Nothing Special   »   [go: up one dir, main page]
Next Article in Journal
Multi-Omics Approaches Uncovered Critical mRNA–miRNA–lncRNA Networks Regulating Multiple Birth Traits in Goat Ovaries
Previous Article in Journal
Remodeling of the Intracardiac Ganglia During the Development of Cardiovascular Autonomic Dysfunction in Type 2 Diabetes: Molecular Mechanisms and Therapeutics
Previous Article in Special Issue
Gla Rich Protein (GRP) Mediates Vascular Smooth Muscle Cell (VSMC) Osteogenic Differentiation, Extracellular Vesicle (EV) Calcification Propensity, and Immunomodulatory Properties
You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJMS
Volume 25
Issue 22
10.3390/ijms252212465
ijms-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

The Gut–Heart Axis: Molecular Perspectives and Implications for Myocardial Infarction

by
Katherine Rivera
1,2,3,
Leticia Gonzalez
2,3,
Liena Bravo
2,3,
Laura Manjarres
2,3 and
Marcelo E. Andia
2,3,*
1
Doctoral Program in Medical Sciences, Faculty of Medicine, Pontificia Universidad Católica de Chile, Santiago de Chile 8331010, Chile
2
Biomedical Imaging Center, School of Medicine, Pontificia Universidad Católica de Chile, Santiago de Chile 7820436, Chile
3
Millennium Institute for Intelligent Healthcare Engineering iHEALTH, Santiago de Chile 7820436, Chile
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2024, 25(22), 12465; https://doi.org/10.3390/ijms252212465
Submission received: 31 October 2024 / Revised: 15 November 2024 / Accepted: 19 November 2024 / Published: 20 November 2024
(This article belongs to the Special Issue Molecular Advances and Insights on Diagnosis, Prevention and Therapeutics of Cardiovascular Diseases)
Browse Figures
Figure 1
<p>Host–microorganism interface. (<b>A</b>) Schematic representation of the main components of the intestinal barrier. (<b>B</b>) Junctional complexes linking adjacent epithelial cells in normal and impaired intestinal barrier.</p> "> Figure 2
<p>Complexity of the gut microbiota and its adaptation to different microenvironments in the lower GI tract. Four major bacterial phyla (Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria) are found in different sections of the GI tract. Oxygen levels decrease progressively from the stomach to the colon, reflecting a shift from an aerobic to an anaerobic environment. Population density and mucus thickness both increase from the stomach to the colon, corresponding with higher microbial diversity and density in the large intestine, while pH decreases along the tract, providing favorable conditions for specific bacterial communities in different regions.</p> "> Figure 3
<p>Risk factors in the gut–heart axis in health and disease. In a healthy state (eubiosis), factors like exercise and a fiber- and antioxidant-rich diets support beneficial gut bacteria, boosting SCFA production and limiting harmful compounds like TMA and LPS. Conversely, risk factors such as a Western diet, aging, antibiotics, and pollution lead to gut dysbiosis, where pathogenic bacteria increase inflammatory mediators, impair gut integrity, and raise systemic inflammation and MI risk.</p> ">
Versions Notes

Abstract

:
Myocardial infarction (MI) remains the leading cause of death globally, imposing a significant burden on healthcare systems and patients. The gut–heart axis, a bidirectional network connecting gut health to cardiovascular outcomes, has recently emerged as a critical factor in MI pathophysiology. Disruptions in this axis, including gut dysbiosis and compromised intestinal barrier integrity, lead to systemic inflammation driven by gut-derived metabolites like lipopolysaccharides (LPSs) and trimethylamine N-oxide (TMAO), both of which exacerbate MI progression. In contrast, metabolites such as short-chain fatty acids (SCFAs) from a balanced microbiota exhibit protective effects against cardiac damage. This review examines the molecular mediators of the gut–heart axis, considering the role of factors like sex-specific hormones, aging, diet, physical activity, and alcohol consumption on gut health and MI outcomes. Additionally, we highlight therapeutic approaches, including dietary interventions, personalized probiotics, and exercise regimens. Addressing the gut–heart axis holds promise for reducing MI risk and improving recovery, positioning it as a novel target in cardiovascular therapy.

1. Introduction

Myocardial infarction (MI), commonly known as heart attack, is the leading cause of death worldwide, significantly contributing to both morbidity and healthcare costs [1]. MI typically results from a completely or partially obstructed coronary blood flow, leading to ischemia and myocardial damage that can culminate in heart failure (HF) and increased mortality among survivors [2,3]. Despite advancements in diagnostic techniques, pharmacological therapies, and surgical interventions, the prevalence and mortality of MI continue to rise, underscoring the need for novel therapeutic approaches that address underlying and exacerbating mechanisms [4].
Traditionally, MI pathophysiology has focused on coronary artery disease (CAD) and its established traditional cardiac risk factors, such as dyslipidemia, hypertension, smoking, diabetes mellitus, and obesity [5]. However, emerging research has highlighted the gut–heart axis as a significant contributor to cardiovascular outcomes, challenging the traditional view of the gut as an isolated organ system [6,7]. This axis represents a dynamic, bidirectional network in which gut health, specifically through intestinal barrier integrity and gut microbiota homeostasis, plays a pivotal role in maintaining immune and metabolic balance in the host [8,9,10]. Given these findings, the gut–heart axis is increasingly recognized as a central component of cardiovascular health, linking extrinsic factors such as diet, exercise, age, and sex hormones to MI outcomes. This review comprehensively analyzes the molecular mediators and signaling pathways that constitute the gut–heart axis. By examining how integrity of the gut barrier, microbiota composition, and systemic inflammation influence MI, we highlight innovative therapeutic strategies that target this axis, such as dietary interventions, probiotics, and exercise, to mitigate the risk of MI and improve recovery outcomes. These insights advance our understanding of the gut–heart axis as a promising target in cardiovascular therapeutics.

2. The Gut–Heart Axis: A Molecular Perspective

2.1. Intestinal Barrier Integrity and MI: Mechanistic Insights

The intestinal barrier serves as a critical interface between the external environment and the internal systems of the body, maintaining physiological homeostasis by selectively absorbing nutrients while blocking harmful antigens and microorganisms from entering the systemic circulation (Figure 1) [11]. Structurally, the intestinal barrier consists of several layers that comprise chemical, immunological, physical, and microbial components, which together regulate its structural integrity and metabolic activity (Figure 1A). The mucus secreted by goblet cells forms the chemical shield rich in antimicrobial peptides and immunoglobulin A (IgA), which allows the growth of commensal bacteria, limiting pathogenic bacteria proliferation and enhancing immunological defense [12]. The physical barrier of the gut is formed by a single layer of enterocytes connected by tight junction proteins (e.g., claudins, occluding, zonula occludens (ZOs), and the junctional adhesion molecule (JAM)), along with adherent junctions and desmosomes (Figure 1B). Together, these structures are essential for maintaining gut integrity by regulating paracellular permeability, thereby preventing luminal antigens from entering the underlying tissue and triggering chronic inflammation [13,14].
Disruptions in the components of the gut barrier are associated with various intestinal and systemic diseases [13,15,16,17,18]. In particular, intestinal dysfunction has been closely linked to cardiovascular diseases (CVDs), with intestinal-related conditions increasing the risk of atherosclerosis, CAD, stroke, HE, and atrial fibrillation [19]. Several studies have established a connection between MI and intestinal barrier disruptions (Table 1).
For example, elevated serum levels of ZO, a critical tight junction protein responsible for maintaining intestinal barrier integrity, have been observed in MI patients and positively correlate with systemic inflammation markers such as IL-10 [20,21,22,23]. Additionally, intestinal fatty acid-binding protein (I-FABP), a marker of gut mucosal injury, has recently been linked to larger infarct sizes and poorer cardiac function in acute MI [24]. This highlights its value as a biomarker for MI severity and enables early identification of patients at higher risk of complications [24]. Another significant marker of compromised gut integrity is serum lipopolysaccharide (LPS), a bacterial-derived endotoxin significantly elevated in ST-elevation MI (STEMI) patients, which positively correlates with systemic inflammation, worsened cardiac damage, and larger post-MI infarct sizes [20,21,22,23,25,26]. Also, elevated serum LPS levels were significantly correlated with serum ZO and blood bacterial load, raising the possibility that intestinal bacteria might invade the blood post-MI as a consequence of enhanced gut permeability [21,23]. Furthermore, elevated levels of LPS are associated with both short- and long-term risk of cardiovascular events in patients with community-acquired pneumonia, suggesting that ZO could serve as a useful biomarker for identifying individuals at greater risk of adverse ischemic outcomes [27]. LPS typically translocates from the gut lumen into circulation when intestinal barrier integrity is compromised, leading to the activation of toll-like receptor 4 (TLR4) on immune cells [21,25]. This activation triggers a pro-inflammatory cascade, resulting in cytokine release that can exacerbate myocardial damage and impair recovery post-MI. Supporting this connection, immunohistochemical analysis of coronary thrombi in MI patients has revealed the presence of LPS within the thrombus, along with the overexpression of TLR4 and cathepsin G in leukocytes, which promotes leukocyte–platelet binding and activation [21,28]. These findings suggest a mechanistic link between gut-derived endotoxins and thrombotic processes in MI. Notably, injections of E. coli-LPS in mice, which archived LPS levels similar to those found in human coronary thrombi, were associated with increased arterial thrombosis and platelet activation [21]. This evidence indicates that LPS not only drives systemic inflammation but also promotes thrombogenesis in MI, as gut-derived LPS exacerbates MI severity by fostering pro-thrombotic conditions and intensifying inflammation within coronary vessels. Furthermore, circulating D-lactate—a byproduct of bacterial metabolism—is elevated in MI patients, correlating with systemic inflammation and an increased risk of post-MI HF, underscoring the critical role of gut barrier dysfunction in MI progression [26]. Experimental models further support these findings, demonstrating that disrupted gut integrity and microbial metabolites exacerbate inflammation, oxidative stress, and MI severity [21,23,26,29,30]. Emerging therapeutic strategies are now focusing on restoring gut barrier integrity, particularly by targeting pathways such as TLR4-mediated signaling. TLR4 inhibitors are currently under investigation for their potential to reduce LPS-induced inflammation and protect myocardial tissue after MI [21,31,32]. Preserving gut barrier function shows significant promise as a therapeutic approach in MI, although it remains unclear whether vascular or intestinal dysfunction is the primary trigger in this complex process [33].

2.2. Gut Microbiota Composition and MI

The gut microbiota is a complex ecosystem of trillions of symbiotic microorganisms, including bacteria, archaea, viruses, and fungi, which have coevolved with humans to support essential physiological functions [34]. Comprising approximately 70% of the body’s microbial cells, this community plays a key role in digestion, nutrient absorption, vitamin synthesis, and maintaining intestinal barrier integrity. It also produces crucial metabolites, such as short-chain fatty acids (SCFAs), which are vital for health [35,36]. The gut microbiota is predominantly made up of the bacterial phyla Firmicutes and Bacteroidetes, with significant diversity in composition and distribution throughout the gastrointestinal (GI) tract, particularly in the densely populated cecum and colon (see Figure 2) [37,38,39].
Due to this complexity, researchers often use fecal samples as a proxy to estimate gut microbiota composition [40]. Emerging research demonstrates that gut microbiota composition plays a significant role in cardiovascular health. Dysbiosis—characterized by a reduction in beneficial microbial species and an overgrowth of pathogenic bacteria—has been increasingly linked to intestinal and extra-intestinal conditions, including obesity, diabetes, and CVD [41,42,43]. Evidence suggest that gut microbiota significantly influences the severity and outcomes of MI by affecting systemic inflammation, immune modulation, and metabolic pathways. Disbiotic shifts can promote disease progression through mechanisms such as microbial translocation, altered production of gut-derived metabolites, and increased leakage of metabolic waste, thereby activating systemic inflammation. Advanced sequencing techniques, such as 16S rRNA and metagenomic analysis, have enabled a precise mapping of microbiota diversity and its impact on MI outcomes [44,45]. For instance, MI patients often show reduced levels of beneficial Firmicutes species and increased levels of pro-inflammatory bacteria like Bacteroidetes and Verrucomicrobia [46,47]. This imbalance leads to elevated levels of pro-inflammatory metabolites, exacerbating myocardial injury [26,46,48]. Additionally, gut microbiota has been implicated in modulating neutrophil extracellular trap (NET) formation, shedding light on mechanisms of ischemia/reperfusion (I/R) injury in MI [23,49]. Specific bacterial species have also been linked to MI severity; for example, increased levels of Streptococcus salivarius and Klebsiella pneumonia are associated with more severe MI, while Roseburia hominis, an SCFA producer, is inversely related to MI severity [50]. These findings underscore the potential of targeting gut microbiota for novel therapeutic strategies to mitigate MI risk and improve patient outcomes.
Metagenomic studies reveal significant microbial translocation into the systemic circulation following STEMI, which amplifies inflammation and increases the risk of subsequent cardiovascular events [26]. Pathogens like Enterobacteriaceae and Escherichia coli contribute to this process by releasing LPS and other factors that activate harmful immune responses in cardiac tissue [26,46,48]. Additionally, blood microbiota composition post-MI is influenced by low-density lipoprotein (LDL) levels, with elevated LDL promoting increased microbial diversity and inflammation [51]. Experimental models further support these findings. Suppressing gut microbiota in MI models reduced monocyte infiltration in the peri-infarct region, decreased ventricular rupture, and lowered mortality rates. Conversely, fecal microbiota transplantation from healthy donors minimizes infarct size and improved survival outcomes [30,52,53]. Interestingly, recent studies indicate that the role of the gut microbiota in MI pathogenesis may differ between diabetic and non-diabetic individuals due to variations in host metabolic states and microbial composition [54,55]. Diabetic MI patients typically exhibit an increased abundance of Firmicutes and a reduction in Bacteroidetes, alterations linked to systemic inflammation and metabolic dysregulation, which may contribute to a poorer prognosis. In contrast, non-diabetic MI patients show higher levels of beneficial bacteria, potentially explaining their relatively better cardiac outcomes following MI. These findings underscore a complex relationship between gut dysbiosis and MI, suggesting that targeted therapies focusing on the gut–heart axis could enhance MI recovery and reduce post-infarction complications. By understanding the differential impact of gut microbiota on MI progression in diabetic versus non-diabetic patients, future research can better tailor interventions to optimize cardiovascular outcomes in these distinct patient groups.

2.3. Molecular Pathways Linking Gut-Derived Metabolites to MI

The gut microbiota converts dietary nutrients into bioactive metabolites that significantly influence host physiology [10]. The balance between harmful and beneficial metabolites can greatly impact MI outcomes. One such metabolite is trimethylamine (TMA), which is produced by intestinal bacteria from dietary sources like choline, betaine, and L-carnitine. TMA is subsequently oxidized in the liver to form trimethylamine-N-oxide (TMAO), which has been consistently linked to an increased risk of adverse cardiovascular outcomes, including MI and mortality [56,57]. As such, TMAO is emerging as a potential biomarker for assessing cardiovascular risk and guiding therapeutic interventions. Studies have shown that elevated TMAO levels can predict a heightened risk of major adverse cardiovascular events, even after adjustment for traditional risk factors [58]. Furthermore, high circulating TMAO levels are associated with a poorer prognosis post-MI, correlating with an increased risk of death and recurrent infarctions during follow-up periods [59,60,61,62,63,64,65,66]. While the precise mechanisms by which TMAO increases MI risk are not yet fully elucidated, current evidence suggests that TMAO induces alterations in cholesterol metabolism, promotes inflammation, oxidative stress, and endothelial dysfunction—all key factors in vascular dysfunction [67,68,69,70,71,72]. Additionally, TMAO contributes to plaque instability and rupture, enhancing platelet aggregation and thereby increasing the risk of thrombosis, a critical factor in MI [73,74,75,76]. Emerging evidence also indicates that TMAO promotes myocardial hypertrophy, exacerbates myocardial interstitial and perivascular fibrosis, and impairs cardiac compliance and function, collectively hindering post-MI recovery [29,64,77,78,79,80]. These findings underscore the critical role of TMAO in worsening cardiovascular outcomes, suggesting that interventions targeting TMAO pathways may improve MI prognosis.
On the other hand, SCFAs such as butyrate, acetate, malonate, succinate, and propionate are produced by anaerobic bacteria through the fermentation of dietary fiber [81,82]. Unlike TMAO, SCFAs generally exhibit cardioprotective effects that positively influence MI outcomes. Several studies have shown that reduced SCFA levels impair immune response and increase mortality after MI, suggesting a protective role for SCFA in cardiac health [53,83,84,85,86]. Butyrate and propionate, in particular, have been shown to reduce apoptosis and enhance cell survival in experimental models, potentially preventing MI [87]. Butyrate also mitigates myocardial fibrosis by regulating macrophages M1/M2 polarization and promoting mitochondrial function recovery [88,89,90]. Propionate has been shown to lower the risk of MI-induced ventricular arrhythmias and improve cardiac electrophysiology stability, partially through parasympathetic activation [91]. Similarly, dietary interventions that enhance SCFA production emphasize their potential as therapeutic targets to reduce ischemic injury and systemic inflammation [92,93]. However, recent evidence suggests that the cardioprotective effects of SCFAs are context-dependent, influenced by specific G-protein-coupled receptors they activate [94]. For instance, SCFAs activate free fatty acid receptor 2 (FFAR2) to trigger anti-inflammatory pathways, whereas activation of FFAR3 may stimulate sympathetic nervous activity and adrenal catecholamine release. This activation can increase heart rate, blood pressure, and pro-inflammatory cytokine levels, potentially exacerbating cardiac stress [95,96,97,98]. Thus, optimizing therapeutic strategies using SCFAs requires careful consideration of their receptor-specific actions to maximize their benefits.
Beyond TMAO and SCFAs, other gut-derived metabolites, such as bile acids (BAs) and indole derivatives, play significant roles in cardiovascular health. Bile acids, which are modified by gut microbiota, influence lipid metabolism and systemic inflammation through receptors like FXR and TGR5. These pathways are strongly associated with the presence and severity of CAD, particularly in MI patients; however, the precise molecular mechanism remain controversial [99,100]. Also, indole derivatives, produced from microbial metabolism of tryptophan, exert anti-inflammatory effects by activating the aryl hydrocarbon receptor (AhR), thereby reducing endothelial dysfunction and vascular inflammation [101,102,103]. These pathways highlight additional therapeutic targets, suggesting that a broader range of gut-derived metabolites could be leveraged to mitigate MI risk.

