Unveiling the Gut–Heart Axis in Cardiac Amyloidosis: A Systematic Review of Emerging Evidence

Unveiling the Gut–Heart Axis in Cardiac Amyloidosis: A Systematic Review of Emerging Evidence | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Unveiling the Gut–Heart Axis in Cardiac Amyloidosis: A Systematic Review of Emerging Evidence Taha Bhatti, Dean Whaley, Zain Nadeem This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6638994/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Cardiac amyloidosis is an underdiagnosed infiltrative cardiomyopathy caused by the extracellular deposition of misfolded proteins. The two principal subtypes—light-chain (AL) amyloidosis and transthyretin (ATTR) amyloidosis—differ in pathogenesis and clinical course. Growing evidence implicates the gut microbiota in cardiovascular diseases through immune, inflammatory, and metabolic pathways. However, its potential role in cardiac amyloidosis remains unexplored. Methods: This systematic review was conducted in accordance with the PRISMA 2020 and PRISMA-S guidelines. A comprehensive search of PubMed, EMBASE, and Web of Science was performed from inception to April 2025. Eligible studies included original human research evaluating the gut microbiota in the context of AL or ATTR cardiac amyloidosis via validated molecular techniques such as 16S rRNA sequencing. Titles, abstracts, and full texts were screened by two reviewers, and key variables were extracted and synthesised narratively. Results: Three studies met the inclusion criteria. In a case–control study of hereditary ATTR (ATTRv), patients presented increased microbial α diversity and enrichment of Clostridia-class taxa, particularly those with increased myocardial amyloid burden. A cross-sectional study of ATTRv patients carrying the V142I mutation revealed that Streptococcus and Hungatella were associated with elevated cardiac biomarkers, whereas Intestinimonas was linked to increased left ventricular mass and impaired physical performance. Conversely, in AL amyloidosis, patients showed enrichment of Akkermansia and Bifidobacterium alongside depletion of Faecalibacterium—microbial signatures suggestive of impaired gut barrier integrity and systemic inflammation. A machine learning classifier based on gut microbial taxa achieved a diagnostic accuracy with an AUC of 0.95 in distinguishing AL patients from controls. Across studies, specific genera correlated with cardiac markers such as NT-proBNP, troponin, and left atrial volume. Conclusion: Despite limited sample sizes and methodological heterogeneity, current evidence supports a potential link between gut dysbiosis and cardiac amyloidosis. Microbial signatures may serve as non-invasive biomarkers of disease severity and progression. Further research in larger, multiethnic, and longitudinal cohorts is warranted to validate these associations and explore their therapeutic implications. Cardiac amyloidosis gut microbiota ATTRv AL amyloidosis dysbiosis heart failure NT-proBNP microbial biomarkers systemic inflammation gut–heart axis Figures Figure 1 1. Background 1.1 Overview of Cardiac Amyloidosis Cardiac amyloidosis (CA) is an infiltrative cardiomyopathy characterised by the extracellular deposition of misfolded protein fibrils within the myocardium, leading to progressive diastolic dysfunction and eventual heart failure [1]. The principal subtypes include immunoglobulin light-chain (AL) amyloidosis and transthyretin (ATTR) amyloidosis, the latter of which are subdivided into wild-type (ATTRwt) and hereditary (ATTRv) forms [2]. AL amyloidosis results from the overproduction of monoclonal light chains by clonal plasma cells, leading to rapid cardiac involvement and a poor prognosis if untreated [3]. ATTRwt, formerly termed senile systemic amyloidosis, results from age-related misfolding of wild-type transthyretin, predominantly affecting elderly males [4]. ATTRv is caused by mutations in the TTR gene, with the Val122Ile mutation being notably prevalent among individuals of African descent [1]. These subtypes exhibit distinct pathophysiological mechanisms, clinical presentations, and therapeutic responses [1,5]. The clinical burden of CA is substantial, yet it remains underdiagnosed, particularly in patients presenting with heart failure with preserved ejection fraction (HFpEF) [6]. Studies have reported ATTRwt in approximately 13% of HFpEF patients undergoing transcatheter aortic valve replacement, underscoring its prevalence in this cohort [6]. The nonspecific nature of symptoms, such as fatigue and dyspnoea, often leads to misdiagnosis or delayed recognition [7]. In a survey of patients with ATTR cardiomyopathy (ATTR-CM), more than 39% reported initial misdiagnoses, with some consulting multiple physicians before receiving an accurate diagnosis [8]. This diagnostic delay can result in disease progression and diminished therapeutic efficacy [7,9]. Mortality rates in CA vary by subtype and stage at diagnosis. Untreated AL amyloidosis patients with cardiac involvement have a median survival of approximately six months [3], whereas ATTRwt and ATTRv amyloidosis patients have median survival times of 3.6 and 5.8 years, respectively [4]. Diagnostic challenges stem from overlapping clinical features with other cardiomyopathies and the need for specialised imaging and laboratory assessments [1,2]. Advancements in non-invasive diagnostic modalities, such as cardiac magnetic resonance imaging and bone scintigraphy, have improved detection rates [9]. Nevertheless, increased awareness and a high index of suspicion among clinicians are essential to facilitate early diagnosis and intervention [10]. 1.2 The Gut–Heart Axis: Rationale for Microbiota Exploration The gut–heart axis is an emerging paradigm that captures the complex bidirectional relationship between the intestinal microbiota and cardiovascular function. The gut microbiota plays a critical role in regulating systemic inflammation, immune responses, and proteostasis, all of which are integral to CVD development and progression [11]. Dysbiosis, or an imbalance in microbial composition, can lead to increased intestinal permeability and microbial translocation, which in turn promotes systemic inflammation through toll-like receptor activation and cytokine release [12]. Additionally, microbial metabolites such as trimethylamine-N-oxide (TMAO) have been implicated in endothelial dysfunction and cardiac fibrosis [13]. In addition to its role in cardiovascular health, the gut microbiota is involved in the pathogenesis of neurodegenerative disorders. Microbiota-derived metabolites and immune signalling molecules are increasingly recognised as modulators of central nervous system homeostasis, as evidenced in conditions such as Alzheimer's disease and amyotrophic lateral sclerosis [14,15]. The shared immune‒metabolic pathways between the gut–brain and gut–heart axes underscore the systemic relevance of the microbiota in both neurocardiac and vascular pathologies. In the context of cardiac amyloidosis, the gut–heart axis presents a compelling avenue of investigation. Amyloidosis involves immune dysregulation and proteostatic failure, both of which can be influenced by gut microbial activity. Investigating how dysbiosis may influence amyloid deposition, cardiac biomarker levels, or disease progression could offer new diagnostic biomarkers and therapeutic targets. Given the systemic nature of cardiac amyloidosis and its association with immune and metabolic dysfunction, the gut microbiota represents a biologically plausible factor in disease pathogenesis and clinical heterogeneity. 