The Intersection of Immunology and Metabolism in Myocardial Disease

Abstract

Immunometabolism is an emerging field at the intersection of immunology and metabolism. Immune cell activation plays a critical role in the pathogenesis of cardiovascular diseases and is integral for regeneration during cardiac injury. We currently possess a limited understanding of the processes governing metabolic interactions between immune cells and cardiomyocytes. The impact of this intercellular crosstalk can manifest as alterations to the steady state flux of metabolites and impact cardiac contractile function. While much of our knowledge is derived from acute inflammatory response, recent work emphasizes heterogeneity and flexibility in metabolism between cardiomyocytes and immune cells during pathological states, including ischemic, cardiometabolic, and cancer-associated disease. Metabolic adaptation is crucial because it influences immune cell activation, cytokine release, and potential therapeutic vulnerabilities. This review describes current concepts about immunometabolic regulation in the heart, focusing on intercellular crosstalk and intrinsic factors driving cellular regulation. We discuss experimental approaches to measure the cardio-immunologic crosstalk, which are necessary to uncover unknown mechanisms underlying the immune and cardiac interface. Deeper insight into these axes holds promise for therapeutic strategies that optimize cardioimmunology crosstalk for cardiac health.

Introduction

Immunometabolism has emerged at the forefront of immunology and intersects closely with cardiovascular research. Immune cells can contribute up to ten percent of the heart ¹. Historically characterized as sentinels that guard against infection and respond to injury, new data across multiple organs highlight the contribution of innate immune cells to noncanonical aspects of organ homeostasis ². It is increasingly clear that immune cells have heterogeneous metabolic preferences and dependencies, and the cellular environment influences their activity states. Interactions between immune cells and cardiomyocytes are significant because immune cell activation requires precise metabolic regulation ^3–5. Unlike any other organ, the heart can utilize almost any nutrient class to provide ATP, creating a unique metabolic environment for immune cells during cardiac injury. Metabolic intermediates signal, regulate, and provide cellular processes ranging from energy in the form of ATP to the synthesis of macromolecules such as proteins and lipids. How these metabolic signals are integrated and regulated has been a focus of cardiovascular research for over 70 years^6–9. The emergence of advanced technologies has led to the discovery that the heart comprises a heterogeneous cell population, including immune and stromal cells, and certain nutrients support metabolic crosstalk between cardiomyocytes and non-cardiomyocytes. Metabolic changes in the heart are dynamic, and the combined effect of extrinsic changes in the environment (oxygen and nutrient supplies) and their intrinsic integration is based on the cellular composition (e.g., protein level, gene expression). Understanding how metabolic interactions between cardiomyocytes and immune cells emerge requires a deeper knowledge of their dynamic regulation at the cellular level and recognizing divergent immune cell populations. These relationships include distinct immune cell activation during inflammation^10,11, ischemic heart disease^12–14, cardiomyopathy^15–19, and malignancies^20–23. We have only started to recognize the unique metabolic properties within the cellular milieu of the heart and how these factors drive disease progression. Understanding metabolic drivers in the crosstalks between cardiomyocytes and immune cells will influence therapeutic and diagnostic strategies. Here, we discuss recent work toward understanding the mechanisms by which metabolism is directly or indirectly linked to the crosstalk between cardiomyocytes and immune cells in the heart. We also discuss how inflammation and the innate immune response influence cardiac metabolism and contractile function and how scientists can apply novel technologies to understand metabolic interactions at a systems level. The dynamic relationship between metabolism and cellular functions explains the interplay between inflammation, immune cells, and cardiomyocytes.

Immune Cell Composition of the Normal and Inflamed Heart.

The healthy heart comprises a heterogeneous cell population, including myeloid and lymphoid cells. Recent single-cell transcriptomic approaches revealed that the distribution of immune cells differs between atrial and ventricular tissue. Atrial tissue contains 10.4% immune cells, while ventricular tissue comprises 5.3% immune cells ²⁴. The primary immune cells are myeloid cells, typically resident macrophages, and account for up to 8% of the total cell population in the heart ¹. In comparison, a sparse number of T lymphocytes reside in the heart (<1%), which are increased during the acute immune response and recruited alongside an influx of B-cells, neutrophils, and monocytes. Prolonged and uncontrolled activation of immune responses can lead to adverse cardiac remodeling and impair cardiac contractile function ²⁵.

In the heart, macrophages have received a significant amount of attention for their effects on myocardial biology and serve as an example of how the immune compartment can regulate cardiac function. Macrophages support the metabolic homeostasis of multiple tissues and contribute to cardiac development, cardiac homeostasis, and the response to stress ²⁶. In a healthy heart, macrophages can be divided into subtypes according to their distinct ontological origins. Among these subtypes are long-lived yolk sac-derived macrophages and adult monocyte-derived macrophages ^27,28. Comparing chemokine (C-C motif) receptor 2 (CCR2) expression levels is a reliable way to differentiate between subtypes of cardiac macrophages. For example, CCR2⁺ macrophages arise from circulating monocytes, unlike resident macrophages that lack CCR2 (CCR2⁻). CCR2⁻ macrophages can self-renew and often derive from embryonic seeding ²⁷. CCR2⁻ macrophages can further be divided by expression level of major histocompatibility complex class II ²⁹, or HLA-DR^{hi 4} in humans. Tissue-resident macrophages interact with as many as five distinct cardiomyocyte populations ³⁰, regulate local iron availability, and modulate the tissue microenvironment, contributing to cellular and tissue function ³¹. Furthermore, resident macrophages support cardiac metabolic homeostasis by facilitating the clearance of mitochondria, which are released from cardiomyocytes ³⁰.

