Information

To define the total Resistance of Systemic Blood Circulation


Some systems are in parallel. For instance, the resistance of lungs $R_{ ext{lungs}}$. Assume here for simplicity that these parallel systems can be handled linearly. We also consider only Total Vascular Resistance for simplification. So we have now only systems in series under consideration.

Linear system for Systemic Vascular Resistance

Formula for the total resistance as mechanical definition as assuming linear connections between those systems:

$$R_{ ext{total}}=R_A+R_a+R_c+R_V+R_v$$

where appropriate resistances are

  • $R_c$ capillaries,
  • $R_a$ arterioles,
  • $R_A$ Small artery,
  • $R_v$ venules and
  • $R_V$ vein.

Nonlinear system for Systemic Vascular Resistance

There are many factors involved in these locations:

  • permeability
  • vasoconstriction
  • growth factors (FGF) for renewal of the vessel wall
  • different channels (activated, deactivated - mostly potassium channels)

where I skip the consideration of vasoconstriction, growth factors and different channels.

Permeability is one which applies to all types of vessels. Change in permeability of one location does not mean a linear change in permeability in another. A change in the permeability of small arterioles does not lead to a similar change in the arteries or venules.

The vessel is permeable to gas and liquid. Let's consider only these components. I want to include these facts into the definition because, in the pathological situations, different state of inflammation for instance can apply to a vessel. Let's call total permeability $S$ which is dependent on gas and liquid components, first on liquid component (so inner integral).

I could give you the nonlinear formula of the total resistance but I think it goes over the skills most here. Let's call the nonlinear resistance dependent on permeability of the vessel, $W(x,y)(t,f)$ in time and space. So consider only the nonlinear component of the permeability formula after parametrisation i.e. permeability, let's call it $T$, which is dependent on changes in water (w) and gas (g) components over a path integral. The path covers all components in the vascular system that are in series. So total resistance defined nonlinearly

$$W(x,y)(t,f) = int_{gamma} T(u) frac{1}{u} int_{t-u/2}^{t+u/2} T(w) , S(x,y)(t,f) dw , du$$

where the inner integral corresponds to the water component while the outer integral to the gaseous component. There is only an averaging in the inner integral when the width of the window is $u$. However, we do not any windowing here actually, just because of this averaging, so we lose no data and can handle the total resistance as a single process.

Notice that change in $T(u)$ leads to a change in $T(w)$ nonlinearly. I skip the nonlinear definition of $S(x,y)(t,f)$ which stands for the energy in time in each instance - you can think it as the amount of permeability in each position of the vessel. Actually, I also skipped the explicit definitions of the water and gaseous components too.

I have not found any work done on the nonlinear development of the resistance. I think this is necessary for defining inflammation explicitly.

How can you describe the total resistance as an nonlinear operation better?


Pulmonary Circulation and Systemic Circulation: The Routes and Function of Blood Flow

Blood must always circulate to sustain life. It carries oxygen from the air we breathe to cells throughout the body. The pumping of the heart drives this blood flow through the arteries, capillaries, and veins. One set of blood vessels circulates blood through the lungs for gas exchange. The other vessels fuel the rest of the body. Read on to learn more about these crucial circulatory system functions.


Mechanism

Multiple mechanisms regulate and contribute to pulmonary vascular resistance.਋road categories include pulmonary vascular pressure, lung volume, gravity, smooth muscle tonicity, and alveolar hypoxia.[4]

Pulmonary Intravascular Pressure

As cardiac input increases, for example, during exercise, the pulmonic circulation must adapt to accommodate this increased forward flow. Therefore, pulmonary intravascular pressure and pulmonary vascular resistance are inversely related. Experiments have shown that increasing the pulmonary arterial pressure while holding left atrial pressure constant results in a decrease in pulmonary vascular resistance. This decrease occurs via two mechanisms: capillary recruitment and capillary distension.

The first mechanism that occurs is capillary recruitment. At baseline, some of the pulmonary capillaries are partially or entirely਌losed and allow no blood flow. Capillary recruitment is the opening of these closed capillaries during states of increased blood flow. Distribution of flow over a greater cross-sectional surface area reduces the overall vascular resistance. Recruitment usually occurs in zone 1 of the lung (apices), where the capillary pressures are the lowest.

Capillary distension is the second mechanism and involves the widening of the capillaries to accommodate increased blood flow. The Ovular vessels become more circular, which is the predominant mechanism for maintaining low PVR at higher pulmonary arterial pressures.[1]

Alveolar pressures and volumes greatly influence pulmonary vascular resistance. The effect of lung volume depends on the type of vessel. Extra-alveolar vessels run through the lung parenchyma. These vessels have smooth muscle and elastic tissue, which inherently reduces vessel circumference by counteracting distension. As the lung expands, the diameter of these vessels increases via radial traction of the vessel walls. Therefore, vascular resistance is low at large lung volumes. During lung collapse, there is increased resistance through the vessels due to the unopposed action of vessel elasticity. Critical opening pressure represents that air pressure needed to allow blood flow through extra-alveolar capillaries. This concept is applicable when modeling vascular resistance in a collapsed lung.

Alveolar capillaries include capillaries and vessels in the corner of the alveolar walls. The determinant of the amount of distension within these vessels is their transmural pressure (Figure 3).

Alveolar pressure is highest in zone 1 (near the apices) and lowest in zone 3 (near the bases). During inspiration, alveolar pressure rises, which compresses the surrounding alveolar capillaries. Even with the increased right heart return associated with inspiration, stretching and thinning of the alveolar walls reduces capillary caliber and ultimately leads to an increase in PVR at large lung volumes. PVR is highest at total lung capacity (TLC), high at residual volume (RV), and lowest at functional residual capacity (FRC) (Figure 4).[5]

Figure 5 illustrates the different zones of the lung. PVR is greatest at zone 1 since the elevated alveolar pressure increases the inward transmural pressure on the alveolar-capillary. The capillary becomes collapsible, and the resistance increases. PVR is lowest at zone 3, where the arterial pressure is higher than the alveolar pressure, causing an increased outward transmural pressure and increased vessel caliber.[6]

Hypoxia within alveoli induces vasoconstriction within the lung vasculature. This homeostatic mechanism allows the lungs to shunt blood to more oxygenated lung segments, thus allowing for enhanced ventilation/perfusion matching, which in turn improves oxygen delivery throughout the body. This mechanism becomes abundantly important when the lungs are exposed to disruptive processes, such as consolidation (e.g., pneumonia) or blockage within the vasculature (e.g., pulmonary emboli), thereby allowing for appropriate compensation. The theory is that this response begins at the molecular level in which a mitochondrial sensor utilizes redox coupling reactions to alter the elasticity of pulmonary artery smooth muscle cells (PASMC). The redox reactions lead to the depolarization of PASMC via activation of voltage-gated calcium channels and inhibition of potassium channels, which leads to decreased elasticity within arterioles of hypoxic lung segments. Further, if there is sustained hypoxia, alternative pathways can become activated (e.g., rho kinase), and the release of chemokines (e.g., hypoxia-inducible factor (HIF)-1alpha) can occur, which enhances the vasoconstrictive effects as well as remodeling of the vasculature.[7]

Smooth Muscle Tonicity

Generally, the pulmonary circulation has a low vascular tone this is due to pulmonary vessels having proportionately less smooth muscle compared to vessels of similar diameter in other organs. Compared to systemic vessels, the smooth muscle tissue in pulmonary vessels is distributed less evenly in the tunica intima. The pulmonary veins are also more compliant than systemic arteries due to lack of tissue around small vessels, reduced elastin and collagen fibers, and reduced smooth muscle content. A phenomenon that is demonstrated by the pressure gradient observed between the right and left ventricles.[2][8]

Pulmonary arteries are both elastic and muscular. These arteries contain smooth muscle within the tunica media that is surrounded by internal and external elastic laminae. These include the pulmonary artery trunk, main branches, and extra-alveolar vessels. Larger, peri-bronchial arteries are more muscular (Ϣmm). Peri-bronchial arteries lie within the lung lobules. These extra-alveolar arteries control PVR through neural, humoral, or gaseous control. As the vessels become smaller, smooth muscle content decreases. The smooth muscle takes on a spiral shape and becomes the pulmonary arterioles that supply alveoli and alveolar ducts. If smooth muscle exceeds 5% of the external diameter, it is considered pathological.

