = 0.138, P = 0.039). The mean age of subjects
in the homozygous mutant group was lower than those of subjects in the other groups (Table 6).
MTHFR genotypes CC CT TT
Homocysteine in cases (µmol/L)
Homocysteine in referents (µmol/L)
Homocysteine in all subjects (µmol/L)
Homocysteine in all subjects 58 years
Homocysteine in all subjects > 58 years
Age (years)†
11.5±2.9
12.5±6.0
12.2±5.2
11.3±3.0
12.8±6.0
55.1±6.9
12.5±4.1
11.6±3.9
12.0±4.0
11.7±3.3
12.1±4.3
55.3±6.5
11.4±1.7
11.6±2.6
11.5±2.2
11.3±1.8
12.0±2.5
46.6±10.2
Table 6. Plasma concentrations of total plasma homocyst(e)ine in the study population by 5,10-
methylenetetrahydrolfate reductase (MTHFR) 677 C>T genotype and age. All values are means ±
SD. †P for age by analysis of variance < 0.001.
Study III
In this study, the summarised importance of haemostatic (tPA, PAI-1, VWF) and metabolic
variables (insulin, lipids including lipoprotein (a) (Lp(a)) and leptin) in predicting first myocardial
infarction, as well as possible interactions among these variables were investigated among the 62
men cases and 124 men referents. The insulin variables were, as expected, correlated to each other,
as well as to BMI, leptin, PAI-1, tPA, VWF, and systolic and diastolic blood pressure. Proinsulin
was also correlated to VWF. High levels of leptin were associated with BMI, blood pressure, and
high plasma levels of PAI-1, tPA, VWF, and apo B. Lp(a) correlated only positively to Apo B. tPA
and PAI-1 were correlated to each other. Partial correlations after adjustment for BMI resulted in r
0.30 for insulin in relation to proinsulin, specific insulin, and leptin; proinsulin to leptin and
specific insulin; leptin to PAI-1; cholesterol to ApoA1 and apo B; and systolic blood pressure to
diastolic pressure.
57
Table 7. Odds ratios for first myocardial infarction based on conditional logistic regression analysis of 62 male cases matched with double referents
BMI, body mass index; apo A-I, apolipoprotein A-I; tPA, tissue plasminogen activator; PAI-1, plasminogenactivator inhibitor-1; vWF, von Willebrand factor; Lp(a), lipoprotein (a). * Significant relation. † 2 test.
Relative risk matched for age (95%
CI)
P for
trend†
Multivariate model including all the
variables with calculations (95% CI)No history of diabetes 1.00 0.11 1.00History of diabetes 6.00 (0.62-57.7) 0.42 (0.002-118)
Non-smoker 1.00 0.09 1.00Daily smoker 2.11 (1.08-4.12)* 2.10 (0.61-7.26)
Normotensive 1.00 0.2 1.00Hypertensive 1.76 (0.87-3.56) 0.86 (0.22-3.39)
BMI 26,9 kg/m2 1.00 0.3 1.00
BMI 27-29,9 kg/m2 1.15 (0.56-2.36) 0.59 (0.14-2.52)
BMI 30 kg/m2 2.18 (0.75-6.29) 0.57 (0.10-3.22)
Cholesterol <6,5 mmol/l 1.00 0.02 1.00Cholesterol 6,5-7,79 mmol/l 1.33 (0.68-2.61) 1.73 (0.49-6.04)Cholesterol 7,8 mmol/l 2.63 (1.09-6.37)* 2.33 (0.40-13.4)
ApoA1 1038 mg/L 1.00 0.002 1.00ApoA1 1038-1136 mg/L 0.40 (0.17-0.92)* 0.16 (0.03-0.89)*ApoA1 1136-1242 mg/L 0.28 (0.11-0.74)* 0.17 (0.03-0.96)*ApoA1 1223 mg/L 0.22 (0.08-0.62)* 0.15 (0.02-0.93)*
tPA 5.9 g/L 1.00 0.001 1.00tPA 5.9-8.5 g/L 2.22 (0.73-6.71) 2.51 (0.41-15.4)tPA 8.5-12.2 g/L 3.95 (1.24-12.55) 7.29 (0.79-67.2)tPA 12.2 g/L 7.53 (2.24-25.26)* 21.3 (2.04-222)*
PAI-1 5.8 g/L 1.00 0.03PAI-1 5.8-8.2 g/L 1.56 (0.59-4.14)PAI-1 8.2-14.0 g/L 2.18 (0.81-5.84)PAI-1 14.0 g/L 2.98 (1.09-8.16)*
VWF 102 % 1.00 0.2VWF 102-124 % 1.42 (0.56-3.61)VWF 124-151 % 1.28 (0.49-3.31)VWF 151 % 1.93 (0.79-4.70)
Proinsulin 4.5 pmol/L 1.00 0.02 1.00Proinsulin 4.5-6.8 pmol/L 4.97 (1.47-16.76) 4.55 (0.57-36.6)Proinsulin 6.8-11 pmol/L 3.33 (1.06-10.44) 2.66 (0.28-25.4)Proinsulin > 11 pmol/L 5.50 (1.64-18.44)* 6.47 (0.54-78.1)
Lp(a) 30 mg/L 1.00 0.002 1.00Lp(a) 30-65 mg/L 0.56 (0.21-1.54) 0.95 (0.15-5.93)Lp(a) 65-134 mg/L 0.67 (0.22-2.06) 0.91 (0.12-6.92)Lp(a) 134 mg/L 2.59 (1.14-5.90)* 7.21 (1.31-39.8)
Leptin 3.0 ng/mL 1.00 0.002 1.00Leptin 3.0 -4.1 ng/mL 1.00(0.34-2.90) 0.11(0.01-1.21)Leptin 4.1-6.4 ng/mL 2.25 (0.77-6.58) 0.14 (0.01-2.08)Leptin >6.4 ng/mL 4.89 (1.63-14.7)* 0.83 (0.04-19.59)
58
In conditional univariate logistic regression analysis, smoking, hypercholesterolemia, and high
plasma levels of tPA, PAI-1, proinsulin, Lp(a), and leptin, and low plasma levels of ApoA1 were all
associated with significant increases in the risk of first myocardial infarction (Table 7). Tests for
trends after categorization of the continuous variables were significant for cholesterol, ApoA1, tPA,
PAI-1, proinsulin, Lp(a), and leptin (Table 7). In multivariate conditional logistic regression
analysis, after simultaneously controlling for all traditional atherosclerotic risk factors available in
this study (diabetes, smoking, hypertension, BMI, and cholesterol) together with each of the
variables shown in Table 7, only high plasma levels of tPA, proinsulin, and Lp(a), and low plasma
levels of ApoA1 remained significant risk determinants for first myocardial infarction, though high
leptin was also borderline significant (p=0.06). Combining these variables with the traditional risk
factors, only tPA, Lp(a), and ApoA1 remained significant risk determinants for first myocardial
infarction (table 7). If a cut-off level of 200mg/L for Lp(a) was implemented according to our
previous report (144), then odds ratio for Lp(a) 200mg/L increased to 20.4 (95% CI, 3.2-129) in
the final model. If the categories for leptin were reduced by combining quartiles 1 and 2, a method
employed in a previous report (155), then the odds ratio for leptin levels 6.4 ng/mL increased to
8.4 (95% CI, 1.01-70) in the final model. Repeated analysis after exclusion of diabetic subjects (3
cases and their respective referents, and 1 referent subject) did not alter the results of the uni- and
multivariate analyses.