3. Influence of Sex, Age, and Lifestyle Factors on the Gut–Heart Axis

The gut–heart axis is influenced by various host factors, with sex, age, and lifestyle playing pivotal roles in modulating gut microbiota composition and function. These factors not only affect microbiota diversity but also influence metabolite production, immune response, and inflammatory pathways, all of which are crucial for MI risk and recovery (Figure 3).

3.1. Sex-Related Differences

Health and disease susceptibility, including CVD, are influenced by sex chromosomes and hormone-driven physiological differences. Modifiable CVD risk factors—such as smoking, obesity, diabetes, and socioeconomic status—tend to have a stronger impact on women, who generally develop CVD later in life than men but experience more comorbidities and poorer outcomes after MI [104,105,106,107]. Diagnostic biomarkers, like cardiac troponin, also show lower sensitivity in women, highlighting the need for sex-specific cut-off values in clinical practice [108]. The increased CVD risk in postmenopausal women, driven by reduced estrogen levels, has led to studies demonstrating that hormone replacement can thereby reduce CVD risk, emphasizing the modulating effects of sex hormones throughout life [109,110,111]. Recent research shows that these hormonal effects extend to gut microbiota composition, potentially influencing MI risk. Animal studies indicate that gut microbiota profiles vary significantly by sex, with interventions like gonadectomy shifting microbiota composition towards profiles typically observed in the opposite sex [112,113]. In male mice, certain bacteria species are more prevalent, with sex accounting for 11.6% of microbiota variance [114]. In humans, women generally have lower levels of the Bacteroidetes phylum, while castration in male mice shifts their microbiota profiles to resemble those of females, a change reversible with testosterone supplementation [112,115,116]. Fecal transplantation and hormone studies further demonstrate sex-related microbiota differences [117,118,119,120]. Sex-specific differences in gut-derived metabolites also influence MI outcomes. For instance, MI patients initially have higher circulating TMAO levels in women than men, with levels normalizing through dietary changes and exercise during cardiac rehabilitation [121]. Moreover, distinct metabolomic profiles, such as elevated histidine and O-acetyl-glycoprotein (OAG) in men and succinate in women, underscore the importance of sex-specific biomarkers for improving MI risk stratification and treatment [122].

3.2. Age-Related Changes

The incidence of CVD increases significantly with age, primarily due to prolonged exposure to risk factors and cumulative physiological changes [123,124]. Early management of these risk factors can yield substantial benefits; for example, a 10% reduction in cholesterol levels in younger adults can decrease ischemic heart disease risk by up to 54%, compared to only 27% in older adults [125,126]. The incidence of MI also escalates with age, doubling in men and increasing fivefold in women between ages 55–64 and 85–94 [127]. Mortality rates post-MI are particularly high in elderly patients, partly due to delayed diagnosis from atypical symptoms and increased procedural complications [128,129]. Aging also significantly impacts gut microbiota composition, which in turn influences cardiovascular health [130]. Early-life factors like birth type and feeding shape microbiota profiles, while diet and lifestyle drive composition in adulthood [131]. Generally, Bacteroidetes are more prevalent in childhood but decline with age, whereas Firmicutes increase [132]. In the elderly, Bacteroidetes levels rise, while beneficial anaerobes like Bifidobacterium decrease, and pathogenic groups such as Enterobacteria increase, contributing to chronic low-grade inflammation, a key factor in age-related conditions, including CVD [133,134,135]. Animal studies support these findings, showing that transferring microbiota from aged donors to younger, germ-free recipients induces inflammation, activating inflammatory pathways like TLR2 [135]. Aging is also associated with elevated plasma levels of TMAO, which correlate with adverse cardiovascular outcomes [136,137]. Higher TMAO levels in older adults result from a greater abundance of TMA-producing bacteria and are linked to markers of vascular aging, such as increased carotid intima–media thickness [122,138]. Additionally, elevated levels of TMAO and related metabolites (e.g., choline and carnitine) have been linked to higher mortality from both CVD and non-CVD causes in individuals over 65 [139]. These findings highlight the need for age-specific CVD treatment strategies. Approaches targeting TMAO reduction, gut microbiota modulation, and anti-inflammatory therapies may help mitigate age-related cardiovascular risks and improve outcomes in older adults.

3.3. Lifestyle Factors

3.3.1. Unhealthy Diet

Poor diets, often high in refined grains, added sugars, salt, unhealthy fats, and animal-source foods, but low in whole grains, fruits, vegetables, legumes, fish, and nuts, are a major risk factor for CVD and contribute substantially to the global burden of non-communicable diseases [140,141]. Western diets, characterized by high saturated fats, refined carbohydrates, and processed foods, are closely linked to increased severity of coronary artery lesions and elevated risk of MI and stroke [142,143]. For example, frequent consumption of fried food is associated with a 28% increase in the risk of major cardiovascular events, partly because saturated and trans fats elevate cholesterol levels, promoting atherosclerosis and increasing MI risk [144,145,146]. Importantly, diets significantly affect gut microbiota, with dietary patterns accounting for 57% of microbiota variation, compared to just 12% from genetics [147]. High-fat diets, for instance, disrupt gut barrier integrity and promote endotoxemia by reducing protective bacteria [148]. A Western diet often leads to gut dysbiosis, marked by a decrease in beneficial Bacteroidetes and an increase in Firmicutes, which is linked to obesity and metabolic disturbances [149,150]. This imbalance reduces SCFA production and increases gut permeability, allowing endotoxins into circulation and promoting inflammation that drives atherosclerosis and MI [149,151]. Beyond saturated fats and refined carbs, other dietary patterns also influence MI risk and gut microbiota. High-salt diets are linked to hypertension, a major CVD risk factor, and reduced levels of beneficial Lactobacillus species, while low-fiber and polyphenol-poor diets fail to support SCFA-producing bacteria essential for gut health and inflammation control [152,153,154]. Diets rich in animal-based protein, especially red and processed meats, increase harmful metabolites like TMAO [155]. Ultra-processed foods, with additives, artificial sweeteners, and emulsifiers, damage the gut’s mucus layer, increase permeability, and promote endotoxemia, contributing to atherosclerosis and heightened MI risk [156]. High-fructose diets, commonly from sugary beverages and sweets, disrupt the gut microbiota, favoring pro-inflammatory bacteria [157]. High glycemic diets also increase CVD risk by causing oxidative stress, LDL oxidation, inflammation, protein glycation, and procoagulant activity [143,158]. These findings highlight the importance of reducing refined and processed foods and increasing fiber- and polyphenol-rich foods to support a heart-healthy gut microbiota and reduce MI risk.

3.3.2. Sedentarism and Physical Inactivity

Physical inactivity comprises two independent but interrelated behaviors: insufficient moderate-to-vigorous physical activity and prolonged sedentary behavior. Epidemiological studies indicate that sedentary behavior is a significant predictor of CVD risk and a major contributor to the overall CVD burden [159]. Specifically, high sedentary time (>4 h/day) and physical inactivity are notably associated with all-cause mortality among MI survivors [160,161]. Sedentary lifestyles are also linked to alterations, including reduced microbial diversity and shifts in metabolic activity, resulting in lower network complexity than observed in active individuals [162,163,164,165,166]. In particular, sedentary behavior is associated with reduced levels of Ruminococcaceae, a butyrate-producing bacterial family, and increased levels of Streptococcus spp., especially in older adults [167]. This imbalance suggests a diminished capacity for butyrate production, a metabolite crucial for maintaining intestinal barrier integrity and anti-inflammatory effects. Further evidence from a hypoactivity model, such as dry immersion, demonstrated that certain bacteria and metabolites, including propionate, are sensitive to reduced physical inactivity, potentially impacting health during prolonged sedentary lifestyles [168]. Additionally, studies on sedentary women revealed higher abundances of bacteria linked to inflammatory profiles and adverse metabolic outcomes [169]. Recent research indicates that sedentary behavior and physical activity influence similar gut microbiota species in opposite directions; for instance, a sedentary lifestyle correlates with reduced carbohydrate-degrading capacity in the microbiota, particularly from dietary fibers, while physical activity supports a microbiome that fosters metabolic health [170,171]. These effects can be explained by both physiological and lifestyle factors. Physical inactivity may slow gut motility and reduce blood flow, creating a less favorable environment for diverse gut bacteria [172]. However, sedentary lifestyles often include unhealthy habits—like low fiber intake and high processed food consumption—that independently affect gut microbiota, making sedentarism a possible confounding variable. Clarifying these overlapping factors in research could help determine if inactivity alone changes the gut microbiome or if these changes are mostly due to associated behaviors. By targeting gut microbiota changes associated with sedentary behavior, interventions promoting physical activity could mitigate CVD risk and support overall cardiovascular health.

3.3.3. Alcohol Consumption

Alcohol consumption is a known risk factor for multiple diseases, including CVD, but its relationship with MI risk varies based on drinking patterns and quantity [173,174]. For years, studies have suggested an association between moderate alcohol intake, particularly red wine, and improved heart health; however, recent evidence indicates that even a low level of alcohol consumption increases heart disease risk [175,176]. Episodes of heavy drinking, meanwhile, are strongly linked to an increased risk of MI, especially in older adults [177]. This elevated risk among heavy drinkers may be related to a pro-thrombotic state that arises during alcohol withdrawal phases, increasing the likelihood of ischemic events [178]. Beyond its cardiovascular effects, alcohol impacts the GI tract in ways that may exacerbate MI risk. Ethanol weakens the protective intestinal mucus layer, increasing gut permeability and promoting the overgrowth of Gram-negative bacteria that release inflammatory endotoxins, such as LPS [179,180,181]. This inflammation-induced vascular injury highlights the direct pathway by which alcohol-related gut dysbiosis and increased endotoxemia contribute to MI risk. Chronic alcohol use has also been shown to reduce gut microbiota diversity and promote dysbiosis, particularly in individuals with alcohol-associated liver disease or alcohol use disorder (AUD) [182,183]. Specifically, studies report an increase in Proteobacteria, a marker of gut dysbiosis, and a decrease in beneficial anaerobes like Bacteroidetes among heavy drinkers [181]. For patients with AUD, reducing alcohol intake and implementing microbiota-targeted therapies, such as probiotics, may help to rebalance gut health and reduce inflammation. These findings underscore the need for a nuanced approach to alcohol consumption, recognizing both the risks of heavy drinking and the emerging evidence that any alcohol consumption may increase cardiovascular risk.

4. Therapeutic Frontiers Targeting Gut Microbiota to MI Management

The gut–heart axis offers promising avenues for MI management, with dietary interventions, personalized probiotics, and exercise regimens emerging as key strategies to modulate gut microbiota and reduce cardiovascular risk. Table 2 provides a comprehensive summary of therapeutic strategies targeting the gut–heart axis, including specific mechanisms, evidence of benefits, population types studied, and key references for further reading.

4.1. Dietary Interventions

Dietary habits are the most important element in influencing both MI risk and gut microbiota composition. A meta-analysis of randomized controlled trials indicated that reducing dietary saturated fats leads to a 21% reduction in cardiovascular events [184]. Similarly, replacing saturated fatty acids with n-6 polyunsaturated fatty acids (PUFAs) has been associated with a 6% reduction in mortality in a prospective cohort followed over 16 years [185]. Rather than focusing on isolated components, improving overall dietary patterns appears to be a key driver in reducing all-cause and cardiovascular mortality post-MI [186].

4.1.1. Mediterranean Diet (MD)

The Mediterranean diet (MD), characterized by a high intake of olive oil, fruits, nuts, vegetables, and whole grains, as well as a moderate intake of animal proteins and sugars, has shown substantial cardiovascular benefits [186,187]. High adherence to MD has been linked to lower all-cause mortality and a reduction in major cardiovascular events, including MI, stroke, and CVD mortality, in both primary and secondary prevention settings [188]. Compared to low-fat diets, MD has been associated with better outcomes in secondary prevention, likely due to its impact on various CVD risk factors, such as blood pressure, plasma cholesterol, arterial stiffness, and plaque stability [189,190,191,192,193,194,195]. The benefits of MD also extend to gut microbiota composition. Studies show that MD increases Bacteroidetes and decreases Firmicutes, lowering the Firmicutes/Bacteroidetes ratio, which is often linked to better metabolic outcomes [150,196]. MD has also been associated with an increase in SCFA-producing bacteria, which contribute anti-inflammatory properties and improve host metabolism [197,198,199]. Additionally, MD and other plant-based diets have been shown to lower levels of TMAO [200,201].
Table 2. Therapeutic approaches targeting gut microbiota for MI management.
Table 2. Therapeutic approaches targeting gut microbiota for MI management.
Therapeutic ApproachDescriptionMechanismEvidence of Cardiovascular BenefitReferences
Mediterranean DietHigh intake of olive oil, fruits, vegetables, nuts, and moderate animal proteinIncreases SCFA-producing bacteria and lowers TMAO levelsLowers MI risk and improves cardiovascular outcomes[150,186,187,189,190,191,192,193,194,195,196,200,201]
Dietary FiberRich in fruits, vegetables, and whole grainsSupports SCFA production and strengthens gut barrier integrityReduces systemic inflammation, endotoxemia, and MI risk[26,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216]
Antioxidants and PolyphenolsFound in foods like berries, tea, and olive oilAct as prebiotics and promote beneficial bacteriaDecrease oxidative stress, support endothelial function, and lower MI risk[145,217,218,219,220,221,222,223,224,225,226,227,228]
Personalized ProbioticsAdministration of specific beneficial bacteria strainsModulate gut microbiota and reduce inflammationReduce MI size and improve cardiac function in animal models[229,230,231,232,233,234,235,236]
Physical ActivityRegular moderate-to-vigorous exerciseEnhances gut microbiota diversity and reduces inflammationAssociated with reduced CVD and all-cause mortality[162,166,237,238,239,240,241,242,243,244,245,246,247,248]

4.1.2. Fiber Intake

Dietary fiber intake is strongly associated with improved cardiovascular health and a reduced risk of MI [202,203,204,205,206,207]. Fiber, primarily found in fruits, vegetables, whole grains, and legumes, plays a critical role in supporting a healthy gut microbiota. Studies show that fiber intake promotes shifts in gut microbiome composition, increasing the abundance of beneficial bacteria like Faecalibacterium prausnitzii, Bifidobacterium, and Lactobacillus, while lowering the Firmicutes/Bacteroidetes ratio, a marker often associated with metabolic health improvements [208]. Fiber serves as a substrate for beneficial gut bacteria, especially those that produce SCFAs, for maintaining intestinal barrier integrity, as they strengthen tight junctions between epithelial cells, reduce gut permeability, and protect against the translocation of endotoxins to the bloodstream [209]. These effects can significantly impact systemic inflammation, lipid metabolism, and vascular health, which are all critical factors in MI risk [210,211]. In particular, butyrate and propionate produced by commensal bacteria such as Lactobacillus and Bifidobacterium have been shown to reduce inflammation and strengthen the gut barrier. This offers protective effects against cardiac damage by inhibiting immune cell activation and reducing systemic inflammatory markers, including IL-6, TNF-alpha-R2, and C-reactive protein (CRP) [212,213]. High-fiber diets have also been seen to decrease endotoxemia by fostering a microbiota composition that discourages the growth of LPS-producing bacteria [249]. Moreover, dietary fiber supplementation is linked to reduced activation of macrophages and dendritic cells, and it enhances the suppressive function of T-regulatory cells, thereby reducing metabolic endotoxemia and inflammatory responses [214,215]. In animal studies, high-fiber diets have been shown to reduce infarct size and improve cardiac function post-MI, likely due to the protective role of SCFAs on cardiomyocytes and their immune-modulating effects [26,209,216]. These findings underscore the importance of dietary fiber as a cornerstone of dietary interventions aimed at reducing MI risk and supporting overall cardiovascular health.

4.1.3. Antioxidants and Polyphenols

The role of dietary antioxidants and polyphenols in cardiovascular health, particularly for managing MI, has gained significant attention. These compounds, abundant in fruits, vegetables, tea, coffee, nuts, olive oil, and dark chocolate, offer protective effects on cardiovascular health through their impact on systemic inflammation, endothelial function, and gut microbiota [145]. Unlike other nutrients, polyphenols are not fully absorbed in the upper GI tract; instead, they reach the colon, where they interact with gut microbiota, acting as prebiotic substrates to support the growth of beneficial bacteria such as Lactobacillus and Bifidobacterium, while reducing the number of pathogenic bacteria such as Escherichia coli, Clostridium perfringens, and Helicobacter pylori [217,218]. Through microbial metabolism, polyphenols are converted into bioactive metabolites, such as urolithins and phenolic acids, which exert anti-inflammatory and antioxidant effects crucial for cardiovascular health [219,220]. For instance, anthocyanins and resveratrol found in berries and grapes are known to increase SCFA production, inhibit pathogenic bacteria, and improve endothelial function by reduce oxidative stress [221,222,223]. These effects may contribute to lower plaque formation risk and improved plaque stability, both essential in MI prevention and management [224,225]. Green tea and coffee contain catechins and chlorogenic acid, respectively, which support beneficial gut microbiota, reduce endotoxemia, and improve blood pressure and cholesterol levels, key factors in cardiovascular health [226,227]. Extra virgin olive oil, a staple in the MD, is rich in hydroxytyrosol and oleuropein, which possess potent anti-inflammatory and antioxidant effects that foster a gut environment favorable beneficial bacteria, thereby reducing oxidative stress and systemic inflammation [228]. These evidence linking dietary antioxidants and polyphenols to improved cardiovascular outcomes via gut microbiota modulation underscore the therapeutic potential of these compounds in MI management. Incorporating polyphenol-rich foods into dietary interventions offers a natural, multifaceted approach to enhance gut health, reduce inflammation, and protect against MI. Further research, including randomized clinical trials, is needed to clarify optimal dosages, effective polyphenol sources, and their long-term effects on cardiovascular health and MI prevention.