Pulmonary arteries have more smooth muscle relative to veins and represent the primary sites of constriction by vasoactive mediators. Capillaries are devoid of vasomotor control. Factors that cause increased tone and thereby increased PVR include serotonin, epinephrine, norepinephrine, histamine, ATP, adenosine, neurokinin A, endothelin, angiotensin, thromboxane A/Prostaglandins/Leukotrienes (LTB). Most of these factors act through a G-protein coupled pathway, which activates myosin contraction. Neuronally, pulmonary constriction is under the mediation of the sympathetic nervous system through the stimulation of a1 adrenergic receptors.[9]

Factors that decrease smooth muscle tonicity and decrease PVR include acetylcholine and isoproterenol, prostacyclin (PGI), bradykinin, vasopressin, ANP, substance P, VIP, histamine (during adrenaline response). Most of the factors act through activation of cyclic adenosine 3’,5’ monophosphate (cAMP). cAMP de-phosphorylates myosin and reduces calcium levels, causing relaxation of smooth muscle. Pulmonary endothelial cells cause relaxation through the production of nitric oxide (NO). NO diffuses through smooth muscle cells, activates cyclic guanosine 3’, 5’ monophosphate (cGMP), which causes smooth muscle relaxation through the de-phosphorylation of myosin. Additionally, stimulus from the parasympathetic nervous system via the vagus nerve on M muscarinic receptors in the vasculature cases NO-dependent vasodilation.[9]


Design of Cardiovascular System

Rapid blood flow in one direction is called bulk flow. This is produced by pumping action of the heart. The high branching of blood vessels ensures the proximity of all cells to some capillaries. Nutrients and metabolic end products move between capillary blood and interstitial fluid by diffusion.

The heart is longitudinally divided into 2 halves: left and right, and each half contains two chambers: the upper atrium and the lower ventricle. The atrium on each side is connected to the ventricle on that side but there is no connection between the two atria or the two ventricles. Blood is pumped out of the heart through one set of vessels and returns to the heart via another set. Vessels carrying blood away from the heart are called arteries while those carrying blood toward heart are called veins.

Pulmonary circulation (through lungs for oxygenation) Systemic circulation (to extremities and back)

Pressure, Flow, and Resistance

Blood flows from a region of high to a region of low pressure and rate of blood flow (F) is given

The heart is a muscle enclosed in a sac called the pericardium. The walls of the heart are composed of cardiac muscle cells called myocardium. A thin layer of cells called endothelial cells lines the inner surface. Located between the atrium and ventricle on each side are the atrioventricular (AV) valves. The right AV valve is called the tricuspid valve and the left AV valve is called the mitral valve. The valve at the opening of the right ventricle into the pulmonary artery is called a pulmonary valve. The valve where the left ventricle enters the aorta is called the aortic valve and these two valves are also called semilunar valves. These valves will only allow blood to flow in one direction and their opening and closing is a passive process resulting from pressure differences across the valves.

Cardiac muscle

Cardiac muscle cells are striated. The desmosomes and the gap junctions at the structures called intercalated disks join adjacent cells. Some cells do not function in contraction but they do form the conducting system that initiates the heartbeat and spreads it throughout the heart. These muscle cells are obviously vital and they are innervated with a rich supply of sympathetic fibers that release norepinephrine and parasympathetic fibers that release acetylcholine. Blood supply to cardiac muscle cells is supplied and drained by the coronary arteries and the coronary veins, respectively. Blood that is pumped through the chambers does not exchange substances with the cells of the heart muscle.

Heartbeat coordination

The sequence of excitation. A group of nerve cells called the sinoatrial (SA) node in the right atrium depolarizes first. The discharge rate of the SA node determines the heart rate. Depolarization quickly spreads to the left atrium and the two atria contract simultaneously. The action potential then spreads to ventricles after a small delay through the atrioventricular (AV) node that is located at the base of the right atrium. The delay in the action potential allows atrial contraction to be completed before the ventricle contracts. The potential then spreads to the ventricles via the bundle of His (atrioventricular bundle) and the Purkinje fibers and both ventricles contract simultaneously. The capacity of the SA node for spontaneous, rhythmical self-excitation is a result of gradual depolarization (the pacemaker potential) of the cells. Depolarization, in turn, occurs when Na+ channels open once again during the repolarization phase of the previous potential.

Electrocardiogram. Electrical events in the heart can be indirectly recorded at the surface of the skin from the currents generated in the extracellular fluids. An EKG (ECG) recording should consist of 3 deflections: (1) P wave – the atrial depolarization, (2) QRS complex – the ventricular depolarization, and (3) T wave – the ventricular repolarization. The long refractory period of heart muscle cells limits the re-excitation of cardiac nerve cells, thus inhibiting tetanus.

Mechanical events of the cardiac cycle

The cardiac cycle is divided into two phases:

  1. Systole: the phase of ventricular contraction and blood ejection. During the first part of the systole phase, the ventricles contract while all valves are still closed and therefore no blood is ejected. This period is called the isovolumetric ventricular contraction. The volume of blood ejected from each ventricle is called the stroke volume (SV). The amount of blood remaining after ejection is called the end-systolic volume (ESV).
  2. Diastole: the phase when the ventricles relax and blood fills into the chambers. During the first part of the diastole, the ventricles relax while all valves are still closed. This period is called isovolumetric ventricular relaxation. The amount of blood in the ventricle at the end of diastole is called end-diastolic volume (EDV).

SV = EDV – ESV

Cardiac output

To find the volume of blood pumped by each ventricle per minute:
CO = HR x SV Cardiac output equals heart rate multiplied by stroke volume.

Control of Heart Rate. SA node is innervated by the autonomic nervous system. Activity in parasympathetic nerves releases Ach, which close Na+ channels and decreases the slope of pacemaker potential, causing the heart rate to decrease. Activity in sympathetic nerves releases norepinephrine, which then opens Na+ channels and increases the slope of pacemaker potential, causing the heart rate to increase.

Control of Stroke Volume. A more forceful contraction of the ventricle can cause a greater emptying of the ventricle, thus increasing stroke volume.

EDV & SV: Frank-Starling Mechanism. The greater the EDV means the greater stretching of the ventricular muscles. This also means producing a more forceful contraction. Cardiac muscle is normally not at its optimal length (lo). Thus, additional stretching increases the force of contraction. In sum, as the end-systolic volume decreases, the overall stroke volume increases.

Sympathetic nerves release norepinephrine, which can increase myocardial contractility by increasing calcium infusion.


Circulatory response to exercise in health

Engagement in muscular exercise involves complex local and nervous adjustments of the circulation. In the active muscles, including cardiac muscle, the resistance vessels relax in response to local chemical changes to provide an increase in blood flow adequate for their metabolic requirements. There is increased release of norepinephrine from the sympathetic nerve endings as a result of increased sympathetic outflow the resultant alpha-receptor activation leads to constriction of both systemic resistance and capacitance vessels outside the active muscles, and the beta-receptor activation leads to an increase in heart rate, shortening of the refractory period, and enhancement of myocardial contractility. As a consequence, the filling pressure of the heart and arterial blood pressure are maintained, and the increase in left ventricular output is directed primarily to the active muscles. During upright exercise, the action of the leg muscle pump contributes to the maintenance of the cardiac filling pressure. As exercise continues and body temperature rises, the skin flow increases to dissipate heat from the body. Static exercise causes a greater increase in arterial blood pressure than dynamic exercise. This is due to the combination of an increase in cardiac output and in total systemic vascular resistance as a consequence of increase sympathetic outflow and mechanical compression of the vessels in the active muscles. The hemodynamic changes result from activation of ergoreceptors in the contracted muscles and from central command. The increase in pressure helps to oppose the mechanical compression. The arterial baroreceptors are reset so that they operate normally around the higher blood pressure.