1.3 Objective and Scope of the Review This systematic review aims to synthesise the current body of human evidence investigating the relationship between the gut microbiota composition and CA. Despite advances in the diagnosis and management of ATTR and AL subtypes, little is known about how gut microbial profiles may influence disease mechanisms or clinical expression. This review systematically evaluates published human studies to identify associations between specific microbial taxa and CA subtypes, severity markers, or cardiac biomarkers. It also explores potential mechanistic pathways linking dysbiosis to amyloid deposition, immune activation, and metabolic dysfunction. By collating these findings, the review assesses whether microbiota signatures possess translational relevance as diagnostic adjuncts or indicators of disease progression, thereby contributing to a more comprehensive understanding of the gut–heart axis in CA. 2. Methods 2.1 Search strategy This systematic review was conducted in accordance with the PRISMA 2020 guidelines and the PRISMA-S extension. A comprehensive search of three major electronic databases — PubMed, EMBASE, and Web of Science — was undertaken to identify original studies evaluating the relationship between the gut microbiota and CA. The search covered all records from database inception to April 2025. To maximise sensitivity, the strategy combined controlled vocabulary terms (e.g., MeSH and EMTREE) with free-text keywords related to the gut microbiota (e.g., “gut microbiome”, “dysbiosis”) and cardiac amyloidosis (e.g., “ATTR”, “AL amyloidosis”, “amyloid cardiomyopathy”). Boolean operators were used to combine concept blocks, and field tags (e.g., title/abstract, ti/ab) were applied to refine relevance. Given the rarity of CA and the emerging nature of microbiota research in this context, search strings were deliberately broadened to include mechanistic keywords such as “bacterial amyloids”, “curli”, and “cross-seeding”. The database-specific search strings were adapted appropriately and are presented in Table 1 . No date or study design restrictions were applied during the initial search phase. However, only English-language, peer-reviewed, full-text articles were eligible for inclusion during the screening process. In addition to database searches, the reference lists of all included studies were manually reviewed to identify any additional relevant articles not captured through electronic searches. All records were exported and managed in EndNote for deduplication prior to screening. Table 1 Database search strings Database Search String PubMed ("gut microbiota"[Title/Abstract] OR "intestinal microbiota"[Title/Abstract] OR "gut microbiome"[Title/Abstract] OR "dysbiosis"[Title/Abstract] OR "gut flora"[Title/Abstract]) AND ("amyloidosis"[Title/Abstract] OR "cardiac amyloidosis"[Title/Abstract] OR "transthyretin amyloidosis"[Title/Abstract] OR "ATTR"[Title/Abstract] OR "AL amyloidosis"[Title/Abstract] OR "amyloid cardiomyopathy"[Title/Abstract]) OR ("bacterial amyloids"[Title/Abstract] OR "curli"[Title/Abstract] OR "cross-seeding"[Title/Abstract]) AND ("cardiac"[Title/Abstract] OR "heart"[Title/Abstract]) EMBASE ((gut microbiota or gut flora or intestinal microbiome or dysbiosis) and (amyloidosis or cardiac amyloidosis or transthyretin amyloidosis or ATTR or AL amyloidosis or amyloid cardiomyopathy) and (cardiac or heart or cardiomyopathy)).ti, ab. Web of Science Search strategy adapted from PubMed using keyword-based syntax with topic field (TS=), e.g.: TS=("gut microbiota" OR "intestinal microbiota" OR "dysbiosis") AND TS=("cardiac amyloidosis" OR "ATTR" OR "AL amyloidosis") AND TS=("cardiac" OR "heart") 2.2 Eligibility criteria Studies were eligible for inclusion if they met the following criteria: (i) were original human research articles; (ii) investigated the gut microbiota in the context of cardiac amyloidosis, including transthyretin-related forms (ATTRwt or ATTRv), light-chain amyloidosis (AL), or unspecified subtypes with documented cardiac involvement; (iii) used validated microbiota assessment techniques, such as 16S rRNA gene sequencing; and (iv) reported clinical outcomes relevant to amyloid deposition, myocardial dysfunction, or disease progression. The exclusion criteria were as follows: (i) nonoriginal publications such as reviews, meta-analyses, editorials, commentaries, or conference abstracts; (ii) studies based exclusively on animal models or in vitro data; (iii) articles focused solely on noncardiac forms of amyloidosis or unrelated disease entities; (iv) lack of gut microbiota assessment or unclear methodological reporting; and (v) non-English publications or articles without full-text availability. This review was not registered on PROSPERO owing to its exploratory scope and the emerging nature of the topic. 2.3 Study Selection and PRISMA Flow The titles and abstracts of all identified records were screened by two independent reviewers to assess eligibility. Full-text articles were subsequently retrieved for studies deemed potentially relevant. Discrepancies at any stage of the selection process were resolved through consensus or, where necessary, consultation with a third reviewer. Duplicate records were manually removed prior to screening. A PRISMA 2020-compliant flow diagram is provided to illustrate the selection process from initial identification to final inclusion (Fig. 1 ). 2.4 Data Extraction and Management Data were extracted via a predefined Excel spreadsheet developed a priori to ensure consistency and relevance to the review objectives. Two reviewers independently extracted information and cross-verified all entries to minimise errors. The key variables included study design, sample size, participant characteristics, amyloidosis subtype, microbiota assessment technique, and primary outcomes. Additional extracted data included microbial diversity metrics, taxonomic alterations, cardiac biomarkers, and reported clinical phenotypes associated with cardiac amyloidosis. 2.5 Quality assessment Owing to the limited number of eligible studies (n = 3) and the substantial heterogeneity in study design, population characteristics, and outcome reporting, a formal risk-of-bias tool (e.g., ROBINS-I or the Newcastle–Ottawa Scale) was not applied. Instead, a qualitative appraisal of methodological quality was performed. This included assessment of study design robustness, sample size adequacy, validity and reproducibility of microbiota sequencing platforms (e.g., 16S rRNA, amplicon region), statistical methods used for microbial diversity analysis, and the clarity of amyloidosis subtype classification and cardiac endpoint definition. The methodological variability reflects the novelty of this field and reinforces the need for future studies to adopt standardised diagnostic and analytic frameworks to improve comparability and reproducibility across microbiome–cardiac amyloidosis research. 3. Results Table 2 Summary of Included Studies Study Country Design Sample Size (CA/Controls) Subtype(s) Microbiota Methods Key Findings Chen et al., 2024 [ 16 ] Taiwan Case–control 38 ATTRv/39 ATTRv (A97S predominant) 16S rRNA (V3–V4), QIIME2 ↑ α-diversity in ATTRv; ↑ Clostridia (e.g., Eubacterium , Oscillibacter ); ↓ Bacteroidetes ; diversity correlated with technetium-pyrophosphate uptake and inversely with neuropathy severity. Rissato et al., 2025 [ 17 ] Brazil Cross-sectional 39 ATTR (85% ATTRv), 21 controls ATTRv (V142I common), ATTRwt 16S rRNA (V3–V4), LEfSe Streptococcus and Hungatella ↑ in patients with ↑ BNP/troponin; Lachnospiraceae UCG-003 associated with ↓ BNP; Intestinimonas correlated with ↑ LV mass, ↓ 6MWT; partial overlap in core microbiota. Yan et al., 2022 [ 18 ] China Case–control 27 AL/27 AL 16S rRNA (V3–V4), Random Forest ↑ Akkermansia , Bifidobacterium ; ↓ Faecalibacterium ; compositional β-diversity shift (PERMANOVA p = 0.001); POD classifier AUC = 0.95; taxa correlated with NT-proBNP, cTnT, Mayo stage; barrier dysfunction and inflammation implied. 3.1 Microbial Diversity in Hereditary ATTRv (Chen et al.) In this case–control study, Chen et al. (2024) investigated the gut microbiota composition in 38 patients with ATTRv, primarily those carrying the A97S mutation, and compared them with 39 age-matched household controls. All patients demonstrated sensorimotor polyneuropathy and had evidence of cardiac involvement, which was confirmed by 99mTc-PYP SPECT imaging. Notably, 58.3% of patients presented a visual score (VS) of 3, which is indicative of substantial myocardial amyloid uptake. Gut microbiota profiling was performed via 16S rRNA V3–V4 sequencing. Compared with controls, ATTRv patients presented significantly greater α diversity, as evidenced by elevated amplicon sequence variant (ASV) richness (p = 0.046) and Shannon effective numbers (p = 0.049), suggesting increased microbial richness and evenness. β-Diversity analysis via UniFrac distances demonstrated a distinct microbial community structure in ATTRv patients (p = 0.001, PERMANOVA), reinforcing the occurrence of compositional shifts. LEfSe analysis revealed an increased abundance of taxa within Firmicutes, including Clostridia, Eubacterium, the Lachnospiraceae NK4A136 group, and Oscillospira, while Bacteroidetes were significantly depleted. Importantly, patients with greater cardiac amyloid burden (VS 3) had greater microbial α diversity (p = 0.033), suggesting a link between microbiota complexity and the cardiomyopathy phenotype. Furthermore, the abundance of Clostridia-class taxa (e.g., Eubacterium oxidoreducens, Oscillibacter) was inversely correlated with neuropathic severity, including intraepidermal nerve fibre density and sensory thresholds on quantitative sensory testing, suggesting a potential neuroprotective or modulatory role of these bacteria in peripheral nerve integrity. Together, these findings highlight a dysbiotic gut microbial profile in ATTRv, characterised by an elevated Firmicutes-to-Bacteroidetes ratio and increased Clostridia abundance, with potential pathophysiological relevance to both cardiac and peripheral nerve manifestations. 