The Role of the Gut Microbiome in Cardiovascular Diseases

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The Role of the Gut Microbiome in Cardiovascular Diseases

Candidate name: Masooma Shehzad Supervisor: Asim K. Duttaroy

University of Oslo Faculty of Medicine

04.02.22

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Acknowledgments

I would like to express my deepest thanks to my supervisor, Professor Asim K.Duttaroy, Department of Nutrition, IMB, Faculty of Medicine, for all of his support and guidance throughout this project.

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Abstract

In recent years, the role of the gut microbiome in the development of cardiovascular diseases (CVD) has been extensively studied. There has been done a lot of research supporting the claim that dysbiosis can contribute to CVD development. Association studies show that the microbiome composition differs between healthy controls and those with CVDs. Possible mechanisms include microbial metabolites, including short-chain fatty acids (SCFAs), TMAO, and bile acids, which can exert different effects on the body. The purpose of this paper was to look at intervention studies supporting this research and to prove a causal effect between the microbiome and CVDs.

To investigate this, I searched PubMed and Cochrane library. I looked for intervention trials with prebiotics, probiotics, and polyphenols. The different populations included healthy, hypertensive, diabetic, at-risk for cardiovascular disease, and CVD patients. The outcomes looked at were cardiovascular risk factors and stool samples before and after the intervention.

The purpose was to see if cardiovascular risk factor changes correlated with changes in the stool samples. 10 studies were selected that met these criteria.

The studies showed that all interventions, including probiotics, prebiotics, and polyphenols led to improvements in anthropometric data, blood pressure, lipid profile, insulin values, glucose values, CRP levels, and flow-mediated dilation. These changes were correlated with the Bacteroidetes/Firmicutes ratio and numbers, Bifidobacterium, Roseburia, and microbial diversity. The results also showed that intervention on the microbiome might be more beneficial to those individuals with pathological conditions.

This review provides very promising evidence to support the claim that the microbiome is involved in the development of CVDs and, therefore, may also be a promising intervention.

However, more research is required to confirm these findings, understand the in-depth mechanisms involved , and to be able to apply these findings in clinical practice.

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Introduction

Cardiovascular diseases (CVDs) are very prevalent worldwide. In Norway, it is estimated that a fifth of the entire population is living with CVD or is at high risk of developing it.

However, recent statistics show that the number of new cases of myocardial infarction is declining, and the cases are less severe. This is thought to be due to reducing smoking and better available treatments. However, it is still believed that the number of people with CVDs will increase in the future, mainly due to an aging population. In addition, people suffer from less severe CVDs, thereby increasing the number of years they are living, which would, in turn, lead to an increase in the number of people living with CVD.

Today’s treatment of CVDs involves various medications, such as statins, beta-blockers, ACE inhibitors, calcium channel blockers, and diuretics. While these medicines do have an effect, they are not effective for everyone. Statins are a big part of prevention therapy. Studies on statins show that they reduce mortality and cardiovascular events by about 30% and 34%, respectively (1). These medications can have side effects in some patients like muscle aches, gastrointestinal complaints, effects on liver function, and rhabdomyolysis in more severe cases. This shows that while statins are beneficial, different and alternate treatments may be needed to replace them or supplement them. The other medications used also have various side effects and may have low efficacy on some individuals.

Due to the potential for improvement in treatment strategy, and the high prevalence of CVDs, it is important to understand the mechanisms for the development of CVDs, thereby creating new therapeutic strategies. In recent years, the role of the gut microbiome in the development of CVDs has been extensively studied. In the future, this may serve as a therapeutic target.

Therefore, it is of interest to study what role, if any, our gut microbiome plays in our bodies and the development of CVD. This paper will explore this relationship between the gut microbiota and the development of CVDs.

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The Microbiome

The human body has many bacteria, viruses, archaea, and unicellular eucaryotes which coexist within us. This is referred to as the microbiome. These bacteria and microorganisms mostly colonize the gastrointestinal tract because the anaerobic environment is nutritious.

The gut microbiome has several physiological functions in our bodies. It is involved in the digestion of food through two main metabolic pathways. Firstly, the gut microbiota breaks down carbohydrates and is therefore responsible for producing short chain fatty acids.

Secondly, the gut microbiome is also involved in the fermentation of proteins, also leading to the production of short chain fatty acids, as well as other metabolites like ammonia, amines, thiols, phenols, and indoles.

Gut microbiota also has other roles in the body including regulation of the intestinal mucosal barriers, controlling nutrient metabolism and uptake, and immunological functions. Under normal conditions, the microbiota of the gut stimulates the immune system, thereby improving the host’s defense against microorganisms (2).

Taxonomically, the bacteria are classified into phylum, class, order, families, genera, and species. The most dominant phylum are Firmicutes, Bacteroidetes, Actinobacteria, Proteobacteria, Fusobacteria, and Verrucomicrobia. Of these, the firmicutes and

Bacteroidetes represent 90% of the gut microbiome. Of the firmicutes phylum, there are many genera such as Lactobacillus, Bacillus, Clostridium, Enterococcus, and Ruminicoccus.

In these, the clostridia represent 95% of them. The second phylum, Bacteroidetes, consists mainly of Bacteroides and prevotella (3).

From Physiology to Disease: Roles of the Microbiome

Everyone has a different microbiome. Therefore, it has been hard to know precisely which microbiome is a healthy microbiome. However, it is generally accepted that the microbiome of healthy people has high microbial diversity. It also has a predominance of Bacteroidetes and firmicutes.

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The disruption of the healthy microbes is called dysbiosis. This is when there is an imbalance between the healthy and harmful bacteria in the gut. This kind of dysbiosis can be linked to several diseases, including CVDs (4). Different mechanisms could be involved in this, as discussed later in this paper.

Risk Factors for Cardiovascular Diseases and Microbiome

Several external factors may affect the composition of the gut microbiota, thereby leading to dysbiosis. There’s a long list of factors ranging from early childhood to lifestyle in the adult years. Some of these factors include delivery mode. The delivery method impacts the bacteria that the baby comes into contact with and, therefore, the gut microbiota (2). This microbiota keeps changing in the first year of life in response to changing diet, antibiotic use, bread feeding status, and the introduction of different types of food. Other factors such as geographic location and ethnicity are also influencing factors. Later in life, diet, stress, phycological stress, use of medications, use of antibiotics, and exercise routines also have an impact.

Many of these factors are also risk factors for CVD. Therefore, these may be indirectly involved in the development of CVD by modulating the gut microbiome. These factors may explain how and why the gut microbiome is involved in the disease progression of CVD (5).

