4.14: Secondary Messengers - Biology

4.14: Secondary Messengers - Biology

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Second messengers are molecules that relay signals received at receptors on the cell surface — such as the arrival of protein hormones, growth factors, etc. — to target molecules in the cytosol and/or nucleus. But in addition to their job as relay molecules, second messengers serve to greatly amplify the strength of the signal. Binding of a ligand to a single receptor at the cell surface may end up causing massive changes in the biochemical activities within the cell.

There are 3 major classes of second messengers:

  1. cyclic nucleotides (e.g., cAMP and cGMP)
  2. inositol trisphosphate (IP3) and diacylglycerol (DAG)
  3. calcium ions (Ca2+)

Cyclic Nucleotides

Cyclic AMP (cAMP)

Some of the hormones that achieve their effects through cAMP as a second messenger:

  • adrenaline
  • glucagon
  • luteinizing hormone (LH)

Cyclic AMP is synthesized from ATP by the action of the enzyme adenylyl cyclase.

  • Binding of the hormone to its receptor activates
  • a G protein which, in turn, activates
  • adenylyl cyclase.
  • The resulting rise in cAMP turns on the appropriate response in the cell by either (or both):
    • changing the molecular activities in the cytosol, often using Protein Kinase A (PKA) — a cAMP-dependent protein kinase that phosphorylates target proteins
    • turning on a new pattern of gene transcription

Cyclic GMP (cGMP)

Cyclic GMP is synthesized from the nucleotide GTP using the enzyme guanylyl cyclase. Cyclic GMP serves as the second messenger for

  • atrial natriuretic peptide (ANP)
  • nitric oxide (NO)
  • the response of the rods of the retina to light

Some of the effects of cGMP are mediated through Protein Kinase G (PKG) — a cGMP-dependent protein kinase that phosphorylates target proteins in the cell.

Inositol trisphosphate (IP3) and diacylglycerol (DAG)

Peptide and protein hormones like vasopressin, thyroid-stimulating hormone (TSH), and angiotensin and neurotransmitters like GABA bind to G protein-coupled receptors (GPCRs) that activate the intracellular enzyme phospholipase C (PLC).

As its name suggests, it hydrolyzes phospholipids — specifically phosphatidylinositol-4,5-bisphosphate (PIP2) which is found in the inner layer of the plasma membrane. Hydrolysis of PIP2 yields two products:

  • diacylglycerol (DAG): DAG remains in the inner layer of the plasma membrane. It recruits Protein Kinase C (PKC) — a calcium-dependent kinase that phosphorylates many other proteins that bring about the changes in the cell. As its name suggests, activation of PKC requires calcium ions. These are made available by the action of the other second messenger — IP3.
  • inositol-1,4,5-trisphosphate (IP3): This soluble molecule diffuses through the cytosol and binds to receptors on the endoplasmic reticulum causing the release of calcium ions (Ca2+) into the cytosol. The rise in intracellular calcium triggers the response.


The calcium rise is needed for NF-AT (the "nuclear factor of activated T cells") to turn on the appropriate genes in the nucleus.

The remarkable ability of tacrolimus and cyclosporine to prevent graft rejection is due to their blocking this pathway.

The binding of an antigen to its receptor on a B cell (the BCR) also generates the second messengers DAG and IP3.

Calcium ions (Ca2+)

As the functions of IP3 and DAG indicate, calcium ions are also important intracellular messengers. In fact, calcium ions are probably the most widely used intracellular messengers.

In response to many different signals, a rise in the concentration of Ca2+ in the cytosol triggers many types of events such as

  • muscle contraction
  • exocytosis, e.g.
    • release of neurotransmitters at synapses (and essential for the long-term synaptic changes that produce Long-Term Potentiation (LTP) and Long-Term Depression (LTD);
    • secretion of hormones like insulin
  • activation of T cells and B cells when they bind antigen with their antigen receptors (TCRs and BCRs respectively)
  • adhesion of cells to the extracellular matrix (ECM)
  • apoptosis
  • a variety of biochemical changes mediated by Protein Kinase C (PKC).

Normally, the level of calcium in the cell is very low (~100 nM). There are two main depots of Ca2+ for the cell:

  • The extracellular fluid (ECF — made from blood), where the concentration is ~ 2 mM or 20,000 times higher than in the cytosol;
  • the endoplasmic reticulum ("sarcoplasmic" reticulum in skeletal muscle).

However, its level in the cell can rise dramatically when channels in the plasma membrane open to allow it in from the extracellular fluid or from depots within the cell such as the endoplasmic reticulum and mitochondria.

Getting Ca2+ into (and out of) the cytosol

  • Voltage-gated channels
    • open in response to a change in membrane potential, e.g. the depolarization of an action potential
    • are found in excitable cells:
      • skeletal muscle
      • smooth muscle (These are the channels blocked by drugs, such as felodipine [Plendil®], used to treat high blood pressure. The influx of Ca2+ contracts the smooth muscle walls of the arterioles, raising blood pressure. The drugs block this.)
      • neurons. When the action potential reaches the presynaptic terminal, the influx of Ca2+ triggers the release of the neurotransmitter.
      • the taste cells that respond to salt.
    • allow some 106 ions to flow in each second following the steep concentration gradient.
  • Receptor-operated channels
    These are found in the post-synaptic membrane and open when they bind the neurotransmitter. Example: NMDA receptors.
  • G-protein-coupled receptors (GPCRs). These are not channels but they trigger a release of Ca2+ from the endoplasmic reticulum as described above. They are activated by various hormones and neurotransmitters (as well as bitter substances on taste cells in the tongue).

Ca2+ ions are returned

  • to the ECF by active transport using
    • an ATP-driven pump called a Ca2+ ATPase;
    • two Na+/Ca2+ exchangers. These antiport pumps harness the energy of
      • 3 Na+ ions flowing DOWN their concentration gradient to pump one Ca2+ against its gradient and
      • 4 Na+ ions flowing down to pump 1 Ca2+ and 1 K+ ion up their concentration gradients.
  • to the endoplasmic (and sarcoplasmic) reticulum using another Ca2+ ATPase.

How can such a simple ion like Ca2+ regulate so many different processes? Some factors at work:

  • localization within the cell (e.g., released at one spot — the T-system is an example — or spread throughout the cell)
  • by the amount released (amplitude modulation, "AM")
  • by releasing it in pulses of different frequencies (frequency modulation, "FM")

Role and Functions of Second Messengers | Pharmacodynamics

After reading this article you will learn about the role and functions of second messengers.

Many hormones, neurotransmitters, autacoids and drugs act on specific membrane receptors, the immediate consequence of which is activation of a cytoplasmic component of the receptor, which may be an enzyme such as adenylate cyclase, guanylate cyclase or activation of a transport systems or opening of an ion-channel.

These cytoplasmic components which carry forward the stimulus from the receptors are known as second messengers the first messenger being the receptor itself. Examples of second messengers are-cAMP, cGMP, ca 2+ , G-proteins, IP3, DAG, etc.