4.2. Personalized Probiotics

Probiotics are living microorganisms that can be ingested for their potential health benefits, including enhancing the immune microenvironment and increasing microbial richness and diversity. Studies have demonstrated that certain bacterial strains, when administered based on a patient’s microbiome, can improve cardiac outcomes by reducing systemic inflammation and oxidative stress, both critical in post-MI recovery [229]. For example, many animal studies have confirmed that probiotics, as a combination of Lactobacillus acidophilus and Bifidobacterium animalis subsp. lactis, reduced myocardial infarct size in rats with diet-induced obesity and chemically-induced colitis, suggesting their applicability in ischemic heart disease prevention [232]. Similarly, supplementation with strains like Lactobacillus rhamnosus and Lactobacillus johnsonii has been shown to reduce the MI size, cardiac hypertrophy, and improve cardiac function after MI by reprogramming the gut microbiome [231,233,236]. Interestingly, a randomized, placebo-controlled clinical trial evaluating the effects of Lactobacillus rhamnosus supplementation on symptoms of depression and quality of life in MI patients reported significant improvements in depressive symptoms, quality of life, and markers of oxidative stress and inflammation [230]. Despite traditional probiotic treatments have often utilized broad-spectrum bacterial strains, such as Lactobacillus and Bifidobacterium, to restore microbial balance and enhance gut barrier integrity; emerging evidence suggests that personalized probiotics tailored to an individual’s unique microbiota composition may provide superior benefits in the context of MI recovery, playing a vital role in advancing treatment approaches [232]. For instance, a clinical trial reported that Saccharomyces boulardii supplementation reduced ventricular remodeling after MI and improved ventricular systolic function in patients with HE, indicating potential benefits for MI prognosis [250]. Additionally, a recent study explored the effect of daily oral administration of an engineered probiotic derived from a modified Escherichia coli Nissle 1917 strain, designed to continuously secrete SCFAs as a preventive strategy against myocardial injury in an I/R animal model [251]. This intervention significantly reduced myocardial injury and improved cardiac performance compared to controls receiving the unmodified strain, likely due to reduced neutrophil infiltration into the infarct site and promotion of wound-healing macrophage polarization. These findings highlight the potential of tailored probiotic therapies as a natural, multifaceted approach to supporting cardiovascular health post-MI. However, further research, including human clinical trials, is needed to optimize strain selection, dosing, and therapeutic timing.

4.3. Exercise Regimens

Physical activity, which increases energy expenditure, is widely recognized as a critical approach to managing multiple conditions linked to CVD and MI risk [237]. Current guidelines recommend that adults engage in at least 150 min of moderate-intensity aerobic exercise or a minimum of 75 min of vigorous-intensity aerobic exercise weekly to prevent CVD [238]. Adherence to these recommendations has been shown to reduce CVD and all-cause mortality by 23–40% and 27–30%, respectively [239,240]. In secondary prevention, regular exercise training is essential for therapeutic intervention, with exercise adherence linked to a reduction in adverse outcomes over a 36-month follow-up in patients with stable heart disease [241]. Replacing just 30 min per day of sedentary behavior with physical activity is associated with a 3–12% reduction in CVD risk, further emphasizing the cardioprotective effects of exercise [242]. These benefits are mediated through multiple mechanisms, including improvement of insulin resistance, hypertension, dyslipidemia, endothelial dysfunction, and systemic inflammation [237,243]. However, a prospective study in healthy middle-aged women revealed that traditional CVD risk factors accounted for only 59% of the observed reduction in CVD risk due to exercise, suggesting that other less conventional factors play a role in these cardioprotective effects [244]. Emerging evidence indicates that exercise independently alters the composition and functional capacity of the gut microbiota, which may contribute to these cardiovascular benefits [245]. Cross-sectional studies in humans report that professional athletes have greater gut microbiota diversity, with a higher abundance of Firmicutes and a lower abundance of Bacteroidetes compared to lean sedentary controls [166,246]. However, studies in older adults have shown inconsistent results, with some reporting no associations between physical activity and gut microbiota diversity [162,247,248]. In this age group, other factors like weight and biological age may also influence the microbiota response to exercise, indicating a need for further research to clarify these interactions. In a recent study, an eight-week exercise regimen after left anterior descending coronary artery ligation in animal models altered gut microbiota composition, increasing Bacteroidetes and decreasing Firmicutes compared to non-exercising controls [70]. These findings suggest that the positive effects of exercise on gut microbiota may partially explain the cardiovascular improvements seen in individuals with active lifestyles. Thus, enhancing gut microbiota composition through exercise could be considered a supplementary therapeutic approach for MI management. Nevertheless, further studies are needed to determine the optimal type, intensity, and duration of exercise to achieve the best results for both gut health and cardiovascular protection.

5. Challenges and Future Directions

Next-generation sequencing has significantly advanced our understanding of the human gut microbiota by enabling the discovery and characterization of unculturable microbes and predicting their functions [44]. Although the gut–heart axis holds promise for MI treatment, research and clinical application face challenges due to the complexity of gut microbiota composition, which is influenced by genetics, sex, aging, lifestyle, and environmental factors [252]. While our discussion focuses primarily on the impact of lifestyle habits such as diet, physical inactivity, and alcohol consumption on the gut–heart axis, other lifestyle factors—such as pollutants, stress, and sleep quality—also play significant roles. These factors contribute to gut dysbiosis and subsequent inflammation, potentially exacerbating MI risk [253]. Although not the primary focus of our review, these interconnected factors interact with diet, physical activity, and alcohol intake to influence the gut–heart axis. Addressing these factors holistically could enhance cardiovascular disease prevention by promoting a healthier gut microbiome and reducing inflammation.
Investigating the gut–heart axis and its role in MI remains challenging due to inconsistent data across diverse populations. These discrepancies are often attributed to differences in diet, ethnicity, lifestyle, environmental exposures, and research methodologies, all of which affect gut microbiota composition and its cardiovascular impact [254,255]. Diet, in particular, is a key determinant of microbiota composition and varies widely across region and culture, complicating the synthesis of global conclusions. Ethnic differences in microbiota profiles can also lead to varying susceptibility to MI, making it challenging to generalize findings. Furthermore, methodological variations—such as differences in sample collection, sequencing techniques, and data analysis—further complicate cross-study comparisons. To address these issues, large-scale, multi-ethnic cohort studies and standardized methods are needed. Advances in sequencing and multi-omics (genomics, metabolomics, and proteomics) could help identify specific microbial functions related to the gut–heart axis, enabling more tailored interventions. Developing reliable biomarkers, such as specific microbial profiles or metabolites, is crucial for personalized treatments and monitoring MI recovery. A deeper understanding of these complexities will improve the precision of gut microbiota-based therapies for MI prevention and treatment.
An important area for future research involves exploring the bidirectional nature of the gut–heart relationship. While gut dysbiosis can affect MI outcomes, the impact of MI and related treatments on gut health, particularly under conditions of stress or medication, remains underexplored. Long-term prospective studies in MI patients are needed to clarify how changes in gut microbiota influence cardiac function over time and, conversely, how cardiac injury alters gut microbiota composition. Leveraging multi-omics techniques can provide a comprehensive view of the molecular interactions between the gut and the heart. Additionally, mechanistic studies using animal models that mimic human MI conditions, such as the SR-B1−/−ApoE-R61h/h model, are essential for dissecting the pathways involved in gut–heart interactions. These models can help explore how gut permeability, endotoxemia, and specific microbial metabolites contribute to cardiac damage, as well as how cardiac dysfunction influences gut health.

6. Conclusions

The significant changes in Western dietary patterns over the past 50 years have brought various benefits, such as reductions in malnutrition and gastrointestinal infections. However, this rapid dietary transformation has also affected multiple bodily systems, notably the intestinal microbiota. Although the precise functional role of individual microbiota components remains incompletely understood, growing evidence points to a symbiotic relationship between the host and its microbes. The gut–heart axis has thus emerged as a crucial factor in understanding and managing MI. Disruptions in gut integrity and microbial balance, along with the influence of gut-derived metabolites like LPS and TMAO, significantly exacerbate systemic inflammation and cardiovascular injury in MI contexts. Conversely, beneficial metabolites such as SCFAs provide protective effects, highlighting the potential of gut-targeted interventions—including dietary modifications, personalized probiotics, antioxidants, polyphenols, and exercise—as promising therapeutic strategies. While research supports the efficacy of these interventions, advancing the field requires overcoming challenges related to biomarker development, interindividual variability, and long-term clinical outcomes. Integrating the gut–heart axis into MI management could lead to more holistic and effective treatment approaches, ultimately reducing CVD burden and improving patient recovery. However, due to limited evidence on causality in human subjects, the precise sequence of pathological events between gut microbiota alterations and host status remains a “chicken-and-egg” dilemma.

Author Contributions

K.R. and M.E.A. designed the study; K.R., L.G., L.B. and L.M. screened the available literature; K.R. and L.G. wrote the original draft; M.E.A. reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the National Agency for Research and Development (ANID) program Fondo Nacional del Desarrollo Científico y Tecnológico (FONDECYT) of Ministry of Science and Technology, Government of Chile, through grants #1220922. This publication also has received funding from Millennium Science Initiative Program—ICN2021-004. Ph.D. Fellowship ANID-PFCHA/Doctorado Nacional/2020 -21201346.

