Cardiovascular disease (CVD) is the broad class of diseases that involves the heart or/and blood vessels. CVD includes atherosclerosis, heart valve disease, arrhythmia, heart failure, hypertension, endocarditis, diseases of the aorta, disorders of the peripheral vascular system, and congenital heart disease . However, atherosclerosis accounts for the major part of CVD (up to xx%), and sometimes CVD is misleading used as a synonym for atherosclerosis [REF]. Because atherosclerosis is the underlying disease of several CVD, part of patients, where one diagnosis of CVD became manifest, may present with further co-morbidities, especially other diagnosis of CVD are common. However, the portion of patients with co-morbidities is depending on the baseline disease [2-4]. For example 40-60% of patients with Peripheral Arterial Disease (PAD) also have coronary artery disease (CAD) and cerebral artery disease, but only 10-30% of patients with CAD have also PAD (Figure 1) [2, 4]. Further, the severity of cardiovascular co-morbidities correlates well with each other[5-7]. CVD is today responsible for ca. 30% of all deaths worldwide , while heart disease and stroke are the leading causes of mortality and disability in developed countries . Although the mortality rates of CVD has a considerable variation across countries (xx% in xx to xx% in xx) , a common trend of increasing rates has been observed worldwide. Before 1900, infectious diseases and malnutrition were the most common causes of death throughout the world, and CVD was responsible for <10% of all deaths. In 2030, CDV will account for estimated 32.5% off all death worldwide, what will be equal to a number of 24.2 million deaths per year . Therefore, CVD is seen as a true global epidemic . The economic burden and the public health costs are mainly driven by CVD. In terms of combined morbidity and mortality, 148 million Disability-Adjusted Life-Years (DALYs) were lost worldwide (2002), which represents about 10% of all lost DALYs [REF]. In 2008, CVD costs about 192 billion Euros a year alone in the European Union, which results in a per capita cost of 391 Euros .
Atherosclerosis is the most frequent and important pattern of Arteriosclerosis, other forms of Arteriosclerosis are Mönckeberg medial calcific sclerosis and Arteriolosclerosis, which vary in pathophysiological and clinical presentation . As described above (3.1), atherosclerosis is the leading cause of death (up to 30%) in developed countries and represents the major portion of CVD. Atherosclerosis (literal origin from Greek: athero = “gruel or paste”; sclerosis = “hardness”) is defined as “thickening and loss of elasticity of arterial walls” and describes a process, where fatty substances, cholesterol, cellular waste products, calcium and fibrin building up in the inner lining of arteries . These intimal lesions are called “atheromas”, “atheromatous” or “fibrofatty plaques”, which lead into an obstruction of vascular lumens and weakness the underlying media. Even within a given arterial bed, lesions or stenoses due to atherosclerosis tend to occur focally, typically in certain predisposed regions.
Due to overwhelming importance of atherosclerosis, enormous efforts have been spent to discover its cause over the last few decades. Today, the currently accepted concept, so called “the response to injury hypothesis”, considers atherosclerosis to be a chronic inflammatory response of the arterial wall initiated by injury to the endothelium . Furthermore, lesion initiation and progression are sustained by interaction between lipoproteins, macrophages, T-lymphocytes, and the normal cellular constituents of the arterial wall. This process of developing atherosclerosis, which typically lasts over a period of many years – usually many decades, can be divided into several consecutive steps, as illustrated in Figure 2 [REF]. Parallel, a morphological change is observed within the artery wall, where “fatty streak” represents the initial morphological lesion, even so the pathogenesis has started quite earlier with a chronic endothelial injury [REF]. Figure 2: Illustration of the Pathogenesis and Morphological Development of Atherosclerosis. SMC: Smooth muscle Cell; 6 ?m thick histology slices of coronary arteries stained with Movat’s pentachrome. A: pathological intimal thickening with a “fatty streak”; B: pathological intimal thickening with a macrophage infiltration; C: early fibroatheroma with neoangiogenesis; D: fibroatheroma with thin fibrous cap and a healed rupture; E; late fibroatheroma with a sheet calcification. * demarks necrotic scores. Histology performed by CVPath Laboratory, Maryland, MD. The below described steps of the pathogenesis of atherosclerosis shouldn’t been seen as a separated processes. They are interconnected and occur parallel. Further, several mechanism of vicious circles are described [REF]. However, the stratification into the flowing six steps helps to understand the complex pathogenesis and represents the current understanding:
As the earliest step in the pathogenesis of atherosclerosis, endothelial activation and chronic injury, also known as endothelial dysfunction, have been described . The following factors contributed in different extent to endothelial dysfunction and are partly known as traditional risk factors for atherosclerosis : advancing age, dyslipidemia, hypertension, increased levels angiotensin, insulin resistance and diabetes, smoking, estrogen deficiency. Several biochemical pathways have been described for those factors increasing the endothelial dysfunction. Other factors like hyperhomocysteinemia, possible infection and especially low or oscillatory shear stress are still discussed whether they significantly contribute to endothelial dysfunction [18-22]. The phenotypic features of endothelial dysfunction are described as the reduced vasodilator and increased vasoconstrictor capacity, an enhanced leukocyte adhesion, an increase of pro-thrombotic and decrease of fibrinolytic activity, and an increase in growth-promoting.
In addition and due the endothelial dysfunction lipoproteins, especially low density lipoprotein (LDL), sequestered from plasma in the extracellular space of the arterial intima. Beside the extent of endothelial dysfunction, this process is depending on the concentration of LDL in the blood circulation . Even so several mechanisms have been proposed for transport of LDL into the arterial intima including vesicular ferrying through endothelial cells, passive sieving through endothelial-cell pores, passage between cells, it’s not finally understand. However, strong evidence exist, that the accommodation of LDL in the arterial intima is not only a passive effect by a “leaking” vascular endothelium [REF]. Part of the lipoproteins that have entered the arterial wall stay there and are modified subsequently. Especially the modification of the lipoproteins has a trapping function for die selbigen . The most common modification is the oxidation of lipoproteins, giving rise to hydroperoxides, lysophospholipids, oxysterols, and aldehydic breakdown products of fatty acids and phospholipids. But further modification like fusion of lipoproteins, proteolysis, lipolytic degradation and glycation are well known . Such modified lipoproteins or particles of the modification process have inflammatory potential and trigger a local inflammatory response responsible for signaling subsequent steps in the atherogenesis. It includes a further increased endothelial dysfunction, which may cause a vicious circle of LDL accumulation, and activation of various cell types [24, 26, 27].
More important, the inflammatory response induces migration of leukocytes such as monocytes or lymphocytes into the lesion. Leukocytes are attracted by chemoattractant factors including modified lipoprotein particles themselves and chemoattractant cytokines depicted by the smaller spheres, such as the chemokine monocyte chemoattractant protein-1, interleukin 1 (IL-1) or tumor necrosis factor alpha (TNF-?) produced by vascular wall cells in response to the inflammatory process [REF]. The activated arterial endothelial cells express a number of adhesion molecules and receptors on their surface, which participate in the recruitment of leukocytes from the blood to the nascent lesion [REF]. Macrophages are a key player in atherogenesis . They develop from recruited monocytes, which migrated as described above into the lesion. In the mediator stimulated process of maturation, those macrophages become lipid-laden foam cells by uptake of lipoprotein particles through receptor-mediated endocytosis [REF]. The accumulation of lipid in the macrophages results in the apoptosis and necrosis, which lead first to a boosted expression and secretion of inflammatory cytokines and second to a release of their lipid excess into a necrotic lipid-core [REF]. Macrophages further produce enzymes, such as metalloproteinases, that degrade the extracellular matrix and lead to instability of plaques [REF].