Age is an essential factor. Several studies indicate that aging leads to less diversified microbiota, reduced amounts of firmicutes and Bifidobacterium, and increased amounts of Bacteroidetes and Enterobacteriaceae. Therefore, aging leads to a less optimal gut

microbiome. It is unclear, though, to what extent aging itself impacts the gut microbiome or other factors such as diet, exercise, medication use, hospitalization, and long-term residential care cause the microbiome to change with age. However, animal studies do suggest that aging in itself changes the microbiome.

Exercise has been shown to increase the diversity of microbes in the gut microbiome. It has also been shown to reduce pathogenic bacteria. The human clinical trials have shown that there is an increase in many taxa with exercise, including Verrucomicrobiaceae,

Ruminococcaceae, Provotellaceae. However, many of these studies have linked the changes

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study now, but many new studies have started studying the effects of diet and exercise combined on the gut microbiome, and they have found that exercise in itself can also change the microbiome. However, many questions remain unanswered, like the effect that different types of exercise can have, such as strength training or cardio.

Another factor, obesity, has also been shown to reduce microbial diversity and increase the firmicutes: Bacteroidetes ratio. The microbiome can also promote fat storage and reduce lipolysis. This was first proven in an animal study. Leptin deficient ob/ob mice have also been used to show this. They were fed a standard chow diet. The obese mice still had a different microbiome composition, indicating that obesity is a factor that can change the microbiome. However, many more recent human studies have not found a significant correlation between BMI and microbiome composition. This may, however, be due to other confounding factors or the fact that the methods these studies used were not all the same and standardized. The connection between obesity and the microbiome is a topic still being studied.

Diet is seen as the single most important factor influencing the composition of our

microbiome. Studies have shown that changing the diet can induce microbial changes within 24 hours, and the bacteria go back to their original state within 48 hours if the changes in diet are not maintained. It has been shown that plant-based diets have lower levels of Bacteroides and more Bifidobacterium and Lactobacillus. This combination of the microbiome has been associated with beneficial health effects. On the other hand, animal-based diets have been shown to increase levels of TMAO, a microbial metabolite, which is associated with higher levels ofcardiovascular diseases. The effects of fat on the microbiome depend on the fat consumed. Eating more long-chain saturated fats has shown good effects with increases in Bacteroides and bilophila. Diets high in nondigestible carbohydrates show a more diverse microbiome, and diets with lower nondigestible carbohydrates show a more dysbiotic microbiome. Studies have also been done to study diet types rather than individual

macronutrients. For example, the Mediterranean diet has been shown to give higher levels of Prevotella and Firmicutes. On the other hand, western diets decrease the diversity of the microbiome and reduce Bifidobacterium and Eubacterium (4).

Diabetes is also a risk factor for CVD. Studies have been done that show differences in the microbiome composition between diabetic individuals and a control population. The studies

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did report different findings, but many have shown that diabetic individuals have a lower level of butyrate-producing bacteria. Some studies have suggested that these effects come from metformin treatment. In contrast, other studies done have indicated that it is

independent of this because the same changes have been seen in diabetic individuals who have not been treated with metformin. Studies have also been done on individuals with insulin resistance. It has been found that they have higher levels of branched-chain amino acids biosynthesis, which is driven by the bacteria Provotella copri and Bacteroides vulgatus.

Another important bacterium that seems to be A. muciniphila, which is decreased in those who are prediabetic (6).

High levels of lipids are also a risk factor for CVD. The link between high lipid levels and the microbiome has been extensively studied in mice and to some extent in humans too.

Association studies in obese individuals have shown that less microbiome diversity is associated with higher total serum cholesterol and triglycerides. When statistically analyzed, they found that the microbiome could attribute to 6% of the changes in triglycerides and 4%

to the changes in HDL (7).

Association Studies

There have been many association studies done to find correlations between the composition of the gut microbiome and the occurrence of CVDs. The gut microbiome consists of four main phyla: Firmicutes, Bacteroidetes, Actinobacteria and Proteobacteria. The majority of the bacteria are a part of the phyla Firmicutes and Bacteroidetes. Association studies have found a link between the Firmicutes/Bacteroidetes ratio and the occurrence of CVDs. In addition, findings show that opportunistic bacteria in the host (Escherichia coli, Clostridium

ramosum, Bacteroides caccae, and Eggerthella lenta), and lower short-chain fatty acid- producing bacteria (Roseburia, Faecalibacterium, and Eubacterium rectale) are linked to pathology.

Several association studies have been done to find a connection between atherosclerosis and the microbiome. Initially, studies showed that the same bacteria:

Staphylococcus species, Proteus vulgaris, Klebsiella pneumoniae, and Streptococcus species were found in both the gut microbiome and atherosclerotic plaque. This suggests that there is

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study done in Poland, high LDL levels were associated with high levels of Prevotella, and low Clostridium and Faecalibacterium. In another study done in china, the subjects with atherosclerosis had high levels of Streptococcus and E. coli, and lower levels of Bacteroides and Prevotella. In another study, the genus Collinsella was increased in those subjects who had symptomatic atherosclerosis. In mice models and humans, the reduction of short chain fatty acid producing bacteria like Roseburia and Eubacterium was correlated with more plaque formation. Lastly, the diversity of the microbiome is shown to be important for plaque formation and stability. From these studies, it is not clear which species are important in the development of atherosclerosis, and the underlying mechanisms are not clear.

Hypertension has also been linked to the microbiome. Initially, it was shown that treatment with antibiotics had an effect on blood pressure in rats. In association studies, hypertension has been linked to the Firmicutes/Bacteroidetes ratio, increased opportunistic bacteria, and lower levels of short-chain fatty acid-producing bacteria. The mechanisms behind this are also not clear.

The gut microbiome is also associated with heart failure. Heart failure is the end-stage disease for most heart conditions. In this condition, there is often an increased intestinal permeability in the gut, so that the microbiome can have more effects on the host. This permeability leads to leakage of LPS (lipopolysaccharides) and subsequent inflammation. In human association studies, the microbiome composition is altered in those subjects with heart failure. Those with heart failure also had less microbial diversity. Studies have also shown that individuals with heart failure have more pathogenic bacteria (Campylobacter, Shigella, and Salmonella) and reduced Eubacterium rectale and Dorea longicatena. In addition, the subjects with very reduced ejection fraction had lower levels of Faecalibacterium

prausnitzii and higher levels of Ruminococcus gnavus populations (8).

CVD and Gut Microbiota: Mechanisms Involved

As seen, there is an association between the risk factors for CVD, the occurrence of CVDs, and the microbiome. Different mechanisms are thought to be involved in the development of CVD. In particular, there has been a lot of research done on the microbial metabolites:

TMAO, short-chain fatty acids (SCFA), and bile acids. These will be discussed in this section.

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Short-chain fatty acids have been associated with CVDs. In our gut, we have complex carbohydrates, which are fermented by the gut microbiota bacteria, and turned into SCFA.