Acknowledgments

All figures were created with BioRender.com.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Martin, S.S.; Aday, A.W.; Almarzooq, Z.I.; Anderson, C.A.; Arora, P.; Avery, C.L.; Baker-Smith, C.M.; Barone Gibbs, B.; Beaton, A.Z.; Boehme, A.K.; et al. 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data from the American Heart Association. Circulation 2024, 149, E347–E913. [Google Scholar] [CrossRef] [PubMed]
  2. Vaduganathan, M.; Mensah, G.A.; Turco, J.V.; Fuster, V.; Roth, G.A. The Global Burden of Cardiovascular Diseases and Risk: A Compass for Future Health. J. Am. Coll. Cardiol. 2022, 80, 2361–2371. [Google Scholar] [CrossRef] [PubMed]
  3. Salari, N.; Morddarvanjoghi, F.; Abdolmaleki, A.; Rasoulpoor, S.; Khaleghi, A.A.; Hezarkhani, L.A.; Shohaimi, S.; Mohammadi, M. The global prevalence of myocardial infarction: A systematic review and meta-analysis. BMC Cardiovasc. Disord. 2023, 23, 206. [Google Scholar] [CrossRef] [PubMed]
  4. Lieb, W.; Enserro, D.M.; Larson, M.G.; Vasan, R.S. Residual cardiovascular risk in individuals on lipid-lowering treatment: Quantifying absolute and relative risk in the community. Open Heart 2018, 5, e000722. [Google Scholar] [CrossRef] [PubMed]
  5. Yusuf, P.S.; Hawken, S.; Ôunpuu, S.; Dans, T.; Avezum, A.; Lanas, F.; McQueen, M.; Budaj, A.; Pais, P.; Varigos, J.; et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): Case-control study. Lancet 2004, 364, 937–952. [Google Scholar] [CrossRef]
  6. Ahlawat, S.; Asha; Sharma, K.K. Gut–organ axis: A microbial outreach and networking. Lett. Appl. Microbiol. 2021, 72, 636–668. [Google Scholar] [CrossRef]
  7. Witkowski, M.; Weeks, T.L.; Hazen, S.L. Gut microbiota and cardiovascular disease. Circ. Res. 2020, 127, 553. [Google Scholar] [CrossRef]
  8. Daniel, N.; Lécuyer, E.; Chassaing, B. Host/microbiota interactions in health and diseases—Time for mucosal microbiology! Mucosal Immunol. 2021, 14, 1006–1016. [Google Scholar] [CrossRef]
  9. Di Vincenzo, F.; Del Gaudio, A.; Petito, V.; Lopetuso, L.R.; Scaldaferri, F. Gut microbiota, intestinal permeability, and systemic inflammation: A narrative review. Intern. Emerg. Med. 2024, 19, 275–293. [Google Scholar] [CrossRef]
  10. Sittipo, P.; Shim, J.W.; Lee, Y.K. Microbial Metabolites Determine Host Health and the Status of Some Diseases. Int. J. Mol. Sci. 2019, 20, 5296. [Google Scholar] [CrossRef]
  11. Chelakkot, C.; Ghim, J.; Ryu, S.H. Mechanisms regulating intestinal barrier integrity and its pathological implications. Exp. Mol. Med. 2018, 50, 1–9. [Google Scholar] [CrossRef] [PubMed]
  12. Song, C.; Chai, Z.; Chen, S.; Zhang, H.; Zhang, X.; Zhou, Y. Intestinal mucus components and secretion mechanisms: What we do and do not know. Exp. Mol. Med. 2023, 55, 681–691. [Google Scholar] [CrossRef] [PubMed]
  13. Horowitz, A.; Chanez-Paredes, S.D.; Haest, X.; Turner, J.R. Paracellular permeability and tight junction regulation in gut health and disease. Nat. Rev. Gastroenterol. Hepatol. 2023, 20, 417–432. [Google Scholar] [CrossRef] [PubMed]
  14. Spadoni, I.; Zagato, E.; Bertocchi, A.; Paolinelli, R.; Hot, E.; Di Sabatino, A.; Caprioli, F.; Bottiglieri, L.; Oldani, A.; Viale, G.; et al. A gut-vascular barrier controls the systemic dissemination of bacteria. Science 2015, 350, 830–834. [Google Scholar] [CrossRef] [PubMed]
  15. Zeissig, S.; Bürgel, N.; Günzel, D.; Richter, J.; Mankertz, J.; Wahnschaffe, U.; Kroesen, A.J.; Zeitz, M.; Fromm, M.; Schulzke, J.D. Changes in expression and distribution of claudin 2, 5 and 8 lead to discontinuous tight junctions and barrier dysfunction in active Crohn’s disease. Gut 2007, 56, 61–72. [Google Scholar] [CrossRef]
  16. Sun, M.; He, C.; Cong, Y.; Liu, Z. Regulatory immune cells in regulation of intestinal inflammatory response to microbiota. Mucosal Immunol. 2015, 8, 969–978. [Google Scholar] [CrossRef]
  17. Schumann, M.; Günzel, D.; Buergel, N.; Richter, J.F.; Troeger, H.; May, C.; Fromm, A.; Sorgenfrei, D.; Daum, S.; Bojarski, C.; et al. Cell polarity-determining proteins Par-3 and PP-1 are involved in epithelial tight junction defects in coeliac disease. Gut 2012, 61, 220–228. [Google Scholar] [CrossRef]
  18. Di Tommaso, N.; Gasbarrini, A.; Ponziani, F.R. Intestinal Barrier in Human Health and Disease. Int. J. Environ. Res. Public Health 2021, 18, 12836. [Google Scholar] [CrossRef]
  19. Wu, H.; Hu, T.; Hao, H.; Hill, M.A.; Xu, C.; Liu, Z. Inflammatory bowel disease and cardiovascular diseases: A concise review. Eur. Heart J. Open 2021, 2, oeab029. [Google Scholar] [CrossRef]
  20. Oikonomou, I.; Papageorgiou, A.; de Lastic, A.L.; Moulias, A.; Georgopoulou, G.A.; Mouzaki, A.; Koufou, E.E.; Tsigkas, G.; Gogos, C.; Davlouros, P.; et al. Gut barrier dysfunction, endotoxemia and inflammatory response in STEMI patients and effect of primary PCI. Am. J. Med Sci. 2024, 368, 485–493. [Google Scholar] [CrossRef]
  21. Carnevale, R.; Sciarretta, S.; Valenti, V.; di Nonno, F.; Calvieri, C.; Nocella, C.; Frati, G.; Forte, M.; d’Amati, G.; Pignataro, M.G.; et al. Low-grade endotoxaemia enhances artery thrombus growth via Toll-like receptor 4: Implication for myocardial infarction. Eur. Heart J. 2020, 41, 3156–3165. [Google Scholar] [CrossRef]
  22. Carrera-Bastos, P.; Picazo, Ó.; Fontes-Villalba, M.; Pareja-Galeano, H.; Lindeberg, S.; Martínez-Selles, M.; Lucia, A.; Emanuele, E. Serum Zonulin and Endotoxin Levels in Exceptional Longevity versus Precocious Myocardial Infarction. Aging Dis. 2018, 9, 317–321. [Google Scholar] [CrossRef]
  23. Zhao, J.; Zhang, Q.; Cheng, W.; Dai, Q.; Wei, Z.; Guo, M.; Chen, F.; Qiao, S.; Hu, J.; Wang, J.; et al. Heart–gut microbiota communication determines the severity of cardiac injury after myocardial ischaemia/reperfusion. Cardiovasc. Res. 2023, 119, 1390. [Google Scholar] [CrossRef]
  24. Nendl, A.; Andersen, G.Ø.; Seljeflot, I.; Trøseid, M.; Awoyemi, A. Intestinal fatty acid binding protein is associated with infarct size and cardiac function in acute heart failure following myocardial infarction. Open Heart 2024, 11, e002868. [Google Scholar] [CrossRef]
  25. Barillà, F.; Cammisotto, V.; Bartimoccia, S.; Loffredo, L.; Nocella, C.; Bruno, N.; Torromeo, C.; Rosa, P.; Viceconte, N.; Pignatelli, P.; et al. Toll-like receptor 4 activation in platelets from myocardial infarction patients. Thromb. Res. 2022, 209, 33–40. [Google Scholar] [CrossRef]
  26. Zhou, X.; Li, J.; Guo, J.; Geng, B.; Ji, W.; Zhao, Q.; Li, J.; Liu, X.; Liu, J.; Guo, Z.; et al. Gut-dependent microbial translocation induces inflammation and cardiovascular events after ST-elevation myocardial infarction. Microbiome 2018, 6, 66. [Google Scholar] [CrossRef]
  27. Cangemi, R.; Carnevale, R.; Nocella, C.; Calvieri, C.; Bartimoccia, S.; Frati, G.; Pignatelli, P.; Picchio, V.; Violi, F. Low-grade endotoxemia is associated with cardiovascular events in community-acquired pneumonia. J. Infect. 2024, 88, 89–94. [Google Scholar] [CrossRef]
  28. Hally, K.E.; La Flamme, A.C.; Larsen, P.D.; Harding, S.A. Platelet Toll-like receptor (TLR) expression and TLR-mediated platelet activation in acute myocardial infarction. Thromb. Res. 2017, 158, 8–15. [Google Scholar] [CrossRef]
  29. Lam, V.; Su, J.; Hsu, A.; Gross, G.J.; Salzman, N.H.; Baker, J.E. Intestinal Microbial Metabolites Are Linked to Severity of Myocardial Infarction in Rats. PLoS ONE 2016, 11, e0160840. [Google Scholar] [CrossRef]
  30. Wu, Z.X.; Li, S.F.; Chen, H.; Song, J.X.; Gao, Y.F.; Zhang, F.; Cao, C.F. The changes of gut microbiota after acute myocardial infarction in rats. PLoS ONE 2017, 12, e0180717. [Google Scholar] [CrossRef]
  31. Paz-García, M.; Povo-Retana, A.; Jaén, R.I.; Prieto, P.; Peraza, D.A.; Zaragoza, C.; Hernandez-Jimenez, M.; Pineiro, D.; Regadera, J.; García-Bermejo, M.L.; et al. Beneficial effect of TLR4 blockade by a specific aptamer antagonist after acute myocardial infarction. Biomed. Pharmacother. 2023, 158, 114214. [Google Scholar] [CrossRef]
  32. Fujiwara, M.; Matoba, T.; Koga, J.I.; Okahara, A.; Funamoto, D.; Nakano, K.; Tsutsui, H.; Egashira, K. Nanoparticle incorporating Toll-like receptor 4 inhibitor attenuates myocardial ischaemia-reperfusion injury by inhibiting monocyte-mediated inflammation in mice. Cardiovasc. Res. 2019, 115, 1244–1255. [Google Scholar] [CrossRef]
  33. Odenwald, M.A.; Turner, J.R. The intestinal epithelial barrier: A therapeutic target? Nat. Rev. Gastroenterol. Hepatol. 2017, 14, 9. [Google Scholar] [CrossRef]
  34. Hillman, E.T.; Lu, H.; Yao, T.; Nakatsu, C.H. Microbial Ecology along the Gastrointestinal Tract. Microbes Environ. 2017, 32, 300. [Google Scholar] [CrossRef]
  35. Nicholson, J.K.; Holmes, E.; Kinross, J.; Burcelin, R.; Gibson, G.; Jia, W.; Pettersson, S. Host-gut microbiota metabolic interactions. Science 2012, 336, 1262–1267. [Google Scholar] [CrossRef]
  36. Donaldson, G.P.; Lee, S.M.; Mazmanian, S.K. Gut biogeography of the bacterial microbiota. Nat. Rev. Microbiol. 2016, 14, 20–32. [Google Scholar] [CrossRef]
  37. McCallum, G.; Tropini, C. The gut microbiota and its biogeography. Nat. Rev. Microbiol. 2024, 22, 105–118. [Google Scholar] [CrossRef]
  38. Nava, G.M.; Friedrichsen, H.J.; Stappenbeck, T.S. Spatial organization of intestinal microbiota in the mouse ascending colon. ISME J. 2011, 5, 627–638. [Google Scholar] [CrossRef]
  39. Gu, S.; Chen, D.; Zhang, J.N.; Lv, X.; Wang, K.; Duan, L.P.; Nie, Y.; Wu, X.L. Bacterial community mapping of the mouse gastrointestinal tract. PLoS ONE 2013, 8, e74957. [Google Scholar] [CrossRef]
  40. Glover, J.S.; Ticer, T.D.; Engevik, M.A. Characterizing the mucin-degrading capacity of the human gut microbiota. Sci. Rep. 2022, 12, 1–14. [Google Scholar] [CrossRef]
  41. Van Hul, M.; Cani, P.D. The gut microbiota in obesity and weight management: Microbes as friends or foe? Nat. Rev. Endocrinol. 2023, 19, 258–271. [Google Scholar] [CrossRef]
  42. Crudele, L.; Gadaleta, R.M.; Cariello, M.; Moschetta, A. Gut microbiota in the pathogenesis and therapeutic approaches of diabetes. eBioMedicine 2023, 97, 104821. [Google Scholar] [CrossRef]
  43. Masenga, S.K.; Hamooya, B.; Hangoma, J.; Hayumbu, V.; Ertuglu, L.A.; Ishimwe, J.; Rahman, S.; Saleem, M.; Laffer, C.L.; Elijovich, F.; et al. Recent advances in modulation of cardiovascular diseases by the gut microbiota. J. Hum. Hypertens. 2022, 36, 952–959. [Google Scholar] [CrossRef]
  44. Roume, H.; Mondot, S.; Saliou, A.; Le Fresne-Languille, S.; Doré, J. Multicenter evaluation of gut microbiome profiling by next-generation sequencing reveals major biases in partial-length metabarcoding approach. Sci. Rep. 2023, 13, 22593. [Google Scholar] [CrossRef]
  45. Hou, K.; Wu, Z.X.; Chen, X.Y.; Wang, J.Q.; Zhang, D.; Xiao, C.; Zhu, D.; Koya, J.B.; Wei, L.; Li, J.; et al. Microbiota in health and diseases. Signal Transduct. Target. Ther. 2022, 7, 135. [Google Scholar] [CrossRef]
  46. Han, Y.; Gong, Z.; Sun, G.; Xu, J.; Qi, C.; Sun, W.; Jiang, H.; Cao, P.; Ju, H. Dysbiosis of Gut Microbiota in Patients With Acute Myocardial Infarction. Front. Microbiol. 2021, 12, 1489. [Google Scholar] [CrossRef]
  47. Qian, X.; Liu, A.; Liang, C.; He, L.; Xu, Z.; Tang, S. Analysis of gut microbiota in patients with acute myocardial infarction by 16S rRNA sequencing. Ann. Transl. Med. 2022, 10, 1340. [Google Scholar] [CrossRef]
  48. Zullo, A.; Lorenzetti, R.; Hassan, C. Is Escherichia coli involved in the myocardial infarction? Eur. Heart J. 2020, 41, 2220. [Google Scholar] [CrossRef]
  49. Chen, C.; Zhang, H.; Xie, R.; Wang, Y.; Ma, Y. Gut microbiota aggravate cardiac ischemia-reperfusion injury via regulating the formation of neutrophils extracellular traps. Life Sci. 2022, 303, 120670. [Google Scholar] [CrossRef]
  50. Liu, C.; Sun, Z.; Shali, S.; Mei, Z.; Chang, S.; Mo, H.; Xu, L.; Pu, Y.; Guan, H.; Chen, G.C.; et al. The gut microbiome and microbial metabolites in acute myocardial infarction. J. Genet. Genom. 2022, 49, 569–578. [Google Scholar] [CrossRef]
  51. Amar, J.; Lelouvier, B.; Servant, F.; Lluch, J.; Burcelin, R.; Bongard, V.; Elbaz, M. Blood Microbiota Modification After Myocardial Infarction Depends Upon Low-Density Lipoprotein Cholesterol Levels. J. Am. Heart Assoc. 2019, 8, e011797. [Google Scholar] [CrossRef]
  52. Gagné, M.A.; Barbeau, C.; Frégeau, G.; Gilbert, K.; Mathieu, O.; Auger, J.; Tompkins, T.A.; Charbonney, E.; Godbout, R.; Rousseau, G. Dysbiotic microbiota contributes to the extent of acute myocardial infarction in rats. Sci. Rep. 2022, 12, 16517. [Google Scholar] [CrossRef]
  53. Tang, T.W.; Chen, H.C.; Chen, C.Y.; Yen, C.Y.; Lin, C.J.; Prajnamitra, R.P.; Chen, L.L.; Ruan, S.C.; Lin, J.H.; Lin, P.J.; et al. Loss of Gut Microbiota Alters Immune System Composition and Cripples Postinfarction Cardiac Repair. Circulation 2019, 139, 647–659. [Google Scholar] [CrossRef]
  54. Lei, C.; Zhang, X.; Chen, E.; Lin, L.; Zhou, Z.; Wang, Z.; Liu, T.; Liu, Z. Compositional alterations of the gut microbiota in acute myocardial infarction patients with type 2 diabetes mellitus. Ann. Transl. Med. 2023, 11, 317. [Google Scholar] [CrossRef]
  55. Lymperopoulos, A. Gut microbiota alterations in acute myocardial infarction: (diabetic) context is everything. Ann. Transl. Med. 2023, 11, 404. [Google Scholar] [CrossRef]
  56. Schiattarella, G.G.; Sannino, A.; Toscano, E.; Giugliano, G.; Gargiulo, G.; Franzone, A.; Trimarco, B.; Esposito, G.; Perrino, C. Gut microbe-generated metabolite trimethylamine-N-oxide as cardiovascular risk biomarker: A systematic review and dose-response meta-analysis. Eur. Heart J. 2017, 38, 2948–2956. [Google Scholar] [CrossRef]
  57. Tan, Y.; Zhou, J.; Yang, S.; Li, J.; Zhao, H.; Song, L.; Yan, H. Addition of Plasma Myeloperoxidase and Trimethylamine N-Oxide to the GRACE Score Improves Prediction of Near-Term Major Adverse Cardiovascular Events in Patients With ST-Segment Elevation Myocardial Infarction. Front. Pharmacol. 2021, 12, 632075. [Google Scholar] [CrossRef]
  58. Tang, W.W.; Wang, Z.; Levison, B.S.; Koeth, R.A.; Britt, E.B.; Fu, X.; Wu, Y.; Hazen, S.L. Intestinal Microbial Metabolism of Phosphatidylcholine and Cardiovascular Risk. N. Engl. J. Med. 2013, 368, 1575–1584. [Google Scholar] [CrossRef]
  59. Suzuki, T.; Heaney, L.M.; Jones, D.J.; Ng, L.L. Trimethylamine N-oxide and Risk Stratification after Acute Myocardial Infarction. Clin. Chem. 2017, 63, 420–428. [Google Scholar] [CrossRef]
  60. Li, N.; Wang, Y.; Zhou, J.; Chen, R.; Li, J.; Zhao, X.; Zhou, P.; Liu, C.; Chen, Y.; Song, L.; et al. Association between the Changes in Trimethylamine N-Oxide-Related Metabolites and Prognosis of Patients with Acute Myocardial Infarction: A Prospective Study. J. Cardiovasc. Dev. Dis. 2022, 9, 380. [Google Scholar] [CrossRef]
  61. Almesned, M.A.; Prins, F.M.; Lipšic, E.; Connelly, M.A.; Garcia, E.; Dullaart, R.P.; Groot, H.E.; van der Harst, P. Temporal Course of Plasma Trimethylamine N-Oxide (TMAO) Levels in ST-Elevation Myocardial Infarction. J. Clin. Med. 2021, 10, 5677. [Google Scholar] [CrossRef] [PubMed]
