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The Potential Role of Gut Microbiota in Alzheimer’s Disease: From Diagnosis to Treatment

Department of Biology and Biotechnology, University of Pavia, 27100 Pavia, Italy
Almo Collegio Borromeo, 27100 Pavia, Italy
School of Medicine, Faculty of Clinical and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK
Emergency Medicine, Université Libre de Bruxelles, 1050 Brussels, Belgium
Department of Emergency Medicine and Surgery, IRCCS Fondazione Policlinico San Matteo, 27100 Pavia, Italy
Council for Nutritional and Environmental Medicine (CONEM), 8610 Mo i Rana, Norway
Department of Drug Sciences, University of Pavia, 27100 Pavia, Italy
Unit of Nephrology and Dialysis, ICS Maugeri, University of Pavia, 27100 Pavia, Italy
Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37121 Verona, Italy
Section of Pharmacology, Department of Drug Sciences, University of Pavia, 27100 Pavia, Italy
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Nutrients 2022, 14(3), 668;
Received: 21 January 2022 / Revised: 2 February 2022 / Accepted: 3 February 2022 / Published: 5 February 2022
(This article belongs to the Special Issue The Impact of Nutrition on Brain Metabolism and Disease)


Gut microbiota is emerging as a key regulator of many disease conditions and its dysregulation is implicated in the pathogenesis of several gastrointestinal and extraintestinal disorders. More recently, gut microbiome alterations have been linked to neurodegeneration through the increasingly defined gut microbiota brain axis, opening the possibility for new microbiota-based therapeutic options. Although several studies have been conducted to unravel the possible relationship between Alzheimer’s Disease (AD) pathogenesis and progression, the diagnostic and therapeutic potential of approaches aiming at restoring gut microbiota eubiosis remain to be fully addressed. In this narrative review, we briefly summarize the role of gut microbiota homeostasis in brain health and disease, and we present evidence for its dysregulation in AD patients. Based on these observations, we then discuss how dysbiosis might be exploited as a new diagnostic tool in early and advanced disease stages, and we examine the potential of prebiotics, probiotics, fecal microbiota transplantation, and diets as complementary therapeutic interventions on disease pathogenesis and progression, thus offering new insights into the diagnosis and treatment of this devastating and progressive disease.

1. Introduction

Alzheimer’s disease (AD), which affects approximately 50,000,000 people worldwide, is the most frequent cause of dementia, constituting a real global health problem [1]. The disease is characterized by the progressive deposition of beta amyloid (Aβ) plaques and tangles of hyperphosphorylated tau neurofibrils, leading to neuroinflammation and progressive cognitive decline [2]. Synaptic dysfunction and neuronal death are at least in part due to the excessive or non-resolving activation of the immune response and any infections or traumatic events affecting the brain (traumatic brain injury) can interfere with central immune homeostasis and accelerate the progression of the disease [3]. Although several hypotheses have been formulated about the causes of AD pathogenesis and progression, both the onset and the evolution of the disease remain not entirely clear. Therefore, although different therapeutic options have been proposed, many have failed in clinical trials and have not been found to produce significant benefits [4,5,6]. It is widely thought that an early diagnosis could be essential to act at the earliest disease stages, but effective and reproducible biomarkers are still far from clinical application [7,8].
In recent years, the gut microbiota brain axis (GMBA) has been at the center of biomedical research and it has been suggested as a potential therapeutic target for disorders affecting the central nervous system, including AD [9,10,11].
The term “gut microbiota” refers to the commensal microbial community that colonizes the gastrointestinal tract and is constituted by bacteria, fungi, archaea, viruses, and protozoans living in symbiotic relationship with our intestine [9,12,13,14]. Thanks to their active role in regulating host’s homeostasis and disease, they are becoming more and more important in the pathogenetic mechanisms of neurodegenerative disorders, such as AD [15,16,17,18]. Indeed, even though for a long time it was believed that the brain was a totally isolated organ, recent evidence shows that the gut microbiota is at the center of a bidirectional communication between intestine and brain, the so-called microbiota gut–brain axis [15,19,20,21]. This interplay involves the central nervous system (CNS), the autonomic nervous system, the enteric nervous system (ENS), and the hypothalamus-pituitary-adrenal axis (HPA), and it has been reported to be implicated in a number of physiological and pathological processes such as satiety, food intake, glucose and fat metabolism, insulin sensitivity, and stress [22]. Although the mechanisms underlying this interaction are not fully understood, targeting the microbiota might represent a new diagnostic and therapeutic strategy in AD and in other neurodegenerative diseases [23]. However, despite several published papers having reviewed possible microbiome-based therapies, to our knowledge a comprehensive view of gut microbiota-based diagnostic and therapeutic approaches is still lacking. Here, based on the main studies addressing gut microbiota dysregulation in AD, we discuss how the microbiota-derived biomarkers might be exploited for early disease detection, and we review the potentiality of probiotics, prebiotics, diet, and fecal microbiota transplantation as complementary therapeutic options for this devastating and progressive disease.

2. Main

2.1. The Gut–Brain Axis: An Overview

The gut–brain axis (GBA) consists of a signaling pathway between the gastrointestinal (GI) tract and the CNS, which allows a bidirectional communication between the two systems. Its primary role is to monitor and integrate intestinal functions as well as to link, through immune and neuro-endocrine mediators, the emotional and cognitive centers of the brain with peripheral intestinal mechanisms such as immune activation, intestinal permeability, enteric reflex, and entero-endocrine signaling [20]. In this communicating network, the brain affects gut movement, sensory, and secretion functions, and in turn the signals from the gut affect brain function [24]. This relationship is therefore of outmost importance for the maintenance of gut homeostasis, and it has been reported to be also involved in the etiology of several metabolic and mental (psychiatric and neurological) dysfunctions and disorders [21,25].
Different routes of communication between the gut microbiota and the brain have been suggested:
  • Through incoming and outgoing branches of the vagus nerve [26], which represents the major modulatory pathway [27].
  • Through the generation of metabolites and bioactive peptides (such as short-chain fatty acids) as well as the modulation of transmitters (e.g., serotonin and acetylcholine) by the microbiota [26,27,28].
  • Through the secretion of cortisol by the HPA in case of stress, which can affect intestinal motility, integrity, and mucus production, leading to changes in gut microbiota composition. This alteration, in turn, may affect the CNS through the modulation of stress hormones [28].
  • Through pro-inflammatory cytokines and chemokines [29].
  • Immunity is also critically involved. Specifically, toll-like receptors (TLRs) and peptidoglycans (PGNs) mediate the immune response towards microbes by acting as sensors of microbial components [30,31]. A local immune activation can, throughout different pathways, lead to an immune activation in different organs, including the brain [32]. This low-grade immune activation has been implicated in the pathophysiology of some forms of depression and neurodegenerative disorders such as AD and Parkinson’s disease (PD) [26].
Given this complex interplay, it is not surprising that the gut–brain axis, and therefore the gut microbiota as main component of this crosstalk, directly or indirectly affects neuropsychiatric illnesses [33].

2.2. The GMBA in Alzheimer’s Disease: What’s New?

The role of gut microbiota and GMBA in AD is of utmost importance [34]. The composition of the gut bacteria affects dramatically any age-related neurological disorder, such as AD, and mood disorders. Extrinsic factors including diet, lifestyle, or also pro-inflammatory insults, along with intrinsic components including genetic polymorphism, immunity, metabolites, and hormones, profoundly affect the composition of the gut microflora, which in turn produces signaling molecules such as short chain fatty acids (SCFAs), tryptophan, choline, and hormones (such as ghrelin, leptin) in the GI tract able to regulate CNS functions [35]. Aging has a strong impact on gut microbiota composition favoring the development of pro-inflammatory bacteria (such as Bacillus fragilis, Faecalibacterium prausnitzii, Eubacterium rectale, Eubacterium hallii, and Bacteroides fragilis) to the detriment of anti-inflammatory bacteria, a condition that induces local systemic inflammation then leading to enhanced permeability of the gastrointestinal tract, an impairment in the blood–brain barrier (BBB), finally promoting neuroinflammation. Indeed, Cattaneo et al. observed such pro-inflammatory bacteria in amyloid-positive patients when compared to healthy subjects [36]. In transgenic mice (mutant human APP) when infected with Salmonella enterica and in transgenic Caenorhabditis elegans (human Aβ42 peptide) infected with Candida albicans, the authors reported a susceptibility to further infections although they died later with respect to wild type animals. Probably, this was due to the antimicrobial activity of Aβ peptide, as the heparin-binding motif of Aβ oligomers make easier the binding to the glycosyl group of the carbohydrate moiety in the bacterial cell wall, so preventing its adhesion to the host cell and the induction of microbial agglutination [37]. Also, bacteria-derived amyloids have been reported to be causative factors for Aβ peptide aggregation in AD. For example, amyloids produced by bacteria such as curli (E. coli), TasA (Bacillus subtilis), CsgA (S. Typhimurium), FapC (Pseudomonas fluorescens), phenol soluble modulins (Staphylococcus aureus), etc., have been shown to contribute to the development of AD pathology particularly by promoting Aβ oligomers and fibrils formation [38].
Besides bacteria-derived amyloids, further components contribute to the onset and pathogenesis of AD. For instance, lipopolysaccharides (LPS) from bacteria inoculated in experimental animals (in the fourth ventricle of the brain) generated a symptomatology very akin to AD [39]. Even the injection of LPS in mice induces elevation of Aβ in the hippocampal area causing cognition defects, thus supporting the role of LPS in amyloid fibrillogenesis [40,41]. When in circulation, LPS has been found to activate the TLR4 pathway, thus triggering immune cells to secrete pro-inflammatory cytokines and IgM/IgA, exacerbating systemic inflammation [42,43,44,45]. In this perspective, gut inflammation may be a cause of AD pathogenesis.
The relationship among gut microbiome composition, inflammation, further neuroinflammation, and AD onset, is a fundamental matter of debate in AD etiopathogenesis. A certain number of investigations reported the presence of pathogens in the post mortem brains of AD patients [46,47,48,49]. Among them are herpes simplex virus type 1 and bacteria such as Chlamydophila pneumoniae, Borrelia burgdorferi, or other spirochetes [50,51,52]. Furthermore, a significant increase in the level of Helicobacter pylori-specific IgG antibodies, found in the cerebrospinal fluid and in the serum of AD patients, was reported [53]. In this context, novel therapeutic approaches can be envisaged by investigating the crucial role of some gut microbiota compositions leading to AD with the aim of promoting the prevalence of health-associated species, also adjusting both dietary habits and lifestyle, that could help to prevent disease development/progression [54,55,56].

2.3. Gut Microbiota Alterations in AD

Intestinal dysbiosis is a condition of microbial imbalance caused by an overgrowth of “bad” bacteria inside the gut, associated with potential negative outcomes such as the incorrect production of essential metabolites or even the genesis of harmful metabolites [14,57]. Although the composition of a “healthy microbiota” has not yet been defined, a balanced environment between the host and microorganisms is known to be essential to carry on the necessary immunological and metabolic functions [58]. Over the past years, dysbiosis has been reported to be implicated in the development of several disorders, such as obesity, diabetes, chronic fatigue syndrome, intestinal bowel syndrome, cancer, autoimmune diseases, depression, anxiety, PD, multiple sclerosis, amyotrophic lateral sclerosis, and other neuropsychiatric disorders [59,60,61,62,63,64,65,66,67,68,69]. Recently, many studies have shown that gut microbiota alterations directly influence cognitive decline, actively participating in AD pathogenesis and progression [36,70,71,72,73]. Generally, AD patients are often characterized by a decreased gut microbial diversity, with a significant shift in favor of pro-inflammatory taxa at the expense of the more beneficial anti-inflammatory ones, similar to what has been observed in both mouse and human aging [25,36,70,71,72,73,74,75]. For example, when fecal microbiota 16S rRNA sequencing was performed on 97 individuals [33 AD, 32 MCI (mild cognitive impaired) and 32 controls], a significant decrease in Firmicutes was accompanied with a higher Proteobacteria, Gammaproteobacteria, and Enterobacteria abundance in patients with neurodegeneration compared to healthy subjects. Interestingly, a pronounced difference in Enterobacteriaceae has been reported also between MCI and AD patients, thus indicating a progressive change in the gut microbiota composition during disease progression [72]. Similarly, Vogt et al. detected a significant dampen in Firmicutes and Bifidobacteria in the fecal samples of AD patients, and this decrease was counterbalanced by the overgrowth of Bacteroidetes species in the same individuals [70]. Alterations in the gut microbiota composition during neurodegeneration has also been reported by Zhuang et al. when comparing 43 AD patients with age- and sex-matched controls: enriched Bacteroidetes and decreased Actinobacteria at the phylum level were paralleled by enhanced Ruminococcaceae, Enterococcaceae, and Lactobacillaceae, together with less Lanchnospiraceae, Bacteroidaceae, and Veillonellaceae at the family level [76]. However, in contrast with this evidence, lower Bacteroides, Lachnospira, and Ruminiclostridium and higher levels of Prevotella have been reported in another study [77]. Although reductive, this discrepancy might be at least in part explained by the different geographical origin of the participants, since regional identity may strongly affect gut microbiota composition, as well as other comorbidities [78]. In this respect, larger studies are certainly needed to establish standard and reproducible inclusion criteria, possibly excluding also the possible confounding effect of other comorbidities.
A growing body of evidence indicates that gut microbiota dysfunctions are involved in the early disease stages of AD pathogenesis, enhancing immuno-senescence, oxidative stress, cytokine secretion, and neuroinflammation [79]. In this respect, Cattaneo et al. report that patients with AD show an increase in pro-inflammatory endobacteria species of Escherichia/Shigella and a decrease in the anti-inflammatory taxon E. rectale, and that this microbiota alteration is associated with amyloidosis and peripheral inflammation [36]. Moreover, when stool samples were collected from 108 nursing home elders and analyzed with metagenomic sequencing, a decline in butyrate-synthetizing bacteria was paralleled by a rise in pro-inflammatory taxa in AD elders, thus possibly exacerbating local and systemic inflammation [71]. Interestingly, these data have been correlated with low levels of expression of the P-glycoprotein, an essential molecule required for intestinal homeostasis, therefore indicating a clear nexus between microbiome dysregulation and intestinal inflammation [71]. These results further support the concept that changes in gut microbiota composition also reflect in alterations in intestinal function. Indeed, differences in gut microbiota population may influence tryptophan and serotonin levels in the body and may affect the synthesis of some key molecules useful for the brain, such as dopamine, norepinephrine, and brain-derived neurotrophic factor (BDNF) [80,81,82]. As mentioned, another beneficial role exerted by the gut microbiota is the production of SCFAs, including butyrate, propionate, and acetate, essential for energy production, gut epithelia homeostasis, and immune regulation [83]. When their production is altered as a consequence of dysbiosis, Aß plaques deposition, metabolic dysfunctions, and microglia dysregulation is favored, thus promoting cognitive decline [84,85,86]. Moreover, a decrease in butyrate-producing bacteria, as reported in AD, has been linked to T cell imbalance, epithelial barrier leakage (so called “leaky gut”), and increased bacterial translocation [80,87,88]. Consequently, circulating Gram negative endobacteria-derived LPS, also known as metabolic endotoxemia, triggers systemic inflammation via TLR4 and promotes BBB disruption, thus fostering neuroinflammation. [89,90]. Intestinal dysbiosis can also contribute to the increase of harmful substances such as amyloid and trimethylamine N-oxide (TMAO). TMAO is a microbial metabolite that has been recently implicated in increased formation of beta amyloid, peripheral immune response activation, enhanced oxidative stress, platelet hyperactivity, intestinal mucosal barrier dysfunction, and BBB permeability, thus promoting the consequent passage of bile acids produced by bacteria and cholesterol in the brain [91,92,93,94,95]. Finally, the ability of some endobacteria to produce gaseotransmitter molecules, such as nitric oxide (NO), hydrogen (H2), ammonia (NH3), methane (CH4), and hydrogen sulfide (H2S) seems to be fundamental for the proper neuronal function, and its alteration participates to AD pathogenesis [96,97]. Overall, these data indicate that the dialogue between gut microbiota and brain is much more complicated than previously thought, and only its entire understanding can provide insights into new diagnostic and therapeutic interventions.