The inflammatory process, especially triggered by the necrosis of the foam cells, microscopic breaches in endothelial integrity may occur. Platelets adhere to such sites of limited endothelial denudation owing to exposure of the thrombogenic extracellular matrix of the underlying basement membrane and form microthrombi. Although most of the arterial mural microthrombi resolve without any clinical manifestation, they lead indirectly to lesion progression by pro-fibrotic stimulation [REF]. The platelets, activated by adhesion, release numerous factors that promote a fibrotic response, including platelet-derived growth factor (PDGF), fibroblast growth factor (FGF), insulin-like growth factor 1 (IGF-1), and transforming growth factor alpha (TGF-?) [28-30]. Thrombin itself generates fibrin that has a pro-fibrotic stimulus .
The pro-fibrotic response includes first the migration of SMC from the media of the arterial wall, through the internal elastic membrane, and the accumulation within the expanding intima of the arterial wall. Second, stimulate the proliferation of SMC, which is responsible to form the bulk of the advanced lesion. Another part of the advanced lesions is an increased extracellular matrix. TGF-? and other mediators stimulate the interstitial collagen production by SMC. These mediators may arise not only from neighboring endothelial cells or leukocytes (a “paracrine” pathway) but also from the same cell that responds to the factor (an “autocrine” pathway). Together, these alterations in smooth-muscle cells, signaled by these mediators acting at short distances, can accelerate transformation of the early lesion (“fatty streak”) into a more fibrous SMC and extracellular matrix-rich plaque.
The formation of a complex atherosclerotic lesion is characteristic by an extent remodeling process. Further foam cells within the expanding intimal lesion perish, while they phagocytose more and more lipids. The fibrotic cap between the so arisen lipid-rich necrotic core and the vascular lumen may vary in thickness and allows the classification of “thin cap fibroatheroma”, which correlates with a higher risk for acute luminal thrombosis [REF]. The production of extracellular matrix, as well plaque evolution and complication can be stimulated by diverse growth factors or cytokines like IL-1 or TNF-?, and can be inhibited by other cytokines (e.g. interferon alpha (IFN-?)) [REF]. As atherosclerotic plaques advance, they show intimal arterial calcification [REF]. The same proteins, which can be found in bone, are also localize in atherosclerotic lesions, e.g., osteocalcin, osteopontin, and bone morphogenetic proteins . Both, passive and active models are discussed for the development calcification . SMC can, promoted by several cytokines (e.g. transcription core binding factor ?1), acquire osteoblast-like characteristics and secrete bone matrix . These examples illustrate how the pathogenesis of atherosclerosis involves a complex mix of mediators that in the balance determines the characteristics of particular lesions [REF].
The role of inflammation is central, while those inflammatory mechanisms mediate initiation, progression, and the complications of atherosclerotic lesions [26, 34]. Through the inflammatory process, arterial endothelial cells begin to express on their surface selective adhesion molecules that bind various classes of leukocytes, especially monocyte and T lymphocyte which are found in early human and experimental atheroma [REF]. After monocytes adhere to the endothelium, they can first migrate in the intima, largely stimulated by chemokines; and second transform into macrophages and avidly engulf lipoproteins, largely oxidized LDL [REF]. Although the phagocytosis of potentially harmful lipid particles by macrophages and subsequently the transformation into foam cells has an initially protective, this process involves further expression and secretion of inflammatory chemokines like Interleukin (IL)-1, Monocyte Chemotactic Protein (MCP)-1 or Tumor Necrosis Factor (TNF)-?. Those enhance the inflammatory reaction and enable the further migration of leukocytes into the lesion [REF]. Macrophages also produce toxic oxygen species that cause additional oxidation of the LDL in the lesions, and they elaborate growth factors that may contribute to SMC proliferation [REF]. Similary, T lymphocytes (both CD4+ and CD8+) are also recruited to the intima by chemo-attractants. Cross-talk between macrophages and T cells induces a chronic inflammatory state regarding cellular and humoral immune activation characteristics. This state of a chronic inflammation leads also to the next observed steps in the development and progression of atherosclerosis. Thus, it stimulates the migration and proliferation of smooth muscle cells (SMC), as well the proliferation of vascular endothelial cells in the lesion. Through fibrogenic mediators, released from activated leukocytes and intrinsic arterial cells, the replication of SMCs is getting enhanced and contributes to elaboration by these cells of a dense extracellular matrix characteristic of the more advanced atherosclerotic lesion.
The vasa vasorum of the aorta is as a plexus in the wall of artery of microvessels, which are functional endarteries [35, 36]. They either originate from major branches, originate from the main lumen of the aorta or drain in concomitant veins . These vessels allow the humoral communication between intravascular lumen, vessel wall and adventitial layer of large arteries including oxygen and nutrients supply [REF]. Several studies demonstrated that hypoxia , cytokines (e.g. vascular endothelial growth factor) [39, 40], pro-angiogenic factors (e.g. hypertension or hypercholesterolemia) stimulate the growth of the vasa vasorum . Those increased microvascular network may contribute to inflammation and lesion complications in several ways. First, the vasa vasorum provides an abundant surface area for leukocytes trafficking and may serve as the portal of entry and exit of white blood cells from the established atheroma. Microvessels in the plaques may also furnish foci for intraplaque hemorrhage. Like the neovessels in the diabetic retina, microvessels in the atheroma may be friable and prone to rupture and can produce focal hemorrhage. Such a vascular leak leads to thrombosis in situ and thrombin generation from prothrombin. In addition to its role in blood coagulation, thrombin can modulate many aspects of vascular cell function, as described above. Atherosclerotic plaques often contain fibrin and hemosiderin, an indication that episodes of intraplaque hemorrhage contribute to plaque complications. Multiple and often competing signals regulate these various cellular events. Increasingly, we appreciate links between atherogenic risk factors, inflammation, and the altered behavior of intrinsic vascular wall cells and infiltrating leukocytes that underlie the complex pathogenesis of these lesions. The present data indicate that vasa vasorum neoangiogenesis and atherosclerosis are seemingly inseparably linked, triggered and perpetuated by inflammatory reactions within the vascular wall.
Local shear stress – In the coronary circulation, for example, the proximal left anterior descending coronary artery exhibits a particular predilection for developing atherosclerotic disease. Likewise, atherosclerosis preferentially affects the proximal portions of the renal arteries and, in the extracranial circulation to the brain, the carotid bifurcation. Indeed, atherosclerotic lesions often form at branching points of arteries, regions of disturbed blood flow. Age, Gender, HTN, HLP, DM, Smoking, Race/Ethnicity,
In the characteristic distribution of atherosclerotic plaques in humans the abdominal aorta (Fig. 11-8) is usually much more involved than the thoracic aorta, and lesions tend to be much more prominent around the origins (ostia) of major branches. In descending order (after the lower abdominal aorta), the most heavily involved vessels are the coronary arteries, the popliteal arteries, the internal carotid arteries, and the vessels of the circle of Willis. Vessels of the upper extremities are usually spared, as are the mesenteric and renal arteries, except at their ostia. Nevertheless, in an individual case, the severity of atherosclerosis in one artery does not predict the severity in another. In an individual, and indeed within a particular artery, lesions at various stages often coexist. 2009_Dijk_The natural history of aortic atherosclerosis_A systematic histopathological evaluation of the peri-renal region.pdf
Peripheral Arterial Disease (PAD) is caused by atherosclerosis and represents the most common cause of lower extremity ischemic syndromes in developed countries . Symptoms of PAD are variable including pain, ache, hair loss, thickened nails, smooth and shiny skin, reduced skin temperature, cramp, muscle atrophy, or a sense of fatigue in the muscles. Because of the variability of symptoms, the diagnosis of PDA is frequently missed . In addition, the major part of patients with PAD is asymptomatic [REF]. Beside these diagnostic challenges, PAD affects a large and increasing numbers of patients worldwide. Round 30 million people are diseased in worldwide, but of those only 10 million patients are presenting with symptoms . Further, the prevalence is increasing with age [6, 45], while the prevalence is 10% at the age of 60 years . Association to mortality!!!