T lymphocytes are critical in responding to cardiac injury by regulating the cellular response from the acute to the chronic phase. Resting or naïve T cells become activated after stimulation by antigens and costimulatory signals, which are related to cellular injury (e.g., ischemia, drug-induced) or viral infections. These activated T cells produce and consume cytokines. Regulatory CD4⁺ T cells (Tregs) promote reparative fibrosis and support tissue regeneration by depriving cycling T cells of cytokines ¹². This interaction limits prolonged antigenic stimulation. Sustained T cell response in the heart causes adverse cardiac remodeling and contributes to the progression of ischemic heart failure, which is primarily attributed to increased levels of cytotoxic CD8⁺ T-cells. Once the antigen and cytokine stimulation decreases, a small fraction of T cells will be reprogrammed to expand a small population of antigen-specific T cells. These cells serve as memory T cells to facilitate a persistent immune response if the pathogen returns. These critical roles of T cell populations make them an attractive target for clinical therapeutic strategies and central for immunotherapy.

Metabolic Demands of Immune Cells

Interactions between cardiomyocytes and immune cells within the heart are critical because both cell types require precise regulation of metabolic processes for their cellular function. Studying these interactions is important for a mechanistic understanding of inflammation and innate immune activation during the progression of cardiac disease (e.g., cardiac ischemia, heart failure, myocarditis, sepsis, cardiac allograft rejection) and might broaden the application of clinical immunotherapy. A few studies have begun to explore the impact of the innate and adaptive immune response during cardiometabolic stress and whether cellular effects drive cardiac remodeling. These mostly preclinical studies suggest that the immune cell response influences cardiomyocyte cell functions and might contribute to treatment failures. Thus, there is clinical value in defining the metabolic basis for altered immune cell activation and factors that drive metabolic changes in cardiomyocyte functions. To understand these relationships, we first need to discuss the nutrient needs of immune cells, particularly resident macrophages and T cells in the heart (Table 1).

Table 1.

Metabolic Propensities of Immune Cells.

	Anti-inflammatory and Repair Macrophage	Inflammatory Macrophage	Activated T cell	Treg cell	Naïve T cell
Glycolysis	Favors mitochondrial metabolism33	Primary source for ATP provision; Supports phagocytosis and inflammatory cytokine production32	Supports proliferation and inflammatory cytokine production37	Supports cell migration35	Favors mitochondrial metabolism38
Krebs cycle	Primary source for ATP provision; Supports oxidative phosphorylation and cell homeostasis43	Impaired oxidative metabolism: Redirection of Krebs cycle flux supports citrate production and de novo fatty acid synthesis102	Supports epigenetic remodeling39	Associated with suppressive function36	Supports oxidative phosphorylation and cell homeostasis38
Pentose phosphate pathway	Implicated in cellular proliferation158	Supports nucleotide and ROS production34	Unclear role	Epigenetic remodeling159	Preferred in proliferating cells37
Fatty acid β-oxidation	Primary source for ATP provision; Inhibition of inflammatory signal33	Glycolysis favored32	Promotes cell proliferation and regulates cytokine production49	Promotes cell differentiation and stimulation49	Favored over glycolysis38
Fatty acid synthesis	Unclear role	Glucose-derived citrate supports proliferation and inflammatory cytokine production48	Unclear role49	Promotes functional maturation51	Promotes cell proliferation and survival50
Amino acid metabolism	Supports arginase pathway activity160	Supports proliferation and NO production54	Promotes memory T cell formation56,60,161	Promotes Treg activity55,59	Quiescent56,59

Glucose, fatty acids, and amino acids, especially glutamine, serve as primary nutrient sources for ATP provision in immune cells. Glycolytic intermediates enhance the rapid activation of inflammatory macrophages^32–34, Tregs^35,36 and memory T cells^37–39 undergoing rapid activation in response to cytokine receptor or antigen receptor stimulation. Glycolytic flux serves both ATP provision and the production of biosynthetic precursors for synthesizing DNA, RNA, proteins, and lipids. For example, in macrophages, phagocytosis, and inflammatory cytokine production depends on glycolytic flux. Key regulatory enzymes within the glycolytic pathway serve both metabolic and signaling functions. The pyruvate kinase isoenzyme M2 (PKM2) reduces pyruvate entry into the Krebs cycle and redirects glycolytic intermediates to biosynthetic pathways. Translocation of PKM2 into the nucleus interacts with HIF1-α^32,40, driving the expression of glycolytic enzymes and inflammatory factors. Likewise, enolase⁴¹ and hexokinase⁴² have signaling properties that are activated during inflammatory response and regulate immune cell reprogramming by activating mTOR and HIF-signaling pathways.

Recent work indicates that fatty acid β-oxidation modulates macrophage and T cell function. Fatty acids are the primary source of ATP in naïve T cells³⁸, anti-inflammatory macrophages^33,43, and repair macrophages^33,43. Accumulation of unsaturated (e.g., oleic acid and linoleic acid) but not saturated fatty acids stimulates the production of inflammatory macrophages in vivo ^44–46. Impaired oxidative metabolism in macrophages redirects glucose-derived citrate flux toward the cytosol, increasing de novo fatty acid synthesis ^47,48. Similarly, the generation and proliferation of Tregs and memory T cells are driven by fatty acid β-oxidation while inhibiting effector T cell polarization ^49–51. Oxidation of fatty acids is downregulated upon T cell activation. Consistently, ligation of the inhibitory programmed death 1 (PD1) receptor on T cells resulted in increased expression of CPT1A and elevated fatty acid β-oxidation ^52,53.

Adequate extracellular supplies of glutamine are required for the induction of inflammatory macrophages and NO production during bacterial infections ^34,54. Likewise, glutamine oxidation stimulates Tregs, promoting cell differentiation, proliferation, and cytokine production ⁵⁵. Recent studies indicate that reduced glutamine availability shifts the generation of T helper (Th) cells towards Tregs ⁵⁶. Inhibition of glutaminase activity and genetic loss of the transporter protein ASCT2 decreased the intracellular amount of α-ketoglutarate, which resulted in impaired generation of Th1 and Th17 cells, whereas Treg populations were not affected ^56–59. Pharmacological inhibition of glutaminase activity or glutamine withdrawal in vitro decreases inflammatory macrophage activation, while repair macrophages are not affected ^60,61. Immune cell activation is driven by extracellular nutrients, which create metabolic pressures. Nutrient availability and regional fuel alterations in the heart during stress may impact metabolic demands and profiles in immune cells. The cellular environment is critical in activating or repressing macrophage and T-cell function, and this complexity is likely amplified in the heart because of its unique metabolic capacity and metabolic by-products.