The role of cAMP as a second messenger was first revealed by the work of Sutherland in late 1950’s. This discovery demolished the barriers that existed between biochemistry and pharmacology. cAMP is a nucleotide synthesised within the cell from ATP by the action of adenylate cyclase in response to activation of many receptors. It is inactivated by hydrolysis to 5′-AMP, by the action of enzyme phosphodiesterase.

cAMP has varied regulatory effects on cellular functions, for example, energy metabolism, cell division and cell differentiation, ion-transport, ion-channel function, smooth muscle contractility etc. These varied effects are brought about by a common mechanism, namely the activation of various protein kinases by cAMP.

Many different drugs, hormones of neurotransmitters produce their effects by increasing or decreasing the catalytic activity of adenylate cyclase and thus lowering or raising the concentration of cAMP within the cell. The cAMP levels in the cell can also be raised by inhibiting the metabolizing enzyme phosphodiesterase.

Cyclic guanosine monophosphate is another intercellular messenger synthesised by the enzyme guanylate cyclase from GTP. It has been identified in cardiac cells, bronchial smooth muscle cells, and other tissues. For most of the effects produced, cAMP seems to be stimulatory while cGMP seems to be inhibitory in nature.

When the cAMP and cGMP systems are both present in a single cell or tissue, they are linked to receptors through which drugs produce opposite effects. For examples in cardiac tissue cells, β-adrenoceptors increase the frequency and force of contraction by increasing cAMP levels, whereas cholinergic receptors have opposite effect by increasing cGMP levels.

The IP3 and DAG system is another important intracellular second messenger system, and was identified first by Michell in 1975. Both are degradation products of membrane phospholipids by an enzyme phospholipase C. IP3 acts very effectively to release calcium from intracellular stores. This Ca 2+ is known to regulate the function of various enzymes, contractile proteins and ion- channels.

DAG directly activates protein kinase C and controls phosphorylation of ammo acids of a variety of intracellular proteins. This causes release of hormones from endocrine glands or modulates neuro­transmitter release or modulates smooth muscle contractibility or inflammatory responses or ion-transport or tumour promotion etc. There exist at least six different types of PKC distributed unequally in different cells.

Activation of another enzymes phospholipase A2 leads to production of arachidonic acid from the membrane phospholipids, which are further broken down to prostaglandins, leukotrienes, thromboxanes etc.

They are well known for their role as local hormones, but it is of interest that arachidonic acid itself and its metabolites have recently been shown to function as intracellular, messengers, controlling potassium channel function in certain neurons.

Calcium ions are of great importance amongst many other intracellular second messengers. Many regulatory actions are mediated by Ca 2+ bound to its intracellular regulatory protein, calmodulin. Ca 2+ ions are also involved in release of arachidonic acid from membrane phospholipids by activated phospholipases and so initiate the synthesis of prostaglandins and leukotrienes. Ca 2+ in synergism with PKC have been shown to activate cellular function like hepatocyte glycogenolysis, insulin release from pancreas. Ca 2+ also plays an important role in contraction and relaxation of skeletal and smooth muscles of body.

G-proteins represent the level of middle management in the cellular organisation and are able to communicate between the receptors and the effector enzymes or ion-channels. They were called G-proteins because of their interaction with the guanine nucleotides, GTP and GDP.

The G proteins are bound to the cytoplasmic surface of the plasma membrane. They are heterotrimeric molecules consisting of 3 subunits α, β and γ (fig 3.10). Their classification as stimulatory or inhibitory is based on the identity of their distinct α subunit.

The β and γ subunits remain associated as β γ complex with the cytoplasmic surface of the membrane when the system is inactive or in resting state, GDP is bound to the α subunit.

Whenever an agonist interacts with the receptor, this facilitates GTP binding to α subunit and promotes dissociation of GDP from its place. Binding of GTP activates the α subunit and α-GTP is then thought to dissociate from β and interact with a membrane bound effector.

The process is terminated when the hydrolysis of GTP to GDP occurs through the GTpase activity of the α-subunit. The resulting α-GDP then dissociates from the effector, and reunites with β γ completing the response cycle. Attachment of the subunit to an effector molecule actually increases its GTpase activity, the magnitude of this increase varies for different types of effector.

Mechanisms of this type in general result in amplification because a single agonist receptor complex can activate several G-protein molecules in turn, and each of these can remain associated with the effector enzyme for long enough to produce many molecules of product.

The product is often a second messenger, and further amplification occurs before the final cellular response is produced. It is the biological adaptation of an organism for judicious use of its transmitter substances.

G-proteins are not all identical, the α-subunit in particular shows variability. It is believed that there are three main varieties of G-protein viz. Gs, Gi and Gq. Gs and Gi produce respectively stimulation and inhibition of the effector system (fig. 3.11). It is not unusual for several receptors in an individual cell to activate a single G protein and a single receptor regulating more than one G-proteins.


Signals received by receptors at the cell surface or, in some cases, within the cell are often relayed throughout the cell via generation of small, rapidly diffusing molecules referred to as second messengers. These second messengers broadcast the initial signal (the 𠇏irst message”) that occurs when a ligand binds to a specific cellular receptor (see Heldin et al. 2014) ligand binding alters the protein conformation of the receptor such that it stimulates nearby effector proteins that catalyze the production or, in the case of ions, release or influx of the second messenger. The second messenger then diffuses rapidly to protein targets elsewhere within the cell, altering the activities as a response to the new information received by the receptor. Three classic second messenger pathways are illustrated in Figure 1 : (1) activation of adenylyl cyclase by G-protein-coupled receptors (GPCRs) to generate the cyclic nucleotide second messenger 3′-5′-cyclic adenosine monophosphate (cAMP) (2) stimulation of phosphoinositide 3-kinase (PI3K) by growth factor receptors to generate the lipid second messenger phosphatidylinositol 3,4,5-trisphosphate (PIP3) and (3) activation of phospholipase C by GPCRs to generate the two second messengers membrane-bound messenger diacylglycerol (DAG) and soluble messenger inositol 1,4,5-trisphosphate (IP3), which binds to receptors on subcellular organelles to release calcium into the cytosol. The activation of multiple effector pathways by a single plasma membrane receptor and the production of multiple second messengers by each effector can generate a high degree of amplification in signal transduction, and stimulate diverse, pleiotropic, responses depending on the cell type.

Second messengers disseminate information received from cell-surface receptors. Indicated are three examples of a receptor activating an effector to produce a second messenger that modulates the activity of a target. On the right, binding of agonists to a GPCR (the receptor) can activate adenylyl cyclase (the effector) to produce cAMP (the second messenger) to activate protein kinase A (PKA the target). On the left, binding of growth factors to a receptor tyrosine kinase (RTK the receptor) can activate PI3K (the effector) to generate PIP3 (the second messenger), which activates Akt (the target). In the center, binding of ligands to a GPCR (receptor) activates phospholipase C (PLC the effector), to generate two second messengers, DAG and IP3, which activate protein kinase C (PKC the target) and release calcium from intracellular stores, respectively.