2.4. Gut Microbiota-Based AD Biomarkers

One of the major concerns in AD research is to find predictive, sensitive, non-invasive accurate, and accessible biomarkers for early disease diagnosis [98,99]. Although many studies focus on fluid biomarkers for early disease detection, we are still far from having found an effective and consistent assay to be used in the clinical practice [100]. As mentioned above, the gut microbiota has emerged as a key player in regulating both physiological and non-physiological conditions, thus gut microbiota-related biomarkers may represent a promising alternative/complementary tool to assess disease conditions [101]. Indeed, although initially hypothesized for gastrointestinal disorders [102], gut microbiome-derived biomarkers have also been considered for psychological and neurodegenerative diseases (i.e., bipolar disorder, multiple Sclerosis, and PD), reporting powerful predictivity and differential diagnosis ability [103,104,105]. Regarding AD, promising results have recently been obtained, and Table 1 summarizes the main findings [72,73,106,107,108,109,110,111,112,113,114,115] (Table 1). Whilst species of Prevotella and Helicobacter have been shown to be significantly different between APP/PS1 transgenic mice and controls, Actinobacteria and TM7 phylum seem to be more accurate in diagnosing AD when using the triple transgenic mouse model [106,107,109]. Changes in beta diversity and variations in circulating metabolites involved in inflammatory pathways and metabolism of nucleotides, lipids, and sugars (i.e., glutamate, hypoxanthine, thymine, hexanoyl-CoA, and leukotrienes) have also been considered in the same studies, showing promising results [106,107]. Remarkably, when the gut microbiota of APP/PS1 mice at different ages was compared to matched controls, huge shifts in the abundance of the families Proteobacteriaceae, Verrucomicrobiaceae, Bifidobacteriaceae, Erysipelotrichaceae, Prevotellaceae, Bacteroidaceae, and Rikenellaceae could be detected far before any plaque deposition in the brain, suggesting a great potentiality for early diagnosis [110]. Although nowadays, mice clearly represent the most used animal model, some evidence obtained with Drosophila melanogaster indicate Wolbachia as a potential AD biomarker, while Stenotrophomonas appears to exert a beneficial role in preventing neurodegeneration [111].
In humans, when a cohort of individuals with AD and/or MCI were compared to healthy controls, significant differences in microbial diversity and in the fecal and blood abundance of 11 genera were observed [112,113]. Importantly, Li et al. report no major variation in the analyzed gut microbiota biomarkers between MCI and AD groups, suggesting a better ability in early detection rather than in clinical progression monitoring [113]. Similarly, cerebrospinal fluid levels of the gut microbiome-dependent metabolite TMAO were not different in AD compared to MCI patients, although significantly higher than controls [114]. On the contrary, other studies report the capability of some biomarkers (i.e., Enterobacteriaceae, SCFAs, and indole-3-pyruvic acid abundance) to clearly differentially diagnose between a mild symptomatic disease (MCI) and a more advanced stage, thus leaving the debate open [72,115]. Other suggestions might come from the evidence of a progressive shift from Faecalibacterium to Bifidobacterium genera in AD, thus offering the possibility to follow the ratio of butyrate/lactate producing genera as a disease marker of neurodegeneration [73]. Although the data are still limited, it would be interesting to see the results of the currently undergoing Emory Healthy Aging and Emory Healthy Brain Studies, aimed at following 50–75 years old individuals (without AD or any other cognitive impairment), to identify early disease biomarkers, comprised the gut microbiome ones [116]. Biosignatures from the gut microbiota might also be exploited for patients’ stratification and therapy in clinical trials aimed at applying precision medicine in AD treatment, but the information remains for now limited [117]. Finally, although our review focuses on the gut microbiota, it is important to mention that oral microbiota has been implicated in AD pathogenesis and might also represent a source of novel salivary biomarkers in AD, possibly in a combinatorial approach with the gut microbiota ones [118,119,120,121,122].
Although these preliminary data may appear promising, several limitations still exist and must be accounted. First, when looking for a new biomarker, large cohorts should always be preferred over smaller ones, and the evidence obtained should be confirmed on a validating group [100]. Secondly, since the gut microbiome composition changes widely according to nationality, lifestyle, and dietary habits, it is not often easy to distinguish between real evidence and confounding factors, thus questioning the relevance of the results [123]. Additionally, the importance of age- and gender-matched control groups should not be underestimated, and the respective cohorts should be designed accordingly [100]. To partially solve these limitations, a combination of different biomarkers could be adopted. For example, Zhang et al. report how gut microbiota composition, serum miRNAs and dietary quality scores can be used together to improve reproducibility and consistency [112]. In this respect, it would be interesting to investigate whether SCFAs, in combination with other fluid biomarkers, might prove effective in disease diagnosis and clinical monitoring, as some evidence already suggested [108].
Overall, although there are still some limitations, these data indicate that gut microbiota-based biomarkers might represent an alternative and/or an integration to the existing ones and should encourage scientists to plan larger investigations in humans.

2.5. Prebiotics

Prebiotics are non-digestible organic substances (i.e., short-chain carbohydrates) capable of selectively stimulating the growth and/or activity of one or a limited number of beneficial bacteria present in the gut [124]. Being used as food from the gut microbiota, they stimulate the production of SCFAs, thus influencing both gastrointestinal and extra-intestinal functionality [125]. A growing body of evidence suggests their potentiality as adjuvant therapy in different neurological and psychiatric conditions, such as anxiety, depression, and PD [126]. Recently, some studies are also considering the use of prebiotics for AD prevention/therapy, with promising results [124,126,127,128,129,130,131,132,133,134,135,136]. For example, yeast beta glucans administration to mouse models of AD proved effective in re-establishing the balance between pro-inflammatory and anti-inflammatory gut microbiome species, promoting SCFAs production and limiting neuroinflammation and insulin resistance [127]. Reduced neuroinflammation and improved short-term memory and cognitive ability in mice resembling AD features were also reported upon pre-treatment with lactulose and melibiose, two trehalose analogues, possibly via enhanced autophagy function [129]. Furthermore, 5xFAD mice fed for eight weeks with mannan oligosaccharide were shown capable of favoring the growth of Lactobacillus species and decreasing Helicobacter abundance, therefore preventing LPS leakage and intestinal epithelial barrier and BBB dysfunctions [130]. Interestingly, this prebiotic-driven reshaping of the gut microbiota was also accompanied by reduced Aβ accumulation in different brain areas (i.e., cortex, hippocampus, and amygdala), re-established redox homeostasis, and increased butyrate levels [130]. Similar results were also obtained in both rats and mice models of AD via oral administration of Marinda officinalis-derived oligosaccharides, reporting improved memory and learning ability, together with a decrease in plaque formation, oxidative stress, and overall inflammation [134,135]. Although the mechanism of action of the above-mentioned prebiotics is not totally clear, the capability of these molecules to sustain gut microbiota diversity and stability might be at the basis of these improvements [127,132,134]. This hypothesis is reinforced by recent evidence showing that a combination of probiotics and prebiotics (so-called synbiotics) seems to be more effective in increasing neurogenesis and reducing local and systemic inflammation compared to prebiotics alone [132].
Regarding humans, data on a large multi-ethnic longitudinal study comprising 1837 elderly people with no evidence of neurodegeneration have shown that daily administration of fructan, a well-known prebiotic, reduces the risk of AD development, confirming the previous evidence in mice [131]. However, despite this study being conducted normalizing for age, gender, recruitment time, ethnicity, daily caloric intake, education, and APOE genotype, other authors point out that the evidence for the use of prebiotics in the clinical practice still lacks robustness [133]. Altogether, these data suggest that prebiotics may be helpful as preventative/adjuvant therapy for AD, but more human clinical trials are needed before drawing any conclusion.

2.6. Probiotics

In 1965, Lilly and Stillwell introduced for the first time in the literature, the term “probiotics”, defining them as “living microorganisms with a low or zero pathogenicity that provide beneficial effects on the health of the host” [137]. Studies on human and animal models have shown that probiotics can modulate intestinal ecosystem homeostasis, regulate intestinal epithelial functions by helping to maintain the epithelial barrier, producing SCFAs, supporting cell survival, enhancing protective immune response, and inhibiting the production of pro-inflammatory cytokines [83,138,139,140,141,142,143,144,145,146,147]. Many of these responses arise from the regulation of specific intracellular signaling ways by probiotics, such as mitogen-activated protein kinases (MAPK) and nuclear factor (NF) -κB in intestinal epithelial cells [83,138,139,140,141,142,143,144,145,146,147]. Probiotic bacteria, through the modulation of the intestinal microbial ecosystem, have shown capable of playing an important role in immune response regulation by Th1, Th2, Th17, Treg cells, and NK and B cells stimulation [148]. Several studies have also confirmed the anti-inflammatory capacity of specific probiotics, by modulating the cytokine network and the macrophage tissue pattern, to reduce the mucosal inflammatory process and modulate the local immune response [149].
Probiotics can also modulate the gut–brain axis. The so-called psychobiotics, a new class of probiotics with potential applications in the treatment of psychiatric diseases, are able to modulate the bidirectional communication between brain and gut through the modulation of neurotransmitters and proteins, including gamma-aminobutyric acid, serotonin, glutamate, and the brain-derived neurotrophic factor, which play important roles for the functionality of our central nervous system, mood, cognitive functions, learning and memory processes [150,151,152,153]. The administration of a probiotic mixture modified the gut microbiota in an animal model of AD by increasing Actinobacteria and Bacteroides with a significant impact on the enhancement of long-term memory, inflammation, and neural plasticity [154]. Mitochondrial dysfunction, excessive production of reactive oxygen species, and increased apoptosis have been implicated in the pathogenesis of AD. In this respect, several studies have highlighted the role of superoxide anion, hydroxyl radical, hydrogen peroxide, and nitric oxide in neurodegeneration mediated by oxidative stress in AD [155,156]. Recently, a study on transgenic AD mice demonstrates that the administration of a probiotic formulation (SLAB51) significantly reduces oxidative stress by inducing SIRT-1-dependent mechanisms [157]. In addition, the probiotic integration of a multispecies mixture of Lactobacillus and Bifidobacterium has proven capable of modifying specific brain metabolites such as γ-aminobutyric acid and glutamate [158]. Immune response and neural inflammation were also suppressed after probiotic integration with short A1 strain of Bifidobacterium [159]. Furthermore, the integration of L. acidophilus, L. fermentum, B. lactis, and B. longum improved learning disability and oxidative stress of rats subjected to intra-hippocampal injection of Aβ1-42 [160].
Although these studies on animal models show that probiotics may play an important role in two-way communication between gut and brain and support the potential role of probiotics in improving cognitive health, the results of clinical studies in subjects with AD or MCI are controversial.
In a recent randomized, double-blind, clinically controlled trial, 60 AD patients were divided into two groups and administered milk (control group) or probiotics (probiotic group). After 12 weeks of daily administration of 200 mL of a mixture of Lactobacillus acidophilus, Lactobacillus casei, Bifidobacterium bifidum, and Lactobacillus fermentum, a significant improvement in the mini-mental state exam (MMSE) score was reported compared to controls (p < 0.001). Changes in plasma malondialdehyde, serum C-reactive protein, beta cells function, serum triglycerides, and differences in the quantitative control index of insulin sensitivity were also improved in the individuals receiving the probiotic mixture [161]. Similarly, data from another meta-analysis report a significant amelioration in cognition and a consistent reduction in post-intervention levels of malondialdehyde and high sensitivity C-reactive protein in subjects receiving probiotics compared to controls [162]. Although these results indicate potential benefit of probiotics in the management of patients with AD, other studies show contrary data. For example, in a recently published randomized, double-blind, placebo-controlled clinical trial, AD patients (between 65 and 90 years old) were supplemented with placebo (control group, n = 23, 13 females and 10 males) or a probiotic mixture (probiotic groups, n = 25, 18 females and 7 males). Two different probiotic capsules were used in this study: one containing Lactobacillus fermentum, Lactobacillus plantarum, and Bifidobacterium lactis, and one containing Lactobacillus acidophilus, Bifidobacterium bifidum, and Bifidobacterium longum. After 12 weeks of alternate day administration, the levels of proinflammatory (TNF-α and IL-6) and anti-inflammatory (IL-10) cytokines, as well as the levels of oxidizing (MDA and 8-OHdG) and antioxidants factors (TAC, GSH), were not significantly changed between the two groups. Of note, no improvements in cognitive functions were reported in the probiotic group compared to the placebo one, suggesting insensitivity to probiotic supplementation for severe AD patients [163].
In conclusion, even if there are several studies that show the influence of gut microbiota in neurological and psychiatric pathologies, the mechanisms of action and the effects of probiotics rest largely unknown, and several gaps and inconsistences remain. Therefore, human studies need to be further developed and need to include analysis of the gut microbiota composition in specific populations of patients by identifying probiotic bacteria strains able to significantly affect gut–brain axis and assess their safe use.

2.7. Diet

Diet is a rapid and direct way of modifying the gut microbiota composition and function, reducing inflammation, and helping in eubiosis maintenance [123,164,165]. Given the evidence of association between neuropsychiatric conditions and gut microbiota dysregulation, it is worth speculating that dietary interventions could represent effective candidates for preventing and delaying the pathogenesis and progression of AD [166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186] (Table 2). Here, we present some of the most promising dietary therapies proposed in the literature, with a particular focus on Mediterranean and ketogenic diets.

2.7.1. Mediterranean, DASH (Dietary Approaches to Stop Hypertension), and MIND (Mediterranean-DASH Intervention for Neurodegenerative Delay)

The renowned and ancient Mediterranean diet (Medi), rich in vegetables, fruit, whole grains, nuts, olive oil, moderate consumption of fish and poultry and limited consumption of red meat and sweets, have been extensively described for their protective role against non-communicable diseases [187]. DASH diet (Dietary Approaches to Stop Hypertension), designed for hypertension treatment, overlaps the Medi diet in composition, with more attention on salt introduction (less than 2.4 g/day) [188]. Similarly, MIND diet (Mediterranean-DASH Intervention for Neurodegenerative Delay) is a combination of both, DASH and Medi, specifically developed to delay neurodegeneration. Besides being rich in fruits, vegetables and legumes, the MIND includes the consumption of single dietary components, i.e., green leafy vegetables and berries, which have displayed a superior effect against cognitive impairment and decline compared to other vegetables and fruits [189].
Although Randomized Clinical trials (RCT) and Observational Cohort Studies (ObS) have been conducted to unravel the potential therapeutic effect of Medi, DASH, and MIND in AD, the results are still unclear [166]. Two large RCT conducted in Spain in 2013 and 2015 have demonstrated a positive correlation between ‘Medi diet plus olive oil’ or ‘Medi diet plus nuts’ with cognitive performance [190,191]. More recently, an additional RCT study also associated Medi diet with improved cognition [192]. However, differential results from another RCT did not show any significant association [193]. Further narrative, systematic reviews, and meta-analyses have evidenced the protective and promising therapeutic role of Medi diet in AD disease, confirming its ability to hinder cognitive impairment [167,169]. Generally, any dietary pattern rich in fruits, vegetables, and legumes and poor in saturated fats and sweets seems to provide protective effects [194]. Similarly, results presented by Barbaresko et al. on 20 systematic reviews and meta-analyses, highlighted the benefits of the Medi diet as a protective factor for AD [195].
So far, besides promising results for Medi diet, the role of DASH diet in AD prevention and therapy is still unveiled [168], and more studies should be carried out before driving any conclusion. Moreover, standard tools for assessing food intake and cognitive decline are needed to state which dietary pattern might be the most effective in protecting and delaying the onset of neurodegenerative diseases, and to ensure reproducibility [166].
Concerning MIND diet, Morris at al. were the first to show that a moderate adherence to this dietary habit slows cognitive decline compared to a moderate adherence to Medi and DASH diets; however, they have also confirmed that a high adherence to Medi and DASH diets can reduce AD risk [189]. Potential neuroprotective mechanisms shared by those dietary regimes are the presence of antioxidant and anti-inflammatory compounds, which contribute to a reduction in brain inflammation and oxidative stress, high abundances of fibers, vitamin C, beta-carotene, and folate, which lead to a better brain integrity and increase in brain tissue volume [196,197]. Also, the scarcity in saturated and trans fatty acids can reduce BBB dysfunction and amyloid aggregation [183,198,199].
A significant improvement in cognition was also reported among older adults following the MIND diet, confirming the effectiveness of this approach [170]. Despite those findings, the lack of evidence on the correlation between MIND diet and brain-related mechanisms, and given the similarities with the Medi and DASH diets in terms of nutrients composition, MIND diet cannot be disclosed as more proactive than Medi and DASH diets.
On the whole, as previously mentioned, the protective and potential therapeutic effect of Medi (and similar diets) might be based on the consumption of much food rich in vitamins and polyphenols, i.e., fruits, vegetables, legumes and whole grains, a moderate amount of fish, and less meat and food rich in trans and saturated fats. Regarding meat, so far, the majority of the studies did not report any significant association with cognitive impairment or decline [177]. Differently, fish intake is inversely associated with AD—likely related to omega-3 (EPA/DHA) contents [195]. Interestingly, the regular consumption of fish up to two portions per week seems to be more protective than EPA/DHA supplementation [184]. Even though many studies are supporting the protective effect of unsaturated fatty acids EPA/DHA, their role in the brain is still under debate [200,201,202,203,204]. Medi diet is also connected to an improved lipid profile. Overall, lipid dysregulation might contribute to AD pathogenesis, enhancing synaptic loss, BBB dysfunction, mitochondrial disruption, oxidative stress, and inflammation [198,205]. Indeed, in large longitudinal studies, high levels of triglycerides and cholesterol in the serum are significantly associated with cognitive impairment [178]. Again, a recent cross-sectional study with 689 participants including AD and healthy patients, revealed that reduced levels of triglycerides were related to better cognitive performance and a reduction in brain dysfunction and atrophy [206]. In conclusion, even if the interplay between dietary lipids and AD pathogenesis is not straightforward, Medi diet with consequent improvement in lipid dysregulation through dietary changes is strongly recommended.
Dietary regimens based on a daily integration of the essential nutrients and vitamins are also of interest, but the data remain limited. Cross-sectional and longitudinal cohort studies on vitamins C and E consumption showed promising effects in reducing cognitive decline, but no difference has been identified in intervention trials [182]. Similarly, low levels of vitamin D in the serum seem to be associated with an increased risk of cognitive decline, but its supplementation did not provide any difference [182]. Vitamin B (folic acid, pyridoxine, and cobalamin) consumptions lead to ambiguous results, with only a few RTC displaying beneficial effects in slowing the cognitive decline [182]. Finally, even though vitamin A supplementation might reduce the risk of cognitive decline, there are not enough consistent data to confirm its protective and therapeutic effect in AD [182]. Overall, it seems that some vitamin supplementation might delay the progression of AD and dementia; nonetheless, due to the lack of statistically significant results and limited scientific evidence analyzing the role of vitamins in older adults [167,185], it is not possible, at least until now, to point out their specific protective and therapeutic effects in AD.
Besides micronutrients and omega-3, further nutritional formula including ginseng, inositol, and coconut oil have been recently studied as potential therapy in AD patients, but the effects are inconclusive [176].
Polyphenols are receiving growing interest in AD research due to their antioxidant, anti-inflammatory, and neurotrophic properties supported by preclinical evidence. Nonetheless, so far, there is no conclusive evidence on the association between polyphenols and AD in humans. On 24 RCT conducted on AD patients exposed to polyphenols (mainly flavonoids), only 12 have shown a reduction in cognitive decline [181]. Again, further trials carried out in people with mild cognitive impairment consuming grape juice or blueberries rich in polyphenols showed minimal benefits in memory or no significant results [179,180]. A polyphenol that might contribute to neuroprotection is resveratrol. This phenolic compound promotes synthesis of glutamate receptors, enhances synaptic transmission, activates SIRT1, exerts antioxidant and anti-inflammatory actions [186,207]. Results from in vitro and in vivo (mice and rats) studies underscored resveratrol as a potential treatment for AD; however, its effectiveness is only partially understood in humans [208]. Although some research groups have performed trials in humans to test the potential protective effect of resveratrol, results have failed to demonstrate a positive correlation. The lack of a substantial number of clinical trials and issues related to clinical applications, e.g., dosage, bioavailability, side effects, etc., emphasize the need of further investigation [186].

