THE MULTIFACTORIAL MODEL

War II, the era of antibiotics had begun. Numerous other antibiotics were soon in development; at the same time, virologists continued to tackle one disease after another, producing vaccines for viral and bacterial disorders.

One result of these scientific advances was a dramatic change in the profile of fatal human diseases. Fewer people would die of the complications that can occur when the streptococcus bacillus that causes simple “strep” sore throat invades the heart, kidneys, and other major organ systems. Similarly, antibiotics could effectively treat tuberculosis, and increasingly effective vaccines helped to prevent influenza and a host of other dangerous viral diseases, as well as bacterial forms of pneumonia and other disorders.

With these important medical developments, life expectancy has gradually risen to 77.6 years in the United States (Hoyert, Kung, & B. Smith, 2005). Like taxes, however, death is certain, and new primary causes of mortality were inevitable.

Living to more advanced ages means dying of disorders that tend to develop over longer periods of time and therefore to depend far more on lifestyle factors. Such slowly progressing disorders include heart disease, cancer, and stroke, the three principal causes of death in Western societies today (Hoyert et al., 2005). It is also notable that two of the three are cardiovascular disorders.

In the United States, 1 in every 2.6 deaths (38%) is the result of cardiovascular disease. In fact, over 70 million people were estimated to have cardiovascular disease in 2002, and over 900,000 died of the disease in that year. Of these deaths, nearly 500,000 were in women (American Heart Association, 2005). Coronary heart disease remains the leading cause of death in the United States and worldwide (Hoyert et al., 2005). However, according to the American Cancer Society, cancer surpassed heart disease as the leading cause of death in people under the age of 85 when data were aggregated by age (Jemal et al., 2005). This discrepancy can be explained by the method of aggregation employed by the ACS and the delay in data collection and reporting by the Centers for Disease Control and World Health Organization.

Despite their high mortality rates, heart disease and cancer have shown down-ward trends. The incidence of heart disease declined 2.8% from 2001 to 2002, while cancer declined 1.3% (National Center for Vital Statistics Reports, 2004). Although one would hope for a continual decline, the high prevalence of heart disease within our society is certain and will most likely remain for quite some time. Clearly, anything we can learn about the causes of this major killer will potentially extend many lives across age groups and genders.

THE MULTIFACTORIAL MODEL

Our particular interest in CHD here revolves around the long-standing speculation and evidence that caffeine consumption may be one of its causal or contributing factors (Lane, Pieper, Philips–Bute, Bryant, & Kuhn, 2002). Clinical observation suggested as early as the 1940s that CHD was not a function of any one or two simple factors. However, it was not until the 1960s and 1970s that randomized, controlled trials began the systematic effort to assess etiology. The major early—

and continuing—investigation was the Framingham Heart Study (D. Smith, 2000), but many others have now been completed or are under way. By examining the

96 Caffeine and Activation Theory: Effects on Health and Behavior

factors derived from these studies, we will be better able to see just where caffeine might fit into the overall causal puzzle, if at all.

The classic etiological triad includes hypercholesterolemia, smoking, and hyper-tension (D. Smith, 2000), and the Framingham Study and others have added family history/genetics and diabetes mellitus (Singh, Wiegers, & Goldstein, 2001). How-ever, a number of other factors have also been clearly implicated in recent scientific literature. Such factors include elevations in low-density lipoprotein, homocysteine, and C-reactive protein (Wilson, 2004). As we will see, some evidence suggests that caffeine may contribute to or interact with several of these and other factors.

FAMILY HISTORY AND GENETICS

Before the human genome was fully mapped, researchers had discovered that cor-onary heart disease and stroke run in families. Family history is a particularly strong factor when CHD occurs in younger people, but is also predictive in older age groups (Friedlander et al., 2001). In addition, behavior genetic research has demonstrated substantial heritability for cardiovascular diseases (Aoki et al., 2001; Katzmarzyk et al., 2000). For example, genetic and environmental influences on coronary heart disease were examined in the HERITAGE Family Study. The investigators assessed several CHD risk factors, including age, family history, LDL cholesterol, HDL cholesterol, blood pressure, diabetes, and smoking status. Based upon this informa-tion, a CHD risk index was created and familial heritability determined. Maximal heritability was 34% in Whites and 53% in Blacks (Katzmarzyk et al., 2000).