To explore possible interactions among plasma levels of tPA, ApoA1, Lp(a), leptin, and proinsulin,
these variables were dichotomized according to the median values of the controls and analysed in
pairs by conditional logistic regression (Tables 8 and 9). No significant synergistic interactions were
observed for any of these combinations (Tables 8 and 9 and Figure 8).
59
Table 8. Interaction analysis by conditional logistic regression on pairs of selected
dichotomized variables for 62 male cases of first myocardial infarction matched with double
referents
Relative risk matched
for age (95% CI)
P value for trend
chi-square test
Synergy index
(95%CI)
Leptin-ApoA1
low-high 1.00 0.001
low-high 1.08 (0.36-3.21)
high-high 1.13 (0.35-3.65)
high-low 3.93 (1.48-10.4)* 14.6†
Leptin-Lp(a)
low-low 1.00 0.001
low-high 1.66 (0.61-4.55)
high-low 1.72 (0.56-5.25)
high-high 6.02 (2.05-17.7)* 3.6 (0.7-17.9)
Leptin-proinsulin
low-low 1.00 0.01
low-high 1.06 (0.37-3.05)
high-low 2.32 (0.83-6.51)
high-high 2.84 (1.22-6.64)* 1.3 (0.2-7.4)
Leptin-tPA
low-low 1.00 0.003
low-high 1.50 (0.50-4.54)
high-low 1.69 (0.55-5.17)
high-high 4.59 (1.71-12.29)* 3.0 (0.4-19.0)
tPA-Lp(a)
low-low 1.00 <0.001
low-high 2.29 (0.80-6.59)
high-low 2.74 (0.88-8.57)
high-high 7.86 (2.60-23.80)* 2.3 (0.8-6.6)
ApoA1, apolipoprotein A1; Lp(a), lipoprotein (a); tPA, tissue plasminogen activator. * Denotes
significant relations. † Confidence interval not depicted because of too high standard error.
”Low” and ”high” are defined as values at or below the median, and above the median value,
respectively.
60
Table 9. Interaction analysis by conditional logistic regression on pairs of selected
dichotomized variables for 62 male cases of first myocardial infarction matched with double
referents
Relative risk matched
for age (95% CI)
P value for trend
chi-square test
Synergy index
(95% CI)
tPA-proinsulin
low-low 1.00 0.007
low-high 0.87 (0.31-2.46)
high-low 1.96 (0.73-5.28)
high-high 3.22 (1.30-7.95)* 2.7 (0.3-26.1)
Lp(a)-proinsulin
low-low 1.00 0.003
low-high 1.45 (0.48-4.42)
high-low 2.36 (0.81-6.85)
high-high 3.89 (1.37-11.0)* 1.6 (0.4-7.1)
Lp(a)-ApoA1
low-high 1.00 0.001
low-low 2.40 (0.75-7.68
high-high 1.86 (0.59-5.85)
high-low 6.53 (2.10-20.31)* 2.5 (0.7-8.7)
Proinsulin-ApoA1
low-high 1.00 0.02
low-low 1.92 (0.70-5.28)
high-high 1.17 (0.41-3.28)
high-low 3.33 (1.29-8.62)* 2.2 (0.3-13.5)
tPA-ApoA1
low-high 1.00 0.001
low-low 2.40 (0.77-7.47)
high-high 2.80 (0.85-9.22)
high-low 6.33 (2.07-19.34)* 1.7 (0.6-4.9)
tPA, tissue plasminogen activator; Lp(a), lipoprotein (a); ApoA1, apolipoprotein A1. * Denotes
significant relations.
“Low” and “high” are defined as values at or below the median, and above the median value,
respectively.
61
0
2
4
6
8
10
low-low low-high high-low high-high
Relative risk
Figure 8. Interaction analysis by conditional logistic regression of four different combinations oflow and high plasma concentrations of tPA and Lp(a) for 62 male cases of first myocardialinfarction matched with double referents.
Study IV
In this study comparison of plasma homocysteine, plasma creatinine and plasma albumin in 50
cases and 56 referent subjects were investigated before and after the development of a first
myocardial infarction. The first myocardial infarct events for the 50 cases occurred on average 20
months after participation in the first health survey (median, 18 months). The time interval between
the two screening episodes had a mean of 8.4 1.8 years (SD) for cases and 8.7 1.7 years (SD) for
referents (unpaired t-test: p=0.5). Baseline characteristics for the 50 cases and 56 referents are
shown in Table 10.
62
Table 10. Characteristics of variables in study subjects at baseline and follow-up.
