Abstract

Background:

Gut microbiome disturbances have been proposed as contributors to amyotrophic lateral sclerosis (ALS), a multisystem neurodegenerative disorder characterised by motor neuron loss, extra-motor symptoms, and rapid progression. Mechanistic links between dysbiosis, epithelial and blood–brain barrier dysfunction, metabolic imbalance, and immune activation have been suggested, but causality remains unresolved. We conducted a systematic review to evaluate the evidence supporting microbiome involvement in ALS pathogenesis.

Methods:

We searched PubMed, Medline, Embase, Scopus, Semantic Scholar, and Google Scholar (Nov 23, 2025) for human and ALS-relevant animal studies assessing bacterial microbiota, gut or blood–brain barrier integrity, microbial metabolites, or immune pathways. No language or date restrictions were applied. Studies were screened according to predefined criteria, and quality was assessed using QUADAS-2. Owing to the heterogeneity of study designs and sequencing approaches, findings were synthesised narratively.

Findings:

61 of 2,397 studies met inclusion criteria. Across human cohorts, ALS was consistently associated with reduced microbial diversity, shifts in key taxa, and disruption of microbial pathways regulating short-chain fatty acids, nicotinamide metabolism, and inflammatory signalling. Several mechanistic animal studies demonstrated that microbiota manipulation, through antibiotics, faecal microbiota transfer, or supplementation with protective taxa, modulated motor function, microglial activation, gut permeability, and survival, indicating that dysbiosis can influence disease trajectories. Conversely, longitudinal human data showed that dysbiosis often emerged alongside worsening physical function, gastrointestinal dysmotility, weight loss, and changes in dietary intake, suggesting secondary effects of disease progression. Integrative multi-omics studies linked microbial alterations with systemic cytokine profiles, metabolic stress pathways, and CNS immune phenotypes, reinforcing a bidirectional gut–brain axis. However, the predominance of cross-sectional designs and small sample sizes substantially limits causal inference.

Interpretation:

Current evidence supports a model in which gut dysbiosis interacts with ALS via barrier failure, metabolic disruption, and immune dysregulation, but does not establish dysbiosis as a primary cause of disease. Preclinical findings highlight microbiome-derived mechanisms with disease-modifying potential, yet human data largely indicate association rather than initiation. Clarifying temporal relationships will require longitudinal, multi-modal studies, integration with pre-symptomatic cohorts, and controlled interventional trials. Microbiome-targeted therapies remain a promising but unproven avenue for ALS.

1 Introduction

Amyotrophic lateral sclerosis (ALS), also known as motor neuron disease (MND) is a neurodegenerative disease marked by progressive weakness resulting from the degeneration of both upper and lower motor neurons (Brown and Al-Chalabi, 2017; Hardiman et al., 2017; van Es et al., 2017). Alongside motor symptoms, ALS also includes a spectrum of non-motor manifestations, with around 15–20% of individuals developing frontotemporal dementia (FTD) and up to 50% exhibiting milder cognitive or behavioural changes, in addition to autonomic and neuropsychiatric symptoms (Crockford et al., 2018). Typically, ALS progresses to death within 2–3 years most commonly from neuromuscular respiratory failure (Xu et al., 2020). Genetic factors contribute substantially to disease risk. Around 10% of patients report a family history of ALS or frontotemporal dementia, and clinically actionable variants can be identified in approximately 20% of all cases (Mehta et al., 2022). However, the majority of ALS is isolated, suggesting important roles for environmental, metabolic, and immunological influences. Clinical heterogeneity is considerable: most patients present with limb-onset disease, while a minority present with bulbar or respiratory onset, and rates of progression vary widely (Zhang et al., 2005; Kenna et al., 2013; Niccolai et al., 2021). This heterogeneity is paralleled by diverse molecular processes implicated in ALS pathobiology, including protein misfolding, RNA dysfunction, mitochondrial impairment, autophagy defects, neuroinflammation, and dysregulation of systemic metabolism (Kenna et al., 2013; Niccolai et al., 2021).

Despite advances in understanding disease mechanisms, therapeutic options remain limited. Riluzole and newer disease-modifying agents offer some since tofersen offers considerable benefit, and there is increasing interest in identifying upstream pathways that may influence ALS susceptibility, onset, or progression (Lacomblez et al., 1996; Fang et al., 2018). One emerging area is the potential contribution of the gastrointestinal microbiome, the complex community of bacteria, fungi, viruses, and metabolites that regulate immunity, metabolism, and host–environment interactions (Taylor et al., 2016; Martin et al., 2017).