Further examinations of heritability have included molecular genetic studies using functional genomic methodology in an attempt to identify specific genes that may code for CHD. For example, high levels of fibrinogen have been found to predict future coronary heart disease. Fibrinogen is a large glycoprotein, which is a clotting factor that serves to activate thrombin and aggregate platelets. Variants of the h-fibrinogen gene subunit on 4q28 are associated with these elevated levels (Yang et al., 2005), though further research is needed to establish a direct causal link to CHD (G. Smith, Harbord, Milton, Ebrahim, & Sterne, 2005). Another genetic study focused on the involvement of the renin–angiotensin system (RAS) in premature CHD risk. Higher frequencies of the angiotensin-converting enzyme (ACE) and angiotensinogen (AGT) gene polymorphisms contributed to increased CHD risk, and the ACE genotype may thus be a risk factor (Sekuri et al., 2005).

A number of other specific genes also have been tentatively identified as contrib-uting to CHD risk. They include the MEF2A, LTA, LGALS2, and ALOX5AP, all of which appear to be associated with myocardial infarction (Wang, 2005). Like CHD, the consumption and effects of caffeine have a hereditary component that may partially explain its role as a potential risk factor (Luciano, Kirk, Heath, & Martin, 2005).

DISEASES AND CONDITIONS

The genetic factors in CHD may be expressed through a variety of mechanisms, including those that underlie blood lipids, homocysteine, and C-reactive protein.

Further complicating the causal model is the fact that these same mechanisms may also be subject to environmental and behavioral influences.

The Multifactorial Model of Cardiovascular Pathology 97

Blood Lipids

Among the major factors in this broad category is lipid status, and caffeine may be a factor in that status (see later discussion in this chapter and, for a more compre-hensive review, chapter 7). Our understanding of the role of lipids in heart disease has evolved from the relatively simple idea that higher levels of total cholesterol are associated with CHD to an increasing understanding of the roles of various lipid components.

A steroid alcohol that regulates membrane fluidity, cholesterol comprises two major subtypes, low-density (LDL) and high-density (HDL) lipoproteins. High levels of LDL cholesterol and low levels of HDL cholesterol represent significant risk factors for CHD. Both types exhibit high heritability, but both can also be altered through behaviors and drugs (Wang & Paigen, 2005). At least four large clinical trials to date confirm that cholesterol is a factor in cardiovascular disease and that modifying its levels is an important aspect of primary prevention (Lloyd–Jones et al., 2001). A recent study involving data from several European countries confirms this finding by demonstrating that a single cholesterol measurement at baseline was a strong predictor of CHD-related death 35 years later (Menotti et al., 2005).

Although total cholesterol does predict CHD, the breakdown into LDL and HDL adds precision to that prediction, providing a better understanding of the mechanisms that underlie the role of cholesterol in CHD. Accordingly, high levels of LDL) are consistently associated with coronary heart disease (Slapikas, 2005). However, recent investigations suggest that low levels of HDL may be even more predictive of CHD mortality (Rosenson, 2005). HDL serves to break down LDL and prevent it from forming plaques on the walls of the coronary arteries. When inadequate HDL is present, LDL plaque formation increases, narrowing the arterial lumen and increas-ing probability of the complete blockage seen in a myocardial infarction (MI). The Helsinki Heart Study has shown that a 1-mg/dl increase in HDL can decrease the probability of a cardiac event by 2 to 3% (Young, Karas, & Kuvin, 2004).

Accordingly, some scientists now hypothesize that low HDL (below about 35 mg/dl) may be a significant independent predictor of CHD (McGovern, 2005).

A genetic mechanism involved in hyperlipidemia that is specifically linked to LDL particle size and apolipoprotein B (apoB) has been proposed. Approximately 37%

of variance of LDL particle size and 23% of the variance of the apoB can be explained by this genetic factor (Juo, Bredie, Kiemeney, Demacker, & Stalenhoef, 1998). Lipid and lipoprotein levels have also been attributed to APOE polymorphism E, as well as apolipoprotein B (Medina–Urrutia, Liria, Posadas–Romero, Cardoso–Saldaga, &

Zamora–Gonzalez, 2004).