3.2 Gut Microbiota Alterations in ATTRv Amyloidosis with Cardiac Involvement (Rissato et al.) In a cross-sectional study by Rissato et al. (2025), the gut microbiota composition of patients with ATTR was analysed in relation to cardiac involvement and genotype. Among the 39 ATTR patients included, 85% had ATTRv, with the V142I variant identified in 52.9%, a mutation strongly associated with cardiac-predominant amyloidosis. Patients were stratified into three groups: those with cardiac involvement (G1), those without cardiac involvement (G2), and healthy controls (G3). Compared with G2 patients, G1 patients had significantly elevated levels of cardiac biomarkers, including BNP (mean 484.3 pg/mL vs 21.4 pg/mL, p = 0.033), higher troponin I levels, and increased left ventricular mass index and left atrial volume. These findings confirmed the presence of clinically and echocardiographically defined cardiac amyloidosis in G1. Microbiota profiling via 16S rRNA gene sequencing revealed differences in bacterial taxa between groups, although overall α-diversity and β-diversity did not significantly differ. Within the ATTR cohort, the genus Streptococcus was positively associated with elevated troponin I, and Hungatella was correlated with increased BNP levels and greater gastrointestinal symptom burden. In contrast, Lachnospiraceae UCG-003 was associated with lower BNP levels and smaller left atrial volumes, suggesting a potential protective microbial influence on cardiac remodelling. Notably, the Intestinimonas genus was enriched in V142I carriers and associated with an increased cardiac mass index, increased troponin, and reduced physical performance on the six-minute walk test. These associations support a possible relationship between the gut microbial composition and the severity of the cardiac phenotype in genetically predisposed individuals. The study also revealed that while no consistent core microbiome was found, 65% of all samples across groups shared an ASV belonging to the genus Dorea, indicating partial microbial overlap despite differing disease phenotypes. Collectively, these findings highlight gut microbial dysbiosis in V142I carriers with cardiac amyloidosis and suggest a potential role for the microbiota in modulating cardiac biomarker profiles and structural cardiac changes in ATTRv. 3.3 Microbial signatures and cardiac biomarker associations in AL amyloidosis (Yan et al.) Yan et al. (2022) conducted a prospective, single-centre case–control study in which gut microbiota profiles were compared between 27 treatment-naïve patients with AL amyloidosis and 27 age- and sex-matched healthy controls. Cardiac involvement was present in 81.5% of AL patients, as defined by elevated NT-proBNP (median 6,158 pg/mL) and/or cardiac troponin T (cTnT) levels, with staging on the basis of the Mayo 2004/2012 criteria. Compared with controls, patients had markedly elevated median NT-proBNP and cTnT values (p < 0.0001), confirming clinically significant myocardial involvement. Microbiota analysis via 16S rRNA sequencing (V3–V4 region) revealed significant taxonomic differences. At the phylum level, AL patients presented a greater relative abundance of Actinobacteria (p = 0.018) and a lower abundance of Firmicutes (p = 0.012). At the genus level, Bifidobacterium and Akkermansia were significantly enriched in AL patients (p = 0.003 and p = 0.004, respectively), whereas the short-chain fatty acid (SCFA)-producing genus Faecalibacterium was markedly depleted (p < 0.001). To evaluate diagnostic utility, the authors constructed a probability of disease (POD) index via a random forest classifier trained on eight discriminative genera. This model achieved an area under the curve (AUC) of 0.95, demonstrating excellent discrimination between AL patients and healthy controls. Notably, higher POD scores were significantly correlated with Mayo cardiac staging, NT-proBNP levels, and cTnT concentrations (all p < 0.01), suggesting a potential link between gut microbial alterations and cardiac disease severity in AL amyloidosis patients. The alpha diversity indices (Shannon and Chao1 indices) did not differ significantly between the groups. However, beta diversity (Bray‒Curtis dissimilarity) revealed clear compositional separation between the AL and control microbiota (PERMANOVA p = 0.001), reflecting distinct community structures. Overall, the gut microbiota of AL amyloidosis patients is characterised by taxonomic signatures associated with impaired intestinal barrier function and systemic inflammation. The enrichment of Akkermansia and Bifidobacterium, coupled with the depletion of Faecalibacterium, suggests that a dysbiotic pattern potentially contributes to disease progression. These findings further support the relevance of microbiota-derived signatures as non-invasive biomarkers for the cardiac amyloid burden in AL patients. A summary of microbial taxa associated with cardiac biomarkers, structural metrics, and functional outcomes across the included studies is presented in Table 3 . Table 3 Taxa–phenotype associations across studies Taxon Study Associated Cardiac Phenotype Direction Clostridia spp. Chen et al. (2024) Higher α-diversity; ↑ cardiac uptake on PYP scan ↑ in ATTRv Streptococcus Rissato et al. (2025) ↑ Troponin I ↑ in ATTRv (V142I) Hungatella Rissato et al. (2025) ↑ BNP, GI symptoms ↑ in cardiac ATTRv Intestinimonas Rissato et al. (2025) ↑ LV mass, ↓ 6MWT ↑ in V142I carriers Lachnospiraceae UCG-003 Rissato et al. (2025) ↓ BNP, ↓ LA volume ↑ in noncardiac ATTRv Akkermansia Yan et al. (2022) Barrier thinning; systemic inflammation ↑ in AL Faecalibacterium Yan et al. (2022) SCFA-producing; anti-inflammatory ↓ in AL 4. Discussion 4.1 Shared and Divergent Microbial Alterations in Cardiac Amyloidosis Subtypes Across the three studies included in this review, distinct gut microbial profiles were observed in patients with different forms of CA, highlighting both shared dysbiotic features and subtype-specific divergences that may reflect differences in cardiac pathophysiology, systemic involvement, and disease burden. In ATTRv, particularly among A97S carriers with confirmed cardiac uptake via 99mTc-PYP SPECT imaging, Chen et al. reported a significant increase in microbial α diversity compared with that of age-matched controls. This increase—quantified by amplicon sequence variant (ASV) richness (p = 0.046) and Shannon effective numbers (p = 0.049)—was most pronounced in patients with greater myocardial amyloid burden (visual score 3), suggesting that increased microbial diversity may cooccur with, or even influence, the progression of cardiac involvement. Taxonomically, the ATTRv microbiota was characterised by enrichment in Firmicutes, particularly members of the Clostridia class (including Eubacterium , Lachnospiraceae NK4A136 , and Oscillospira ), whereas Bacteroidetes were significantly depleted. These compositional shifts may indicate microbial participation in inflammatory or metabolic pathways relevant to cardiac tissue stress, although causality remains undetermined. The study by Rissato et al. further revealed a microbial link to the cardiac phenotype in ATTRv, specifically among patients carrying the V142I mutation, which is known to preferentially affect the heart. Although α- and β-diversity metrics did not significantly differ between patients with and without cardiac involvement, genus-level associations revealed meaningful patterns. In patients with echocardiographic and biomarker-confirmed disease, a higher relative abundance of Streptococcus was associated with elevated troponin I, and Hungatella correlated with increased BNP levels and gastrointestinal symptom severity. In contrast, Lachnospiraceae UCG-003 —another SCFA-producing taxon—was inversely associated with BNP and left atrial volume, implying a potential protective role against cardiac remodelling. Most notably, Intestinimonas was enriched in V142I carriers and was significantly associated with increased cardiac mass index, elevated troponin, and impaired functional capacity on the six-minute walk test. These correlations suggest that microbial composition may not only reflect systemic disease burden but also track the structural and functional cardiac phenotype. Although causation cannot be established, such findings support the hypothesis that gut dysbiosis may participate in or respond to disease processes involving myocardial strain, neurohormonal activation, or systemic inflammation in genetically