Cases Referent Subjects
(n = 50) SD (n = 56) SD
Sex (male/female) 42/8 47/9
Age at first blood sampling, year 53.7 7.5 53.1 8.3
Smokers, % 19/44 (43%) 13/55 (24%)
Diabetes, yes/no, % 2/46 (4.4%) 0/56 (0%)
Systolic blood pressure (mmHg) 140 24 136 21
Diastolic blood pressure (mmHg) 86 9 83 10
History of hypertension, % 17/46 (37%) 14/56 (25%)
Body mass index, kg/m2 27.0 4.2 25.7 3.6
Cholesterol, baseline (mmol/L) 6.7 1.5 6.4 1.4
Homocysteine, baseline ( mol/L) 11.4 2.8 10.7 2.0
Homocysteine, follow-up ( mol/L) 12.4 3.2 11.9 3.2
Albumin, baseline (g/L) 43.0 2.0 42.9 2.5
Albumin, follow-up (g/L) 41.7 1.8 41.9 2.0
Creatinine, baseline ( mol/L) 95.8 13.1 92.2 13.1
Creatinine, follow-up ( mol/L) 100.7 14.6 95.8 15.3
SD, Standard deviation.
Established cardiovascular risk factors such as smoking, diabetes, and hypertension were more
common among cases than referents, whereas none of the continuous variables differed between the
groups. There was a significant increase in total plasma homocysteine concentrations during follow-
up among both cases and referents. The mean increase in tHcy among cases and referents were
comparable (1.0 2.8 mol/L versus 1.1 2.6 mol/L). The difference in homocysteine
concentration at follow-up and baseline was not correlated to the time interval between the two
health survey occasions (Spearman´s rho correlation coefficient – 0.064, p=0.5). There were
63
significant increases in plasma creatinine concentrations in cases (4.9 12.4 mol/L; p<0.01) and
referents (3.7 11.6 mol/L; p<0.05), and significant decreases in plasma albumin concentrations
in cases (-1.2 2.1 g/L; p<0.001) and referents (-1.0 2.9 g/L; p<0.05) during follow-up.
Significant correlations were observed between baseline plasma homocysteine concentration and
body mass index (r=0.25; p<0.05), creatinine (r=0.31; p<0.01) and plasma homocysteine
concentration at follow-up (r=0.633; p<0.001). For both creatinine and albumin in plasma, a
correlation was found between baseline and follow-up concentrations (r = 0.66; p<0.001 and r = –
0.25; p<0.05 respectively). Conditional univariate logistic regression analysis of all the continuous
variables showed no significant associations with first myocardial infarction (Table 11). High
plasma concentrations of homocysteine at follow-up and high plasma concentrations of creatinine at
baseline and follow-up were associated with first myocardial infarction (Table 11).
Multivariate analysis with conditional logistic regression in models including two variables
indicated that high homocysteine concentrations at follow-up remained associated to a first
myocardial infarction when combined with albumin at follow-up, whereas the same was true only
for high concentrations of creatinine in combination with tHcy at follow-up (Table 12). Multivariate
conditional logistic regression analysis with the three variables homocysteine, albumin and
creatinine showed that only creatinine at baseline (OR 2.94; 95% CI 1.05-8.21) and creatinine at
follow-up (OR 3.38; 95% CI 1.21-9.48) were significantly associated with outcome (Table 12).
64
Table 11. Odds ratios of myocardial infarction from a matched analysis of 47 case-
referent pairs/triplets with conditional logistic regression
Odds ratio matched for age with continuous variables (95% CI)
Odds ratio matched for age with variables dichotomised or as specified (95% CI)
Non-smokerSmoker
1.003.36 (1.07-10.55)*
Cholesterol< 6.5 mmol/L6.5-7.79mmol/L
7.8 mmol/L
1.04 (0.80-1.35)1.000.92 (0.38-2.23)1.79 (0.64-4.99)
NormotensiveHypertensive
1.001.82 (0.60-5.47)
Body mass index 26.9 kg/m2
27-29.9 kg/m2
30 kg/m2
1.08 (0.96-1.22)1.001.20 (0.45-3.35)2.66 (0.66-10.74)
Homocysteine, baseline 10.66 mol/L 10.67 mol/L
1.13 (0.93-1.38)1.001.34 (0.59-3.11)
Homocysteine, follow-up 10.88 mol/L 10.89 mol/L
1.08 (0.95-1.22)1.002.49 (1.03-6.02)*
Albumin, baseline 43 g/L 44 g/L
0.97 (0.81-1.16)1.000.61 (0.25-1.48)
Albumin, follow-up 41 g/L 42 g/L
0.93 (0.74-1.19)1.001.00 (0.41-2.44)
Creatinine, baseline 90 mol/L 91 mol/L
1.02 (0.98-1.05)1.002.72 (1.05-7.07)*
Creatinine, follow-up 93 mol/L 94 mol/L
1.03 (1.00-1.06)1.004.05 (1.49-11.0)*
* Significant relation
65
Table 12. Multivariate conditional logistic regression analyses on odds ratios of myocardial
infarction in models including two or three variables.
Odds ratio (95%CI)
with two variables
respectively
Odds ratio (95%CI)
with three variables
respectively
Homocysteine, baseline, median
Albumin, baseline, median
Creatinine, baseline, median
1.38 (0.56-3.24)
0.60 (0.24-1.48)
1.06 (0.43-2.61)
0.51 (0.19-1.39)
2.94 (1.05-8.21)*
Homocysteine, baseline, median
Creatinine, baseline, median
1.05 (0.44-2.54)
2.68 (0.99-7.20)
Homocysteine, follow-up, median
Albumin, follow-up, median
Creatinine, follow-up, median
2.50 (1.03-6.07)*
0.94 (0.37-2.33)
1.83 (0.70-4.78)
0.90 (0.35-2.36)
3.38 (1.21-9.48)*
Homocysteine, follow-up, median
Creatinine, follow-up, median
1.82 (0.70-4.75)
3.38 (1.20-9.47)*
* Significant relation
66
DISCUSSION
Current smoking, hypertension and diabetes in combination accounted for 53 % of the population
attributable risks of acute myocardial infarction in the Interheart case-control study (156).
Identification of other markers associated with an increased risk of atherosclerotic vascular disease
may allow better insight into the pathobiology of atherosclerosis and facilitate the development of
preventive and therapeutic measures (157).
Thrombus formation requires complex interactions involving injury to the vascular endothelium,
platelet adherence, aggregation and release, and clotting factor activation. This process eventually
leads to thrombin generation and fibrin formation (43). The availability of a useful index of
endothelial dysfunction may, therefore, have potential value as measurement of such a marker can
be a non-invasive way of assisting in diagnosis, as well as an indicator of disease progression or
prognosis (43).