Plasma Homocysteine

An elevation in plasma homocysteine levels (hyperhomocysteinemia) is another substantial risk factor for cardiovascular disease, accounting for an estimated 10%

of CHD risk (Fowler, 2005). Homocysteine is a sulfur-containing amino acid derived from methionine during its metabolism. Hyperhomocysteinemia promotes the devel-opment of thrombosis, atherosclerosis, and oxidative damage. As many as 10 to 20%

of coronary heart disease cases are causally linked to homocysteine elevation (Rogers,

98 Caffeine and Activation Theory: Effects on Health and Behavior

Sanchez–Saffon, Frol, & Diaz–Arrastia, 2003). A case-control study, for example, evaluated the relationship of homocysteine levels to 149 coronary events (74 deaths and 75 MIs) that occurred in women over a 13-year follow-up period and compared them with matched control subjects. Among women with heart disease at baseline, relative coronary risk, adjusted for other known factors, was 3.32 in the highest homocysteine quintile as compared to the lowest quintile (Knekt et al., 2001).

Elevated plasma homocysteine has also been linked to premature coronary artery disease (CAD) risk. In one investigation, three groups were studied: one with traditional risk factors, one with nontraditional risk factors, and a normal/control group.

Enzyme-linked immunosorbent assay (ELISA) was used to estimate the homocys-teine levels, and a significant association between premature CAD risk and elevated levels of homocysteine was found (Barghash, Barghash, El Dine, Elewa, & Hamdi, 2004). Other studies show that those with a history of myocardial infarction tend to have much higher homocysteine levels than controls (Boufidou et al., 2004).

As with cholesterol, genetic and environmental factors contribute to homocys-teine levels. Numerous studies have reported significant heritability for homocyshomocys-teine levels, and the recent AtheroGene study confirmed that homocysteine level is strongly influenced by genetic predisposition (Schnabel et al., 2005). At the molec-ular level, the genetic mutation C677T at the methylenetetrahydrofolate reductase (MTHFR) gene is associated with a substantially elevated risk of hyperhomocys-teinemia and of developing CHD at an early age (Mager, Harell, Battler, Koren–Morag, & Shohat, 2005).

In addition to the genetic factor, hyperhomocysteinemia is associated with folate and vitamin B-12 deficiencies (Saibeni et al., 2005); the former is of less concern due to the folic acid fortification found in many foods today (Green & Miller, 2005).

Vitamin B-6 and riboflavin are also involved in homocysteine metabolism and have been shown to decrease homocysteine levels (Strain, Pentieva, McNulty, Dowey, &

Ward, 2004). Additionally, alcoholics tend to have elevated levels of homocysteine, with the highest levels seen in those with liver damage. Thus, methionine metabo-lism, a factor in liver deterioration, may play a role (Blasco et al., 2005). Some evidence suggests that components of coffee may affect homocysteine levels (Strandhagen & Thelle, 2003).

Inflammation: C-Reactive Protein and White Cell Count

Elevations in serum C-reactive protein (CRP) indicate the presence of inflammation and appear to be associated with an increased risk of coronary artery disease (Bello

& Mosca, 2004; Luc et al., 2003). A recent 10-year prospective study showed that higher baseline levels of CRP were associated with elevated CHD risk, even in the absence of other cardiac risk factors (Cushman et al., 2005). Another study of 30,000 American women also demonstrated that CRP is an independent predictor of CHD incidence when all other known factors are controlled for (Ridker, Rifai, Rose, Buring, & Cook, 2002). Mackness and colleagues showed that higher levels of CRP and lower levels of paroxanase1, an anti-inflammatory agent, were present in indi-viduals with CHD than in controls (Mackness, Hone, McElduff, & Mackness, 2005).

A second marker for inflammation, white blood cell count, may also be a useful predictor of CHD risk (Koren–Morag, Tanne, & Goldbourt, 2005). Additionally, a

The Multifactorial Model of Cardiovascular Pathology 99

recent review of 32 investigations showed that exercise, which reduces cardiovas-cular risk (Courville, Lavie, & Milani, 2005; CDC, 2005; Frank et al., 2005), increases short-term but reduces long-term inflammation, further supporting the role of arterial inflammation in CHD (Kasapis & Thompson, 2005).