  62. Aldujeli, A.; Patel, R.; Grabauskyte, I.; Hamadeh, A.; Lieponyte, A.; Tatarunas, V.; Khalifeh, H.; Briedis, K.; Skipskis, V.; Aldujeili, M.; et al. The Impact of Trimethylamine N-Oxide and Coronary Microcirculatory Dysfunction on Outcomes following ST-Elevation Myocardial Infarction. J. Cardiovasc. Dev. Dis. 2023, 10, 197. [Google Scholar] [CrossRef]
  63. Matsuzawa, Y.; Nakahashi, H.; Konishi, M.; Sato, R.; Kawashima, C.; Kikuchi, S.; Akiyama, E.; Iwahashi, N.; Maejima, N.; Okada, K.; et al. Microbiota-derived Trimethylamine N-oxide Predicts Cardiovascular Risk After STEMI. Sci. Rep. 2019, 9, 11647. [Google Scholar] [CrossRef] [PubMed]
  64. Li, X.; Sun, Y.; Zhang, X.; Wang, J. Reductions in gut microbiota-derived metabolite trimethylamine N-oxide in the circulation may ameliorate myocardial infarction-induced heart failure in rats, possibly by inhibiting interleukin-8 secretion. Mol. Med. Rep. 2019, 20, 779–786. [Google Scholar] [CrossRef] [PubMed]
  65. Aleksova, A.; Fluca, A.L.; Stornaiuolo, M.; Barbati, G.; Pierri, A.; Zwas, D.R.; Santon, D.; D’Errico, S.; Marketou, M.; Sinagra, G.; et al. Intra-hospital variation of gut microbiota product, trimethylamine N-oxide (TMAO), predicts future major adverse cardiovascular events after myocardial infarction. Hell. J. Cardiol. Hjc Hell. Kardiol. Ep. 2024, in press. [Google Scholar] [CrossRef]
  66. Gao, J.; Yan, K.T.; Wang, J.X.; Dou, J.; Wang, J.; Ren, M.; Ma, J.; Zhang, X.; Liu, Y. Gut microbial taxa as potential predictive biomarkers for acute coronary syndrome and post-STEMI cardiovascular events. Sci. Rep. 2020, 10, 2639. [Google Scholar] [CrossRef]
  67. Seldin, M.M.; Meng, Y.; Qi, H.; Zhu, W.F.; Wang, Z.; Hazen, S.L.; Lusis, A.J.; Shih, D.M. Trimethylamine N-oxide promotes vascular inflammation through signaling of mitogen-activated protein kinase and nuclear factor-κb. J. Am. Heart Assoc. 2016, 5, e002767. [Google Scholar] [CrossRef] [PubMed]
  68. Chen, H.; Li, J.; Li, N.; Liu, H.; Tang, J. Increased circulating trimethylamine N-oxide plays a contributory role in the development of endothelial dysfunction and hypertension in the RUPP rat model of preeclampsia. Hypertens. Pregnancy 2019, 38, 96–104. [Google Scholar] [CrossRef]
  69. Li, T.; Gua, C.; Wu, B.; Chen, Y. Increased circulating trimethylamine N-oxide contributes to endothelial dysfunction in a rat model of chronic kidney disease. Biochem. Biophys. Res. Commun. 2018, 495, 2071–2077. [Google Scholar] [CrossRef]
  70. Zhou, Q.; Deng, J.; Pan, X.; Meng, D.; Zhu, Y.; Bai, Y.; Shi, C.; Duan, Y.; Wang, T.; Li, X.; et al. Gut microbiome mediates the protective effects of exercise after myocardial infarction. Microbiome 2022, 10, 1–19. [Google Scholar] [CrossRef]
  71. Zhou, S.; Xue, J.; Shan, J.; Hong, Y.; Zhu, W.; Nie, Z.; Zhang, Y.; Ji, N.; Luo, X.; Zhang, T.; et al. Gut-Flora-Dependent Metabolite Trimethylamine-N-Oxide Promotes Atherosclerosis-Associated Inflammation Responses by Indirect ROS Stimulation and Signaling Involving AMPK and SIRT1. Nutrients 2022, 14, 3338. [Google Scholar] [CrossRef] [PubMed]
  72. Li, X.; Geng, J.; Zhao, J.; Ni, Q.; Zhao, C.; Zheng, Y.; Chen, X.; Wang, L. Trimethylamine N-Oxide Exacerbates Cardiac Fibrosis via Activating the NLRP3 Inflammasome. Front. Physiol. 2019, 10, 866. [Google Scholar] [CrossRef] [PubMed]
  73. Koay, Y.C.; Chen, Y.C.; Wali, J.A.; Luk, A.W.; Li, M.; Doma, H.; Reimark, R.; Zaldivia, M.T.; Habtom, H.T.; Franks, A.E.; et al. Plasma levels of trimethylamine-N-oxide can be increased with ‘healthy’ and ‘unhealthy’ diets and do not correlate with the extent of atherosclerosis but with plaque instability. Cardiovasc. Res. 2021, 117, 435–449. [Google Scholar] [CrossRef] [PubMed]
  74. Tan, Y.; Sheng, Z.; Zhou, P.; Liu, C.; Zhao, H.; Song, L.; Li, J.; Zhou, J.; Chen, Y.; Wang, L.; et al. Plasma Trimethylamine N-Oxide as a Novel Biomarker for Plaque Rupture in Patients With ST-Segment-Elevation Myocardial Infarction. Circ. Cardiovasc. Interv. 2019, 12, e007281. [Google Scholar] [CrossRef] [PubMed]
  75. Bao, M.; Li, H.; Li, J. Circulating trimethylamine N-oxide is correlated with high coronary artery atherosclerotic burden in individuals with newly diagnosed coronary heart disease. BMC Cardiovasc. Disord. 2024, 24, 265. [Google Scholar] [CrossRef] [PubMed]
  76. Zhu, W.; Gregory, J.C.; Org, E.; Buffa, J.A.; Gupta, N.; Wang, Z.; Li, L.; Fu, X.; Wu, Y.; Mehrabian, M.; et al. Gut Microbial Metabolite TMAO Enhances Platelet Hyperreactivity and Thrombosis Risk. Cell 2016, 165, 111–124. [Google Scholar] [CrossRef]
  77. Zhou, X.; Jin, M.; Liu, L.; Yu, Z.; Lu, X.; Zhang, H. Trimethylamine N-oxide and cardiovascular outcomes in patients with chronic heart failure after myocardial infarction. ESC Heart Fail. 2020, 7, 188–193. [Google Scholar] [CrossRef]
  78. Yang, W.; Zhang, S.; Zhu, J.; Jiang, H.; Jia, D.; Ou, T.; Qi, Z.; Zou, Y.; Qian, J.; Sun, A.; et al. Gut microbe-derived metabolite trimethylamine N-oxide accelerates fibroblast-myofibroblast differentiation and induces cardiac fibrosis. J. Mol. Cell. Cardiol. 2019, 134, 119–130. [Google Scholar] [CrossRef]
  79. Chen, K.; Zheng, X.; Feng, M.; Li, D.; Zhang, H. Gut microbiota-dependent metabolite Trimethylamine N-oxide contributes to cardiac dysfunction in western diet-induced obese mice. Front. Physiol. 2017, 8, 253623. [Google Scholar] [CrossRef]
  80. Li, Z.; Wu, Z.; Yan, J.; Liu, H.; Liu, Q.; Deng, Y.; Ou, C.; Chen, M. Gut microbe-derived metabolite trimethylamine N-oxide induces cardiac hypertrophy and fibrosis. Lab. Investig. 2018, 99, 346–357. [Google Scholar] [CrossRef]
  81. Koh, A.; De Vadder, F.; Kovatcheva-Datchary, P.; Bäckhed, F. From Dietary Fiber to Host Physiology: Short-Chain Fatty Acids as Key Bacterial Metabolites. Cell 2016, 165, 1332–1345. [Google Scholar] [CrossRef] [PubMed]
  82. Yukino-Iwashita, M.; Nagatomo, Y.; Kawai, A.; Taruoka, A.; Yumita, Y.; Kagami, K.; Yasuda, R.; Toya, T.; Ikegami, Y.; Masaki, N.; et al. Short-Chain Fatty Acids in Gut–Heart Axis: Their Role in the Pathology of Heart Failure. J. Pers. Med. 2022, 12, 1805. [Google Scholar] [CrossRef] [PubMed]
  83. Lin, C.J.; Cheng, Y.C.; Chen, H.C.; Chao, Y.K.; Nicholson, M.; Yen, E.; Kamp, T.; Hsieh, P.C. Abstract P2016: Gut Microbiota-derived Short-chain Fatty Acids Benefit Cardiac Extracellular Matrix Remodeling In Pressure Overload. Circ. Res. 2022, 131, AP2016. [Google Scholar] [CrossRef]
  84. Tan, C.; Wu, Q.; Wang, H.; Gao, X.; Xu, R.; Cui, Z.; Zhu, J.; Zeng, X.; Zhou, H.; He, Y.; et al. Dysbiosis of Gut Microbiota and Short-Chain Fatty Acids in Acute Ischemic Stroke and the Subsequent Risk for Poor Functional Outcomes. JPEN J. Parenter. Enter. Nutr. 2020, 45, 518. [Google Scholar] [CrossRef]
  85. Guo, M.; Fan, X.; Tuerhongjiang, G.; Wang, C.; Wu, H.; Lou, B.; Wu, Y.; Yuan, Z.; She, J. Targeted metabolomic analysis of plasma fatty acids in acute myocardial infarction in young adults. Nutr. Metab. Cardiovasc. Dis. 2021, 31, 3131–3141. [Google Scholar] [CrossRef] [PubMed]
  86. Avendaño-Ortiz, J.; Lorente-Ros, Á.; Briones-Figueroa, A.; Morán-Alvarez, P.; García-Fernández, A.; Garrote-Corral, S.; Amil-Casas, I.; Carrasco-Sayalero, Á.; Tejada-Velarde, A.; Camino-López, A.; et al. Serological short-chain fatty acid and trimethylamine N-oxide microbial metabolite imbalances in young adults with acute myocardial infarction. Heliyon 2023, 9, e20854. [Google Scholar] [CrossRef]
  87. Lim, S.H.; Song, K.S.; Lee, J. Butyrate and propionate, short chain fatty acids, attenuate myocardial damages by inhibition of apoptosis in a rat model of ischemia-reperfusion. J. Appl. Biol. Chem. 2010, 53, 570–577. [Google Scholar] [CrossRef]
  88. Li, X.; Li, R.; You, N.; Zhao, X.; Li, J.; Jiang, W. Butyric Acid Ameliorates Myocardial Fibrosis by Regulating M1/M2 Polarization of Macrophages and Promoting Recovery of Mitochondrial Function. Front. Nutr. 2022, 9, 875473. [Google Scholar] [CrossRef]
  89. Hu, X.R.; Zhang, K.; Xu, C.W.; Chen, Z.Q.; Jiang, H. Anti-inflammatory effect of sodium butyrate preconditioning during myocardial ischemia/reperfusion. Exp. Ther. Med. 2014, 8, 229–232. [Google Scholar] [CrossRef]
  90. Jiang, X.; Huang, X.; Tong, Y.; Gao, H. Butyrate improves cardiac function and sympathetic neural remodeling following myocardial infarction in rats. Can. J. Physiol. Pharmacol. 2020, 98, 391–399. [Google Scholar] [CrossRef]
  91. Zhou, M.; Li, D.; Xie, K.; Xu, L.; Kong, B.; Wang, X.; Tang, Y.; Liu, Y.; Huang, H. The short-chain fatty acid propionate improved ventricular electrical remodeling in a rat model with myocardial infarction. Food Funct. 2021, 12, 12580–12593. [Google Scholar] [CrossRef] [PubMed]
  92. Mcmillan, A.; Hazen, S.L. Gut microbiota involvement in ventricular remodeling post myocardial infarction: New insights into how to heal a broken heart. Circulation 2019, 139, 660. [Google Scholar] [CrossRef] [PubMed]
  93. Nogal, A.; Valdes, A.M.; Menni, C. The role of short-chain fatty acids in the interplay between gut microbiota and diet in cardio-metabolic health. Gut Microbes 2021, 13, 1897212. [Google Scholar] [CrossRef]
  94. Lymperopoulos, A.; Suster, M.S.; Borges, J.I. Short-Chain Fatty Acid Receptors and Cardiovascular Function. Int. J. Mol. Sci. 2022, 23, 3303. [Google Scholar] [CrossRef] [PubMed]
  95. Masui, R.; Sasaki, M.; Funaki, Y.; Ogasawara, N.; Mizuno, M.; Iida, A.; Izawa, S.; Kondo, Y.; Ito, Y.; Tamura, Y.; et al. G protein-coupled receptor 43 moderates gut inflammation through cytokine regulation from mononuclear cells. Inflamm. Bowel Dis. 2013, 19, 2848–2856. [Google Scholar] [CrossRef]
  96. Maslowski, K.M.; Vieira, A.T.; Ng, A.; Kranich, J.; Sierro, F.; Di, Y.; Schilter, H.C.; Rolph, M.S.; MacKay, F.; Artis, D.; et al. Regulation of inflammatory responses by gut microbiota and chemoattractant receptor GPR43. Nature 2009, 461, 1282–1286. [Google Scholar] [CrossRef]
  97. Carbone, A.M.; Borges, J.I.; Suster, M.S.; Sizova, A.; Cora, N.; Desimine, V.L.; Lymperopoulos, A. Regulator of G-Protein Signaling-4 Attenuates Cardiac Adverse Remodeling and Neuronal Norepinephrine Release-Promoting Free Fatty Acid Receptor FFAR3 Signaling. Int. J. Mol. Sci. 2022, 23, 5803. [Google Scholar] [CrossRef]
  98. Nagliya, D.; Baggio Lopez, T.; Del Calvo, G.; Stoicovy, R.A.; Borges, J.I.; Suster, M.S.; Lymperopoulos, A. Differential Modulation of Catecholamine and Adipokine Secretion by the Short Chain Fatty Acid Receptor FFAR3 and α2-Adrenergic Receptors in PC12 Cells. Int. J. Mol. Sci. 2024, 25, 5227. [Google Scholar] [CrossRef] [PubMed]
  99. Li, W.; Shu, S.; Cheng, L.; Hao, X.; Wang, L.; Wu, Y.; Yuan, Z.; Zhou, J. Fasting serum total bile acid level is associated with coronary artery disease, myocardial infarction and severity of coronary lesions. Atherosclerosis 2020, 292, 193–200. [Google Scholar] [CrossRef]
  100. Liu, T.T.; Wang, J.; Liang, Y.; Wu, X.Y.; Li, W.Q.; Wang, Y.H.; Jing, A.R.; Liang, M.M.; Sun, L.; Dou, J.; et al. The level of serum total bile acid is related to atherosclerotic lesions, prognosis and gut Lactobacillus in acute coronary syndrome patients. Ann. Med. 2023, 55, 2232369. [Google Scholar] [CrossRef]
  101. Ramakrishna, K.; Krishnamurthy, S. Indole-3-carbinol ameliorated the isoproterenol-induced myocardial infarction via multimodal mechanisms in Wistar rats. Nat. Prod. Res. 2022, 36, 6044–6049. [Google Scholar] [CrossRef] [PubMed]
  102. Andreadou, I.; Tasouli, A.; Iliodromitis, E.; Tsantili-Kakoulidou, A.; Papalois, A.; Siatra, T.; Kremastinos, D.T. Reduction of myocardial infarct size in rabbits by a novel indole derivative with antioxidant and free radical scavenging properties. Eur. J. Pharmacol. 2002, 453, 271–277. [Google Scholar] [CrossRef] [PubMed]
  103. Hou, S.; Yan, X.; Gao, X.; Jockusch, S.; Gibson, K.M.; Shan, Z.; Bi, L. Enhancing Cardiomyocyte Resilience to Ischemia-Reperfusion Injury: The Therapeutic Potential of an Indole-Peptide-Tempo Conjugate (IPTC). ACS Omega 2024, 9, 39401–39418. [Google Scholar] [CrossRef]
  104. Backholer, K.; Peters, S.A.; Bots, S.H.; Peeters, A.; Huxley, R.R.; Woodward, M. Sex differences in the relationship between socioeconomic status and cardiovascular disease: A systematic review and meta-analysis. J. Epidemiol. Community Health 2017, 71, 550–557. [Google Scholar] [CrossRef]
  105. Pancholy, S.B.; Shantha, G.P.S.; Patel, T.; Cheskin, L.J. Sex differences in short-term and long-term all-cause mortality among patients with ST-segment elevation myocardial infarction treated by primary percutaneous intervention: A meta-analysis. JAMA Intern. Med. 2014, 174, 1822–1830. [Google Scholar] [CrossRef]
  106. Mehta, L.S.; Beckie, T.M.; DeVon, H.A.; Grines, C.L.; Krumholz, H.M.; Johnson, M.N.; Lindley, K.J.; Vaccarino, V.; Wang, T.Y.; Watson, K.E.; et al. Acute Myocardial Infarction in Women: A Scientific Statement From the American Heart Association. Circulation 2016, 133, 916–947. [Google Scholar] [CrossRef] [PubMed]
  107. Westin, L.; Carlsson, R.; Erhardt, L.; Cantor-Graae, E.; McNeil, T. Differences in quality of life in men and women with ischemic heart disease. A prospective controlled study. Scand. Cardiovasc. J. SCJ 1999, 33, 160–165. [Google Scholar] [CrossRef] [PubMed]
  108. Slagman, A.; Searle, J.; Vollert, J.O.; Storchmann, H.; Büschenfelde, D.M.Z.; Von Recum, J.; Vlasny, D.; Ale-Abaei, A.; Koch, M.; Müller, C.; et al. Sex differences of troponin test performance in chest pain patients. Int. J. Cardiol. 2015, 187, 246–251. [Google Scholar] [CrossRef]
  109. Mosca, L.; Collins, P.; Herrington, D.M.; Mendelsohn, M.E.; Pasternak, R.C.; Robertson, R.M.; Schenck-Gustafsson, K.; Smith, S.C.; Taubert, K.A.; Wenger, N.K. Hormone Replacement Therapy and Cardiovascular Disease. Circulation 2001, 104, 499–503. [Google Scholar] [CrossRef]
  110. Woodward, M. Cardiovascular Disease and the Female Disadvantage. Int. J. Environ. Res. Public Health 2019, 16, 1165. [Google Scholar] [CrossRef]
  111. Sawano, M.; Lu, Y.; Caraballo, C.; Mahajan, S.; Dreyer, R.; Lichtman, J.H.; D’Onofrio, G.; Spatz, E.; Khera, R.; Onuma, O.; et al. Sex Difference in Outcomes of Acute Myocardial Infarction in Young Patients. J. Am. Coll. Cardiol. 2023, 81, 1797–1806. [Google Scholar] [CrossRef] [PubMed]
  112. Org, E.; Mehrabian, M.; Parks, B.W.; Shipkova, P.; Liu, X.; Drake, T.A.; Lusis, A.J. Sex differences and hormonal effects on gut microbiota composition in mice. Gut Microbes 2016, 7, 313–322. [Google Scholar] [CrossRef] [PubMed]
  113. Sinha, T.; Vich Vila, A.; Garmaeva, S.; Jankipersadsing, S.A.; Imhann, F.; Collij, V.; Bonder, M.J.; Jiang, X.; Gurry, T.; Alm, E.J.; et al. Analysis of 1135 gut metagenomes identifies sex-specific resistome profiles. Gut Microbes 2019, 10, 358. [Google Scholar] [CrossRef] [PubMed]
  114. Elderman, M.; Hugenholtz, F.; Belzer, C.; Boekschoten, M.; van Beek, A.; de Haan, B.; Savelkoul, H.; de Vos, P.; Faas, M. Sex and strain dependent differences in mucosal immunology and microbiota composition in mice. Biol. Sex Differ. 2018, 9, 26. [Google Scholar] [CrossRef] [PubMed]