Study base
The two surveys fulfil the criteria of a population-based study cohort and the observed prevalence
of traditional risk factors should be expected to be representative of a larger population. A total of
78 first myocardial infarctions were included between 1985 and 1994, which may appear
unexpectedly low considering the size of the study cohort. There are several explanations for this.
First, participants in the surveys are predominantly middle-aged with a low incidence of
cardiovascular disease. Second, only cases with a first myocardial infarction were included and
subjects with previous stroke were excluded. In addition, all cases with diagnosed cancer and cases
with no blood sample or blood sample not adequate for analysis were also excluded from the
studies. Finally, the VIP and MONICA surveys started in 1985 and the number of screened subjects
has a linear growth. During the first years of the VIP survey only a few screening centers were
performing health examinations. Consequently, years at risk for cardiovascular disease are therefore
relatively shorter for a majority of the participants (136).
67
Determinants of myocardial infarction
Study I showed that established cardiovascular risk factor such as smoking, hypertension, and
diabetes were more common in the cases, and they had higher mean levels of body mass index,
systolic and diastolic blood pressure, and serum cholesterol concentrations and lower mean
concentrations of ApoA1. The overall results are in concordance with previous prospective studies
on myocardial infarction and should be expected to be representative of the whole cohort.
Hemostatic factors and myocardial infarction
High PAI-1 and tPA mass concentrations are associated with increased risk of a first myocardial
infarction in both men and women (study I). For tPA, the association is strong, especially in women,
is independent of established cardiovascular risk factors, and is continuous across the tPA strata.
Increased levels of PAI-1 were also associated with first myocardial infarctions in both sexes in
univariate, but not multivariate analyses when adjusted for traditional risk factors. In multivariate
analysis high plasma levels of tPA remained significant risk markers for a first myocardial
infarction after adjustment for traditional risk factors (diabetes, smoking, hypertension, BMI, and
cholesterol) and proinsulin, ApoA1, Lp(a) and leptin (study III). Our study in men emphasizes the
position of tPA mass concentration as an independent risk determinant.
Although there is a statistically significant association between circulating concentrations of tPA
mass and subsequent coronary heart disease, additional studies are needed to determine to what
extent this is independent from other risk determinants like markers of systemic inflammation and
kidney function. It is not known how much of the residual association between tPA and coronary
heart disease would persist with more complete adjustment for these (and other) factors (38). At
present the pathophysiological relevance of circulating levels of tPA to plaque rupture remains
uncertain (38). Epidemiological studies of tPA consistently show strong correlations with PAI-1
activity or mass concentration (38). This association may reflect simultaneous release from
68
endothelial cells, delayed clearance of tPA-PAI-1 complexes, acute-phase reactions, or mutual
correlations with measures of insulin resistance (38).
Although PAI-1 poorly predicts coronary heart disease in healthy subjects, an underlying
association between PAI-1 levels and coronary disease may be hidden by the confounding effect of
the close correlation between levels of PAI-1 and other established cardiovascular risk factors,
particularly those that occur in association with insulin resistance (158).
It is evident that PAI-1 can play an ambivalent role, either by contributing to plaque stabilization by
reducing local plasmin activity and therefore the activation of matrix metallopeptidases (39), or by
enhancing the risk of thrombosis after plaque rupture with ensuing increased fibrin deposition (39).
In addition, as for other “players” acting locally as autocrine/paracrine factors, the relationship
between circulating (plasma) and local (tissue) levels of PAI-1 must be taken into consideration.
This has been neglected in most available studies (39). Thus, although it has been hypothesizes that
an increase in local levels of PAI-1 might contribute to the pathogenesis of atherosclerosis, it is still
unclear whether the increase in PAI-1 plasma levels observed in this pathological condition
represents cause, effect, or both (39). In our view, the cause-effect relationship must be
demonstrated in prospective studies of healthy populations before PAI-1 can be considered a risk
factor for coronary atherosclerosis. Whether PAI-1, per se, carries an increased risk of
cardiovascular disease remains to be determined, perhaps with the exception of late restenosis after
percutaneous coronary intervention (39).
Cases had higher mean VWF values than controls, and this difference was also significant in
subgroup analysis of women, but not in men (study I). VWF was predictive of a future myocardial
infarction, and its OR actually increased slightly after adjustment for traditional risk factors. The
predictive value of VWF may thus be real in the type of subjects studied here, although the
introduction of confounding variables in multivariate analyses resulted in too great a loss of
statistical power to achieve statistical significance. The precise mechanism by which VWF is
associated with cardiovascular risk is unclear (113). As well as having roles in haemostais and
69
thrombosis, circulating VWF values can increase markedly during acute phase responses to
systemic and/or local inflammation and to endothelial injury (46). However, in the PRIME study
(113), the contribution of VWF to coronary heart disease was independent of inflammatory markers
and traditional risk factors, suggesting different pathways through which VWF and inflammation
determine coronary heart disease risk.
No significant differences in the mean levels of plasma TM were found between the case and
control groups, although TM tended to be higher in subgroup analysis of male cases compared with
controls (study I). However, in a stratified subgroup analysis of women, high levels of TM were
predictive of future myocardial infarction. Results of prospective studies on TM and cardiovascular
end-points have been inconsistent (113,114), and more specially designed studies are therefore
necessary to confirm the possibility that TM may be a risk determinant, albeit a weak one, of a first
myocardial infarction. Both endothelial cell protein C receptor and thrombomodulin are severely
downregulated over atherosclerotic plaque, vein bypass grafts, in diabetes, and by acute
inflammmatory insults like bacterial infection, potentially contributing to both thrombosis and
plaque rupture through localized thrombin generation and subsequent metalloproteinase activation
(53). Since raised thrombomodulin concentrations indicate an increased risk of bleeding in patients
receiving oral anticoagulants (159), circulating thrombomodulin might reflect not only endothelial
cell damage, but also increased synthesis, which would therefore enhance the anticoagulant
property of the endothelial cell surface. The importance of circulating TM as an indicator of
anticoagulant or procoagulant activity on the surface of the endothelium is still unclear and data on
the relation between soluble TM and membrane bound TM are not available. Whether low levels of
soluble TM represent high amounts of membrane bound TM due to reduced shedding from the
endothelium or whether low levels reflect low amounts of membrane bound TM due to impaired
expression of TM to the endothelial surface is unknown. It thus remains to be determined whether
thrombosis or hemorrhage can be directly attributed to the plasma concentration of TM or whether
it is only a reflection of other pathophysiological processes (160).