susceptible individuals. In contrast, AL amyloidosis presents a distinct microbiota signature, which is consistent with its fundamentally different pathogenesis involving monoclonal light chain deposition and systemic endothelial toxicity. Yan et al. demonstrated that AL patients—81.5% of whom had cardiac involvement on the basis of elevated NT-proBNP and cTnT—had a relatively high relative abundance of Actinobacteria and specific enrichment of Bifidobacterium and Akkermansia , alongside a marked depletion of Faecalibacterium . While α diversity did not differ significantly from that of the controls, beta diversity revealed clear compositional segregation (PERMANOVA p = 0.001). The loss of Faecalibacterium , a major producer of butyrate and anti-inflammatory metabolites, may contribute to impaired gut barrier integrity and systemic inflammatory signalling, which in turn could exacerbate cardiac tissue vulnerability to amyloid light chain toxicity. The associations between specific microbial taxa and Mayo cardiac staging, NT-proBNP, and cTnT further support the hypothesis that the gut microbiota may reflect or amplify the severity of cardiac dysfunction in AL. The construction of a POD index from eight discriminatory genera, with an AUC of 0.95, also raises the possibility that microbiota profiling could serve as a non-invasive biomarker for cardiac amyloid burden. While Firmicutes-to-Bacteroidetes ratios are often discussed in the literature as broad markers of gut health, the direction of phylum-level shifts in CA is not consistent across subtypes. Firmicutes were enriched in ATTRv (Chen), particularly among Clostridial taxa, whereas they were depleted in AL (Yan), suggesting that phylum-level interpretations may obscure more relevant genus-level or function-specific changes. The role of SCFA metabolism appears central, particularly given the depletion of Faecalibacterium in AL and the correlation of Lachnospiraceae UCG-003 with favourable cardiac markers in ATTRv. These observations point toward microbial contributions to cardiomyocyte stress responses, inflammation, or fibrotic remodelling, although whether such patterns are primary drivers or downstream markers of systemic disease remains to be determined. Nevertheless, the strong correlation of microbiota shifts with structural (e.g., LV mass), biochemical (NT-proBNP, troponin), and functional (6MWT) cardiac parameters across studies suggests that the gut microbiome could represent a relevant component of disease expression in cardiac amyloidosis and warrants further investigation. 4.2 Immune, barrier, and cardiometabolic pathways The interplay between the gut microbiota and host immunity is increasingly recognised as a key driver of systemic diseases, including cardiac conditions. In CA, where chronic inflammation and endothelial dysfunction contribute to myocardial vulnerability and fibrotic progression, microbiota-derived pathways may represent both upstream modulators and downstream amplifiers of disease activity. The findings from this review suggest distinct immunometabolic profiles across amyloidosis subtypes, with implications for both cardiac stress and systemic amyloidogenesis. For hereditary ATTRv, Chen et al. reported enrichment of Clostridia -class taxa, particularly Eubacterium oxidoreducens and Oscillibacter , in patients with a high cardiac amyloid burden. These taxa were inversely correlated with neuropathy severity, suggesting that their metabolites—such as secondary bile acids or anti-inflammatory SCFAs—may exert neuroprotective and potentially cardioprotective effects. In contrast, Rissato et al. reported that Streptococcus and Hungatella , which are enriched in patients with cardiac involvement, were positively correlated with troponin I and BNP. These taxa have been previously linked to systemic inflammation and gut permeability, suggesting that they play a role in exacerbating myocardial stress through immune activation or microbial translocation [ 12 , 19 ]. The strongest evidence for gut barrier dysfunction and immune-metabolic disturbance emerged in AL amyloidosis. Yan et al. reported an increased abundance of Akkermansia , a mucin-degrading genus associated with epithelial thinning, and depletion of Faecalibacterium , a major SCFA producer known to support mucosal integrity. These changes are consistent with a loss of anti-inflammatory capacity and greater potential for systemic translocation of microbial products such as LPS or peptidoglycan [ 20 ]. Butyrate, produced by genera such as Faecalibacterium , regulates tight junction integrity and suppresses proinflammatory cytokine expression via TLR signalling pathways [ 21 ]. Its loss could amplify low-grade inflammation and increase endothelial susceptibility to amyloid deposition. This gut–cardiac axis is well established in other cardiovascular diseases. In heart failure, elevated plasma levels of TMAO—a gut microbial metabolite of dietary choline and carnitine—have been associated with vascular inflammation, myocardial fibrosis, and worse clinical outcomes [ 22 ]. While TMAO was not evaluated in the studies included here, its mechanistic relevance supports the plausibility of microbiota-mediated pathways in CA. Additionally, microbial ligands such as LPS may activate Toll-like receptor 4 on cardiomyocytes, promoting profibrotic and apoptotic signalling cascades. These effects could converge with amyloid toxicity to accelerate cardiac dysfunction. Taken together, the immunometabolic alterations associated with gut dysbiosis in CA—particularly in AL—suggest that microbial imbalance is not merely an epiphenomenon but may also contribute to disease progression via systemic inflammation, barrier failure, and cardiometabolic stress. Future studies should incorporate targeted measurements of immune and barrier markers, alongside microbiota and cardiac phenotyping, to delineate causal relationships and identify potential points of therapeutic intervention. 4.3 Clinical and Translational Implications The emerging gut microbial signatures identified in patients with CA carry significant translational potential, particularly as non-invasive biomarkers and adjunctive therapeutic targets. Among the most compelling findings is the construction of a POD classifier by Yan et al., which is based on eight discriminatory genera. This model achieved an AUC of 0.95 and showed strong correlations with Mayo cardiac stage, NT-proBNP levels, and troponin T concentrations, highlighting its potential value in risk stratification for AL amyloidosis. While formal classifiers have not yet been developed for ATTRv, several microbial taxa have shown reproducible associations with clinically relevant phenotypes. For example, Intestinimonas was linked to cardiac mass and impaired six-minute walk test performance, whereas Lachnospiraceae UCG-003 correlated with lower BNP and left atrial volume, suggesting potential utility in identifying more favourable cardiac remodelling phenotypes. These findings raise the possibility of using microbiota-based metrics to complement imaging and serum biomarkers in risk stratification, particularly in genotype-positive individuals with early or subclinical disease. Microbial profiling could also be integrated into longitudinal care, potentially serving as a tool to track disease progression or treatment response in patients receiving TTR stabilisers or immunosuppressive therapy. In ambiguous clinical scenarios, especially where cardiac involvement is uncertain, microbiota composition may increase diagnostic certainty when used alongside conventional parameters. Therapeutically, microbiota-targeted interventions—such as dietary modulation, SCFA restoration, prebiotics, or faecal microbiota transplantation (FMT)—could, in theory, modulate immune responses and restore gut barrier function. Although not yet trialled in amyloidosis, such approaches have shown efficacy in models of heart failure, atherosclerosis, and hypertension, where microbial manipulation reduces myocardial fibrosis, oxidative stress, and neurohormonal activation [ 23 , 24 ]. Given the parallels in endothelial dysfunction and systemic inflammation, these strategies warrant exploration in CA, beginning with mechanistic studies and preclinical models. 