There are many different short-chain fatty acids, but the bulk of them compromise of butyrate, propionate, and acetate (8). Most of these act locally in the gut to increase mucus production, stimulate motility in the colon, upregulate the tight junctions between epithelial cells and act as an energy substrate for the colonic epithelium. Some of the SCFA cross over the intestinal epithelium and exert different effects on the host. A few studies have been done on atherosclerosis. In studies done on mice, it was shown that giving butyrate reduced

atherosclerotic lesions and gave reduced levels of superoxide (a reactive oxygen species) and nitrotyrosine (a marker of reactive oxygen species). This indicates that the reduction in atherosclerosis was likely due to reduced oxidative stress (4). SCFAs have also been shown to be involved in lipid pathways. There have been some discrepancies in the data regarding this, as some studies show increased total cholesterol levels when given SCFA while others don’t. One study showed that propionate inhibits the enzyme HmG CoA reductase and thereby reduces the levels of cholesterol in the host. SCFAs have also been shown to impact glucose metabolism, thereby being important in the development of diabetes and metabolic syndrome. Association studies showed butyrate-producing bacteria (in the phylum

Firmicutes: Coprococci, Eubacterium, Roseburia, and Facecalibactrium genera and in the Bacteroidetes phylum: Odoribacter and Alistipes genera) had been linked with the occurrence of type 2 diabetes. In addition, SCFAs have immune-modulatory effects. SCFAs have also been linked to obesity and SCFAs have lead to weight loss. The mechanisms for this are unknown but may be because propionate and butyrate reduce appetite (9). Lastly, SCFAs are involved in the regulation of blood pressure. After being absorbed into the body, the SCFAs work on two receptors on the small resistance blood vessels, Olfactory receptors 78 (Olfr78) and G protein-coupled receptor 41 (GPCR41). When these receptors are stimulated by SCFA, GPR41 acts to dilate the vessel and reduce blood pressure. These effects are neutralized by the Olfr78 receptor (8). Olfr78 is also found in the juxtaglomerular apparatus, where it leads to increased renin secretion (10). This information has been summarized in figure 1.

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Figure 1: SCFA and cardiovascular diseases (adapted from Dietary metabolism, the gut microbiome, and heart failure by W.H. Wilson Tang (10), and Gut microbes in CVD and their potential therapeutic applications by Ling Jin (8))

Another microbial metabolite, TMAO, has been linked to CVD. The gut microbiome bacteria metabolize some dietary precursors, including phosphatidylcholine, choline, L-carnitine, to create TMA. This compound travels to the hepatic circulation and is oxidized in the liver by flavin-containing monooxygenases (isoform FMO3) to create TMAO. TMAO has been linked to CVDs in the animal model and human studies. In human cohort studies, TMAO has been linked to increased risk of CVD, myocardial infarction (MI), stroke and death. Studies in mice showed that this is due to atherosclerosis. In these mice, TMAO, choline and carnitine were given, which led to increased macrophage foam cell creation and plaque. In human studies, causality has also been shown. The subjects received TMA rich microbiome transplantations, and had lower levels of atherosclerosis. The mechanisms behind this have

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been linked to platelet function. It is shown that TMAO increases platelet aggregation through increased Ca2+ release in leading to increased aggregation, in human studies. In another study, humans taking choline supplements had higher levels of TMAO and ADP dependent aggregation response. This relationship has shown to be dose dependent. TMAO has also been shown to be pro inflammatory, but the mechanisms of this are not clear. TMAO has also been linked to heart failure. In mice studies, it was shown that supplementation with TMAO or choline led to higher levels of heart failure, through ventricular modeling and myocardial fibrosis. When mice were given TMAO inhibitors these parameters were improved. In human studies, subjects with heart failure have higher levels of TMAO when comparing them to age and sex matched subjects. Higher levels of TMAO were also linked with a worse prognosis. The mechanisms are not known, but could be linked to diastolic dysfunction caused by myocardial fibrosis, and reduced contractibility in the myocytes (10).

TMAO has also been linked to glucose metabolism. In mice models, high TMAO levels were found in those who were diabetic or had metabolic disease. In these mice models, knockdown of FMO3 (the enzyme responsible for making TMAO) led to improved insulin tolerance and reduced risk of CVD. TMAO has also been linked to worsening lipid profile (9). Below, in figure 2, the role of TMAO in different cardiovascular parameters has been summarized.

Figure 2: TMAO and cardiovascular diseases (adapted from Dietary metabolism, the gut microbiome, and heart failure by W.H. Wilson Tang (10), and Gut microbes in cardiovascular diseases and their potential therapeutic applications by Ling Jin (8))

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Bile acids have also been linked to CVD in literature. Bile acids are normally made in the liver by oxidation of cholesterol. Normally these are used in the uptake of fats, and then are reabsorbed into the bloodstream. However, some of them stay in the colon, and are

metabolized through the action of the gut microbiota to secondary bile acids like

deoxycholate (DCA), lithocholate (LCA), ursodeoxycholate (UDCA), and many others.

There have been many studies that have shown a link between CVD and bile salts. There have been association studies that show that elevated plasma concentrations of LCA were linked to a higher risk of CVD. In other studies, those with coronary artery disease had a lower excretion of secondary bile salts and lower rates of bile acid synthesis. Some studies have linked lower excretion of secondary bile salts to have a higher risk for stroke and mortality. Association studies have also shown that bile acids are linked with lipid profile, insulin resistance, and glucose levels. Several possible mechanisms have been suggested for some of these findings. There are many different types of bile acid-responsive receptors. The ones most studied are FXR (farnesoid nuclear receptor) and TGR5. NF-kappaB is a

transcription factor important for inducing expression of proinflammatory genes including cytokines. In studies, it was shown that activation of FXR by secondary bile acids reduced the expression of pro inflammatory mediators in response to activation of NF- kappaB. In this way, FXR activation has been linked to reduced atherosclerosis, liver pathology and obesity (10). In mice studies, FXR deficient mice had a reduced reverse cholesterol transport which led to hypercholesterolemia (9). In some human trials, agonists for FXR have also been linked to less fibrosis in the liver and a better lipid profile (10). The other receptor, TGR5 has been shown to be athroprotective (11). The activation of this receptor induces NF-kappaB inhibition. Studies have shown that activation of both of these receptors together led to reduced atherosclerosis and obesity (10). Other non-receptor dependent mechanisms have been postulated. These include vasodilation of vessels through different mechanisms including enhanced NO activity, activation of muscarinic receptors, and activation of Ca2+

dependent K+ channels. However, these mechanisms have not been studied much and require further research (4). Bile acids have also been linked to heart failure. Human studies have shown that the ratio of primary to secondary bile acids is altered in those subjects who had heart failure. These patients had low levels of primary bile salts and an altered composition of secondary bile salts. It has also been shown that bile salts exert a negative chronotropic effect on the heart. Additionally, rat studies have shown that higher levels of bile salts led to

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reduced levels and affinity of B adrenoceptors (10). The role of bile acids in cardiovascular diseases is summarized in figure 3.