70
DHEAS
No predictive value of DHEAS regarding the risk of a first myocardial infarction was found for
either men or women in Study I. The epidemiological and experimental data on the relationship
between DHEAS and coronary artery disease are inconsistent and unconvincing (115) and do not
support the hypothesis that DHEAS deficiency is a risk factor for coronary artery disease fatalities
or that DHEAS may confer an anti-atherogenic action in men or women (115). The age-related
decline in serum DHEA and DHEAS has suggested that a relative deficiency of these steroids may
be causally related to the development of chronic diseases generally associated with aging,
including insulin resistance, obesity, cardiovascular disease, cancer, reductions of the immune
defense, depression and a general deterioration in the sense of well-being (55). There is still a lack
of understanding of the basic biological effects of DHEAS and further data in both men and women
from prospective studies and randomized trials are needed (57).
MTHFR
Study II shows that homozygosity for the point mutation C677>T in the gene for MTHFR is not a
clinically useful predictor of a greater than normal risk of a first myocardial infarction for the
population of Northern Sweden. The low prevalence of the homozygous MTHFR mutant, 5% in the
present study or estimated 6.25%, compared with 10 % to 12% reported in the meta-analysis by
Klerk et al (88) might have been caused by the sampling strategy. We found that the homozygous
carriers of MTHFR mutation were younger than individuals with the mutation in the heterozygous
state and homozygous normal genotypes. The consequence of this could be a selection bias in
reports by authors using other than prospective designs for the evaluation of the importance of the
MTHFR mutation. However, studies comparing the allele frequency of the C677>T /MTHFR
genotypes in the newborn, young and elderly (161,162) could not demonstrate significant gene
mutations differences among the various age groups, suggesting that the point mutation C677>T in
71
the gene for MTHFR do not contribute significantly to longevity. Klerk et al (88) reported that
individuals with the MTHFR 677 TT genotype had a significantly higher risk of coronary heart
disease, particular in the setting of low folate status. However, the increased risk with the TT
genotype was shown only for retrospective studies, which are restricted to survivors, whereas
prospective studies can include fatal and non-fatal outcomes. In the face of a low prevalence of the
MTHFR mutation, we conclude that the MTHFR mutation does not explain any major part of the
risk of a first myocardial infarction in the area of Northern Sweden. Klerk et al (88) also concluded
that provided that folate status is adequate, there is little clinical value of screening for MTHFR 677
TT genotype in the general population for prediction of coronary heart disease. Epidemiologic
observations have led to the hypothesis that the risk of developing coronary artery disease in
adulthood is influenced not only by genetic and adult life-style factors but also by environmental
factors acting in early life (163). Thereby, also the folate intake by the mothers in early pregnancy
could be important as well as the type of feeding in the postnatal and infant phase.
Homocysteine
Study II and IV show that baseline plasma homocysteine concentration was not associated with a
first myocardial infarction. However, homocysteine concentrations at follow-up were significantly
associated with myocardial infarction when dichotomized with the median value as cut-off (study
IV). This association disappeared after adjustment for creatinine concentrations (study IV). Total
plasma homocysteine concentrations during eight and a half years of follow-up evolved similarly in
subjects who developed a first myocardial infarction compared to referents (study IV). These data
are not compatible with the hypothesis that homocysteine increases secondarily to a first myocardial
infarction. On the contrary, Nurk et al (164) reported from a population-based, prospective study in
7031 subjects from western Norway who constituted 2 age groups (41-42 and 65-67 years) at
baseline. Previously healthy subjects who developed cardiovascular disease or hypertension during
6 years of follow-up had a significantly higher mean increase in total plasma homocysteine than did
72
those who were free of cardiovascular disease or hypertension (164). The reason for the
discrepancies between our and the Hordaland study could be differences in the age groups studied
and the end points.
Prospective studies of the association of hyperhomocysteinemia and the risk of arterial disease in
otherwise healthy subjects at the time of randomization have given contrasting results. Among the
possible explanations for the different results, the effects of genetic and/or nutritional differences
and of different cardiovascular risk profiles among the populations studied could be considered
(66). The findings that hyperhomocysteinemia consistently proved to be predictive of
cardiovascular events in patients affected by pathologies associated with high cardiovascular risk
suggest that the basal cardiovascular risk profile of the population may be relevant (66). Renal
function is an important determinant of circulating homocysteine concentrations independent of B
vitamin status (72,165). Results of prospective studies of patients with renal disease suggest that
individuals with higher homocysteine levels are at increased risk of cardiovascular events and death
(166,167). In a recent report, Go et al (168) found an independent, graded association between a
reduced estimated glomerular filtration rate and the risk of death, cardiovascular events, and
hospitalization in a large, community-based population. Reduced kidney function was also
associated with increased levels of inflammatory factors, enhanced coagulability, abnormal
apolipoprotein levels, elevated plasma homocysteine, oxidative stress, anemia, left ventricular
hypertrophy, increased arterial calcification, derangement in calcium-phosphate homeostasis, and
arterial stiffness, all of which are associated with accelerated atherosclerosis and endothelial
dysfunction (168,169). Other non-conventional risks that progressively increase with renal decline
include albuminuria, proteinuria, and elevated uric acid levels (169). Whether and how these and
other factors interact to increase the risk of adverse outcomes remains unclear but are the focus of
ongoing investigations (168).