The leading cause of PAD is atherosclerosis, especially in older patients (>40 years) and at the lower extremities . Other, but rare causes of PAD include embolism, vasculitis, fibromuscular dysplasia, entrapment, and trauma. Atherosclerotic lesions, which are segmental and cause stenosis, are usually localized to large and medium-sized vessels. The pathology of these lesions is based on atherosclerotic plaques development, as described above (xxx). The primary sites of involvement are the abdominal aorta and iliac arteries (30% of symptomatic patients), the femoral and popliteal arteries (80-90%), and the more distal arteries (40-50%) [REF]. Atherosclerotic lesions have been predominantly observed at arterial branch points. These may be explained by altered shear stress [REF]. However, the involvement of the distal and smaller arteries is more common in elderly individuals and patients with diabetes mellitus [REF].
While atherosclerosis is the major underlying condition of PAD, the risk factors for PAD are essentially the same as those for other form of atherosclerosis (like e.g. CAD), see Table 1 [47-50]. However, the risk factors smoking and diabetes may have even greater effect for PAD as compared for CAD .
Increased risk for PAD Hypercholesterolemia 1- to 2-fold (low) Homocysteinemia 1- to 3-fold (moderate) Hypertension 1- to 3-fold (moderate) Smoking (current and past) 2- to 4-fold (high) Diabetes mellitus 2- to 4-fold (high)
PAD affects more often the lower extremities (xx times more often than upper extremities) [REF]. The most common symptom of PAD is intermittent claudication, which is defined as presence of pain, ache, cramp, numbness, or a sense of fatigue in the muscles. Those symptoms occur during exercise and are relieved by rest, as result of the increased muscle ischemia during exercise caused by obstruction to arterial flow. Patients with PAD in the lower extremities resulting in ischemia may range in presentation from no symptoms to limb-threatening gangrene. Two major classifications based on the clinical presentations are established, the Fontaine and the Rutherford classification. While the more simple Fontaine classification consists of four stages (Table 2) , the Rutherford classification has four grades (0-III) and seven categories (0-6). Asymptomatic patients are classified into Rutherford category 0. Any patient with claudicants are stratified into Rutherford grade I and divided into three categories based on the severity of the symptoms. If patients have pain at rest, they belong to Rutherford grade II and category 4. Any patient with tissue loss are classified into Rutherford grade III and categories 5 and 6, based on the significance of the tissue loss . These two clinical classifications can be translated into each other according to Table 2.
Rutherford Classification Stage Clinical Grade Category Clinical I Asymptomatic 0 0 Asymptomatic IIa Mild claudication I 1 Mild claudication IIb Moderate to severe claudication I 2 Moderate claudication I 3 Severe claudication III Ischemic rest pain II 4 Ischemic rest pain IV Ulceration or gangrene III 5 Minor tissue loss III 6 Major tissue loss
In the Framingham Offspring Study, the prevalence of PAD was determined in 1554 males and 1759 females from 1995 to 1998.55 The mean age was 59 years. PAD, defined as an ankle-brachial (blood pressure) index (ABI) of <0.90, was present in 3.9 percent of males and 3.3 percent of females. Yet, the prevalence of intermittent claudication was only 1.9 percent in males and 0.8 percent in females suggesting that only half of men and only a quarter of women have subjective symptoms. Lower extremity bruits were present in 2.4 percent of males, 2.3 percent of females; prior surgical intervention was 1.4 percent in males and 0.5 percent in females. The PARTNERS (PAD Awareness, Risk, and Treatment: New Resources for Survival) program assessed the prevalence of PAD in patients older than age 70 years and those ages 50 to 69 years with a smoking history or diabetes at 250 primary clinics across the United States.56 As defined by a charted or screening ABI of <0.90, 29 percent of the population was found to have PAD. There was a high incidence (nearly half) of concurrent coronary or cerebral vascular disease.
The physician also queried the participant about symptoms of intermittent claudication using a standardized questionnaire .
SACK: Epicardial, mesenteric, and omental fat all share the same origin from the splanchnopleuric mesoderm associated with the gut.11 Pericardial fat (pericardial adipose tissue [PAT]) is defined as epicardial fat in all these possible locations plus paracardial fat.14 Paracardial fat is situated on the external surface of the parietal pericardium within the mediastinum and has alternatively been termed mediastinal fat.15 Paracardial fat originates from the primitive thoracic mesenchyme, which splits to form the parietal (fibrous) pericardium and the outer thoracic wall.16 Epicardial adipose tissue is supplied by branches of the coronary arteries, whereas paracardial fat is supplied from different sources including the pericardiacophrenic artery, a branch of the internal mammary.17 Lipolysis and lipogenesis have not been measured directly in human epicardial fat. Based on approximately 2-fold higher rates of lipolysis and lipogenesis in guineapig epicardial fat than other fat depots, Marchington et al18,19 proposed that EAT serves to capture and store intravascular free fatty acid (FFA) to protect cardiomyocytes from exposure to excessive coronary arterial FFA concentrations during increased energy intake and, at other times, to release FFA as an immediate ATP source for the myocardium during periods of need. Epicardial fat and the myocardium are contiguous. Islands of mature adipocytes are more frequent within the subepicardial myocardium of the RV than the LV13 and may act as more readily available, direct sources of FFA for cardiomyocytes. The thickness of the wall of the right atrium is about 2 mm; the left atrium, 3 to 5 mm; the RV, 3 to 5 mm; and the LV, 13 to 15 mm.20 Possibly, FFAs could diffusebidirectionally in interstitial fluid across concentration gradients from epicardial fat into the atrial and RV walls where EAT predominates and vice versa, but this process in the LV wall can be questioned because the diffusion distance is much longer. Peri-vascular adipose tissue is defined as any adipocytes, which are located close to the vascular wall and has the possibility to secret their biomarkers into the vasa vasora of the wall (see 220.127.116.11).
Adipose tissue is known to have more functions than lipid storing. Adipose tissue secrets biomarkers and serves as an endocrine organ. Beside hormones, it secrets also different inflammatory cytokines and chemokines. The amount of adipose tissue were associated to xxx, xxx, xxx (FRAMINGHAM?!). Especially peri-vascular adipose tissue like epicardial or visceral adipose tissue demonstrated higher expression of inflammatory biomarkers compared to other adipose tissue depots in the body [REF]. Beside the systemic effect of the secreted cytokines and chemokines, also a local effect/paracrine is hypothesied. Biomarkers secreted of peri-vascular adipose tissue reach over the vasa vasora of the major arteries their adventitia, media, and intima. Therefore it might be involved in the inflammatory process of atherosclerotic plaque. Further, a local effect can be thought by direct diffusion.