Figure 3: Bile acids and cardiovascular disease

Modulation of the Microbiome: Role of Various Factors

There are many different ways to modulate the microbiome clinically. Antibiotic treatment is often used in experiments to modulate the microbiome. However, most trials do not support using antibiotics clinically to treat dysbiosis because of bacterial resistance, side effects, and that antibiotics are not selective for certain bacteria and would also have an effect on the beneficial bacteria in the gut.

Fecal microbiota transplantation can also be used. This is the process in which a fecal

transplant from a donor is placed into the gastrointestinal tract of a recipient. This method has been tested specially to treat clostridium difficile infections. Antibiotics are the standard treatment for this condition, but fecal transplant has been compared to antibiotics in a clinical

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recurrent infection cases. Few studies to date have used fecal microbiota transplant in treating cardiovascular disease, but this is a possible way of modulating the microbiome, which can be tested in the future. However, this method does have limitations because it is not very practical. It also makes significant changes to the microbiome, including the beneficial bacteria, and therefore can cause unwanted side effects like infections.

Probiotics can also alter the microbiome. They are live bacteria and yeast and are considered to be beneficial bacteria. They can be found in fermented food, like yogurt or capsule form.

Probiotics come in many types, and the most common ones are Lactobacillus and

Bifidobacterium. It is important to note that different probiotics may not necessarily have the same effects. Probiotics work in many different ways. The mechanisms of action can be divided into three. Firstly, probiotics can modulate the immune system. They can also

directly affect microorganisms, and lastly, they can affect microbial and host toxins. They can potentiate their effect through the inactivation of certain toxins (12).

Prebiotics are nondigestible foods that increase the number of healthy bacteria in the gut.

There are many different types of prebiotics, and the most commonly studied ones are dietary fibers and other digestion-resistant carbohydrates, like oligofructose, inulin, and

galactooligosaccharides. Since these substances cannot be absorbed in the small intestine, they serve as energy for the bacteria in the colon. They are fermented by these bacteria, which produce short-chain fatty acids. They are also not fermented by all bacteria, and therefore prebiotics can be used as a target for a specific group of bacteria in treatment. Since prebiotics is such a large group of substances, different bacteria ferment different prebiotics.

That’s why each prebiotic can have a different effect depending on the type of prebiotic used and the gut microbiome that the individual has.

Other targeted therapies can also be used to modulate the microbiome. For example, there’s a lot of evidence now that TMAO, a material metabolite, is involved in cardiovascular disease development, as mentioned above. Therefore, there has been the development of TMAO inhibitors as a potential for treatment. This is just one example of an intervention of this type.

Polyphenols are compounds that are present in many plant-based foods. When ingested, these have antioxidant properties, which are suitable for human health. The microbiome and

polyphenols affect each other. The microbiome bacteria metabolize the polyphenols

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improving the bioavailability and health benefits. Polyphenols modulate the composition of the microbiome too by acting on their growth or metabolism. Polyphenol metabolism can be different among people because everyone has their own microbiome, and therefore the effects observed by taking polyphenols may vary between individuals (13).

Aims

As seen, there is extensive evidence of the involvement of the microbiome in CVDs. There are many studies done on the association between microbial metabolites (SCFAs, TMAO, and bile acids) and CVDs. As discussed, the microbiome composition between patients with CVD and healthy controls differs statistically significantly and has been proven in many clinical trials. However, these association studies do not strongly prove any causal

relationship. This means that we cannot ascertain by just these studies that the microbiome is involved in the development and treatment of CVDs. To examine this, I will look at what evidence supports these associations. To do this, I will look at human intervention trials that can prove a causal relationship between the microbiome and cardiovascular diseases.

If the microbiome plays a significant role in developing cardiovascular diseases, then I hypothesize that we can alter the cardiovascular endpoint by selectively modulating the microbiome. Therefore, the review will focus on this.

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Methodologies

Since the area of research is so broad, part of the work was to define and narrow the research question more. To do this, I had to also look at what research was available and what was not available. My main goal was to see if modulating the microbiome can change the

cardiovascular endpoint.

First, I had to decide on many factors like the population I would focus on, the method of modulating the microbiome used, which cardiovascular outcome would be examined, and more.

First, I researched different ways of modulating the microbiome, and I found the most common probiotics and prebiotics. Others included polyphenols, antibiotics, and fecal microbiome transplants (see introduction). In this research, I decided to focus on prebiotics, probiotics, and polyphenols because these are the most clinically relevant ones and could have the potential to be used together with medicines in the future. However, this is not the case for antibiotics. I also chose not to focus on fecal microbiome transplants because I found that few studies had been done using this technique after a quick search. I also decided to look for studies in which stool samples had been done before and after the intervention. This would be to see if it can be the modulation of the microbiome that is correlated with any outcomes. Also, to test the intervention and its effectiveness, I decided to include only intervention trials, and tried to mostly find randomized controlled trials (RCT) because these are the most reliable. However, not all the trails are RCTs.

Next, I had to decide which cardiovascular endpoint I could focus on in my research.

Initially, I wanted to focus on a specific disease, like coronary artery disease and see what effect microbiome modulation would have on the outcome of this disease. This could have been measured with the arterial flow before and after. However, upon a quick search, I found that few studies had been done. This could be because this kind of project would take a lot of time, as it may take some time before a result is seen in this patient. Then, I decided to search for cardiovascular diseases in general. I found that a lot of work had been done on

cardiovascular risk factors, so I decided that I could focus on cardiovascular risk factors as my outcome for my research.

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Next, I had to decide which population I would focus on. It would have been ideal to find studies on a mixed population with mixed age groups, genders, nationalities, ethnicities, and other factors that can influence the microbiome (see introduction). However, I found studies that were done on many different population groups, so I decided to include healthy groups as well as those with cardiovascular and cardiometabolic diseases, but not other groups like liver diseases and kidney diseases. This was done to make the scope of the research a little

narrower, but not so narrow that there would not be enough research on the area.

Putting all this together I came up with inclusion and exclusion criteria used.

Inclusion criteria:

• Intervention trial

• Time frame: done in the last 10 years

• Population: healthy, hypertensive, diabetic, at-risk population, cardiovascular diseases, cardiometabolic disease

• Outcome: cardiovascular risk factors and stool sample before and after intervention

• Intervention: polyphenols, probiotic, prebiotic Exclusion criteria:

• Studies measuring metabolites like TMAO

• Studies done on other population groups like liver and kidney patients

The search was done with some help from a librarian. First, I had to choose which search words I wanted to use. The search words I used were as follows: (("cardiovascular disease OR cardiovascular risk factor OR atherosclerosis OR coronary artery disease) AND (probiotic OR prebiotic OR symbiotic OR polyphenol)) AND (stool analysis OR gut microbiome OR microbiota). No asterisks or other annotation was used so that the database could on its own connect the words in the search to other terms in the Mesh terms.