Birth Weight

The fetal growth rate is one of two major factors that determine the weight of the fetus at birth, or birth weight, which averages about 3.4 kg (7.5 lb.) in a full-term infant. The other factor that determines birthweight is the length of gestation. Infants born before full term, which is defined as 36-40 weeks after fertilization, are usually smaller than full-term infants because they have spent less time growing in the uterus. Pre-term birth is one of the major causes of low birth weight, which is defined as a birth weight lower than 2.5 kg (5.5 lb.), regardless of gestational age. Low birth weight increases the risk of death shortly after birth. As many as 30 percent of deaths in the first month of life occur in preterm infants. Holding the length of gestation constant, a newborn may be classified as small for gestational age, appropriate for gestation age, or large for gestational age. Fetuses that did not grow adequately before birth may end up being small for gestational age, even when they are born at full term.


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I read a book a while ago which went through experiments people had done to prove or disprove old wives tales.

One of the things they had was a story about some scientists who shipped a lot of water from hot pools, famous for their healing powers, to their laboratory and heated it up and sat in it, then sat in normal hot water to see if the water made any difference.

What they found out was sitting in water decreases the TPR, making it easier for blood to get around the body. It also did a bunch of other things that are beneficial, although the person had to be submerged up to their neck.

The two different kinds of water worked in exactly the same way. pleonasm November 12, 2011

@indigomoth - Not only do you decrease the distance the blood has to travel, if you are able to make sure you don't have too much fatty tissue between your organs, you're giving your heart and lungs more room to work.

Also, depending on what kind of exercise you do, you're making them stronger, so the level of resistance doesn't matter as much.

Just bear in mind, though that TPR isn't really the distance that the heart has to pump. It's more related to how much force is needed to pump into the arteries.

So, obesity may increase TPR by creating fatty deposits in the arteries, thus blocking part of the blood flow to the body, but the distance the blood has to go doesn't make a difference to the total peripheral resistance equation. indigomoth November 11, 2011

I imagine that the size of a person would also increase the total peripheral resistance.

I remember seeing on one of the many doctor shows they once had, a doctor talking to an obese patient and explaining to her that the heart is about the same size in all of us, and that she was giving hers about three times as much work as a normal heart.

He was trying to impress upon her that she would wear her heart out before its time.

The patient wasn't very impressed, but it made an impression on me.

I struggle with my weight sometimes, but I think that the health benefits of keeping it within a certain range are immense. For one thing, you give your poor heart a break by lowering the resistance against it.


The Future of Vascular Biology and Medicine

From Veterans Affairs Boston Healthcare System, MA (S.K.) and Brigham and Women’s Hospital and Harvard Medical School, Boston, MA (S.K., T.M., J.A.L.).

From Veterans Affairs Boston Healthcare System, MA (S.K.) and Brigham and Women’s Hospital and Harvard Medical School, Boston, MA (S.K., T.M., J.A.L.).

From Veterans Affairs Boston Healthcare System, MA (S.K.) and Brigham and Women’s Hospital and Harvard Medical School, Boston, MA (S.K., T.M., J.A.L.).

Introduction

During the past several decades, landmark discoveries in the field of vascular biology have evolved our understanding of the biology of blood vessels and the pathobiology of local and systemic vascular disease states and have led to novel disease-modifying therapies for patients. In 1980, Furchgott and Zawadzki 1 radically changed our focus in blood vessel research with the discovery of endothelium-derived nitric oxide and its effects on vascular tone. This seminal discovery redefined blood vessels as dynamic organs with autocrine, paracrine, and endocrine functions that are capable of regulating their own environment. The later recognition that many risk factors associated with vascular disease perturb nitric oxide-mediated homeostatic mechanisms lent further credence to the concept of blood vessels as complex organs rather than inert tubes.

In the decades to follow, research in vascular biology predominantly targeted 3 facets of vascular function: vasomotor tone, inflammation, and the balance between thrombosis and thrombolysis. This occurred because atherosclerotic cardiovascular disease reached epidemic levels and atherothrombosis was found to feature disturbances in these functions that preceded visible pathology and clinical manifestations of the disease. Furthermore, modification of responsible causal factors reversed impaired vascular function (eg, lowering levels of low-density lipoproteins in atherosclerosis), and clinical studies began to validate the importance of preclinical vascular biology research in the treatment of hypertension, atherosclerosis, pulmonary vascular disease, erectile dysfunction, Raynaud phenomenon, and neointimal proliferation after mechanical vascular intervention.

More recently, advances in molecular biology and –omics technologies have facilitated in vitro and in vivo studies that revealed that blood vessels regulate their own redox milieu, metabolism, mechanical environment, and phenotype, in part, through complex interactions between cellular components of the blood vessel wall and circulating factors. These interactors include stem, progenitor, and differentiated cells microRNAs, long noncoding RNAs, and DNA and, hormones, proteins, and lipids. Dysregulation of these carefully orchestrated homeostatic interactions has also been implicated as the mechanism by which risk factors for cardiopulmonary vascular disease lead to vascular dysfunction, structural remodeling, and, ultimately, adverse clinical events, including myocardial infarction, stroke, critical limb ischemia, and pulmonary hypertension.

New Directions in Vascular Biology

With all that is known, what directions will vascular biology research take over the coming years, and how will we advance the field? Although some future avenues will arise as the natural evolution of previous work, there are also some experimental and conceptual trends that we believe are evident. The majority of studies examining vascular cell functional responses are performed using passaged cells cultured on hard plastic dishes in an artificial medium, which does not mimic the biological, biochemical, or mechanical conditions present in normal or diseased blood vessels. Possible platforms to replace our current models could range from a self-contained blood vessel organ-on-a-chip system to one that is composed of 3-dimensional flexible tubular biomaterials that could be layered with vascular cells, perfused with typical blood or serum components, pressurized, and subjected to varied flow conditions. Studies performed in these systems will be complemented by in silico analyses done with supercomputing to predict structural or functional changes with resolution to the levels of single vascular cells. Second, with respect to in vivo studies, we will continue to search for better models and grow less reliant on the knockout mouse. This model system also does not take into account the notion that epigenetic or posttranslational modification of a protein may play a greater role in disease biology by altering expression, putative binding partners, downstream signaling pathways, and response to inhibitors/medications. Add to the mix human-mouse species-related differences, and it is not surprising that many findings obtained in these models are not confirmed in human studies. 2 Thus, it becomes clear that the knockout mouse model is more of a crude tool. On the basis of this conclusion, identifying accessible in vivo models that are more relevant and predictable for human vascular disease is necessary.

There will also be a conceptual change in how we approach new questions in vascular biology, with a shift away from a reductionist approach (ie, 1 gene–1 protein–1 disease) to one akin to network analysis and systems biology in which interactions between genes, proteins, and metabolites are considered simultaneously. Furthermore, although the entire vascular system is one connected functional unit, vascular beds are phenotypically different and are likely to take on organ-specific properties through cross-talk with structural cells. In addition, we will begin to explore mechanisms that govern interindividual patient variability by examining key gene-environment interactions that affect the vasculature such as that between humans and commensal microbes. This latter nascent area in blood vessel research is discussed further as an example of a new frontier in vascular biology that will likely use the aforementioned principles in future studies to define how the microbiome regulates cardiopulmonary vascular disease.

The Microbiome Is Associated With Vascular Dysfunction

New and emerging technologies are continuing to reveal that the microbiome plays a critical role in the maintenance of vascular health and the development of vascular disease (Figure 1). The diversity of the human microbiome between individuals, in both species and patterns of colonization, may underlie the differential phenotypic expression of vascular disease and ultimately establish a new paradigm in personalized medicine.

Figure 1. The gut microbiome. The gut microbiome is composed of up to 1000 different species of bacteria, the majority of which belong to the phyla Bacteroidetes and Firmicutes. The microbiome performs several homeostatic functions, is subject to interindividual variability, and has been implicated in disease.