The gut microbiota, comprising bacteria, fungi, viruses, protozoa, and parasites, engages in bidirectional communication with the central nervous system via neural, immune, metabolic, and endocrine pathways (Figure 1) (Rooks and Garrett, 2016; Jandhyala et al., 2015). Despite anatomical distance, gut and brain exert reciprocal effects throughout life (Laue et al., 2022). Microbial metabolites, including neuroactive molecules, may influence central processes, while dysbiosis can disrupt immune and metabolic homeostasis (Ahmed et al., 2022; Gomaa, 2020).

The brain-gut-microbiota axis. The bidirectional communication between gut microbiota and the central nervous system is maintained by either immune or metabolic signals via circulation, or by the enteric nervous system and autonomic nervous system. Microbiome dysbiosis can disrupt the physiological function of the brain-gut bi-directional axis (Created in https://BioRender.com).

Several clinical observations have prompted an investigation into a gut–ALS connection. Gastrointestinal symptoms are frequently reported in ALS, including constipation, rectal tenesmus, hard stools, and borborygmus (Parra-Cantu et al., 2021; Shojaie et al., 2024). Gastrointestinal motor dysfunction, such as delayed colonic transit, impaired gastric emptying, and anorectal sphincter abnormalities, has also been described and may precede formal diagnosis (Martin et al., 2022; McCombe et al., 2017; Oprisan and Popescu, 2023; Finsterer and Strobl, 2024; Rowin et al., 2017; Gotkine et al., 2020).

Current research has been focused on mechanistic roles of the gut–brain axis in various neurodegenerative conditions. In Parkinson’s disease, gut microbiome dysbiosis is thought to promote intestinal inflammation and increased gut permeability, enabling bacterial metabolites and endotoxins to trigger α-synuclein aggregation in the enteric nervous system, which may then propagate to the central nervous system (de Castro Fonseca et al., 2026). In Alzheimer’s disease, alterations in gut microbial composition can increase production of pro-inflammatory metabolites and lipopolysaccharides, contributing to systemic inflammation and enhancing amyloid-β deposition and microglial activation, thereby accelerating neurodegeneration (Seo and Holtzman, 2024).

Similar changes in the gut microbiota, including reduced diversity and shifts in specific taxa, have been described in multiple cohorts of ALS patients. Experimental studies in both animal models and patients further suggest that microbial metabolites can modulate immune responses, intestinal barrier function, and even central nervous system inflammation, providing plausible biological links between dysbiosis and neurodegeneration (Chen et al., 2025; Abou Izzeddine et al., 2025). However, whether these alterations represent causal contributors, downstream consequences, or simple correlates of disease remains unclear. Conversely, neurodegeneration and impaired nutrition may themselves reshape the gut environment, complicating the interpretation of observed microbiome changes. Given these uncertainties, a comprehensive synthesis of current evidence is needed.

This systematic review evaluates human and preclinical studies examining the gut microbiota, intestinal and blood–brain barrier function, microbial metabolism, and immune responses in ALS. We aimed to characterise the consistency of reported findings, assess mechanistic plausibility, and clarify the extent to which dysbiosis may act as a contributor, consequence, or correlate of ALS pathogenesis.

2 Methods2.1 Search strategy

A systematic literature search was conducted on 7 February 2026 across PubMed, MEDLINE, Embase, Scopus, Semantic Scholar, and Google Scholar to identify studies investigating ALS and its relationship with the gastrointestinal microbiome, gut barrier function, and microbiome-derived metabolites.

The PubMed search used the following query:

(“Amyotrophic Lateral Sclerosis”[Mesh] OR “Motor Neuron Disease”[Mesh] OR amyotrophic lateral sclerosis[tiab] OR ALS[tiab] OR motor neuron disease*[tiab] OR MND[tiab] OR Lou Gehrig*[tiab]) AND (“Gastrointestinal Microbiome”[Mesh] OR microbiota[tiab] OR microbiome[tiab] OR gut microbiome[tiab] OR gut microbiota[tiab] OR intestinal microbiota[tiab] OR dysbiosis[tiab] OR gut dysbiosis[tiab]) AND (barrier*[tiab] OR “intestinal barrier”[tiab] OR “gut–brain axis”[tiab] OR permeability[tiab] OR “gut permeability”[tiab] OR metabolite*[tiab] OR butyrate[tiab] OR propionate[tiab]).