2.7.2. Ketogenic Diet

Ketogenic diet (KD) is a nutritional program rich in fats and low in carbohydrates and proteins (ideally, 90% fat, 4% carbohydrates, 6% proteins) developed in the early 1990s as a treatment for epilepsy, with numerous studies consistently supporting its effectiveness [209]. Recently, the application of KD as potential treatment for other neurological diseases, such as PD and AD, has been investigated in vitro and in vivo [210,211,212]. The sugar-shortage leads the body to break down and oxidate fats with the production of ketone bodies, used as an alternative energy-substrate to glucose by many organs, including the brain [213]. In mice models, ketone bodies influence neurotransmission, channels modulation, increase BDNF, reduce neuroinflammation and oxidative stress, improve mitochondrial functions, reduce amyloid accumulation, and improve learning and memory abilities [213,214,215,216]. In humans, results from RCT reported that KD might be beneficial in people with mild cognitive impairment or AD [171,172]. Similar to KD in terms of mechanisms (i.e., ketone bodies production), medium-chain triglyceride (MCT) diet/supplementation and the modified Atkins diet are effective in counteracting cognitive decline in AD, symptoms such as fatigue and daytime sleepiness in PD, epileptic seizures and mood swings in depression [173,174,175,217,218]. Moreover, the modified Atkins diet, which does not restrict protein intake as the KD protocol, allows a much more nutritional flexibility than classic KD. Indeed, overall, dietary patterns that lead to ketone bodies production seem to represent a promising therapy for AD, but more investigation to unveil protective mechanisms in humans and adverse aspects is needed—including the lack of flexibility and variability of the alimentary regimen easily leading to a drop-out, the scarcity of plant-based food rich in vitamins, and other antioxidant compounds [219].
Even if further well-designed human clinical trials are needed to better understand the role of diet for the prevention and treatment of AD, up to now, most of the diet-related beneficial effects in AD patients seem to be in favor of the Medi diet. Vitamins and other phenolic compounds might represent potential boosts for AD patients.

2.7.3. The Role of Diet in AD Mediated through Gut Microbiota

Diet is the most impactful modulator of gut microbiota across lifespan. Considering that, as previously mentioned, AD is associated with changes in microbiota composition, it is reasonable to assume that dietary interventions, and the related gut microbiota composition shifts, might constitute a future complementary tool to prevent or manage dementia. However, the proof of a cause–effect relationship among gut microbiota, diet, and neurodegeneration is very poor, with a low number of clinical studies analyzing the interplay among those elements.
Current evidence shows that the Medi diet beneficially impacts the gut microbiota composition in elderly adults reducing frailty [220,221]. The abundance of specific “protective” taxa (e.g., Faecalibacterium or Roseburia) was positively associated with improved cognitive function and negatively associated with pro-inflammatory markers, possibly related to an increase in SCFAs [165]. Medi diet is rich in polyphenols, and emerging evidence supports the beneficial role of polyphenols in preventing and/or ameliorating AD progression, reducing plaques formation and protecting blood brain barrier disruption [222]. Wine polyphenols, for instance, may lead to an increase in Bacteroides, Bifidobacteria, and Lactobacilli, re-storing a ‘healthy’ microflora composition in AD patients [223].
Improvement in the microbiota profile as a result of KD was initially showed in preclinical animal models, where mice subjected to KD diet displayed an increase in Akkermansia and Lactobacillus and a parallel enhancement in vascular brain function [224]. An interventional study, where MCI patients followed a modified Medi-KD, demonstrated that dietary regimen positively affects the gut microbiota composition, with an increase in the abundance of Enterobacteriaceae, Akkermansia, Christensenellaceae, and in SCFAs production, with a consequent improvement in cognitive symptoms [225]. Nonetheless, while a recent study in an animal model of AD revealed that KD might exacerbate gut dysbiosis, a diet rich in carbohydrates seemed to improve the microbiota profile with an increase in Bacteroidetes and a reduction in Proteobacteria [226,227]. Dietary patterns that allow not-refined carbohydrates consumption, but still lead to ketone bodies production, e.g., intermitting fasting, might be a promising protective dietary strategy for dementia [226].
Decoding the interplay between microbiota and diet in neurogenerative disease patients seem to be promising; however, all the multi-faceted aspects of dietary patterns on human health should be examined in depth, considering the body as a superorganism, made of human and microbial cells.

2.8. Fecal Microbiota Transplantation

Fecal microbiota transplantation (FMT) is a procedure where a solution of fecal material from a donor is transferred (through colonoscopy, nasogastric tube, or oral pills) into the intestinal tract of a recipient, aimed at directly changing the gut microbiota composition [227]. Reprogramming the gut microbiota eubiosis by FMT has been already used to successfully treat C. difficile infections and could be an innovative therapy for various neurological diseases in an imminent future [228]. So far, most of the limited number of studies have been conducted in mice/rats, with promising but not conclusive results (Table 3) [10,229,230,231,232,233,234,235,236,237,238,239].
Impaired neurogenesis, decreased BDNF expression, increased memory impairment, enhanced circulating pro-inflammatory cytokines, and Aβ plaques deposition were detected when feces from AD-model donor mice were transplanted in healthy mice [231,233]. Moreover, FMT from senescence-accelerated mice or from senescence-accelerated-resistant mice into germ-free (GF) mice revealed significant differences on behaviors, cognitive performance, and gut microbiota composition, with a better profile in recipient mice receiving the microbiota from senescence-accelerated-resistant donors compared to senescence-accelerated mice [236]. Similarly, GF mice receiving fecal material from APPPS1 transgenic mice developing cerebral Aβ-deposition showed an increase in plaques formation [234,235]. When FMT was carried out from an AD patient into GF mice, accelerated cognitive decline and a decrease in microbiota-derived metabolites important for the nervous system function were reported [235].
Successfully, researchers confirmed that interventions aimed at manipulating gut microbiota influence brain disorders. Indeed, transplanting healthy fecal microbiota from wild-type mice to mouse models of AD documented a decrease in cognitive impairment, amyloid accumulation, and circulating levels of pro-inflammatory markers [10]. Improved cognition, reduced amyloid accumulation and tau expression, enhanced synaptic plasticity, and increased SCFAs-producing gut endobacteria were also confirmed in another study [232]. Dodiya et al. reported the effectiveness of FMT in restoring microbiota composition in the APP/PS1 transgenic mouse model of AD, improving microglia and Aβ deposition profile [237].
Regarding humans, only two case-studies showing promising results have been conducted so far [229,230]. Hazan et al. demonstrated an improvement in AD symptoms (cognitive function, memory, and mood) in a 82-year-old man after FMT from a 85-year-old woman (recipient’s wife) [229]. A second case-study, involving a 90-year-old woman with AD and severe C. difficile infection who received FMT from a 27-year-old healthy man, also showed an improvement in cognitive function, microbiota diversity, and SCFAs production [230].
Despite the potential application of FMT in AD treatment, several limitations still exist. Standardization of the therapeutic protocols, timings and length of administration, short and term risks, and inclusion criteria are all points that should be considered and addressed [68,240,241,242,243,244].
In conclusion, although the promising results obtained in mice certainly prove that the gut microbiota is involved in the pathogenesis and progression of neurological diseases, more human studies are needed before pointing out FMT as an AD complementary therapy.

3. Conclusions

AD is a neurodegenerative disorder, often occurring in the elderly, which has a fundamental causative source in the impairments in the GMBA. Recent data, which are to be further deepened and improved in any investigation planning, reported to date a close relationship between gut microbiota composition (then affected by nutritional habits) and AD onset, usually derived from neuroinflammation caused by bacteria products or bacterial brain migration, a circumstance that normally occurs to contribute to the regulation of brain synaptogenesis and development, besides mood and cognition evolution. Given the close cross talk between gut bacteria and brain, here we reviewed that gut microbiota dysregulations, often reported in AD patients, can be exploited to investigate both new diagnostic and therapeutic approaches for this devastating disease. However, despite promising results have been published, more research is needed to limit interstudy inconsistencies and enhances reproducibility before considering a clinical application.

Author Contributions

Conceptualization, A.V. and G.R.; Writing—original draft preparation, A.V., G.B.P., E.P., M.R., S.C., G.B., A.O. and C.A.; Writing—review and editing, A.V. and A.P.; Supervision, A.P., C.E. and G.R. All authors have read and agreed to the published version of the manuscript.


This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.


We kindly thank the Department of Internal Medicine and Therapeutics of the University of Pavia, Pavia, Italy, and MR MEDICA SRL for supporting the publication costs.

Conflicts of Interest

The authors declare no conflict of interest.