Metabolic Alterations Induced by Cytokine Signaling

Crosstalk between cells is facilitated through various mechanisms, the most appreciated form being crosstalk between proteins derived from signaling cascades. A case in point is the regulation of inflammation via cytokines. During cardiac stress, impairments in cardiac function and metabolism are correlated to escalations in inflammation and escalation of cytokines. Low-grade sterile inflammation, in the absence of a pathogen, is linked to numerous chronic diseases, including muscle pathologies, and cytokines can modulate cardiac function ⁶². A few studies have begun to explore the impact of the innate and adaptive immune response during cardiometabolic stress and whether cellular effects drive cardiac remodeling. A recent preclinical study of heart failure with preserved ejection fraction (HFpEF) in a combined model of obesity and hypertension demonstrated that cytokine-secreting immune cells accumulate in the myocardium during disease progression ⁶³. The cytokines Tumor necrosis factor alpha (TNF-α) and interleukin 6 (IL-6) can attenuate insulin signaling and promote insulin resistance in the heart and skeletal muscle (Figure 1) ^64,65. This interference can occur by direct impairments in glucose uptake and through alterations of insulin signal transduction. Exposure of cardiomyocytes to both TNF-α, IL-1α, and interferon-gamma (IFN-γ) by lymphocytes (Th1 cells) impairs pyruvate dehydrogenase activity, disrupting Krebs cycle function and oxidative phosphorylation ⁶⁶ and leading to mitochondrial dysfunction in cardiomyocytes ⁶⁷. Consistently blocking TNF-α attenuates the development of experimental diabetic cardiomyopathy, in conjunction with reduced inflammation ⁶⁸.

Figure 1. The interface of inflammation and immune cells with cardiac cell metabolism and cardiac function.

Depicted in the figure is a working model of the contributions of inflammation and immune cells to cardiac metabolism and cardiac function. As described in the body of the text, immune cells and/or cytokines have the capacity regulate cardiomyocyte functional and metabolic responses. Cardiomyocytes also secrete factors that are recognized by immune cells, such as spent mitochondria (exophers). Abbreviations: FAO, fatty acid β-oxidation; IFN-γ, Interferon-gamma; OXPHOS, oxidative phosphorylation; STAT1, Signal Transducer and Activator of Transcription 1; TNFα, Tumor necrosis factor alpha; TNFR, Tumor necrosis factor receptor.

Myocardial metabolism can also be regulated through the control of cytokine receptors. For example, the interleukin (IL)-13 receptor chain alpha 1 (IL-13Rα1) (Figure 1), a component of a common receptor to IL-4 and IL-13, can regulate myocardial metabolism and contractile function⁶⁹. Loss of IL-13Rα1 was associated with a downregulation of genes related to glycolysis, Krebs cycle and pyruvate metabolism, and computational flux analysis revealed decreased metabolic fluxes in these pathways ⁶⁹. This interaction is significant because these receptors elicit inflammatory responses from alternatively activated macrophages, T helper 2 cells, and other components of the type II immune response ⁷⁰. Inflammatory activation is also linked as a risk factor for arrhythmias with arrhythmogenic effects of proinflammatory cytokines ⁷¹. For instance, in an experimental mouse model of diabetes mellitus, increased myocardial IL-1β was directly correlated with QT-interval prolongation and an increased inducibility of ventricular tachycardia ⁷². Cytokines may also influence cardiac function by affecting the stromal cells of the heart. Transforming growth factor-β (TGF-β) can be sourced from macrophages and stimulate fibroblasts to synthesize collagen ⁷³. Excessive collagen production has been associated with increased myocardial stiffness and diastolic dysfunction. Together these examples highlight the importance of protein signaling in communicating metabolic alterations in the context of cardiac diseases.

Metabolic Relationships between Cardiomyocytes and Immune Cells during Disease

Metabolic demands rapidly change during inflammation and immune cell activation, which require cellular responses at the molecular level within seconds or minutes. These alterations allow immune cells to adapt to changes in the body, supporting energy provision and immune effector functions. Metabolic regulation and control are tightly linked to enzyme-catalyzed cellular reactions. However, it takes hours for an inducing or repressing signal to impact enzyme concentrations. In contrast, intermediary metabolites serve as rapid response signals driving inflammation through the activation of signaling pathways, transcription factors, and epigenetic regulation ^{7–9,74–76}. Among the most important cellular pathways are glycolysis, the pentose phosphate pathway, the Krebs cycle, fatty acid oxidation, fatty acid synthesis, and amino acid pathways. These metabolic pathways yield chemically diverse end-products serving unique cellular and immune (Figure 2) functions that allow interactions within the cell and beyond.

Figure 2. Intersection of Metabolites and Cell and Crosstalk Signaling.

Depiction of select metabolites that also regulate cellular signaling pathways. Abbreviations are as follows: α-KG, α-Ketoglutarate; ACL, ATP-dependent citrate-lyase; ACOD, Aconitate decarboxylase; DNMT, DNA methyltransferase; FAO, fatty acid oxidation; HAT, histone acyltransferase; HMT, histone methyltransferase; IDH, Isocitrate dehydrogenase; JHDM, Jumonji C domain-containing HDM; PDH, pyruvate dehydrogenase; SLC, Solute Carrier; TET, Tet methylcytosine dioxygenase.