Equivalent controlled vocabulary and keyword adaptations were applied for MEDLINE and Embase, while Semantic Scholar, Google Scholar, and Scopus were searched using relevant keyword combinations.

All retrieved records were screened and managed using Rayyan (Rayyan Systems Inc., Cambridge, MA, United States). No restrictions on publication date or language were applied during the initial search. Reference lists of all included articles were also manually screened to identify additional relevant studies. The search strategy was developed collaboratively by the authors to ensure broad coverage of the heterogeneous microbiome and ALS literature. The complete search strategies for all databases are provided in Supplementary Table 1B. A formal review protocol was not registered.

As this study involved secondary analysis of published literature, ethical approval and participant consent were not required.

2.2 Study selection

Study selection followed PRISMA guidelines. After removal of duplicate records, titles and abstracts were screened independently by two reviewers (T.R. and D.C.) using the Rayyan systematic review platform for blinded screening and tagging of inclusion and exclusion decisions.

Articles deemed potentially eligible proceeded to full-text assessment, which was also conducted independently by the same two reviewers. Any disagreements at the title/abstract or full-text screening stages were resolved through discussion and consensus, with a third reviewer (A.A.K.) adjudicating when necessary.

A total of 89 studies underwent full-text assessment, of which 45 studies met the eligibility criteria and were included in the final analysis. The screening and selection process is illustrated in the PRISMA flow diagram (Figure 2). The inclusion and exclusion criteria used for study selection are summarised in Table 1.

Screening and selection procedure using PRISMA guidelines (Page et al., 2021). For more information, visit www.prismastatement.org.

Inclusion criteriaExclusion criteriaHuman participants with ALS or MND (including presymptomatic genetic carriers)Studies not involving ALS/MND or where ALS data cannot be separatedALS-relevant animal models (e.g., SOD1-G93A, TDP-43, C9orf72)Non-ALS animal models and unrelated neurodegenerative conditions without ALS-specific analysisStudies examining the bacterial gut microbiome (e.g., 16S rRNA sequencing, metagenomics, qPCR)Studies focusing on fungal, viral, or other non-bacterial microbiota (mycobiome, virome)Studies evaluating gut dysbiosis, gut–brain axis interactions, intestinal barrier function, or microbiome-related metabolitesStudies without microbiome, barrier, immune, metabolic, or ALS-relevant outcomesObservational, interventional, or mechanistic studies in English with accessible full textReviews, commentaries, editorials, or case reports without primary microbiome data

Inclusion and exclusion criteria.

2.3 Data extraction and synthesis

Data extraction was performed independently by two reviewers (T.R. and D.C.) using a structured data extraction framework developed for this review. The following information was extracted from each included study:

Study design and setting.

Study population or animal model.

Sample size.

Microbiome analysis methods (e.g., 16S rRNA sequencing, metagenomics, metabolomics).

Key microbial taxa or metabolic pathways identified.

Outcomes related to intestinal barrier integrity, immune signalling, metabolic pathways, or neurodegeneration.

Major findings relevant to ALS pathophysiology.

Discrepancies in extracted data were resolved through reviewer discussion, with third-reviewer adjudication (A.A.K.) where necessary. Due to methodological heterogeneity across microbiome studies, a narrative synthesis approach was used. Findings were grouped into thematic categories, including microbial dysbiosis, intestinal barrier dysfunction, metabolic pathways, immune mechanisms, and genetics/multi-omics studies, and summarised.

2.4 Quality assessment

Methodological quality and risk of bias were assessed independently by two reviewers (T.R. and D.C.) using study-design-specific tools:

Newcastle–Ottawa Scale (NOS) for observational human studies.

RoB 2 for randomised controlled trials.

ROBINS-I for non-randomised interventional studies.

SYRCLE Risk of Bias tool for animal studies.

STROBE-MR guidelines for Mendelian randomisation studies.

Disagreements in quality assessment were resolved through discussion, with A.A.K. acting as a third reviewer where consensus could not be reached. Detailed quality metrics and individual study assessments are provided in Supplementary Tables 2A–E. All studies meeting the inclusion criteria were retained regardless of risk-of-bias; however, methodological limitations identified during quality assessment were considered when interpreting the findings.

3 Results

The database search identified 2,397 records, of which 1,493 duplicates were excluded. After screening 904 titles and abstracts, 89 articles underwent full-text review, and 45 studies met the inclusion criteria. The included literature comprised human observational studies, mechanistic rodent studies, and interventional experiments evaluating microbiome manipulation. Across studies, substantial heterogeneity was observed in cohort size, sequencing methodology (16S rRNA, metagenomics, qPCR), analytical pipelines, and clinical phenotyping.