In a recent randomized clinical trial with high and low dose B-vitamin treatment there was no effect
on any clinical endpoint despite a significant decrease of homocysteine by 2 µmol/L in the high
73
dose group (170). Nevertheless, baseline homocysteine concentrations in that study were
significantly associated with new coronary events, indicating homocysteine as a marker and not a
causal factor for coronary disease. No adjustment for creatinine or albumin concentrations was
performed. Two coronary angioplasty studies (171,172) have shown contradictory results regarding
oral supplementation with a combination of folic acid and vitamins B6 and B12 and risk of
restenosis. The two studies differed regarding doses of vitamins and the patients differed regarding
smoking habits, diabetes mellitus, prior myocardial infarction, treatment with statins and
angiotensin-converting-enzyme inhibitors, coronary artery lesion size and use of balloon
angioplasty and stents (173). Studies are needed to clarify the optimal dose, route, and timing of
administration and the subgroups of patients who might benefit from this treatment. Burke et al
(174) reported that increased serum homocysteine was associated with coronary atherosclerosis
with fibrous plaques, a mechanism of atherogenesis separate from that induced by hyperlipidemia,
which is believed to be mediated largely by inflammatory cells, especially macrophages.
Homocysteine was not associated with acute or organized coronary thrombi (174). The issue of
whether mild elevation of homocysteine is a marker or a mediator of vascular disease is still
unresolved.
In the present study, significant decreases in plasma albumin concentrations in cases and referents
were observed during follow up. Prior epidemiologic studies have reported an inverse association
between serum albumin and coronary heart disease (175-177). In a meta-analysis (176), low
albumin was associated with a 50% increased risk of coronary heart disease, and the combined
relative risk for all-cause mortality associated with low albumin was 1.9 (95% CI: 1.6 to 2.3). In
contrast, several observational studies did not find an association between serum albumin and
coronary heart disease (178-181). Albumin is an acute phase protein, whose plasma concentration
decreases in response to inflammatory stimuli (182). Certain conditions, such as increasing age or
several renal or hepatic diseases, might reduce serum albumin, and thus produce spurious inverse
associations (183). Albumin has potent anti-oxidant properties inhibiting the production of free
74
radicals, lipid peroxidation and endothelial cell apoptosis (184-187), mechanisms who are
fundamentally involved in atherogenesis. It is not clear whether low serum albumin concentration is
a nonspecific, prognostic variable, a marker for subclinical disease, or a part of the causal
mechanism leading to coronary heart disease (188).
Apolipoprotein A1
In multivariate analysis low plasma levels of ApoA1 remained significant risk markers for a first
myocardial infarction in men after adjustment for traditional risk factors (diabetes, smoking,
hypertension, body mass index, and cholesterol) and proinsulin, tPA, Lp(a) and leptin (Study III).
ApoA1 was also found to be a risk determinant for first myocardial infarction in women, but
multivariate analyses were not done (Study I). Due to sampling conditions and missing data, it was
not possible to include HDL-cholesterol in the analysis. It can therefore not be concluded that
ApoA1 is a more powerful predictor than indices such as HDL, total/HDL and LDL/HDL
cholesterol ratios (65,120) and LDL-cholesterol (118). In the Interheart case-control study (156),
raised ApoB/ApoA1 ratio (odds ratio 3.25 for top versus lowest quintile, population attributable
risks 49.2% for top four quintiles versus lowest quintiles) was related to myocardial infarction. In
our study, was the mean ratio of ApoB/ApoA1 1.666 for 50 cases (0.298 SD) and 0.966 for 55
referents (0.298 SD) (unpaired student´s t-test for cases versus referents: p = 0.001). Conditional
logistic regression on 46 matched sets showed that the odds ratio of ApoB/ApoA1 was 5.66 (95%
CI 1.44 – 22.28). Odds ratio for the highest quartile of ApoB/ApoA1 versus the lowest quartile was
4.20 (95% CI 1.002 – 17.63). So, our data also support the importance of ApoB/ApoA1 as a risk
determinant for a first myocardial infarction.
Lp(a)
75
In multivariate analysis high plasma levels of Lp(a) remained significant risk markers for a first
myocardial infarction in men after adjustment for traditional risk factors (diabetes, smoking,
hypertension, BMI, and cholesterol) and proinsulin, tPA, leptin and ApoA1 (Study III). Our study
and a recent meta-analysis of prospective studies (121) demonstrate a clear association between
Lp(a) and coronary heart disease.
Non-significant synergistic interactions were noted for high plasma levels of Lp(a) in combination
with high plasma levels of leptin or tPA, and between high plasma levels of Lp(a) and low plasma
levels of ApoA1 in men who had two of these metabolic alterations (study III). We have previously
shown that Lp(a) and cholesterol levels act synergistically (144). Concentrations of plasma Lp(a)
and classic vascular risk factors have not been found to be strongly correlated. This suggests that
the influence of Lp(a) is unlikely to be accounted for by effects on, or confounding with, classic
vascular risk factors (121). Although the unique structural features of Lp(a) suggest both
thrombogenic and atherogenic potential, the precise mechanism of Lp(a) action is still uncertain
(63). Lp(a) may acquire a pathogenic profile on entering the arterial wall as a consequence of
modifications effected by factors operating in the inflammatory milieu of the atheromatous vessel
(64). Given this complex picture, it appears that the cardiovascular pathogenicity of Lp(a) is
influenced by both external factors and factors within the wall of the artery (64).
Leptin
In conditional univariate logistic regression analysis, a high plasma concentration of leptin was
associated with significant increase in the risk of first myocardial infarction in men (Study III),
whereas the association disappeared in multivariate analysis after adjustment for traditional risk
factors (diabetes, smoking, hypertension, BMI, and cholesterol) and proinsulin, tPA, Lp(a) and
ApoA1 (Study III). Considering the different designs of this and other studies, including sample
size, choice of primary endpoint, and variables in the multivariate analyses, especially markers of
76
insulin resistance, further epidemiologic and experimental studies are needed to evaluate the role of
leptin as an atherothrombotic factor. Leptin is undoubtly a major regulator of appetite and food
intake and by altering body mass influences insulin sensitivity profoundly (189). However, its
potential, direct peripheral effects on insulin sensitivity are inconsistent and unclear (189).
In a recent study in which the accumulation of subcutaneous and intra-abdominal fat was studied in
insulin-sensitive and insulin-resistant lean and obese individuals, it was concluded that intra-
abdominal fat correlates with insulin resistance, whereas subcutaneous fat deposition correlates with
circulating leptin levels (190). The investigators also concluded that the concurrent increase in these
two metabolically distinct fat compartments is a major explanation for the association between
insulin resistance and elevated circulating leptin concentrations in lean and obese individuals (190).