4.4 Limitations and Future Directions Despite promising associations between the gut microbiota and CA subtypes, the current evidence remains preliminary and should be interpreted with caution. All included studies were modest in scale, with sample sizes ranging from 27 to 39 participants, limiting their statistical power and precluding stratified analysis by clinically relevant variables such as genotype, disease stage, or treatment status. This is particularly important given the interpersonal variability of the gut microbiome and the heterogeneity of CA phenotypes. Geographic and ethnic restrictions further limit generalisability. Each study was single-centre and conducted in East Asia or South America, with limited ethnic or dietary diversity. As the gut microbial composition is shaped by environmental, genetic, and cultural factors, replication in multiethnic, geographically diverse cohorts is essential to validate both taxonomic patterns and biomarker potential. Methodological heterogeneity also complicates interpretation. Differences in 16S rRNA variable regions, sequencing platforms, bioinformatic pipelines, and statistical analysis frameworks reduce comparability across studies. None of the included investigations employed shotgun metagenomics, metabolomic profiling, or host–microbiome integration, nor did they incorporate advanced cardiac phenotyping such as MRI or positron emission tomography -based amyloid quantification. This limits both mechanistic interpretation and clinical translatability. Critically, all studies were cross-sectional and observational in design, precluding causal inference. Confounding variables such as diet, medications, and comorbidities likely influence gut microbial composition and may obscure true biological associations. The dynamic nature of the microbiome also demands longitudinal validation in ethnically and geographically diverse populations before clinical application. Without such longitudinal data, it remains unclear whether dysbiosis precedes cardiac involvement, evolves in parallel, or results from amyloid-induced systemic dysfunction. In summary, while preliminary, current evidence supports further investigation into the use of gut microbiota profiling for diagnostic augmentation, risk stratification, and potentially therapeutic modulation in cardiac amyloidosis. Future research must adopt prospective, multicentre designs with harmonised sequencing protocols and comprehensive cardiac phenotyping. Stratification by genotype, sex, and amyloid subtype will be key to uncovering clinically meaningful associations. Integration of microbiome data with host immune, proteomic, and imaging biomarkers will enable a systems-level understanding of gut–heart interactions in CA. Experimental models—including germ-free or humanised microbiota mice—may also help clarify causal mechanisms and evaluate microbiota-targeted interventions before clinical translation. 5. Conclusion This systematic review provides emerging evidence that the composition of the gut microbiota is altered in CA and may reflect, amplify, or modulate disease expression across subtypes. In ATTRv, distinct microbial profiles, particularly those involving Clostridia , Intestinimonas , and Lachnospiraceae , appear to track cardiac remodelling and biomarker elevation, suggesting their relevance to myocardial strain and functional reserve. In AL amyloidosis, enrichment of Akkermansia and depletion of Faecalibacterium indicate that gut barrier dysfunction, systemic inflammation, and endothelial vulnerability are possible drivers of cardiac toxicity. These subtype-specific microbial patterns, and their associations with established cardiac biomarkers and structural indices, support the potential of the gut microbiome as a novel non-invasive tool for disease stratification, risk assessment, and monitoring. Moreover, the integration of microbial data into personalised care models could complement current diagnostic and therapeutic strategies, especially in genotype-positive or early-stage cases. Nonetheless, the current literature is limited by small sample sizes, methodological heterogeneity, and a lack of longitudinal or mechanistic studies. Future research should focus on validating these findings in larger, multiethnic cohorts, applying harmonised metagenomic pipelines, and incorporating host transcriptomic, immunologic, and imaging markers. Experimental studies in preclinical amyloidosis models will be critical to establishing causality and testing the feasibility of microbiota-targeted interventions. Overall, the gut–heart axis represents a promising and underexplored frontier in the pathophysiology and clinical management of cardiac amyloidosis. As the field advances, multidisciplinary research integrating cardiology, immunology, and microbiology will be key to translating these insights into therapeutic impact. Abbreviations AL : Light-chain amyloidosis ASV : Amplicon sequence variant ATTR : Transthyretin amyloidosis ATTRv : Hereditary transthyretin amyloidosis ATTRwt : Wild-type transthyretin amyloidosis AUC : Area under the curve BNP : B-type natriuretic peptide CA : Cardiac amyloidosis cTnT : Cardiac troponin T HFpEF : Heart failure with preserved ejection fraction NT-proBNP : N-terminal pro–B-type natriuretic peptide POD : Probability of disease rRNA : Ribosomal ribonucleic acid SCFA : Short-chain fatty acid SPECT : Single-photon emission computed tomography TMAO : Trimethylamine-N-oxide TLR : Toll-like receptor VS : Visual score Declarations Ethics approval and consent to participate Ethics approval was waived, as this study was a systematic review of previously published studies and did not involve direct human or animal research. Consent for publication Not applicable. Availability of data and materials Data sharing is not applicable to this article, as no new datasets were generated or analysed during the current study. All the data analysed during this study are included in this published article and its referenced source materials. Competing interests The authors declare that they have no competing interests. Funding The authors received no specific funding for this work. Authors’ contributions T.B. conceived the study, designed the review protocol, performed the literature search, conducted the data analysis, and drafted the manuscript. Z.N. and D.W. contributed as second authors by performing data extraction, proofreading the manuscript, and independently reviewing and verifying the extracted data. All the authors read and approved the final manuscript. Acknowledgements Not applicable. References Kittleson MM, Maurer MS, Ambardekar AV, et al. Cardiac amyloidosis: evolving diagnosis and management: a scientific statement from the American Heart Association. Circulation. 2020;142(1):e7–e22. Falk RH, Alexander KM, Liao R, Dorbala S. AL (light-chain) cardiac amyloidosis: a review of diagnosis and therapy. J Am Coll Cardiol. 2016;68(12):1323–1341. Dispenzieri A, Gertz MA, Kyle RA, et al. Serum cardiac troponins and N-terminal pro–brain natriuretic peptide: a staging system for primary systemic amyloidosis. J Clin Oncol. 2004;22(18):3751–3757. Ruberg FL, Berk JL. Transthyretin (TTR) cardiac amyloidosis. Circulation. 2012;126(10):1286–1300. Quarta CC, Kruger JL, Falk RH. Cardiac amyloidosis. Circulation. 2012;126(12):e178–e182. Gonzalez-Lopez E, Gallego-Delgado M, Guzzo-Merello G, et al. Wild-type transthyretin amyloidosis as a cause of heart failure with preserved ejection fraction. Eur Heart J. 2015;36(38):2585–2594. Maurer MS, Elliott P, Merlini G, et al. Design and rationale of the Phase 3 ATTR-ACT clinical trial (tafamidis in transthyretin cardiomyopathy clinical trial). Circ Heart Fail. 2017;10(6):e003815. Maurer MS, Schwartz JH, Gundapaneni B, et al. Tafamidis treatment for patients with transthyretin amyloid cardiomyopathy. N Engl J Med. 2018;379(11):1007–1016. Gillmore JD, Maurer MS, Falk RH, et al. Nonbiopsy diagnosis of cardiac transthyretin amyloidosis. Circulation. 2016;133(24):2404–2412. Banypersad SM, Moon JC, Whelan C, Hawkins PN, Wechalekar AD. Updates in cardiac amyloidosis: a review. J Am Heart Assoc. 2012;1(2):e000364. Witkowski M, Weeks TL, Hazen SL. Gut microbiota and cardiovascular disease. Circ Res. 2020;127(4):553–570. Tang WHW, Kitai T, Hazen SL. Gut microbiota in cardiovascular health and disease. Circ Res. 2017;120(7):1183–1196. Wang Z, Klipfell E, Bennett BJ, et al. Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature. 2011;472(7341):57–63. Zhu S, Jiang Y, Xu K, Cui M, Ye W. The progress of gut microbiome research related to brain disorders. J Neuroinflammation. 2020;17(1):25. Figueroa-Romero C, Guo K, Murdock BJ, et al. Temporal evolution of the microbiome, immune system and epigenome with disease progression in ALS mice. Dis Model Mech. 2019;12(5):dmm041947. Chen C-C, Tseng P-H, Hsueh H-W, et al. Altered gut microbiota in Taiwanese A97S predominant transthyretin amyloidosis with polyneuropathy. Sci Rep. 2024;14:6195. https://doi.org/10.1038/s41598-024-56984-5 Rissato JH, de Melo Pereira N, Romero CE, et al. Different gut microbiome profiles in patients with transthyretin amyloidosis with and without cardiac involvement. Int J Mol Sci. 2025;26(4):1689. https://doi.org/10.3390/ijms26041689 Yan Y, Wang Y, Shi Y, et al. Alterations of the gut microbiota in patients with immunoglobulin light chain amyloidosis. Front Immunol. 