Second messengers fall into four major classes: cyclic nucleotides, such as cAMP and other soluble molecules that signal within the cytosol lipid messengers that signal within cell membranes ions that signal within and between cellular compartments and gases and free radicals that can signal throughout the cell and even to neighboring cells. Second messengers from each of these classes bind to specific protein targets, altering their activity to relay downstream signals. In many cases, these targets are enzymes whose catalytic activity is modified by direct binding of the second messengers. The activation of multiple target enzymes by a single second messenger molecule further amplifies the signal.

Second messengers are not only produced in response to extracellular stimuli, but also in response to stimuli from within the cell. Moreover, their levels are exquisitely controlled by various homeostatic mechanisms to ensure precision in cell signaling. Indeed, dysregulation of the second messenger output in response to a particular agonist can result in cell/organ dysfunction and disease. For example, chronic exposure to cAMP in the heart results in an uncontrolled and asynchronous growth of cardiac muscle cells called pathological hypertrophy. This early stage heart disease presents as a thickening of the heart muscle (myocardium), a decrease in size of the chamber of the heart, and changes in contractility. Because such prolonged exposure to second messengers has deleterious effects, specific enzymes, channels, and buffering proteins exist to rapidly remove second messengers, either by metabolizing them or sequestering them away from target molecules.

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4.14: Secondary Messengers - Biology

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Unlike passive transport, primary active transport utilizes ATP's energy to drive protein pumps embedded in the cell membrane, which transport ions against their electrochemical gradients, a direction they wouldn't normally travel during diffusion.

One such transporter is the sodium-potassium pump, which is initially oriented so that it spans the membrane with its extracellular side closed and its intracellular region open and associated with a molecule of ATP. In this conformation, the transporter has a high affinity for sodium ions normally present in the cell, and three of these ions enter into and attach to the pump.

Such binding allows ATP to transfer one of its phosphate groups to the transporter, providing the energy needed to close the pump's intracellular side and open the extracellular region.

This new conformation decreases the pump's affinity for sodium ions, they're released into the extracellular space, but increases its affinity for potassium, allowing it to bind two potassium ions present in the environment.

The extracellular side of the pump then closes, and the ATP-derived phosphate group on the transporter detaches. This enables a new ATP molecule to associate with the pump's intracellular side, which opens and allows the potassium ions to exit into the cell, returning the transporter to its initial shape, beginning the cycle again.

5.11: Primary Active Transport

In contrast to passive transport, active transport involves a substance being moved through membranes in a direction against its concentration or electrochemical gradient. There are two types of active transport: primary active transport and secondary active transport. Primary active transport utilizes chemical energy from ATP to drive protein pumps that are embedded in the cell membrane. With energy from ATP, the pumps transport ions against their electrochemical gradients&mdasha direction they would not normally travel by diffusion.

Relationship between Concentration, Electrical, and Electrochemical Gradients

To understand the dynamics of active transport, it is important to first understand electrical and concentration gradients. A concentration gradient is a difference in the concentration of a substance across a membrane or space that drives movement from areas of high concentration to areas of low concentration. Similarly, an electrical gradient is the force resulting from the difference between electrochemical potentials on each side of the membrane that leads to the movement of ions across the membrane until the charges are similar on both sides of the membrane. An electrochemical gradient is created when the forces of a chemical concentration gradient and electrical charge gradient are combined.

Sodium-Potassium Pump

One important transporter responsible for maintaining the electrochemical gradient in cells is the sodium-potassium pump. The primary active transport activity of the pump occurs when it is oriented such that it spans the membrane with its extracellular side closed, and its intracellular region open and associated with a molecule of ATP. In this conformation, the transporter has a high affinity for sodium ions normally present in the cell in low concentrations, and three of these ions enter into and attach to the pump. Such binding allows ATP to transfer one of its phosphate groups to the transporter, providing the energy needed to close the pump&rsquos intracellular side and open the extracellular region.

The change in conformation decreases the pump&rsquos affinity for sodium ions&mdashwhich are released into the extracellular space&mdashbut increases its affinity for potassium, allowing it to bind two potassium ions present in low concentration in the extracellular environment. The extracellular side of the pump then closes, and the ATP-derived phosphate group on the transporter detaches. This enables a new ATP molecule to associate with the pump&rsquos intracellular side, which opens and allows the potassium ions to exit into the cell&mdashreturning the transporter to its initial shape beginning the cycle again.

Due to the pump&rsquos primary active transport activity, there ends up being an imbalance in the distribution of ions across the membrane. There are more potassium ions inside the cell and more sodium ions outside the cell. Therefore, the inside of the cells ends up being more negative than the outside. An electrochemical gradient is generated as a result of the ion imbalance. The force from the electrochemical gradient then propels the reactions of secondary active transport. Secondary active transport, also known as co-transport, occurs when a substance is transported across a membrane as a result of the electrochemical gradient established by primary active transport without requiring additional ATP.

Sahoo, Swagatika, Maike K. Aurich, Jon J. Jonsson, and Ines Thiele. &ldquoMembrane Transporters in a Human Genome-Scale Metabolic Knowledgebase and Their Implications for Disease.&rdquo Frontiers in Physiology 5 (March 11, 2014). [Source]

4.14: Secondary Messengers - Biology

How can one signal molecule (hormone, transmitter, etc.) produce different effects on different tissues?

A . Two Basic Methods

1. Using the Same Receptor & same 2nd messenger, but different Target Proteins

a. An example:

(1). In skeletal muscle: epinephrine causes glycogen breakdown.

(2). In smooth muscle of lung: epinephrine causes muscle relaxation.

b. Why does this make sense?

(1). Epinephrine (also called adrenaline) is produced in response to stress.

(2). In response to stress, need to "mobilize" glucose -- release it from storage so it can be broken down to provide energy. Therefore need to increase glycogen breakdown (and decrease glycogen synthesis) in muscle (& liver).

(3). In response to stress, need to breathe more deeply. Therefore need smooth muscle around tubes that carry air (bronchioles) to relax.

c. How is this possible? Same receptors, same 2nd messenger (cAMP) are used.

2. The solution: PKA is activated in both skeletal and smooth muscle. However the target proteins available to be phosphorylated are different in the two tissues. Therefore different proteins are phosphorylated and activated (or inactivated) in the two different tissue types.

a. In skeletal muscle, PKA phosphorylates phosphorylase kinase, glycogen phosphorylase etc, as on handout 12D.

b, In smooth muscle surrounding the bronchioles, PKA phosphorylates a protein (MLCK) needed for contraction, inactivating it. Therefore contraction cannot occur.