* BMI and WC 
* dual energy X-ray absorptiometry (DXA)  * magnetic resonance imaging (MRI) [56, 57] * ultrasound  * multi-detector computed tomography (MDCT) [59, 60]
Infectious diseases were prior to World War II the major burden for public health. But through a greater microbiological knowledge and improved sanitation, the morbidity and mortality of infectious disease decreased continuously. When penicillin was introduced in 1942, a dramatic reduction was made in the prevalence and incidence of infectious diseases, especially by controlling tuberculosis and pneumococcal pneumonia [REF]. Replacing infectious diseases, public health was challenged by a mounting epidemic of CVD starting in the 1940s. With World War II over the alarming rise of CVD became increasingly evident. In the United States, 30% of all men developed CVD before reaching the age sixty. The prevalence of CVD was twice of cancer by 1950 and had become the leading cause of death [REF]. Even so the available statistic data from around the world was often crude and inaccurate, it clearly demonstrated a worldwide atherosclerotic CVD problem. Furthermore there was no known treatment to prolong life and to reduce mortality. Added to these distresses was the fact that little was known about etiology, pathogenesis and epidemiology of CVD. The big gap between the enormous public health burden of CVD on the one site and the little understanding of this disease on the other site increased drastically the need for action. At this time, some believed a primary preventative approach was more promising than a search for cures [Dawber, Thomas R. (1980), The Framingham Study: The Epidemiology of Atherosclerotic Disease, Cambridge, Mass.: Harvard University Press.], while the secrets of the etiology of CVD – and subsequently for treatment – were not being uncovered by basic laboratory and clinical research. Some of these prevention-minded individuals occupied positions of influence and were able to translate their beliefs into actions. The key was to develop a preventive approach, where first of all the characteristics of the “host and environment”, which lead to the early appearance of the disease, had to be determined. In particular, preventable or modifiable predisposing factors had to be identified. If a practical preventive approach was developed, the hope was that doctors and public health officials would adopt it and so have a widespread impact on the reduction of CVD-based morbidity and mortality. Accordingly to the preventive approach, the Framingham Heart Study was designed given the charge to identify these modifiable characteristics of host and environment for CVD.
By the mid 1940s several striking studies were conducted with an examples epidemiological approach in the fields of nutritional imbalance, metabolic disorders, occupational hazards, accidents, cancer and rheumatic fever under principle investigators (PI) Drs. Dawber, Meadors and Moore [REF, Dawber, Meadors and Moore 1951]. In common, an association between the circumstances and the disease could be identified with-out knowledge of the precise etiology. One of those studies was performed by Dr. John Snow in 1936. He demonstrated that cut-ting off the water supply from contaminated wells, despite incomplete knowledge of the pathogenesis of the disease, stopped cholera. He observed on the one hand the source of the water supply and on the other hand the time and place where the disease occurred. He sufficiently pinpointed based on his observations the major environmental factor for cholera. Further investigations into the nature of the offending water could uncover the precise etiology. Thus for CVD the epidemiological approach had promise and the need was obvious. By December 1946 two major projects were planned through the initiative of Dr. Joseph W. Mountin (1891-1952) – a visionary public health leader: the Cardiovascular Hygiene Demonstration in Newton, Massachusetts (PI: Dr. Robbins) and the Heart Disease Epidemiology Study in Framingham, Massachusetts (PI: Dr. Meadors). The latter study started as a demonstration program designed to develop case finding procedures for heart disease. It began accepting volunteers. But after the first exam of the volunteers in September 1948, it became clear that the Framingham Study should pursue more epidemiological goals as discussed thought initially. However, the study would be long and expensive to satisfy best the above objective. This was beyond the capabilities of any one investigator or private institution. Fortunately, the National Heart Institute was founded recently and the Framingham Study was transferred to this governmental controlled and funded institute. In the following years, Dr. Meadors and Felix E. Moore, Jr. (head of the Biometry Unit at the National Heart Institute), developed the formal study protocol and sampling plan to change the Framingham Study into a prospective epidemiological investigation. In April 1950 the study was formally launched by the appointment of Dr. Thomas R. Dawber as the first Director of the Framingham Study.
The objective of the Framingham Heart Study was and is to identify the common factors or characteristics that contribute to CVD by following its development over a long period of time in a large group of participants who were free of clinical symptoms or diagnosis of CVD at the baseline exam. Currently, the NHLBI and the Framingham investigators have expanded their research into further areas such as the role of genetic factors in CVD or new risk markers for CVD. Because of the unique role of the Framingham Heart Study and their profound epidemiological data, Framingham investigators collaborate with leading researchers from around the world on projects including diseases such as stroke and dementia, osteoporosis and arthritis, nutrition, diabetes, eye diseases, hearing disorders, lung diseases, and genetic patterns of common diseases. UDO -> NHLBI Application
UDO -> NHLBI Application * multifactorial causes of CVD * longitudinal study
Previously experiences demonstrated that in the aspired circle of two years that about 6,000 exams could be given in the setting of Framingham Heart Study. The target population was between 30 and 59 years, because they developed on the one hand CVD with a high frequency but on the other hand they would not have a large proportion with preexisting CVD. To achieve the desired sample size of 6,000, the investigators enrolled about two-thirds of the available the population in this age rang in Framingham, MA. They estimated that about 1,000 (17%) would have to be excluded because of preexisting CVD at the baseline exam. Of the remaining 5,000, the investigators estimated that about 400 would develop CVD within five years of the first exam, about 900 by ten years, and 2,150 by the end of twenty years [REF: Gordon and Kannel, 1968a]. The sample plan included separated list of all families for each of the eight precincts in the town. The sample was drawn systematically by arranging each of those eight lists first by family size and then in serial order by address. Two of every 3 families were then selected for the sample. In each family all residents in the eligible age range (due day: January 1, 1950) were invited to have the baseline exam. The new founded Neighborhood Organizations committee ensured that all selected families were contacted by someone they knew personally and urged to participate in the Framingham Heart Study [REF: Dawber, Meadors and Moore, 1951; Feinlieb, 1983 and Gordon and Kannel, 1968a].
The sample was drawn from families living in Framingham, MA – a town with basically middle class whites in 1948. This decision was based on the historical and political development, as described above (chapter 3.3.2), much more then on a reasoning for an epidemiological study. However, this potential bias was recognized from the start and the justification of it was done post-hoc [REF: Dawber and Moore, 1952, p. 242]. While the Framingham investigators have always been aware that the Framingham, MA may not be representative of the whole United States and they have made repeatedly comparisons with other regions to test its generalizability [REF]. Even so the selection process for the geographic location was not driven by the needs for an epidemiological study, Framingham, MA did have certain characteristics that made it eminently suitable for a long-term epidemiological study. Drs Feinlieb et al. described them as the following [REF: Feinlieb 1938]: * Framingham, MA was of adequate size to provide enough individuals for the study. * Framingham, MA was compact enough that the study population could be observed conveniently. * Framingham, MA contained a variety of socioeconomic and ethnic subgroups to provide contrasting groups for analysis. * Framingham, MA had a relatively stable population that enabled adequate follow-up for a long time. This was partly due to a stable economy supported by a diversity of employment opportunities. * Framingham, MA was located near a medical center which could provide consultations and the opportunity for educational development of the staff. * Framingham, MA maintained an annual list of its residents and the staff of a well organized health department helped to provide death certificate information and other vital statistics. * Framingham, MA had been the sight of a community study of tuberculosis nearly 30 years before that had had successful participation by the town’s people. It was believed that this spirit of cooperation was still present in 1949.
The Framingham Heart Study has enrolled so far six groups of participants with in total 15,447 participants, Table 3. In 1948, the first group “Original Cohort” consisted of 5,209 respondents a random sample. They have represented about 2/3 of the adult population of Framingham,MA. The second group was the “Offspring Cohort” and represented the children of the 1387 spouse pairs in the Original Cohort, which had at least one child. In total 5,124 men and women were enrolled in 1971 for the Offspring Cohort, when the need for establishing a prospective epidemiologic study of young adults was recognized [REF]. So far, the Offspring Cohort underwent eight follow up exams, the last began in 2005. The third group was the “Third Generation Cohort”. This cohort existed of prospective participants who had at least one parent in the Offspring Cohort and was at least 20 years old [REF]. The recruitment target of 4,095 participants for the Third Generation Cohort was achieved by July 2005 including a greater resource of phenotypic and genotypic information as compared to the previously two groups [REF].