  1. Hodson, R. Alzheimer’s Disease. Nature 2018, 559, S1. [Google Scholar] [CrossRef] [PubMed][Green Version]
  2. Mattson, M.P. Pathways towards and away from Alzheimer’s Disease. Nature 2004, 430, 631–639. [Google Scholar] [CrossRef] [PubMed][Green Version]
  3. Ashraf, G.M.; Tarasov, V.V.; Makhmutova, A.; Chubarev, V.N.; Avila-Rodriguez, M.; Bachurin, S.O.; Aliev, G. The Possibility of an Infectious Etiology of Alzheimer Disease. Mol. Neurobiol. 2019, 56, 4479–4491. [Google Scholar] [CrossRef] [PubMed]
  4. Oxford, A.E.; Stewart, E.S.; Rohn, T.T. Clinical Trials in Alzheimer’s Disease: A Hurdle in the Path of Remedy. Int. J. Alzheimers Dis. 2020, 2020, 1–13. [Google Scholar] [CrossRef][Green Version]
  5. Yaari, R.; Hake, A. Alzheimer’s Disease Clinical Trials: Past Failures and Future Opportunities. Clin. Investig. 2015, 5, 297–309. [Google Scholar] [CrossRef]
  6. Rosenblum, W.I. Why Alzheimer Trials Fail: Removing Soluble Oligomeric Beta Amyloid Is Essential, Inconsistent, and Difficult. Neurobiol. Aging 2014, 35, 969–974. [Google Scholar] [CrossRef]
  7. Ausó, E.; Gómez-Vicente, V.; Esquiva, G. Biomarkers for Alzheimer’s Disease Early Diagnosis. J. Pers. Med. 2020, 10, 114. [Google Scholar] [CrossRef]
  8. Rasmussen, J.; Langerman, H. Alzheimer’s Disease—Why We Need Early Diagnosis. Degener. Neurol. Neuromuscul. Dis. 2019, 9, 123–130. [Google Scholar] [CrossRef][Green Version]
  9. Cryan, J.F.; O’Riordan, K.J.; Cowan, C.S.M.; Sandhu, K.V.; Bastiaanssen, T.F.S.; Boehme, M.; Codagnone, M.G.; Cussotto, S.; Fulling, C.; Golubeva, A.V.; et al. The Microbiota-Gut-Brain Axis. Physiol. Rev. 2019, 99, 1877–2013. [Google Scholar] [CrossRef]
  10. Kim, M.-S.; Kim, Y.; Choi, H.; Kim, W.; Park, S.; Lee, D.; Kim, D.K.; Kim, H.J.; Choi, H.; Hyun, D.-W.; et al. Transfer of a Healthy Microbiota Reduces Amyloid and Tau Pathology in an Alzheimer’s Disease Animal Model. Gut 2020, 69, 283–294. [Google Scholar] [CrossRef]
  11. Long-Smith, C.; O’Riordan, K.J.; Clarke, G.; Stanton, C.; Dinan, T.G.; Cryan, J.F. Microbiota-Gut-Brain Axis: New Therapeutic Opportunities. Annu. Rev. Pharmacol. Toxicol. 2020, 60, 477–502. [Google Scholar] [CrossRef] [PubMed][Green Version]
  12. Rhee, S.H.; Pothoulakis, C.; Mayer, E.A. Principles and Clinical Implications of the Brain–Gut–Enteric Microbiota Axis. Nat. Rev. Gastroenterol. Hepatol. 2009, 6, 306–314. [Google Scholar] [CrossRef] [PubMed][Green Version]
  13. Sonnenburg, J.L.; Sonnenburg, E.D. Vulnerability of the Industrialized Microbiota. Science 2019, 366, eaaw9255. [Google Scholar] [CrossRef][Green Version]
  14. Pascale, A.; Marchesi, N.; Marelli, C.; Coppola, A.; Luzi, L.; Govoni, S.; Giustina, A.; Gazzaruso, C. Microbiota and Metabolic Diseases. Endocrine 2018, 61, 357–371. [Google Scholar] [CrossRef] [PubMed]
  15. Kowalski, K.; Mulak, A. Brain-Gut-Microbiota Axis in Alzheimer’s Disease. J. Neurogastroenterol. Motil. 2019, 25, 48–60. [Google Scholar] [CrossRef][Green Version]
  16. Liu, S.; Gao, J.; Zhu, M.; Liu, K.; Zhang, H.-L. Gut Microbiota and Dysbiosis in Alzheimer’s Disease: Implications for Pathogenesis and Treatment. Mol. Neurobiol. 2020, 57, 5026–5043. [Google Scholar] [CrossRef]
  17. Burokas, A.; Moloney, R.D.; Dinan, T.G.; Cryan, J.F. Microbiota Regulation of the Mammalian Gut–Brain Axis. Adv. Appl. Microbiol. 2015, 91, 1–62. [Google Scholar]
  18. de J.R. De-Paula, V.; Forlenza, A.S.; Forlenza, O.V. Relevance of Gutmicrobiota in Cognition, Behaviour and Alzheimer’s Disease. Pharmacol. Res. 2018, 136, 29–34. [Google Scholar] [CrossRef]
  19. Stilling, R.M.; Dinan, T.G.; Cryan, J.F. Microbial Genes, Brain & Behaviour—Epigenetic Regulation of the Gut-Brain Axis. Genes Brain Behav. 2014, 13, 69–86. [Google Scholar] [CrossRef]
  20. Carabotti, M.; Scirocco, A.; Maselli, M.A.; Severi, C. The Gut-Brain Axis: Interactions between Enteric Microbiota, Central and Enteric Nervous Systems. Ann. Gastroenterol. 2015, 28, 203–209. [Google Scholar]
  21. Kaur, G.; Behl, T.; Bungau, S.; Kumar, A.; Uddin, M.S.; Mehta, V.; Zengin, G.; Mathew, B.; Shah, M.A.; Arora, S. Dysregulation of the Gut-Brain Axis, Dysbiosis and Influence of Numerous Factors on Gut Microbiota Associated Parkinson’s Disease. Curr. Neuropharmacol. 2020, 19, 233–247. [Google Scholar] [CrossRef] [PubMed]
  22. Heck, A.L.; Handa, R.J. Sex Differences in the Hypothalamic–Pituitary–Adrenal Axis’ Response to Stress: An Important Role for Gonadal Hormones. Neuropsychopharmacology 2019, 44, 45–58. [Google Scholar] [CrossRef][Green Version]
  23. Cerovic, M.; Forloni, G.; Balducci, C. Neuroinflammation and the Gut Microbiota: Possible Alternative Therapeutic Targets to Counteract Alzheimer’s Disease? Front. Aging Neurosci. 2019, 11, 284. [Google Scholar] [CrossRef][Green Version]
  24. Wang, H.-X.; Wang, Y.-P. Gut Microbiota-Brain Axis. Chin. Med. J. 2016, 129, 2373–2380. [Google Scholar] [CrossRef]
  25. Pascale, A.; Marchesi, N.; Govoni, S.; Barbieri, A. Targeting the Microbiota in Pharmacology of Psychiatric Disorders. Pharmacol. Res. 2020, 157, 104856. [Google Scholar] [CrossRef] [PubMed]
  26. Margolis, K.G.; Cryan, J.F.; Mayer, E.A. The Microbiota-Gut-Brain Axis: From Motility to Mood. Gastroenterology 2021, 160, 1486–1501. [Google Scholar] [CrossRef] [PubMed]
  27. Bravo, J.A.; Forsythe, P.; Chew, M.V.; Escaravage, E.; Savignac, H.M.; Dinan, T.G.; Bienenstock, J.; Cryan, J.F. Ingestion of Lactobacillus Strain Regulates Emotional Behavior and Central GABA Receptor Expression in a Mouse via the Vagus Nerve. Proc. Natl. Acad. Sci. USA 2011, 108, 16050–16055. [Google Scholar] [CrossRef] [PubMed][Green Version]
  28. Heijtz, R.D.; Wang, S.; Anuar, F.; Qian, Y.; Bjorkholm, B.; Samuelsson, A.; Hibberd, M.L.; Forssberg, H.; Pettersson, S. Normal Gut Microbiota Modulates Brain Development and Behavior. Proc. Natl. Acad. Sci. USA 2011, 108, 3047–3052. [Google Scholar] [CrossRef][Green Version]
  29. Rea, K.; Dinan, T.G.; Cryan, J.F. The Microbiome: A Key Regulator of Stress and Neuroinflammation. Neurobiol. Stress 2016, 4, 23–33. [Google Scholar] [CrossRef][Green Version]
  30. Dichter, G.S.; Damiano, C.A.; Allen, J.A. Reward Circuitry Dysfunction in Psychiatric and Neurodevelopmental Disorders and Genetic Syndromes: Animal Models and Clinical Findings. J. Neurodev. Disord. 2012, 4, 19. [Google Scholar] [CrossRef][Green Version]
  31. Banks, W.A.; Erickson, M.A. The Blood–Brain Barrier and Immune Function and Dysfunction. Neurobiol. Dis. 2010, 37, 26–32. [Google Scholar] [CrossRef] [PubMed]
  32. Silver, J.; Schwab, M.E.; Popovich, P.G. Central Nervous System Regenerative Failure: Role of Oligodendrocytes, Astrocytes, and Microglia. Cold Spring Harb. Perspect. Biol. 2014, 7, a020602. [Google Scholar] [CrossRef] [PubMed][Green Version]
  33. Kim, Y.-K.; Shin, C. The Microbiota-Gut-Brain Axis in Neuropsychiatric Disorders: Pathophysiological Mechanisms and Novel Treatments. Curr. Neuropharmacol. 2018, 16, 559–573. [Google Scholar] [CrossRef] [PubMed]
  34. Hu, X.; Wang, T.; Jin, F. Alzheimer’s Disease and Gut Microbiota. Sci. China Life Sci. 2016, 59, 1006–1023. [Google Scholar] [CrossRef] [PubMed][Green Version]
  35. Mancuso, C.; Santangelo, R. Alzheimer’s Disease and Gut Microbiota Modifications: The Long Way between Preclinical Studies and Clinical Evidence. Pharmacol. Res. 2018, 129, 329–336. [Google Scholar] [CrossRef] [PubMed]
  36. Cattaneo, A.; Cattane, N.; Galluzzi, S.; Provasi, S.; Lopizzo, N.; Festari, C.; Ferrari, C.; Guerra, U.P.; Paghera, B.; Muscio, C.; et al. Association of Brain Amyloidosis with Pro-Inflammatory Gut Bacterial Taxa and Peripheral Inflammation Markers in Cognitively Impaired Elderly. Neurobiol. Aging 2017, 49, 60–68. [Google Scholar] [CrossRef][Green Version]
  37. Kumar, D.K.V.; Choi, S.H.; Washicosky, K.J.; Eimer, W.A.; Tucker, S.; Ghofrani, J.; Lefkowitz, A.; McColl, G.; Goldstein, L.E.; Tanzi, R.E.; et al. Amyloid-β Peptide Protects against Microbial Infection in Mouse and Worm Models of Alzheimer’s Disease. Sci. Transl. Med. 2016, 8, 340ra72. [Google Scholar] [CrossRef][Green Version]
  38. Kesika, P.; Suganthy, N.; Sivamaruthi, B.S.; Chaiyasut, C. Role of Gut-Brain Axis, Gut Microbial Composition, and Probiotic Intervention in Alzheimer’s Disease. Life Sci. 2020, 264, 118627. [Google Scholar] [CrossRef]
  39. Hauss-Wegrzyniak, B.; Vraniak, P.D.; Wenk, G.L. LPS-Induced Neuroinflammatory Effects Do Not Recover with Time. NeuroReport 2000, 11, 1759–1763. [Google Scholar] [CrossRef]
  40. Kahn, M.S.; Kranjac, D.; Alonzo, C.A.; Haase, J.H.; Cedillos, R.O.; McLinden, K.A.; Boehm, G.W.; Chumley, M.J. Prolonged Elevation in Hippocampal Aβ and Cognitive Deficits Following Repeated Endotoxin Exposure in the Mouse. Behav. Brain Res. 2012, 229, 176–184. [Google Scholar] [CrossRef]
  41. Asti, A.; Gioglio, L. Can a Bacterial Endotoxin Be a Key Factor in the Kinetics of Amyloid Fibril Formation? J. Alzheimers Dis. 2014, 39, 169–179. [Google Scholar] [CrossRef] [PubMed]
  42. Lucas, K.; Maes, M. Role of the Toll Like Receptor (TLR) Radical Cycle in Chronic Inflammation: Possible Treatments Targeting the TLR4 Pathway. Mol. Neurobiol. 2013, 48, 190–204. [Google Scholar] [CrossRef] [PubMed]
  43. Mohammad, S.; Thiemermann, C. Role of Metabolic Endotoxemia in Systemic Inflammation and Potential Interventions. Front. Immunol. 2021, 11, 3379. [Google Scholar] [CrossRef] [PubMed]
  44. Maes, M.; Twisk, F.N.M.; Kubera, M.; Ringel, K.; Leunis, J.-C.; Geffard, M. Increased IgA Responses to the LPS of Commensal Bacteria Is Associated with Inflammation and Activation of Cell-Mediated Immunity in Chronic Fatigue Syndrome. J. Affect. Disord. 2012, 136, 909–917. [Google Scholar] [CrossRef] [PubMed]
  45. Maes, M.; Mihaylova, I.; Leunis, J.-C. Increased Serum IgA and IgM against LPS of Enterobacteria in Chronic Fatigue Syndrome (CFS): Indication for the Involvement of Gram-Negative Enterobacteria in the Etiology of CFS and for the Presence of an Increased Gut–Intestinal Permeability. J. Affect. Disord. 2007, 99, 237–240. [Google Scholar] [CrossRef] [PubMed]
  46. Frost, B.; Diamond, M.I. Prion-like Mechanisms in Neurodegenerative Diseases. Nat. Rev. Neurosci. 2010, 11, 155–159. [Google Scholar] [CrossRef]
  47. Emery, D.C.; Shoemark, D.K.; Batstone, T.E.; Waterfall, C.M.; Coghill, J.A.; Cerajewska, T.L.; Davies, M.; West, N.X.; Allen, S.J. 16S RRNA Next Generation Sequencing Analysis Shows Bacteria in Alzheimer’s Post-Mortem Brain. Front. Aging Neurosci. 2017, 9, 195. [Google Scholar] [CrossRef]
  48. Poole, S.; Singhrao, S.K.; Kesavalu, L.; Curtis, M.A.; Crean, S. Determining the Presence of Periodontopathic Virulence Factors in Short-Term Postmortem Alzheimer’s Disease Brain Tissue. J. Alzheimers Dis. 2013, 36, 665–677. [Google Scholar] [CrossRef]
  49. Zhao, Y.; Jaber, V.; Lukiw, W.J. Secretory Products of the Human GI Tract Microbiome and Their Potential Impact on Alzheimer’s Disease (AD): Detection of Lipopolysaccharide (LPS) in AD Hippocampus. Front. Cell. Infect. Microbiol. 2017, 7, 318. [Google Scholar] [CrossRef]
  50. Hammond, C.J.; Hallock, L.R.; Howanski, R.J.; Appelt, D.M.; Little, C.S.; Balin, B.J. Immunohistological Detection of Chlamydia Pneumoniae in the Alzheimer’s Disease Brain. BMC Neurosci. 2010, 11, 121. [Google Scholar] [CrossRef][Green Version]
  51. Miklossy, J. Bacterial Amyloid and DNA Are Important Constituents of Senile Plaques: Further Evidence of the Spirochetal and Biofilm Nature of Senile Plaques. J. Alzheimers Dis. 2016, 53, 1459–1473. [Google Scholar] [CrossRef][Green Version]
  52. Carter, C. Alzheimer’s Disease: APP, Gamma Secretase, APOE, CLU, CR1, PICALM, ABCA7, BIN1, CD2AP, CD33, EPHA1, and MS4A2, and Their Relationships with Herpes Simplex, C. Pneumoniae, Other Suspect Pathogens, and the Immune System. Int. J. Alzheimers Dis. 2011, 2011, 1–34. [Google Scholar] [CrossRef] [PubMed][Green Version]
  53. Kountouras, J.; Boziki, M.; Gavalas, E.; Zavos, C.; Deretzi, G.; Grigoriadis, N.; Tsolaki, M.; Chatzopoulos, D.; Katsinelos, P.; Tzilves, D.; et al. Increased Cerebrospinal Fluid Helicobacter Pylori Antibody in Alzheimer’s Disease. Int. J. Neurosci. 2009, 119, 765–777. [Google Scholar] [CrossRef] [PubMed]
  54. Shabbir, U.; Arshad, M.S.; Sameen, A.; Oh, D.-H. Crosstalk between Gut and Brain in Alzheimer’s Disease: The Role of Gut Microbiota Modulation Strategies. Nutrients 2021, 13, 690. [Google Scholar] [CrossRef] [PubMed]
  55. Goyal, D.; Ali, S.A.; Singh, R.K. Emerging Role of Gut Microbiota in Modulation of Neuroinflammation and Neurodegeneration with Emphasis on Alzheimer’s Disease. Prog. Neuro Psychopharmacol. Biol. Psychiatry 2020, 106, 110112. [Google Scholar] [CrossRef] [PubMed]
  56. Zhu, F.; Li, C.; Chu, F.; Tian, X.; Zhu, J. Target Dysbiosis of Gut Microbes as a Future Therapeutic Manipulation in Alzheimer’s Disease. Front. Aging Neurosci. 2020, 12, 544235. [Google Scholar] [CrossRef] [PubMed]
  57. Weiss, G.A.; Hennet, T. Mechanisms and Consequences of Intestinal Dysbiosis. Cell. Mol. Life Sci. 2017, 74, 2959–2977. [Google Scholar] [CrossRef][Green Version]
  58. Rinninella, E.; Raoul, P.; Cintoni, M.; Franceschi, F.; Miggiano, G.; Gasbarrini, A.; Mele, M. What Is the Healthy Gut Microbiota Composition? A Changing Ecosystem across Age, Environment, Diet, and Diseases. Microorganisms 2019, 7, 14. [Google Scholar] [CrossRef][Green Version]
  59. Cenit, M.C.; Sanz, Y.; Codoñer-Franch, P. Influence of Gut Microbiota on Neuropsychiatric Disorders. World J. Gastroenterol. 2017, 23, 5486–5498. [Google Scholar] [CrossRef]
  60. Gotkine, M.; Kviatcovsky, D.; Elinav, E. Amyotrophic Lateral Sclerosis and Intestinal Microbiota—Toward Establishing Cause and Effect. Gut Microbes 2020, 11, 1833–1841. [Google Scholar] [CrossRef]
  61. Sun, M.-F.; Shen, Y.-Q. Dysbiosis of Gut Microbiota and Microbial Metabolites in Parkinson’s Disease. Ageing Res. Rev. 2018, 45, 53–61. [Google Scholar] [CrossRef] [PubMed]
  62. Gerhardt, S.; Mohajeri, M. Changes of Colonic Bacterial Composition in Parkinson’s Disease and Other Neurodegenerative Diseases. Nutrients 2018, 10, 708. [Google Scholar] [CrossRef] [PubMed][Green Version]
  63. Jiang, H.; Ling, Z.; Zhang, Y.; Mao, H.; Ma, Z.; Yin, Y.; Wang, W.; Tang, W.; Tan, Z.; Shi, J.; et al. Altered Fecal Microbiota Composition in Patients with Major Depressive Disorder. Brain Behav. Immun. 2015, 48, 186–194. [Google Scholar] [CrossRef][Green Version]
  64. Levy, M.; Kolodziejczyk, A.A.; Thaiss, C.A.; Elinav, E. Dysbiosis and the Immune System. Nat. Rev. Immunol. 2017, 17, 219–232. [Google Scholar] [CrossRef] [PubMed]
  65. Schwabe, R.F.; Jobin, C. The Microbiome and Cancer. Nat. Cancer 2013, 13, 800–812. [Google Scholar] [CrossRef] [PubMed][Green Version]
  66. Abenavoli, L.; Scarpellini, E.; Colica, C.; Boccuto, L.; Salehi, B.; Sharifi-Rad, J.; Aiello, V.; Romano, B.; de Lorenzo, A.; Izzo, A.A.; et al. Gut Microbiota and Obesity: A Role for Probiotics. Nutrients 2019, 11, 2690. [Google Scholar] [CrossRef] [PubMed][Green Version]
  67. Galicia-Garcia, U.; Benito-Vicente, A.; Jebari, S.; Larrea-Sebal, A.; Siddiqi, H.; Uribe, K.B.; Ostolaza, H.; Martín, C. Pathophysiology of Type 2 Diabetes Mellitus. Int. J. Mol. Sci. 2020, 21, 6275. [Google Scholar] [CrossRef]
  68. Varesi, A.; Deumer, U.-S.; Ananth, S.; Ricevuti, G. The Emerging Role of Gut Microbiota in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS): Current Evidence and Potential Therapeutic Applications. J. Clin. Med. 2021, 10, 5077. [Google Scholar] [CrossRef] [PubMed]