FYI only: For smooth muscle to contract, an active kinase (MLCK) must bind Ca ++ (in the form of a calmodulin /Ca ++ complex). If MLCK is phosphorlyated, the Ca ++ /calmodulin complex cannot bind to it, and contraction does not occur. ( We will discuss the role of calmodulin and the mechanism of smooth muscle contraction later.) If you like to see all the details of the role of MLCK, see Becker fig. 16-24.

2. Using different receptors & second messengers in different cell types

(See Becker fig. 14-23 (10-24). An example -- effects of epinephrine (adrenaline) on smooth muscle. Some smooth muscles relax, and some contract in response to epinephrine. In this case, different receptors & 2nd messengers are involved. How does this work? See below.

Try problem 6-11.

B. Example of Using Different Second Messengers (& Different Receptors)

1. The phenomenon:

a. Epinephrine (secreted in response to stress) has different effects on different smooth muscles:

(1). On some smooth muscles, epi → contraction

(2). On other smooth muscles, epi → relaxation (as above)

b. How does this make sense?

(1). In peripheral circulation, smooth muscles around blood vessels (arterioles) contract, diverting blood from peripheral circulation to essential internal organs

(2). In lungs, smooth muscles around tubes carrying air (bronchioles) relax, so lungs can expand more and you can breathe more deeply.

a. Ca ++ stimulates muscle contraction.

b. Epinephrine binds to receptors on some smooth muscles (ex: around arterioles) → Ca ++ released from ER → intracellular Ca ++ up → stimulates contraction.

c. Epinephrine binds to receptors on some smooth muscles (ex: around bronchioles) → phosphorylates protein needed for response to Ca ++ , preventing response.

a. Two basic types of epinephrine receptors -- called alpha and beta adrenergic receptors (adrenergic = for adrenaline). The two types are distinguished (primarily) by their relative affinities for epinephrine (adrenaline) and norepinephrine (noradrenaline).

b. Some types of smooth muscle have mostly one type of receptors some the other. (See table below and table at end of lecture 15 for details of receptor properties.)

c. Two types of receptors activate different G proteins and generate different second messengers as on handout 12A. (We will go over the details later. What you need to know so far is below.)

(1). Beta receptors → G protein type (Gs) → cAMP response → PKA

(2). Alpha1 receptors → different G protein (Gp) → different second messenger (IP3) → binds to receptors on ER membrane → opens Ca ++ channels in ER → Ca ++ release from ER → contraction

4. How does this all work to allow appropriate response to stress (epinephrine)?

a. Beta type receptors. Beta receptors are found in lung tissue in smooth muscle surrounding bronchioles.
Stress (pop quiz, lion in street, etc.) → epinephrine → muscles relax → bronchioles dilate → deeper breathing → more oxygen → energy to cope with stress.

b. Alpha type receptors. Alpha receptors are found in smooth muscle surrounding blood vessels of peripheral circulation.
Stress → epinephrine → muscles contract → constrict peripheral circulation → direct blood to essential organs for responding to stress (heart, lungs, skeletal muscle).

To review effects of different receptors, try problems 6-20 & 6-21. Note that you do not need to know the details of how IP3 is generated, but you do need to know that PLC is the enzyme responsible for producing IP3. For unknown reasons, the Greek symbols in these problems did not prin t in the latest edition of the problem book, and there are spaces instead. Where it says ' 1' or ' 2' receptors it should say '⓫' or '⓬' receptors. Where it says ' / ' it should say 'β/δ'. (There is a missing β & δ in the description of experiment (4) in the table, and in the sentence after the end of 6-21, part C-3.)

  • Agonist = mimic of hormone or ligand binds to receptor and has same effect as ligand.
  • Antagonist = blocker of effect of hormone or ligand binds to receptor (and prevents binding of normal ligand) but does not activate the receptor.

Try Problem 6-8 & 6-9 if not yet. (To review agonists & antagonists.)

6. Summary of epinephrine effects on smooth muscle (in lung vs peripheral circulation)

Note: There are more than two types of epinephrine receptors on smooth muscle cells, so epinephrine may affect smooth muscle in other tissues in other ways. (There are subtypes of alpha and subtypes of beta.)

* Details of how PLC generates IP3 are on handout 12A. We will go over this later.

Second Messengers inside the cell

Many different kinds of molecules can serve as second messengers. The signal, or ligand, binding to a membrane receptor leads to the production of second messengers inside the cell. The original signal usually doesn't enter the cell. The small molecule "cAMP" was the initial second messenger to be identified. Other examples of second messengers include NO, IP3, and DAG. The figure below shows an example of the production of second messengers.

The figure depicts a system where the signal causes a G-protein to become active,stimulating the membrane enzyme phospholipase C. This enzyme degrades cell membrane phosphatidyl inositol releasing IP3 (inositol triphosphate) and leaving diacyl glycerol (glycerol with two fatty acids, DAG). Both are second messengers, with IP3 causing the endoplasmic reticulum to release Ca ++ (also a second messenger). The DAG activates protein kinase C, a kinase that is dependent on Ca ++ for activity. Note that both second messengers play a role in the activation of protein kinase C. The response made by the cell will depend on what targets for protein kinase C are available

MRNA’s role in protein synthesis

  1. Through a process known as transcription, an RNA copy of a DNA sequence for creating a given protein is made.
  2. This copy – mRNA – travels from the nucleus of the cell to the part of the cell known as the cytoplasm, which houses ribosomes. Ribosomes are complex machinery in the cells that are responsible for making proteins.
  3. Then, through another process known as translation, ribosomes ‘read’ the mRNA, and follow the instructions, creating the protein step by step.
  4. The cell then expresses the protein and it, in turn, carries out its designated function in the cell or the body.

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Cyclic guanosine monophosphate ( cGMP ) is a second messenger regulated through natriuretic peptide and nitric oxide pathways. Stimulation of cGMP signaling is a potential therapeutic strategy for heart failure with preserved ejection fraction ( HF p EF ) and atherosclerotic cardiovascular disease ( ASCVD ). We hypothesized that plasma cGMP levels would be associated with lower risk for incident HF p EF , any HF , ASCVD , and coronary heart disease (CHD).

Methods and Results

We conducted a case–cohort analysis nested in the ARIC (Atherosclerosis Risk in Communities) study. Plasma cGMP was measured in 875 participants at visit 4 (1996–1998), with oversampling of incident HF p EF cases. We used Cox proportional hazard models to assess associations of cGMP with incident HF p EF , HF , ASCVD ( CHD +stroke), and CHD . The mean ( SD ) age was 62.4 (5.6) years and median (interquartile interval) cGMP was 3.4 pmol/ mL (2.4–4.6). During a median follow‐up of 9.9 years, there were 283 incident cases of HF p EF , 329 any HF , 151 ASCVD , and 125 CHD . In models adjusted for CVD risk factors, the hazard ratios (95% CI ) associated with the highest cGMP tertile compared with lowest for HF p EF , HF , ASCVD , and CHD were 1.88 (1.17–3.02), 2.18 (1.18–4.06), 2.84 (1.44–5.60), and 2.43 (1.19–5.00), respectively. In models further adjusted for N‐terminal‐proB‐type natriuretic peptide, associations were attenuated for HF p EF and HF but remained statistically significant for ASCVD (2.56 [1.26–5.20]) and CHD (2.25 [1.07–4.71]).