Initiated in Total number of a cohort Male participants of a cohort Original Cohort 1948 5,209 2,336 (45%) Offspring Cohort 1971 5,124 2,483 (48%) Third Generation Cohort 2002 4,095 1,913 (47%) New Offspring Spouse Cohort 2003 103 47 (46%) Omni Generation 1 Cohort 1994 506 212 (42%) Omni Generation 2 Cohort 2003 410 177 (43%)
Further groups in the Framingham Heart Study were the “New Offspring Spouse Cohort”, “Omni Generation 1 Cohort” and “Omni Generation 2 Cohort”, the last two were initiated to reflect the increasing diversity of the community in Framingham, MA. While the first four groups were primarily Caucasian, residents of Framingham, MA with African-American, Hispanic, Asian, Indian, Pacific Islander and Native American origins were eligible for Omni Generation 1 Cohort and Omni Generation 2 Cohort [REF].
UDO -> FHS imaging grant application?
In 1971, the Framingham Offspring Study enrolled 3,539 spouses and children of the original Framingham Heart Study cohort [61, 62]. Between June 2002 and April 2005, there were 1,422 subjects from the Framingham Offspring Study that underwent chest and abdominal multi-detector computed tomography (MDCT) and were eligible for the peri-aortic adipose tissue measurements.
For the assessing the association between peri-aortic adipose tissue and traditional risk factors, as well aortic atherosclerosis, we included only subjects which were free of established cardiovascular disease. Of these, subjects attended exam 7, and had a complete covariate profile, which were included in this analysis.
For the assessing the association between peri-aortic adipose tissue and peripheral artery disease, we included only subjects with non-missing ABI and complete covariates profile. Further, all subjects with ABI >1.4 were excluded because these values are consistent with non-compressible, calcified arteries, and including these values might have resulted in misclassification . Only subjects, who attended exam 8, and had a complete covariate profile, which were included in this analysis.
The study protocol was approved by the institutional review board of the Boston University Medical Center and Massachusetts General Hospital. All subjects provided written informed consent.
We measured adipose tissue volume using multi-detector CT. Images were analyzed on a dedicated offline workstation (Aquarius 3D Workstation, TeraRecon Inc., San Mateo, CA, USA). Because the CT attenuation in absolute Hounsfield units (HU) corresponds to tissue properties, we applied an automatic threshold-based algorithm to identify voxels containing adipose tissue and to determine the volume of adipose tissue using a HU range from -195 to -45 HU [64-66]. Two experienced observers performed a sub-analysis regarding adipose tissue measurements of 100 subjects in random order to assess for inter-observer variability (CLS and SJL), blinded to the readings of the other observer. One reader (CLS) repeated the analysis 1 week later to assess for intra-observer variability.
All subjects underwent computed tomography (CT) scanning in a supine position using an eight-slice MDCT (LightSpeed Ultra, General Electric, Milwaukee, WI, USA).
Helical non-gated CT imaging of the abdomen was performed subsequently (tube voltage: 120 kVp, tube current: 320 or 400mA in participants with a weight of <220 or >220 lbs; respectively). Gantry rotation time was 500ms with a pitch of 1.33 to cover 150mm above the upper edge of S1. Slices were obtained with 8×2.5mm detector width and reconstructed with a 2.5mm slice thickness and a 35 cm field of view.
CT imaging of the thorax was performed during a single inspiratory breath hold with a tube voltage of 120 kVp and a tube current of 320mA in participants with a weight of <220 lbs. Similar to the abdominal scans, the tube current was adjusted in participants with a weight of >220 lbs to 400mAs. The scans were acquired using prospective ECG triggering with the center of the acquisition at 70% with a gantry rotation time of 500 ms and a temporal resolution of 330 ms. The scan covered the region from carina to diaphragm with a slice thickness of 2.5mm. An average scan length of 18 s followed from these parameters. The images were reconstructed with 2.5mm thick, non-overlapping slices in 25cm field of view.
Measurements of abdominal periaortic adipose tissue. To separate periaortic from retroperitoneal adipose tissue and to standardize our measurements, we defined our region of interest in each slice as a circle that had a diameter which was 10mm larger than the anterior-posterior aortic diameter. This predefined ROI was centered over the aorta (Figure 3). This standardization enabled the capture of a cylinder of periaortic adipose tissue. The volume of periaortic adipose tissue was measured over 16 contiguous slices, covering 40mm above the aortic bifurcation. The first slice above the aortic bifurcation was defined as the slice where the difference between transversal and anterior-posterior diameter were less than 1mm. We excluded subjects in whom the difference between transverse and anterior-posterior diameter remained <5mm within the volume of interest because the oval shape of the aorta precluded a standardized measurement of the peri?aortic adipose tissue cylinder. In addition, we excluded all subjects in whom <40mm of the aorta above the bifurcation was captured on CT. To account for the linear relationship between the aortic diameter and the area of the abdominal peri?aortic adipose tissue (AAT) cylinder, given by Equation 1. All AAT measurements were adjusted for aortic diameter (anterior-posterior diameter, first slice above the bifurcation). Equation 1 – Relationship between the Aortic Diameter and the Area of the Abdominal Periaortic Adipose Tissue (AAT) cylinder. V: volume of perivascular adipose tissue (in mL), ?: pi (3.14), d: aorta diameter (in mm), c: thickness of the circle around the aorta (5mm), h: height of the total volume (40 mm).
In contrast to the abdominal aorta, thoracic periaortic adipose tissue can be clearly separated from other anatomical structures. Thus, the region of interest included all of the adipose tissue surrounding the thoracic aorta. The volume of interest was extended 67.5mm below the level of the pulmonary artery bifurcation, which was the highest common denominator for all subjects (Figure 3). If necessary, manual adjustments were made throughout the analyzed imaging volume. Subjects with hiatal hernia and intra-thoracic stomach were excluded from the analysis. Measurements of Abdominal and Thoracic Peri-Aortic Adipose Tissue. Figure 3A demonstrates the schematic border for periaortic adipose tissue around the abdominal (AAT) and Figure 3C around the thoracic (TAT) aorta. 3D rendered volumes are illustrated for of AAT (Figure 3B) and TAT (Figure 3D).
For the assessment of aortic calcification, we used the same multi-slice CT scans as for the assessment of adipose tissue (CT scan protocols see 5.2.1). Both CT scans, thoracic and abdominal, were read by an experienced observer for the presence and quantity of thoracic aortic calcium and abdominal aortic calcium using a dedicated workstation (Aquarius, Terarecon). A calcified lesion in the aorta was defined by the presence of at least 3 connected pixels with attenuation >130 HU. In addition, an Agatston score was calculated by multiplying the lesion area by the attenuation score (in HU). Presence of both thoracic and aortic calcium was based on age and sex-specific 90th percentile cut points derived from a healthy referent sample.
The presence of PAD was defined in two different ways, first by clinical assessment using a dedicated questionnaire and second by the Ankle-Brachial blood pressure Index (ABI).
As part of routine FHS research exams, a physician-administered medical history interview was conducted that included queries about lower extremity revascularization. Medical records were obtained to verify self-report of all revascularization procedures. The physician also queried the participant about symptoms of intermittent claudication using a standardized questionnaire . Intermittent claudication was defined as exertional discomfort in the calf that appeared sooner with uphill or more rapid paced walking and was relieved with rest. An endpoint review panel of three senior investigators made the final determination of the presence of intermittent claudication.