  115. Falony, G.; Joossens, M.; Vieira-Silva, S.; Wang, J.; Darzi, Y.; Faust, K.; Kurilshikov, A.; Bonder, M.J.; Valles-Colomer, M.; Vandeputte, D.; et al. Population-level analysis of gut microbiome variation. Science 2016, 352, 560–564. [Google Scholar] [CrossRef]
  116. Dominianni, C.; Sinha, R.; Goedert, J.J.; Pei, Z.; Yang, L.; Hayes, R.B.; Ahn, J. Sex, Body Mass Index, and Dietary Fiber Intake Influence the Human Gut Microbiome. PLoS ONE 2015, 10, e0124599. [Google Scholar] [CrossRef]
  117. Yurkovetskiy, L.; Burrows, M.; Khan, A.A.; Graham, L.; Volchkov, P.; Becker, L.; Antonopoulos, D.; Umesaki, Y.; Chervonsky, A.V. Gender bias in autoimmunity is influenced by microbiota. Immunity 2013, 39, 400–412. [Google Scholar] [CrossRef]
  118. Bernbom, N.; Nørrung, B.; Saadbye, P.; Mølbak, L.; Vogensen, F.K.; Licht, T.R. Comparison of methods and animal models commonly used for investigation of fecal microbiota: Effects of time, host and gender. J. Microbiol. Methods 2006, 66, 87–95. [Google Scholar] [CrossRef]
  119. Markle, J.G.; Frank, D.N.; Mortin-Toth, S.; Robertson, C.E.; Feazel, L.M.; Rolle-Kampczyk, U.; Von Bergen, M.; McCoy, K.D.; Macpherson, A.J.; Danska, J.S. Sex differences in the gut microbiome drive hormone-dependent regulation of autoimmunity. Science 2013, 339, 1084–1088. [Google Scholar] [CrossRef]
  120. Flores, R.; Shi, J.; Fuhrman, B.; Xu, X.; Veenstra, T.D.; Gail, M.H.; Gajer, P.; Ravel, J.; Goedert, J.J. Fecal microbial determinants of fecal and systemic estrogens and estrogen metabolites: A cross-sectional study. J. Transl. Med. 2012, 10, 253. [Google Scholar] [CrossRef]
  121. Baranyi, A.; Meinitzer, A.; von Lewinski, D.; Rothenhäusler, H.B.; Amouzadeh-Ghadikolai, O.; Harpf, H.; Harpf, L.; Traninger, H.; Hödl, R.; Harb, B.M.; et al. Sex-specific differences in trimethylamine N-oxide (TMAO) concentrations before and after cardiac rehabilitation in acute myocardial infarction patients. EXCLI J. 2022, 21, 1–10. [Google Scholar] [CrossRef] [PubMed]
  122. Liu, W.; Zhang, L.; Shi, X.; Shen, G.; Feng, J. Cross-comparative metabolomics reveal sex-age specific metabolic fingerprints and metabolic interactions in acute myocardial infarction. Free Radic. Biol. Med. 2022, 183, 25–34. [Google Scholar] [CrossRef] [PubMed]
  123. McMechan, S.R.; Adgey, A.A. Age related outcome in acute myocardial infarction: Elderly people benefit from thrombolysis and should be included in trials. BMJ Br. Med J. 1998, 317, 1334. [Google Scholar] [CrossRef] [PubMed]
  124. Sniderman, A.D.; Furberg, C.D. Age as a modifiable risk factor for cardiovascular disease. Lancet 2008, 371, 1547–1549. [Google Scholar] [CrossRef]
  125. Law, M.R.; Wald, N.J.; Thompson, S.G. By how much and how quickly does reduction in serum cholesterol concentration lower risk of ischaemic heart disease? BMJ (Clinical Res. Ed.) 1994, 308, 367. [Google Scholar] [CrossRef]
  126. Kaneko, H.; Yano, Y.; Okada, A.; Itoh, H.; Suzuki, Y.; Yokota, I.; Morita, K.; Fujiu, K.; Michihata, N.; Jo, T.; et al. Age-Dependent Association Between Modifiable Risk Factors and Incident Cardiovascular Disease. J. Am. Heart Assoc. 2023, 12, 27684. [Google Scholar] [CrossRef]
  127. Shih, H.; Lee, B.; Lee, R.J.; Boyle, A.J. The Aging Heart and Post-Infarction Left Ventricular Remodeling. J. Am. Coll. Cardiol. 2010, 57, 9. [Google Scholar] [CrossRef]
  128. Alexander, K.P.; Newby, L.K.; Armstrong, P.W.; Cannon, C.P.; Gibler, W.B.; Rich, M.W.; Van De Werf, F.; White, H.D.; Weaver, W.D.; Naylor, M.D.; et al. Acute coronary care in the elderly, part II: ST-segment-elevation myocardial infarction: A scientific statement for healthcare professionals from the American Heart Association Council on Clinical Cardiology: In collaboration with the Society of Geriatric Cardiology. Circulation 2007, 115, 2570–2589. [Google Scholar] [CrossRef]
  129. Singh, M.; Peterson, E.D.; Roe, M.T.; Ou, F.S.; Spertus, J.A.; Rumsfeld, J.S.; Anderson, H.V.; Klein, L.W.; Ho, K.K.; Holmes, D.R. Trends in the association between age and in-hospital mortality after percutaneous coronary intervention: National Cardiovascular Data Registry experience. Circ. Cardiovasc. Interv. 2009, 2, 20–26. [Google Scholar] [CrossRef]
  130. Xu, C.; Zhu, H.; Qiu, P. Aging progression of human gut microbiota. BMC Microbiol. 2019, 19, 236. [Google Scholar] [CrossRef]
  131. Salazar, N.; Arboleya, S.; Fernández-Navarro, T.; de los Reyes-Gavilán, C.G.; Gonzalez, S.; Gueimonde, M. Age-Associated Changes in Gut Microbiota and Dietary Components Related with the Immune System in Adulthood and Old Age: A Cross-Sectional Study. Nutrients 2019, 11, 1765. [Google Scholar] [CrossRef] [PubMed]
  132. Biagi, E.; Nylund, L.; Candela, M.; Ostan, R.; Bucci, L.; Pini, E.; Nikkïla, J.; Monti, D.; Satokari, R.; Franceschi, C.; et al. Through Ageing, and Beyond: Gut Microbiota and Inflammatory Status in Seniors and Centenarians. PLoS ONE 2010, 5, e10667. [Google Scholar] [CrossRef]
  133. Herzog, E.L.; Wäfler, M.; Keller, I.; Wolf, S.; Zinkernagel, M.S.; Zysset-Burri, D.C. The importance of age in compositional and functional profiling of the human intestinal microbiome. PLoS ONE 2021, 16, e0258505. [Google Scholar] [CrossRef] [PubMed]
  134. Mueller, S.; Saunier, K.; Hanisch, C.; Norin, E.; Alm, L.; Midtvedt, T.; Cresci, A.; Silvi, S.; Orpianesi, C.; Verdenelli, M.C.; et al. Differences in fecal microbiota in different European study populations in relation to age, gender, and country: A cross-sectional study. Appl. Environ. Microbiol. 2006, 72, 1027–1033. [Google Scholar] [CrossRef]
  135. Fransen, F.; van Beek, A.A.; Borghuis, T.; El Aidy, S.; Hugenholtz, F.; van der Gaast de Jongh, C.; Savelkoul, H.F.; de Jonge, M.I.; Boekschoten, M.V.; Smidt, H.; et al. Aged Gut Microbiota Contributes to Systemical Inflammaging after Transfer to Germ-Free Mice. Front. Immunol. 2017, 8, 1385. [Google Scholar] [CrossRef]
  136. Brunt, V.E.; Gioscia-Ryan, R.A.; Richey, J.J.; Zigler, M.C.; Cuevas, L.M.; Gonzalez, A.; Vázquez-Baeza, Y.; Battson, M.L.; Smithson, A.T.; Gilley, A.D.; et al. Suppression of the gut microbiome ameliorates age-related arterial dysfunction and oxidative stress in mice. J. Physiol. 2019, 597, 2361–2378. [Google Scholar] [CrossRef]
  137. Mei, Z.; Chen, G.C.; Wang, Z.; Usyk, M.; Yu, B.; Baeza, Y.V.; Humphrey, G.; Benitez, R.S.; Li, J.; Williams-Nguyen, J.S.; et al. Dietary factors, gut microbiota, and serum trimethylamine-N-oxide associated with cardiovascular disease in the Hispanic Community Health Study/Study of Latinos. Am. J. Clin. Nutr. 2021, 113, 1503–1514. [Google Scholar] [CrossRef]
  138. Rath, S.; Rox, K.; Kleine Bardenhorst, S.; Schminke, U.; Dörr, M.; Mayerle, J.; Frost, F.; Lerch, M.M.; Karch, A.; Brönstrup, M.; et al. Higher Trimethylamine- N -Oxide Plasma Levels with Increasing Age Are Mediated by Diet and Trimethylamine-Forming Bacteria. mSystems 2021, 6, 9. [Google Scholar] [CrossRef]
  139. Fretts, A.M.; Hazen, S.L.; Jensen, P.; Budoff, M.; Sitlani, C.M.; Wang, M.; De Oliveira Otto, M.C.; Didonato, J.A.; Lee, Y.; Psaty, B.M.; et al. Association of Trimethylamine N-Oxide and Metabolites With Mortality in Older Adults. JAMA Netw. Open 2022, 5, e2213242. [Google Scholar] [CrossRef]
  140. Kjeldsen, E.W.; Thomassen, J.Q.; Rasmussen, K.L.; Nordestgaard, B.G.; Tybjærg-Hansen, A.; Frikke-Schmidt, R. Impact of diet on ten-year absolute cardiovascular risk in a prospective cohort of 94 321 individuals: A tool for implementation of healthy diets. Lancet Reg. Health—Eur. 2022, 19, 100419. [Google Scholar] [CrossRef]
  141. Lichtenstein, A.H.; Appel, L.J.; Vadiveloo, M.; Hu, F.B.; Kris-Etherton, P.M.; Rebholz, C.M.; Sacks, F.M.; Thorndike, A.N.; Van Horn, L.; Wylie-Rosett, J. 2021 Dietary Guidance to Improve Cardiovascular Health: A Scientific Statement from the American Heart Association. Circulation 2021, 144, E472–E487. [Google Scholar] [CrossRef] [PubMed]
  142. Oikonomou, E.; Psaltopoulou, T.; Georgiopoulos, G.; Siasos, G.; Kokkou, E.; Antonopoulos, A.; Vogiatzi, G.; Tsalamandris, S.; Gennimata, V.; Papanikolaou, A.; et al. Western Dietary Pattern Is Associated With Severe Coronary Artery Disease. Angiology 2018, 69, 339–346. [Google Scholar] [CrossRef] [PubMed]
  143. Sieri, S.; Agnoli, C.; Grioni, S.; Weiderpass, E.; Mattiello, A.; Sluijs, I.; Sanchez, M.J.; Jakobsen, M.U.; Sweeting, M.; van der Schouw, Y.T.; et al. Glycemic index, glycemic load, and risk of coronary heart disease: A pan-European cohort study. Am. J. Clin. Nutr. 2020, 112, 631–643. [Google Scholar] [CrossRef] [PubMed]
  144. Butler, T.; Kerley, C.P.; Altieri, N.; Alvarez, J.; Green, J.; Hinchliffe, J.; Stanford, D.; Paterson, K. Optimum nutritional strategies for cardiovascular disease prevention and rehabilitation (BACPR). Heart 2020, 106, 724–731. [Google Scholar] [CrossRef]
  145. Iqbal, R.; Anand, S.; Ounpuu, S.; Islam, S.; Zhang, X.; Rangarajan, S.; Chifamba, J.; Al-Hinai, A.; Keltai, M.; Yusuf, S. Dietary patterns and the risk of acute myocardial infarction in 52 countries: Results of the INTERHEART study. Circulation 2008, 118, 1929–1937. [Google Scholar] [CrossRef]
  146. Milanlouei, S.; Menichetti, G.; Li, Y.; Loscalzo, J.; Willett, W.C.; Barabási, A.L. A systematic comprehensive longitudinal evaluation of dietary factors associated with acute myocardial infarction and fatal coronary heart disease. Nat. Commun. 2020, 11, 6074. [Google Scholar] [CrossRef] [PubMed]
  147. Zhang, C.; Zhang, M.; Wang, S.; Han, R.; Cao, Y.; Hua, W.; Mao, Y.; Zhang, X.; Pang, X.; Wei, C.; et al. Interactions between gut microbiota, host genetics and diet relevant to development of metabolic syndromes in mice. ISME J. 2010, 4, 232–241. [Google Scholar] [CrossRef]
  148. Cani, P.D.; Neyrinck, A.M.; Fava, F.; Knauf, C.; Burcelin, R.G.; Tuohy, K.M.; Gibson, G.R.; Delzenne, N.M. Selective increases of bifidobacteria in gut microflora improve high-fat-diet-induced diabetes in mice through a mechanism associated with endotoxaemia. Diabetologia 2007, 50, 2374–2383. [Google Scholar] [CrossRef]
  149. Martinez, K.B.; Leone, V.; Chang, E.B. Western diets, gut dysbiosis, and metabolic diseases: Are they linked? Gut Microbes 2017, 8, 130–142. [Google Scholar] [CrossRef]
  150. Merra, G.; Noce, A.; Marrone, G.; Cintoni, M.; Tarsitano, M.G.; Capacci, A.; De Lorenzo, A. Influence of Mediterranean Diet on Human Gut Microbiota. Nutrients 2020, 13, 7. [Google Scholar] [CrossRef]
  151. Wilson Tang, W.H.; Hazen, S.L. The Gut Microbiome and Its Role in Cardiovascular Diseases. Circulation 2017, 135, 1008–1010. [Google Scholar] [CrossRef] [PubMed]
  152. Hamad, I.; Cardilli, A.; Côrte-Real, B.F.; Dyczko, A.; Vangronsveld, J.; Kleinewietfeld, M. High-Salt Diet Induces Depletion of Lactic Acid-Producing Bacteria in Murine Gut. Nutrients 2022, 14, 1171. [Google Scholar] [CrossRef] [PubMed]
  153. Ramezani, F.; Pourghazi, F.; Eslami, M.; Gholami, M.; Mohammadian Khonsari, N.; Ejtahed, H.S.; Larijani, B.; Qorbani, M. Dietary fiber intake and all-cause and cause-specific mortality: An updated systematic review and meta-analysis of prospective cohort studies. Clin. Nutr. 2024, 43, 65–83. [Google Scholar] [CrossRef]
  154. Kaye, D.M.; Shihata, W.A.; Jama, H.A.; Tsyganov, K.; Ziemann, M.; Kiriazis, H.; Horlock, D.; Vijay, A.; Giam, B.; Vinh, A.; et al. Deficiency of Prebiotic Fiber and Insufficient Signaling Through Gut Metabolite-Sensing Receptors Leads to Cardiovascular Disease. Circulation 2020, 141, 1393–1403. [Google Scholar] [CrossRef]
  155. Wang, M.; Wang, Z.; Lee, Y.; Lai, H.T.; De Oliveira Otto, M.C.; Lemaitre, R.N.; Fretts, A.; Sotoodehnia, N.; Budoff, M.; Didonato, J.A.; et al. Dietary Meat, Trimethylamine N-Oxide-Related Metabolites, and Incident Cardiovascular Disease Among Older Adults: The Cardiovascular Health Study. Arterioscler. Thromb. Vasc. Biol. 2022, 42, E273–E288. [Google Scholar] [CrossRef]
  156. Brichacek, A.L.; Florkowski, M.; Abiona, E.; Frank, K.M. Ultra-Processed Foods: A Narrative Review of the Impact on the Human Gut Microbiome and Variations in Classification Methods. Nutrients 2024, 16, 1738. [Google Scholar] [CrossRef]
  157. Guney, C.; Bal, N.B.; Akar, F. The impact of dietary fructose on gut permeability, microbiota, abdominal adiposity, insulin signaling and reproductive function. Heliyon 2023, 9, e18896. [Google Scholar] [CrossRef] [PubMed]
  158. Jenkins, D.J.; Willett, W.C.; Yusuf, S.; Hu, F.B.; Glenn, A.J.; Liu, S.; Mente, A.; Miller, V.; Bangdiwala, S.I.; Gerstein, H.C.; et al. Association of glycaemic index and glycaemic load with type 2 diabetes, cardiovascular disease, cancer, and all-cause mortality: A meta-analysis of mega cohorts of more than 100 000 participants. Lancet Diabetes Endocrinol. 2024, 12, 107–118. [Google Scholar] [CrossRef]
  159. Jingjie, W.; Yang, L.; Jing, Y.; Ran, L.; Yiqing, X.; Zhou, N. Sedentary time and its association with risk of cardiovascular diseases in adults: An updated systematic review and meta-analysis of observational studies. BMC Public Health 2022, 22, 286. [Google Scholar] [CrossRef]
  160. Wu, Z.; Huang, Z.; Wu, Y.; Huang, S.; Wang, Y.; Zhao, H.; Chen, S.; Wu, S.; Gao, X. Sedentary time, metabolic abnormalities, and all-cause mortality after myocardial infarction: A mediation analysis. Eur. J. Prev. Cardiol. 2019, 26, 96–104. [Google Scholar] [CrossRef]
  161. Tiberi, M.; Piepoli, M.F. Regular physical activity only associated with low sedentary time increases survival in post myocardial infarction patient. Eur. J. Prev. Cardiol. 2019, 26, 94–96. [Google Scholar] [CrossRef] [PubMed]
  162. Strasser, B.; Wolters, M.; Weyh, C.; Krüger, K.; Ticinesi, A. The Effects of Lifestyle and Diet on Gut Microbiota Composition, Inflammation and Muscle Performance in Our Aging Society. Nutrients 2021, 13, 2045. [Google Scholar] [CrossRef] [PubMed]
  163. Xu, L.; Li, W.; Ling, L.; Zhang, Z.; Cui, Z.; Ge, J.; Wang, Y.; Meng, Q.; Wang, Y.; Liu, K.; et al. A Sedentary Lifestyle Changes the Composition and Predicted Functions of the Gut Bacterial and Fungal Microbiota of Subjects from the Same Company. Curr. Microbiol. 2023, 80, 368. [Google Scholar] [CrossRef]
  164. O’Toole, P.W.; Shiels, P.G. The role of the microbiota in sedentary lifestyle disorders and ageing: Lessons from the animal kingdom. J. Intern. Med. 2020, 287, 271–282. [Google Scholar] [CrossRef] [PubMed]
  165. Castellanos, N.; Diez, G.G.; Antúnez-Almagro, C.; Bailén, M.; Bressa, C.; González Soltero, R.; Pérez, M.; Larrosa, M. A Critical Mutualism—Competition Interplay Underlies the Loss of Microbial Diversity in Sedentary Lifestyle. Front. Microbiol. 2020, 10, 3142. [Google Scholar] [CrossRef]
  166. Barton, W.; Penney, N.C.; Cronin, O.; Garcia-Perez, I.; Molloy, M.G.; Holmes, E.; Shanahan, F.; Cotter, P.D.; O’Sullivan, O. The microbiome of professional athletes differs from that of more sedentary subjects in composition and particularly at the functional metabolic level. Gut 2018, 67, 625–633. [Google Scholar] [CrossRef]