  69. Ling, Z.; Liu, X.; Jia, X.; Cheng, Y.; Luo, Y.; Yuan, L.; Wang, Y.; Zhao, C.; Guo, S.; Li, L.; et al. Impacts of Infection with Different Toxigenic Clostridium Difficile Strains on Faecal Microbiota in Children. Sci. Rep. 2014, 4, 7485. [Google Scholar] [CrossRef][Green Version]
  70. Vogt, N.M.; Kerby, R.L.; Dill-McFarland, K.A.; Harding, S.J.; Merluzzi, A.P.; Johnson, S.C.; Carlsson, C.M.; Asthana, S.; Zetterberg, H.; Blennow, K.; et al. Gut Microbiome Alterations in Alzheimer’s Disease. Sci. Rep. 2017, 7, 1–11. [Google Scholar] [CrossRef]
  71. Haran, J.P.; Bhattarai, S.K.; Foley, S.E.; Dutta, P.; Ward, D.V.; Bucci, V.; McCormick, B.A. Alzheimer’s Disease Microbiome Is Associated with Dysregulation of the Anti-Inflammatory P-Glycoprotein Pathway. mBio 2019, 10, e00632-19. [Google Scholar] [CrossRef][Green Version]
  72. Liu, P.; Wu, L.; Peng, G.; Han, Y.; Tang, R.; Ge, J.; Zhang, L.; Jia, L.; Yue, S.; Zhou, K.; et al. Altered Microbiomes Distinguish Alzheimer’s Disease from Amnestic Mild Cognitive Impairment and Health in a Chinese Cohort. Brain Behav. Immun. 2019, 80, 633–643. [Google Scholar] [CrossRef]
  73. Ling, Z.; Zhu, M.; Yan, X.; Cheng, Y.; Shao, L.; Liu, X.; Jiang, R.; Wu, S. Structural and Functional Dysbiosis of Fecal Microbiota in Chinese Patients with Alzheimer’s Disease. Front. Cell Dev. Biol. 2021, 8, 1891. [Google Scholar] [CrossRef] [PubMed]
  74. Hoffman, J.D.; Parikh, I.; Green, S.J.; Chlipala, G.; Mohney, R.P.; Keaton, M.; Bauer, B.; Hartz, A.M.S.; Lin, A.-L. Age Drives Distortion of Brain Metabolic, Vascular and Cognitive Functions, and the Gut Microbiome. Front. Aging Neurosci. 2017, 9, 298. [Google Scholar] [CrossRef] [PubMed][Green Version]
  75. Boyajian, J.L.; Ghebretatios, M.; Schaly, S.; Islam, P.; Prakash, S. Microbiome and Human Aging: Probiotic and Prebiotic Potentials in Longevity, Skin Health and Cellular Senescence. Nutrients 2021, 13, 4550. [Google Scholar] [CrossRef] [PubMed]
  76. Zhuang, Z.-Q.; Shen, L.-L.; Li, W.-W.; Fu, X.; Zeng, F.; Gui, L.; Lü, Y.; Cai, M.; Zhu, C.; Tan, Y.-L.; et al. Gut Microbiota Is Altered in Patients with Alzheimer’s Disease. J. Alzheimers Dis. 2018, 63, 1337–1346. [Google Scholar] [CrossRef] [PubMed][Green Version]
  77. Guo, M.; Peng, J.; Huang, X.; Xiao, L.; Huang, F.; Zuo, Z. Gut Microbiome Features of Chinese Patients Newly Diagnosed with Alzheimer’s Disease or Mild Cognitive Impairment. J. Alzheimers Dis. 2021, 80, 299–310. [Google Scholar] [CrossRef]
  78. He, Y.; Wu, W.; Zheng, H.-M.; Li, P.; McDonald, D.; Sheng, H.-F.; Chen, M.-X.; Chen, Z.-H.; Ji, G.-Y.; Zheng, Z.-D.-X.; et al. Regional Variation Limits Applications of Healthy Gut Microbiome Reference Ranges and Disease Models. Nat. Med. 2018, 24, 1532–1535. [Google Scholar] [CrossRef]
  79. Leblhuber, F.; Steiner, K.; Geisler, S.; Fuchs, D.; Gostner, J.M. On the Possible Relevance of Bottom-up Pathways in the Pathogenesis of Alzheimer’s Disease. Curr. Top. Med. Chem. 2020, 20, 1415–1421. [Google Scholar] [CrossRef]
  80. Morris, G.; Berk, M.; Carvalho, A.; Caso, J.R.; Sanz, Y.; Walder, K.; Maes, M. The Role of the Microbial Metabolites Including Tryptophan Catabolites and Short Chain Fatty Acids in the Pathophysiology of Immune-Inflammatory and Neuroimmune Disease. Mol. Neurobiol. 2017, 54, 4432–4451. [Google Scholar] [CrossRef]
  81. Lee, H.-J.; Lee, K.-E.; Kim, J.-K.; Kim, D.-H. Suppression of Gut Dysbiosis by Bifidobacterium Longum Alleviates Cognitive Decline in 5XFAD Transgenic and Aged Mice. Sci. Rep. 2019, 9, 1–12. [Google Scholar] [CrossRef] [PubMed][Green Version]
  82. Doifode, T.; Giridharan, V.V.; Generoso, J.S.; Bhatti, G.; Collodel, A.; Schulz, P.E.; Forlenza, O.V.; Barichello, T. The Impact of the Microbiota-Gut-Brain Axis on Alzheimer’s Disease Pathophysiology. Pharmacol. Res. 2020, 164, 105314. [Google Scholar] [CrossRef] [PubMed]
  83. Parada Venegas, D.; de la Fuente, M.K.; Landskron, G.; González, M.J.; Quera, R.; Dijkstra, G.; Harmsen, H.J.M.; Faber, K.N.; Hermoso, M.A. Short Chain Fatty Acids (SCFAs)-Mediated Gut Epithelial and Immune Regulation and Its Relevance for Inflammatory Bowel Diseases. Front. Immunol. 2019, 10, 277. [Google Scholar] [CrossRef][Green Version]
  84. Colombo, A.V.; Sadler, R.K.; Llovera, G.; Singh, V.; Roth, S.; Heindl, S.; Sebastian Monasor, L.; Verhoeven, A.; Peters, F.; Parhizkar, S.; et al. Microbiota-Derived Short Chain Fatty Acids Modulate Microglia and Promote Aβ Plaque Deposition. eLife 2021, 10, e59826. [Google Scholar] [CrossRef] [PubMed]
  85. Morrison, D.J.; Preston, T. Formation of Short Chain Fatty Acids by the Gut Microbiota and Their Impact on Human Metabolism. Gut Microbes 2016, 7, 189–200. [Google Scholar] [CrossRef][Green Version]
  86. Wenzel, T.J.; Gates, E.J.; Ranger, A.L.; Klegeris, A. Short-Chain Fatty Acids (SCFAs) Alone or in Combination Regulate Select Immune Functions of Microglia-like Cells. Mol. Cell. Neurosci. 2020, 105, 103493. [Google Scholar] [CrossRef]
  87. Köhler, C.; Maes, M.; Slyepchenko, A.; Berk, M.; Solmi, M.; Lanctôt, K.; Carvalho, A. The Gut-Brain Axis, Including the Microbiome, Leaky Gut and Bacterial Translocation: Mechanisms and Pathophysiological Role in Alzheimer’s Disease. Curr. Pharm. Des. 2016, 22, 6152–6166. [Google Scholar] [CrossRef]
  88. Fuke, N.; Nagata, N.; Suganuma, H.; Ota, T. Regulation of Gut Microbiota and Metabolic Endotoxemia with Dietary Factors. Nutrients 2019, 11, 2277. [Google Scholar] [CrossRef][Green Version]
  89. Browne, T.C.; McQuillan, K.; McManus, R.M.; O’Reilly, J.-A.; Mills, K.H.G.; Lynch, M.A. IFN-γ Production by Amyloid β–Specific Th1 Cells Promotes Microglial Activation and Increases Plaque Burden in a Mouse Model of Alzheimer’s Disease. J. Immunol. 2013, 190, 2241–2251. [Google Scholar] [CrossRef][Green Version]
  90. Bonfili, L.; Cecarini, V.; Gogoi, O.; Gong, C.; Cuccioloni, M.; Angeletti, M.; Rossi, G.; Eleuteri, A.M. Microbiota Modulation as Preventative and Therapeutic Approach in Alzheimer’s Disease. FEBS J. 2021, 288, 2836–2855. [Google Scholar] [CrossRef]
  91. Gamba, P.; Testa, G.; Sottero, B.; Gargiulo, S.; Poli, G.; Leonarduzzi, G. The Link between Altered Cholesterol Metabolism and Alzheimer’s Disease. Ann. N. Y. Acad. Sci. 2012, 1259, 54–64. [Google Scholar] [CrossRef] [PubMed]
  92. Brandscheid, C.; Schuck, F.; Reinhardt, S.; Schäfer, K.-H.; Pietrzik, C.U.; Grimm, M.; Hartmann, T.; Schwiertz, A.; Endres, K. Altered Gut Microbiome Composition and Tryptic Activity of the 5xFAD Alzheimer’s Mouse Model. J. Alzheimers Dis. 2017, 56, 775–788. [Google Scholar] [CrossRef] [PubMed]
  93. Gao, Q.; Wang, Y.; Wang, X.; Fu, S.; Zhang, X.; Wang, R.-T.; Zhang, X. Decreased Levels of Circulating Trimethylamine N-Oxide Alleviate Cognitive and Pathological Deterioration in Transgenic Mice: A Potential Therapeutic Approach for Alzheimer’s Disease. Aging 2019, 11, 8642–8663. [Google Scholar] [CrossRef] [PubMed]
  94. Colciaghi, F.; Marcello, E.; Borroni, B.; Zimmermann, M.; Caltagirone, C.; Cattabeni, F.; Padovani, A.; di Luca, M. Platelet APP, ADAM 10 and BACE Alterations in the Early Stages of Alzheimer Disease. Neurology 2004, 62, 498–501. [Google Scholar] [CrossRef] [PubMed]
  95. Evin, G. Platelets and Alzheimer’s Disease: Potential of APP as a Biomarker. World J. Psychiatry 2012, 2, 102–113. [Google Scholar] [CrossRef]
  96. Szabo, C. Gaseotransmitters: New Frontiers for Translational Science. Sci. Transl. Med. 2010, 2, 59ps54. [Google Scholar] [CrossRef][Green Version]
  97. Oleskin, A.V.; Shenderov, B.A. Neuromodulatory Effects and Targets of the SCFAs and Gasotransmitters Produced by the Human Symbiotic Microbiota. Microb. Ecol. Health Dis. 2016, 27, 634. [Google Scholar] [CrossRef]
  98. Mietelska-Porowska, A.; Wojda, U. T Lymphocytes and Inflammatory Mediators in the Interplay between Brain and Blood in Alzheimer’s Disease: Potential Pools of New Biomarkers. J. Immunol. Res. 2017, 2017, 1–17. [Google Scholar] [CrossRef][Green Version]
  99. Milà-Alomà, M.; Suárez-Calvet, M.; Molinuevo, J.L. Latest Advances in Cerebrospinal Fluid and Blood Biomarkers of Alzheimer’s Disease. Ther. Adv. Neurol. Disord. 2019, 12, 1756286419888819. [Google Scholar] [CrossRef][Green Version]
  100. Mullane, K.; Williams, M. Alzheimer’s Disease beyond Amyloid: Can the Repetitive Failures of Amyloid-Targeted Therapeutics Inform Future Approaches to Dementia Drug Discovery? Biochem. Pharmacol. 2020, 177, 113945. [Google Scholar] [CrossRef]
  101. O’Toole, P.W.; Jeffery, I.B. Gut Microbiota and Aging. Science 2015, 350, 1214–1215. [Google Scholar] [CrossRef]
  102. Magne, F.; Gotteland, M.; Gauthier, L.; Zazueta, A.; Pesoa, S.; Navarrete, P.; Balamurugan, R. The Firmicutes/Bacteroidetes Ratio: A Relevant Marker of Gut Dysbiosis in Obese Patients? Nutrients 2020, 12, 1474. [Google Scholar] [CrossRef] [PubMed]
  103. Lucidi, L.; Pettorruso, M.; Vellante, F.; di Carlo, F.; Ceci, F.; Santovito, M.C.; di Muzio, I.; Fornaro, M.; Ventriglio, A.; Tomasetti, C.; et al. Gut Microbiota and Bipolar Disorder: An Overview on a Novel Biomarker for Diagnosis and Treatment. Int. J. Mol. Sci. 2021, 22, 3723. [Google Scholar] [CrossRef] [PubMed]
  104. Qian, Y.; Yang, X.; Xu, S.; Huang, P.; Li, B.; Du, J.; He, Y.; Su, B.; Xu, L.-M.; Wang, L.; et al. Gut Metagenomics-Derived Genes as Potential Biomarkers of Parkinson’s Disease. Brain 2020, 143, 2474–2489. [Google Scholar] [CrossRef]
  105. Farrokhi, V.; Nemati, R.; Nichols, F.C.; Yao, X.; Anstadt, E.; Fujiwara, M.; Grady, J.; Wakefield, D.; Castro, W.; Donaldson, J.; et al. Bacterial Lipodipeptide, Lipid 654, Is a Microbiome-Associated Biomarker for Multiple Sclerosis. Clin. Transl. Immunol. 2013, 2, e8. [Google Scholar] [CrossRef] [PubMed]
  106. Yan, Y.; Gao, Y.; Fang, Q.; Zhang, N.; Kumar, G.; Yan, H.; Song, L.; Li, J.; Zhang, Y.; Sun, J.; et al. Inhibition of Rho Kinase by Fasudil Ameliorates Cognition Impairment in APP/PS1 Transgenic Mice via Modulation of Gut Microbiota and Metabolites. Front. Aging Neurosci. 2021, 13, 649. [Google Scholar] [CrossRef]
  107. Bello-Medina, P.C.; Hernández-Quiroz, F.; Pérez-Morales, M.; González-Franco, D.A.; Cruz-Pauseno, G.; García-Mena, J.; Díaz-Cintra, S.; Pacheco-López, G. Spatial Memory and Gut Microbiota Alterations Are Already Present in Early Adulthood in a Pre-Clinical Transgenic Model of Alzheimer’s Disease. Front. Neurosci. 2021, 15, 595583. [Google Scholar] [CrossRef]
  108. Gu, X.; Zhou, J.; Zhou, Y.; Wang, H.; Si, N.; Ren, W.; Zhao, W.; Fan, X.; Gao, W.; Wei, X.; et al. Huanglian Jiedu Decoction Remodels the Periphery Microenvironment to Inhibit Alzheimer’s Disease Progression Based on the “Brain-Gut” Axis through Multiple Integrated Omics. Alzheimers Res. Ther. 2021, 13, 1–18. [Google Scholar] [CrossRef]
  109. Shen, L.; Liu, L.; Ji, H.-F. Alzheimer’s Disease Histological and Behavioral Manifestations in Transgenic Mice Correlate with Specific Gut Microbiome State. J. Alzheimers Dis. 2017, 56, 385–390. [Google Scholar] [CrossRef]
  110. Chen, Y.; Fang, L.; Chen, S.; Zhou, H.; Fan, Y.; Lin, L.; Li, J.; Xu, J.; Chen, Y.; Ma, Y.; et al. Gut Microbiome Alterations Precede Cerebral Amyloidosis and Microglial Pathology in a Mouse Model of Alzheimer’s Disease. BioMed Res. Int. 2020, 2020, 1–15. [Google Scholar] [CrossRef]
  111. Tan, F.H.P.; Liu, G.; Lau, S.-Y.A.; Jaafar, M.H.; Park, Y.-H.; Azzam, G.; Li, Y.; Liong, M.-T. Lactobacillus Probiotics Improved the Gut Microbiota Profile of a Drosophila Melanogaster Alzheimer’s Disease Model and Alleviated Neurodegeneration in the Eye. Benef. Microbes 2020, 11, 79–89. [Google Scholar] [CrossRef] [PubMed]
  112. Zhang, X.; Wang, Y.; Liu, W.; Wang, T.; Wang, L.; Hao, L.; Ju, M.; Xiao, R. Diet Quality, Gut Microbiota, and MicroRNAs Associated with Mild Cognitive Impairment in Middle-Aged and Elderly Chinese Population. Am. J. Clin. Nutr. 2021, 114, 429–440. [Google Scholar] [CrossRef] [PubMed]
  113. Li, B.; He, Y.; Ma, J.; Huang, P.; Du, J.; Cao, L.; Wang, Y.; Xiao, Q.; Tang, H.; Chen, S. Mild Cognitive Impairment Has Similar Alterations as Alzheimer’s Disease in Gut Microbiota. Alzheimers Dement. 2019, 15, 1357–1366. [Google Scholar] [CrossRef] [PubMed]
  114. Vogt, N.M.; Romano, K.A.; Darst, B.F.; Engelman, C.D.; Johnson, S.C.; Carlsson, C.M.; Asthana, S.; Blennow, K.; Zetterberg, H.; Bendlin, B.B.; et al. The Gut Microbiota-Derived Metabolite Trimethylamine N-Oxide Is Elevated in Alzheimer’s Disease. Alzheimers Res. Ther. 2018, 10, 1–8. [Google Scholar] [CrossRef][Green Version]
  115. Wu, L.; Han, Y.; Zheng, Z.; Peng, G.; Liu, P.; Yue, S.; Zhu, S.; Chen, J.; Lv, H.; Shao, L.; et al. Altered Gut Microbial Metabolites in Amnestic Mild Cognitive Impairment and Alzheimer’s Disease: Signals in Host–Microbe Interplay. Nutrients 2021, 13, 228. [Google Scholar] [CrossRef]
  116. Goetz, M.E.; Hanfelt, J.J.; John, S.E.; Bergquist, S.H.; Loring, D.W.; Quyyumi, A.; Clifford, G.D.; Vaccarino, V.; Goldstein, F.; Johnson, T.M., II.; et al. Rationale and Design of the Emory Healthy Aging and Emory Healthy Brain Studies. Neuroepidemiology 2019, 53, 187–200. [Google Scholar] [CrossRef]
  117. Forloni, G. Alzheimer’s Disease: From Basic Science to Precision Medicine Approach. BMJ Neurol. Open 2020, 2, e000079. [Google Scholar] [CrossRef]
  118. Bouftas, M. A Systematic Review on the Feasibility of Salivary Biomarkers for Alzheimer’s Disease. J. Prev. Alzheimers Dis. 2020, 8, 84–91. [Google Scholar] [CrossRef]
  119. Olsen, I.; Singhrao, S.K. Low Levels of Salivary Lactoferrin May Affect Oral Dysbiosis and Contribute to Alzheimer’s Disease: A Hypothesis. Med. Hypotheses 2020, 146, 110393. [Google Scholar] [CrossRef]
  120. Floden, A.M.; Sohrabi, M.; Nookala, S.; Cao, J.J.; Combs, C.K. Salivary Aβ Secretion and Altered Oral Microbiome in Mouse Models of AD. Curr. Alzheimer Res. 2021, 17, 1133–1144. [Google Scholar] [CrossRef]
  121. Wu, Y.-F.; Lee, W.-F.; Salamanca, E.; Yao, W.-L.; Su, J.-N.; Wang, S.-Y.; Hu, C.-J.; Chang, W.-J. Oral Microbiota Changes in Elderly Patients, an Indicator of Alzheimer’s Disease. Int. J. Environ. Res. Public Health 2021, 18, 4211. [Google Scholar] [CrossRef] [PubMed]
  122. Zhang, Z.; Tan, X.; Sun, X.; Wei, J.; Li, Q.X.; Wu, Z. Isoorientin Affects Markers of Alzheimer’s Disease via Effects on the Oral and Gut Microbiota in APP/PS1 Mice. J. Nutr. 2022, 152, 140–152. [Google Scholar] [CrossRef] [PubMed]
  123. David, L.A.; Maurice, C.F.; Carmody, R.N.; Gootenberg, D.B.; Button, J.E.; Wolfe, B.E.; Ling, A.V.; Devlin, A.S.; Varma, Y.; Fischbach, M.A.; et al. Diet Rapidly and Reproducibly Alters the Human Gut Microbiome. Nature 2014, 505, 559–563. [Google Scholar] [CrossRef] [PubMed][Green Version]
  124. Davani-Davari, D.; Negahdaripour, M.; Karimzadeh, I.; Seifan, M.; Mohkam, M.; Masoumi, S.; Berenjian, A.; Ghasemi, Y. Prebiotics: Definition, Types, Sources, Mechanisms, and Clinical Applications. Foods 2019, 8, 92. [Google Scholar] [CrossRef] [PubMed][Green Version]
  125. den Besten, G.; van Eunen, K.; Groen, A.K.; Venema, K.; Reijngoud, D.-J.; Bakker, B.M. The Role of Short-Chain Fatty Acids in the Interplay between Diet, Gut Microbiota, and Host Energy Metabolism. J. Lipid Res. 2013, 54, 2325–2340. [Google Scholar] [CrossRef][Green Version]
  126. Rajanala, K.; Kumar, N.; Chamallamudi, M.R. Modulation of Gut-Brain Axis by Probiotics: A Promising Anti-Depressant Approach. Curr. Neuropharmacol. 2021, 19, 990–1006. [Google Scholar] [CrossRef]
  127. Xu, M.; Mo, X.; Huang, H.; Chen, X.; Liu, H.; Peng, Z.; Chen, L.; Rong, S.; Yang, W.; Xu, S.; et al. Yeast β-Glucan Alleviates Cognitive Deficit by Regulating Gut Microbiota and Metabolites in Aβ1–42-Induced AD-like Mice. Int. J. Biol. Macromol. 2020, 161, 258–270. [Google Scholar] [CrossRef]