At exam 8 of the Framingham Offspring Study Examination (2005 to 2008) ankle and brachial blood pressures were routinely measured on all participants. Participants rested for a minimum of five minutes in the supine position on the examining table prior to blood pressure measurement. Blood pressure cuffs were applied to bare ankles with the midpoint of the bladder over the posterior tibial artery approximately three centimeters above the medial malleolus. Systolic blood pressure was obtained using a 9.6 megahertz Doppler pen probe and an ultrasonic Doppler flow detector (Parks Medical Electronics, Inc.). For each limb, the cuff was inflated rapidly to the maximal inflation level and deflated at a rate of 2mmHg per second until the systolic blood pressure became audible. Measurements were obtained in the following order: right arm, right ankle, left ankle, left arm. All limb blood pressures were repeated in reverse order. Measurement was obtained from the dorsalis pedis artery only if the posterior tibial pulse could not be located by palpation or with the Doppler pen probe. The Ankle-Brachial Blood Pressure Index (ABI) was calculated for each leg as the ratio of the average systolic blood pressure in the ankle divided by the average systolic blood pressure in the arm. The higher arm mean was used to calculate the ankle-brachial index for each leg. The lower of the ABIs from the two legs was used for analysis. An ABI of ?0.9 was considered as pathologic regarding PAD.
The demographics of all scanned subjects of the Framingham Heart Study, Offspring Cohort (n=1,422) and of subgroups for each separated analysis are shown in Table 4. All scanned subjects Subgroup “repro-ducibility”1 Subgroup “cardiovascular risk factors /aortic calcification”2 Subgroup “Peripheral Artery Disease”3 N 1,422 100 1,067 1,205 Age, years 60 (13) 59 (9) 66 (9) Women, % 50 54 50 Body Mass Index, kg/m2 27.8 (4.6) 28.4 (5.3) 28.1 (5.1) Waist Circumference, cm 99.1 (12.5) Triglycerides, mg/dL* 133 (77-165) 102 (73, 144) HDL cholesterol, mg/dL 54 (16) Total cholesterol, mg/dL 202 (35) Total/HDL cholesterol 3.74 (??) 3.52 (1.05) Systolic blood pressure, mm Hg 125 (18) Diastolic blood pressure, mm Hg 75 (9) Hypertension, % 36.2 57.1 Fasting plasma glucose, mg/dL 101 (21) Impaired fasting glucose, %† 33.0 Diabetes mellitus, % 9.3 8.1 Smoking, % Current Former Never 9.0 50.9 40.1 8.8 ?? ?? Metabolic Syndrome, % 38.3 Lipid Treatment % 42.9 Postmenopausal, % 81.1** Hormone replacement therapy, % 36.6** Alcohol use, %‡ 15.9 Visceral Adipose Tissue, cm3 2030 (1014) 2009 (1037) 2090 (1100)
Subgroup of subjects who were randomly picked for reproducibility analysis; 2) Subgroup of subjects who were free of CDV disease and included into the analysis of the association of peri-aortic adipose tissue to established cardiovascular risk factors and aortic calcification; 3) Subgroup of subjects who were included into the analysis of the association of thoracic peri-aortic adipose tissue to peripheral atery disease. *Median with 25th-75th percentiles. †Defined as fasting plasma glucose 100-125mg/dL (based on participants without diabetes). **Percentage refers only to women. ‡Defined as ?14 drinks per week (men), or ?7 drinks per week (women). HDL indicates high density lipoprotein.
The assessment of the CT scans was performed between September 2007 and October 2007. On average, the evaluation took 6 min for each subject and each measurement. Of 1,422 eligible subjects, the measurement of abdominal peri-aortic adipose tissue was conducted in 1,262 subjects. 132 subjects (9%) were excluded because of a non tolerable change in the aortic diameter (>5mm) or because the abdominal CT scan covered <40mm of the aorta above the aortic-iliac bifurcation, Table 5. Further, the abdominal CT scans of 14 subjects were missing and 6 were damaged. Thoracic peri-aortic adipose tissue measurements were performed in 1370 subjects. 30 subjects (2%) were excluded because of the CT scan covered <67.5 mm of the aorta below pulmonary artery bifurcation, or because a hiatus hernia, intrathoracic stomach or esophagus diverticulum was presented, Table 5. N %* Abdominal Peri-Aortic Adipose Tissue Measurements Subjects were excluded, because – the aortic diameter changed >5 mm within the included area – CT scan covered <40mm of the aorta above aortic-iliac bifurcation 132 120 12 9% Missing abdominal CT scan 14 1% Damaged abdominal CT scan 6 <1% Thoracic Peri-Aortic Adipose Tissue Measurements Subjects were excluded, because – CT scan covered <67.5mm of the aorta below pulmonary artery bifurcation – presence of a hiatus hernia or intrathoracic stomach – presence of esophagus diverticulum 30 27 2 1 2% Missing thoracic CT scan 14 1% Damaged thoracic CT scan 8 <1%
The mean volume AAT is xx with a standard deviation of xx. The volume for AAT ranges from xx to xx. The median is with xx (interquartile range: xx – xx) slightly above the mean volume of AAT, Figure 4. The mean TAT is xx with a standard deviation of xx. The measurements range from xx to xx. The median was xx (interquartile range: xx – xx), Figure 4. The mean volumes of thoracic and abdominal peri-aortic adipose tissue are higher in men (20.3 and 8.7 cm3) than women (11.9 and 4.8 cm3, p<0.05). There is a strong correlation between thoracic and abdominal peri-aortic adipose tissue (r=0.59, p<0.001).
Reproducibility of the new measurements was assessed in a subgroup of 100 subjects. There demographics are shown in Table 4. The subjects represent a random sample, which is taken to ensure approximately equal number of men and women, and an approximately equal number of participants in each of the age groups of 35?44, 45?54, 55?64, 65?74 and 75?84 years, were represented (approximately 10 per age group per sex). This subgroup do not significantly differ from the whole Framingham Offspring cohort with respect to age, gender, BMI and waist circumference (all p>0.25).
The intra-observer agreement is excellent for both AAT (ICC=0.970; 95%CI: 0.954-0.980, Figure 5a) and TAT (ICC=0.986; 95%CI: 0.979-0.991, Figure 5b). Both the mean absolute and relative intra-observer differences are small for both AAT: -0.08±0.08cm3, p=0.32 and ?1.85±1.28%, respectively and TAT: 0.55±0.14cm3, p=0.0002; 3.56±0.83%, respectively.
Excellent inter-observer agreement is found between the two observers for AAT (ICC=0.968; 95%CI: 0.951-0.979, Figure 6a) and for TAT (ICC=0.983; 95%CI: 0.975-0.989, Figure 6b). Similarly, the variability between two independent observers is small for both absolute and relative differences (AAT: 0.11±0.09cm3, p=0.20 and 7.85±6.08%; respectively; TAT: ?0.74±0.14cm3, p<0.0001 and -4.56±0.85%; respectively).