3.1 Patterns of dysbiosis in ALS

Patterns of gut microbial dysbiosis have been reported in both human ALS cohorts and experimental models. Key findings from these studies are summarised in Table 2.

ThemeModelKey findingsReferencesMicrobial dysbiosis in patientsHumanALS patient cohorts showed reduced microbial α-diversity and altered gut microbiome composition, including changes in the Firmicutes/Bacteroidetes ratio. Several studies also reported reduced abundance of short-chain fatty acid–producing taxa, including butyrate-producing bacteria.Niccolai et al. (2021), Rowin et al. (2017), Fontdevila et al. (2024), Brenner et al. (2018), Zeng et al. (2020), Zhai et al. (2019), Di Gioia et al. (2020), Hertzberg et al. (2022), Nicholson et al. (2021), Fang et al. (2016), Quaranta et al. (2022), Gautam et al. (2025), and Feng et al. (2024)Animal microbial dysbiosisAnimal (Mouse)Increased α-diversity is noted in the ALS mouse model. Studies focus on variation of the ratio of Firmicutes/Bacteroidetes longitudinally throughout the disease course.Blacher et al. (2019), Beraldi et al. (2024), Figueroa-Romero et al. (2019), and Kurlawala et al. (2023)Induced dysbiosis in ALSAnimal (Mouse)Experimental depletion or manipulation of gut microbiota in ALS mouse models correlated with disease progression. Antibiotic treatment and microbiota reconstitution experiments modified neuroinflammatory responses and motor disease phenotype.Blacher et al. (2019), Burberry et al. (2020), Zhang et al. (2017), Zhang et al. (2021), and Cox et al. (2022)

Patterns of gut microbiome dysbiosis reported in amyotrophic lateral sclerosis (ALS).

ALS animal model studies have revealed that experimentally induced dysbiosis promotes disease progression (Blacher et al., 2019; Beraldi et al., 2024; Figueroa-Romero et al., 2019; Kurlawala et al., 2023; Burberry et al., 2020; Zhang et al., 2017; Zhang et al., 2021; Cox et al., 2022). Most human studies reported measurable alterations in the gut microbiota of people with ALS compared with healthy controls. Most findings included reduced α-diversity and significant shifts in relative abundance across multiple bacterial taxa. Several studies report alterations in microbial composition in ALS, including reductions in the Firmicutes-to-Bacteroidetes ratio (Niccolai et al., 2021; Rowin et al., 2017; Fang et al., 2016). Similar studies further revealed increased abundance of taxa such as Bacteroidetes, Odoribacter, Kineothrix, Sporobacter, Parabacteroides, and unclassified Porphyromonadaceae (Zeng et al., 2020). Contradictory results with unchanged or increased Firmicutes-to-Bacteroidetes ratio are also reported (Brenner et al., 2018; Zhai et al., 2019). One study compared ALS subtypes and found a higher proportion of Fusobacteria and Tenericutes in spinal ALS than in bulbar ALS (Fontdevila et al., 2024).

3.2 Microbial functional pathways and barrier dysfunction

Several experimental studies have investigated the role of barrier dysfunction in ALS, particularly focusing on the integrity of the intestinal barrier and the blood–brain barrier. Key findings from these studies are summarised in Table 3.

MechanismModelKey findingsReferencesIntestinal barrier dysfunction in ALSAnimal (Mouse)ALS mouse models showed increased intestinal permeability with disruption of tight junction proteins (e.g., ZO-1, E-cadherin) and structural abnormalities of the intestinal epithelium. These changes were accompanied by intestinal inflammation and evidence of endotoxin translocation.Zhang et al. (2017) and Wu et al. (2015)Blood–brain barrier (BBB) dysfunction in ALSAnimal (Mouse)Gut microbiota were reported to influence BBB integrity, with alterations in microbial composition associated with changes in BBB tight-junction protein expression. Experimental microbiota depletion disrupted the BBB tight-junction structure and increased barrier permeability.McCourt et al. (2026), Zhang et al. (2024), and Aragón-González et al. (2024)Reverse causality of Barrier dysfunction and ALSAnimal (Mouse)Gut microbiota alterations were associated with changes in host metabolic and immune pathways influencing ALS progression. Experimental manipulation of the microbiome, including antibiotic treatment and microbial supplementation, modified disease severity, neuroinflammation, and motor outcomes in ALS models.Gotkine et al. (2020), Zhang et al. (2017), and Zhang et al. (2024)

Evidence linking gut microbiota to barrier dysfunction and disease mechanisms in ALS models.