  128. Wang, Y.; Lim, Y.-Y.; He, Z.; Wong, W.-T.; Lai, W.-F. Dietary Phytochemicals That Influence Gut Microbiota: Roles and Actions as Anti-Alzheimer Agents. Crit. Rev. Food Sci. Nutr. 2021, 1–27. [Google Scholar] [CrossRef]
  129. Lee, Y.-S.; Lai, D.-M.; Huang, H.-J.; Lee-Chen, G.-J.; Chang, C.-H.; Hsieh-Li, H.M.; Lee, G.-C. Prebiotic Lactulose Ameliorates the Cognitive Deficit in Alzheimer’s Disease Mouse Model through Macroautophagy and Chaperone-Mediated Autophagy Pathways. J. Agric. Food Chem. 2021, 69, 2422–2437. [Google Scholar] [CrossRef]
  130. Liu, Q.; Xi, Y.; Wang, Q.; Liu, J.; Li, P.; Meng, X.; Liu, K.; Chen, W.; Liu, X.; Liu, Z. Mannan Oligosaccharide Attenuates Cognitive and Behavioral Disorders in the 5xFAD Alzheimer’s Disease Mouse Model via Regulating the Gut Microbiota-Brain Axis. Brain Behav. Immun. 2021, 95, 330–343. [Google Scholar] [CrossRef] [PubMed]
  131. Nishikawa, M.; Brickman, A.M.; Manly, J.J.; Schupf, N.; Mayeux, R.P.; Gu, Y. Association of Dietary Prebiotic Consumption with Reduced Risk of Alzheimer’s Disease in a Multiethnic Population. Curr. Alzheimer Res. 2021, 18, 984–992. [Google Scholar] [CrossRef] [PubMed]
  132. Deng, S.; Chen, C.; Lin, H.; Cheng, I.H. The Beneficial Effect of Synbiotics Consumption on Alzheimer’s Disease Mouse Model via Reducing Local and Systemic Inflammation. IUBMB Life 2021, in press. [Google Scholar] [CrossRef]
  133. Barbosa, R.S.D.; Vieira-Coelho, M.A. Probiotics and Prebiotics: Focus on Psychiatric Disorders—A Systematic Review. Nutr. Rev. 2019, 78, 437–450. [Google Scholar] [CrossRef] [PubMed]
  134. Xin, Y.; Diling, C.; Jian, Y.; Ting, L.; Guoyan, H.; Hualun, L.; Xiaocui, T.; Guoxiao, L.; Ou, S.; Chaoqun, Z.; et al. Effects of Oligosaccharides from Morinda Officinalis on Gut Microbiota and Metabolome of APP/PS1 Transgenic Mice. Front. Neurol. 2018, 9, 412. [Google Scholar] [CrossRef] [PubMed]
  135. Chen, D.; Yang, X.; Yang, J.; Lai, G.; Yong, T.; Tang, X.; Shuai, O.; Zhou, G.; Xie, Y.; Wu, Q. Prebiotic Effect of Fructooligosaccharides from Morinda Officinalis on Alzheimer’s Disease in Rodent Models by Targeting the Microbiota-Gut-Brain Axis. Front. Aging Neurosci. 2017, 9, 403. [Google Scholar] [CrossRef] [PubMed][Green Version]
  136. Chok, K.C.; Ng, K.Y.; Koh, R.Y.; Chye, S.M. Role of the Gut Microbiome in Alzheimer’s Disease. Rev. Neurosci. 2021, 32, 767–789. [Google Scholar] [CrossRef] [PubMed]
  137. Lilly, D.M.; Stillwell, R.H. Probiotics: Growth-Promoting Factors Produced by Microorganisms. Science 1965, 147, 747–748. [Google Scholar] [CrossRef]
  138. Martinez, F.A.C.; Balciunas, E.M.; Converti, A.; Cotter, P.D.; de Souza Oliveira, R.P. Bacteriocin Production by Bifidobacterium Spp. A Review. Biotechnol. Adv. 2013, 31, 482–488. [Google Scholar] [CrossRef] [PubMed]
  139. Collado, M.C.; Hernandez, M.; Sanz, Y. Production of Bacteriocin-Like Inhibitory Compounds by Human Fecal Bifidobacterium Strains. J. Food Prot. 2005, 68, 1034–1040. [Google Scholar] [CrossRef]
  140. Collado, M.C.; Gueimonde, M.; Sanz, Y.; Salminen, S. Adhesion Properties and Competitive Pathogen Exclusion Ability of Bifidobacteria with Acquired Acid Resistance. J. Food Prot. 2006, 69, 1675–1679. [Google Scholar] [CrossRef]
  141. Bajaj, B.K.; Claes, I.J.J.; Lebeer, S. Functional Mechanisms of Probiotics. J. Microbiol. Biotechnol. Food Sci. 2015, 4, 321–327. [Google Scholar] [CrossRef][Green Version]
  142. Liu, G.; Ren, L.; Song, Z.; Wang, C.; Sun, B. Purification and Characteristics of Bifidocin A, a Novel Bacteriocin Produced by Bifidobacterium Animals BB04 from Centenarians’ Intestine. Food Control 2015, 50, 889–895. [Google Scholar] [CrossRef]
  143. Thomas, C.M.; Versalovic, J. Probiotics-Host Communication. Gut Microbes 2010, 1, 148–163. [Google Scholar] [CrossRef] [PubMed]
  144. Vanderpool, C.; Yan, F.; Polk, B.D. Mechanisms of Probiotic Action: Implications for Therapeutic Applications in Inflammatory Bowel Diseases. Inflamm. Bowel Dis. 2008, 14, 1585–1596. [Google Scholar] [CrossRef] [PubMed]
  145. Bermudez-Brito, M.; Plaza-Díaz, J.; Muñoz-Quezada, S.; Gómez-Llorente, C.; Gil, A. Probiotic Mechanisms of Action. Ann. Nutr. Metab. 2012, 61, 160–174. [Google Scholar] [CrossRef]
  146. van Baarlen, P.; Wells, J.M.; Kleerebezem, M. Regulation of Intestinal Homeostasis and Immunity with Probiotic Lactobacilli. Trends Immunol. 2013, 34, 208–215. [Google Scholar] [CrossRef]
  147. la Rosa, F.; Clerici, M.; Ratto, D.; Occhinegro, A.; Licito, A.; Romeo, M.; Iorio, C.; Rossi, P. The Gut-Brain Axis in Alzheimer’s Disease and Omega-3. A Critical Overview of Clinical Trials. Nutrients 2018, 10, 1267. [Google Scholar] [CrossRef][Green Version]
  148. Dargahi, N.; Johnson, J.; Donkor, O.; Vasiljevic, T.; Apostolopoulos, V. Immunomodulatory Effects of Probiotics: Can They Be Used to Treat Allergies and Autoimmune Diseases? Maturitas 2019, 119, 25–38. [Google Scholar] [CrossRef]
  149. Sichetti, M.; de Marco, S.; Pagiotti, R.; Traina, G.; Pietrella, D. Anti-Inflammatory Effect of Multistrain Probiotic Formulation (L. Rhamnosus, B. Lactis, and B. Longum). Nutrition 2018, 53, 95–102. [Google Scholar] [CrossRef]
  150. Martinowich, K.; Lu, B. Interaction between BDNF and Serotonin: Role in Mood Disorders. Neuropsychopharmacology 2008, 33, 73–83. [Google Scholar] [CrossRef]
  151. Heldt, S.A.; Stanek, L.; Chhatwal, J.P.; Ressler, K.J. Hippocampus-Specific Deletion of BDNF in Adult Mice Impairs Spatial Memory and Extinction of Aversive Memories. Mol. Psychiatry 2007, 12, 656–670. [Google Scholar] [CrossRef][Green Version]
  152. Lu, Y.; Christian, K.; Lu, B. BDNF: A Key Regulator for Protein Synthesis-Dependent LTP and Long-Term Memory? Neurobiol. Learn. Mem. 2008, 89, 312–323. [Google Scholar] [CrossRef] [PubMed][Green Version]
  153. Dinan, T.G.; Stanton, C.; Cryan, J.F. Psychobiotics: A Novel Class of Psychotropic. Biol. Psychiatry 2013, 74, 720–726. [Google Scholar] [CrossRef] [PubMed]
  154. Distrutti, E.; O’Reilly, J.-A.; McDonald, C.; Cipriani, S.; Renga, B.; Lynch, M.A.; Fiorucci, S. Modulation of Intestinal Microbiota by the Probiotic VSL#3 Resets Brain Gene Expression and Ameliorates the Age-Related Deficit in LTP. PLoS ONE 2014, 9, e106503. [Google Scholar] [CrossRef]
  155. Xie, Z.; Wei, M.; Morgan, T.E.; Fabrizio, P.; Han, D.; Finch, C.E.; Longo, V.D. Peroxynitrite Mediates Neurotoxicity of Amyloid β-Peptide1–42-and Lipopolysaccharide-Activated Microglia. J. Neurosci. 2002, 22, 3484–3492. [Google Scholar] [CrossRef] [PubMed][Green Version]
  156. van Dyke, K. The Possible Role of Peroxynitrite in Alzheimer’s Disease: A Simple Hypothesis That Could Be Tested More Thoroughly. Med. Hypotheses 1997, 48, 375–380. [Google Scholar] [CrossRef]
  157. Bonfili, L.; Cecarini, V.; Cuccioloni, M.; Angeletti, M.; Berardi, S.; Scarpona, S.; Rossi, G.; Eleuteri, A.M. SLAB51 Probiotic Formulation Activates SIRT1 Pathway Promoting Antioxidant and Neuroprotective Effects in an AD Mouse Model. Mol. Neurobiol. 2018, 55, 7987–8000. [Google Scholar] [CrossRef][Green Version]
  158. O’Hagan, C.; Li, J.V.; Marchesi, J.R.; Plummer, S.; Garaiova, I.; Good, M.A. Long-Term Multi-Species Lactobacillus and Bifidobacterium Dietary Supplement Enhances Memory and Changes Regional Brain Metabolites in Middle-Aged Rats. Neurobiol. Learn. Mem. 2017, 144, 36–47. [Google Scholar] [CrossRef]
  159. Kobayashi, Y.; Sugahara, H.; Shimada, K.; Mitsuyama, E.; Kuhara, T.; Yasuoka, A.; Kondo, T.; Abe, K.; Xiao, J. Therapeutic Potential of Bifidobacterium Breve Strain A1 for Preventing Cognitive Impairment in Alzheimer’s Disease. Sci. Rep. 2017, 7, 1–10. [Google Scholar] [CrossRef]
  160. Athari Nik Azm, S.; Djazayeri, A.; Safa, M.; Azami, K.; Ahmadvand, B.; Sabbaghziarani, F.; Sharifzadeh, M.; Vafa, M. Lactobacilli and Bifidobacteria Ameliorate Memory and Learning Deficits and Oxidative Stress in β-Amyloid (1–42) Injected Rats. Appl. Physiol. Nutr. Metab. 2018, 43, 718–726. [Google Scholar] [CrossRef]
  161. Akbari, E.; Asemi, Z.; Daneshvar Kakhaki, R.; Bahmani, F.; Kouchaki, E.; Tamtaji, O.R.; Hamidi, G.A.; Salami, M. Effect of Probiotic Supplementation on Cognitive Function and Metabolic Status in Alzheimer’s Disease: A Randomized, Double-Blind and Controlled Trial. Front. Aging Neurosci. 2016, 8, 256. [Google Scholar] [CrossRef] [PubMed][Green Version]
  162. Den, H.; Dong, X.; Chen, M.; Zou, Z. Efficacy of Probiotics on Cognition, and Biomarkers of Inflammation and Oxidative Stress in Adults with Alzheimer’s Disease or Mild Cognitive Impairment—A Meta-Analysis of Randomized Controlled Trials. Aging 2020, 12, 4010–4039. [Google Scholar] [CrossRef] [PubMed]
  163. Agahi, A.; Hamidi, G.A.; Daneshvar, R.; Hamdieh, M.; Soheili, M.; Alinaghipour, A.; Esmaeili Taba, S.M.; Salami, M. Does Severity of Alzheimer’s Disease Contribute to Its Responsiveness to Modifying Gut Microbiota? A Double Blind Clinical Trial. Front. Neurol. 2018, 9, 662. [Google Scholar] [CrossRef] [PubMed][Green Version]
  164. Klingbeil, E.; de La Serre, C.B. Microbiota Modulation by Eating Patterns and Diet Composition: Impact on Food Intake. Am. J. Physiol. Integr. Comp. Physiol. 2018, 315, R1254–R1260. [Google Scholar] [CrossRef] [PubMed][Green Version]
  165. 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]
  166. Duplantier, S.C.; Gardner, C.D. A Critical Review of the Study of Neuroprotective Diets to Reduce Cognitive Decline. Nutrients 2021, 13, 2264. [Google Scholar] [CrossRef]
  167. Bartochowski, Z.; Conway, J.; Wallach, Y.; Chakkamparambil, B.; Alakkassery, S.; Grossberg, G.T. Dietary Interventions to Prevent or Delay Alzheimer’s Disease: What the Evidence Shows. Curr. Nutr. Rep. 2020, 9, 210–225. [Google Scholar] [CrossRef]
  168. Gutierrez, L.; Folch, A.; Rojas, M.; Cantero, J.L.; Atienza, M.; Folch, J.; Camins, A.; Ruiz, A.; Papandreou, C.; Bulló, M. Effects of Nutrition on Cognitive Function in Adults with or without Cognitive Impairment: A Systematic Review of Randomized Controlled Clinical Trials. Nutrients 2021, 13, 3728. [Google Scholar] [CrossRef]
  169. Limongi, F.; Siviero, P.; Bozanic, A.; Noale, M.; Veronese, N.; Maggi, S. The Effect of Adherence to the Mediterranean Diet on Late-Life Cognitive Disorders: A Systematic Review. J. Am. Med Dir. Assoc. 2020, 21, 1402–1409. [Google Scholar] [CrossRef]
  170. Kheirouri, S.; Alizadeh, M. MIND Diet and Cognitive Performance in Older Adults: A Systematic Review. Crit. Rev. Food Sci. Nutr. 2021, 1–19. [Google Scholar] [CrossRef]
  171. Lilamand, M.; Mouton-Liger, F.; Paquet, C. Ketogenic Diet Therapy in Alzheimer’s Disease: An Updated Review. Curr. Opin. Clin. Nutr. Metab. Care 2021, 24, 372–378. [Google Scholar] [CrossRef] [PubMed]
  172. Grammatikopoulou, M.G.; Goulis, D.G.; Gkiouras, K.; Theodoridis, X.; Gkouskou, K.K.; Evangeliou, A.; Dardiotis, E.; Bogdanos, D.P. To Keto or Not to Keto? A Systematic Review of Randomized Controlled Trials Assessing the Effects of Ketogenic Therapy on Alzheimer Disease. Adv. Nutr. Int. Rev. J. 2020, 11, 1583–1602. [Google Scholar] [CrossRef] [PubMed]
  173. Pavón, S.; Lázaro, E.; Martínez, O.; Amayra, I.; López-Paz, J.F.; Caballero, P.; Al-Rashaida, M.; Luna, P.M.; García, M.; Pérez, M.; et al. Ketogenic Diet and Cognition in Neurological Diseases: A Systematic Review. Nutr. Rev. 2020, 79, 802–813. [Google Scholar] [CrossRef] [PubMed]
  174. Jensen, N.J.; Wodschow, H.Z.; Nilsson, M.; Rungby, J. Effects of Ketone Bodies on Brain Metabolism and Function in Neurodegenerative Diseases. Int. J. Mol. Sci. 2020, 21, 8767. [Google Scholar] [CrossRef]
  175. Christensen, M.G.; Damsgaard, J.; Fink-Jensen, A. Use of Ketogenic Diets in the Treatment of Central Nervous System Diseases: A Systematic Review. Nord. J. Psychiatry 2020, 75, 1–8. [Google Scholar] [CrossRef]
  176. Moreira, S.C.; Jansen, A.K.; Silva, F.M. Dietary Interventions and Cognition of Alzheimer’s Disease Patients: A Systematic Review of Randomized Controlled Trial. Dement. Neuropsychol. 2020, 14, 258–282. [Google Scholar] [CrossRef]
  177. Zhang, H.; Hardie, L.; Bawajeeh, A.O.; Cade, J. Meat Consumption, Cognitive Function and Disorders: A Systematic Review with Narrative Synthesis and Meta-Analysis. Nutrients 2020, 12, 1528. [Google Scholar] [CrossRef]
  178. Dimache, A.M.; Șalaru, D.L.; Sascău, R.; Stătescu, C. The Role of High Triglycerides Level in Predicting Cognitive Impairment: A Review of Current Evidence. Nutrients 2021, 13, 2118. [Google Scholar] [CrossRef]
  179. Gkotzamanis, V.; Panagiotakos, D. Dietary Interventions and Cognition: A Systematic Review of Clinical Trials. Psychiatriki 2020, 31, 248–256. [Google Scholar] [CrossRef]
  180. el Gaamouch, F.; Liu, K.; Lin, H.; Wu, C.; Wang, J. Development of Grape Polyphenols as Multi-Targeting Strategies for Alzheimer’s Disease. Neurochem. Int. 2021, 147, 105046. [Google Scholar] [CrossRef]
  181. Colizzi, C. The Protective Effects of Polyphenols on Alzheimer’s Disease: A Systematic Review. Alzheimers Dementia Transl. Res. Clin. Interv. 2018, 5, 184–196. [Google Scholar] [CrossRef] [PubMed]
  182. Mielech, A.; Puścion-Jakubik, A.; Markiewicz-Żukowska, R.; Socha, K. Vitamins in Alzheimer’s Disease—Review of the Latest Reports. Nutrients 2020, 12, 3458. [Google Scholar] [CrossRef] [PubMed]
  183. Szczechowiak, K.; Diniz, B.S.; Leszek, J. Diet and Alzheimer’s Dementia—Nutritional Approach to Modulate Inflammation. Pharmacol. Biochem. Behav. 2019, 184, 172743. [Google Scholar] [CrossRef] [PubMed]
  184. Kosti, R.I.; Kasdagli, M.I.; Kyrozis, A.; Orsini, N.; Lagiou, P.; Taiganidou, F.; Naska, A. Fish Intake, n-3 Fatty Acid Body Status, and Risk of Cognitive Decline: A Systematic Review and a Dose–Response Meta-Analysis of Observational and Experimental Studies. Nut. Rev. 2021, nuab078. [Google Scholar] [CrossRef] [PubMed]
  185. Haider, S.; Schwarzinger, A.; Stefanac, S.; Soysal, P.; Smith, L.; Veronese, N.; Dorner, T.E.; Grabovac, I. Nutritional Supplements for Neuropsychiatric Symptoms in People with Dementia: A Systematic Review and Meta-analysis. Int. J. Geriatr. Psychiatry 2020, 35, 1285–1291. [Google Scholar] [CrossRef] [PubMed]
  186. Arbo, B.D.; André-Miral, C.; Nasre-Nasser, R.G.; Schimith, L.E.; Santos, M.G.; Costa-Silva, D.; Muccillo-Baisch, A.L.; Hort, M.A. Resveratrol Derivatives as Potential Treatments for Alzheimer’s and Parkinson’s Disease. Front. Aging Neurosci. 2020, 12, 103. [Google Scholar] [CrossRef]
  187. Sofi, F.; Macchi, C.; Abbate, R.; Gensini, G.F.; Casini, A. Mediterranean Diet and Health. BioFactors 2013, 39, 335–342. [Google Scholar] [CrossRef]
  188. Filippou, C.D.; Tsioufis, C.P.; Thomopoulos, C.G.; Mihas, C.C.; Dimitriadis, K.S.; Sotiropoulou, L.I.; Chrysochoou, C.A.; Nihoyannopoulos, P.I.; Tousoulis, D.M. Dietary Approaches to Stop Hypertension (DASH) Diet and Blood Pressure Reduction in Adults with and without Hypertension: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Adv. Nutr. Int. Rev. J. 2020, 11, 1150–1160. [Google Scholar] [CrossRef]
  189. Morris, M.C.; Tangney, C.C.; Wang, Y.; Sacks, F.M.; Bennett, D.A.; Aggarwal, N.T. MIND Diet Associated with Reduced Incidence of Alzheimer’s Disease. Alzheimers Dement. 2015, 11, 1007–1014. [Google Scholar] [CrossRef][Green Version]
  190. Martínez-Lapiscina, E.H.; Clavero, P.; Toledo, E.; Estruch, R.; Salas-Salvadó, J.; San Julián, B.; Sanchez-Tainta, A.; Ros, E.; Valls-Pedret, C.; Martinez-Gonzalez, M.Á. Mediterranean Diet Improves Cognition: The PREDIMED-NAVARRA Randomised Trial. J. Neurol. Neurosurg. Psychiatry 2013, 84, 1318–1325. [Google Scholar] [CrossRef][Green Version]