Plasma Catecholamines

Several amines that derive from tyrosine and contain dihydroxybenzene rings con-stitute the group of plasma catecholamines, including norepinephrine, epinephrine, and dopamine. Some investigators have reported higher levels of plasma catechola-mines in CHD patients than in controls (Tjeerdsma et al., 2001). However, it thus far appears that these amines are probably not direct causal factors in CHD (Forslund et al., 2002). Rather, they may be associated indirectly through their role in auto-nomic dysfunction (Carney, Freedland, & Veith, 2005) and stress reactivity (Brunner et al., 2002) in metabolic syndrome. The latter is a condition characterized by three or more factors (such as hypertension, abdominal obesity, and high cholesterol) that are believed to lead to CHD and/or type 2 diabetes.

Thus, current research indicates that the plasma catecholamines are most likely a part of the pathway involved in the development of metabolic syndrome. Higher catecholamine levels lead to autonomic dysfunction and stress reactivity, which then give rise to hypertension, abdominal obesity, and other factors that collectively result in metabolic syndrome. The presence of metabolic syndrome then poses a general risk for CHD. Evidence suggests that caffeine increases catecholamine levels in a dose-dependent fashion (Papadelis et al., 2003).

Diabetes

Diabetes mellitus, a disorder of carbohydrate metabolism resulting from insufficient secretion or exploitation of insulin, is commonly regarded as a prime risk factor for CHD (Geronimo, Abarquez, Punzalan, & Cabral, 2005; Kengne, Amoah, & Mbanya, 2005). Type 1 diabetes (Dahl–Jorgensen, Larsen, & Hanssen, 2005; Skrivarhaug et al., 2005) and type 2 diabetes (Shai et al., 2005; Wannamethee, Shaper, Lennon, &

Morris, 2005) have been linked to CHD and other cardiac events. Evidence indicates that a genetic predisposition combines with environmental factors to create the phenotype for diabetes (Roche, Phillips, & Gibney, 2005; Wolford & Vazarova de Courten, 2004). Currently, the proportion of variance attributable to genetics for type 1 and type 2 diabetes, respectively, is 40 to 50% (Kim & Polychronakos, 2005) and about 26% (Poulsen, Ohm–Kyvik, Vaag, & Beck–Nielsen, 1999).

The mechanism by which diabetes increases CHD risk is poorly understood.

One theory is that diabetic patients have diminished sympathetic responses to exer-cise, including lower peak heart rates and smaller plasma epinephrine responses, both of which have been linked to an elevated risk of cardiovascular events (Endo et al., 2000). Other work has shown that increases in hemoglobin A may indicate increased risk for CHD (Selvin et al., 2005). A marker for long-term glycemic control, elevated hemoglobin A signals chronic hyperglycemia, which may be the culprit in the increased risk of CHD seen in diabetics (Selvin et al., 2005). Considerable further research is needed to assess the mechanisms underlying the relationship

100 Caffeine and Activation Theory: Effects on Health and Behavior

between diabetes and CHD. Some evidence suggests that coffee consumption may actually lower the risk for type 2 diabetes, although further work is needed to confirm this association (van Dam, Willett, Manson, & Hu, 2006).

Hypertension

A well-documented CHD risk factor, hypertension involves genetic and environ-mental factors (Aras, Sowers, & Arora, 2005). Research has demonstrated that 30 to 50% of the variance in hypertension is genetic, with such environmental and behavioral factors as obesity, stress, and lack of exercise completing the causal model (Marteau, Zajou, Siest, & Visvikis–Siest, 2005). The genetic component may be expressed in the reduction in endothelial progenitor cells that is associated with hypertension (Urbich & Dimmeler, 2005). In animal and in human trials, increasing the number of these cells appears to reduce atherosclerosis by promoting vascular-ization. The role of caffeine in hypertension is addressed briefly later in this chapter and more comprehensively in chapter 6.