Glycolysis and pentose phosphate pathway

Glycolysis reduces extracellular glucose to pyruvate, while providing 2 molecules of ATP. However, glycolysis also supports the reduction of NAD⁺ to NADH, which is a cofactor in numerous enzymatic reactions and is required for biosynthetic pathways including protein and lipid synthesis. Glycolysis provides metabolic intermediates for the synthesis of glycogen, ribose from nucleotides (glucose 6-phosphate) in the pentose phosphate pathway, nonessential amino acids (pyruvate to alanine and 3-phosphoglycerate to serine), and fatty acids (pyruvate to acetyl-CoA and citrate). Growth signaling pathways integrate signals from glycolytic intermediates, including mTOR, phosphatidylinositol 3-kinase (PI3K), and mitogen-activated protein kinase (MAPK). Glycolysis is intertwined with the pentose phosphate pathway beyond the production of nucleotides and nonessential amino acids by ensuring the provision of NADPH. The reducing equivalents of NADPH are required co-factors for anabolic reactions, including the synthesis of fatty acids and complex lipids. Therefore, glycolytic intermediates serve as metabolic signals (Figure 2). To maintain glycolytic flux, cells reduce pyruvate to lactate while regenerating NADH and maintaining NAD⁺ levels. Subsequently, lactate is removed from the cell and accumulates in the extracellular space. Skeletal muscle is a major source of systemic lactate production and provides important glycolytic and gluconeogenic intermediates for other tissues, including the heart. Inflammatory macrophages produce lactate, which can function as a paracrine signal ⁷⁷. The decarboxylation of lactate-derived pyruvate in the Krebs cycle can support ATP provision, the incorporation of glucose into glycogen, and the generation of NADPH and pentoses in the oxidative and non-oxidative branch of the pentose phosphate pathway. In macrophages, recognition of injured or dying cells, such as after myocardial infarcts, leads to increased release of lactate into the extracellular milieu through induction of the solute transporter SLC16A1 ⁷⁷. Correspondingly, cardiomyocytes induce monocarboxylate transporters (MCT) that facilitate lactate uptake during the ischemic period ^78–81. Furthermore, the lactate receptor G-protein-coupled receptor 81 (GPR81) has been shown to inhibit pro-inflammatory cytokine production ⁸², creating a negative feedback loop and preventing extensive macrophage activation. Increased lactate release from inflammatory macrophages supports cardiomyocyte dedifferentiation ^83,84 and regeneration after ischemic injury by supporting NADPH synthesis and gene transcription. Likewise, lactate impairs T-cell proliferation by limiting glucose-derived serine production ⁸⁵. Furthermore, lactate favors regulatory T cells ⁸⁶ through increases in intracellular acidity ⁸⁷ and Treg transcription factor Foxp3 ⁸⁸. Taken together, leukocyte secretion of lactate into the ischemic myocardium milieu may alter the cardiomyocyte response.

The Krebs cycle

The Krebs cycle links metabolic fuels with oxidative phosphorylation in the mitochondria to energy in the form of ATP. The decarboxylation of carbons within the Krebs cycle yields NADH and FADH₂, which transfer electrons to the electron transport chain, supporting oxidative phosphorylation and ATP provision. Glucose-derived pyruvate can be converted to acetyl-CoA and subsequently citrate via condensation with oxaloacetate. Likewise, amino acids are integrated at different steps within the Krebs cycle to replenish the cycle or serve as energy-providing substrates. Disruption of Krebs cycle function via ischemia, nutrient stress, or somatic mutations causes the accumulation of its intermediates, including succinate, α-ketoglutarate, citrate, and its derivative itaconate. The accumulation of succinate is a general feature of ischemic hearts ⁵ and inflammatory macrophages. Succinate can be excreted via membrane transporters of the SLC13 family ⁸⁹ and is recognized by neighboring cells by the G protein-coupled receptor-91 (GPR91). GPR91 activation in cardiomyocytes leads to pathological hypertrophy ⁹⁰. Likewise, inflammation induces the expression of immune-responsive gene 1 (Irg1) in myeloid cells. Irg1 encodes aconitate decarboxylase (ACOD1), which produces the immunomodulatory metabolite itaconate by decarboxylation of cis-aconitate in the Krebs cycle. There is evidence that itaconate exerts anti-inflammatory effects in macrophages by inhibiting succinate dehydrogenase (SDH, complex II of the electron transport chain) ^91,92. Itaconate can be secreted from immune cells, which can agonize neighboring cells by activating the G protein-coupled receptor 2-oxoglutarate receptor 1 (OXGR1). Subsequently, there is increasing evidence for the critical role of OXGR1 in heart ⁹³, suggesting a potential IRG1-itaconate axis between cardiomyocytes and macrophages.

Intriguingly, recent studies demonstrated that during stress, cardiomyocytes release membranous particles, like neural exophers, containing dysfunctional mitochondria. Likewise, others ⁹⁴ have identified a subpopulation of cardiac-resident macrophages, actively scavenging mitochondria ejected from cardiomyocytes. Both groups independently demonstrated that disrupting the elimination of damaged mitochondria causes excessive inflammatory response in cardiac tissue, exacerbating cardiac dysfunction and decreasing survival. The clearance of dysfunctional mitochondria helps to preserve the metabolic state of the myocardium. The accumulation of defective mitochondria can lead to diastolic dysfunction, indicating a potential role for metabolism in coordinating the crosstalk between innate immune cells and cardiomyocytes. During sepsis, resident cardiac macrophages that express the marker TREM2 protect the heart by maintaining cardiomyocyte homeostasis ⁹⁴. As introduced above, TREM2-expressing macrophages scavenge cardiomyocyte-ejected dysfunctional mitochondria (Figure 2). After myocardial infarction, loss of macrophage phagocytic receptors prevents mitochondrial clearance from cardiomyocytes, reducing mitochondrial integrity and accelerating cell death ⁹⁵.