Proinsulin
In conditional univariate logistic regression analysis, high plasma concentrations of proinsulin was
associated with significant increase in the risk of first myocardial infarction in men (Study III), and
the association remained in multivariate analysis after adjustment for traditional risk factors
(diabetes, smoking, hypertension, BMI, and cholesterol), but disappeared after adjustment for tPA,
Lp(a) and ApoA1 (study III). Because hyperinsulinemia is a reflection of an insulin-resistant state,
it is now increasingly accepted that insulin resistance rather than hyperinsulinemia is proatherogenic
(99). One mechanism that might connect insulin resistance and atherosclerosis is the
antiinflammatory and potential anti-atherosclerotic effect of insulin, which in the presence of
resistance will lead to a proinflammatory state (191). Insulin resistance at the level of the fat cell is
the initiating insult, leading to increased intracellular hydrolysis of triglycerids and release of fatty
acids into the circulation (192). The inability of insulin-resistant fat cells to store triglycerids is very
likely the initial step in the development of the dyslipidemia characteristic of insulin resistance
(192). The findings by several groups that insulin resistance seems to spare the MAP kinase
(mitogen-activated protein kinase) component of the insulin signalling pathway suggest that insulin
77
could be atherogenic by stimulating division and migration of vascular smooth muscle cells (192).
Insulin´s effects on PAI-1 expression may be mediated by the MAP kinase pathway as well (192).
Indeed, thiazolidinediones and other peroxisome proliferator-activated receptor (PPAR ) ligands
inhibit insulin signalling downstream of MAP kinase, and these agents inhibit smooth muscle cell
proliferation and migration (192). Insulin seems to be one of the main regulators of the cytokine-
associated acute-phase reaction, and tumour necrosis factor- and interleukin-6 is increased in the
insulin resistant states of obesity and type II diabetes (191,193). Recent studies suggest that
adipocytokines are major regulators of insulin sensitivity potentially linking insulin resistance and
obesity (189). These effects indicate that hyperinsulinemia could have a key inhibitory role in the
regulation of factors which are central to atherogenesis, plaque rupture and thrombosis, the final
events which precipitate acute myocardial infarction (100).
Methodological considerations
Observational studies such as cohort and case-control studies, are more appropriate than
randomised trials to study certain cause-effect relationships, and are particular useful in the
evaluation of potential risk factors for cardiac disease (11). Although cohort studies are generally
the preferred approach for observational research, their size and complexity have recently given rise
to several alternatives such as the nested case-control study (11). The nested case-control study is a
relatively new observational design whereby a case-control approach is employed within an
established cohort (11). A major advantage of a cohort study over a case-control study is that
individuals who develop the outcome and individuals who do not develop the outcome derive from
the same source population (i.e., the cohort itself) (11). Another advantage is that, unlike the case-
control study, the cohort study allows for measurement of exposures before the outcome occurs, an
appropriate time sequence for a cause-effect relationship (11). There are different possible reasons
for the discrepant results of case-control and more recent nested case-control studies (11). First,
78
selection bias can be introduced in case-control studies because controls are not randomly selected
from the same predefined study cohort as they are in nested case-controls studies (11). Secondly,
case-control studies are susceptible to the problem of reverse causality, which would occur if the
plasma variable levels (measured after the occurrence of the outcome) become elevated as a result
of the outcome itself directly or indirectly (e.g., changes in therapy or renal function) (11).
The prospective design does not eliminate the influence of other determinants and risk factors for
myocardial infarction. Adjustments for known risk factors are usually made in multivariate
analyses, revealing whether the studied factor is independently associated with myocardial
infarction or not. However, prospective epidemiologic studies still may suffer from confounding of
apparent associations by other known risk factors. These intercorrelations probably argue that
studies of fibrinolytic markers and atherothrombosis should statistically control for other risk
factors as “confounding” variables, to determine the independent effect of fibrinolysis. On the other
hand, it might be that such statistical control is inappropriate because risk factors cluster,
particularly those related to insulin resistance, and may operate together to cause atherothrombosis.
Hence, it is propably inappropiate to adjust for some covariates since they may be mediators and
not true confounders. Therefore, both univariate and multivariate epidemiologic data need to be
considered, in conjunction with knowledege of the underlying biologic processes. However, the
question whether there is a causal relationship between the studied factors and myocardial
infarction cannot be answered with this study design.
Limitations of the study
The limited number of cases confers lower statistical power on the study to detect significant group
differences. This also restricted the number of covariates we were able to control for in order to
assess the independent predictive power of the variable of interest. Hence, residual effects of other
confounders might be present and not adjusted for in the statistical analyses. We had no data on
79
waist-to-hip ratio and physical activity, and did not include psychosocial factors, consumption of
fruits, vegetables, and alcohol in our analysis.
The observational natures of the studies do not allow conclusions about causality, but addresses
only indicators of cardiovascular risk.
A potential limitation in the study design was the single baseline examination and blood-sampling
occasion. Variations within-person of the hemostatic variables may therefore contribute to an
under- or overestimation of the risk due to fluctuations (194). Repeated measurements of the
hemostatic factors would admit calculation of the regression dilution bias and increase the precision
of the statistical analyses. However, investigations of the variability for tPA mass and PAI-1
activity show that the within-person variability is smaller than the between-person variability (195),
suggesting that only one blood sample occasion is sufficient in epidemiological studies.
Overview and future directions
Overall, these studies suggest that hemostatic factors, Lp(a), ApoA1 and proinsulin carry predictive
information about the risk of a first myocardial infarction in addition to traditional cardiovascular
risk factors. Neither leptin and MTHFR, nor homocysteine after adjustment for creatinine, were
clinically useful predictors of a greater than normal risk of a first myocardial infarction in the
population of Northern Sweden. Today, measurement of blood pressure, lipids, and glucose,
together with smoking cessation and weight reduction, guides the preventive treatment of ischemic
heart disease. In the Interheart study (156,196), raised ApoB/ApoA1 ratio, smoking, hypertension,
diabetes, abdominal obesity, psychosocial factors (depression, locus of control, perceived stress,
and life events), consumption of fruits, vegetables, and alcohol, and regular physical activity in
combination accounted for 90% of the population attributable risks in men and 94% in women. In a
previous report on our study population, Weinehall et al (139) found that self-reported perceived ill
health was a risk determinant for a first myocardial infarction and an interaction was found between
80
perceived ill health and smoking, hypertension and hypercholesterolemia. Psychosocial stressors
have been related to a hypercoagulable state reflected by increased procoagulant molecules and by
reduced fibrinolytic capacity (197). Understanding the mechanisms by which societal factors affect
the development of risk factors could lead to new approaches to prevent development of coronary
heart disease. Early detection of ongoing processes preceding cardiac events events by utilization of
a combination of biomarkers in the present studies may be useful.