Several studies identified correlations between microbial composition and indices of barrier permeability linked to neuroinflammatory pathways. Animal model studies evidenced gut and blood brain barrier (BBB) dysfunction in ALS mice correlating with gut dysbiosis (Zhang et al., 2017; Wu et al., 2015; McCourt et al., 2026; Zhang et al., 2024; Aragón-González et al., 2024). A study found, in SOD1-G93A mice, gut dysbiosis emerges before overt ALS phenotypes and is accompanied by reductions in Firmicutes and Escherichia coli, impaired barrier function, and increased permeability (Wu et al., 2015). One study focusing on BBB dysfunction showed brain microvascular endothelial-like cells derived from individuals with C9orf72-linked ALS exhibit reduced barrier integrity (Gotkine et al., 2020).

3.3 Microbial functional pathways and metabolic changes

Several studies have examined microbiota-derived metabolic pathways that may influence ALS pathophysiology. Key findings are summarised in Table 4.

MechanismModelKey findingsReferencesNicotinamide Adenine Dinucleotide (NAD) metabolismHuman; Animal (Mouse)Microbiota-derived metabolites, including nicotinamide, were reported to support mitochondrial proteostasis and improve mitochondrial function in ALS models. These metabolic changes were also associated with enhanced neuronal survival and increased neurogenesis.Gotkine et al. (2020), Blacher et al. (2019), and Zhou et al. (2020).Short-Chain Fatty Acids (SCFAs) (butyrate) metabolismHuman; Animal (Mouse)Reduced abundance of butyrate-producing gut bacteria has been reported in ALS and is associated with increased neuroinflammation and metabolic dysregulation. In experimental models, butyrate supplementation improved intestinal barrier integrity, mitochondrial function, and survival outcomes.Fontdevila et al. (2024), Zhang et al. (2017), Zhang et al. (2025), Ogbu et al. (2022), Veyrat-Durebex et al. (2025), Xin et al. (2024), and Li X. et al. (2022)Other Microbiota–lipid metabolic axisHuman; Animal (Mouse)Human studies reported alterations in bile acids and other lipid metabolites linked to gut microbiota, indicating disruption of the microbiota–lipid metabolic axis in ALS. These metabolic changes were associated with altered plasma lipid profiles and correlated with disease severity.Gautam et al. (2025), Guo et al. (2023), Niccolai et al. (2024), and Christopher et al. (2025)Microbiota amino-acid metabolic axisHumanHuman studies reported alterations in microbiota-associated amino-acid metabolism in ALS, indicating disruption of host energy metabolic pathways. Mitochondrial dysfunction was partially improved with butyrate and NAD precursor supplementation, suggesting links between microbial metabolites and cellular energy regulation.Gautam et al. (2025), Guo et al. (2023), Niccolai et al. (2024), Christopher et al. (2025), and Yan et al. (2024)

Microbiota-derived metabolic pathways implicated in ALS.

Metabolomic data reveal alterations in circulating and faecal metabolites associated with microbial activity. In ALS, reduced abundance of bacterial genes associated with nicotinamide metabolism, alongside lower nicotinamide levels in cerebrospinal fluid and serum, has been reported (Gotkine et al., 2020). In SOD1-G93A mice, colonisation with Akkermansia muciniphila increased nicotinamide concentrations in plasma and CSF and improved motor phenotypes and survival (Blacher et al., 2019). Supplementation with nicotinamide riboside promoted neurogenesis and reduced mitochondrial accumulation of misfolded SOD1 protein (Zhou et al., 2020).

Several studies in ALS models and human cohorts report reductions in butyrate-producing bacteria (Fontdevila et al., 2024; Zhang et al., 2024; Li X. et al., 2022). In motor neuron-like cell models, butyrate supplementation improved mitochondrial respiratory function and restored the expression of respiratory chain genes (Li X. et al., 2022). In ALS mouse models, butyrate or probiotic supplementation improved motor function, reduced intestinal and BBB permeability, and lowered inflammatory cytokine expression (Zhang et al., 2017; Zhang et al., 2024; Ogbu et al., 2022). A recent study conducted in 2025 detected metabolic changes in ALS mouse models without the presence of measurable dysbiosis with significant changes in butyrate-producing bacteria (Veyrat-Durebex et al., 2025).