Contrary to our hypothesis, higher cGMP levels were associated with incident CVD in a community‐based cohort. The associations of cGMP with HF or HF p EF may be explained by N‐terminal‐proB‐type natriuretic peptide, but not for ASCVD and CHD.

Clinical Perspective

What Is New?

In a community‐based cohort of men and women, plasma cyclic guanosine monophosphate levels are associated with increased risk of incident heart failure with preserved ejection fraction and other cardiovascular diseases.

The associations of cyclic guanosine monophosphate with heart failure outcomes may be explained by N‐terminal‐proB‐type natriuretic peptide, but associations with other cardiovascular diseases may follow different pathways.

What Are the Clinical Implications?

Plasma cyclic guanosine monophosphate levels reflect upstream N‐terminal‐proB‐type natriuretic peptide signaling.

Abnormalities in the natriuretic peptide‐cGMP signaling pathway precede the development of heart failure with preserved ejection fraction and other cardiovascular end points these may potentially be targets for therapeutic interventions.


Although progress in clinical management of heart failure (HF) has resulted in decreased mortality, the prognosis of HF with preserved ejection fraction (HFpEF) remains largely the same. 1 HFpEF accounts for 50% of all HF cases, and it is projected to outgrow HF with reduced ejection fraction (HFrEF) over the next decade. 2 , 3 Therefore, factors that influence the pathogenesis of HFpEF may identify potential pharmacotherapy targets and have a direct impact in the prevention or treatment of HFpEF.

Cyclic guanosine monophosphate (cGMP) is an intracellular second messenger generated by guanylyl cyclases linked to either nitric oxide (NO) 4 or natriuretic peptide (NP) 5 signaling. It primarily signals by binding to and activating protein kinase G, and by interactions with other phosphodiesterases that can regulate the companion second messenger cyclic adenosine monophosphate. These effectors in turn contribute to a broad range of cardiovascular effects, including reducing vascular motor tone, antifibrotic and antihypertrophic signaling, 6 and increases in protein quality control. 7 , 8 Alterations in the cGMP signaling cascade have been implicated in several cardiovascular disorders, and new pharmacological approaches to stimulate cGMP synthesis are being evaluated as potential therapeutic agents for HFrEF, 9 , 10 HFpEF, 11 and other cardiovascular diseases (CVD). 12

Population‐based studies on cGMP are largely limited to cross‐sectional evaluations of the association between plasma cGMP and CVD risk factors in small samples. 13 , 14 , 15 , 16 , 17 To our knowledge, the association of plasma cGMP levels with the risk of developing incident CVD events has not been assessed in prospective studies. Using a case–cohort design, we measured plasma cGMP in a subset of women and men in the ARIC (Atherosclerosis Risk in Communities) study to evaluate the association between cGMP levels and CVD end points. Our primary hypothesis was that cGMP levels would be inversely associated with the risk of incident HFpEF. Our secondary hypothesis was that cGMP levels would also be inversely associated with the incidence of atherosclerotic cardiovascular disease (ASCVD), coronary heart disease (CHD), and any HF outcomes. We also assessed whether these associations differed by sex and race, and whether they were independent of NT‐proBNP (N‐terminal pro B‐type natriuretic peptide), an upstream factor regulating NP‐cGMP signaling.


Data Availability Statement

The ARIC cohort participates in the National Heart, Lung, and Blood Institute's Biologic Specimen and Data Repository (BioLINCC). The ARIC data are available upon request through BioLINCC (

Case–Cohort Design

The ARIC Study is an ongoing, prospective, predominantly biracial, community‐based study investigating risk factors for CVD. 18 Women and men 45 to 64 years of age were sampled in 1987–1989 from 4 US communities: Forsyth County, NC Jackson, MS Minneapolis suburbs, MN and Washington County, MD. Follow‐up visits were conducted in 1990–1992 (Visit 2), 1993–1995 (Visit 3), 1996–1998 (Visit 4), 2011–2013 (Visit 5), and 2016–2017 (Visit 6). The ARIC study has been approved by institutional review boards at all centers, and written informed consent was provided by all participants.

Among 9706 participants attending Visit 4 and free of HF at that visit, we conducted a case–cohort analysis based on 332 cases who developed HFpEF between January 1, 2005 (the date of onset for HFpEF adjudication in ARIC) and December 31, 2013 (the administrative censoring date by the time of case selection), as well as a random sample of 700 participants attending Visit 4 and free of HF at that visit (selected using a simple random sampling approach 25 participants in the random cohort sample were also included in the group of incident HFpEF cases). Visit 4 served as the baseline for this analysis. We then excluded participants with depleted plasma sample (n=19), unmeasurable plasma cGMP levels (n=13), participants with self‐reported race other than black or white (n=2), blacks from the Minneapolis and Washington County centers (n=6), and participants with prevalent CVD at Visit 4 (n=92).

The final study sample comprised 875 participants (Figure 1), including 283 participants who developed incident HFpEF, 329 participants who developed any HF, 151 participants who developed incident ASCVD, 125 participants who developed CHD, and 617 participants in the random cohort sample. Of note, association of cGMP with HFrEF was not examined because of few incident HFrEF cases (n=32). The reason for the greater number of HFpEF cases compared with HFrEF is that our study design specifically selected for HFpEF as our case status in this case–cohort design, given our a priori interest in understanding mechanisms for HFpEF development.

Figure 1. Flowchart of study participants. ASCVD indicates atherosclerotic cardiovascular disease cGMP, cyclic guanosine monophosphate CHD, coronary heart disease CVD, cardiovascular disease HFpEF, heart failure with preserved ejection fraction.

Measurement of cGMP

Plasma cGMP was determined from samples collected at visit 4 (1996–1998) and stored at −80°C until cGMP measurement was performed in 2017. cGMP concentrations were assessed at the Atherosclerosis Clinical Research Laboratory at Baylor College of Medicine using a competitive ELISA assay (Cayman Chemical Company, MI), with the addition of an optional acetylation procedure per manufacturer protocol. Intra‐ and interassay coefficients of variation were 4.2% and 13.5%, respectively.

Outcome Assessment

The primary outcome of this study is HFpEF. The secondary outcomes are any HF, ASCVD, and CHD. Participants were followed for CVD‐related events from visit 4 (1996–1998) through December 31, 2016 (the administrative censoring date by the time of data analysis). Incident ASCVD and HF events were identified through annual follow‐up telephone interviews, local hospital discharge lists, and death records from the National Death Index. 19 Information on all hospitalizations was extracted by trained staff and validated by physician reviewers.