The association of peri-aortic adipose tissue to cardiovascular risk factors is assessed in a subgroup, which is free of prevalent CVD. The demographics of this subgroup and their cardiometabolic risk profile are shown in Table 4. In univariate analysis using Pearson correlation, thoracic and abdominal peri-aortic adipose tissue are associated in both genders with increasing age (p<0.001) and clinical and radiologic measures of adiposity (Table 6). Further in both genders, peri-aortic adipose tissue are correlated with BMI (p<0.001), WC (p<0.001), and VAT (p<0.0001). Modest correlations are observed between peri-aortic adipose tissue and all examined cardiometabolic risk factors. Women Men Overall AAT TAT AAT TAT AAT TAT Age 0.26* 0.31* 0.20* 0.30* 0.23* 0.30* BMI 0.51* 0.56* 0.48* 0.58* 0.49* 0.53* WC 0.55* 0.59* 0.45* 0.58* 0.50* 0.54* VAT 0.75* 0.77* 0.64* 0.75* 0.69* 0.75* SAT 0.51* 0.50* 0.41* 0.47* 0.46* 0.46* Log triglycerides 0.32* 0.36* 0.19* 0.26* 0.25* 0.29* HDL cholesterol -0.26* -0.28* -0.15† -0.26* -0.21* -0.25* Total cholesterol 0.10‡ 0.10‡ 0.05 -0.01 0.08‡ 0.04 Systolic blood pressure 0.23* 0.24* 0.05* 0.13* 0.15* 0.17* Diastolic blood pressure 0.24* 0.20* 0.18* 0.17* 0.21* 0.18* Blood glucose 0.28* 0.32* 0.07* 0.22* 0.17* 0.26*
Age-Adjusted Pearson Correlation Coefficients Between Metabolic Risk Factors and Peri-aortic Adipose Tissue among participants without prevalent CVD. *p<0.001; †p<0.01; ‡p<0.05. AAT, abdominal peri-aortic adipose tissue; TAT, thoracic peri-aortic adipose tissue; BMI, body mass index; WC, waist circumference; VAT, visceral adipose tissue; SAT, subcutaneous adipose tissue; HDL, high density lipoprotein. In multivariate analysis, volumes of peri-aortic adipose tissue are associated with most cardiovascular risk factors, with a consistently stronger association in women than men (Table 7 for abdominal peri-aortic adipose tissue (AAT), and Table 8 for thoracic peri-aortic adipose tissue (TAT)). Accordingly, a strong sex interaction is observed for all cardiovascular risk factors, except for diabetes. Upon further adjustment for BMI and WC, most associations remain significant, although some are attenuated. When VAT is additionally included as a covariate, associations between peri-aortic adipose tissue and almost all cardiovascular disease risk covariates are attenuated (all p-values>0.02). A notable exception is the association between TAT and diabetes in men (OR 2.15 (95%CI: 1.40-3.28, p=0.0004). 15 Women Men MV-adjusted residual effect size MV-adjusted residual effect size after BMI-WC adjustment MV-adjusted residual effect size after VAT adjustment MV-adjusted residual effect size MV-adjusted residual effect size after BMI-WC adjustment MV-adjusted residual effect size after VAT adjustment P-value for sex interaction SBP, mm Hg 3.60±0.74* 1.74±0.84‡ 0.86±1.07 0.53±0.72 -0.67±0.80 -0.69±0.92 <0.001 DBP, mm Hg 1.95±0.39* 1.29±0.45† 1.18±0.57‡ 1.59±0.43† 0.99±0.48‡ 1.03±0.56 0.07 FPG, mg/dL 4.13±0.61* 1.96±0.69† -0.08±0.88 1.34±1.00 0.60±1.12 -0.50±1.29 0.003 Log TG, mg/dL 0.17±0.02* 0.086±0.023* -0.01±0.03 0.13±0.03* 0.09±0.03* 0.02±0.03 0.008 HDL, mg/dL -3.93±0.63* -2.08±0.73† 0.23±0.91 -2.43±0.56* -1.29±0.61‡ -0.10±0.70 0.01 Hypertension 1.84(1.50-2.25)* 1.34(1.06-1.70)‡ 1.00 (0.75-1.35) 1.35(1.09-1.68)‡ 1.18(0.93-1.50) 1.11 (0.84-1.46) 0.009 IFG 1.98(1.60-2.46)* 1.59(1.24-2.03)* 1.28 (0.94-1.74) 1.36(1.10-1.68)‡ 1.15(0.91-1.47) 0.90 (0.67-1.19) 0.003 Diabetes 1.43(1.05-1.95)‡ 1.07(0.74-1.55) 0.59 (0.35-0.99)‡ 1.64(1.18-2.29)‡ 1.30(0.88-1.92) 1.44 (0.96-2.14) 0.85 Metabolic Syndrome 2.76(2.21-3.46)* 1.69(1.31-2.19)* 1.14 (0.83-1.56) 1.89(1.52-2.37)* 1.40(1.09-1.80)† 1.13 (0.85-1.49) 0.0007
Data present include effect size (risk factor±SE) per 1 SD of adipose tissue for continuous data, and the odds ratio per 1 SD of adipose tissue with 95% CI for dichotomous data. MV indicates the multivariable model, adjusted for: age, smoking, alcohol use, menopausal status (women only), and hormone replacement therapy (women only). For blood pressure, FPG, HDL cholesterol, and log triglycerides, and additional covariate of treatment for hypertension, diabetes, or lipid disorders, respectively, was included. AAT additionally adjusted for aortic diameter in all models. SBP, systolic blood pressure; DBP, diastolic blood pressure; FPG, fasting plasma glucose; TG, triglyceride; HTN, hypertension; IFG, impaired fasting glucose; and DM, diabetes mellitus. VAT, visceral adipose tissue; BMI, body mass index; WC, waist circumference. P for AAT in the model: *p<0.001; †p<0.01; ‡p<0.05. 15 Women Men MV-adjusted residual effect size MV-adjusted residual effect size after BMI-WC adjustment MV-adjusted residual effect size after VAT adjustment MV-adjusted residual effect size MV-adjusted residual effect size after BMI-WC adjustment MV-adjusted residual effect size after VAT adjustment P-value for sex interaction SBP, mm Hg 3.60±0.75* 1.49±0.90 0.67±1.14 1.79±0.73‡ 0.87±0.91 1.61±1.10 <0.001 DBP, mm Hg 1.69±0.40* 0.69±0.48 0.32±0.60 1.61±0.45† 0.80±0.55 0.95±0.66 0.02 FPG, mg/dL 4.55±0.61* 1.99±0.74† 0.07±0.92 3.59±1.02† 3.55±1.25† 3.62±1.52‡ 0.03 Log TG, mg/dL 0.19±0.02* 0.12±0.024* 0.04±0.03 0.15±0.03* 0.14±0.03* 0.05±0.04 <0.0001 HDL, mg/dL -4.36±0.63* -2.49±0.77† -0.36±0.96 -3.64±0.55* -2.77±0.68* -1.85±0.82‡ 0.002 Hypertension 1.94(1.57-2.39)* 1.37(1.07-1.75)‡ 1.10 (0.81-1.49) 1.52(1.22-1.88)† 1.46(1.12-1.90)† 1.42 (1.03-1.95)‡ 0.001 IFG 2.11(1.68-2.64)* 1.63(1.26-2.11)* 1.38 (1.00-1.91)‡ 1.51(1.21-1.88)† 1.27(0.98-1.65) 0.94 (0.67-1.31) 0.0007 Diabetes 1.77(1.36-2.31)* 1.35(0.97-1.87) 0.98 (0.64-1.48) 1.90(1.43-2.53)* 1.46(1.03-2.07)‡ 2.15 (1.40-3.28)* 0.26 Metabolic Syndrome 3.28(2.54-4.23)* 1.82(1.35-2.44)* 1.26 (0.89-1.79) 2.12(1.69-2.67)* 1.40(1.06-1.83)‡ 1.14 (0.83-1.58) <0.0001
Data present include effect size (risk factor±SE) per 1 SD of adipose tissue for continuous data, and the odds ratio per 1 SD of adipose tissue with 95% CI for dichotomous data. MV indicates the multivariable model, adjusted for age, smoking, alcohol use, menopausal status (women only), and hormone replacement therapy (women only). For blood pressure, FPG, HDL cholesterol, and log triglycerides, and additional covariate of treatment for hypertension, diabetes, or lipid disorders, respectively, was included. SBP, systolic blood pressure; DBP, diastolic blood pressure; FPG, fasting plasma glucose; TG, triglyceride; HTN, hypertension; IFG, impaired fasting glucose; and DM, diabetes mellitus. VAT, visceral adipose tissue; BMI, body mass index; WC, waist circumference. P for TAT in the model: *p<0.001; †p<0.01; ‡p<0.05.