2022;13:973760. https://doi.org/10.3389/fimmu.2022.973760 Karlsson FH, Tremaroli V, Nookaew I, et al. Gut metagenome in European women with normal, impaired and diabetic glucose control. Nature. 2013;498(7452):99–103. Everard A, Belzer C, Geurts L, et al. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity. Proc Natl Acad Sci U S A. 2013;110(22):9066–9071. Furusawa Y, Obata Y, Fukuda S, et al. Commensal microbe-derived butyrate induces the differentiation of colonic regulatory T cells. Nature. 2013;504(7480):446–450. Tang WHW, Wang Z, Levison BS, et al. Intestinal microbial metabolism of phosphatidylcholine and cardiovascular risk. N Engl J Med. 2013;368(17):1575–1584. Lau E, Carvalho D, Freitas P. Gut microbiota: Association with NAFLD and metabolic disturbances. Biomedicines. 2017;5(3):48. Marques FZ, Nelson E, Chu PY, et al. High-fibre diet and acetate supplementation change the gut microbiota and prevent the development of hypertension and heart failure in DOCA-salt hypertensive mice. Circulation. 2018;137(9):964–977. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6638994","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":454858150,"identity":"ef9011b0-f725-4406-8327-a25252b79da4","order_by":0,"name":"Taha Bhatti","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0005-1452-5515","institution":"University of Manchester","correspondingAuthor":true,"prefix":"","firstName":"Taha","middleName":"","lastName":"Bhatti","suffix":""},{"id":454858151,"identity":"65ab3f17-8f89-4bd1-9bb7-fc989d413308","order_by":1,"name":"Dean Whaley","email":"","orcid":"","institution":"Imperial College London","correspondingAuthor":false,"prefix":"","firstName":"Dean","middleName":"","lastName":"Whaley","suffix":""},{"id":454858152,"identity":"ec18ad4a-ad81-444b-a131-f1fe6ab3ccd2","order_by":2,"name":"Zain Nadeem","email":"","orcid":"https://orcid.org/0009-0004-6420-2100","institution":"University of Manchester","correspondingAuthor":false,"prefix":"","firstName":"Zain","middleName":"","lastName":"Nadeem","suffix":""}],"badges":[],"createdAt":"2025-05-11 10:14:37","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6638994/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6638994/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82700430,"identity":"b710bb55-bdb9-4f42-a016-8ca76a259a16","added_by":"auto","created_at":"2025-05-14 09:26:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":179378,"visible":true,"origin":"","legend":"\u003cp\u003ePrisma Flow Chart\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6638994/v1/f574cca9705461b66260f214.png"},{"id":82702254,"identity":"4a27d575-68f4-4ed7-9116-cebb16857e53","added_by":"auto","created_at":"2025-05-14 09:42:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1079983,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6638994/v1/9e15e5ed-a7d6-4870-ba49-26d490c95464.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eUnveiling the Gut–Heart Axis in Cardiac Amyloidosis: A Systematic Review of Emerging Evidence\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Background","content":"\u003cp\u003e\u003cstrong\u003e1.1 Overview of Cardiac Amyloidosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCardiac amyloidosis (CA) is an infiltrative cardiomyopathy characterised by the extracellular deposition of misfolded protein fibrils within the myocardium, leading to progressive diastolic dysfunction and eventual heart failure [1]. The principal subtypes include immunoglobulin light-chain (AL) amyloidosis and transthyretin (ATTR) amyloidosis, the latter of which are subdivided into wild-type (ATTRwt) and hereditary (ATTRv) forms [2]. AL amyloidosis results from the overproduction of monoclonal light chains by clonal plasma cells, leading to rapid cardiac involvement and a poor prognosis if untreated [3]. ATTRwt, formerly termed senile systemic amyloidosis, results from age-related misfolding of wild-type transthyretin, predominantly affecting elderly males [4]. ATTRv is caused by mutations in the TTR gene, with the Val122Ile mutation being notably prevalent among individuals of African descent [1]. These subtypes exhibit distinct pathophysiological mechanisms, clinical presentations, and therapeutic responses [1,5].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe clinical burden of CA is substantial, yet it remains underdiagnosed, particularly in patients presenting with heart failure with preserved ejection fraction (HFpEF) [6]. Studies have reported ATTRwt in approximately 13% of HFpEF patients undergoing transcatheter aortic valve replacement, underscoring its prevalence in this cohort [6]. The nonspecific nature of symptoms, such as fatigue and dyspnoea, often leads to misdiagnosis or delayed recognition [7]. In a survey of patients with ATTR cardiomyopathy (ATTR-CM), more than 39% reported initial misdiagnoses, with some consulting multiple physicians before receiving an accurate diagnosis [8]. This diagnostic delay can result in disease progression and diminished therapeutic efficacy [7,9].\u003c/p\u003e\n\u003cp\u003eMortality rates in CA vary by subtype and stage at diagnosis. Untreated AL amyloidosis patients with cardiac involvement have a median survival of approximately six months [3], whereas ATTRwt and ATTRv amyloidosis patients have median survival times of 3.6 and 5.8 years, respectively [4]. Diagnostic challenges stem from overlapping clinical features with other cardiomyopathies and the need for specialised imaging and laboratory assessments [1,2]. Advancements in non-invasive diagnostic modalities, such as cardiac magnetic resonance imaging and bone scintigraphy, have improved detection rates [9]. Nevertheless, increased awareness and a high index of suspicion among clinicians are essential to facilitate early diagnosis and intervention [10].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.2 The Gut\u0026ndash;Heart Axis: Rationale for Microbiota Exploration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe gut\u0026ndash;heart axis is an emerging paradigm that captures the complex bidirectional relationship between the intestinal microbiota and cardiovascular function. The gut microbiota plays a critical role in regulating systemic inflammation, immune responses, and proteostasis, all of which are integral to CVD development and progression [11]. Dysbiosis, or an imbalance in microbial composition, can lead to increased intestinal permeability and microbial translocation, which in turn promotes systemic inflammation through toll-like receptor activation and cytokine release [12]. Additionally, microbial metabolites such as trimethylamine-N-oxide (TMAO) have been implicated in endothelial dysfunction and cardiac fibrosis [13].\u003c/p\u003e\n\u003cp\u003eIn addition to its role in cardiovascular health, the gut microbiota is involved in the pathogenesis of neurodegenerative disorders. Microbiota-derived metabolites and immune signalling molecules are increasingly recognised as modulators of central nervous system homeostasis, as evidenced in conditions such as Alzheimer\u0026apos;s disease and amyotrophic lateral sclerosis [14,15]. The shared immune‒metabolic pathways between the gut\u0026ndash;brain and gut\u0026ndash;heart axes underscore the systemic relevance of the microbiota in both neurocardiac and vascular pathologies.\u003c/p\u003e\n\u003cp\u003eIn the context of cardiac amyloidosis, the gut\u0026ndash;heart axis presents a compelling avenue of investigation. Amyloidosis involves immune dysregulation and proteostatic failure, both of which can be influenced by gut microbial activity. Investigating how dysbiosis may influence amyloid deposition, cardiac biomarker levels, or disease progression could offer new diagnostic biomarkers and therapeutic targets. Given the systemic nature of cardiac amyloidosis and its association with immune and metabolic dysfunction, the gut microbiota represents a biologically plausible factor in disease pathogenesis and clinical heterogeneity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.3 Objective and Scope of the Review\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis systematic review aims to synthesise the current body of human evidence investigating the relationship between the gut microbiota composition and CA. Despite advances in the diagnosis and management of ATTR and AL subtypes, little is known about how gut microbial profiles may influence disease mechanisms or clinical expression. This review systematically evaluates published human studies to identify associations between specific microbial taxa and CA subtypes, severity markers, or cardiac biomarkers. It also explores potential mechanistic pathways linking dysbiosis to amyloid deposition, immune activation, and metabolic dysfunction. By collating these findings, the review assesses whether microbiota signatures possess translational relevance as diagnostic adjuncts or indicators of disease progression, thereby contributing to a more comprehensive understanding of the gut\u0026ndash;heart axis in CA.