The databases I decided to use were PubMed and Cochrane library. Other databases were not used because these two are the most relevant to the search for clinical trials. In the database, I also limited the search to only clinical trials because there are many reviews on this area, so limiting it to clinical trials made the search narrow. I also limited the search to articles only published in the last 10 years to only include the most recent research.

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Before starting the screening process, I added all the searches to EndNote and deleted the duplicates between the two databases. Then, records were screened based on their title and a quick look at the abstract. Then, the remaining studies were screened for eligibility based on the abstract and skimming the article if needed. Then I conducted another search without the restriction of removing clinical trials. This is because newly published articles may not have been categorized yet. Therefore I did another search using the search words (("cardiovascular disease OR cardiovascular risk factor OR atherosclerosis OR coronary artery disease) AND (probiotic OR prebiotic OR symbiotic OR polyphenol)) AND (stool analysis OR gut microbiome OR microbiota) AND clinical trial, and limited the search to the last year. 12 trials came in this search, of which 5 were screened, but none included. In the end, 10 studies were included. A summary of this process is given in figure 4.

Figure 4: identification of studies

Records identified from: Pubmed (n= 624), Cochrane (n=150)

Databases (n =2)

Records removed before screening:

Records were not clinical trials (n = 583) Duplicates removed (n=14)

Records screened (n =136)

Records excluded (n = 122)

Reason 1: record of liver patient (n=6) Reason 2: dialysis/kidney patient (n=32) Reason 3: measuring TMAO (n=6) Reason 4: not relevant content (n=47) Reason 5: duplicate (n=14)

Reason 6: no results (n=15) Reason 7: not RCT (n=2)

Reason 8: no stool sample (n = 4) Reason 9: outcome not suitable (n= 4)

Reports assessed for eligibility (n = 55)

Reports excluded (n=41) Reason 1: not RCT (n = 3) Reason 2: no stool sample (n = 8) Reason 3: pilot study/study protocol (n =4) Reason 4: outcome not suitable (n= 5) Reason 5: population not suitable (n=1) Reason 6: no results (n=19)

Reason 7: not relevant (n=5)

Studies included in review (n = 10)

IdentificationScreeningIncluded

Identification of studies via databases and registers

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The following 10 articles are included:

1. Effect of probiotic Lactobacillus plantarum Dad-13 powder consumption on the gut microbiota and intestinal health of overweight adults (14)

2. Effects of daily consumption of the probiotic Bifidobacterium animalis subsp. lactis CECT 8145 on anthropometric adiposity biomarkers in abdominally obese subjects: a randomized controlled trial (15)

3. A Mixture of trans-Galactooligosaccharides Reduces Markers of Metabolic

Syndrome and Modulates the Fecal Microbiota and Immune Function of Overweight Adults (16)

4. An in vivo assessment of the cholesterol-lowering efficacy of Lactobacillus plantarum ECGC 13110402 in normal to mildly hypercholesterolemic adults (17)

5. Probiotic therapy to men with incipient arteriosclerosis initiates increased bacterial diversity in the colon: A randomized controlled trial (18)

6. Bifidobacterium Pseudocatenulatum CECT 7765 supplementation improves inflammatory status in insulin-resistant obese children (19)

7. Impact of personalized diet and probiotic supplementation on inflammation, nutritional parameters, and intestinal microbiota - The "RISTOMED project": a randomized controlled trial in healthy older people (20)

8. Diets naturally rich in polyphenols and/or long-chain n-3 polyunsaturated fatty acids differently affect microbiota composition in high-cardiometabolic-risk individuals (21)

9. Effects of Aronia berry (poly)phenols on vascular function and gut microbiota: a double-blind, randomized controlled trial in adult men (22)

10. Red wine polyphenols modulate fecal microbiota and reduce markers of the metabolic syndrome in obese patients (23)

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Results

General Trends

The aim of this paper was to see the general trend of whether the alternation of the

microbiome can be used to positively alter the cardiovascular endpoint. To explore this, 10 studies have been chosen in which a certain prebiotic or probiotic is given to test subjects.

Microbiome analysis is done before and after the studies are completed, and cardiovascular risk factors are also analyzed before and after the intervention. In this way, it is possible to see if the microbiome changes at the same time as the cardiovascular risk factors improve. In this way, we would be able to conclude if changes in the microbiome's composition can positively affect the cardiovascular risk factors or not.

Generally, most of the studies included in this paper show that alteration of the microbiome by using prebiotics, probiotics, or polyphenols leads to a positive effect on different

cardiovascular risk factors. The general characteristics have been summarized in a table in appendix 1. Here, I will highlight some general trends first. In study 1, the consumption of Lactobacillus plantarum led to weight loss, increases in Bacteroidetes, and a decrease in Firmicutes. Many changes were also seen at the genus level (see appendix 1). However, certain factors in this study could suggest that there have been some confounding factors. The subjects are not randomized according to diet and physical activity, and these factors are also not recorded. As mentioned in the introduction, these factors can have a big impact on the microbiome. Therefore it is not possible to deduce if these factors could be enhancing or reducing the effect of the probiotic. In study 2, after consuming Bifidobacterium animalis subsp. lactis CECT 8145, the subjects had improved anthropometric markers, reduced

diastolic blood pressure, and lower HOMA-IR (insulin resistance marker). They also showed increased Akkermansia in the microbiome. The good thing about this study is that exclusion characteristics (BMI, antibiotic treatment, diabetes, pregnancy, abnormal thyroid status, anemia, alcoholism, hypocaloric diet, intestinal disease, food supplement intake) are extensive. Therefore the subjects included would be comparable. There is also an extensive list of baseline characteristics statistically the same between all participants. This further ensures that all participants would be similar at baseline before intervention. In study 3, consuming Galactooligosaccharides led to more beneficial changes in insulin, total

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cholesterol: HDL ratio, and TAG. At the end of the intervention, changes were also seen in bifidobacterial, Bacteroides, C. histolyticum, B-proteobacteria, and Desulfovibro. This study is also a reliable one because all the relevant baseline characteristics have been considered when randomizing the patients. In study 6, the consumption of Bifidobacterium

pseudocatenulatum CECT 7765 led to reduced weight, fat mass, insulin, CRP, and higher HDL. There were changes in the Rikenellaceae family, the Alistipesgenus family, and the amount of B. pseudocatenulatum. The strength of this study is that the subjects were given dietary advice and asked to keep a diet journal to check that the advice is followed. This ensures that diet will not act as a confounding factor. This is important, because diet is a contributes greatly to the composition of the microbiome, as mentioned in the introduction. In study 7, the subjects have consumed a bacterial blend, which led to reduced total cholesterol, blood glucose, and CRP. There were microbiome changes seen in Bifidobacterium and clostridium. This was a very extensive study with many strengths. In this study, there has been done statistical corrections to account for any baseline differences between participants.