Fatty acid β-oxidation and synthesis

Fatty acid β-oxidation and synthesis are both linked to immune cell functions. While fatty acid synthesis seems to regulate the generation and function of pro-inflammatory immune cells positively, fatty β-oxidation inhibits the activation of innate and adaptive immune systems. The β-oxidation of fatty acids occurs within the mitochondria and peroxisomes, yielding ATP, FADH2, and NADH for biosynthetic pathways. Even-chain and odd-chain fatty acids (up to 22 carbons) undergo β-oxidation in the mitochondria, yielding acetyl-CoA and propionyl-CoA as end products, respectively. Propionyl-CoA can be enzymatically converted to succinyl-CoA and subsequently be integrated into the Krebs cycle. Very-long chain fatty acids (>22 carbons) are oxidized within the peroxisomes. Carnitine may transfer medium-chain fatty acids (6–12 carbons) between the peroxisome and the mitochondria or intermediates, which are used for the biosynthesis of complex lipids. Depending on the length of fatty acid, β-oxidation can yield tremendous amounts of ATP per molecule of fatty acid, making it one of the most efficient fuels for cells. The high energy efficiency of fatty acids has led to the perception that immune cells and cardiomyocytes oxidize fatty acids or glucose. The general view of cardiac metabolism has been especially dominated by the incorrect assumption that the adult heart oxidizes fatty acids. At the same time, glucose oxidation is a sign of pathologic remodeling and fetal heart metabolism. Numerous recent studies have provided evidence for a more nuanced view that the oxidation of fatty acids and glucose occurs alongside each other and is required to sustain biochemical adaptation. Based on these new studies, one should consider losing the capacity to oxidize fatty acids as pathologic and reduce metabolic flexibility.

Fatty acids are precursors for complex lipids, including cholesterol, phospholipids, and triacylglycerols, which are required for cell growth, proliferation, and homeostasis. De novo fatty acid synthesis is linked with intermediary metabolism through glucose-derived citrate, which can be released from the mitochondria into the cytosol. Citrate is converted to oxaloacetate and acetyl-CoA via the ATP-dependent citrate lyase (ACL). The acetyl-CoA derived from ACL is further carboxylated by acetyl-CoA carboxylase 1 (ACC1) to yield malonyl-CoA and subsequently used to synthesize fatty acids and cholesterol through fatty acid synthase (FASN) and HMG-CoA synthase activities, respectively. Fatty acids are either condensed with glucose-derived glycerol to synthesize mono-, di-, and triacylglycerols or linked to a phosphate group to form phosphatidate, a critical precursor for phospholipid synthesis. Cytokines (e.g., TNF) triggers fatty acid synthesis via the sterol-regulatory element binding protein (SREBP), which can alternatively activate macrophages ⁹⁶ and increase the expression of FASN and HMG-CoA synthase. Recent studies indicate that fatty acids are linked innately with adaptative immune cell response, including the Toll-like receptor (TLR)-mediated activation of dendritic cells and the proliferation of T cells and B cells through their antigen receptors ⁹⁷. T cell-specific deletion of ACC1 reduces blasting efficacy and lowers accumulation of antigen-specific CD8⁺ T cells, which is attenuated by exogenous fatty acids ⁹⁸. Oxidative phosphorylation requires the synthesis and integration of structural phospholipids, which are the building blocks for the mitochondrial membrane. Cardiolipin is a unique mitochondrial phospholipid localized and synthesized in the inner mitochondrial membrane. Activating inflammatory macrophage depends on cardiolipin by supporting assembly and integration of SDH (complex II) ^47,99. Depletion of cardiolipin causes a hypo-inflammatory phenotype by increasing complex II disassembly, sequestration, and degradation, which reduces cytokine production and prevents inflammatory metabolic remodeling. Likewise, inborn errors of metabolism affecting cardiolipin synthesis are characterized by left ventricular dysfunction and cardiac structural remodeling ¹⁰⁰. Altered lipid metabolism in cardiomyocytes can also affect the innate immune response. For example, natural reductions in carnitine acetyltransferase during heart failure can promote cholesterol catabolism through bile acid synthesis. The accumulation of bile acid intermediates in cardiomyocytes leads to mitochondrial stress, activation of the inflammasome, and secretion of IL1-β from cardiomyocytes ¹⁰¹, which can contribute to heart failure progression.

Amino acid metabolism

Like fatty acids and glucose, amino acids are important energy-providing substrates and precursors for macromolecules, e.g., proteins. In the heart, amino acids are primarily linked to anabolic reactions, and their contribution to ATP provision is minimal. The most abundant amino acid in the blood is glutamine, which is critical for the induction of IL-1 by inflammatory macrophages through glutamine-derived succinate and α-ketoglutarate ^40,61. Recent studies suggest that the ratio of glutamine-derived α-ketoglutarate to succinate adds a layer of regulation. While α-ketoglutarate supports fatty acid β-oxidation and epigenetic reprogramming of macrophages, accumulation of succinate has been associated with a proinflammatory. ¹⁰² and anti-inflammatory phenotype ¹⁰³. These conflicting reports point towards a complex interaction between intracellular and extracellular pools of succinate. In 1978, Heinrich Taegtmeyer first described the increased production and accumulation of succinate in the heart during hypoxia ⁶. Disruption of the oxidation-reduction balance by α-ketoglutarate dehydrogenase (oxidation) and fumarate hydratase (reduction) causes the tissue accumulation of succinate. Recent studies have recapitulated these initial observations and demonstrated that succinate release is mediated by MCT1 and succinate receptor (SUCNR1) ^5,104. The conflicting role of succinate may be due to experimental conditions. Proinflammatory responses of succinate were demonstrated in ex vivo and in vivo models disrupting mitochondrial function (e.g., LPS, hypoxia). In contrast, anti-inflammatory responses were shown in vitro with dimethyl-variants of succinate. Another challenge is the accurate quantification of succinate. Recent studies have demonstrated that succinate and its derivative succinyl-CoA were highly unstable and require accurate analytical workflows ^105,106. Likewise, T cell responses are regulated by glutamine metabolism, which regulates the balance between effector T cells and T reg cells ⁵⁷. Loss of ASCT2 regulating the uptake of glutamine and leucine impairs the generation and function of T helper cells, whereas Treg cells are unaffected. In these contexts, it is relevant to note that glutamine derivatives are cardioprotective during experimental ischemia-reperfusion injury ¹⁰⁷, however, more studies are needed.