HF was defined as the first HF hospitalization (International Classification of Diseases, Ninth Revision [ICD‐9] code 428) or death related to HF (ICD‐9 code 428 or ICD‐10 code I‐50). 20 HF types were classified based on left ventricular ejection fraction results from inpatient or pre‐admission tests. HFpEF was defined as a normal or mildly decreased systolic function (left ventricular ejection fraction ≥50%) within 2 years of reviewer assessment. 21 The median (interquartile range) difference of the EF and HF admission date was 1 (0–2) days.

CHD was defined as definite or probable myocardial infarction, definite fatal CHD, or cardiac procedure (percutaneous coronary interventions, bypass surgery, or coronary revascularization). ASCVD was defined as CHD or ischemic stroke (definite or probable embolic or thrombotic brain infarction).

All ASCVD and HF events were adjudicated by a physician panel using standardized criteria through review of death certificates, hospital discharge summaries, physician notes, and clinical, laboratory, and/or imaging data. While ASCVD, CHD, and any HF events have been ascertained since the ARIC baseline visit, the adjudication for the HF subtypes of HFpEF and HFrEF only became available for HF cases occurring after January 1, 2005.

Risk Factor Assessment

CVD risk factors were collected at baseline and at each follow‐up visit. Sports physical activities were assessed via a modified Baecke questionnaire at visit 3. 22 Weight and height were measured in light clothing. Sitting blood pressure measurements were taken 3 times after 5 minutes of rest during each visit using a random‐zero sphygmomanometer. Blood pressure measurements at visit 4 were calculated as average of the first and second measurements (second and third measurements in previous visits). 23 Diabetes mellitus was defined by self‐report of a physician diagnosis, a fasting blood glucose level ≥126 mg/dL, a nonfasting blood glucose level ≥200 mg/dL, or use of hypoglycemic medications. Total cholesterol, high‐density lipoprotein cholesterol, and triglyceride levels were measured using standardized enzymatic methods. Estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration equation based on serum creatinine. 24 Plasma NT‐proBNP was measured using an electrochemiluminescent immunoassay on an automated Cobas e411 analyzer (Roche Diagnostics). 25

Statistical Analysis

The study end points were the development of incident HFpEF, HF, ASCVD, and CHD. Participants were followed from visit 4 until the development of a study end point, death, dropout, or until December 31, 2016 (the administrative censoring date by the time of data analysis). We used multiple imputation with chained equations to impute missing covariates (8%). Since adjudication for HFpEF cases was only available after January 1, 2005, we specified delayed entry on January 1, 2005 for all analyses (median follow‐up 9.9 years). 26

We used Cox proportional hazards regression models to estimate hazard ratios and 95% CI for the CVD outcomes associated with cGMP tertiles. The tertiles were based on the distribution of cGMP in the random cohort sample, and estimated hazard ratios comparing the second and third tertiles with the first tertile (reference category). To account for the case–cohort design, we used the method of Lin 27 to fit weighted proportional hazards models. In addition to modeling cGMP as categorical variable, we assessed associations of cGMP as a continuous variable with CVD outcomes, per a 1 SD increase in loge‐transformed cGMP levels. We also modeled loge‐transformed cGMP levels as restricted cubic splines with knots at the 5th, 50th, and 95th percentiles of its distribution in the cohort random sample.

For each outcome, we used 4 models with increasing degrees of adjustment. Model 1 adjusted for demographic factors: age, sex, and race/center groups. Model 2 further adjusted for lifestyle variables: education, physical activity, smoking, alcohol consumption, and body mass index. Model 3 further adjusted for intermediate CVD risk factors: systolic blood pressure, use of antihypertensive medications, total cholesterol, high‐density lipoprotein cholesterol, use of lipid‐lowering medication, diabetes mellitus, and estimated glomerular filtration rate. Finally, model 4 further adjusted for loge‐transformed NT‐proBNP.

We conducted subgroup analyses by sex, race, and NT‐proBNP tertile. Spearman's rank‐order correlation efficient was used to assess the correlation between cGMP and NT‐proBNP. Finally, we performed additional analyses to evaluate the association of NT‐proBNP levels with CVD outcomes adjusting for loge‐transformed cGMP. All reported P values were 2‐sided and the significance level was set at 0.05. Statistical analyses were performed using Stata version 15 (StataCorp LP, College Station, TX).


The average age of participants in the random cohort sample (n=617) at baseline was 62.4 years (SD 5.6), and their median cGMP was 3.3 pmol/mL (interquartile interval 2.3–4.4). Participants with higher cGMP levels were more likely to be older, black, and nondiabetic they were more likely to have lower levels of body mass index, triglycerides, estimated glomerular filtration rate, and higher levels of systolic blood pressure, high‐density lipoprotein cholesterol, and NT‐proBNP (Table 1). cGMP and NT‐proBNP were correlated with a Spearman correlation coefficient of 0.37. The baseline characteristics of participants who developed HFpEF, HF, ASCVD, and CHD over follow‐up are shown in Table S1.

Table 1. Baseline Characteristics by cGMP Tertiles Among Random Cohort Sample

BMI indicates body mass index BP, blood pressure cGMP, cyclic guanosine monophosphate eGFR, estimated glomerular filtration rate HDL, high‐density lipoprotein NT‐proBNP, N‐terminal pro B‐type natriuretic peptide.

a Values in the table are mean (SD), median (interquartile interval), or number (percentage).

b Data for physical activity are from Atherosis Risk in Communities (ARIC) visit 3.

During a median of 9.9 years of follow‐up, there were 283 incident cases of HFpEF, 329 any HF, 151 ASCVD, and 125 CHD. In models adjusted for demographics, lifestyle characteristics, and CVD risk factors, higher plasma cGMP levels were associated with a higher risk of incident CVD events (Table 2, model 3). The hazard ratios (95% CI) associated with the highest tertile of cGMP compared with lowest for HFpEF, HF, ASCVD, and CHD were 1.88 (1.17–3.02), 2.18 (1.18–4.06), 2.84 (1.44–5.60), and 2.43 (1.19–5.00), respectively. In models further adjusted for NT‐proBNP, the associations were attenuated and no longer significant for HFpEF and HF, but remained statistically significant for ASCVD and CHD (hazard ratio [95% CI] for HFpEF: 1.30 [0.79–2.14], HF: 1.68 [0.88–3.22], ASCVD: 2.56 [1.26–.20] and CHD: 2.25 [1.07–.71]) (Table 2, model 4).

Table 2. Hazard Ratios (95% CI) for Cardiovascular Outcome Associations With cGMP Levels

ASCVD indicates atherosclerotic cardiovascular disease cGMP, cyclic guanosine monophosphate HFpEF, heart failure with preserved ejection fraction IR, incident rate.