This is good to control the effect of any confounding factors. Additionally, the participants have followed a strict diet which has been ensured with nutritionist appointments. The drawback is that there is no blinding done. However, since the outcomes measured are quantitate this would not have a big effect. In study 8, diets naturally rich in polyphenols were given. Then correlation analysis was done to show that changes in the CLEPT bacteria were associated with changes in insulin and early insulin secretion in the glucose tolerance test. A correlation was found between the Atopobium cluster of bacteria and TAG

(postprandial), large VLDL, and cholesterol in the large VLDL. This study is also not done in a double-blind fashion, which is a drawback. Additionally how the patients have been

followed up and if there have been dropouts has not been described at length. However, one main strength is that there is statistical analysis done to correlate gut bacteria with certain biochemical changes. In study 9, a significant correlation was found between changes in flow-mediated dilation of the vessels and changes in the bacteria Dialister,

hascolarctobacterium, and Roseburia. In this study, confounding factors are controlled well, as the subjects are randomized according to an extensive list of baseline characteristics.

Subjects also kept diet journals. Lastly, in study 10, the subjects had red wine polyphenols, and many correlations were found. The changes in TAG, plasma cholesterol, CRP, and systolic blood pressure were all correlated with specific bacterial changes (details included in the table in appendix 1). As seen, some of the studies have some drawbacks. However the

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effects on cardiovascular risk factors. In study 8, 9, and 10 certain bacteria are also statistically correlated with changes in cardiovascular risk factors. The only exceptions are study 4 and 5, in which no differences were seen in the microbiome, and biochemical markers, respectively.

Changes in Composition of the Microbiome

Most of the studies included show changes in microbiome composition, which correspond to changes in the cardiovascular risk factors. I will explore these changes. These changes have been summarized according to phylum in table 1 below.

Article number

Bacteroidetes Firmicutes Actinobacteria Proteobacteri a

Verrucomic robacteria

Diversity 1 ↑ Bacteroides,

Prevotella

↓ Faecalibacterium ,coproccus, Paenibacillusm, Ruminococcus

↑ Roseburia

↓

Brevidobacteriu m, Consilla

↑

phyllobacteriu m

↓

Akkermansia

↑

2 ↓

Akkermansia 3 ↓ Bacteroides ↓C. histolyticum ↑Bifidobacteriu

m

↓ B-

proteobacteria, Desulfovibro

5 ↑

6 ↑

Rikenellaceae family, Alistipesgenus

↓ Streptococcus ↑ B.

pseudocatenulat um

7 ↑ Clostridium/

Bifidobacterium ratio

↑

Bifidobacterium

8 ↑ CLEPT

↓ EREC

↑

9 ↑ Bacteroides ↓ Clostridium ↑

10 ↓Bacteroides,

↑ Prevotella

↓ Clostridium,

clostridium histolyticum

↑ Blautia cocoides – Eubacterium rectale, Lactobacillus Faecalibacterium prausnitzii, Roseburia

↑

Bifidobacterium , Eggerthella lenta

↑ E.coli ↑

Table 1: microbiome composition changes after intervention (article 4 has been omitted because there were no changes found)

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Several studies showed that increases in the phylum Bacteroidetes and decrease in Firmicutes are correlated with positive changes in cardiovascular risk factors. In study 1, healthy

overweight adults had Lactobacillus plantarum powder. Before and after a 90-day trial, a microbiome sample was taken. This sample showed a significant increase in Bacteroidetes and a significant reduction in Firmicutes. In the phylum Bacteroidetes, it was specifically the genus Bacteroides and Prevotella that increased. In the phylum Firmicutes, it’s the genus Faecalibacterium that was higher in the placebo group after intervention. In study 3, a mixture of trans-Galactooligosaccharides was given to a group of overweight adults. C.

Histolyticum, a genus that is part of the phylum Firmicutes decreased. In this study, FISH analysis was used, where certain probes were used to target specific regions of the

microbiome. Therefore, analysis at the phylum level is not done, and not all genus are analyzed either. Therefore, more similarities cannot be drawn with study 1. In study 6, Bifidobacterium pseudocatenulatum was given to insulin-resistant obese children. In this study, a QIAamp Fast DNA Stool minikit was used, and in this method, it is possible only to analyze at the genus level. In this study, the results showed a significant increase in the Rikenellaceae family and the Alistipesgenus after the intervention period. These are both parts of the phylum Bacteroidetes. In study 10, red wine polyphenols were given to a group of obese patients. In this study, there were healthy controls and a group with obese people, and each of these got the intervention. At baseline, the metabolic syndrome group had higher levels of firmicutes, and after the intervention, there were no significant differences found between the groups. Similar to study 1, there was also an increase in prevotella, a genus part of the Bacteroidetes phylum, after intervention. However, there was a decrease in

Bacteroides, a part of the Bacteroidetes phylum. In this study, analysis is also only done at the genus level. The conclusion that can be made is that in all these studies, the general trend seems to be that a higher level of Bacteroidetes and lower level of firmicutes has a beneficial effect on cardiovascular risk factors. As mentioned in the introduction, the Bacteroidetes/Firmicutes ratio has also earlier been found to an indicator for cardiovascular risk.

Increased levels of Bifidobacterium are correlated with positive changes in cardiovascular risk factors in many of the studies. In study 3, a mixture of trans-

Galactooligosaccharides led to increased levels of Bifidobacterium in the stool. In study 7, the subjects were given a bacterial blend, and one group had to take a capsule with this blend

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the intervention, the subjects in arm B had higher levels of Bifidobacterium. In study 10, there were two study groups, those with metabolic syndrome and healthy patients, and both got the intervention. At the start of the intervention, the healthy group had higher levels of Bifidobacterium in their stool samples, but at the end of the intervention period, there was no significant difference. There were significant increases in both study groups, but the increase was higher in the metabolic syndrome group. In addition, the increase in Bifidobacterium was statistically correlated with reduced plasma cholesterol.

Two of the studies showed an increase in the bacteria Roseburia. In study 1, there are two groups, the intervention and placebo groups. The intervention group got Lactobacillus plantarum Dad-13 powder consumption. After the intervention, the amount of Roseburia in the stool sample increased for both groups. In study 10, two groups, including healthy

patients and those with metabolic syndrome, got the intervention. After the intervention, both of these groups had higher levels of Roseburia. As mentioned in the introduction, Roseburia is a SCFA producing bacteria, and this is likely the mechanism involved here. This shows that roseburia may be one of the gut microbes involved in improving cardiovascular risk factors.