Similarly, recent studies on people with ALS also highlight dysbiosis correlating with a much wider and more complex metabolic network, including medium- and long-chain fatty acids, acylcarnitine metabolism, and amino acid and glutathione metabolism (Gautam et al., 2025; Guo et al., 2023; Yan et al., 2024).

3.4 Microbial functional pathways and immune dysfunction

Immune dysregulation has been widely reported in ALS and may represent a key mechanism linking systemic inflammation with neurodegeneration. Evidence from human and experimental studies describing cytokine alterations and microbial endotoxin–mediated immune activation is summarised in Table 5.

MechanismModelKey findingsReferencesImmune regulatory dysfunctionHumanReduced immune regulatory activity has been reported in ALS patients, including impaired suppressive function of regulatory T cells (Tregs) and reduced Treg numbers. This loss of immune regulation was associated with greater disease severity and faster progression, with Treg suppressive capacity correlating with clinical outcomes.Rentzos et al. (2010) and Beers et al. (2017)Inflammatory cytokines in ALSHumanElevated pro-inflammatory cytokines have been reported in ALS patients in both serum and cerebrospinal fluid, indicating a shift toward a pro-inflammatory immune profile. Increased levels of cytokines including IL-6, TNF-α, and other inflammatory mediators were associated with disease progression and neurodegenerative processes.Niccolai et al. (2021), Rowin et al. (2017), Rentzos et al. (2010), Changqing et al. (2025), Polverino et al. (2020), and Limone et al. (2024).Lipopolysaccharide (LPS)-induced immune activationHuman; Animal (Mouse)Elevated plasma LPS levels have been reported in ALS, indicating exposure to microbial endotoxins and activation of innate immune pathways. In experimental models, LPS exposure triggered neuroinflammatory responses and accelerated motor neuron degeneration, supporting a role for microbial products in chronic immune activation.Zhai et al. (2019), Hertzberg et al. (2022), Kim et al. (2022), Zhang et al. (2005), Zhang et al. (2009), and Nguyen et al. (2004)Peripheral and neuroinflammationAnimal (Mouse)Longitudinal study showed how with disease progression, alteration in gut microbiome correlates with gradual increase in T cells and neutrophils in blood and phenotypic activation of microglia in the spinal cord.Figueroa-Romero et al. (2019).

Immune and inflammatory mechanisms reported in amyotrophic lateral sclerosis (ALS).

Several studies identify correlations between microbial composition and host immune markers, including cytokine profiles. Early dysbiosis in SOD1-G93A mice is associated with altered immune markers in the spinal cord (Figueroa-Romero et al., 2019). Inflammatory cytokine profiles, including elevated IL-17 and IL-23, have been observed in ALS serum and cerebrospinal fluid (Rentzos et al., 2010; Beers et al., 2017; Polverino et al., 2020), consistent with imbalances between T regulatory (Treg) and T helper 17 (Th17) pathways. Several studies demonstrate variations in circulating cytokine levels related to inflammation (Zhang et al., 2025; Polverino et al., 2020).

Elevated plasma lipopolysaccharide (LPS) levels have been reported in ALS patients without clinical infection which shows increased intestinal permeability may permit systemic entry of microbial products (Zhai et al., 2019; Zhang et al., 2009). Chronic low-dose LPS exposure accelerates motor axon loss and reduces survival in SOD1-G37R mice (Nguyen et al., 2004). In patients, increased plasma LPS concentrations correlate with heightened monocyte and macrophage activation measured several years later (Zhang et al., 2005).

Several studies report reduced butyrate-producing bacteria in people with ALS and animal models which may cause short chain fatty acid (SCFA) deficiency contributing to heightened inflammatory tone (Zhai et al., 2019). In SOD1-G37R mice, reduction of butyrate-producing bacteria leads to spinal microglia cells developing a neuroinflammatory phenotype, which preceded the motor dysfunction (Nguyen et al., 2004).

3.5 Interplay between gut dysbiosis and disease-related physiological changes genetics and multi omics studies in gut microbiome and ALS

Genetic and multi-omics approaches have increasingly been used to investigate potential causal relationships between the gut microbiome and ALS. Key findings are summarised in Table 6.

MechanismModelKey findingsReferencesMendelian randomisation: microbiota–ALS causalityGenetic epidemiology; Human genome-wide association study (GWAS)Mendelian randomisation analyses using GWAS datasets evaluated potential causal relationships between gut microbiota composition and ALS risk. The study identified specific bacterial genera whose genetically predicted abundance was associated with ALS susceptibility, suggesting possible causal effects of microbial taxa on disease risk.Changqing et al. (2025),