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Search strategy\u003c/h2\u003e \u003cp\u003eThis systematic review was conducted in accordance with the PRISMA 2020 guidelines and the PRISMA-S extension. A comprehensive search of three major electronic databases \u0026mdash; PubMed, EMBASE, and Web of Science \u0026mdash; was undertaken to identify original studies evaluating the relationship between the gut microbiota and CA. The search covered all records from database inception to April 2025. To maximise sensitivity, the strategy combined controlled vocabulary terms (e.g., MeSH and EMTREE) with free-text keywords related to the gut microbiota (e.g., \u0026ldquo;gut microbiome\u0026rdquo;, \u0026ldquo;dysbiosis\u0026rdquo;) and cardiac amyloidosis (e.g., \u0026ldquo;ATTR\u0026rdquo;, \u0026ldquo;AL amyloidosis\u0026rdquo;, \u0026ldquo;amyloid cardiomyopathy\u0026rdquo;). Boolean operators were used to combine concept blocks, and field tags (e.g., title/abstract, ti/ab) were applied to refine relevance. Given the rarity of CA and the emerging nature of microbiota research in this context, search strings were deliberately broadened to include mechanistic keywords such as \u0026ldquo;bacterial amyloids\u0026rdquo;, \u0026ldquo;curli\u0026rdquo;, and \u0026ldquo;cross-seeding\u0026rdquo;. The database-specific search strings were adapted appropriately and are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. No date or study design restrictions were applied during the initial search phase. However, only English-language, peer-reviewed, full-text articles were eligible for inclusion during the screening process. In addition to database searches, the reference lists of all included studies were manually reviewed to identify any additional relevant articles not captured through electronic searches. All records were exported and managed in EndNote for deduplication prior to screening.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDatabase search strings\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDatabase\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSearch String\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePubMed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(\"gut microbiota\"[Title/Abstract] OR \"intestinal microbiota\"[Title/Abstract] OR \"gut microbiome\"[Title/Abstract] OR \"dysbiosis\"[Title/Abstract] OR \"gut flora\"[Title/Abstract]) AND (\"amyloidosis\"[Title/Abstract] OR \"cardiac amyloidosis\"[Title/Abstract] OR \"transthyretin amyloidosis\"[Title/Abstract] OR \"ATTR\"[Title/Abstract] OR \"AL amyloidosis\"[Title/Abstract] OR \"amyloid cardiomyopathy\"[Title/Abstract]) OR (\"bacterial amyloids\"[Title/Abstract] OR \"curli\"[Title/Abstract] OR \"cross-seeding\"[Title/Abstract]) AND (\"cardiac\"[Title/Abstract] OR \"heart\"[Title/Abstract])\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEMBASE\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e((gut microbiota or gut flora or intestinal microbiome or dysbiosis) and (amyloidosis or cardiac amyloidosis or transthyretin amyloidosis or ATTR or AL amyloidosis or amyloid cardiomyopathy) and (cardiac or heart or cardiomyopathy)).ti, ab.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWeb of Science\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSearch strategy adapted from PubMed using keyword-based syntax with topic field (TS=), e.g.: TS=(\"gut microbiota\" OR \"intestinal microbiota\" OR \"dysbiosis\") AND TS=(\"cardiac amyloidosis\" OR \"ATTR\" OR \"AL amyloidosis\") AND TS=(\"cardiac\" OR \"heart\")\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Eligibility criteria\u003c/h2\u003e \u003cp\u003eStudies were eligible for inclusion if they met the following criteria: (i) were original human research articles; (ii) investigated the gut microbiota in the context of cardiac amyloidosis, including transthyretin-related forms (ATTRwt or ATTRv), light-chain amyloidosis (AL), or unspecified subtypes with documented cardiac involvement; (iii) used validated microbiota assessment techniques, such as 16S rRNA gene sequencing; and (iv) reported clinical outcomes relevant to amyloid deposition, myocardial dysfunction, or disease progression.\u003c/p\u003e \u003cp\u003eThe exclusion criteria were as follows: (i) nonoriginal publications such as reviews, meta-analyses, editorials, commentaries, or conference abstracts; (ii) studies based exclusively on animal models or in vitro data; (iii) articles focused solely on noncardiac forms of amyloidosis or unrelated disease entities; (iv) lack of gut microbiota assessment or unclear methodological reporting; and (v) non-English publications or articles without full-text availability.\u003c/p\u003e \u003cp\u003eThis review was not registered on PROSPERO owing to its exploratory scope and the emerging nature of the topic.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Study Selection and PRISMA Flow\u003c/h2\u003e \u003cp\u003eThe titles and abstracts of all identified records were screened by two independent reviewers to assess eligibility. Full-text articles were subsequently retrieved for studies deemed potentially relevant. Discrepancies at any stage of the selection process were resolved through consensus or, where necessary, consultation with a third reviewer. Duplicate records were manually removed prior to screening. A PRISMA 2020-compliant flow diagram is provided to illustrate the selection process from initial identification to final inclusion (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data Extraction and Management\u003c/h2\u003e \u003cp\u003eData were extracted via a predefined Excel spreadsheet developed a priori to ensure consistency and relevance to the review objectives. Two reviewers independently extracted information and cross-verified all entries to minimise errors. The key variables included study design, sample size, participant characteristics, amyloidosis subtype, microbiota assessment technique, and primary outcomes. Additional extracted data included microbial diversity metrics, taxonomic alterations, cardiac biomarkers, and reported clinical phenotypes associated with cardiac amyloidosis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Quality assessment\u003c/h2\u003e \u003cp\u003eOwing to the limited number of eligible studies (n\u0026thinsp;=\u0026thinsp;3) and the substantial heterogeneity in study design, population characteristics, and outcome reporting, a formal risk-of-bias tool (e.g., ROBINS-I or the Newcastle\u0026ndash;Ottawa Scale) was not applied. Instead, a qualitative appraisal of methodological quality was performed. This included assessment of study design robustness, sample size adequacy, validity and reproducibility of microbiota sequencing platforms (e.g., 16S rRNA, amplicon region), statistical methods used for microbial diversity analysis, and the clarity of amyloidosis subtype classification and cardiac endpoint definition. The methodological variability reflects the novelty of this field and reinforces the need for future studies to adopt standardised diagnostic and analytic frameworks to improve comparability and reproducibility across microbiome\u0026ndash;cardiac amyloidosis research.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of Included Studies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSample Size (CA/Controls)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSubtype(s)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMicrobiota Methods\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eKey Findings\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChen et al., 2024\u003c/b\u003e [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTaiwan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCase\u0026ndash;control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38 ATTRv/39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eATTRv (A97S predominant)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16S rRNA (V3\u0026ndash;V4), QIIME2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026uarr; α-diversity in ATTRv; \u0026uarr; Clostridia (e.g., \u003cem\u003eEubacterium\u003c/em\u003e, \u003cem\u003eOscillibacter\u003c/em\u003e); \u0026darr; \u003cem\u003eBacteroidetes\u003c/em\u003e; diversity correlated with technetium-pyrophosphate uptake and inversely with neuropathy severity.