Many of the studies show that an increase in microbiome diversity is correlated with positive outcomes in cardiovascular risk factors. This has been calculated statistically in some of the studies. In study 1, the stool samples after intervention showed more diversity.

After the intervention, the subjects also had lower weight. In study 5, there is also more diversity of the microbiome after the intervention. There were, however, no significant changes in the biochemical markers. This can be attributed to the fact that there are very few test subjects in this study, and therefore significance cannot be obtained. In study 8, the polyphenol-rich diet increased the diversity of the microbiome. In this study, they also found reduced levels of Malondialdehyde after the intervention, which is a compound related to oxidative stress. In study 9, intake of a high polyphenol diet increased microbial diversity. In study 10, there were two groups, one healthy control and one group with metabolic syndrome subjects. Before the intervention, there were significant differences in the diversity of the gut microbiome between the two groups. After the intervention, there were no significant

differences in the diversity and an increase in the variety of the metabolic syndrome group.

This is suggestive of the fact that the diversity of the microbiome may be important in the pathogenesis and development of the metabolic syndrome. Positive outcomes were also seen

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after intervention in the metabolic syndrome group, including a decrease in systolic blood pressure, diastolic blood pressure, glucose levels, TAG, total cholesterol, CRP, and HDL levels. The healthy control group also had positive changes, including lower plasma cholesterol than their baseline values.

Here we see similarities in the changes of the microbiome changes seen in the 10 studies included. This is despite the fact that there are many different interventions used on different study groups. This suggests that there would be a common set of beneficial gut bacteria which then can exert their effects through different mechanisms like metabolites and then produce the beneficial effects on the cardiovascular risk factors.

Effect on Intervention on Different Populations

While most of the studies showed that the modulation of the microbiome had a positive impact on the cardiovascular risk factors, not all the interventions were equally effective in all populations. This review shows that the use of probiotics, prebiotics, and polyphenols may be more beneficial to certain groups of people.

In some of the studies, statistical analysis shows some genders and age groups have benefited more greatly from the interventions done. In study 3, after 12 weeks of intervention, the TAG was reduced, but at 6 weeks, the effect was only statistically

significant in males. In study 4, LDL was reduced, but this was mostly seen in females, and the effect was higher in those of increasing age. In this same study, there was also an increase in HDL, which was mostly seen in subjects above 60 years of age. In study 2, there were reductions of visceral fat, and when analyzed for gender, the effect was only significant for women.

In some studies, it was also seen that the effects of intervention were greater in those who have pathological conditions, rather than healthy individuals. In study 2, the probiotic Bifidobacterium animalis subsp. lactis CECT 8145 was given. The participant's weight was measured and the amount of Akkermansia bacteria in their gut. The Akkermansia bacteria increased, and this effect was greater for those who had a basal weight above 90kg compared to those with a weight below 90kg. In study 7, there were two groups, of which one got a capsule with a probiotic, and the other did not get this. In the group with the capsule, there

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were increases in Bifidobacterium. Still, the changes were present only for those with low- grade inflammation and no changes for those with no inflammation in their body (using CRP values). In study 10, the intervention was done on healthy controls and a metabolic syndrome group. The same intervention had positive effects in a lot of parameters in the metabolic syndrome group, including a decrease in systolic blood pressure, diastolic blood pressure, glucose, TAG, total cholesterol, CRP, LPS, and increased HDL. However, in the healthy control group, the intervention only led to lower plasma cholesterol levels.

Effect of Intervention

The results show that modulation of the microbiome alters the cardiovascular endpoint, as discussed. Many different endpoints and different cardiovascular risk factors changed after intervention in all these studies, including anthropometric data, blood pressure, lipid profile, insulin and glucose values, CRP levels, and flow-mediated dilation. In studies 1,2,6, and 7 there was weight loss after the interventions. In addition, in study 2 there was a reduced waist size and waist to hip ratio. Blood pressure reduction is seen in studies 2, 4, and 10. An

improved lipid profile (lower TAG, lower total cholesterol, lower LDL, and higher HDL) was seen in studies 4, 6, 8, and 10. Lower glucose levels are seen in study 10, and better glucose tolerance is seen in study 8. Lower levels of insulin are also achieved after intervention in studies 3, 6, and 8. A marker of insulin resistance, HOMA IR, is also reduced in study 2. CRP reductions are seen after interventions in studies 6, 7, and 10. Lastly, after the intervention, there is an increase in flow-mediated dilation in study 9. The two things to note here is that most of these studies have used a different type of probiotic (refer to appendix 1). However, we see that various different interventions have led to improvements in the same

cardiovascular risk factors. The other point to note is that the same intervention in one study has been shown to affect an array of cardiovascular risk factors. Therefore it would be beneficial in improving many factors at the same time. This means that there are many different ways/interventions of effectively modulating the microbiome and that this modulation can simultaneously affect many cardiovascular endpoints/risk factors.

Type of Intervention

In this review, the goal was to look at modulating the microbiome on cardiovascular risk factors. As seen, the 10 studies included all use different interventions/ways to modulate the

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microbiome. The results show that the type of intervention used may impact the outcomes, as different interventions may have slightly different working mechanisms. For example, in study 2 the probiotic Bifidobacterium animalis subsp. lactis CECT 8145 was given. These were given in both the heat-killed format and normal, and the results of these were slightly different. The heat-killed version led to changes in visceral fat. The normal version led to changes in BMI. Both of them led to decreased waist size, waist-to-height ratio, and conicity index. These observations show that the intervention used can be important for the types of results that can be expected. Additionally, as seen in table 2 below, there is a variety of different interventions including prebiotics, probiotics and polyphenols included in the studies. Most of them show beneficial effects. Therefore we can conclude that many different types of microbiome targeted interventions may be beneficial for different cardiovascular risk factors. The specific probiotic strains that certain patients should use remains to be a topic of further investigation.