Heart Rate and Arrhythmias

Absolute heart rate and cardiac arrhythmias have been suggested as risk factors.

Lower peak heart rates during exercise (Endo et al., 2000), as well as high resting heart rates (Jouven et al., 2005) may be related to myocardial infarction. Similarly, arrhythmias are associated with acute cardiac events such as sudden cardiac death (Antezano & Hong, 2003; Buxton et al., 2003; de Sutter, Firsovaite, & Tavernier, 2002; Pacifico & Henry, 2003). The effects of caffeine on heart rate and rhythm are addressed briefly later in this chapter and more fully in chapter 4.

Smoking

Smoking is a major risk factor for CHD and cardiac death (Weisz et al., 2005). In fact, smokers have a 70% greater risk of death due to CHD than nonsmokers, and 30 to 40% of CHD deaths result from smoking (Kabat, 2003). Nicotine and carbon monoxide may be the chief pathogens in smoke, but tars may also be involved (Kabat). Moreover, the nitrogen oxides present in smoke are such powerful patho-gens that CHD mortality is higher in neighborhoods where air pollution includes elevations in the levels of these chemicals (Maheswaran et al., 2005).

There is a strong dose-dependent relationship between smoking and CHD, and it appears that smoking may have synergistic interactions with hypertension and hyperlipidemia, thereby further increasing CHD risk (Rigotti & Pasternak, 1996).

In addition, smoking has been shown to reduce the oxygen-carrying capacity of hemoglobin (Sansores, Pare, & Abboud, 1992), create higher blood levels of carbon monoxide (Gottlieb, 1992; McDonough & Moffitt, 1999), contribute to atheroscle-rosis (Ramos & Moorthy, 2005), stimulate platelet production and thereby clotting (Bell, 2004), and increase LDL cholesterol levels (Sharma et al., 2005).

The causal mechanisms underlying the smoking–CHD relationship have been at least partially described:

The Multifactorial Model of Cardiovascular Pathology 101

Smoking may interfere with arterial wall collagen metabolism, which weak-ens arteries and contributes to atherosclerosis (Raveendran et al., 2004).

Nicotine appears to alter the expression of endothelial genes that regulate vascular tone and thrombogenicity, which also increases the risk of athero-sclerosis (Zhang, Day, & Ye, 2000).

Components of smoke may cause or exacerbate proinflammatory and proco-agulatory responses (MacCallum, 2005) and may increase blood levels of homocysteine (Stein et al., 2002).

Smokers exhibit poor dietary habits. As compared to nonsmokers, smokers consume less vitamin C and vitamin E, fiber, and important nutrients, such as beta carotene, thereby increasing their levels of LDL cholesterol (Dallongeville, Marecaux, Fruchart, & Amouyel, 1998; Galan et al., 2005).

Caffeine is associated with smoking in a way that makes some caffeine studies more difficult to interpret, as we will see later in this chapter.

Obesity and Exercise

Obesity has a well-established relationship to CHD and is influenced by genetic as well as environmental factors (Liu, Xiao, Xiong, Recker, & Deng, 2005). Abdominal obesity, in particular, has been linked to higher plasma fibrinogen, a protein important in blood clotting, and other coagulatory abnormalities that are further linked to atherothrombosis (de Pergola & Pannacciulli, 2002). Additionally, left ventricular mass, which can be affected by obesity, is related to CHD (Post, Larson, Myers, Galderisi, & Levy, 1997). On the other hand, regular exercise is associated with improved cardiovascular function and reduced CHD risk (Wamhoff, Bowles, Dietz, Hu, & Sturek, 2002). In fact, some evidence suggests a dose–response relationship.

However, the combination of frequent, intense exercise with a proper diet appears to provide the best cardiovascular outcomes (Al-Ajlan & Mehdi, 2005).

Interactions Among Factors

Although literature assessing the associations among the multiple risk factors is scant, there has been some speculation as to the nature of their interactions. Burns (2003), for example, has recently suggested that the presence of smoking as a risk factor is multiplicative when other risk factors are also present and there is little doubt that overall cardiovascular risk increases with the number of pathogenic factors present in a given individual. We will consider shortly just where caffeine may fit into the overall risk pattern and how it may interact with other factors.