Integration of knowledge involving novel hemostatic biomarkers at the genetic, biochemical, and
clinical-epidemiologic levels should lead to a significant development in understanding the
pathophysiology of arterial thrombotic disease, the assessment of cardiovascular risk, and the
targeting of specific antithrombotic therapies in high-risk individuals.
For instance, treatment with an ACE inhibitor has been shown to decrease not only PAI-1 levels
(198) and rate of cardiovascular events (199) but also the incidence of type 2 diabetes (200). In this
way, PAI-1 could represent a potential target for therapeutic intervention that aims to decrease the
risk of both cardiovascular disease and Type 2 diabetes (201,202). However, further research in this
area is needed before these biomarkers could be used in clinical practice. Furthermore, hemostatic
factors are genetically determined and future studies should be designed to identify key
combinations of polymorphisms of the hemostatic system and to investigate the extent to which
environmental cardiovascular risk factors interact with genetic factors. Future studies in this field
have to include sufficient numbers of women to make it possible to draw conclusions about
cardiovascular risk in females.
In our study 7 cases died within 24 hours and 3 cases within 28 days. Subgroup analysis on cases
developing sudden cardiac death could be valuable to identify individuals who would benefit for
treatment with a prophylactic implantable cardioverter in future research.
Preanalytical handling, precision in measurement, adequate standardization, intra-individual
variability, and finally costs may represent other issues which should be addressed in more detail
before introducing a new disease marker in clinical medicine (203).
81
CONCLUSIONS
High plasma concentrations of tPA and PAI-1 mass, VWF, Lp(a), leptin and proinsulin, and
low plasma concentrations of ApoA1 are associated with subsequent development of a first
myocardial infarction. This relation was also shown in men for tPA, PAI-1, Lp(a), leptin,
proinsulin and ApoA1 and in women for tPA, PAI-1, TM and ApoA1.
High tPA and Lp(a) and low ApoA1 are significant risk markers for a first myocardial
infarction in multivariate analysis with smoking habits, body mass index, hypertension,
cholesterol, and diabetes included as covariates. There are non-significant synergic
interactions between high Lp(a) and leptin and tPA respectively, and between high Lp(a)
and low ApoA1.
Neither homozygosity for the point mutation C677>T in the gene for MTHFR nor
homocysteine was related to a greater than normal risk of a first myocardial infarction.
High homocysteine at follow-up but not at baseline was associated with first myocardial
infarction, but the relation disappeared in multivariate analyses including plasma creatinine
and plasma albumin.
Total plasma homocysteine concentrations during eight and a half years of follow-up
evolved similarly in subjects who developed a first myocardial infarction compared to
referents.
82
ACKNOWLEDGMENTS
I wish to express my deep gratitude and appreciation to all those who, in different ways and during
different periods of time, have contributed to this thesis, and in particular to:
All the patients and referent subjects that participated in the studies.
Associate professor Jan-Håkan Jansson, my tutor, for introducing me to the field of fibrinolysis,
and for sharing his vast knowledge in this field. For never ending enthusiasm, encouragement and
endless support in a fantastic way. For being concise, prompt, honest and having a big humane
insight.
Professor Torbjörn K. Nilsson, my co-tutor, for sharing some of your profound knowledge in the
fields of hemostasis and genetics, for thorough work with manuscripts, for expert supervision of the
analysis of the biomarkers, and for great support.
Professor Per-Olav Wester, former head of the Department of Internal medicine, for introducing me
to research and sharing his profound knowledge in the fields of magnesium therapy in
cardiovascular disease. For encouragement and support.
Professor Göran Hallmans, co-author, for being a visionary and creating a friendly atmosphere, and
taking responsibility of the Medical Biobank at the University of Umeå. For valuable criticism of
manuscripts, and for support.
Professor Kurt Boman, co-author, for fruitful discussions and criticism of the manuscripts,
enthusiasm and encouragement.
83
Professor Kjell Asplund, for providing excellent research conditions and support.
Lars Weinehall Johan Hultdin, Stefan Söderberg, Vivan Lundberg, Owe Johnson and Gösta
Dahlén, co-authors for valuable contributions to the manuscripts, including statistical analyses.
Hans Stenlund for expert statistical assistance and valuable discussions.
Professor Anders Waldenström, for encouragement and kindness.
Professor Tommy Olsson, for encouragement and support.
Research assistant Åsa Ågren, for untiring performance in preparing data for this study.
The county Council of Västerbotten for its persistence in maintaining the community promotion
program care and thereby creating and guaranteeing the study base.
Steffen Helqvist my collegue and office partner. At moments when I was sad, he was the remedy.
For laughter and fun.
My family for love and support, especially my mother Kathrine who has taken care of my son
Christian whenever I needed it.
KUNDSKAB GØR SIG
Kundskab gør sig altid flot
og bør helligt fredes.
Husk i din begejstring blot:
Ku det ikke lissågodt
være anderledes.
GRUK/Piet Hein
84
Freely translated to English:
Knowledge always makes impression
and should holy be preserved.
Remember in your enthusiasm merely:
Couldn´t it just be otherwise.
This study was supported by grants from the Swedish Council for Planning and Coordination of
Research, the Swedish National Public Health Institute, the Swedish Medical Research Council
(27X-07192, -08267 and 6834), Joint Committee of the Northern Sweden Health Care Region,
Heart and Chest Region, Heart and Chest Fund, the Swedish Heart-Lung Foundation, King Gustaf
V´s 80th Anniversary Fund, the Kempe Foundations, the Swedish Council for Forestry and
Agriculture, Västerbotten County Council, Norrbotten County Council and Umeå University.
85
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