Type of intervention Studies

Probiotics 1,4,5: Lactobacillus plantarum

2: Bifidobacterium animalis subsp. lactis CECT 8145

6: Bifidobacterium Pseudocatenulatum CECT 7765

7: bacterial blend

Prebiotics 3: trans-Galactooligosaccharides

Polyphenols 8: diets rich in polyphenols

9: Aronia berry polyphenols 10: red wine polyphenols Table 2: Type of Intervention

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Discussion

Comments

The good thing about my review is that I have reviewed all the studies in detail and used a checklist from kunnskapsbasertpraksis.no to analyze the articles and judge the reliability of the conclusions being made. However, this review has certain limitations, which will be discussed here. The conclusions made above are pretty general, as there are primarily general trends analyzed. With the set of articles chosen, it is difficult to make very detailed

conclusions about which interventions are more useful, more specific microbiome changes that are beneficial for cardiovascular risk factors, and which cardiovascular risk factors would benefit from which kind of microbiome alterations. This is due to many factors in the article selection. The selected articles are very heterogenous and have many differences, making comparing and contrasting more challenging. The population in which the interventions are done is pretty diverse, ranging from healthy individuals to those with metabolic or

cardiovascular disease. Most of the studies are done on adults, but in study 6 the population group is children, which can also impact the microbiome. As seen in appendix 1, the studies have also been done in many different countries, thereby making the population diverse and difficult to compare. There are also different ways of modulating the microbiome, including probiotics and prebiotics. In the selected articles, there is a wide range of different types of these pro and prebiotics used. This is because today, there is no standard on which probiotic and prebiotic should be used. Along with this, the dosing and formulations are also varied.

Additionally, many different cardiovascular risk factors were measured in the studies, and not all the studies have measured the same ones. There would also be differences between the labs and the analysis methods done in the different studies. Specifically, there are various techniques used to measure the microbiome in the stool samples. The most common

technique is to amplify the 16sRNA segment and only certain genus are amplified. This is the method used in most of the studies included, and all of them measure slightly different genus.

This can make it harder to compare results. A more reliable method would be full DNA amplification, but this is very costly and time consuming. To improve the selection of articles, there should have been a more limited selection of articles, with a more defined population, the type of probiotic or prebiotic, and the specific cardiovascular risk factors

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used. However, there would be fewer articles in this case, and this would also be a weakness in the review.

Generally, there was an extensive range of articles picked, as mentioned. This is because of the type of material that was available on this topic. Generally, few intervention trails were made in which the microbiome is analyzed using stool samples. There were also few studies in which statistical analysis was done to find out which microbiome component is correlated with which change in cardiovascular risk factors. This is because studies like these require a lot of recourses and time, and it may not be easy to find participants willing to follow up the whole intervention. There were also many studies in which there is only a study design published, but no study has been completed. All these factors meant that the articles chosen were quite broad so that enough articles could be chosen to generate a conclusion.

There are also some limitations in the individual articles chosen. Generally, because doing these kind of interventions takes a lot of recourses and time, there were few test subjects. This means that there would be big confidence intervals in the results. This is especially true for studies 1, 3, 2, 5 and 9. There are also especially small numbers of subjects in study 5 and 10.

This means that while the interventions may be having an effect, it may be difficult to see significant changes. Another problem was that there were different methods used for measuring the microbiome. In studies 1 and 10, a comprehensive analysis was done.

However, in some other studies, like in study 2 and study, 4 only specific phyla or genus were chosen to analyze. Another issue is that most studies do not provide any statistical correlation analysis between certain microbiome bacteria and certain changes in the

microbiome. Therefore, to conclude that these two factors are linked would require controlled confounding factors. As mentioned in the introduction, diet is a factor that has a significant impact on the microbiome. Therefore it would act as a confounding factor in this type of study. However, in studies 1 and 5, the diet is not controlled, and therefore it could make the results less reliable, as discussed earlier. The study design is also slightly varied. Studies 7, 8, and 10 are not done in a double-blind fashion. If this had been done, the results would have been more reliable.

There are also some discrepancies found in these articles, which could be due to a number of the factors discussed above, such as confounding factors, varied population, methods used

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In study 2, this bacteria Akkermansia reduced and was inversely related to weight. In this study, they have statistically correlated the two factors and concluded. However, in study 1, Akkermansia reduced, and weight also reduced. This shows two different trends, and it is hard to conclude which one is correct. This is one example where it is difficult to compare and contrast small details. To comment on small discrepancies like these and generate more detailed conclusions, I would have needed to increase the search of articles and include more of them in this review. However, as mentioned before, the material on this topic is limited, and the time scope of this project is another limitation making this difficult.

This project shows many of the same conclusions which are seen in other reviews and also shows some interesting new findings. There are many reviews done on the effect of

probiotics and prebiotics on cardiovascular risk factors. All of them show that these

positively affect the risk factors, which is also seen in my conclusions. However, few of these studies have done an analysis of the microbiome, which is done in this study, and therefore, that aspect cannot be compared. In my work, I have looked at the microbiome analysis before and after the intervention to compare and conclude if the microbiome gives positive

cardiovascular risk outcomes. There is no other review that has looked at this, and therefore this creates some fascinating new areas of work. There is extensive research done on the metabolites from the microbiome and how these exert their effects to create better

cardiovascular outcomes. However, to date, very little is known about which bacteria produce which metabolites, and there is no overview about which bacteria are more beneficial than others. In my study, I have found that the microbiome composition is different in a patient before and after the intervention. Therefore, it would be a new area of research to look at the mechanisms involved here, particularly which metabolite each bacteria produces and the mechanisms involved further. In the results section, I have mentioned some common changes in the microbiome found in all the studies, suggesting that there could be some common mechanisms involved. Some of these bacteria may also exert their effects through other mechanisms and not through metabolites which would also be something that requires further research. Researching this would allow us to create a map of an ideal gut microbiome profile and have an overview of the effects of the microbiome. Thereby we could predict which strains of probiotics and prebiotics are more suitable for certain patients.

This work also points to other areas that require further investigation. As mentioned in the results, some interventions had a better effect on the already at-risk population, such as those

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with CVD or metabolic syndrome. Medicine is becoming a more individualized field, and therefore it may be of interest to investigate further if the use of probiotics and prebiotics can be more individualized. The type of intervention chosen can be targeted towards the patient, their disease, age, and other factors. As we see, there are also many types of probiotics and prebiotics used and doses. More research is needed to determine which type of intervention and dose to use in which patient group. Another thing seen is that diet is significant. In study 9, the patients had a diet high in polyphenols, and this had positive effects on the microbiome and cardiovascular risk factors. Therefore, it is possible to investigate if we can achieve the same results through certain dietary modifications. Lastly, we see that probiotics and

prebiotics positively affect cardiovascular risk factors. However, to use these interventions in clinical practice, there would need to be trials done to compare the effectiveness of traditional therapies, for example, blood pressure medications or statins, to probiotics and prebiotics.

Therefore we would know how to use these either in combination with or as a supplement to these medications to improve the cardiovascular health of our patients.

Concluding remarks

This review provides promising evidence to support the claim that the microbiome is involved in developing cardiovascular diseases and may also be a good intervention.

However, more research is required to confirm these findings further and fully understand the mechanisms involved. We also need to do more research on which interventions are more suitable for certain groups of patients in the future. In this way, microbiome modulating techniques can become a part of our clinical practice.

The Role of the Gut Microbiome in Cardiovascular Diseases