The association of peri-aortic adipose tissue to cardiovascular risk factors is assessed in a subgroup without prevalent CVD (n=1,067). The demographics of this subgroup and their cardiometabolic risk profile are shown in Table 4. Abdominal aortic calcification is present in xx participants with an average Agatston score of xx. The 90th percentile cut point for male and female participants 23.1 and 16.1, respectively. Thoracic aortic calcification is present xx participants with an average Agatston score of xx. The 90th percentile cut point for male and female participants 35.3 and 31.2, respectively
Abdominal peri-aortic adipose tissue (AAT) is not associated with abdominal aortic calcification in age-sex adjusted models, and an inverse association was observed between AAT and thoracic aortic calcification in age-sex adjusted models that persisted with further adjustment (Table 9). Thoracic Aortic Calcification Abdominal Aortic Calcification Model Adjustments OR (95% CI) p-value OR (95% CI) p-value Age, Sex* 0.83 (0.70-0.99) 0.04 1.06 (0.87-1.29) 0.55 Age, Sex, VAT* 0.77 (0.60-0.99) 0.04 0.80 (0.61-1.05) 0.11 Age, Sex, MV†* 0.71 (0.59-0.86) 0.0006 0.82 (0.65-1.02) 0.08 Age, Sex, MV†*, VAT 0.75 (0.58-0.96) 0.02 0.81 (0.60-1.09) 0.16 Age, Sex, MV†*, VAT, BMI, WC 0.75 (0.58-0.96) 0.02 0.81 (0.60-1.09) 0.16
Data present as odds ratio of thoracic or abdominal aortic calcification per 1 standard deviation increase of either thoracic or abdominal fat. *additionally adjusted for aortic diameter; †Multivariable (MV) adjusted for systolic blood pressure, hypertension treatment, diabetes, total/HDL cholesterol, lipid treatment, smoking, alcohol, menopausal status, hormone replacement therapy. VAT, visceral adipose tissue; BMI, body mass index; WC, waist circumference.
Thoracic peri-aortic adipose tissue (TAT) is associated with thoracic calcification in models containing VAT (OR 1.31, 95% CI 1.01-1.71, p=0.04, Table 10), but is attenuated after adjustment for CVD risk factors (OR 1.16, 95% CI 0.88-1.51, p=0.30). However, TAT is strongly associated with abdominal aortic calcification, even in multivariable models that additionally adjusted for CVD risk factors, VAT, BMI, and WC (OR 1.49, p=0.007). Thoracic Aortic Calcification Abdominal Aortic Calcification Model Adjustments OR (95% CI) p-value OR (95% CI) p-value Age, Sex 1.06 (0.90-1.26) 0.50 1.46 (1.23-1.75) <0.0001 Age, Sex, VAT 1.31 (1.01-1.71) 0.04 1.70 (1.30-2.21) 0.0001 Age, Sex, MV† 0.89 (0.73-1.08) 0.23 1.10 (0.90-1.35) 0.36 Age, Sex, MV†, VAT 1.16 (0.88-1.51) 0.30 1.48 (1.11-1.98) 0.008 Age, Sex, MV†, VAT, BMI, WC 1.16 (0.89-1.53) 0.27 1.49 (1.12-1.99) 0.007
Data presented as odds ratio of thoracic or abdominal aortic calcification per 1 standard deviation increase of thoracic abdominal fat. †Multivariable (MV) adjusted for systolic blood pressure, hypertension treatment, diabetes, total/HDL cholesterol, lipid treatment, smoking, alcohol, menopausal status, hormone replacement therapy. VAT, visceral adipose tissue; BMI, body mass index; WC, waist circumference.
The association of peri-aortic adipose tissue to peripheral arterial disease (PAD) was limited to thoracic fat measurements (TAT). In total, 1,205 participants of the Framingham Heart Study, Offspring cohort are included, which had a non-missing ABI ?1.4 and complete covariate profile. The demographics are shown in Table 4. Of those, 45 participants (4%) have ABI ?0.9, which is define as pathognomic for PAD. Further, 35 participants (3%) have a history of intermittent claudication.
In minimally adjusted models, per standard deviation increase in TAT, the odds ratio (OR) for low ABI is 1.89 (95% CI 1.42-2.52, p<0.001; Table 11). Further adjustment for clinical covariates associated with low ABI affect minimally the OR (OR 1.78, p<0.001). Similarly, additional adjustment for BMI and VAT do not materially impact the results (OR 2.07; 1.98, respectively). In contrast, VAT is associated with low ABI in minimally adjusted models (OR 1.54, 95% CI 1.14-2.08, p=0.005), but these findings are attenuated after adjustment for standard covariates (p=0.06). 6.6.2 Association between Thoracic Peri-Aortic Fat and Intermittent Claudication In minimally adjusted models, TAT is associated with intermittent claudication (OR 1.90, 95% CI 1.39-2.59; p<0.001; Table 11). Results are somewhat attenuated after multivariable adjustment (OR 1.54, p=0.02) and after adjustment for BMI and VAT (OR 1.62; 1.69, respectively), but still remain statistically significant. Conversely, VAT is not associated with intermittent claudication after multivariable adjustment (p=0.27). Low ABI Intermittent Claudication OR (95% CI) p-value OR (95% CI) p-value Age, Sex 1.89 (1.42-2.52) <0.001 1.90 (1.39-2.59) <0.001 Age, Sex, MV† 1.78 (1.27-2.48) <0.001 1.54 (1.08-2.19) 0.02 Age, Sex, MV† + BMI 2.07 (1.41-3.04) <0.001 1.62 (1.09-2.41) 0.02 Age, Sex, MV† + VAT 1.98 (1.25-3.13) 0.004 1.69 (1.05-2.72) 0.03
Data present as odds ratio (OR) of low ABI or intermittent claudication per 1 standard deviation increase of peri-aortic fat. †Multivariable (MV) adjusted for smoking, diabetes, hypertension, total/HDL cholesterol, lipid treatment, log triglycerides. VAT, visceral adipose tissue; BMI, body mass index.
The significance in the TAT measurement can be explained as a statistical artifact and is due to the very small variation. However, although statistically significant, this finding can be attributed to the small variation of differences between the two observers rather than practically relevant variations of the measurement.13 The on average higher volume of TAT compared to AAT is explained by the
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Parts of the present work entitled “Local Adopise Tissue Depots in the Association to Atherosclerosis and Peripheral Arterial Disease: The Framingham Heart Study” has been published as part of conference abstracts and the following original articles. Schlett CL, Massaro JM, Lehman SJ, Bamberg F, O’Donnell CJ, Fox CS, Hoffmann U. Novel measurements of periaortic adipose tissue in comparison to anthropometric measures of obesity, and abdominal adipose tissue. Int J Obes (Lond), 2009. 33(2): p.226-32. Fox CS, Massaro JM, Schlett CL, Lehman SJ, O’Donnell CJ, Hoffmann U, Murabito JM. Peri-vascular Fat Deposition is Associated with Peripheral Arterial Disease: the Framingham Heart Study. Circulation, Nov 2009; 120: S509 (oral presentation) Lehman SJ, Massaro JM, Schlett CL, O’Donnell CJ, Hoffmann U, Fox CS. Thoracic and Abdominal Perivascular Fat, Cardiovascular Disease Risk Factors, and Aortic Calcification: The Framingham Heart Study (Atherosclerosis, in revision) Fox CS, Massaro JM, Schlett CL, Lehman SJ, O’Donnell CJ, Hoffmann U, Murabito JM. Peri-aortic Fat Deposition is Associated with Peripheral Arterial Disease: the Framingham Heart Study (Circulation, in revision)
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