Skip to main content
Download PDF

Exploring the gut-brain axis in alzheimer’s disease treatment via probiotics: evidence from animal studies-a systematic review and meta-analysis

BMC Neurology volume 24, Article number: 481 (2024) Cite this article

Abstract

Introduction

Alzheimer’s disease (AD) is a prevalent neurodegenerative disorder in the elderly, causing cognitive impairment. Its pathogenesis is characterized by amyloid beta deposition, neurofibrillary tangles, and neuroinflammation. Recent research has identified the link between gut dysbiosis, an imbalance of intestinal microorganisms, to this pathogenesis via the gut-brain axis. This study aims to review the probiotics’ therapeutic effect, targeting the gut-brain axis, for AD treatment in animals.

Methods

The method utilized in this study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. Three reviewers searched articles through PubMed, Scopus, and Embase using advanced search strategy. Articles published between 2010 and 2023 that met the criteria were included.

Results

Of 2,273 articles, 21 animal studies measuring the effects of probiotics genera Lactobacillus and/or Bifidobacterium on AD via at least one of these four outcomes: AD pathology, cognitive function, neuroinflammation, and gut microbiota composition. The results demonstrated that probiotics could repair gut dysbiosis by decreasing pro-inflammatory bacteria and increasing anti-inflammatory bacteria. Repaired dysbiosis was found to be associated with less neuroinflammation as significant reductions in neuroinflammatory markers related to the pathogenesis of AD such as TNF-α (SMD = -2.08, P = 0.005), IL-6 (SMD = -2.98, P < 0.0005), and IL-1β (SMD = -2.49, P = 0.003) were observed. Reduced amyloid beta deposition (SMD = -1.17, P = 0.009) was reported, but reduction in tau hyperphosphorylation was found to be insignificant. For cognitive function, positive results were demonstrated for all three aspects of cognitive function including long-term memory (SMD = 2.55, P < 0.00001), short-term memory (SMD = 1.32, P = 0.003), and spatial recognition (SMD = -1.13, P < 0.00001).

Conclusions

Particular formulas of probiotics showed potential effectiveness in AD therapies with demonstrated association with the gut-brain axis. Future studies are required to investigate strain-specific results and optimal dosages and regimens.

Peer Review reports

Introduction

Every five years after turning 65, the number of people with AD doubles. According to the Centers for Disease Control and Prevention, this number will nearly triple by 2060, reaching 14 million, making it one of the significant issues in the future [1]. AD risk increases from the age 65 to 85 by 3% to nearly 30%. AD can develop before 65 (early onset) or after 65 (late onset) [2]. Most of the cases are late onset. Even though there are substantial studies on amyloid beta and tau protein as pathologic features of this disease, it is still challenging to understand the causes of this disease because patient-specific risk factors combination can cause AD via various mechanisms [3].

Since the beginning of the twentieth century, amyloid-beta deposition and tau hyperphosphorylation have been the hallmark of cognitive decline [4]. The hyperphosphorylation of tau causes tau aggregation, leading to paired helical filament-like structures. This is the component of neurofibrillary tangles, which is a hallmark of AD [5]. One of the earliest signs of this disease is memory loss. Short-term memory is mostly impaired in its early stages. However, patients will become more forgetful after the disease progresses or lose long-term memory [6].

Besides short and long-term memory loss, spatial memory impairment can also be found in mild AD patients [7]. Spatial memory is the memory that is used to return to rewarding locations such as home. This memory is found to be crucial in a variety of animals from invertebrates to humans [8]. There is also evidence that certain inflammatory markers, such as tumor necrosis factor (TNF), interleukin-6 (IL-6), and acute phase reactant protein C reactive protein (CRP), act on the brains or the peripheral areas of dementia patients [9].

Although there are several proposed pathogeneses of this disease, there is still a lack of effective treatment for this disease. The recent investigation exposed a gap in our knowledge of AD pathology by claiming the hypothesis that gut microbiota are related to brain development and behavioral functions [10]. Through systems like the immune system, neuroendocrine system, and autonomic nervous system, the gut microbiota communicates in both directions with the central nervous system (CNS). Microbiota creates metabolites and neuroactive substances. These substances can affect immunological reactions, metabolism, brain signaling, and integrity of intestinal barriers [11]. The brain also directly influences the function of the gut by releasing signaling molecules to control the physiological function of the gastrointestinal system in relation to hunger and satiety [12].

Gut dysbiosis is a general term that is used to describe the imbalance of the gut microbiota that can lead to negative consequences [13]. Gut dysbiosis may make it easier for pathogens to enter the blood and brain because it increases permeability and damages the intestinal barrier and blood–brain barrier (BBB), leading to the state of leaky gut and BBB, increasing neuroinflammation and triggering amyloid accumulation, which is a primitive immune response in the brain. Consequently, raised IL-6 levels in the blood are a way that increased intestinal permeability and microbial dysbiosis cause systemic inflammation in the body [14]. It is also suggested that systemic inflammation in AD causes proinflammatory microglial and astrocytic characteristics. These phenotypes promote tau hyperphosphorylation, oligomerization, component activation, and the degradation of neurotransmitters into potentially harmful metabolites [15].