The microbial world has long been viewed as adverse to human health. The advent of germ theory in the 19th century implicated microbes as the source of infection and death. The development of antibiotics and the implementation of hygienic public health standards served to mitigate the effects of pathogenic microorganisms, even while the emergence of antibiotic resistance attenuated the efficacy of the powerful antimicrobial agents developed in the latter half of the 20th century. A less malignant view of the interactions between humans and microbes evolved from the discovery that vitamins essential for human health (eg, vitamin K and some B vitamins) are the products of microbial metabolism in the gut. 3 Thus, the relationship between humans and microbes reflects a commensal interaction in which it appears that both have coevolved to their mutual benefit. Despite this view, our awareness of critical connections between the microbial ecology of the gut and the pathobiology of the vascular wall has emerged only recently.

Studies of gnotobiotic (ie, pathogen-free) mice have provided important insights into the role of microbes in vascular biology. It has long been known that gnotobiotic mice have stunted growth, which is consistent with the role of gut bacteria in energy and vitamin metabolism. These mice also have marked abnormalities in vascular development that can be reversed with the restoration of normal gut flora, suggesting that the gut epithelium is able to transduce signals initiated by resident microbes to the microvasculature. 4 In some mouse lines, gnotobiotic animals are more prone to the development of atherosclerosis than genetically identical mice with normal microbial flora. 5 Interestingly, gnotobiotic mice are resistant to other systemic disorders associated with vascular dysfunction, including diet-induced obesity and diabetes mellitus. The resistance to these diseases is lost with restoration of normal bacterial flora. 6 Taken together, these early observations in gnotobiotic mice established a clear link between the gut microbiome and vascular pathobiology and did so in the absence of traditional predisposing risk factors. There are, however, difficulties in extrapolating discoveries made in gnotobiotic mice to humans, in whom the biological and biochemical diversity of the microbiome differs by orders of magnitude.

In recent years, we have begun to appreciate the magnitude of the interaction between the microbiome and the human body. The Human Microbiome Project used next-generation DNA sequencing to identify thousands of distinct bacterial species that are resident in and on the normal human body. 7 The aggregate number of bacteria far exceeds the total number of human cells and accounts for 1% to 3% of the total body mass (ie, 0.7–2.1 kg in a 70-kg person). DNA sequence analysis also revealed that microbes residing in different anatomic sites such as the gut, skin, respiratory tract, and genitourinary system are characterized by distinct enzymatic pathways that are adapted to metabolize nutrients present in the local environment. 7

The greatest mass and diversity of bacterial species are found in the human colon. The gut microbiome consists of ≈1000 distinct bacterial species that coexist with the genes and gene products of their host to make up the human metagenome. Sequencing of 16S ribosomal RNA found in all bacteria identified 2 large and diverse groups that predominate in the human gut, Firmicutes and Bacteroidetes. 8 Subsequent studies related changes in the levels of these bacteria to human disease and uncovered a complex interplay between human genetic variability, the effects of diet, and the composition of the gut microbiome in the development of obesity and hypertension. 9,10

Mechanisms by Which the Microbiome Mediates Vascular Disease

To understand the mechanism(s) by which the microbiome regulates vascular function, metabolomic profiling was used to identify specific bacteria-derived molecules related to energy metabolism and vascular homeostasis. Further analysis identified trimethylamine as the gut metabolite and bacteria-derived chemical with the clearest association with cardiovascular disease. 11 In clinical studies, unbiased metabolic profiling further revealed a significant increase in the levels of trimethylamine-N-oxide (TMAO) and related metabolites in plasma samples from patients with increased risk for cardiovascular disease compared with matched control subjects. 12 TMAO is formed by bacterial metabolism of choline and phosphatidylcholine in the gut to yield trimethylamine, which is oxidized in the liver by the enzyme flavin monooxygenase-3 to form TMAO (Figure 2). 11 Studies in human subjects, cultured cells, and animal models have converged on a comprehensive view of TMAO as a critical molecule associated with atherosclerosis, myocardial infarction, stroke, insulin resistance, and chronic kidney disease. TMAO has become the target of several therapeutic interventions, ranging from schemes to reduce dietary intake of trimethylamine precursors to manipulations of the gut microbiome to reduce trimethylamine synthesis. The revelation that atherosclerosis susceptibility could be transmitted from an atherosclerosis-prone strain of mice to another strain typically resistant to atherosclerosis simply by the transplantation of gut microbes, an effect that was closely related to TMAO levels, provided additional causal evidence to support the role of the gut microbiome in regulating atherosclerosis. 13

Figure 2. The gut microbiome and atherosclerosis. Dietary intake of foods high in phosphatidylcholine results in increased formation of trimethylamine (TMA) by the gut microbiome. TMA is then transformed into trimethylamine-N-oxide (TMAO) in the liver by flavin-containing monooxygenase-3 (FMO3). Elevated levels of TMAO have been implicated in atherosclerosis.

The Microbiome and Peripheral Vascular Disease

Peripheral artery disease is an often underappreciated and understudied manifestation of atherosclerosis. Peripheral arterial disease either is asymptomatic and portends an increased risk of adverse cardiovascular events or is present as symptomatic claudication with exercise or ischemic pain at rest with evidence of tissue loss. Obstructive atherosclerosis, which reduces perfusion to the limbs, defines this disorder. The ankle-brachial index, the ratio of systolic pressure at the ankle to the highest brachial pressure, is a highly sensitive and specific indicator of peripheral artery disease. 14 There is, however, a substantial variability in the correlation between limb perfusion pressure measured by the ankle-brachial index and symptoms or function in patients with peripheral artery disease. There is also limited mechanistic understanding of the disease pathobiology at the cellular, molecular, and metabolic levels to explain the mismatch between symptoms and perfusion pressure. 15 Furthermore, studies using supervised exercise programs or cilostazol, 2 mainstays in the treatment of claudication, show impressive improvements in walking function without making substantial changes in the resting ankle-brachial index. 16–18 This suggests that the manifestations of peripheral artery disease are dependent not only on perfusion pressure of the conduit arteries of the legs but also on other as-yet unrecognized factors. Previous studies have shown that exercise improves endothelial function 15,19–22 and were focused on identifying related mechanisms, including increased nitric oxide synthase activity, 23,24 decreased expression of genes related to vascular inflammation, 25 enhanced production of endothelial progenitor cells to promote endothelial repair and angiogenesis, 26 and telomere stabilization to prevent endothelial cell senescence. 27

Microbiome and Exercise

Accumulating evidence suggests that the microbiome might regulate the development of peripheral arterial disease and exercise-induced angiogenesis, which is widely thought of as the physiological mechanism by which exercise improves peripheral vascular disease symptoms. The gut microbiota has been shown to contribute to nitric oxide levels by reducing nitrate to ammonia with the generation of gaseous nitric oxide through nonenzymatic nitrite reduction. 28 Exercise-induced angiogenesis has also been related to activation of AMP-activated protein kinase, hypoxia inducible factor-1α, and peroxisome proliferator–activated receptor-γ coactivator-1α, which stimulate vascular endothelial growth factor and skeletal muscle angiogenesis, potentially through interactions with muscle innervation and β-adrenergic signals. 29 In fact, expression and activity of these molecules have been regulated by changes in the gut microbiome. 5,30 Moreover, exercise has been linked to changes in the microbiome in experimental models and increased diversity in the gut microbiome in humans. In a murine model of diet-induced obesity, after 12 weeks of exercise, there was a shift in the gut microbiota that correlated with the exercise dose and differed from the effects observed with diet alone. 31 In humans, exercise correlates with microbiome diversity with up to 22 distinct phyla identified in professional athletes compared with healthy individuals matched for age, ethnicity, and body mass index who had only 9 to 11 distinct phyla. 32 Although these early studies do not provide causal or definitive evidence to link exercise to the gut microbiome and improved peripheral vascularization, they underscore the complexity needed in experimental design for future studies in this area. They may also explain why clinical trials of cell-based therapies as a method to increase angiogenesis that failed to take into account the effects of the microbiome on cell activity have been largely unsuccessful. 16 Thus, exploring the effects of physical activity on the gut microbiome in the future may provide insights into new therapies for peripheral vascular disease that do not rely on improving the ankle-brachial index.