The crosstalk between immune cells and cardiac metabolism has a profound impact on disease pathogenesis and progression. These metabolic vulnerabilities create opportunities for therapeutic intervention and define clinical profiles.

Effect of Cancer-associated Inflammation on Cardiac Metabolism and Function

Inflammation is closely associated with the development and progression of cancer at all stages. Tumors frequently create an immunosuppressive stage through direct interaction within their microenvironment and beyond, which supports cancer cell proliferation, development, and metastasis. Therefore, recent therapeutic strategies aim to activate an acute immune response to promote cancer cell death. Immune checkpoint proteins, including both stimulatory and inhibitory molecules, regulate T lymphocyte activity. The antigen 4 (CTLA4) and programmed cell death 1 (PD1) are the most established T cell immune checkpoint molecules. The approval of immune checkpoint inhibitors (ICI) for various types of cancer-targeting T cell immune checkpoint proteins has exponentially increased in the last 5 years. Over ten antibodies targeting PD-1 (e.g., pembrolizumab, nivolumab)^108–110, three CTLA4 (ipilimumab, tremelimumab, zalifrelimab)¹¹¹, six programmed cell death 1 ligand 1 (PD-L1) (e.g., atezolizumab, avelumab and durvalumab), and one T cell immunoreceptor with Ig and ITIM domains (TIGIT, vibostolimab) are currently approved for cancer-related treatments. Activating stimulatory immune checkpoint proteins enhance T cell activation and promote antitumor functions, including inducible costimulatory (ICOS; vopratelimab)¹¹² and lymphocyte activation gene 3 (LAG-3; relatlimab)¹¹³. The clinical application of ICIs that target CTLA4, PD-1, or its ligand PD-L1 activates the immune system to detect and remove cancer cells. The tumor microenvironment alters the availability of nutrients, which promotes metabolic stress in immune cells and limits their activity. Glycolytic tumors increase the availability of lactate in the tumor microenvironment^114–116. Lactate promotes PD-1 expression and limits IF-γ production in tumor-infiltrating regulatory T cells, promoting an immunosuppressive environment¹¹⁷. In macrophages, lactate promotes polarization and HIF1-α stabilization¹¹⁸, causing epigenetic modifications¹¹⁹ and transcriptional activation of genes, including IL-6 and ARG1. This metabolic competition between cancer cells and immune cells has been shown to drive tumor progression and create metabolic vulnerabilities for therapeutic strategies targeting PD-L1 or CTLA4¹²⁰. A metabolic switch in tumor cells or immune cells commonly affects the utilization of glucose and fatty acids. Recent studies demonstrated that PD-1 prevents effector T cell development by inhibiting glycolytic reprogramming and promoting fatty acid β-oxidation^52,121. Conversely, CTLA4 inhibits glucose uptake, augmenting fatty acid β-oxidation and sustaining naïve T cell populations. This metabolic switch promotes increased lipid remodeling by activating cholesterol and triacylglycerol synthesis. The challenge in harnessing these immune checkpoints is to balance an acute immune response without systemic chronic inflammation, which promotes therapeutic resistance and immune-related adverse events (irAE), including myositis. In the recent decade, ICIs have transformed therapeutic options for patients with skin and solid tumors at any disease stage and significantly improved survival rates. In 2019, Haslam estimated that between 36% to 38% of cancer patients are eligible to receive an ICI medication. A major clinical concern is irAEs, which affect between 70 to 90% of patients receiving ICI medications. The most common irAE is colitis with an associated mortality at 2% to 5% ¹²², while ICI-myocarditis is rare (approximately 0.3 to 1%) yet fatal in 30 to 50% of affected patients ¹²³. ICI-colitis is closely linked to the metabolism of the gut microbiome, and obesity has been identified as a major risk factor. Recent preclinical studies suggest cell-cell interactions and metabolic crosstalk between the gut microbiome and CD4⁺ regulatory T cells drive excess immune responses. Whether these interactions extend beyond the digestive system to the heart and skeletal muscle has yet to be determined. Future studies are needed to address the mechanistic connection between immune checkpoint proteins and the metabolism of immune cells.

Strategies to Interrogate Immunometabolism in Cardiovascular Research.

Readers of this review may have asked themselves how to implement the above-detailed interactions into their studies or, despite their best efforts, transcriptomic analysis, uncovered gene set enrichments in metabolic pathways. These situations frequently leave scientists with the daunting task of probing metabolic changes in their experimental model. This review cannot cover all technical solutions and strategies, but we will attempt to provide a guide that may assist in reducing the sheer endless possibilities of studying metabolism. The most important step when designing a metabolic experiment is to decide the scope of the study and which question needs to be answered: (1) the type of metabolites, (2) the amounts or concentrations of metabolites that may be changed, (3) global or targeted metabolic changes, (4) endpoint or sequential measurements, (5) functional changes within a cell, between cells, tissues or within the whole body. Several different techniques allow the measurement of metabolic changes across scales (Figure 3A). However, investigators need to consider the functional output of each method because some may provide direct analysis of metabolites and flux while others cannot offer such output of metabolism.

Figure 3. Implementation of metabolomics into experimental workflows.

(A) The discovery of metabolic crosstalk between cardiomyocytes and immune cells requires integration of diverse analytical techniques into experimental workflows. (B) Phases for metabolic quantification and discovery include: (1) Experimental design, (2) Metabolite extraction (3) Metabolite detection, and (4) Data analysis and interpretation. Integration of tracer-based labelling into metabolomics workflows depend on the experimental scope (static vs dynamic metabolomics), the type of tracer and how tracers are delivered in the experimental setting. Sample preparation is critical to ensure accurate metabolite quantification and frequently determine which type of metabolomics techniques can be applied. For example, tissue-based metabolite extractions allow various analytical techniques while histological slides limit metabolite detection. Extracted metabolites are subjected to analytical separation using NMR-based, MS-based, or imaging-based technologies. The analysis of metabolomics requires accurate metabolite identification based on the expected m/z and other analytical criteria. For tracing experiments, isotopomer distributions are identified and normalized by naturally occurring isotopes.