One way to disrupt the pathogenesis of AD is to repair gut dysbiosis or alter the gut microbiota composition by adding beneficial bacteria to the gut lumen. The beneficial bacteria that can improve people's health when consumed are called probiotics. Probiotics can be found in several dietary choices, including yogurt, fermented foods, dietary supplements, and cosmetics products. Some strains can produce vitamins, assist in the breakdown of disease-causing cells, and aid with food digestion [16]. Several bacteria may be present in probiotics. Bacteria from the families Lactobacillus and Bifidobacterium are the most prevalent. As probiotics, other bacteria and yeasts such as Saccharomyces boulardii, may be employed. Different species and strains of probiotics exhibit different properties on human bodies [16].

Several studies have evaluated current evidence on the application of probiotic treatments for the therapeutic purpose of AD and other neurological disorders [17, 18]. However, only a few studies demonstrated the therapeutic effects of probiotics on AD by covering the four important parameters and outcome measurements including AD pathology, cognitive function, neuroinflammation, and gut microbiota composition. Hence, this systematic review and meta-analysis aims to assess the therapeutic potential of probiotics via all of these four main outcome measurements enabling the discussion about potential mechanisms of probiotics on the gut-brain axis which is currently unclear.

Materials and methods

Eligibility criteria

The study inclusion criteria were: (i) controlled trials focusing on probiotics genera Lactobacillus and/or Bifidobacterium (ii) studies conducted only in animals (iii) studies investigating at least one of the following outcomes: AD pathology, cognitive function, neuroinflammation, and gut microbiota composition (iv) a study published in English (v) a study published in year 2010–2023. While (i) reviews, meta-analyses, case reports, commentaries and patents (ii) studies investigating probiotics combined with other interventions were excluded.

Search Strategy and Study Selection

The literature was done following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [19]. A systematic search of the literature was conducted in PubMed, Central, Embase, and Scopus using search string (Supplementary material 1): from 2010 to April 2023.

Three reviewers independently screened and included the title, abstracts, and full-text articles that meet the criteria based on the Fig. 1. The initial search yielded 2,273 studies, of which 359 duplicates were removed. A total of 1,851 articles were ruled out as they did not meet the inclusion criteria, which resulted in 63 studies eligible for full-text evaluation. Another 42 articles were excluded due to wrong outcomes, population, intervention, or study design, along with no full-texts available. Consequently, 21 studies were included in this review.

Fig. 1
figure 1

PRISMA flow chart

Full size image

Risk of bias assessment

The risk of bias was assessed using the Systematic Review Center for Laboratory Animal Experimentation (SYRCLE), based on the Cochrane Collaboration Risk of Bias tool and adapted to be more specific to animal research [20]. Ten domains consist of sequence generation, baseline characteristics, allocation concealment, random housing, blinding (performance bias), random outcome assessment, blinding (detection bias), incomplete outcome data, selective outcome, and other sources of bias. The risk of bias was assessed by answering SYRCLE’s signaling questions with “yes” indicating low risk of bias, “no” indicating high risk of bias, and “unclear” indicating an unclear risk of bias. The number of yeses compared to the number of SYRCLE items were calculated as a summary score. Two of three reviewers conducted an assessment, and consensus resolved discrepancies Fig. 2.

Fig. 2
figure 2

Table of risk of bias assessment (+ reflects yes, x reflects no, and—reflects unclear)

Full size image

Study characteristics (Table 1)

Table 1 Overview of characteristics of included studies
Full size table

Statistical analysis

The RevMan 5.4 software [41] was used for meta-analysis. The primary outcome of this study was the standardized mean differences (SMDs) of AD pathology, cognitive function, and neuroinflammation between control group and experimental group. A Z statistical test tested the SMDs, and a two-tailed P < 0.05 was considered statistically significant. A P value of 0.10 is used for the test of heterogeneity. The I2 statistic, ranging from 0 to 100%, indicates the magnitude of heterogeneity. Greater I2 indicates more heterogeneity. The I2 below 40% may suggest no important heterogeneity, while the I2 over 75% may suggest considerable heterogeneity [42]. For all analyses, SMDs were calculated by a random-effects model.

Results

The research results consist of three animal types: mice, rats, and drosophila. The outcomes from 21 studies were grouped into four categories: AD pathology, cognitive function, neuroinflammation, and gut microbiota composition. The numerical results were reported using SMD with 95% confidence intervals and presented in a forest plot. We used AD animals as models and administered probiotics to the intervention group.

AD pathology

Pooled data from included studies show a significant reduction of amyloid beta deposition in AD induced animals (SMD = −1.17, P = 0.009) (Fig. 3), however, probiotics treatment did not show a significant reduction in tau hyperphosphorylation (SMD = 0.36, P = 0.35) (Fig. 4).

Fig. 3
figure 3

Forest plot showing the effects of probiotics treatment on amyloid beta deposition in AD induced animals (ng/mL)

Full size image
Fig. 4
figure 4

Forest plot showing the effects of probiotics treatment on tau hyperphosphorylation in AD induced animals (relative value)

Full size image

Cognitive function

For the next parameter, cognitive function. The included studies’ data were grouped into three categories which are short-term memory, long-term memory, and spatial recognition. Short-term memory, using results from the y-maze test to assess the animals' short-term memory. The y-maze test was the method used to assess animals’ willingness to explore new environments. The results show a significant improvement in the probiotics treatment group (SMD = 1.32, P = 0.003) (Fig. 5). For long-term memory, the passive avoidance test was used to evaluate the animals’ latency time to avoid an unpleasant stimulus. The results showed a significant improvement in the probiotics treatment group (SMD = 2.55, P < 0.00001) (Fig. 6). Spatial recognition was measured using the Morris water maze test which is the test that observes animals’ ability to find a hidden platform in the water. The results also showed a significant improvement in probiotic treatment group (SMD = −1.13, P < 0.00001) (Fig. 7).

Fig. 5
figure 5

Forest plot showing the effects of probiotics treatment on short term memory of AD-induced animals (percent of alteration)

Full size image
Fig. 6
figure 6

Forest plot showing the effects of probiotics treatment on long term memory of AD-induced animals using the unit latency time (second)

Full size image
Fig. 7
figure 7

Forest plot showing the effects of probiotics treatment on spatial recognition of AD induced animals using the unit latency time (second). Combined probiotics A = L. reuteri, L. rhamnosus, and B. infantis. Combined probiotics B = L. acidophilus, L. fermentum, B. lactis, and B. longum. Combined probiotics C = L. acidophilus, B. bifidum and B. longum in capsulated form

Full size image

Neuroinflammation

In this review, the neuroinflammatory markers from all findings were into three groups: inflammatory markers, glial cell markers, and synaptic plasticity markers. TNF-α, IL-1β, and IL-6 from inflammatory markers group, Ionized calcium-binding adaptor molecule 1 (Iba1), Glial fibrillary protein (GFAP) from glial cell markers group, and Brain-derived neurotrophic factor (BDNF) from synaptic plasticity markers group were selected for the study as shown in the figures.

Probiotic-fed groups showed significant decreases in TNF-α (SMD = −2.08, P = 0.005) (Fig. 8), IL-1 (SMD = −2.49, P = 0.003) (Fig. 9), and IL-6 (SMD = −2.98, P = 0.0005) (Fig. 10), Iba1 (SMD = −3.12, P = 0.002) (Fig. 11). However, no significant change in GFAP level was observed (SMD = −1.87, P = 0.12) (Fig. 12). Moreover, the experimental groups showed a significant increase in BDNF (SMD = 2.23, P = 0.04) (Fig. 13).

Fig. 8
figure 8

Forest plot showing the effects of probiotics treatment on TNF-α level (pg/mg)

Full size image
Fig. 9
figure 9

Forest plot showing the effects of probiotics treatment on IL-1β level (pg/mg)

Full size image
Fig. 10
figure 10

Forest plot showing the effects of probiotics treatment on IL-6 level (relative value)

Full size image
Fig. 11
figure 11

Forest plot showing the effects of probiotics treatment on Iba1 level (relative value)

Full size image
Fig. 12
figure 12

Forest plot showing the effects of probiotics treatment on GFAP level (relative value)

Full size image
Fig. 13
figure 13

Forest plot showing the effects of probiotics treatment on BDNF level (relative value)

Full size image

Gut microbiota composition

Among all included studies, eleven studies measured gut microbiota composition changes in the probiotic-treated group (Table 2). Two aspects of microbiome composition were assessed, diversity and abundance. Six studies investigated the effects of probiotics on gut microbiome diversity. Four studies observed an increase in either or both alpha and beta diversity, while Webberley et al. and Abdelhamid et al. observed no significant change in alpha diversity and both types of diversity, respectively. All eleven studies measure the changes in abundance of the bacteria. At phylum level, increases in phylum Verrucomicrobia, Actinobacteria and Firmicutes as well as decreases in phylum Proteobacteria and Bacteroidetes were observed. At family level, family Lactobacillaceae, Bifidobacteriaceae, Lachnospiraceae, Oscillospiraceae, and Ruminococcaceae were found in increased richness, while family Rikenellaceae, Christensenellaceae, AC160630_f, Prevotellaceae, Muribaculaceae, Odoribacteraceae and Lachnospiraceae decreased in richness. At genus level, Genus Bifidobacterium, Akkermansia, Faecalibacterium, Erysipelatoclostridium, Candidatus_Stoquefichus, LLKB_g, PAC001092_g, Stenotrophomonas, Serratia, Corynebacterium_1, Enterococcus, Parabacteroides, Alistipes, Coprobacillus, Aerococcus, Jeotgalicoccus, Prevotella, and Candidatus arthromitus, Pseudomonas, Acetatifactor, and Millionella increases, while genus Parvibacter, Incertae_Sedis, Oscillibacter, Coprococcus, Alistipes, Helicobacter, Wolbachia, Desulfovibrio, Intestinimonas, and unidentified Ruminococcaceae were found in decreased abundance compared to AD group. Some studies showed increases in genus Lactobacillus and Bacteroides, while some showed decreases in both. At species level, increases in species Akkermansia muciniphila and Lactobacillus reuteri and a decrease in species PAC001071_s were observed. However, Abdelhamid et al. reported no significant change in microbiome richness.

Table 2 Results of gut microbiota composition in terms of richness and diversity in AD animals that were treated with probiotics compared with AD animals without probiotic supplementation
Full size table

Discussion

Potential mechanism of probiotics on the gut-brain axis

Role of the gut-brain axis on the pathogenesis of AD

Several studies mentioned the protective effects of probiotics along the gut-brain axis, which is eventually linked to the pathogenesis of AD. To elucidate the potential mechanism of action of this therapeutic intervention, the pathogenesis of AD that is a result of the alteration of the gut-brain axis should be discussed. One postulated AD pathogenesis mentioned gut dysbiosis as the cause [43]. Gut dysbiosis, characterized by an increase in Firmicutes/Bacteroidetes ratio, leads to a decrease in the releases of protective microbial metabolites and an increase in the release of harmful microbial metabolites such as Trimethylamine-N-oxide (TMAO), which has been claimed to deteriorate the cognitive functions during the aging process in mice models [44]. Short-chain fatty acids (SCFA), protective microbial metabolites, exhibit protective effects on AD via the disruption of toxic soluble Aβ aggregates formation [45]. These alterations in microbial metabolites lead to the state of a leaky intestinal barrier and blood–brain barrier, activating peripheral immune responses and central oxidative stress levels. This eventually leads to neuroinflammation and amyloid plaque deposition [43].

Gut dysbiosis as AD therapeutic target of probiotics

According to the results from four outcome measurements, probiotics as therapeutic interventions for AD may reduce the pathogeneses via treating gut dysbiosis. The findings from the included studies supported this hypothesis as a partial restoration of both alpha and beta diversity, as well as a decrease in Firmicutes/Bacteroidetes ratio in the probiotic-treated AD group, were reported [22, 23, 38]. Changes in the abundance of particular bacteria were also investigated. Probiotics increase the “good” bacteria, which exhibit anti-inflammatory effects on the gut while decrease the “bad” bacteria, which exhibit pro-inflammatory effects on the gut. Phylum Proteobacteria, claimed as a microbial signature of gut dysbiosis, was found in a decreased abundance [23]. At the genus level, significant changes in some particular groups of bacteria were mentioned: increases in genus Akkermansia, Acetobacter, Strenotrophomonas, and Lactobacillus and a decrease in genus Wolbachia. These changes in abundance may result in altered metabolites and oxidative stress leading to less neuroinflammation, neuronal damage and amyloid plaque deposition. For instance, Lactobacillus spp. was found to have anti-oxidative potential in the aging process in animal models [46].

Effects of probiotics on neuroinflammatory responses and AD pathology

Aβ plaque deposition is strongly supported by scientific evidence to be the hallmark of AD. From the findings of the studies measuring this parameter, probiotics can significantly reduce Aβ deposition in AD animal models. Another distinctive feature of AD patients’ brains is tau hyperphosphorylation. However, the findings of the effects of probiotics on tau hyperphosphorylation were insignificant, indicating that cognitive function improvements are not associated with this mechanism. Another hypothesis that may be associated with the negative findings of tau hyperphosphorylation is host genetic variation which was not included in the inclusion or exclusion criteria of this study. While gut microbiota composition may strongly be influenced by various environmental factors such as diet, lifestyle, host genetic factor is also considered a strong regulator of the host microbiome [47, 48]. A recent study has investigated the interrelationships between gut microbiota, neuroinflammation, and tau-mediated neurodegeneration using genetically engineered mouse model of taupathy with human ApoE isoforms expression. The results showed that gut microbiota alteration reduced gliosis, tau pathology, and neugeneration. However, these manipulations occur in a sex- and ApoE isoform-dependent manner [48,49,50]. This implies that the relationship between gut microbiota alteration and reduced tau hyperphosphorylation may not show positive correlation in animal models without ApoE expression.

Neuroinflammatory responses were measured in some included studies to monitor the progression of AD. Neuroinflammation, inflammation within the central nervous system, leads to an activated state of astrocytes and microglia which eventually promotes amyloid beta plaque deposition [51]. However, a piece of scientific evidence mentioned that neuroinflammation itself may also possibly be the direct etiology of AD since treatments that can effectively reduce Aβ plaque deposition cannot delay or thwart the progression of AD in some studies [52]. Hence, neuronal damage in AD may directly or indirectly come from neuroinflammation.

In this study, probiotic-treated AD groups demonstrated significantly lower levels of pro-inflammatory cytokines, including TNF-ɑ, IL-1β, and IL-6. The findings in most studies that measured both neuroinflammatory cytokines and gut microbiota profile support the hypothesis that altered gut microbiota profile may influence neuroinflammatory processes. Interestingly, Abdelhamid et al. observed no significant change in gut microbiota profile, but a significant decrease of IL-6 and IL-1β in the hippocampus and cortex were reported in the probiotic-treated AD group, suggesting that other possible mechanisms of probiotics without treating dysbiosis may also exist [33, 34].

Glial hyperactivation was also measured via two biomarkers, Iba1 and GFAP levels, respectively. Oral supplementation of probiotics significantly decreases the level of Iba1 protein, while there are no significant alterations in GFAP, an astrocytic marker, in the probiotic-treated AD group. This suggests that probiotic supplementation may be associated with the attenuation of microglial activation.

BDNF, as a synaptic plasticity marker, controls the metabolism of glucose and energy and shows preventive properties towards the exhaustion of beta cells. A decrease in BDNF level is associated with neurodegenerative diseases with neuronal loss [53]. The findings in this study demonstrated the therapeutic effects of probiotics on synaptic plasticity as BDNF levels were restored after the probiotic supplementation.

Effects of probiotics on cognitive functions

Cognitive functions in animal models were assessed in three different aspects: spatial recognition using the Morris water maze test, short-term memory using the Y-maze test, and long-term memory using the passive avoidance test. Probiotics can significantly improve spatial recognition, long-term memory and short-term memory as shown in Figs. 5, 6, 7. In some studies, AD Mice treated with B. breve XY from Zhu et al. did not show obvious improvement in behavioral tests in spite of the reduction in Aβ plaque deposition [22]. This suggests that further application should consider clinical significance in accordance with measured pathology.

Dosages & feasibility in delivering therapeutic doses in human

Dosages of probiotic administration are among the biggest concerns in clinical application As dosages in certain animal studies that showed positive results may not be able to be administered in human. Hence, human equivalent dose (HED) should be considered. Conversion to HED of probiotics was performed (except included studies with drosophila models due to no available data for dosage conversion and those with inadequate information) using the method from Nair et al. that is based on body surface area [54]. The extrapolated HED was presented in Supplementary material 2 which is adjusted to the dosage per day for 60 kg in weight for human. The dosage ranges from a minimum of 9.72 × 108 CFU/day to a maximum of 8.75 × 1014 CFU/day. Compared with the doses in commercial yogurts, the doses range from 4.8 × 109 to 9.5 × 1010 CFU per a single 100 mL serving [55]. Moreover, probiotic dosages that were used in human studies about obesity-related microbiota dysbiosis range from 1 × 108 CFU/day to 1.35 × 1015 CFU/day [56]. Therefore, the doses in the included studies can be delivered in human. Although this extrapolation may show feasibility in the admistration of probiotic in clinical setting, higher CFU counts may not reflect improvement in therapeutic effects [57]. This would suggest further studies in human to investigate optimal dosages for clinical use.

Limitations, strengths and suggestions for further studies

There are some limitations of this study to be considered. The first limitation is the variations in outcome measurements. As the inclusion criteria for outcomes measured in included studies were set to measure at least one out of four outcomes, including AD pathology, cognitive function, neuroinflammation, and gut microbiota composition, a direct comparison of a single outcome among all included studies could not be made. Moreover, one outcome may be measured via different methods. For instance, the measurements of amyloid beta plaque deposition were done in different manners, such as histological examination and quantification of amyloid beta plaque, which resulted in different units of measurement. Different aspects of cognitive function assessment in each study, such as short-term memory and spatial recognition, also make it difficult for the conclusions to be drawn. The second limitation includes the variations in strains and dosages of probiotics treatment, species of animal models, and intervention time. There are three species of animal models included in this study: mice, rats, and drosophila. The lifespans of each species vary. Along with the differences in the intervention time, variations in the percentage of intervention time per lifespan may disrupt the conclusion of long-term results of probiotics on AD which are the effect that lasts long even after a certain period of time of the intervention cessation. Most studies did not continue to observe these effects such as the progression of AD pathology, cognitive function. For instance, the gut microbiota composition was not continuously detected to find the duration of the probiotic action or the duration when the pathology may return after the cessation of probiotic administration. The third limitation is AD pathological conditions created in animal models. Different substances were used to simulate the pathological condition of AD. Most studies injected intrahippocampal amyloid beta into animal models, which may not be able to fully represent the actual pathological conditions of AD in humans.

The strengths of this study are the demonstration of the therapeutic effects of probiotics on AD via several parameters and outcome measurements, which enables the discussion about potential mechanisms of probiotics on the gut-brain axis. Despite the variations in probiotic strains and animal species, probiotics still reveal promising therapeutic results in most outcomes.

Further studies are suggested to focus on strain-specific results of probiotics in clinical settings. It should be noted that different species respond differently to the same interventions. Hence, more clinical trials should be done to elucidate clearer mechanisms of each strain of probiotics on AD, optimal dosages, and possible side effects. Moreover, the effects of long-term use of probiotics on memory impairment and cognitive function should be assessed. Importantly, the safety of each strain or formula is the primary concern. Probiotics are claimed as Generally Recognized as Safe (GRAS) by the American Food and Drug Administration (FDA) [58]. Some widely-mentioned strains for treating AD include L. acidophilus, L. casei, B. bifidum, L. fermentum [58]. However, probiotics should be used with caution in some situations, including immunodeficient patients, premature babies, patients with a catheter inserted into large veins, and patients in severe clinical conditions [58].

Conclusion

This study demonstrates the effects of probiotic administration in animal models on multiple outcomes including gut microbiota profile, AD pathology, neuroinflammation, and cognitive function. The results showed significant reductions in Aβ plaque deposition, decreased neuroinflammation, and improved cognitive function along with the alterations in gut microbiota profile in both diversity and richness. Future studies are suggested to further elucidate the strain-specific results and optimal dosages and regimens before clinical application.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

AD:

Alzheimer’s disease

PRISMA:

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Iba1:

Ionized calcium-binding adaptor molecule, also called allograft inflammatory factor 1, is a well-established marker for microglia/macrophages

BDNF:

Brain-derived neurotrophic factor (BDNF) plays an important role in neuronal survival and growth, serves as a neurotransmitter modulator, and participates in neuronal plasticity, which is essential for learning and memory. It is widely expressed in the CNS, gut and other tissues

References

  1. Blennow K, de Leon MJ, Zetterberg H. Alzheimer’s disease. Lancet. 2006;368:387–403.

    Article  CAS  PubMed  Google Scholar 

  2. Sheppard O, Coleman M. Alzheimer's disease: etiology, neuropathology and pathogenesis. In: Huang X, editor. Alzheimer's disease: drug discovery. Brisbane (AU): Exon Publications; 2020.

  3. Centers for Disease Control and Prevention. About Alzheimer’s Disease. 2023. https://www.cdc.gov/aging/aginginfo/alzheimers.htm.

  4. d’Errico P, Meyer-Luehmann M. Mechanisms of pathogenic tau and abeta protein spreading in Alzheimer’s disease. Front Aging Neurosci. 2020;12:265.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Turab Naqvi AA, Hasan GM, Hassan MI. Targeting Tau hyperphosphorylation via kinase inhibition: strategy to address Alzheimer’s disease. Curr Top Med Chem. 2020;20:1059–73.

    Article  PubMed  Google Scholar 

  6. Jahn H. Memory loss in Alzheimer’s disease. Dialogues Clin Neurosci. 2013;15:445–54.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Gazova I, Vlcek K, Laczo J, et al. Spatial navigation—a unique window into physiological and pathological aging. Front Aging Neurosci. 2012;4:16.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Pritchard DJ. Spatial memory☆. In: Choe JC, editor. Encyclopedia of animal behavior. 2nd ed. Oxford: Academic Press; 2019. p. 320–6.

  9. Zhu Y, Chai YL, Hilal S, et al. Serum IL-8 is a marker of white-matter hyperintensities in patients with Alzheimer’s disease. Alzheimer’s Dementia: Diagn Assess Dis Monit. 2017;7:41–7.

    Google Scholar 

  10. Diaz Heijtz R, Wang S, Anuar F, et al. Normal gut microbiota modulates brain development and behavior. Proc Natl Acad Sci U S A. 2011;108:3047–52.

    Article  PubMed  Google Scholar 

  11. Morais LH, Schreiber HLT, Mazmanian SK. The gut microbiota-brain axis in behaviour and brain disorders. Nat Rev Microbiol. 2021;19:241–55.

    Article  CAS  PubMed  Google Scholar 

  12. Publishing HH. The gut-brain connection. Harvard Health; 2019. https://www.health.harvard.edu/diseases-and-conditions/the-gut-brain- connection.

  13. Hooks KB, O’Malley MA. Dysbiosis and its discontents. mBio. 2017;8:10.

    Article  Google Scholar 

  14. Li Z, Zhu H, Zhang L, et al. The intestinal microbiome and Alzheimer’s disease: a review. Animal Model Exp Med. 2018;1:180–8.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Walker KA, Ficek BN, Westbrook R. Understanding the role of systemic inflammation in Alzheimer’s disease. ACS Chem Neurosci. 2019;10:3340–2.

    Article  CAS  PubMed  Google Scholar 

  16. Health NCfCaI. Probiotics: what you need to know. 2019. https://www.nccih.nih.gov/health/probiotics-what-you-need-to-know.

  17. Tamtaji OR, Milajerdi A, Reiner Ž, et al. A systematic review and meta-analysis: the effects of probiotic supplementation on metabolic profile in patients with neurological disorders. Complement Ther Med. 2020;53: 102507.

    Article  PubMed  Google Scholar 

  18. Amirani E, Milajerdi A, Mirzaei H, et al. The effects of probiotic supplementation on mental health, biomarkers of inflammation and oxidative stress in patients with psychiatric disorders: a systematic review and meta-analysis of randomized controlled trials. Complement Ther Med. 2020;49: 102361.

    Article  PubMed  Google Scholar 

  19. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviewsDeclaracion PRISMA 2020: una guia actualizada para la publicacion de revisiones sistematicas. Rev Panam Salud Publica. 2022;46: e112.

    PubMed  PubMed Central  Google Scholar 

  20. Hooijmans CR, Rovers MM, de Vries RB, et al. SYRCLE’s risk of bias tool for animal studies. BMC Med Res Methodol. 2014;14:43.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Kim H, Kim S, Park SJ, et al. Administration of Bifidobacterium bifidum BGN4 and Bifidobacterium longum BORI improves cognitive and memory function in the mouse model of Alzheimer’s disease. Front Aging Neurosci. 2021;13: 709091.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Zhu G, Zhao J, Zhang H, et al. Administration of Bifidobacterium breve improves the brain function of Aβ1-42-Treated Mice via the Modulation of the Gut Microbiome. Nutrients. 2021;13: 1602.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Lee D-Y, Shin Y-J, Kim J-K, et al. Alleviation of cognitive impairment by gut microbiota lipopolysaccharide production-suppressing Lactobacillus plantarum and Bifidobacterium longum in mice. Food Funct. 2021;12:10750–63.

    Article  CAS  PubMed  Google Scholar 

  24. Nimgampalle M, Kuna Y. Anti-Alzheimer properties of probiotic, Lactobacillus plantarum MTCC 1325 in Alzheimer’s disease induced albino rats. J Clin Diagn Res. 2017;11:KC01–5.

    PubMed  PubMed Central  Google Scholar 

  25. Mehrabadi S, Sadr SS. Assessment of probiotics mixture on memory function, inflammation markers, and oxidative stress in an Alzheimer’s disease model of rats. Iran Biomed J. 2020;24:220–8.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Liu G, Tan FHP, Lau SYA, et al. Lactic acid bacteria feeding reversed the malformed eye structures and ameliorated gut microbiota profiles of Drosophila melanogaster Alzheimer’s disease model. J Appl Microbiol. 2022;132:3155–67.

    Article  CAS  PubMed  Google Scholar 

  27. Azm SAN, Djazayeri A, Safa M, et al. Lactobacilli and bifidobacteria ameliorate memory and learning deficits and oxidative stress in β-amyloid (1–42) injected rats. Appl Physiol Nutr Metab. 2018;43:718–26.

    Article  Google Scholar 

  28. Song X, Zhao Z, Zhao Y, et al. Lactobacillus plantarum DP189 prevents cognitive dysfunction in D-galactose/AlCl3 induced mouse model of Alzheimer’s disease via modulating gut microbiota and PI3K/Akt/GSK-3β signaling pathway. Nutr Neurosci. 2022;25:2588–600.

    Article  CAS  PubMed  Google Scholar 

  29. Huang H-J, Chen J-L, Liao J-F, et al. Lactobacillus plantarum PS128 prevents cognitive dysfunction in Alzheimer’s disease mice by modulating propionic acid levels, glycogen synthase kinase 3 beta activity, and gliosis. BMC Complementary Medicine and Therapies. 2021;21:259.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Tan FHP, Liu G, Lau SA, et al. 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.

    Article  CAS  PubMed  Google Scholar 

  31. Wang F, Xu T, Zhang Y, et al. Long-term combined administration of Bifidobacterium bifidum TMC3115 and Lactobacillus plantarum 45 alleviates spatial memory impairment and gut dysbiosis in APP/PS1 mice. FEMS Microbiol Lett. 2020;367:fnaa048.

    Article  CAS  PubMed  Google Scholar 

  32. Wang Y, Wang D, Lv H, et al. Modulation of the gut microbiota and glycometabolism by a probiotic to alleviate amyloid accumulation and cognitive impairments in AD rats. Mol Nutr Food Res. 2022;66: e2200265.

    Article  PubMed  Google Scholar 

  33. Abdelhamid M, Zhou C, Jung C-G, et al. Probiotic Bifidobacterium breve MCC1274 mitigates Alzheimer’s Disease-Related Pathologies in Wild-Type Mice. Nutrients. 2022;14: 2543.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Abdelhamid M, Zhou C, Ohno K, et al. Probiotic Bifidobacterium breve prevents memory impairment through the reduction of both amyloid-β production and microglia activation in app knock-in mouse 1. J Alzheimers Dis. 2022;85:1555–71.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Rezaei Asl Z, Sepehri G, Salami M. Probiotic treatment improves the impaired spatial cognitive performance and restores synaptic plasticity in an animal model of Alzheimer’s disease. Behav Brain Res. 2019;376: 112183.

    Article  PubMed  Google Scholar 

  36. Mallikarjuna N, Praveen K, Yellamma K. Role of Lactobacillus plantarum MTCC1325 in membrane-bound transport ATPases system in Alzheimer’s disease-induced rat brain. J Bioimpacts. 6;4:203–9. http://bi.tbzmed.ac.ir/FullHtml/BI_13567_20160819103635.

  37. Zahra R, Mahmoud S, Gholamreza S. The effects of probiotic Lactobacillus and Bifidobacterium strains on memory and learning behavior, long-term potentiation (LTP), and some biochemical parameters in β-amyloid-induced rat’s model of Alzheimer’s disease. Preventive Nutrition and Food Science. 2019;24:265–73.

    Article  Google Scholar 

  38. Webberley TS, Masetti G, Bevan RJ, et al. The impact of probiotic supplementation on cognitive, pathological and metabolic markers in a transgenic mouse model of Alzheimer’s disease. Front Neurosci. 2022;16: 843105.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Kobayashi Y, Sugahara H, Shimada K, et al. Therapeutic potential of Bifidobacterium breve strain A1 for preventing cognitive impairment in Alzheimer’s disease. Sci Rep. 2017;7:13510.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Wu Q, Li Q, Zhang X, et al. Treatment with Bifidobacteria can suppress Aβ accumulation and neuroinflammation in APP/PS1 mice. PeerJ. 2020;8: e10262.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Review Manager (RevMan). version 5.4 ed: The Cochrane Collaboration.

  42. Higgins JPT TJ, Chandler J, Cumpston M, Li T, Page MJ, Welch VA, editors. Cochrane handbook for systematic reviews of interventions version 6.4 (updated August 2023). 2023. https://www.training.cochrane.org/handbook.

  43. Liu S, Gao J, Zhu M, et al. Gut microbiota and dysbiosis in Alzheimer’s disease: implications for pathogenesis and treatment. Mol Neurobiol. 2020;57:5026–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Brandscheid C, Schuck F, Reinhardt S, et al. Altered gut microbiome composition and tryptic activity of the 5xFAD Alzheimer’s mouse model. J Alzheimers Dis. 2017;56:775–88.

    Article  CAS  PubMed  Google Scholar 

  45. Ho L, Ono K, Tsuji M, et al. Protective roles of intestinal microbiota derived short chain fatty acids in Alzheimer’s disease-type beta-amyloid neuropathological mechanisms. Expert Rev Neurother. 2018;18:83–90.

    Article  CAS  PubMed  Google Scholar 

  46. Kumar H, Bhardwaj K, Valko M, et al. Antioxidative potential of Lactobacillus sp. in ameliorating D-galactose-induced aging. Appl Microbiol Biotechnol. 2022;106:4831–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Rothschild D, Weissbrod O, Barkan E, et al. Environment dominates over host genetics in shaping human gut microbiota. Nature. 2018;555:210–5.

    Article  CAS  PubMed  Google Scholar 

  48. Seo D-o, Holtzman DM. Current understanding of the Alzheimer’s disease-associated microbiome and therapeutic strategies. Experimental and Molecular Medicine. 2024;56:86–94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Seo DO, O'Donnell D, Jain N, et al. ApoE isoform- and microbiota-dependent progression of neurodegeneration in a mouse model of tauopathy. Science 2023;379:eadd1236.

  50. Loh JS, Mak WQ, Tan LKS, et al. Microbiota–gut–brain axis and its therapeutic applications in neurodegenerative diseases. Signal Transduct Target Ther. 2024;9:37.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Calsolaro V, Edison P. Neuroinflammation in Alzheimer’s disease: current evidence and future directions. Alzheimers Dement. 2016;12:719–32.

    Article  PubMed  Google Scholar 

  52. Varnum MM, Ikezu T. The classification of microglial activation phenotypes on neurodegeneration and regeneration in Alzheimer’s disease brain. Arch Immunol Ther Exp (Warsz). 2012;60:251–66.

    Article  CAS  PubMed  Google Scholar 

  53. Bathina S, Das UN. Brain-derived neurotrophic factor and its clinical implications. Arch Med Sci. 2015;11:1164–78.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Nair AB, Jacob S. A simple practice guide for dose conversion between animals and human. J Basic Clin Pharm. 2016;7:27–31.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Dunlap BS, Yu H, Elitsur Y. The probiotic content of commercial yogurts in West Virginia. Clin Pediatr. 2009;48:522–7.

    Article  Google Scholar 

  56. López-Moreno A, Suárez A, Avanzi C, et al. Probiotic strains and intervention total doses for modulating obesity-related microbiota dysbiosis: a systematic review and meta-analysis. Nutrients. 2020;12:1921.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Health NIo. Probiotics: fact sheet for health professionals, 2023. https://ods.od.nih.gov/factsheets/Probiotics-HealthProfessional/.

  58. Dudek-Wicher R, Junka A, Paleczny J, et al. Clinical trials of probiotic strains in selected disease entities. Int J Microbiol. 2020;2020:8854119.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We would like to thank Assoc. Prof. Krit Pongpirul for supervising the methodology of this study. Moreover, we would like to thank Chatuthanai Savigamin and Piyawat Kantogowit for their valuable advice and feedback.

Funding

None.

Author information

Authors and Affiliations

  1. Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand

    Yada Siripaopradit, Oranut Chatsirisakul & Tassanee Ariyapaisalkul

  2. Center of Excellence in Nanomedicine, Department of Anatomy, Faculty of Medicine, Chulalongkorn University, 1873 Rama 4 Road, Pathumwan, Bangkok, 10330, Thailand

    Amornpun Sereemaspun

Authors
  1. Yada Siripaopradit
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Oranut Chatsirisakul
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Tassanee Ariyapaisalkul
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Amornpun Sereemaspun
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

YS: project administration, conceptualization, data curation, formal analysis, investigation, methodology, visualization, writing original draft (results, discussion, conclusion), writing-review and editing. OC: data curation, formal analysis, investigation, methodology, visualization, writing original draft (introduction, results), writing-review and editing. TA: data curation, formal analysis, investigation, methodology, visualization, writing original draft (methodology, results), writing-review and editing. AS: funding acquisition, supervision, validation. All authors have approved the final version of this manuscript and contributed to the process of making arguments within the manuscript.

Corresponding author

Correspondence to Amornpun Sereemaspun.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Glossary

IL-1𝛽

is used as a biological response modifier to boost the immune system in cancer therapy. Interleukin-1-beta is a type of cytokine. Also called IL-1-beta and IL-1B

IL-6

is a soluble mediator with a pleiotropic effect on inflammation, immune response, and hematopoiesis

TNF-𝛼

Tumour Necrosis Factor alpha is an inflammatory cytokine produced by macrophages / monocytes during acute inflammation and is responsible for a diverse range of signalling events within cells, leading to necrosis or apoptosis

GFAP

Glial fibrillary acidic protein is an intermediate filament (IF) III protein uniquely found in astrocytes in the CNS, non-myelinating Schwann cells in the peripheral nervous system (PNS), and enteric glial cells

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Siripaopradit, Y., Chatsirisakul, O., Ariyapaisalkul, T. et al. Exploring the gut-brain axis in alzheimer’s disease treatment via probiotics: evidence from animal studies-a systematic review and meta-analysis. BMC Neurol 24, 481 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12883-024-03978-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12883-024-03978-5

Keywords

BMC Neurology

ISSN: 1471-2377

Contact us