Diet and the Microbiome

There is very little exploration of the effect of diet on vascular function in patients with peripheral artery disease however, extrapolating from studies in patients with coronary artery disease had led to an endorsement of a Mediterranean diet for these patients. This diet is made up of foods higher in monounsaturated fats, with greater proportions of fruit, vegetables, and whole grains than processed foods and the selection of fatty fish over red meats. 33 This dietary pattern is associated with lower rates of cardiovascular events related to atherosclerosis. The effects of diets on vascular function are also sparse. Diets rich in fruit and vegetables 34 and some foods high in flavonoids 35,36 improve vascular function in limited studies.

Studies of the gut microbiome in rodent models show that in response to changes in dietary intake of carbohydrates, fat, and fiber, there are changes in the gut microbiota at the phylum level. Similar studies in humans have shown the same trend, but there is significant interindividual variability. There is also regional variability in the microbiome, and the diversity and composition can reflect an industrialized versus agrarian diet. Thus, it may be possible to predict disease risk vis-à-vis diets rich in phosphatidylcholine, a source of choline, or dietary carnitine, which is ultimately metabolized to TMAO. 37 Investigators have exploited knowledge about these relationships to identify the choline analog 3,3-dimethyl-1-butanol as an inhibitor of trimethylamine formation that can be given orally to mice. In animals fed a high-choline or high-carnitine diet, dimethyl-1-butanol decreased TMAO levels and inhibited atherosclerosis development. 38 The presence of other microbes in the gut, including archaea, bacteriophages, and fungi, has also been associated with diet and, in some cases, linked to disease. Interestingly, analyses of the gut microbiome and the metabolome from individuals who follow the Mediterranean diet revealed that there was an association between dietary compliance and increased fecal short-chain fatty acid abundance that likely reflected the presence of Firmicutes and Bacteroidetes bacteria and lower levels of TMAO. 39 It is also interesting to speculate that there may be a relationship between the gut microbiome and bacteria resident in atherosclerotic plaques. Analysis of directional coronary atherectomy specimens obtained from patients with atherosclerotic epicardial coronary artery disease revealed the presence of a number of diverse bacterial species, including members from the phylum Firmacutes. 40 Future studies will need to determine if these 2 reservoirs of microbes have distinct origins or if plaque bacteria represents a “metastasis” from the gut if the bacteria resident in atherosclerotic plaque are merely a structural finding or have functional implications and if interventions modify both areas equally.

The Potential Role of the Microbiome in Pulmonary Hypertension

Although we are only just beginning to understand the role of the gut microbiome in systemic vascular disease, even less is known about the effects of the microbiome on pulmonary vascular structure and function, especially in pathological conditions characterized by pulmonary vascular remodeling such as pulmonary arterial hypertension. The current World Health Organization identifies 5 groups of patients on the basis of disease pathogenesis and pathophenotype 41 however, there is growing recognition that subsets of patients in different groups share commonalities that are not immediately attributable to any one broad factor. The biological basis of these similarities is not yet known, but it is plausible that the gut microbiome, possibly in combination with the lung microbiome, may modulate genetic, epigenetic, or environmental factors that predispose to aberrant pulmonary vascular remodeling and pulmonary arterial hypertension.

From what is known about the gut microbiome–regulating response in the systemic circulation, it is certainly possible that it also affects the development of pulmonary vascular diseases. As mentioned, studies that examine the gut microbiome effects in the pulmonary compartment also need to consider the importance of the lung microbiome. This distinction achieves importance because the lining of the trachea and the bronchi contains heavily glycosylated proteins, similar to the gut, whereas the more distal airways are coated with lipid-containing surfactant. Thus, the proximal airways may support a microbiome that is similar to what is observed in the gut. 42 Whether this occurs and has any pathophysiological significance for pulmonary vascular remodeling remains to be determined. Interestingly, it is also recognized that components of the microbiome respond to autocrine and paracrine signaling molecules released by human cells, including several that have been implicated in the pathobiology of pulmonary hypertension such as steroid hormones, catecholamines, and the cytokines interleukin-6 and tumor necrosis factor-α. 42

Other data supporting a putative role for the gut microbiome in pulmonary vascular disease come from lung ischemia/reperfusion studies performed in mice. In these studies, mice were administered antibiotics that localized to the intestine. Treatment with antibiotics attenuated both lung and circulating inflammatory markers and decreased alveolar damage. When alveolar macrophages were isolated from mice treated with antibiotics, they were found to generate fewer and lower levels of cytokines compared with control macrophages. Thus, this study suggested that the intestinal microbiome could play a role in regulating the inflammatory response in pulmonary disease. 43 Other supporting evidence comes from studies that examined the effect of Escherichia coli, a component of the gut microbiome, on the inflammatory response in endothelial cells. These bacteria constitutively release nano-sized vesicles that contain pathogen-associated molecular patterns, lipoproteins, and DNA. When endothelial cells are exposed to these vesicles, they demonstrate an acute inflammatory response by upregulating expression of the endothelial cell adhesion molecules E-selectin, intercellular adhesion molecule-1, and vascular cell adhesion molecule-1. 44

The gut microbiome may also regulate vascular remodeling in pulmonary hypertension through effects on pulmonary vascular smooth muscle cells. In the systemic vasculature, there is evidence that the gut microbiome regulates smooth muscle cell proliferation and the formation of neointimal hyperplasia in response to injury after balloon angioplasty. In one study, rats treated with the antibiotic vancomycin had demonstrated changes in gut flora that were evident 4 weeks after initiation of treatment. The rats were shown to have decreased abundance of Firmicutes and an increase in the ratio of Bacteroidetes to Firmicutes. Antibiotic treatment was also found to lower serum levels of butyrate, one of the beneficial short-chain fatty acids produced by fermentation of dietary fiber. After vascular injury, neointimal hyperplasia was more severe in vancomycin-treated animals compared with controls however, neointimal hyperplasia was ameliorated when antibiotic-treated animals were supplemented with butyrate. Butyrate limited neointimal formation through a mechanism that involved decreased aortic smooth muscle cell proliferation, cell cycle progression, and migration. 45

Experimental evidence further links diet and the gut microbiome with pulmonary hypertension. In studies performed in apolipoprotein E knockout mice fed a Paigen diet (high fat, high choline) for 8 weeks, mice were found to have pulmonary hypertension with pulmonary vascular remodeling compared with mice fed a regular chow diet. 46 Because choline is the precursor for TMAO, it is likely that the gut microbiome influenced the development of pulmonary arterial remodeling and pulmonary hypertension in this model. Furthermore, diet has been shown to improve pulmonary hemodynamics in a chronically hypoxic rat model of pulmonary hypertension. This study demonstrated that rats fed a diet containing fish oil (part of the Mediterranean diet) had lower mean pulmonary artery pressures, fibrosis, right ventricular hypertrophy, and platelet aggregation compared with rats with pulmonary hypertension fed other high-fat diets. This translated into lower mortality rates. 47 Considered together, these findings indicate that it is very likely that the gut microbiome influences pulmonary vascular disease and the development of pulmonary hypertension.

Conclusions

At present, the causal pathways and molecular mechanisms whereby the gut microbiome initiates and perpetuates cardiopulmonary vascular disease remain incompletely characterized. However, early studies in the field indicate that future in vitro and in vivo studies of the blood vessel function must now contend with an additional layer of complexity in experimental design. These studies will need to examine local and remote interaction with the gut microbiota and metabolites for in vitro studies often done in the presence of antibiotics, this remains a challenge. Further adding to the experimental complexity, the microbiome may be altered by diet and by drugs. Thus, in addition to standardizing diets for in vivo studies, the effects of drugs (and delivery vehicle) will need to be evaluated. For example, it has been suggested that some of the beneficial effects of the antidiabetic drug metformin may be a consequence of the effect of the drug on the gut microbiome (Table). 48 This underscores the possibility that other pathway inhibitors and receptor blockers commonly used as medications may also modulate the gut microbiome, thereby confounding interpretation of past studies that failed to rigorously account for drug use. A detailed characterization of drug effects on the gut microbiome could also lead to the repurposing of existing medications that may be called metabiotic therapies to reflect the higher-order modulation of the microbial environment by drugs to achieve a salutary response.