  191. Valls-Pedret, C.; Sala-Vila, A.; Serra-Mir, M.; Corella, D.; de la Torre, R.; Martínez-González, M.Á.; Martínez-Lapiscina, E.H.; Fitó, M.; Pérez-Heras, A.; Salas-Salvadó, J.; et al. Mediterranean Diet and Age-Related Cognitive Decline. JAMA Intern. Med. 2015, 175, 1094–1103. [Google Scholar] [CrossRef] [PubMed][Green Version]
  192. Marseglia, A.; Xu, W.; Fratiglioni, L.; Fabbri, C.; Berendsen, A.A.M.; Bialecka-Debek, A.; Jennings, A.; Gillings, R.; Meunier, N.; Caumon, E.; et al. Effect of the NU-AGE Diet on Cognitive Functioning in Older Adults: A Randomized Controlled Trial. Front. Physiol. 2018, 9, 349. [Google Scholar] [CrossRef] [PubMed]
  193. Knight, A.; Bryan, J.; Wilson, C.; Hodgson, J.; Davis, C.; Murphy, K. The Mediterranean Diet and Cognitive Function among Healthy Older Adults in a 6-Month Randomised Controlled Trial: The MedLey Study. Nutrients 2016, 8, 579. [Google Scholar] [CrossRef] [PubMed][Green Version]
  194. Liu, Y.-H.; Gao, X.; Na, M.; Kris-Etherton, P.M.; Mitchell, D.C.; Jensen, G.L. Dietary Pattern, Diet Quality, and Dementia: A Systematic Review and Meta-Analysis of Prospective Cohort Studies. J. Alzheimers Dis. 2020, 78, 151–158. [Google Scholar] [CrossRef] [PubMed]
  195. Barbaresko, J.; Lellmann, A.W.; Schmidt, A.; Lehmann, A.; Amini, A.M.; Egert, S.; Schlesinger, S.; Nöthlings, U. Dietary Factors and Neurodegenerative Disorders: An Umbrella Review of Meta-Analyses of Prospective Studies. Adv. Nutr. Int. Rev. J. 2020, 11, 1161–1173. [Google Scholar] [CrossRef]
  196. Prinelli, F.; Fratiglioni, L.; Kalpouzos, G.; Musicco, M.; Adorni, F.; Johansson, I.; Marseglia, A.; Xu, W. Specific Nutrient Patterns Are Associated with Higher Structural Brain Integrity in Dementia-Free Older Adults. NeuroImage 2019, 199, 281–288. [Google Scholar] [CrossRef]
  197. Croll, P.H.; Voortman, T.; Ikram, M.A.; Franco, O.H.; Schoufour, J.D.; Bos, D.; Vernooij, M.W. Better Diet Quality Relates to Larger Brain Tissue Volumes. Neurology 2018, 90, e2166–e2173. [Google Scholar] [CrossRef]
  198. Kao, Y.-C.; Ho, P.-C.; Tu, Y.-K.; Jou, I.-M.; Tsai, K.-J. Lipids and Alzheimer’s Disease. Int. J. Mol. Sci. 2020, 21, 1505. [Google Scholar] [CrossRef]
  199. Rainey-Smith, S.R.; Gu, Y.; Gardener, S.L.; Doecke, J.D.; Villemagne, V.L.; Brown, B.M.; Taddei, K.; Laws, S.M.; Sohrabi, H.R.; Weinborn, M.; et al. Mediterranean Diet Adherence and Rate of Cerebral Aβ-Amyloid Accumulation: Data from the Australian Imaging, Biomarkers and Lifestyle Study of Ageing. Transl. Psychiatry 2018, 8, 1–7. [Google Scholar] [CrossRef][Green Version]
  200. Cole, G.M.; Frautschy, S.A. Docosahexaenoic Acid Protects from Amyloid and Dendritic Pathology in an Alzheimer’s Disease Mouse Model. Nutr. Heal. 2006, 18, 249–259. [Google Scholar] [CrossRef]
  201. Freund-Levi, Y.; Eriksdotter-Jönhagen, M.; Cederholm, T.; Basun, H.; Faxén-Irving, G.; Garlind, A.; Vedin, I.; Vessby, B.; Wahlund, L.-O.; Palmblad, J. ω-3 Fatty Acid Treatment in 174 Patients with Mild to Moderate Alzheimer Disease: OmegAD Study. Arch. Neurol. 2006, 63, 1402–1408. [Google Scholar] [CrossRef] [PubMed][Green Version]
  202. Ma, Q.-L.; Teter, B.; Ubeda, O.J.; Morihara, T.; Dhoot, D.; Nyby, M.D.; Tuck, M.L.; Frautschy, S.A.; Cole, G.M. Omega-3 Fatty Acid Docosahexaenoic Acid Increases SorLA/LR11, a Sorting Protein with Reduced Expression in Sporadic Alzheimer’s Disease (AD): Relevance to AD Prevention. J. Neurosci. 2007, 27, 14299–14307. [Google Scholar] [CrossRef] [PubMed]
  203. Wilson, D.M.; Binder, L.I. Free Fatty Acids Stimulate the Polymerization of Tau and Amyloid Beta Peptides. In Vitro Evidence for a Common Effector of Pathogenesis in Alzheimer’s Disease. Am. J. Pathol. 1997, 150, 2181–2195. [Google Scholar] [PubMed]
  204. Snowden, S.G.; Ebshiana, A.A.; Hye, A.; An, Y.; Pletnikova, O.; O’Brien, R.; Troncoso, J.; Legido-Quigley, C.; Thambisetty, M. Association between Fatty Acid Metabolism in the Brain and Alzheimer Disease Neuropathology and Cognitive Performance: A Nontargeted Metabolomic Study. PLoS Med. 2017, 14, e1002266. [Google Scholar] [CrossRef] [PubMed][Green Version]
  205. Takechi, R.; Galloway, S.; Pallebage-Gamarallage, M.M.; Lam, V.; Dhaliwal, S.S.; Mamo, J.C. Probucol Prevents Blood-Brain Barrier Dysfunction in Wild-Type Mice Induced by Saturated Fat or Cholesterol Feeding. Clin. Exp. Pharmacol. Physiol. 2012, 40, 45–52. [Google Scholar] [CrossRef]
  206. Bernath, M.M.; Bhattacharyya, S.; Nho, K.; Barupal, D.K.; Fiehn, O.; Baillie, R.; Risacher, S.L.; Arnold, M.; Jacobson, T.; Trojanowski, J.Q.; et al. Serum Triglycerides in Alzheimer Disease. Neurology 2020, 94, e2088–e2098. [Google Scholar] [CrossRef]
  207. Yan, Y.; Yang, H.; Xie, Y.; Ding, Y.; Kong, D.; Yu, H. Research Progress on Alzheimer’s Disease and Resveratrol. Neurochem. Res. 2020, 45, 989–1006. [Google Scholar] [CrossRef]
  208. Rahman, M.; Akter, R.; Bhattacharya, T.; Abdel-Daim, M.M.; Alkahtani, S.; Arafah, M.W.; Al-Johani, N.S.; Alhoshani, N.M.; Alkeraishan, N.; Alhenaky, A.; et al. Resveratrol and Neuroprotection: Impact and Its Therapeutic Potential in Alzheimer’s Disease. Front. Pharmacol. 2020, 11, 2272. [Google Scholar] [CrossRef]
  209. Ułamek-Kozioł, M.; Czuczwar, S.J.; Januszewski, S.; Pluta, R. Ketogenic Diet and Epilepsy. Nutrients 2019, 11, 2510. [Google Scholar] [CrossRef][Green Version]
  210. Włodarek, D. Role of Ketogenic Diets in Neurodegenerative Diseases (Alzheimer’s Disease and Parkinson’s Disease). Nutrients 2019, 11, 169. [Google Scholar] [CrossRef][Green Version]
  211. Broom, G.M.; Shaw, I.C.; Rucklidge, J.J. The Ketogenic Diet as a Potential Treatment and Prevention Strategy for Alzheimer’s Disease. Nutrition 2019, 60, 118–121. [Google Scholar] [CrossRef]
  212. Rusek, M.; Pluta, R.; Ułamek-Kozioł, M.; Czuczwar, S.J. Ketogenic Diet in Alzheimer’s Disease. Int. J. Mol. Sci. 2019, 20, 3892. [Google Scholar] [CrossRef] [PubMed][Green Version]
  213. Masino, S.A.; Rho, J.M. Mechanisms of Ketogenic Diet Action. Epilepsia 2012, 51, 85. [Google Scholar] [CrossRef]
  214. Rojas-Morales, P.; Pedraza-Chaverri, J.; Tapia, E. Ketone Bodies, Stress Response, and Redox Homeostasis. Redox Biol. 2020, 29, 101395. [Google Scholar] [CrossRef] [PubMed]
  215. Kashiwaya, Y.; Bergman, C.; Lee, J.-H.; Wan, R.; King, M.T.; Mughal, M.R.; Okun, E.; Clarke, K.; Mattson, M.P.; Veech, R.L. A Ketone Ester Diet Exhibits Anxiolytic and Cognition-Sparing Properties, and Lessens Amyloid and Tau Pathologies in a Mouse Model of Alzheimer’s Disease. Neurobiol. Aging 2012, 34, 1530–1539. [Google Scholar] [CrossRef] [PubMed][Green Version]
  216. Yin, J.X.; Maalouf, M.; Han, P.; Zhao, M.; Gao, M.; Dharshaun, T.; Ryan, C.; Whitelegge, J.; Wu, J.; Eisenberg, D.; et al. Ketones Block Amyloid Entry and Improve Cognition in an Alzheimer’s Model. Neurobiol. Aging 2015, 39, 25–37. [Google Scholar] [CrossRef] [PubMed]
  217. Włodarek, D. The Possibility of Use of the Ketogenic Diet and Medium Chain Triglycerides Supplementation in the Support Therapy of Alzheimer Disease. Curr. Opin. Clin. Nutr. Metab. Care 2021, 24, 385–391. [Google Scholar] [CrossRef]
  218. Taylor, M.K.; Sullivan, D.K.; Mahnken, J.D.; Burns, J.M.; Swerdlow, R.H. Feasibility and Efficacy Data from a Ketogenic Diet Intervention in Alzheimer’s Disease. Alzheimers Dementia: Transl. Res. Clin. Interv. 2018, 4, 28–36. [Google Scholar] [CrossRef]
  219. Bostock, E.C.S.; Kirkby, K.C.; Taylor, B.V.M. The Current Status of the Ketogenic Diet in Psychiatry. Front. Psychiatry 2017, 8, 43. [Google Scholar] [CrossRef][Green Version]
  220. 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]
  221. Ghosh, T.S.; Rampelli, S.; Jeffery, I.B.; Santoro, A.; Neto, M.; Capri, M.; Giampieri, E.; Jennings, A.; Candela, M.; Turroni, S.; et al. Mediterranean Diet Intervention Alters the Gut Microbiome in Older People Reducing Frailty and Improving Health Status: The NU-AGE 1-Year Dietary Intervention across Five European Countries. Gut 2020, 69, 1218–1228. [Google Scholar] [CrossRef] [PubMed][Green Version]
  222. Moreno-Arribas, M.V.; Bartolomé, B.; Peñalvo, J.L.; Pérez-Matute, P.; Motilva, M.J. Relationship between Wine Consumption, Diet and Microbiome Modulation in Alzheimer’s Disease. Nutrients 2020, 12, 3082. [Google Scholar] [CrossRef] [PubMed]
  223. Nash, V.; Ranadheera, C.S.; Georgousopoulou, E.N.; Mellor, D.D.; Panagiotakos, D.B.; McKune, A.J.; Kellett, J.; Naumovski, N. The Effects of Grape and Red Wine Polyphenols on Gut Microbiota—A Systematic Review. Food Res. Int. 2018, 113, 277–287. [Google Scholar] [CrossRef] [PubMed]
  224. Ma, D.; Wang, A.C.; Parikh, I.; Green, S.J.; Hoffman, J.D.; Chlipala, G.; Murphy, M.P.; Sokola, B.S.; Bauer, B.; Hartz, A.M.S.; et al. Ketogenic Diet Enhances Neurovascular Function with Altered Gut Microbiome in Young Healthy Mice. Sci. Rep. 2018, 8, 1–10. [Google Scholar] [CrossRef] [PubMed][Green Version]
  225. Nagpal, R.; Neth, B.J.; Wang, S.; Craft, S.; Yadav, H. Modified Mediterranean-Ketogenic Diet Modulates Gut Microbiome and Short-Chain Fatty Acids in Association with Alzheimer’s Disease Markers in Subjects with Mild Cognitive Impairment. EBioMedicine 2019, 47, 529–542. [Google Scholar] [CrossRef] [PubMed][Green Version]
  226. Park, S.; Zhang, T.; Wu, X.; Yi Qiu, J. Ketone Production by Ketogenic Diet and by Intermittent Fasting Has Different Effects on the Gut Microbiota and Disease Progression in an Alzheimer’s Disease Rat Model. J. Clin. Biochem. Nutr. 2020, 67, 188–198. [Google Scholar] [CrossRef] [PubMed][Green Version]
  227. Gupta, S.; Allen-Vercoe, E.; Petrof, E.O. Fecal Microbiota Transplantation: In Perspective. Ther. Adv. Gastroenterol. 2015, 9, 229–239. [Google Scholar] [CrossRef][Green Version]
  228. Surawicz, C.M.; Brandt, L.J.; Binion, D.G.; Ananthakrishnan, A.N.; Curry, S.R.; Gilligan, P.H.; McFarland, L.V.; Mellow, M.; Zuckerbraun, B.S. Guidelines for Diagnosis, Treatment, and Prevention of Clostridium Difficile Infections. Am. J. Gastroenterol. 2013, 108, 478–498. [Google Scholar] [CrossRef]
  229. Hazan, S. Rapid Improvement in Alzheimer’s Disease Symptoms Following Fecal Microbiota Transplantation: A Case Report. J. Int. Med Res. 2020, 48, 0300060520925930. [Google Scholar] [CrossRef]
  230. Park, S.-H.; Lee, J.H.; Shin, J.; Kim, J.-S.; Cha, B.; Lee, S.; Kwon, K.S.; Shin, Y.W.; Choi, S.H. Cognitive Function Improvement after Fecal Microbiota Transplantation in Alzheimer’s Dementia Patient: A Case Report. Curr. Med Res. Opin. 2021, 37, 1739–1744. [Google Scholar] [CrossRef]
  231. Kim, N.; Jeon, S.H.; Ju, I.G.; Gee, M.S.; Do, J.; Oh, M.S.; Lee, J.K. Transplantation of Gut Microbiota Derived from Alzheimer’s Disease Mouse Model Impairs Memory Function and Neurogenesis in C57BL/6 Mice. Brain Behav. Immun. 2021, 98, 357–365. [Google Scholar] [CrossRef] [PubMed]
  232. Sun, J.; Xu, J.; Ling, Y.; Wang, F.; Gong, T.; Yang, C.; Ye, S.; Ye, K.; Wei, D.; Song, Z.; et al. Fecal Microbiota Transplantation Alleviated Alzheimer’s Disease-like Pathogenesis in APP/PS1 Transgenic Mice. Transl. Psychiatry 2019, 9, 1–13. [Google Scholar] [CrossRef] [PubMed][Green Version]
  233. Wang, M.; Cao, J.; Gong, C.; Amakye, W.K.; Yao, M.; Ren, J. Exploring the Microbiota-Alzheimer’s Disease Linkage Using Short-Term Antibiotic Treatment Followed by Fecal Microbiota Transplantation. Brain Behav. Immun. 2021, 96, 227–238. [Google Scholar] [CrossRef] [PubMed]
  234. Harach, T.; Marungruang, N.; Duthilleul, N.; Cheatham, V.; Mc Coy, K.D.; Frisoni, G.; Neher, J.J.; Fåk, F.; Jucker, M.; Lasser, T.; et al. Reduction of Abeta Amyloid Pathology in APPPS1 Transgenic Mice in the Absence of Gut Microbiota. Sci. Rep. 2017, 7, 41802. [Google Scholar] [CrossRef]
  235. Fujii, Y.; Nguyen, T.T.T.; Fujimura, Y.; Kameya, N.; Nakamura, S.; Arakawa, K.; Morita, H. Fecal Metabolite of a Gnotobiotic Mouse Transplanted with Gut Microbiota from a Patient with Alzheimer’s Disease. Biosci. Biotechnol. Biochem. 2019, 83, 2144–2152. [Google Scholar] [CrossRef]
  236. Zhan, G.; Yang, N.; Li, S.; Huang, N.; Fang, X.; Zhang, J.; Zhu, B.; Yang, L.; Yang, C.; Luo, A. Abnormal Gut Microbiota Composition Contributes to Cognitive Dysfunction in SAMP8 Mice. Aging 2018, 10, 1257–1267. [Google Scholar] [CrossRef]
  237. Dodiya, H.B.; Kuntz, T.; Shaik, S.M.; Baufeld, C.; Leibowitz, J.; Zhang, X.; Gottel, N.; Zhang, X.; Butovsky, O.; Gilbert, J.A.; et al. Sex-Specific Effects of Microbiome Perturbations on Cerebral Aβ Amyloidosis and Microglia Phenotypes. J. Exp. Med. 2019, 216, 1542–1560. [Google Scholar] [CrossRef][Green Version]
  238. Cui, B.; Su, D.; Li, W.; She, X.; Zhang, M.; Wang, R.; Zhai, Q. Effects of Chronic Noise Exposure on the Microbiome-Gut-Brain Axis in Senescence-Accelerated Prone Mice: Implications for Alzheimer’s Disease. J. Neuroinflammation 2018, 15, 190. [Google Scholar] [CrossRef]
  239. Valeri, F.; dos Santos Guilherme, M.; He, F.; Stoye, N.M.; Schwiertz, A.; Endres, K. Impact of the Age of Cecal Material Transfer Donors on Alzheimer’s Disease Pathology in 5xFAD Mice. Microorganisms 2021, 9, 2548. [Google Scholar] [CrossRef]
  240. Shanahan, F.; Quigley, E.M.M. Manipulation of the Microbiota for Treatment of IBS and IBD—Challenges and Controversies. Gastroenterology 2014, 146, 1554–1563. [Google Scholar] [CrossRef]
  241. Schmulson, M.; Bashashati, M. Fecal Microbiota Transfer for Bowel Disorders: Efficacy or Hype? Curr. Opin. Pharmacol. 2018, 43, 72–80. [Google Scholar] [CrossRef] [PubMed]
  242. Evrensel, A.; Ceylan, M.E. Fecal Microbiota Transplantation and Its Usage in Neuropsychiatric Disorders. Clin. Psychopharmacol. Neurosci. 2016, 14, 231–237. [Google Scholar] [CrossRef] [PubMed][Green Version]
  243. Choi, H.H.; Cho, Y.-S. Fecal Microbiota Transplantation: Current Applications, Effectiveness, and Future Perspectives. Clin. Endosc. 2016, 49, 257–265. [Google Scholar] [CrossRef] [PubMed]
  244. Tan, P.; Li, X.; Shen, J.; Feng, Q. Fecal Microbiota Transplantation for the Treatment of Inflammatory Bowel Disease: An Update. Front. Pharmacol. 2020, 11, 1409. [Google Scholar] [CrossRef] [PubMed]
Table 1. Gut microbiota-based biomarkers for AD.
Table 1. Gut microbiota-based biomarkers for AD.
Ref.JournalStudy Cohort and DesignAnalysis PerformedResultsBiomarker/s
Yan et al., 2021 [106]Front. Aging Neurosci.APP/PS1 transgenic mice (8 months old, n = 7) receiving fasudil (ADF group) or saline (ADNS group) were compared to age- and gender- matched WT miceFecal metagenomic and metabolitesFirmicutes/Bacteroidetes in ADNS compared to WT
Firmicutes/Bacteroidetes in ADF compared to WT
↑Metabolites involved in metabolism of nucleotides, lipids, sugars and inflammation
  • s_Prevotella_sp_CAG873 as ADF biomarker
  • s_Helicobacter_typhlonius and s_Helicobacter_sp_MIT_03-1616 as ADNS biomarkers
  • Glutamate, hypoxanthine, thymine, hexanoyl-CoA, and leukotrienes in ADF or ADNS
Bello-Medina et al., 2021 [107]Front. Neurosci.Mice 3xTg-AD 3 and 5 month-old (n = 10 females and n = 10 males) compared to matched controlsFecal sample collection, α and β diversity, LDA and LEfSeActinobacteria and TM7 in 3xTg-AD compared to controls at 3 month-old
≠ β diversity in female and male 3xTg-AD mice compared to controls
  • Actinobacteria and TM7 phylum alterations
  • β diversity changes
  • Increase in the bacteria families and genera: Gemella, Allobacullum and Selenomonas
Gu et al., 2021 [108]Alzheimers Res. Ther.APP/PS1 transgenic mice (n = 11) were compared to WT16S rRNA sequencing of the gut microbiome and integrated metabolomics↓ SCFA-producing bacteria (i.e., Parasutterella and Blautia) in APP/PS1 mice compared to controls