  167. Zhong, X.; Powell, C.; Phillips, C.M.; Millar, S.R.; Carson, B.P.; Dowd, K.P.; Perry, I.J.; Kearney, P.M.; Harrington, J.M.; O’Toole, P.W.; et al. The Influence of Different Physical Activity Behaviours on the Gut Microbiota of Older Irish Adults. J. Nutr. Health Aging 2021, 25, 854–861. [Google Scholar] [CrossRef]
  168. Jollet, M.; Nay, K.; Chopard, A.; Bareille, M.P.; Beck, A.; Ollendorff, V.; Vernus, B.; Bonnieu, A.; Mariadassou, M.; Rué, O.; et al. Does physical inactivity induce significant changes in human gut microbiota? New answers using the dry immersion hypoactivity model. Nutrients 2021, 13, 3865. [Google Scholar] [CrossRef]
  169. Bressa, C.; Bailén-Andrino, M.; Pérez-Santiago, J.; González-Soltero, R.; Pérez, M.; Montalvo-Lominchar, M.G.; Maté-Muñoz, J.L.; Domínguez, R.; Moreno, D.; Larrosa, M. Differences in gut microbiota profile between women with active lifestyle and sedentary women. PLoS ONE 2017, 12, e0171352. [Google Scholar] [CrossRef]
  170. Baldanzi, G.; Sayols-Baixeras, S.; Ekblom-Bak, E.; Ekblom, Ö.; Dekkers, K.F.; Hammar, U.; Nguyen, D.; Ahmad, S.; Ericson, U.; Arvidsson, D.; et al. Accelerometer-based physical activity is associated with the gut microbiota in 8416 individuals in SCAPIS. EBioMedicine 2024, 100, 104989. [Google Scholar] [CrossRef]
  171. Campbell, S.C.; Wisniewski, P.J.; Noji, M.; McGuinness, L.R.; Häggblom, M.M.; Lightfoot, S.A.; Joseph, L.B.; Kerkhof, L.J. The Effect of Diet and Exercise on Intestinal Integrity and Microbial Diversity in Mice. PLoS ONE 2016, 11, e0150502. [Google Scholar] [CrossRef] [PubMed]
  172. De Schryver, A.M.; Keulemans, Y.C.; Peters, H.P.; Akkermans, L.M.; Smout, A.J.; De Vries, W.R.; Van Berge-Henegouwen, G.P. Effects of regular physical activity on defecation pattern in middle-aged patients complaining of chronic constipation. Scand. J. Gastroenterol. 2005, 40, 422–429. [Google Scholar] [CrossRef] [PubMed]
  173. Lim, S.S.; Vos, T.; Flaxman, A.D.; Danaei, G.; Shibuya, K.; Adair-Rohani, H.; Amann, M.; Anderson, H.R.; Andrews, K.G.; Aryee, M.; et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012, 380, 2224–2260. [Google Scholar] [CrossRef]
  174. Ronksley, P.E.; Brien, S.E.; Turner, B.J.; Mukamal, K.J.; Ghali, W.A. Association of alcohol consumption with selected cardiovascular disease outcomes: A systematic review and meta-analysis. BMJ 2011, 342, 479. [Google Scholar] [CrossRef]
  175. Pearson, T.A. Alcohol and heart disease. Circulation 1996, 94, 3023–3025. [Google Scholar] [CrossRef] [PubMed]
  176. Biddinger, K.J.; Emdin, C.A.; Haas, M.E.; Wang, M.; Hindy, G.; Ellinor, P.T.; Kathiresan, S.; Khera, A.V.; Aragam, K.G. Association of Habitual Alcohol Intake With Risk of Cardiovascular Disease. JAMA Netw. Open 2022, 5, e223849. [Google Scholar] [CrossRef]
  177. Leong, D.P.; Smyth, A.; Teo, K.K.; McKee, M.; Rangarajan, S.; Pais, P.; Liu, L.; Anand, S.S.; Yusuf, S. Patterns of alcohol consumption and myocardial infarction risk: Observations from 52 countries in the INTERHEART case-control study. Circulation 2014, 130, 390–398. [Google Scholar] [CrossRef]
  178. McKee, M.; Britton, A. The positive relationship between alcohol and heart disease in eastern Europe: Potential physiological mechanisms. J. R. Soc. Med. 1998, 91, 402–407. [Google Scholar] [CrossRef]
  179. Giuffrè, M.; Campigotto, M.; Campisciano, G.; Comar, M.; Crocè, L.S. A story of liver and gut microbes: How does the intestinal flora affect liver disease? A review of the literature. Am. J. Physiology. Gastrointest. Liver Physiol. 2020, 318, G889–G906. [Google Scholar] [CrossRef]
  180. Ying, W.; Jing, T.; Bing, C.; Baifang, W.; Dai, Z.; Bingyuan, W. Effects of alcohol on intestinal epithelial barrier permeability and expression of tight junction-associated proteins. Mol. Med. Rep. 2014, 9, 2352–2356. [Google Scholar] [CrossRef]
  181. Mutlu, E.A.; Gillevet, P.M.; Rangwala, H.; Sikaroodi, M.; Naqvi, A.; Engen, P.A.; Kwasny, M.; Lau, C.K.; Keshavarzian, A. Colonic microbiome is altered in alcoholism. Am. J. Physiol.—Gastrointest. Liver Physiol. 2012, 302, G966. [Google Scholar] [CrossRef] [PubMed]
  182. Addolorato, G.; Ponziani, F.R.; Dionisi, T.; Mosoni, C.; Vassallo, G.A.; Sestito, L.; Petito, V.; Picca, A.; Marzetti, E.; Tarli, C.; et al. Gut microbiota compositional and functional fingerprint in patients with alcohol use disorder and alcohol-associated liver disease. Liver Int. Off. J. Int. Assoc. Study Liver 2020, 40, 878–888. [Google Scholar] [CrossRef] [PubMed]
  183. Kosnicki, K.L.; Penprase, J.C.; Cintora, P.; Torres, P.J.; Harris, G.L.; Brasser, S.M.; Kelley, S.T. Effects of moderate, voluntary ethanol consumption on the rat and human gut microbiome. Addict. Biol. 2019, 24, 617–630. [Google Scholar] [CrossRef] [PubMed]
  184. Hooper, L.; Martin, N.; Jimoh, O.F.; Kirk, C.; Foster, E.; Abdelhamid, A.S. Reduction in saturated fat intake for cardiovascular disease. Cochrane Database Syst. Rev. 2020, 8, CD011737. [Google Scholar] [CrossRef]
  185. Zhuang, P.; Zhang, Y.; He, W.; Chen, X.; Chen, J.; He, L.; Mao, L.; Wu, F.; Jiao, J. Dietary Fats in Relation to Total and Cause-Specific Mortality in a Prospective Cohort of 521 120 Individuals With 16 Years of Follow-Up. Circ. Res. 2019, 124, 757–768. [Google Scholar] [CrossRef]
  186. Li, S.; Chiuve, S.E.; Flint, A.; Pai, J.K.; Forman, J.P.; Hu, F.B.; Willett, W.C.; Mukamal, K.J.; Rimm, E.B. Better Diet Quality and Decreased Mortality Among Myocardial Infarction Survivors. JAMA Intern. Med. 2013, 173, 1808–1819. [Google Scholar] [CrossRef]
  187. Willett, W.C.; Sacks, F.; Trichopoulou, A.; Drescher, G.; Ferro-Luzzi, A.; Helsing, E.; Trichopoulos, D. Mediterranean diet pyramid: A cultural model for healthy eating. Am. J. Clin. Nutr. 1995, 61, 1402S–1406S. [Google Scholar] [CrossRef]
  188. Laffond, A.; Rivera-Picón, C.; Rodríguez-Muñoz, P.M.; Juárez-Vela, R.; Ruiz de Viñaspre-Hernández, R.; Navas-Echazarreta, N.; Sánchez-González, J.L. Mediterranean Diet for Primary and Secondary Prevention of Cardiovascular Disease and Mortality: An Updated Systematic Review. Nutrients 2023, 15, 3356. [Google Scholar] [CrossRef]
  189. Delgado-Lista, J.; Alcala-Diaz, J.F.; Torres-Peña, J.D.; Quintana-Navarro, G.M.; Fuentes, F.; Garcia-Rios, A.; Ortiz-Morales, A.M.; Gonzalez-Requero, A.I.; Perez-Caballero, A.I.; Yubero-Serrano, E.M.; et al. Long-term secondary prevention of cardiovascular disease with a Mediterranean diet and a low-fat diet (CORDIOPREV): A randomised controlled trial. Lancet 2022, 399, 1876–1885. [Google Scholar] [CrossRef]
  190. Casas, R.; Sacanella, E.; Urpí-Sardà, M.; Chiva-Blanch, G.; Ros, E.; Martínez-González, M.A.; Covas, M.I.; Lamuela-Raventos, R.M.; Salas-Salvadó, J.; Fiol, M.; et al. The effects of the mediterranean diet on biomarkers of vascular wall inflammation and plaque vulnerability in subjects with high risk for cardiovascular disease. A randomized trial. PLoS ONE 2014, 9, e100084. [Google Scholar] [CrossRef]
  191. Meslier, V.; Laiola, M.; Roager, H.M.; De Filippis, F.; Roume, H.; Quinquis, B.; Giacco, R.; Mennella, I.; Ferracane, R.; Pons, N.; et al. Mediterranean diet intervention in overweight and obese subjects lowers plasma cholesterol and causes changes in the gut microbiome and metabolome independently of energy intake. Gut 2020, 69, 1258–1268. [Google Scholar] [CrossRef] [PubMed]
  192. Solá, R.; Fitó, M.; Estruch, R.; Salas-Salvadó, J.; Corella, D.; de La Torre, R.; Muñoz, M.A.; del Carmen López-Sabater, M.; Martínez-González, M.A.; Arós, F.; et al. Effect of a traditional Mediterranean diet on apolipoproteins B, A-I, and their ratio: A randomized, controlled trial. Atherosclerosis 2011, 218, 174–180. [Google Scholar] [CrossRef] [PubMed]
  193. Vogel, R.A.; Corretti, M.C.; Plotnick, G.D. The postprandial effect of components of the Mediterranean diet on endothelial function. J. Am. Coll. Cardiol. 2000, 36, 1455–1460. [Google Scholar] [CrossRef] [PubMed]
  194. Liu, Y.; Milner, M.; Klonizakis, M. Physiological effects of a short-term lifestyle intervention based on the Mediterranean diet: Comparison between older and younger healthy, sedentary adults. Nutrition 2018, 55–56, 185–191. [Google Scholar] [CrossRef]
  195. Jimenez-Torres, J.; Alcalá-Diaz, J.F.; Torres-Peña, J.D.; Gutierrez-Mariscal, F.M.; Leon-Acuña, A.; Gómez-Luna, P.; Fernández-Gandara, C.; Quintana-Navarro, G.M.; Fernandez-Garcia, J.C.; Perez-Martinez, P.; et al. Mediterranean Diet Reduces Atherosclerosis Progression in Coronary Heart Disease: An Analysis of the CORDIOPREV Randomized Controlled Trial. Stroke 2021, 52, 3440–3449. [Google Scholar] [CrossRef]
  196. Mitsou, E.K.; Kakali, A.; Antonopoulou, S.; Mountzouris, K.C.; Yannakoulia, M.; Panagiotakos, D.B.; Kyriacou, A. Adherence to the Mediterranean diet is associated with the gut microbiota pattern and gastrointestinal characteristics in an adult population. Br. J. Nutr. 2017, 117, 1645–1655. [Google Scholar] [CrossRef]
  197. Garcia-Mantrana, I.; Selma-Royo, M.; Alcantara, C.; Collado, M.C. Shifts on Gut Microbiota Associated to Mediterranean Diet Adherence and Specific Dietary Intakes on General Adult Population. Front. Microbiol. 2018, 9, 890. [Google Scholar] [CrossRef]
  198. Pagliai, G.; Russo, E.; Niccolai, E.; Dinu, M.; Di Pilato, V.; Magrini, A.; Bartolucci, G.; Baldi, S.; Menicatti, M.; Giusti, B.; et al. Influence of a 3-month low-calorie Mediterranean diet compared to the vegetarian diet on human gut microbiota and SCFA: The CARDIVEG Study. Eur. J. Nutr. 2020, 59, 2011–2024. [Google Scholar] [CrossRef]
  199. Tuttolomondo, A.; Simonetta, I.; Daidone, M.; Mogavero, A.; Ortello, A.; Pinto, A. Metabolic and Vascular Effect of the Mediterranean Diet. Int. J. Mol. Sci. 2019, 20, 4716. [Google Scholar] [CrossRef]
  200. Estruch, R.; Ros, E.; Salas-Salvadó, J.; Covas, M.I.; Corella, D.; Arós, F.; Gómez-Gracia, E.; Ruiz-Gutiérrez, V.; Fiol, M.; Lapetra, J.; et al. Primary Prevention of Cardiovascular Disease with a Mediterranean Diet Supplemented with Extra-Virgin Olive Oil or Nuts. New Engl. J. Med. 2018, 378, e34. [Google Scholar] [CrossRef]
  201. Lombardo, M.; Aulisa, G.; Marcon, D.; Rizzo, G. The Influence of Animal- or Plant-Based Diets on Blood and Urine Trimethylamine-N-Oxide (TMAO) Levels in Humans. Curr. Nutr. Rep. 2022, 11, 56–68. [Google Scholar] [CrossRef] [PubMed]
  202. Liu, S.; Buring, J.E.; Sesso, H.D.; Rimm, E.B.; Willett, W.C.; Manson, J.E. A prospective study of dietary fiber intake and risk of cardiovascular disease among women. J. Am. Coll. Cardiol. 2002, 39, 49–56. [Google Scholar] [CrossRef] [PubMed]
  203. Threapleton, D.E.; Greenwood, D.C.; Evans, C.E.; Cleghorn, C.L.; Nykjaer, C.; Woodhead, C.; Cade, J.E.; Gale, C.P.; Burley, V.J. Dietary fibre intake and risk of cardiovascular disease: Systematic review and meta-analysis. BMJ 2013, 347, f6879. [Google Scholar] [CrossRef] [PubMed]
  204. Li, S.; Flint, A.; Pai, J.K.; Forman, J.P.; Hu, F.B.; Willett, W.C.; Rexrode, K.M.; Mukamal, K.J.; Rimm, E.B. Dietary fiber intake and mortality among survivors of myocardial infarction: Prospective cohort study. BMJ 2014, 348, g2659. [Google Scholar] [CrossRef]
  205. Mueller, P. High Dietary Fiber Intake Is Associated with Lower Mortality After Myocardial Infarction. 2014. Available online: https://www.jwatch.org/na34503/2014/05/06/high-dietary-fiber-intake-associated-with-lower-mortality (accessed on 31 October 2024).
  206. Dong, W.; Yang, Z. Association of Dietary Fiber Intake With Myocardial Infarction and Stroke Events in US Adults: A Cross-Sectional Study of NHANES 2011–2018. Front. Nutr. 2022, 9, 936926. [Google Scholar] [CrossRef] [PubMed]
  207. Kwon, Y.J.; Lee, H.S.; Park, G.; Kim, H.M.; Lee, J.W. Association of Dietary Fiber Intake with All-Cause Mortality and Cardiovascular Disease Mortality: A 10-Year Prospective Cohort Study. Nutrients 2022, 14, 3089. [Google Scholar] [CrossRef]
  208. Lin, D.; Peters, B.A.; Friedlander, C.; Freiman, H.J.; Goedert, J.J.; Sinha, R.; Miller, G.; Bernstein, M.A.; Hayes, R.B.; Ahn, J. Association of dietary fibre intake and gut microbiota in adults. Br. J. Nutr. 2018, 120, 1014–1022. [Google Scholar] [CrossRef]
  209. Zhao, J.; Cheng, W.; Lu, H.; Shan, A.; Zhang, Q.; Sun, X.; Kang, L.; Xie, J.; Xu, B. High fiber diet attenuate the inflammation and adverse remodeling of myocardial infarction via modulation of gut microbiota and metabolites. Front. Microbiol. 2022, 13, 1046912. [Google Scholar] [CrossRef]
  210. Marques, F.Z.; Nelson, E.; Chu, P.Y.; Horlock, D.; Fiedler, A.; Ziemann, M.; Tan, J.K.; Kuruppu, S.; Rajapakse, N.W.; El-Osta, A.; et al. High-fiber diet and acetate supplementation change the gut microbiota and prevent the development of hypertension and heart failure in hypertensive mice. Circulation 2017, 135, 964–977. [Google Scholar] [CrossRef]
  211. Ma, W.; Nguyen, L.H.; Song, M.; Wang, D.D.; Franzosa, E.A.; Cao, Y.; Joshi, A.; Drew, D.A.; Mehta, R.; Ivey, K.L.; et al. Dietary fiber intake, the gut microbiome, and chronic systemic inflammation in a cohort of adult men. Genome Med. 2021, 13. [Google Scholar] [CrossRef] [PubMed]
  212. Qi, X.; Li, Y.; Fang, C.; Jia, Y.; Chen, M.; Chen, X.; Jia, J. The associations between dietary fibers intake and systemic immune and inflammatory biomarkers, a multi-cycle study of NHANES 2015–2020. Front. Nutr. 2023, 10, 1242115. [Google Scholar] [CrossRef]
  213. Shivakoti, R.; Biggs, M.L.; Djoussé, L.; Durda, P.J.; Kizer, J.R.; Psaty, B.; Reiner, A.P.; Tracy, R.P.; Siscovick, D.; Mukamal, K.J. Intake and Sources of Dietary Fiber, Inflammation, and Cardiovascular Disease in Older US Adults. JAMA Netw. Open 2022, 5. [Google Scholar] [CrossRef]
  214. Di Caro, V.; Cummings, J.L.; Alcamo, A.M.; Piganelli, J.D.; Clark, R.S.; Morowitz, M.J.; Aneja, R.K. Dietary Cellulose Supplementation Modulates the Immune Response in a Murine Endotoxemia Model. Shock 2019, 51, 526–534. [Google Scholar] [CrossRef]
  215. Ranneh, Y.; Fadel, A.; Md Akim, A.; Idris, I.; Ilesanmi-Oyelere, B.L.; Ismail, L.C. Effect of Dietary Fiber Supplementation on Metabolic Endotoxemia: A Protocol for Systematic Review and Meta-Analysis of Randomized Clinical Trials. Methods Protoc. 2023, 6, 84. [Google Scholar] [CrossRef]
  216. Schoultz, I.; Keita, Å.V. The Intestinal Barrier and Current Techniques for the Assessment of Gut Permeability. Cells 2020, 9, 1909. [Google Scholar] [CrossRef] [PubMed]
  217. Gowd, V.; Karim, N.; Shishir, M.R.I.; Xie, L.; Chen, W. Dietary polyphenols to combat the metabolic diseases via altering gut microbiota. Trends Food Sci. Technol. 2019, 93, 81–93. [Google Scholar] [CrossRef]
  218. Ma, G.; Chen, Y. Polyphenol supplementation benefits human health via gut microbiota: A systematic review via meta-analysis. J. Funct. Foods 2020, 66, 103829. [Google Scholar] [CrossRef]
  219. García-Villalba, R.; Beltrán, D.; Frutos, M.D.; Selma, M.V.; Espín, J.C.; Tomás-Barberán, F.A. Metabolism of different dietary phenolic compounds by the urolithin-producing human-gut bacteria Gordonibacter urolithinfaciens and Ellagibacter isourolithinifaciens. Food Funct. 2020, 11, 7012–7022. [Google Scholar] [CrossRef]