Model 1: age, sex, race/center. Model 2: model 1 + education, smoking, alcohol consumption, body mass index, physical activity. Model 3: model 2 + systolic blood pressure, hypertension medication, diabetes mellitus, total and high‐density lipoprotein cholesterol, lipid‐lowering medication, estimated glomerular filtration rate. Model 4: model 3 + log‐transformed N‐terminal pro B‐type natriuretic peptide. 1 SD of loge‐transformed cGMP levels: 0.64.

In spline regression analyses, there was generally a positive dose–response relationship between higher cGMP levels and incident CVD outcomes (Figure 2). The P values for the nonlinear spline components of cGMP for the outcomes of HFpEF, HF, ASCVD, and CHD were 0.80, 0.27, 0.90, and 0.52, respectively, indicating that the associations between cGMP with these end points were approximately linear.

Figure 2. HR for incident cardiovascular outcomes by cGMP levels. The curves represent the adjusted hazard ratios for heart failure with preserved ejection fraction ( HF p EF ), heart failure ( HF ), atherosclerotic cardiovascular disease ( ASCVD ), and coronary heart disease ( CHD ) by log‐ cGMP levels. The dose–response association was estimated using linear cubic splines for log‐ cGMP levels in multivariable Cox regression models. The models were adjusted for age, sex, race/center, education, smoking, alcohol consumption, body mass index, physical activity, systolic blood pressure, hypertension medication, diabetes mellitus, total and high‐density lipoprotein cholesterol, lipid‐lowering medication, estimated glomerular filtration rate, and log‐transformed NT ‐pro BNP . Curves represent adjusted HRs (solid lines) and their 95% CI (dashed lines) based on restricted cubic splines for log‐ cGMP with knots at the 5th, 50th, and 95th percentiles of the distribution of cGMP in the random cohort sample. The reference values (diamond dots) were set at 10th percentile of the distribution of cGMP in the random cohort sample. The histogram represents the distribution of cGMP in the random cohort sample. ASCVD indicates atherosclerotic cardiovascular disease cGMP , cyclic guanosine monophosphate CHD , coronary heart disease HF p EF , heart failure with preserved ejection fraction HR, hazard ratio NT ‐pro BNP , N‐terminal pro B‐type natriuretic peptide.

In subgroup analysis, the associations between cGMP and CVD outcomes were consistent across NT‐pro‐BNP levels, with P values for interaction of 0.94, 0.32, 0.56, and 0.52 for HFpEF, HF, ASCVD, and CHD, respectively (Table 3). There were no significant interactions by sex and race for the associations of cGMP and CVD outcomes, although the associations appeared to be stronger in women than men (Tables S2, S3). Finally, the associations between NT‐proBNP and HFpEF/HF outcomes were slightly attenuated but remained strong after additionally adjusting for loge‐transformed cGMP (Table S4). However, the association between NT‐proBNP with ASCVD/CHD outcomes was no longer significant after adjusting for cGMP.

Table 3. Hazard Ratios (95% CI) for Cardiovascular Outcomes Associations With cGMP and NT‐proBNP Levels

ASCVD indicates atherosclerotic cardiovascular disease cGMP, cyclic guanosine monophosphate HFpEF, heart failure with preserved ejection fraction NT‐proBNP, N‐terminal pro B‐type natriuretic peptide.

1 SD of loge‐transformed cGMP levels: 0.64.

* Model adjusted for age, sex, race/center, education, smoking, alcohol consumption, body mass index, physical activity, systolic blood pressure, hypertension medication, diabetes mellitus, total and high‐density lipoprotein cholesterol, lipid‐lowering medication, and estimated glomerular filtration rate.


In this community‐based cohort of middle‐aged to older men and women followed for 10 years, higher plasma cGMP levels were associated with an increased risk of incident HF and CVD outcomes. However, the associations for HFpEF and HF were largely explained by NT‐proBNP, an upstream messenger to cGMP in the NP signaling pathway. On the other hand, the associations of cGMP with ASCVD and CHD, while attenuated, remained strong and statistically significant after adjustment for NT‐proBNP, suggesting alternate pathways in their relationships not fully explained by the NP pathway. The associations between cGMP levels and CVD outcomes were generally consistent by sex and NT‐proBNP levels, although the associations appeared to be stronger in women than in men. Our findings contradict our initial hypothesis of an inverse association between cGMP and CVD outcomes, and suggest that the association of plasma cGMP with HF outcomes reflect the underlying association between NT‐proBNP and HF outcomes. In hindsight, this makes plausible biological sense given that circulating plasma cGMP is largely reflective of NP, and not NO, pools.

CGMP Signaling Pathways and Mechanisms of Action

BNP is a hormone released by myocardial cells as a compensatory mechanism in response to ventricular wall stretch stemming from increased ventricular blood volume. 28 BNP‐signaling binds to the particulate (membrane‐bound) guanylate cyclase complex (guanylyl cyclases‐A), which stimulates the synthesis of cGMP. cGMP in turn binds to regulatory domains in protein kinase G as well as modulates selective phosphodiesterases that control cGMP or cyclic adenosine monophosphate hydrolysis 7 . Prior Mendelian randomization studies have suggested a protective effect of the NP‐cGMP pathway, demonstrating that genetic variants associated with increased circulating BNP were found to be associated with reduced frequency of hypertension, metabolic dysfunction, and mortality. 29 , 30 However, the current study found a direct association between plasma NT‐proBNP and cGMP with CVD outcomes.

Rather than suggesting cGMP and its associated signaling are maladaptive, the new findings are likely explained by 2 factors. First, elevated plasma cGMP, like NT‐proBNP, serves as a biomarker for subclinical CVD, its elevation being a reflection of compensations that ultimately proved inadequate. Second, cGMP‐targeting phosphodiesterases could have potentially depressed cGMP levels despite higher NP‐stimulated synthesis. If so, the relation of cGMP to CVD risk would not have mirrored that of NT‐proBNP. That they do mirror one another indicates that phosphodiesterases regulatory differences are less important in predicting CVD evolution.

Another reason for the observed correlations between cGMP and NT‐proBNP is that we assessed plasma, which reflects cGMP production via the NP pathway more than the NO pathway. 31 This is because NP‐generated cGMP resides at the plasma membrane and is secreted into the extracellular space, whereas NO signaling via intracellular guanylyl cyclases‐1 generates very small compartmentalized cGMP that is not as easily detected in plasma. 32 A prior study found that infusion of the endogenous NO inhibitor, asymmetrical dimethylarginine, decreased plasma cGMP, lowered cardiac output, and increased vascular resistance. 33 However, in other studies, nitrate therapy decreased 17 or did not change plasma cGMP. 34 Similarly, in the INDIE‐HFpEF (Inorganic Nitrite Delivery to Improve Exercise Capacity in HFpEF) trial, inorganic nitrite also did not change plasma cGMP levels. 35 By contrast, studies of sacubitril/valsartan therapy in HFrEF subjects, the former being a neprilysin inhibitor that can augment NP‐dependent signaling, have consistently found associations with elevated plasma and urinary cGMP. 10 Both plasma and urinary cGMP are derived from the NP pathway, but they are not correlated. 36 Plasma cGMP is only partially eliminated through renal clearance, whereas urinary cGMP is primarily generated by renal cells. 31