Metabolomics

Metabolomics is an integral component of multi-omics analyses and complements transcriptomics and proteomics studies. Mass spectrometry (MS) or nuclear magnetic resonance (NMR) are used to identify and quantify metabolites. The advantages of MS over NMR are higher throughput, sensitivity, analysis speed, and a broader range of applications. Targeted metabolomics can be used when investigators want to quantify a known metabolite or set of metabolites (Figure 3B). Global untargeted metabolomics is a powerful tool for identifying metabolites in a biological sample without prior knowledge of the metabolite type. A limitation of untargeted metabolomics is the chemical diversity within complex biological samples, which limits sensitivity and reproducibility depending on the substrate class. Further, identifying unknown compounds may be limited due to the availability of analytical standards and spectral information in public databases. Another concern is speedy sample collection and preparation are critical to avoid metabolite degradation. For example, several intermediates (e.g., succinyl-CoA) or co-factors (e.g., NADPH) are unstable and degrade within seconds.¹⁰⁵ Newer techniques, such as imaging mass spectrometry, permit measuring the spatial distribution of lipids and protein species from tissue sections. This approach has uncovered spatially correlated lipid and protein changes in the myocardium after cardiac ischemia ¹²⁴.

Metabolic tracing and flux analysis.

Metabolomics provides a snapshot of the metabolite composition from a biological sample. Metabolomics cannot answer how the appearance or disappearance of a metabolite occurred. Additional information on the flux through an enzymatic reaction or network is required to answer this question. Flux analysis encompasses a set of different tools to answer such questions, including tracer-based metabolomics^12,125,126, measurements of enzymatic activities, or computational modeling^127–129 (Figure 3B). The most important tools for flux analysis are tracer-based studies, including stable-isotope tracers of common nutrients or radioactive probes. These techniques can be used in vitro, ex vivo using organ perfusions (e.g., working heart perfusion preparation), or in vivo using catheter-based infusions and imaging. Stable-isotope tracers are combined with targeted metabolomics to quantify the isotopomer distribution of labeled carbon, nitrogen, or hydrogen¹³⁰. Recent ¹³C-glucose-based flux analysis revealed distinct T cell metabolic profiles in vivo¹³⁰ and demonstrated nutrient dependencies shift-based T cell activation phases. Likewise, ¹³C-serine labeling quantified metabolic flux contributions of the mitochondrial one-carbon metabolism and de novo purine biosynthesis in naïve and activated T cells.¹³¹ Another strategy to complement targeted metabolomics is kinetic studies using enzymatic assays. Measurements of enzymes within the glycolysis, pentose phosphate pathway, and Krebs cycle have been used for decades and are well established. However, less established metabolomics pathways may pose a challenge, and assays are limited by throughput, sample quantity, and long tissue extraction times.

Live monitoring of cellular metabolism.

Longitudinal metabolism analysis in cells, whole organs, or animals can be achieved using different techniques depending on the experimental question and available equipment. NMR spectroscopy can measure cellular metabolism and mitochondrial respiration in cell culture and organ model systems (Figure 3B) ^132–134. Most NMR studies apply ³¹P and ¹³C labeled nutrients to quantify metabolic fluxes. In addition to targeted metabolomics, NMR allows the quantification of oxygen consumption to assess mitochondrial respiration and indirectly quantify mitochondrial oxidative phosphorylation. Alternatively, to NMR spectroscopy, fluorescent dyes and oxygen sensors or optical sensors can be used to measure respiration. Although these methods are very cost-efficient and readily implemented in most laboratory settings, none directly measure metabolites or flux changes. In case investigators seek a detailed analysis of metabolic pathways, detailed NMR or MS-based studies are required. The mitochondrial membrane potential can be measured qualitatively and quantitatively using readily available fluorescent probes. This method can help gauge mitochondrial function and, therefore, metabolic capacity. Emerging probes have the potential for measurements in living tissue ¹³⁵. Another way to quantify metabolic respiration and acidification is a Clark Electrode or Seahorse Analyzer. Both instruments quantify oxygen concentration or pH, which provides indirect information about mitochondrial function or nutrient utilization (e.g., glucose and fatty acids). The advantage of Seahorse Analysis is the relatively high throughput and coupling with other assays that allow the measurement of cellular energy substrate metabolism. The Seahorse Analyzer has been widely adopted for in vitro and ex vivo analyses. Though helpful in this context, this approach is not compatible with tissues and so requires isolations of single cells or mitochondria from tissue.

Mass spectrometry imaging for spatial and single-cell quantification.