  220. Plamada, D.; Vodnar, D.C. Polyphenols—Gut Microbiota Interrelationship: A Transition to a New Generation of Prebiotics. Nutrients 2021, 14, 137. [Google Scholar] [CrossRef]
  221. Chen, Y.W.; Liu, R.Y.; Shih, M.K.; Lin, W.W.; Cheng, C.M.; Hsieh, C.W.; Hou, C.Y.; Chen, S.Y. The monomer of resveratrol butyrate ester ameliorates obesity and gut microbiota in high-fat diet rats. J. Funct. Foods 2024, 118, 106260. [Google Scholar] [CrossRef]
  222. Zhuang, Y.; Huang, H.; Liu, S.; Liu, F.; Tu, Q.; Yin, Y.; He, S. Resveratrol Improves Growth Performance, Intestinal Morphology, and Microbiota Composition and Metabolism in Mice. Front. Microbiol. 2021, 12, 726878. [Google Scholar] [CrossRef] [PubMed]
  223. Kapoor, P.; Tiwari, A.; Sharma, S.; Tiwari, V.; Sheoran, B.; Ali, U.; Garg, M. Effect of anthocyanins on gut health markers, Firmicutes-Bacteroidetes ratio and short-chain fatty acids: A systematic review via meta-analysis. Sci. Rep. 2023, 13, 1729. [Google Scholar] [CrossRef] [PubMed]
  224. Hayek, T.; Fuhrman, B.; Vaya, J.; Rosenblat, M.; Belinky, P.; Coleman, R.; Elis, A.; Aviram, M. Reduced progression of atherosclerosis in apolipoprotein E-deficient mice following consumption of red wine, or its polyphenols quercetin or catechin, is associated with reduced susceptibility of LDL to oxidation and aggregation. Arterioscler. Thromb. Vasc. Biol. 1997, 17, 2744–2752. [Google Scholar] [CrossRef]
  225. Rivera, K.; Salas-Pérz, F.; Echeverría, G.; Urquiaga, I.; Dicenta, S.; Pérez, D.; De La Cerda, P.; González, L.; Andia, M.E.; Uribe, S.; et al. Red Wine Grape Pomace Attenuates Atherosclerosis and Myocardial Damage and Increases Survival in Association with Improved Plasma Antioxidant Activity in a Murine Model of Lethal Ischemic Heart Disease. Nutrients 2019, 11, 2135. [Google Scholar] [CrossRef]
  226. Sidhu, D.; Vasundhara, M.; Dey, P. The intestinal-level metabolic benefits of green tea catechins: Mechanistic insights from pre-clinical and clinical studies. Phytomedicine 2024, 123, 155207. [Google Scholar] [CrossRef] [PubMed]
  227. Ye, X.; Liu, Y.; Hu, J.; Gao, Y.; Ma, Y.; Wen, D. Chlorogenic Acid-Induced Gut Microbiota Improves Metabolic Endotoxemia. Front. Endocrinol. 2021, 12, 762691. [Google Scholar] [CrossRef]
  228. Millman, J.F.; Okamoto, S.; Teruya, T.; Uema, T.; Ikematsu, S.; Shimabukuro, M.; Masuzaki, H. Extra-virgin olive oil and the gut-brain axis: Influence on gut microbiota, mucosal immunity, and cardiometabolic and cognitive health. Nutr. Rev. 2021, 79, 1362–1374. [Google Scholar] [CrossRef]
  229. Cai, J.J.; Jiang, H. Application Potential of Probiotics in Acute Myocardial Infarction. Cardiovasc. Innov. Appl. 2022, 7, 991. [Google Scholar] [CrossRef]
  230. Moludi, J.; Alizadeh, M.; Mohammadzad, M.H.S.; Davari, M. The Effect of Probiotic Supplementation on Depressive Symptoms and Quality of Life in Patients after Myocardial Infarction: Results of a Preliminary Double-Blind Clinical Trial. Psychosom. Med. 2019, 81, 770–777. [Google Scholar] [CrossRef]
  231. Gan, X.T.; Ettinger, G.; Huang, C.X.; Burton, J.P.; Haist, J.V.; Rajapurohitam, V.; Sidaway, J.E.; Martin, G.; Gloor, G.B.; Swann, J.R.; et al. Probiotic administration attenuates myocardial hypertrophy and heart failure after myocardial infarction in the rat. Circ. Heart Fail. 2014, 7, 491–499. [Google Scholar] [CrossRef]
  232. Borshchev, Y.Y.; Burovenko, I.Y.; Karaseva, A.B.; Minasian, S.M.; Protsak, E.S.; Borshchev, V.Y.; Semenova, N.Y.; Borshcheva, O.V.; Suvorov, A.N.; Galagudza, M.M. Probiotic Therapy with Lactobacillus acidophilus and Bifidobacterium animalis subsp. lactis Results in Infarct Size Limitation in Rats with Obesity and Chemically Induced Colitis. Microorganisms 2022, 10, 2293. [Google Scholar] [CrossRef] [PubMed]
  233. Lam, V.; Su, J.; Koprowski, S.; Hsu, A.; Tweddell, J.S.; Rafiee, P.; Gross, G.J.; Salzman, N.H.; Baker, J.E. Intestinal microbiota determine severity of myocardial infarction in rats. FASEB J. Off. Publ. Fed. Am. Soc. Exp. Biol. 2012, 26, 1727–1735. [Google Scholar] [CrossRef]
  234. Sadeghzadeh, J.; Vakili, A.; Sameni, H.R.; Shadnoush, M.; Bandegi, A.R.; Khorasani, M.Z. The Effect of Oral Consumption of Probiotics in Prevention of Heart Injury in a Rat Myocardial Infarction Model: A Histopathological, Hemodynamic and Biochemical Evaluation. Iran. Biomed. J. 2017, 21, 174–181. [Google Scholar] [CrossRef] [PubMed]
  235. Konhilas, J. Abstract 444: Probiotic Administration Mitigates the Detrimental Effects of Myocardial Infarction in Mice. Circ. Res. 2016, 119. [Google Scholar] [CrossRef]
  236. Zhong, X.; Zhao, Y.; Huang, L.; Liu, J.; Wang, K.; Gao, X.; Zhao, X.; Wang, X. Remodeling of the gut microbiome by Lactobacillus johnsonii alleviates the development of acute myocardial infarction. Front. Microbiol. 2023, 14, 1140498. [Google Scholar] [CrossRef] [PubMed]
  237. Tucker, W.J.; Fegers-Wustrow, I.; Halle, M.; Haykowsky, M.J.; Chung, E.H.; Kovacic, J.C. Exercise for Primary and Secondary Prevention of Cardiovascular Disease: JACC Focus Seminar 1/4. J. Am. Coll. Cardiol. 2022, 80, 1091–1106. [Google Scholar] [CrossRef]
  238. WHO. WHO Guidelines on Physical Activity and Sedentary Behaviour; WHO: Geneve, Switzerland, 2020. [Google Scholar]
  239. Moore, S.C.; Patel, A.V.; Matthews, C.E.; Berrington de Gonzalez, A.; Park, Y.; Katki, H.A.; Linet, M.S.; Weiderpass, E.; Visvanathan, K.; Helzlsouer, K.J.; et al. Leisure time physical activity of moderate to vigorous intensity and mortality: A large pooled cohort analysis. PLoS Med. 2012, 9, e1001335. [Google Scholar] [CrossRef]
  240. Wahid, A.; Manek, N.; Nichols, M.; Kelly, P.; Foster, C.; Webster, P.; Kaur, A.; Friedemann Smith, C.; Wilkins, E.; Rayner, M.; et al. Quantifying the Association Between Physical Activity and Cardiovascular Disease and Diabetes: A Systematic Review and Meta-Analysis. J. Am. Heart Assoc. Cardiovasc. Cerebrovasc. Dis. 2016, 5, e002495. [Google Scholar] [CrossRef]
  241. Kasargod Prabhakar, C.R.; Stewart, R. Physical activity and mortality in patients with stable coronary heart disease. Curr. Opin. Cardiol. 2018, 33, 653–659. [Google Scholar] [CrossRef]
  242. Li, X.; Ma, H.; Zhou, T.; Qi, L. Replacing Sedentary Behavior Time With Physical Activities, Recommended Physical Activity, and Incident Coronary Heart Disease. Mayo Clin. Proc. 2023, 98, 111–121. [Google Scholar] [CrossRef] [PubMed]
  243. Fiuza-Luces, C.; Santos-Lozano, A.; Joyner, M.; Carrera-Bastos, P.; Picazo, O.; Zugaza, J.L.; Izquierdo, M.; Ruilope, L.M.; Lucia, A. Exercise benefits in cardiovascular disease: Beyond attenuation of traditional risk factors. Nat. Re. Cardiol. 2018, 15, 731–743. [Google Scholar] [CrossRef]
  244. Mora, S.; Cook, N.; Buring, J.E.; Ridker, P.M.; Lee, I.M. Physical activity and reduced risk of cardiovascular events: Potential mediating mechanisms. Circulation 2007, 116, 2110–2118. [Google Scholar] [CrossRef] [PubMed]
  245. Mailing, L.J.; Allen, J.M.; Buford, T.W.; Fields, C.J.; Woods, J.A. Exercise and the Gut Microbiome: A Review of the Evidence, Potential Mechanisms, and Implications for Human Health. Exerc. Sport Sci. Rev. 2019, 47, 75–85. [Google Scholar] [CrossRef]
  246. Clarke, S.F.; Murphy, E.F.; O’Sullivan, O.; Lucey, A.J.; Humphreys, M.; Hogan, A.; Hayes, P.; O’Reilly, M.; Jeffery, I.B.; Wood-Martin, R.; et al. Exercise and associated dietary extremes impact on gut microbial diversity. Gut 2014, 63, 1913–1920. [Google Scholar] [CrossRef]
  247. Fart, F.; Rajan, S.K.; Wall, R.; Rangel, I.; Ganda-Mall, J.P.; Tingö, L.; Brummer, R.J.; Repsilber, D.; Schoultz, I.; Lindqvist, C.M. Differences in Gut Microbiome Composition between Senior Orienteering Athletes and Community-Dwelling Older Adults. Nutrients 2020, 12, 2610. [Google Scholar] [CrossRef] [PubMed]
  248. Morita, E.; Yokoyama, H.; Imai, D.; Takeda, R.; Ota, A.; Kawai, E.; Hisada, T.; Emoto, M.; Suzuki, Y.; Okazaki, K. Aerobic Exercise Training with Brisk Walking Increases Intestinal Bacteroides in Healthy Elderly Women. Nutrients 2019, 11, 868. [Google Scholar] [CrossRef]
  249. Li, L.L.; Wang, Y.T.; Zhu, L.M.; Liu, Z.Y.; Ye, C.Q.; Qin, S. Inulin with different degrees of polymerization protects against diet-induced endotoxemia and inflammation in association with gut microbiota regulation in mice. Sci. Rep. 2020, 10, 978. [Google Scholar] [CrossRef]
  250. Costanza, A.C.; Moscavitch, S.D.; Faria Neto, H.C.; Mesquita, E.T. Probiotic therapy with Saccharomyces boulardii for heart failure patients: A randomized, double-blind, placebo-controlled pilot trial. Int. J. Cardiol. 2015, 179, 348–350. [Google Scholar] [CrossRef]
  251. Pham, Q.H.; Bui, T.V.A.; Sim, W.S.; Lim, K.H.; Law, C.O.K.; Tan, W.; Kim, R.Y.; Chow, K.T.; Park, H.J.; Ban, K.; et al. Daily oral administration of probiotics engineered to constantly secrete short-chain fatty acids effectively prevents myocardial injury from subsequent ischaemic heart disease. Cardiovasc. Res. 2024, cvae128. [Google Scholar] [CrossRef]
  252. Rai, S.; Singh, D.K.; Kumar, A. Microbial, environmental and anthropogenic factors influencing the indoor microbiome of the built environment. J. Basic Microbiol. 2021, 61, 267–292. [Google Scholar] [CrossRef] [PubMed]
  253. Zhang, Y.; Huang, K.; Duan, J.; Zhao, R.; Yang, L. Gut microbiota connects the brain and the heart: Potential mechanisms and clinical implications. Psychopharmacology 2024, 241, 637–651. [Google Scholar] [CrossRef] [PubMed]
  254. Dwiyanto, J.; Hussain, M.H.; Reidpath, D.; Ong, K.S.; Qasim, A.; Lee, S.W.; Lee, S.M.; Foo, S.C.; Chong, C.W.; Rahman, S. Ethnicity influences the gut microbiota of individuals sharing a geographical location: A cross-sectional study from a middle-income country. Sci. Rep. 2021, 11, 2618. [Google Scholar] [CrossRef] [PubMed]
  255. Rosas-Plaza, S.; Hernández-Terán, A.; Navarro-Díaz, M.; Escalante, A.E.; Morales-Espinosa, R.; Cerritos, R. Human Gut Microbiome Across Different Lifestyles: From Hunter-Gatherers to Urban Populations. Front. Microbiol. 2022, 13, 843170. [Google Scholar] [CrossRef] [PubMed]
Ijms 25 12465 g001
Figure 1. Host–microorganism interface. (A) Schematic representation of the main components of the intestinal barrier. (B) Junctional complexes linking adjacent epithelial cells in normal and impaired intestinal barrier.
Figure 1. Host–microorganism interface. (A) Schematic representation of the main components of the intestinal barrier. (B) Junctional complexes linking adjacent epithelial cells in normal and impaired intestinal barrier.
Ijms 25 12465 g001
Ijms 25 12465 g002
Figure 2. Complexity of the gut microbiota and its adaptation to different microenvironments in the lower GI tract. Four major bacterial phyla (Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria) are found in different sections of the GI tract. Oxygen levels decrease progressively from the stomach to the colon, reflecting a shift from an aerobic to an anaerobic environment. Population density and mucus thickness both increase from the stomach to the colon, corresponding with higher microbial diversity and density in the large intestine, while pH decreases along the tract, providing favorable conditions for specific bacterial communities in different regions.
Figure 2. Complexity of the gut microbiota and its adaptation to different microenvironments in the lower GI tract. Four major bacterial phyla (Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria) are found in different sections of the GI tract. Oxygen levels decrease progressively from the stomach to the colon, reflecting a shift from an aerobic to an anaerobic environment. Population density and mucus thickness both increase from the stomach to the colon, corresponding with higher microbial diversity and density in the large intestine, while pH decreases along the tract, providing favorable conditions for specific bacterial communities in different regions.
Ijms 25 12465 g002
Ijms 25 12465 g003
Figure 3. Risk factors in the gut–heart axis in health and disease. In a healthy state (eubiosis), factors like exercise and a fiber- and antioxidant-rich diets support beneficial gut bacteria, boosting SCFA production and limiting harmful compounds like TMA and LPS. Conversely, risk factors such as a Western diet, aging, antibiotics, and pollution lead to gut dysbiosis, where pathogenic bacteria increase inflammatory mediators, impair gut integrity, and raise systemic inflammation and MI risk.
Figure 3. Risk factors in the gut–heart axis in health and disease. In a healthy state (eubiosis), factors like exercise and a fiber- and antioxidant-rich diets support beneficial gut bacteria, boosting SCFA production and limiting harmful compounds like TMA and LPS. Conversely, risk factors such as a Western diet, aging, antibiotics, and pollution lead to gut dysbiosis, where pathogenic bacteria increase inflammatory mediators, impair gut integrity, and raise systemic inflammation and MI risk.
Ijms 25 12465 g003
Table 1. Main biomarkers of intestinal barrier dysfunction in MI.
Table 1. Main biomarkers of intestinal barrier dysfunction in MI.
BiomarkerPopulationTechniqueChange in MIReferences
ZOMI patientsSerum biomarker analysisElevated ZO levels correlated with systemic inflammation[20,21,22,23]
I-FABPMI patientsSerum biomarker analysisHigher I-FABP levels linked to larger infarct sizes and worsened cardiac function[24]
LPSMI patients and experimental MI modelsSerum biomarker analysisIncreased serum LPS triggering systemic inflammation via TLR4 activation, worsening myocardial damage[20,21,22,23,25,26]
D-lactateMI patients and experimental MI modelsSerum biomarker analysisElevated D-lactate levels associated with systemic inflammation and predictive of adverse cardiovascular events[26]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Rivera, K.; Gonzalez, L.; Bravo, L.; Manjarres, L.; Andia, M.E. The Gut–Heart Axis: Molecular Perspectives and Implications for Myocardial Infarction. Int. J. Mol. Sci. 2024, 25, 12465. https://doi.org/10.3390/ijms252212465

AMA Style

Rivera K, Gonzalez L, Bravo L, Manjarres L, Andia ME. The Gut–Heart Axis: Molecular Perspectives and Implications for Myocardial Infarction. International Journal of Molecular Sciences. 2024; 25(22):12465. https://doi.org/10.3390/ijms252212465

Chicago/Turabian Style

Rivera, Katherine, Leticia Gonzalez, Liena Bravo, Laura Manjarres, and Marcelo E. Andia. 2024. "The Gut–Heart Axis: Molecular Perspectives and Implications for Myocardial Infarction" International Journal of Molecular Sciences 25, no. 22: 12465. https://doi.org/10.3390/ijms252212465

APA Style

Rivera, K., Gonzalez, L., Bravo, L., Manjarres, L., & Andia, M. E. (2024). The Gut–Heart Axis: Molecular Perspectives and Implications for Myocardial Infarction. International Journal of Molecular Sciences, 25(22), 12465. https://doi.org/10.3390/ijms252212465

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop