Causal Associations Between Gut Microbiota,Gut Microbiota-Derived Metabolites,and Alzheimer’s Disease: A Multivariable Mendelian Randomization Study

Abstract

Background:

Multiple studies have demonstrated that the gut microbiome is closely related to the onset of Alzheimer’s disease, but the causal relationship between the gut microbiome and AD, as well as potential mediating factors, have not been fully explored.

Objective:

Our aim is to validate the causal relationship between the gut microbiome and the onset of AD and determine the key mechanism by which the gut microbiome mediates AD through blood metabolites using Mendelian randomization (MR) analysis methods.

Methods:

We first conducted bidirectional and mediating MR analyses using gut microbiota, blood amino acid metabolites, and AD-related single nucleotide polymorphisms as research data. In the analysis process, the inverse variance-weighted average method was mainly used as the primary method, with other methods serving as supplementary evidence.

Results:

Ultimately, we found that six types of gut bacteria and two blood amino acid metabolites have a causal effect on AD. Subsequent mediation analysis proved that decreased glutamine concentration mediates the negative causal effect of Holdemanella bacteria on AD (mediation ratio of 14.5%), and increased serum alanine concentration mediates the positive causal effect of Parabacteroide bacteria on AD (mediation ratio of 9.4%).

Conclusions:

Our study demonstrates the causality of Holdemanella and Parabacteroides bacteria in the onset of AD and suggests that the reduced glutamine and increased alanine serums concentration may be key nodes in mediating this effect.

Keywords

Alzheimer’s disease gut microbiome Mendelian randomization metabolites

INTRODUCTION

Alzheimer’s disease (AD) is a neurodegenerative disorder. It involves the gradual loss of neurons in both the central and peripheral nervous systems. This leads to irreversible motor and cognitive impairments over time [1, 2]. With increasing life expectancy, the prevalence of AD is on the rise globally, becoming a major source of morbidity and mortality [2, 3]. Due to its complex pathogenesis and the significant challenges in drug development, it is essential to identify biomarkers that can recognize individuals at high risk for AD and pinpoint the earliest stages of pathological onset. Clarifying the correlations and causal relationships between these biomarkers and the disease could aid in promoting early intervention and treatment for AD [4, 5].

The human gut microbiome, a symbiotic organ of microorganisms residing in the intestines, plays a crucial role in key metabolic and immune processes, including host immunity, food digestion, intestinal endocrine function, and intestinal permeability, thereby regulating the onset and progression of various diseases [6]. Previous studies on the microbiome have discovered that a variety of gut microbiota such as Bacteroidetes, Escherichia coli, Bacillus subtilis, Salmonella enterica, Enterococcus faecalis, Mycobacterium tuberculosis, and Staphylococcus aureus are enriched in the intestines and closely related to AD [7]. Meanwhile, the absence of Lactobacilli of the phylum Firmicutes in the intestines is also associated with AD [7 –10]. The systemic effects of the gut microbiome are partly mediated by its by-products (microbial metabolites), and previous research has found that short-chain fatty acids, branched-chain amino acids, trimethylamine N-oxide, and tryptophan derivatives are associated with AD [7 , 12]. However, these studies only analyzed the correlation between specific gut microbiota, metabolites, and AD. The causal relationship between gut microbiota, blood metabolites, and AD, as well as how the gut microbiota mediates AD through metabolites, remains unclear.

Randomized controlled trials (RCTs) are the gold standard for studying causal relationships, but traditional RCTs are costly and difficult, and prone to limitations and false positives due to biases such as confounding. Mendelian randomization (MR) is an analytical method where genetic variations associated with a proposed risk factor are used as proxies to make causal inferences about the impact of that exposure on an outcome of interest [13]. MR mimics the randomization process that supports causal reasoning in RCTs. Several articles have already studied the causal relationships between the microbiome and other diseases, including mental disorders and autoimmune diseases using MR methods [14 –16]. Yet, few have yet to explore such causal relationships in AD.

In this study, we use bidirectional and mediating MR research to assess the causal relationship between the gut microbiome and AD, as well as identifying the potential role of amino acid metabolites as mediators. Our study provides a theoretical basis for subsequent studies on the pathogenesis of AD, as well as early screening and prevention of the disease.

MATERIALS AND METHODS

Study design

The research design is illustrated in Fig. 1. We initially employed two-sample Mendelian randomization (2SMR) to investigate the causal relationships between the classification of the gut microbiome, the abundance of amino acids in blood metabolites, and AD (Fig. 1A,B). After identifying the gut microbiota and blood metabolite groups closely associated with AD onset, we used mediating MR analysis to construct a chain of relationships between microbiota, metabolites, and AD, in order to interpret the mechanisms by which gut microbiota regulate AD onset through metabolites (Fig. 1C).

Fig. 1

Overview of the whole design. A,B) Mendelian randomization the casual relation of gut microbiota and blood amino acid metabolic to AD. C) Two-step Mendelian randomization analysis of the mediate effect of blood amino acid metabolic in the casual relationship between gut microbiota and AD.

Data sources and study participants

The blood metabolite exposures and AD phenotypes used in the study are based on previous genome-wide association study (GWAS), detailed in Supplementary Table 1.

We extracted summary statistics of gut microbiota, and blood amino acids metabolic data and AD, from their respective consortiums. We obtained both datasets from the MRC Integrative Epidemiology Unit (IEU) at University of Bristol (https://gwas.mrcieu.ac.uk/). These summary statistics were from publicly available abstract-level genome-wide association study (GWAS) of gut microbiota (N = 14,306), blood fatty acid metabolites (N = 7,804) and a meta-analysis AD (N = 54,162) [17 –19].

Selection of genetic instrumental variables

In the MR analysis of this study, single nucleotide polymorphisms (SNPs) associated with gut microbiota, blood amino acid metabolites, and AD were selected as instrumental variables (IVs). The criteria for selecting IVs are as follows: SNPs related to phenotypes at the genome-wide significance threshold of p < 5×10^-6 for preliminary screening, excluding palindromic A/T or G/C alleles. For SNPs within a single bacterial taxonomic unit, independence must be ensured, with a linkage disequilibrium (LD) threshold set at r² ^< 0.01 and a clustering window of 5000 kb. To assess the strength of SNP selection, F-statistics were calculated, where F-statistics greater than 10 indicate a strong association between the SNP and exposure, while SNPs with F-statistic less than 10 were considered weak instrumental variables and excluded (Supplementary Tables 2–4).

Statistical analysis

Five methods were used to estimate the causal effects of the gut microbiome and blood metabolites on AD and the causal relationship between the gut microbiome and blood metabolites: Inverse Variance-Weighted (IVW) [20], MR-Egger [21], weighted median [22], simple mode, and weighted mode methods [23]. Assuming all SNPs are valid instruments, the IVW method was used as the primary analysis standard. Fixed-effect meta-analyses were used to combine estimates of each outcome from different sources. Heterogeneity between SNP estimates was assessed using Cochran’s Q value [24]. Two types of sensitivity analyses were conducted to detect potential horizontal pleiotropy and check for consistency in associations, including MR-Egger, and Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) analysis methods to detect potential outliers [21, 25]. The MR-Egger regression provides MR estimates and adjusts for horizontal pleiotropy detected by its intercept test. The MR-PRESSO method can detect SNP outliers with pleiotropic effects and provides estimates identical to IVW after removing the outliers.

To study the mediating role of blood metabolites in the causal effect of gut microbiota on AD, a two-step MR analysis was conducted. The proportion of the indirect effect mediated by amino acid blood metabolites to the total effect [β1×β2 / β3] was estimated, where β1 represents the impact of gut microbiota on blood amino acids, β2 represents the impact of blood amino acids on AD, and β3 represents the impact of gut microbiota on AD. Effect estimates were made using two-sample MR analysis.

All analyses were conducted on the R Studio platform (version 4.2.1). The “TwoSampleMR,” “MRPRESSO,” “ggplot2,” and “circlize” packages were used for statistical analysis and data visualization.

RESULTS

Instrument variables included in analysis

The detailed characteristics of SNPs associated with microbial taxa, blood amino acid metabolics, and AD can be found in their respective Supplementary Tables 2–4. The F-statistics for all SNPs analyzed were greater than 10.

Correlation between gut microbiota and AD

Through MR analysis, we discovered that the bacteria Holdemanella [odds ratio (OR)=1.1008; 95% confidence interval (CI)=1.022–1.186; p = 0.0112] and Prevotella (OR = 1.08; 95% CI = 1.017–1.147; p = 0.012) play a promoting role in the onset of heart failure. Conversely, the abundance of Parabacteroides (OR = 0.8629; 95% CI = 0.749–0.994; p = 0.0413), Lachnospiraceae (OR = 0.797; 95% CI = 0.687–0.926; p = 0.003), Bacteroides (OR = 0.863; 95% CI = 0.746–0.999; p = 0.049), Alloprevotella (OR = 0.904; 95% CI = 0.830–0.986; p = 0.022), Sutterella (OR = 0.896; 95% CI = 0.809–0.992; p = 0.035), and Ruminococcus (OR = 0.905; 95% CI = 0.827–0.990; p = 0.029) can suppress the development of AD. To assess the impact of horizontal pleiotropy on MR analysis, we conducted sensitivity and pleiotropy analyses to test the robustness of the aforementioned associations. After analyzing using the statistical methods MR-Egger and Q tests, all corresponding p values in MR analysis were found to be above 0.05, indicating no pleiotropy or heterogeneity in MR analysis results.

Causal relationship between amino acid metabolites and AD onset

We conducted MR analysis on the concentration of amino acid metabolites in blood serum and the onset of AD disease. We found that alanine (OR = 0.805; 95% CI = 0.675–0.960; p = 0.016) and glutamine (OR = 0.825; 95% CI = 0.700–0.973; p = 0.023) could reduce the risk of AD onset. Here, we primarily used the IVW method as the main evaluation standard, with other methods including MR-Egger, weight mode, simple mode, and weighted median methods serving as auxiliary analysis tools. Polymorphism and heterogeneity of the analysis results were assessed using the MR-Egger method. As shown in Fig. 2, all test p values were greater than 0.05, indicating no risk of heterogeneity or polymorphism in the analysis results.

Fig. 2

Mendelian randomization analysis on the causal effect of the gut microbiota on AD. OR, odds ratio; CI, confidence interval.

Fig. 3

Mendelian randomization analysis on the causal effect of the amino acid on AD. OR, odds ratio; CI, confidence interval.

Fig. 4

The serum alanine and glutamine concentration mediated the casual effect of Parabacteroides andholdmanella on AD. The β value among microbial, amino acid and AD were obtained based on method.

Constructing the pathway of amino acid metabolites mediating gut microbiota’s regulation of AD onset risk

We conducted MR analysis on eight types of gut microbiota and two amino acid metabolites, constructing a pathway in which amino acid metabolites mediate the regulation of gut microbiota. Among them, Holdemanella causally decreased glutamine levels in serum (OR = 0.954; 95% CI = 0.915–0.995; p = 0.0293), which was associated with an increased risk of AD, with a mediated proportion of 14.5%. Parabacteroides causally increased serum alanine concentration (OR = 1.103; 95% CI = 1.015–1.198; p = 0.0215), and was associated with a decreased risk of AD with a mediated proportion of 9.4%.

DISCUSSION

In this study, we identified correlations between eight types of gut bacteria, two peripheral blood amino acid concentrations, and the onset of AD. Subsequent mediating MR analysis constructed two gut microbiota-blood metabolite-AD regulatory pathways: (1) the abundance of Holdemanella in the gut increases the risk of AD by reducing the level of glutamine in the peripheral blood, while the increased abundance of Parabacteroides in the gut can reduce the risk of AD by increasing the concentration of alanine in the blood. These preclinical findings may provide new insights into the gut microbiota-blood metabolite-AD interactions and their role in the pathogenesis of AD. The results were validated by the sensitivity and robustness of the MR measurement methods.

Research has linked variations in the composition and abundance of the gut microbiome to a range of neurodegenerative disorders. Within the human gut microbiome, Parabacteroides spp. are fundamental constituents, typically representing about 1.27% of the total gut flora. Recent studies have highlighted a significant correlation between Parabacteroides and various aspects of human health, including conditions such as metabolic syndrome, inflammatory bowel disease, and obesity [26]. Notably, Parabacteroides are characterized by their ability to metabolize carbohydrates and produce short-chain fatty acids [27]. Parabacteroides species, notably Parabacteroides distasonis and Pa. goldsteinii, benefit host health by modulating the immune system, reducing inflammation, affecting metabolism, and producing health-promoting metabolites like acetate, propionate, and butyrate. Parabacteroides distasonis could reduce proinflammation factors (TNF-α, IL-6, or IL-17) release and control innate inflammatory responses [28]. Oral admission of Pa. goldsteinii can reduce the expression levels of endotoxin and inflammatory factors in blood, protect intestinal permeability and inhibit the occurrence of obesity in mice [29]. Previous studies have shown that the abundance and proportion of Bifidobacterium in AD patients are significantly lower than in healthy individuals, and the same is true for the abundance of Parabacteroides [10, 30]. These observational results suggest a correlation between the amount of Parabacteroides present in the gut and the onset of AD. These results suggest that oral administration of Parabacteroides probiotics or enhancing the proportion of Parabacteroides in the gut microbiota through diet adjustment could effectively inhibit the onset of AD.

Our MR analysis found that a high abundance of Holdemanella in the gut can enhance the risk of developing AD. Although current literature has not directly demonstrated a link between Holdemanella bacteria and AD, the abundance of the Holdemania genus in the gut microbiota is significantly higher in similar neurological disorders (such as Parkinson’s disease, depression, etc.) compared to the control group [31, 32]. In addition, the abundance of the Holdemania genus is associated with clinical indicators of impaired lipid metabolism [33]. Among physically active older women, there is a negative correlation between the abundance of the Holdemania genus and skeletal muscle mass [34]. Furthermore, Holdemania is positively correlated with gout [35]. These results all suggest that the Holdemania genus may play a negative role in overall health and can be seen as a reflection of a poorer lifestyle. Our mendelian randomization analysis demonstrates that an increase in Holdemanella abundance has a suppressive effect on the onset of AD, further supporting the hypothesis that Holdemanella bacteria might be an instrumental risk factor in the development of AD. These findings indicate that through targeted dietary adjustments and the introduction of specific probiotics to reduce the abundance of detrimental bacteria like Holdemanella, along with optimizing the balance of Parabacteroides and Holdemanella in the gut microbiota, we can effectively suppress the progression and potentially delay the onset of AD.

Gut microbiota generally regulates various regulatory body systems by affecting blood metabolites, including the immune system, thereby influencing the development of various diseases. In AD, the concentration of amino acid metabolites plays a significant role in neural activity and immune environment regulation. Our MR analysis found that increased serum levels of alanine and glutamine significantly suppress the risk of AD onset. Existing research has not explored the relationship between alanine and AD onset. however, alanine plays a significant role in regulating human inflammatory responses and neural functions. It inhibits inflammation-induced apoptosis by altering the energy metabolism pattern of β-cells [36]. Moreover, alanine reduces intestinal inflammation in mice by suppressing the expression of IL-12 and IL-23 within macrophages, further emphasizing its role in modulating immune system responses [37]. In the nervous system, alanine acts as a potent agonist for the NMDA glycine binding site, which is crucial for maintaining normal neurotransmission and function [38, 39]. Its involvement in the functional changes of NMDA receptors is associated with the pathogenesis of various neurological disorders, including the hyperfunction of NMDA receptors in depression and neurodegenerative diseases, and the hypofunction of NMDA receptors in schizophrenia [39, 40]. In studies of pediatric autoimmune neurological diseases, changes in the gut microbiome affect the serum alanine levels through the gut-brain axis, revealing the complex interactions between gut health and neural system health, as well as alanine’s regulatory role [41]. This regulation involves not only the suppression of inflammatory responses but also the protection and modulation of neural functions, highlighting alanine’s potential applications in preventing and treating neuro-related diseases.

Meanwhile, glutamine is the most abundant non-essential amino acid in serum, performing numerous metabolic functions in the cell [42]. The glutamate/glutamine cycle in astrocytes plays an important role in the nervous system. The decrease in glutamine/glutamate levels in the brains of individuals with AD is directly associated with neurodegenerative conditions [43 –45]. It has been observed that glutamine supplements exhibit anti-inflammatory effects within the brain, potentially offering benefits to AD patients. Furthermore, these supplements can enhance the DNA damage response, which may positively influence the mitigation of symptoms associated with delayed-onset diseases such as AD [46, 47]. The lack of glutamine leads to a reduction in autophagy, a crucial process for maintaining the health of cells and organisms. By boosting autophagy, glutamine supplementation could combat the observed reduction of this vital mechanism in AD [48]. Encouraging outcomes from glutamine supplementation in familial AD mouse models indicate that nutritional support with glutamine might serve as a viable therapeutic approach, aiming to disrupt the neurodegenerative features characteristic of AD [47]. Besides, other MR studies found that increased serum glutamine concentration can effectively reduce the risk of AD onset. Complementing these findings, our study provides clinical validation, indicating a direct causal relationship between decreased levels of glutamine in the peripheral blood and the onset of AD. These findings indicate that lower serum levels of glutamine and alanine may be predictive of an increased risk for AD. Consequently, elevating the levels of glutamine and alanine in the serum through dietary modifications or supplementation could serve as an effective strategy for the prevention of AD onset.

Previous studies have only focused on the unidirectional causality of gut microbiota and blood metabolite levels on AD disease [7 , 50]. Our use of mediating MR analysis successfully established two circular pathways of gut microbiota, blood metabolites, and AD onset, with mediating efficiencies of 14.5% and 9.4%, respectively. This provides new insights for subsequent research into the mechanisms by which gut microbiota promote/inhibit the risk of AD disease.

Research limitations

There are, however, limitations to our study. Firstly, MR provides an important alternative method for validating effects, but it should be noted that MR effect estimates reflect lifetime genetic exposures and may not accurately reflect the magnitude of benefit from shorter-term microbiome changes. Nevertheless, the causal direction of the expected effect can inform potential efficacy, which can be further formally investigated in animal experiments and clinical trials. Secondly, the limited sample size of the gut microbiome GWAS may not be sufficient to adequately detect potential causal relationships. However, this is the largest gut microbiome GWAS to date, which has species-level data and provides a more precise classification of gut microbial taxa we can get. Finally, because our analyses were conducted primarily in European populations, we should be cautious in generalizing our findings to other populations, given the potential race-specific associations between the host genome and gut microbiome.

Conclusion

Our MR study results established potential causal relationships between gut microbiota, amino acid metabolites, and AD. Specifically, decreased serum glutamine concentration mediates the casual effect of Holdemanella on AD risk, while increased serum alanine concentration mediates the reduction of AD onset risk by Parabacteroides. These findings provide genetic evidence for the connections between gut microbiota, amino acid metabolites, and AD, and may inform future mechanistic and clinical research in this field. Thus, by consuming probiotics and regulating diet to increase the proportion of Parabacteroides in the gut flora, decrease the proportion of Holdemanella, and increase the concentration levels of glycine and glutamine in serum, the onset and progression of AD can be effectively inhibited.

AUTHOR CONTRIBUTIONS

Min Ning (Conceptualization; Formal analysis; Methodology; Project administration; Writing – original draft; Writing – review & editing); Lina An (Conceptualization; Investigation; Supervision; Visualization; Writing – original draft; Writing – review & editing); Liang Dong (Conceptualization; Investigation; Supervision; Visualization; Writing – original draft; Writing – review & editing); Ranran Zhu (Resources; Validation); Jingjing Hao (Data curation); Xueyuan Liu (Conceptualization; Project administration; Supervision); Yuanyuan Zhang (Conceptualization; Funding acquisition; Project administration; Supervision).

Footnotes

ACKNOWLEDGMENTS

We thank all individuals providing and conducting data collection for this work.

FUNDING

This work was supported by the Natural Science Foundation of Shaanxi Province (Grant no. 2022JM-546).

CONFLICT OF INTEREST

The authors have no conflict of interest to report.

DATA AVAILABILITY

The authors applied a broad consent to allow research participants to query and download a wide range of their data because the data for this study was obtained via a database at .

The supplementary material is available in the electronic version of this article: .

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