Immunometabolic alterations affect a heterogeneous set of cells; thus, single-cell analysis has become a stable of metabolic studies. The emerging field of spatial and single-cell metabolomics focuses on how metabolic profiles change between cell states, including alterations in immune cell functions during homeostasis, infection, immunotherapy, as well as metabolic dysregulation in cardiovascular diseases. Technologies using imaging combined with mass spectroscopy^136,137 and sequencing^138,139 have emerged to capture metabolic profiles of cells within a cell population. The sensitivity of the detection method is critical to successfully identify and quantify metabolites or flux changes at the single-cell level. Therefore, MS-based approaches are primarily used for single-cell analysis. These methods are broadly divided into two types: mass spectrometry imaging (MSI)^136,140 and live single-cell MS (Figure 3B). MSI uses matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) or laser ablation electrospray ionization mass spectrometry (LAESI-MS), which allows the mapping of the cellular metabolome in 3D. MSI often requires cell fixation or preservation that potentially interferes with the metabolism. Live single-cell MS combines optical microscopes with MS to overcome this challenge. The content of a single cell is directly fed into the MS via a microcapillary system at a high voltage, inducing nanospray ionization. Metabolites are identified using exact mass or tandem mass spectrometry (MS/MS) analysis, and isomers can be separated by combining live single-cell MS with ion-mobility separation^141,142. MSI can be combined with stable isotope tracer labeling, which allows the mapping of cells within a tissue. In cancer, this technique has revealed distinct metabolic patterns within the tumor environment and surrounding tissue¹⁴⁰. Likewise, recent studies used MSI to study metabolic remodeling during the early phase (<4h) after myocardial infarction and characterize spatial distribution patterns of lipids and intermediary metabolites from tissue sections^124,143. Flow cytometry analysis can be combined with MS using single-cell mass cytometry (CyTOF)¹⁴⁴, which allows measuring 40 to 100 different parameters within a cell. Recent studies combined CyTOF with RNA sequencing to examine the checkpoint protein expression in T lymphocytes in patients with glioblastoma multiforme¹⁴⁵. Spatial metabolomics is an emerging area with significant potential to inform how localized cardiomyocyte metabolism may be altered at the immune interface¹⁴⁶. MSI can profile cells in situ, minimizing metabolite degradation and confounding chemical modifications during the extraction process. Recent single-cell metabolomics and lipidomics MSI approaches have demonstrated comprehensive compound profiles that allow the accurate prediction of cell types^146–148. Computational methods for the analysis and interpretation of these datasets, including deep learning, evolve rapidly alongside MS-based technologies.^147,149 Algorithms such as “CellChat” permit the inference of cell-cell communication and will help predict crosstalk mechanisms at the immune and cardiac interface ¹⁵⁰. The single-cell approach has inferred cardiomyocyte to macrophage intercommunication during metabolic stress ¹⁵¹. Spatial metabolomics is a rapidly emerging field at the intersection of metabolomics, mass spectrometry, imaging, and computational modeling. This technology will advance our understanding of cell-cell interactions and spatial distributions of cell states while creating novel challenges in the analysis and interpretation of the data.

Systems biology approaches to study metabolism.

Systems biology aims to holistically capture processes at every level of a biological system, ranging from genes to proteins and metabolites, as well as cell-cell interactions^128,129,152. Inherently, systems biology approaches do not represent hypothesis-driven or reductionist science; instead, they use inductive strategies to study complex biological systems. These data-driven (or “top-down”) approaches complement hypothesis-driven experimental studies and can be integrated iteratively. Bulk RNA-sequencing and metabolomics data have generated tissue-specific human genome-scale metabolic models, including CardioNet¹⁵³, HepatoNet¹⁵⁴ and Recon2¹⁵⁵. Genome-scale metabolic networks provide gene-protein-metabolite connectivity and enable the integration of multiple layers of information from a biological system and theoretical analysis of intracellular processes using computational simulations. Recent approaches have combined single-cell RNA-sequencing to generate genome-scale metabolic models capturing multiple human cell populations¹²⁷, study metabolic states of T helper 17 cells¹⁵⁶ and the metabolic regulation through cytokines⁶⁹. Combining single-cell RNA sequencing with computational flux balance analysis revealed metabolic adaptation from glycolysis towards fatty acid oxidation and demonstrated the capabilities of mathematical modeling to capture biological profiles. Broad integration of these applications is still limited because of the need for advanced data integration and bioinformatics workflows that may pose a barrier for investigators. However, these methods are promising to enable the characterization of metabolic alterations and cell-cell interactions within heterogenous cell populations during diseases. In addition to multi-omics data, experimental information from tracer labeling can be used to determine metabolic flux alterations in mathematical modeling and predict phenotypes by estimating changes through metabolic or regulatory networks ^{74,115,126,134,157}. A challenge in tracer-based measurements is the limited number of metabolites and isotope transitions. Isotope techniques can identify the state of a steady-state system, but they cannot be used to explain or predict it. Genome-scale metabolic modeling aims to bridge this gap and facilitate predicting metabolic flux rates using mixed integer programming and optimization ⁹. Mathematical optimization of metabolic models tries to answer which metabolic pathways are used and how metabolites are synthesized or utilized through these pathways ^{74,133,134,157}. The integration of multi-omics data from patients holds the promise to (1) characterize the metabolic state of cells at different disease stages, (2) study how dysregulated metabolism drives disease progression, and (3) make predictions on how to limit pathologic remodeling. Applying these methods to human diseases will provide new insights and open new avenues for therapeutic strategies across populations. This includes metabolomics in population-based epidemiology research to identify biomarkers and infer causality.

Conclusion

Immunometabolism is an emerging field at the intersection of different sub-specialties, including immunology and cardiology. Metabolic alterations are heterogeneous and intricately linked to regulating immune cells and cardiomyocytes. The causes of metabolic heterogeneity are multi-factorial and directly influence disease progression and cellular states. It is challenging to decipher metabolic phenotypes in immune cells, predict clinical outcomes, and identify mechanisms driving these alterations. Recent technological advances are providing opportunities to overcome these challenges and design translational studies that encompass every level of the cellular system. A critical step in advancing both fields forward is the implementation of appropriate model systems and define experimentally traceable metabolite profiles for translation into human studies. To achieve these goals, a combination of techniques is needed, including the application of computational approaches to support the analysis of high-dimensional datasets and to complement hypothesis-driven studies with inductive research. While the underlying cellular crosstalk between the immune system and cardiac cells remains poorly understood, the evidence for the contribution of inflammation to cardiac disease is growing and warrants further investigation. The interplay between the immune system and cardiac function stands to be a target area for strategies that seek to ameliorate cardiac disease.

Abbreviations

IGF

Insulin Growth Factor

IGF-R

IGF Receptor

IFN

Interferon

IFN-R

IFN Receptor

MCT

Monocarboxylate Transporter

Mϕ

Macrophage

OXPHOS

Oxidative Phosphorylation

MERTK

Myeloid-Epithelial-Reproductive Tyrosine Kinase

PM

Plasma Membrane

PMN

Polymorphnuclear neutrophil

SUC

Succinate

TNF

Tumor Necrosis Factor