Population‐Based Studies

Based on preclinical and small clinical studies, stimulation of the cGMP pathway appeared to be a promising potential therapeutic strategy for the treatment of HFpEF. 37 Nevertheless, more understanding is needed regarding the utility of measuring plasma cGMP levels as a prognostic marker of incident disease. However, few prior population studies have evaluated the association between cGMP with incident CVD risk. A case–control study showed that plasma cGMP levels were higher in 18 HF patients compared with 15 controls. 17 Similarly, plasma and urinary cGMP levels were significantly higher in 50 congestive HF patients than in 70 randomly selected healthy participants. 36 In another study of 84 asymptomatic men, plasma cGMP was positively associated with carotid intima‐media thickness and diameter, but was not associated with atherosclerotic plaques. 16 These studies were limited by cross‐sectional or retrospective designs, small sample sizes, poor adjustment for covariates, and the use of highly selected samples. Importantly, our study newly adds to the literature by now presenting associations of plasma cGMP with various incident CVD outcomes in a community‐based cohort free of HF and CVD at baseline, and our prospective findings of cGMP being associated with incident CVD events are consistent with prior cross‐sectional studies.

Biomarker Paradox

In the PARADIGM‐HF (Prospective Comparison of ARNI [Angiotensin Receptor‐Neprilysin Inhibitor] with ACEI [Angiotensin‐Converting‐Enzyme Inhibitor] to Determine Impact on Global Mortality and Morbidity in Heart Failure) trial, both urinary cGMP and plasma BNP levels were higher with sacubitril/valsartan treatment than with enalapril, but NT‐proBNP levels were lower. Since BNP is a substrate for neprilysin, the higher BNP levels likely reflect the effect of the neprilysin inhibitor sacubitril while the lower concentrations of NT‐proBNP on drug treatment likely reflect the favorable effects on reducing myocardial stress. 10 This paradox highlights the complexity of interpreting these biomarkers in serum/plasma, where despite the cardioprotective effects of natriuretic peptides, plasma levels of NT‐proBNP are elevated in pathological states.

We had hypothesized that cGMP would be inversely associated with CVD outcomes, but found the opposite instead. The NP pathway is a major upstream regulator of plasma cGMP, 31 and our findings here in the ARIC study, as well as in a cross‐sectional analysis from the MESA study (Multi‐Ethnic Study of Atherosclerosis), 38 indicate that plasma cGMP levels directly track with plasma NT‐proBNP levels. Our results suggest that abnormalities in the NP‐cGMP signaling pathway may precede HFpEF and other CVDs. These changes may be amenable to therapeutic interventions. However, in our study, the associations between cGMP and CVD outcomes did not differ across NT‐proBNP levels, suggesting that the cardiovascular effects of cGMP did not depend on the bioavailability of NT‐proBNP. A limitation of our study was the lack of information on other natriuretic peptides including BNP and atrial natriuretic peptide, as well as the lack of information on NO‐dependent cGMP, and we were not able to tease out the associations of plasma cGMP derived from other signaling pathways.

Race and Sex Differences

We could not detect differences in the association of cGMP levels with CVD end points by sex and race. However, because of limited power, the effect modifications by sex and race require evaluation in other studies. Plasma cGMP levels in our random cohort sample were slightly lower in whites than in blacks (median 3.1 versus 3.7 pmol/mL, p=0.03), whereas previous studies demonstrate that plasma NT‐proBNP levels were higher in whites than in blacks in ARIC and in other cohorts, 39 , 40 and genetic European ancestry was associated with higher NT‐proBNP levels compared with African ancestry. 40 , 41 The associations of NT‐proBNP with all‐cause and cardiovascular mortality were similar by race in the REGARDS (Reasons for Geographic and Racial Differences in Stroke) study, 39 but there may be racial differences in NP‐mediated cGMP production and its association with CVD outcomes. Additionally, women have both higher cGMP levels and NT‐proBNP levels when compared with men, 42 and the prevalence of HFpEF is higher in women versus men. 43 The racial and sex differences in cGMP signaling physiology and their implications for prognosis and treatment of CVD need to be further examined in population studies, including a more detailed evaluation of the differences in genetic variants that determine cGMP levels.

Strengths and Limitations

Our study has some additional limitations. First, we measured plasma cGMP and NT‐proBNP at only a single point in time and did not have data on longitudinal changes that may be more informative of the underlying cardiovascular changes that determine disease risk. Single measurements may have also resulted in measurement error because of within‐person variability in cGMP and NT‐proBNP levels. Second, our study was designed primarily to evaluate the association of cGMP with incident HFpEF (the case status selected for our case–cohort design), and had limited power to evaluate some CVD end points such as stroke and HFrEF, as well as to perform subgroup analyses. Third, we could only identify HF and CVD cases through hospitalization or death certificate, which might miss patients who were not hospitalized presenting with less severe cases of HF managed entirely in the outpatient setting. Nevertheless, among HF diagnosed in a community‐based outpatient setting, 74% are hospitalized within 1.7 years. 44 Finally, our study was observational in nature, and we were not able to evaluate whether inhibition or enhancement of cGMP by therapeutic interventions were associated with changes of risk for CVD outcomes.

The strengths of this study included the use of a well‐established cohort with a rigorous study protocol, high‐quality measurements of cGMP and other study variables, and detailed information on multiple potential factors, including NT‐proBNP. The 10 years of follow‐up also enabled us to estimate the long‐term associations of cGMP with incident ASCVD and HF risk.


In summary, our findings suggest that abnormalities in the NP‐cGMP signaling pathway precede the development of HFpEF and other CVD end points. We found that higher cGMP levels were associated with incident HFpEF and any HF, but these associations were attenuated and were no longer significant after adjusting for NT‐proBNP. Since cGMP synthesis is activated by NPs, our findings suggest that the association of plasma cGMP with HF outcomes reflects the underlying association between NT‐proBNP and HF outcomes. However, the associations of the highest tertile of cGMP levels (compared with lowest) with ASCVD and CHD outcomes remained statistically significant even after adjusting for NT‐proBNP, suggesting other pathways explain the relationship that are not entirely mediated through NT‐proBNP. Repeated measurements of biomarkers in this pathway are needed to better understand the complex changes that occur before the development of clinically overt CVD. Additional studies should further explore the potential role of cGMP as a diagnostic and prognostic biomarker for HF and other CVD outcomes.

Sources of Funding

This work was funded by the American Heart Association Go Red for Women Strategically Focused Research Network grant 16SFRN27870000. The Atherosclerosis Risk in Communities study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, under Contract nos. (HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700005I, and HHSN268201700004I). Drs Zhao and Michos are also funded by the Blumenthal Scholars Preventive Cardiology Fund at Johns Hopkins University.

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