↑ Gut dysbiosis in APP/PS1 mice compared to controls
Firmicutes/Bacteroidetes in APP/PS1 compared to WT
  • Inflammatory factors (IL-6 and INF-γ), phosphatidylcholines and SCFA-producing bacteria as combinatorial biomarker for AD
Shen et al., 2017 [109]J. Alzheimers Dis.APP/PS1 transgenic mice were compared to WT16S rRNA sequencing↓ Gut microbiota diversity in APP/PS1 mice compared to controls
Prevotella in APP/PS1 compared to controls
Helicobacteraceae and Desulfovibrionaceae in APP/PS1 compared to controls
  • Gut microbiota signature in AD and controls
Chen et al., 2020 [110]Biomed. Res. Int.APP/PS1 transgenic mice were compared to WT controls (n = 14–24 at 1–2–3–9 months and n = 31–34 at 6 months)16S rRNA sequencing from fecal samplesProteobacteriaceae, Verrucomicrobiaceae, Bifidobacteriaceae, Erysipelotrichaceae and Prevotellaceae in APP/PS1 mice
Bacteroidaceae and Rikenellaceae in APP/PS1 mice
  • Changes in gut microbiota composition precede plaque deposition: early biomarker
Tan et al., 2020 111]Benef. MicrobesDrosophila melanogaster AD model compared to WT controls Gut microbiota composition analysisWolbachia in AD flies compared to controls
↓Gut microbiota diversity in AD flies compared to controls
  • Wolbachia as a potential biomarker for AD
  • Stenotrophomonas negatively correlated with neurodegeneration
Zhang et al., 2021 [112]Am. J. Clin. Nutr.Humans: 75 MCI individuals and 52 heathy controlsChanges in gut microbiota and serum miRNA expression↓ Microbial diversity, Faecalibacterium, Ruminococcaceae, Alipstes in MCI compared to controls
↑Proteobacteria and Gammaproteobacteria in MCI compared to controls
  • Differential gut microbiota composition, diet quality scores and serum miRNA as combinatorial biomarker for MCI patients
Li et al., 2019 [113]Alzheimers Dement.Humans: AD patients (n = 30), MCI patients (n = 30), heathy controls (n = 30). Analysis of microbiota community in the faeces and blood via 16S rRNA sequencing↓ Microbial diversity in AD and MCI compared to controls
≠ 11 genera in the feces and in the blood between AD/MCI and controls
= Genera in the blood and feces between AD and MCI
  • Changes in gut microbiota as early diagnosis in AD
Liu et al., 2019 [72]Brain Behav. Immun.Humans: AD patients (n = 33), MCI patients (n = 32) and healthy controls (n = 32)16S rRNA MiSeq sequencing and phylogenetic investigation of communities by recontruction of unobserved states↓ Microbial diversity in AD compared to MCI and controls
Firmicutes in AD compared to controls
Proteobacteria in AD compared to controls
Gammaproteobacteria, Enterobacteriales and Enterobacteriaceae in AD > MCI > controls
  • The abundance of the Enterobacteriaceae family as a differential diagnostic tool for AD, MCI and healthy individuals.
Ling et al., 2021 [73]Front. Cell Dev. Biol.Humans: 100 AD patients and 71 age- and gender- matched healthy controls16S rRNA Miseq sequencing of fecal microbiota↓ Microbial diversity in AD compared to controls
↓ Butyrate producing bacteria (Faecalibacterium)
↑ Lactate producing bacteria (Bifidobacterium)
  • Microbiota shift from butyrate producer to lactate producer genera (from Faecalibacterium to Bifidobacterium)
Vogt et al., 2018 [114]Alzheimer Res. Ther.Humans: AD patients (n = 40), MCI patients (n = 35) and healthy controls (n = 335)Cerebrospinal TMAO levels measurement↑ TMAO in AD and MCI compared to controls
  • TMAO levels in the cerebrospinal fluid
Wu et al., 2021 [115]NutrientsHumans: AD patients (n = 27), MCI patients (n = 22) and healthy controls (n = 28)LC/GC/MS metabolomics profiling of fecal microbiota↓ Tryptophan metabolites in MCI and, more pronounced, in AD compared to controls
↓ SCFAs in MCI and, more pronounced, in AD compared to controls
  • Indole-3-pyruvic acid and five SCFAs for pre-onset and progression of AD
Abbreviations: APP/PS1: APPswe/PSEN1dE9 transgenic; GC: gas chromatography; LDA: linear discriminant analysis; LEfSe: linear disciminant analysis effect size; LC = liquid chromatography; MCI: mild cognitive impaired; MS: mass spectrometry; SCFAs: short chain fatty acids; 3xTg; triple-transgenic mouse model of AD; TMAO: Trimethylamine N-oxide; WT: wild type; ↑: increase; ↓: decrease.
Table 2. Evidence of diet as a possible complementary therapy in AD.
Table 2. Evidence of diet as a possible complementary therapy in AD.
ReferencesType of StudiesDietary InterventionAimOutcomes
Duplantier et al., Nutrients, 2021 [166]27 ObS, 5 RCTMedi or DASH or MINDAssociation between diet and cognitive healthPromising results for Medi diet but inconsistent outcomes. Lack of accuracy and standard tools
Bartochowski et al., Curr. Nutr. Rep., 2020 [167]4 RCTMedi or MINDAssociation between diet and ADProtective and promising therapeutic role of Medi. Not enough evidence for MIND.
24 RCTVitamins and supplements (curcumin, EGb 761, EPA, DHA)No statistically significant results; promising evidence for vitamin D supplementation and curcumin use.
Gutierrez et al., Nutrients, 2021 [168]61 RCTDifferent dietary patternsEffects of nutrition on cognitive functionHealthy food consumption (Medi Diet) improves cognitive function. Polyphenols have protective effects. Low evidence for PUFAs, vitamin D and other supplements.
Limongi et al., J. Am. Med. Dir. Assoc., 2020 [169]38 LS and 7 RCTMediAssociation between diet and late-life cognitive disordersProtective and promising therapeutic role of Medi diet for cognitive impairment.
Kheirouri et al., Critical Reviews in Food Science and Nutrition, 2021 [170]9 CS, 3CrS, 1 RCTMINDAssociation between diet and neurodegenerative delay and cognitive functionsImprovement in cognition; limited number of studies and lack of mechanistic aspects in humans.
Lilamand et al., Curr. Opin. Clin. Nutr. Metab. Care, 2021 [171]8 ISKD or KSAssociation between diet and cognitive and biological/neuropathological outcomesEvident improvement: decrease in cerebral inflammation, Aβ-amyloid, aggregates of tau protein.
Grammatikopoulou et al., Adv. Nutr., 2020 [172]10 RCTKD or KSEffects of KD on patients with AD/mild cognitive impairmentImprovement in acute and long-term cognition.
Pavón et al., Nutr.
Rev., 2021 [173]
N/AKD or KSEffect of KD on cognitive skills in patients with AD, PD, refractory epilepsy, and type 1 glucose deficiency syndromeImprovements in memory, cognitive performance and learning capabilities
Jensen et al., Int. J. Mol. Sci., 2020 [174]N/AKD or KSEffects of KD on brain metabolism and function in neurodegenerative diseasesReduction in AD symptoms.
Christensen et al., Nord. J. Psychiatry, 2021 [175]24 RCTKD or KS or modified Atkins dietEffects of KD on CNS diseasesModified-Atkins diet significantly improved memory in AD patients.
Moreira et al., Dement. neuropsychol., 2020 [176]32 RCTOmega-3, nutritional formula including ginseng, inositol and coconut oilAssociation between diet and cognitive performance in ADOmega-3 fatty acids showed positive effects at different doses. Probiotic, Ginseng, Inositol and specialized nutritional formulas might have a positive effect on cognition.
Zhang et al., Nutrients, 2020 [177]12 CS, 3 case-control, 13 CrS, 1 IS MeatAssociation between meat (red meat, processed meat and poultry) consumption and cognitive functionsNo significant association.
Dimache et al., Nutrients, 2021 [178]21 (ObS, LS, CrS, IS) Association between triglycerides with cognitive, vascular cognitive impairment and amyloid accumulationIn longitudinal studies: TG level is associated with cognitive decline. In cross sectional studies no correlation.
Gkotzamanis et al., Psychiatriki, 2020 [179]4 RCTOmega-3Effect of supplementation on dementiaPromising preventative but not therapeutic effect.
6 RCTpolyphenols
El Gaamouch et al., Neurochem. Int., 2021 [180]N/A Grape polyphenolsAssociation between grape polyphenols and AD No significant results from interventions.
Colizzi et al., Alzheimers Dement. (N Y), 2019 [181]24 RCTPolyphenolsAssociation between polyphenols and AD12 studies found a positive correlation with reduced cognitive decline; 5 studies did not find any correlation and 7 studies reported mixed results.
Mielech et al., Nutrients, 2020 [182]8 CS/RCTVitamins BAssociation between antioxidant vitamins and AD and cognitive decline4 studies: beneficial effect slowing cognitive decline; 4 studies: no differences
3 CS/RCTVitamin AProtective effect for cognitive functions in 2 studies.
7 CS/RCTVitamins C and EProtective effect for AD in 5 studies.
7 CS/RCTVitamin DLow level in the serum associated with increased risk of cognitive decline; no positive correlation with supplementation.
Szczechowiak et al., Pharmacology Biochemistry and Behavior, 2019 [183]N/APro-inflammatory (rich in saturated fats, meat) vs. anti-inflammatory (rich in vitamins, antioxidants, probiotics) dietAssociation between pro- and anti-inflammatory diets and AD prevention and treatmentOverconsumption of foods rich in d-AGEs (Dietary Advanced Glycosylation End-products), saturated fats and red and processed meat have a pro-inflammatory influence on AD patients’ brains.
Kosti et al., Nutr. Rev., 2021 [184] Fish, EPA/DHA supplementationAssociations between fish intake and AD dementia or AD and the effect of EPA/DHA supplementation on cognitive performance.Regular consumption of fish up to 2 portions per week seems to be more protective than EPA/DHA supplementation.
Haider et al., International Journal of Geriatric Psychiatry, 2020 [185]4 RCTVitamins B and E, omega-3, polyunsaturated fatty acids. Effects of nutritional supplementation
on neuropsychiatric symptoms among people with dementia
No significant results.
Arbo et al., Front. Aging Neurosci., 2020 [186]3 RCT, 1 retrospective studyResveratrolEffect of resveratrol as potential treatment in AD and PDNo significant results in human trails.
Abbreviations: CrS: cross sectional study; CS: cohort studies; DHA: docosahexaenoic acid; EGb 761: Ginkgo biloba extract 761; EPA: eicosapentaenoic acid; KD: ketogenic diet; KS: ketogenic supplement; IS: interventional study; LS: longitudinal study; Obs: observational studies; RCT: randomized controlled trial.
Table 3. Murine and human studies performing FMT in AD.
Table 3. Murine and human studies performing FMT in AD.
Ref.JournalStudy Cohort/Sample SizeDonorRecipientTransplantation TechniqueResults
Hazan et al., 2020 [229]J. Int. Med. Res.Case study (n = 1)85-year-old woman (recipient’s wife)82-year-old man with recurrent CDI and ADSingle 300 mL FMT infusion↑ Cognitive function (MMSE test)
↑ Memory
↑ Mood
Park et al., 2021 [230]Curr. Med. Res. Opin.Case study (n = 1)27-year-old healthy man90-year-old woman with AD and severe CDIColonoscopy (60 g of stool suspension for 2 times).↑ Cognitive function tests (MMSE, MCA and CDR tests)
↑ Microbiota α diversity
= Microbiota β diversity
Kim et al., 2021 [231]Brain. Behav. Immun.Mouse
(n = 8)
5xFAD miceC57BL/6 mice Oral gavage (200 ul for 5 consecutive days)↓ Adult hippocampal neurogenesis and BDNF expression
↑ p21 expression
↑ Microglia activation
↑ TNF-α and IL-1β
↑Colon and plasma pro-inflammatory cytokines
Sun et al., 2019 [232]Transl. PsychiatryMice
(n = 8)
WT miceAPPswe/PS1dE9 transgenic (Tg) mouse modelIntragastrically (0.2 mL of fresh fecal solution once daily for 4 weeks)↑ Cognitive function (MWM and ORT tests)
↓ Amyloid β brain deposition (Aβ40 and Aβ42)
↓ Tau protein phosphorylation
↑ Synaptic plasticity (increased PSD-95 and synapsin I)
↓ COX2 and CD11b
↑ SCFA and microbiota composition
Wang et al., 2021 [233]Brain. Behav. Immun.Mice
(n = 4)
16 months old APPSWE/PS1ΔE9 mice3 months old APPSWE/PS1ΔE9 miceAntibiotic cocktails for 2 weeks by gavage and then FMT for 7 consecutive days by oral gavage↑ Aβ plaques
↓ Astrocyte activation around Aβ plaques
Kim et al., 2020 [10]GutMice (n = 16)WT miceADLPAPT transgenic mouse modelFresh fecal matters for 16 weeks by oral gavage or for 4 weeks in mice pre-treated with antibiotics↓ Aβ plaques
↓ Neurofibrillary tangles
↓ Glial reactivity
↓ Cognitive impairment
↓ Circulating blood inflammatory monocytes
Harach et al., 2017 [234]Sci. Rep.Mice
(n = 6)
12 month-old) CONVR-WT or CONVR-APPPS1 mice4 month-old GF-APPPS1 miceOral gavage of fecal contents on day 1 and day 4↑ Cerebral Aβ pathology
Fujii et al., 2019 [235]Biosc. Biotechnol. Biochem.Humanized mice
(n = 7)
4-weeks old germ-free C57BL/6N miceHuman healthy volunteers (76-year-old female) or AD patients (82-year-old male)Oral inoculation↓ OLT and ORT in mice colonized with AD microbiome
↓ γ-aminobutyrate, taurine and valine in mice colonized with AD microbiome
Zhan et al., 2018 [236]AgingMice
(n = 8)
SAMP8 or SAMR1 micepseudo germ-free mice0.2 mL fecal suspension by gavage for 14 days↑ Behaviour (only from SAMR1 transplant)
↑ α diversity and β diversity (only from SAMR1 transplant)
↓ Abnormal microbiota
Dodiya et al., 2019 [237]J. Exp. Med.Mice
(n = 9)
age-matched APPPS1-21ABX-treated APPPS1-21 male0.2 mL fecal slurry by gastric gavage daily starting on P25 until sacrifice↓ Aβ pathology
↑ Microglial physiology
Cui B. et al.,2018 [238]Journal of NeuroinflammationMice
(n = 6)
Low intensity noise (LN) exposure SAMP8 mice (control group) and high intensity noise (HN) exposure (AD model group)male 3-month-old SAMP8 mice0.1 mL fecal preparation via oral gavage twice per week for 30 days↑ CLDN1 and ZO-1 in intestine and hippocampus of HN microbiota recipient
↑ Aβ in hippocampus of the HN microbiota recipient
Valeri et al., 2021 [239]MicroorganismsMice
(n = 10)
Either 4 months old or 1 year old wild type mice5xFAD mice (4-month old)150 µ fecal preparation via oral gavage one time after antibiotics-treatmentEnterobacteriaceae, Lactobacillaceae, serum LPS binding protein
↑ Plaques in dentate gyrus and prefrontal cortex
ABX: antibiotic cocktail; APPSWE/PS1L166P: APPPS1-21; BDNF: brain derived neurotrophic factor; CDI: Clostridioides difficile infection; CDR: Clinical Dementia Rating assessment; CLDN1: claudin 1; CONVR-APPPS1: conventionally-raised transgenic APPPS1 mice; COX2: cyclooxygenase 2; FMT: fecal microbiota transplantation; LPS: lipopolysaccharide; MCA: Montreal Cognitive Assessment; MMSE: Mini-Mental State Examination; MWM: Morris water maze test; OLT: object location test; ORT: object recognition test; PSD-95: postsynaptic density protein 95; SAMP8: senescence-accelerated mouse prone 8; SAMR1: senescence-accelerated mouse resistant 1; SCFAs: short chain fatty acids; ZO-1: Tight junction protein-1; ↑: increase; ↓: decrease.
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Varesi, A.; Pierella, E.; Romeo, M.; Piccini, G.B.; Alfano, C.; Bjørklund, G.; Oppong, A.; Ricevuti, G.; Esposito, C.; Chirumbolo, S.; et al. The Potential Role of Gut Microbiota in Alzheimer’s Disease: From Diagnosis to Treatment. Nutrients 2022, 14, 668.

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Varesi A, Pierella E, Romeo M, Piccini GB, Alfano C, Bjørklund G, Oppong A, Ricevuti G, Esposito C, Chirumbolo S, et al. The Potential Role of Gut Microbiota in Alzheimer’s Disease: From Diagnosis to Treatment. Nutrients. 2022; 14(3):668.

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Varesi, Angelica, Elisa Pierella, Marcello Romeo, Gaia Bavestrello Piccini, Claudia Alfano, Geir Bjørklund, Abigail Oppong, Giovanni Ricevuti, Ciro Esposito, Salvatore Chirumbolo, and et al. 2022. "The Potential Role of Gut Microbiota in Alzheimer’s Disease: From Diagnosis to Treatment" Nutrients 14, no. 3: 668.

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