Table. Categorization of Therapeutics That Target the Gut Microbiome


Definition of Metabolic Syndrome

The National Cholesterol Education Program’s Adult Treatment Panel III report (ATP III) 1 identified the metabolic syndrome as a multiplex risk factor for cardiovascular disease (CVD) that is deserving of more clinical attention. The cardiovascular community has responded with heightened awareness and interest. ATP III criteria for metabolic syndrome differ somewhat from those of other organizations. Consequently, the National Heart, Lung, and Blood Institute, in collaboration with the American Heart Association, convened a conference to examine scientific issues related to definition of the metabolic syndrome. The scientific evidence related to definition was reviewed and considered from several perspectives: (1) major clinical outcomes, (2) metabolic components, (3) pathogenesis, (4) clinical criteria for diagnosis, (5) risk for clinical outcomes, and (6) therapeutic interventions.

Clinical Outcomes of Metabolic Syndrome

ATP III viewed CVD as the primary clinical outcome of metabolic syndrome. Most individuals who develop CVD have multiple risk factors. In 1988, Reaven 2 noted that several risk factors (eg, dyslipidemia, hypertension, hyperglycemia) commonly cluster together. This clustering he called Syndrome X, and he recognized it as a multiplex risk factor for CVD. Reaven and subsequently others postulated that insulin resistance underlies Syndrome X (hence the commonly used term insulin resistance syndrome). Other researchers use the term metabolic syndrome for this clustering of metabolic risk factors. ATP III used this alternative term. It avoids the implication that insulin resistance is the primary or only cause of associated risk factors. Although ATP III identified CVD as the primary clinical outcome of the metabolic syndrome, most people with this syndrome have insulin resistance, which confers increased risk for type 2 diabetes. When diabetes becomes clinically apparent, CVD risk rises sharply. Beyond CVD and type 2 diabetes, individuals with metabolic syndrome seemingly are susceptible to other conditions, notably polycystic ovary syndrome, fatty liver, cholesterol gallstones, asthma, sleep disturbances, and some forms of cancer.

Components of Metabolic Syndrome

ATP III 1 identified 6 components of the metabolic syndrome that relate to CVD:

Insulin resistance ± glucose intolerance

These components of the metabolic syndrome constitute a particular combination of what ATP III terms underlying,major, and emerging risk factors. According to ATP III, underlying risk factors for CVD are obesity (especially abdominal obesity), physical inactivity, and atherogenic diet the major risk factors are cigarette smoking, hypertension, elevated LDL cholesterol, low HDL cholesterol, family history of premature coronary heart disease (CHD), and aging and the emerging risk factors include elevated triglycerides, small LDL particles, insulin resistance, glucose intolerance, proinflammatory state, and prothrombotic state. For present purposes, the latter 5 components are designated metabolic risk factors. Each component of the metabolic syndrome will be briefly defined.

Abdominal obesity is the form of obesity most strongly associated with the metabolic syndrome. It presents clinically as increased waist circumference.

Atherogenic dyslipidemia manifests in routine lipoprotein analysis by raised triglycerides and low concentrations of HDL cholesterol. A more detailed analysis usually reveals other lipoprotein abnormalities, eg, increased remnant lipoproteins, elevated apolipoprotein B, small LDL particles, and small HDL particles. All of these abnormalities have been implicated as being independently atherogenic.

Elevated blood pressure strongly associates with obesity and commonly occurs in insulin-resistant persons. Hypertension thus commonly is listed among metabolic risk factors. However, some investigators believe that hypertension is less “metabolic” than other metabolic-syndrome components. Certainly, hypertension is multifactorial in origin. For example, increasing arterial stiffness contributes significantly to systolic hypertension in the elderly. Even so, most conference participants favored inclusion of elevated blood pressure as one component of the metabolic syndrome.

Insulin resistance is present in the majority of people with the metabolic syndrome. It strongly associates with other metabolic risk factors and correlates univariately with CVD risk. These associations, combined with belief in its priority, account for the term insulin resistance syndrome. Even so, mechanisms underlying the link to CVD risk factors are uncertain, hence the ATP III’s classification of insulin resistance as an emerging risk factor. Patients with longstanding insulin resistance frequently manifest glucose intolerance, another emerging risk factor. When glucose intolerance evolves into diabetes-level hyperglycemia, elevated glucose constitutes a major, independent risk factor for CVD.

A proinflammatory state, recognized clinically by elevations of C-reactive protein (CRP), is commonly present in persons with metabolic syndrome. Multiple mechanisms seemingly underlie elevations of CRP. One cause is obesity, because excess adipose tissue releases inflammatory cytokines that may elicit higher CRP levels.

A prothrombotic state, characterized by increased plasma plasminogen activator inhibitor (PAI)-1 and fibrinogen, also associates with the metabolic syndrome. Fibrinogen, an acute-phase reactant like CRP, rises in response to a high-cytokine state. Thus, prothrombotic and proinflammatory states may be metabolically interconnected.

Pathogenesis of Metabolic Syndrome

The metabolic syndrome seems to have 3 potential etiological categories: obesity and disorders of adipose tissue insulin resistance and a constellation of independent factors (eg, molecules of hepatic, vascular, and immunologic origin) that mediate specific components of the metabolic syndrome. Other factors—aging, proinflammatory state, and hormonal changes—have been implicated as contributors as well.

Obesity and Abnormal Body Fat Distribution

ATP III considered the “obesity epidemic” as mainly responsible for the rising prevalence of metabolic syndrome. Obesity contributes to hypertension, high serum cholesterol, low HDL cholesterol, and hyperglycemia, and it otherwise associates with higher CVD risk. Abdominal obesity especially correlates with metabolic risk factors. Excess adipose tissue releases several products that apparently exacerbate these risk factors. They include nonesterified fatty acids (NEFA), cytokines, PAI-1, and adiponectin. A high plasma NEFA level overloads muscle and liver with lipid, which enhances insulin resistance. High CRP levels accompanying obesity may signify cytokine excess and a proinflammatory state. An elevated PAI-1 contributes to a prothrombotic state, whereas low adiponectin levels that accompany obesity correlate with worsening of metabolic risk factors. The strong connection between obesity (especially abdominal obesity) and risk factors led ATP III to define the metabolic syndrome essentially as a clustering of metabolic complications of obesity.

Insulin Resistance

A second category of causation is insulin resistance. Many investigators place a greater priority on insulin resistance than on obesity in pathogenesis. 2,3 They argue that insulin resistance, or its accomplice, hyperinsulinemia, directly causes other metabolic risk factors. Identifying a unique role for insulin resistance is complicated by the fact that it is linked to obesity. Insulin resistance generally rises with increasing body fat content, yet a broad range of insulin sensitivities exists at any given level of body fat. 4 Most people with categorical obesity (body mass index [BMI] ≥30 kg/m 2 ) have postprandial hyperinsulinemia and relatively low insulin sensitivity, 5 but variation in insulin sensitivities exists even within the obese population. 4 Overweight persons (BMI 25 to 29.9 kg/m 2 ) likewise exhibit a spectrum of insulin sensitivities, suggesting an inherited component to insulin resistance. In some populations (eg, South Asians), insulin resistance occurs commonly even with BMI <25 kg/m 2 and apparently contributes to a high prevalence of type 2 diabetes and premature CVD. South Asians and others who manifest insulin resistance with only mild-to-moderate overweight can be said to have primary insulin resistance. Even with primary insulin resistance, however, weight gain seems to enhance insulin resistance and metabolic syndrome. Thus, dissociation of obesity and primary insulin resistance in patients with metabolic syndrome is difficult.

This is not to say that insulin resistance per se does not play a significant role in causation of metabolic syndrome. When insulin-resistant muscle is already overloaded with lipid from high plasma NEFA levels, some excess NEFA presumably is diverted to the liver, promoting fatty liver and atherogenic dyslipidemia. Hyperinsulinemia may enhance output of very-low-density lipoprotein triglycerides, raising triglycerides. Insulin resistance in muscle predisposes to glucose intolerance, which can be worsened by increased hepatic gluconeogenesis in insulin-resistant liver. Finally, insulin resistance may raise blood pressure by a variety of mechanisms.

Independent Factors That Mediate Specific Components of the Metabolic Syndrome

Beyond obesity and insulin resistance, each risk factor of the metabolic syndrome is subject to its own regulation through both genetic and acquired factors. This leads to variability in expression of risk factors. Lipoprotein metabolism, for instance, is richly modulated by genetic variation hence, expression of dyslipidemias in response to obesity and/or insulin resistance varies considerably. The same holds for blood pressure regulation. Moreover, glucose levels depend on insulin-secretory capacity as well as insulin sensitivity. This variation in distal regulation cannot be ignored as an important factor in causation of metabolic syndrome.

Other Contributing Factors

Advancing age probably affects all levels of pathogenesis, which likely explains why prevalence of the metabolic syndrome rises with advancing age. 6 Recently, a proinflammatory state has been implicated directly in causation of insulin resistance, as well as atherogenesis. Finally, several endocrine factors have been linked to abnormalities in body-fat distribution and hence indirectly to metabolic syndrome. Thus, pathogenesis of the metabolic syndrome is complex and ripe with opportunities for further research.

Criteria for Clinical Diagnosis of Metabolic Syndrome

At least 3 organizations have recommended clinical criteria for the diagnosis of the metabolic syndrome. 1,7–9 Their criteria are similar in many aspects, but they also reveal fundamental differences in positioning of the predominant causes of the syndrome. Each will be reviewed briefly.

ATP III

Criteria of ATP III 1 are shown in Table 1. When 3 of 5 of the listed characteristics are present, a diagnosis of metabolic syndrome can be made. The primary clinical outcome of metabolic syndrome was identified as CHD/CVD. Abdominal obesity, recognized by increased waist circumference, is the first criterion listed. Its inclusion reflects the priority given to abdominal obesity as a contributor to metabolic syndrome. Also listed are raised triglycerides, reduced HDL cholesterol, elevated blood pressure, and raised plasma glucose. Cutpoints for several of these are less stringent than usually required to identify a categorical risk factor, because multiple marginal risk factors can impart significantly increased risk for CVD. Explicit demonstration of insulin resistance is not required for diagnosis however, most persons meeting ATP III criteria will be insulin resistant. Finally, the presence of type 2 diabetes does not exclude a diagnosis of metabolic syndrome.

TABLE 1. ATP III Clinical Identification of the Metabolic Syndrome

World Health Organization

In 1998, a World Health Organization (WHO) consultation group outlined a provisional classification of diabetes that included a working definition of the metabolic syndrome. 7 This report was finalized in 1999 and placed on the WHO website 8 (see Table 2). The guideline group also recognized CVD as the primary outcome of the metabolic syndrome. However, it viewed insulin resistance as a required component for diagnosis. 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), a glucose uptake below the lowest quartile for background population under hyperinsulinemic, euglycemic conditions. In addition to insulin resistance, 2 other risk factors are sufficient for a diagnosis of metabolic syndrome. A higher blood pressure was required than in ATP III. BMI (or increased waist:hip ratio) was used instead of waist circumference, and microalbuminuria was listed as one criterion. The requirement of objective evidence of insulin resistance should give more power to predict diabetes than does ATP III, but like ATP III, the presence of type 2 diabetes does not exclude a diagnosis of metabolic syndrome. A potential disadvantage of the WHO criteria is that special testing of glucose status beyond routine clinical assessment may be necessary to diagnose metabolic syndrome.

TABLE 2. WHO Clinical Criteria for Metabolic Syndrome *

American Association of Clinical Endocrinologists

The American Association of Clinical Endocrinologists (AACE) 9 proposes a third set of clinical criteria for the insulin resistance syndrome (Table 3). These criteria appear to be a hybrid of those of ATP III and WHO metabolic syndrome. However, no defined number of risk factors is specified diagnosis is left to clinical judgment. When a person develops categorical diabetes, the term insulin resistance syndrome no longer applies. In patients without IFG, a 2-hour postglucose challenge is recommended when an abnormality is clinically suspected. Finding abnormal 2-hour glucose will improve prediction of type 2 diabetes.

TABLE 3. AACE Clinical Criteria for Diagnosis of the Insulin Resistance Syndrome *

Issue of Oral Glucose Tolerance Test

Both WHO and AACE include IGT, detected by oral glucose tolerance test (OGTT) or 2-hour postglucose challenge, among the risk factors for metabolic syndrome. ATP III did not include it because of the added inconvenience and cost of OGTT in clinical practice. Its added value for CVD risk prediction appears small. However, several conference participants suggested adding OGTT at the physician’s discretion in nondiabetic patients with ATP III–defined metabolic syndrome or ≥2 metabolic risk factors (Table 1). Several potential benefits were noted. First, in the absence of IFG, IGT could count as one metabolic risk factor defining metabolic syndrome. If IGT were to be added to ATP III criteria, metabolic syndrome prevalence over age 50 years would increase by ≈5% (Table 4). Second, IGT carries increased risk for type 2 diabetes. Third, postprandial hyperglycemia in a patient with IFG denotes diabetes, a high-risk condition for CVD.

TABLE 4. Impact on Prevalence of Metabolic Syndrome if Impaired Glucose Tolerance Plus 2 or More Risk Factors Is Added to the National Cholesterol Education Program Definition *

Metabolic Syndrome as a Risk Condition

It seems self-evident that a condition characterized by multiple risk factors will carry a greater risk for adverse clinical outcomes than will a single risk factor. This conclusion is implicit in Framingham risk equations, which incorporate many of the components of the metabolic syndrome. For this conference, Framingham investigators examined their extensive database for the relation between metabolic syndrome and future development of both CVD and diabetes. Their analysis was carried out on 3323 Framingham offspring men and women (mean age, 52 years) in 8 years of follow-up.

Metabolic Syndrome as a Predictor of CVD

Individuals with metabolic syndrome are at increased risk for CHD. 10 In Framingham, the metabolic syndrome alone predicted ≈25% of all new-onset CVD. In the absence of diabetes, the metabolic syndrome generally did not raise 10-year risk for CHD to >20% this is the threshold for ATP III’s CHD risk equivalent. Ten-year risk in men with metabolic syndrome generally ranged from 10% to 20%. Framingham women with metabolic syndrome had relatively few CHD events during the course of the 8-year follow-up this was due in part to the high proportion of women who were under 50 years of age. Although the metabolic syndrome in these women appeared to be accompanied by higher risk for CVD/CHD, the confidence interval was wide, and differences between those with and without metabolic syndrome were not statistically significant. Of note, the 10-year risk for CHD in most women in this relatively young cohort did not exceed 10%.

Framingham investigators then examined whether the metabolic syndrome carries incremental risk beyond the usual risk factors of the Framingham algorithm. Analyses were carried out both including and excluding patients with diabetes. Several models were tested. Results were compared as C statistics. The C statistic is the probability that the model used will place a person in the right order, giving the higher probability to the one who develops the disease than to the one who does not. Some investigators consider this approach to have limitations, particularly because of the high contribution of age alone to the C statistic. Nonetheless, this is a standard method for evaluating the power of adding new risk factors to multiple–risk factor equations. Various models were tested. These included (1) the standard Framingham algorithm, 11 (2) ATP III metabolic syndrome risk factors alone, (3) metabolic syndrome risk factors + age, (4) usual Framingham risk factors + unique metabolic syndrome risk factors (obesity, triglycerides, glucose), and (5) usual Framingham risk factors + metabolic syndrome as a single variable. When usual risk factors and unique metabolic syndrome risk factors were combined, either on a continuous or categorical basis, the reliability of prediction (C statistic) increased only marginally. The results of this analysis indicated that no advantage is gained in risk assessment by adding the unique risk factors of the ATP III metabolic syndrome to the usual Framingham risk factors in risk assessment. It is likely that most of the risk associated with the metabolic syndrome is captured by age, blood pressure, total cholesterol, diabetes, and HDL cholesterol. Beyond these, obesity, triglycerides, and glucose levels (in the absence of diabetes) provided little additional power of prediction. Repetition of the analysis including patients with diabetes had little impact on the C statistic. Serum CRP possibly has independent predictive power beyond usual risk factors and/or metabolic syndrome however, the absolute increment in risk associated with elevated CRP has not been adequately tested.

Metabolic Syndrome as a Predictor of Diabetes

When the risk for new-onset diabetes was examined for the Framingham cohort, in both men and women, the presence of metabolic syndrome was highly predictive of new-onset diabetes. Almost half of the population-attributable risk for diabetes could be explained by the presence of ATP III metabolic syndrome.

Diabetes as a Predictor of CVD

Framingham data showed that most men with diabetes had a 10-year risk for CHD >20% in contrast, women rarely exceeded the 20% level. Some authorities believe that improved risk assessment in individuals with diabetes would be clinically useful in risk management. Oxford investigators therefore have developed a risk engine (available on the World Wide Web) 12 based on the large UK Prospective Diabetes Study (UKPDS) database, which had >500 hard CHD events. It differs from the Framingham algorithm in that it includes a measure of glycemia and duration of diabetes. Surveys of other diabetic populations by UKPDS investigators found that Framingham equations considerably underestimate risk for CHD and stroke, whereas the UKPDS Risk Engine provides a more robust estimate.

Therapeutic Implications

Obesity and Body Fat Distribution as Targets of Therapy

ATP III recommended that obesity be the primary target of intervention for metabolic syndrome. First-line therapy should be weight reduction reinforced with increased physical activity. Weight loss lowers serum cholesterol and triglycerides, raises HDL cholesterol, lowers blood pressure and glucose, and reduces insulin resistance. Recent data further show that weight reduction can decrease serum levels of CRP and PAI-1. Most conference participants held that obesity contributes significantly to development of the metabolic syndrome in the general population. They further acknowledged that clinical management should focus first on lifestyle changes—particularly weight reduction and increased exercise. Even participants who emphasized the role of insulin resistance in the pathogenesis of the metabolic syndrome acknowledged that therapeutic lifestyle changes deserve priority. Some participants questioned whether such changes could successfully be implemented in clinical practice. Still, the potential for benefit certainly exists implementation is the challenge.

Insulin Resistance as Target of Therapy

If insulin resistance, whether primary or secondary to obesity, is in the chain of causation of metabolic syndrome, it would be an attractive target. Certainly, weight reduction and increased physical activity will reduce insulin resistance. Insulin resistance as a target has caught the imagination of the pharmaceutical industry, and drug discovery is underway. Two classes of drugs are currently available that reduce insulin resistance. These are metformin and insulin sensitizers such as thiazolidinediones (TZDs).

Metformin has long been used for treatment of type 2 diabetes. In UKPDS, metformin apparently reduced new-onset CHD in obese patients with diabetes. In the Diabetes Prevention Program, metformin therapy prevented (or delayed) onset of type 2 diabetes in persons with IGT. There are, however, no CVD end-point studies on metformin-treated patients with metabolic syndrome. Thus, at present, metformin cannot be recommended for the express purpose of reducing risk for CVD in persons with the metabolic syndrome.

TZDs currently are approved for treatment of type 2 diabetes. They reduce insulin resistance, favorably modify several metabolic risk factors, and reverse abnormal arterial responses. Nonetheless, no clinical trial data yet exist to document benefit in CVD risk reduction. Thus, in spite of promise, TZDs cannot be recommended at present for preventing CVD in patients with either metabolic syndrome or diabetes.

Specific Metabolic Risk Factors as Targets of Therapy

Atherogenic Dyslipidemia

Although statins typically are recognized to be LDL-lowering drugs, they reduce all apolipoprotein B–containing lipoproteins. Recent subgroup analyses of statin trials reveal that statins reduce risk for CVD events in patients with metabolic syndrome. Fibrates also favorably modify atherogenic dyslipidemia and may directly reduce atherogenesis. Post hoc analysis of recent fibrate trials strongly suggests that they reduce CVD end points in patients with atherogenic dyslipidemia and metabolic syndrome. 13 Moreover, clinical studies demonstrate that abnormal lipoprotein patterns are doubly improved by combined statin-fibrate therapy, but just how much this combination reduces CVD events beyond statins alone awaits demonstration with controlled clinical trials.

Elevated Blood Pressure

There is full agreement that hypertensive patients with metabolic syndrome deserve lifestyle therapies to reduce blood pressure. In addition, antihypertensive drugs should be used as recommended by hypertension guidelines. No class of antihypertensive drugs has been identified as being uniquely efficacious in patients with metabolic syndrome.

Prothrombotic State

No drugs are available that target PAI-1 and fibrinogen. An alternative approach to the prothrombotic state is antiplatelet therapy. For example, low-dose aspirin reduces CVD events in both secondary and primary prevention. Thus, use of aspirin for primary prevention in patients with metabolic syndrome is promising. According to current recommendations, low-dose aspirin therapy has a favorable efficacy/side effect ratio when 10-year risk for CHD is ≥10%.

Proinflammatory State

There is growing interest in development of drugs to dampen the proinflammatory state. Several lipid-lowering drugs will reduce CRP levels, which could reflect an antiinflammatory action.

Hyperglycemia

When patients with metabolic syndrome develop type 2 diabetes, they are at high risk for CVD. All CVD risk factors should be intensively reduced. In addition, glucose levels should be appropriately treated with lifestyle therapies and hypoglycemic agents as needed to keep hemoglobin A1c levels below guideline targets.

Conclusions

Conference participants agreed that CVD is the primary clinical outcome of metabolic syndrome. Additionally, risk for type 2 diabetes is higher, and diabetes is a major risk factor for CVD. ATP III criteria provide a practical tool to identify patients at increased risk for CVD. WHO and AACE criteria require further oral glucose testing if IFG and diabetes are absent. IGT on OGTT denotes greater risk for diabetes than does metabolic syndrome without elevated fasting glucose. Several potential benefits make OGTT in such patients an attractive option for use at the discretion of the physician. First, in the absence of IFG, IGT could count as one metabolic risk factor defining metabolic syndrome, besides carrying increased risk for type 2 diabetes. Moreover, postprandial hyperglycemia in a patient with IFG denotes diabetes, a high-risk condition for CVD.

Regardless of diagnostic criteria used, there is full agreement that therapeutic lifestyle change, with emphasis on weight reduction, constitutes first-line therapy for metabolic syndrome. Drug treatment to directly reduce insulin resistance is promising, but clinical trials to prove reduction of CVD are lacking. In patients in whom lifestyle changes fail to reverse metabolic risk factors, consideration should be given to treating specific abnormalities in these risk factors with drugs. Use of drugs to target risk factors should be in accord with current treatment guidelines.

The American Heart Association makes every effort to avoid any actual or potential conflicts of interest that may arise as a result of an outside relationship or a personal, professional, or business interest of a member of the writing panel. Specifically, all members of the writing group are required to complete and submit a Disclosure Questionnaire showing all such relationships that might be perceived as real or potential conflicts of interest.

This statement was approved by the American Heart Association Science Advisory and Coordinating Committee on November 14, 2003. A single reprint is available by calling 800-242-8721 (US only) or writing the American Heart Association, Public Information, 7272 Greenville Ave, Dallas, TX 75231-4596. Ask for reprint No. 71-0274. To purchase additional reprints: up to 999 copies, call 800-611-6083 (US only) or fax 413-665-2671 1000 or more copies, call 410-528-4121, fax 410-528-4264, or e-mail [email protected] To make photocopies for personal or educational use, call the Copyright Clearance Center, 978-750-8400.


Systemic circulation

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Systemic circulation, in physiology, the circuit of vessels supplying oxygenated blood to and returning deoxygenated blood from the tissues of the body, as distinguished from the pulmonary circulation. Blood is pumped from the left ventricle of the heart through the aorta and arterial branches to the arterioles and through capillaries, where it reaches an equilibrium with the tissue fluid, and then drains through the venules into the veins and returns, via the venae cavae, to the right atrium of the heart. Pressure in the arterial system, resulting from heart action and distension by the blood, maintains systemic blood flow. The systemic pathway, however, consists of many circuits in parallel, each of which has its own arteriolar resistance that determines blood flow independently of the overall flow and pressure and without necessarily disrupting these. For example, the blood flow through the digestive tract increases after meals, and that through working muscles increases during exercise. See also pulmonary circulation.


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