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRissato et al., 2025\u003c/b\u003e [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 ATTR (85% ATTRv), 21 controls\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eATTRv (V142I common), ATTRwt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16S rRNA (V3\u0026ndash;V4), LEfSe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eStreptococcus\u003c/em\u003e and \u003cem\u003eHungatella\u003c/em\u003e \u0026uarr; in patients with \u0026uarr; BNP/troponin; \u003cem\u003eLachnospiraceae UCG-003\u003c/em\u003e associated with \u0026darr; BNP; \u003cem\u003eIntestinimonas\u003c/em\u003e correlated with \u0026uarr; LV mass, \u0026darr; 6MWT; partial overlap in core microbiota.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYan et al., 2022\u003c/b\u003e [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCase\u0026ndash;control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 AL/27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16S rRNA (V3\u0026ndash;V4), Random Forest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026uarr; \u003cem\u003eAkkermansia\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e; \u0026darr; \u003cem\u003eFaecalibacterium\u003c/em\u003e; compositional β-diversity shift (PERMANOVA p\u0026thinsp;=\u0026thinsp;0.001); POD classifier AUC\u0026thinsp;=\u0026thinsp;0.95; taxa correlated with NT-proBNP, cTnT, Mayo stage; barrier dysfunction and inflammation implied.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Microbial Diversity in Hereditary ATTRv (Chen et al.)\u003c/h2\u003e \u003cp\u003eIn this case\u0026ndash;control study, Chen et al. (2024) investigated the gut microbiota composition in 38 patients with ATTRv, primarily those carrying the A97S mutation, and compared them with 39 age-matched household controls. All patients demonstrated sensorimotor polyneuropathy and had evidence of cardiac involvement, which was confirmed by 99mTc-PYP SPECT imaging. Notably, 58.3% of patients presented a visual score (VS) of 3, which is indicative of substantial myocardial amyloid uptake.\u003c/p\u003e \u003cp\u003eGut microbiota profiling was performed via 16S rRNA V3\u0026ndash;V4 sequencing. Compared with controls, ATTRv patients presented significantly greater α diversity, as evidenced by elevated amplicon sequence variant (ASV) richness (p\u0026thinsp;=\u0026thinsp;0.046) and Shannon effective numbers (p\u0026thinsp;=\u0026thinsp;0.049), suggesting increased microbial richness and evenness. β-Diversity analysis via UniFrac distances demonstrated a distinct microbial community structure in ATTRv patients (p\u0026thinsp;=\u0026thinsp;0.001, PERMANOVA), reinforcing the occurrence of compositional shifts.\u003c/p\u003e \u003cp\u003eLEfSe analysis revealed an increased abundance of taxa within Firmicutes, including Clostridia, Eubacterium, the Lachnospiraceae NK4A136 group, and Oscillospira, while Bacteroidetes were significantly depleted. Importantly, patients with greater cardiac amyloid burden (VS 3) had greater microbial α diversity (p\u0026thinsp;=\u0026thinsp;0.033), suggesting a link between microbiota complexity and the cardiomyopathy phenotype. Furthermore, the abundance of Clostridia-class taxa (e.g., Eubacterium oxidoreducens, Oscillibacter) was inversely correlated with neuropathic severity, including intraepidermal nerve fibre density and sensory thresholds on quantitative sensory testing, suggesting a potential neuroprotective or modulatory role of these bacteria in peripheral nerve integrity.\u003c/p\u003e \u003cp\u003eTogether, these findings highlight a dysbiotic gut microbial profile in ATTRv, characterised by an elevated Firmicutes-to-Bacteroidetes ratio and increased Clostridia abundance, with potential pathophysiological relevance to both cardiac and peripheral nerve manifestations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Gut Microbiota Alterations in ATTRv Amyloidosis with Cardiac Involvement (Rissato et al.)\u003c/h2\u003e \u003cp\u003eIn a cross-sectional study by Rissato et al. (2025), the gut microbiota composition of patients with ATTR was analysed in relation to cardiac involvement and genotype. Among the 39 ATTR patients included, 85% had ATTRv, with the V142I variant identified in 52.9%, a mutation strongly associated with cardiac-predominant amyloidosis. Patients were stratified into three groups: those with cardiac involvement (G1), those without cardiac involvement (G2), and healthy controls (G3). Compared with G2 patients, G1 patients had significantly elevated levels of cardiac biomarkers, including BNP (mean 484.3 pg/mL vs 21.4 pg/mL, p\u0026thinsp;=\u0026thinsp;0.033), higher troponin I levels, and increased left ventricular mass index and left atrial volume. These findings confirmed the presence of clinically and echocardiographically defined cardiac amyloidosis in G1.\u003c/p\u003e \u003cp\u003eMicrobiota profiling via 16S rRNA gene sequencing revealed differences in bacterial taxa between groups, although overall α-diversity and β-diversity did not significantly differ. Within the ATTR cohort, the genus Streptococcus was positively associated with elevated troponin I, and Hungatella was correlated with increased BNP levels and greater gastrointestinal symptom burden. In contrast, Lachnospiraceae UCG-003 was associated with lower BNP levels and smaller left atrial volumes, suggesting a potential protective microbial influence on cardiac remodelling. Notably, the Intestinimonas genus was enriched in V142I carriers and associated with an increased cardiac mass index, increased troponin, and reduced physical performance on the six-minute walk test. These associations support a possible relationship between the gut microbial composition and the severity of the cardiac phenotype in genetically predisposed individuals.\u003c/p\u003e \u003cp\u003eThe study also revealed that while no consistent core microbiome was found, 65% of all samples across groups shared an ASV belonging to the genus Dorea, indicating partial microbial overlap despite differing disease phenotypes. Collectively, these findings highlight gut microbial dysbiosis in V142I carriers with cardiac amyloidosis and suggest a potential role for the microbiota in modulating cardiac biomarker profiles and structural cardiac changes in ATTRv.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Microbial signatures and cardiac biomarker associations in AL amyloidosis (Yan et al.)\u003c/h2\u003e \u003cp\u003eYan et al. (2022) conducted a prospective, single-centre case\u0026ndash;control study in which gut microbiota profiles were compared between 27 treatment-na\u0026iuml;ve patients with AL amyloidosis and 27 age- and sex-matched healthy controls. Cardiac involvement was present in 81.5% of AL patients, as defined by elevated NT-proBNP (median 6,158 pg/mL) and/or cardiac troponin T (cTnT) levels, with staging on the basis of the Mayo 2004/2012 criteria. Compared with controls, patients had markedly elevated median NT-proBNP and cTnT values (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), confirming clinically significant myocardial involvement. Microbiota analysis via 16S rRNA sequencing (V3\u0026ndash;V4 region) revealed significant taxonomic differences. At the phylum level, AL patients presented a greater relative abundance of Actinobacteria (p\u0026thinsp;=\u0026thinsp;0.018) and a lower abundance of Firmicutes (p\u0026thinsp;=\u0026thinsp;0.012). At the genus level, Bifidobacterium and Akkermansia were significantly enriched in AL patients (p\u0026thinsp;=\u0026thinsp;0.003 and p\u0026thinsp;=\u0026thinsp;0.004, respectively), whereas the short-chain fatty acid (SCFA)-producing genus Faecalibacterium was markedly depleted (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eTo evaluate diagnostic utility, the authors constructed a probability of disease (POD) index via a random forest classifier trained on eight discriminative genera. This model achieved an area under the curve (AUC) of 0.95, demonstrating excellent discrimination between AL patients and healthy controls. Notably, higher POD scores were significantly correlated with Mayo cardiac staging, NT-proBNP levels, and cTnT concentrations (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), suggesting a potential link between gut microbial alterations and cardiac disease severity in AL amyloidosis patients. The alpha diversity indices (Shannon and Chao1 indices) did not differ significantly between the groups. However, beta diversity (Bray‒Curtis dissimilarity) revealed clear compositional separation between the AL and control microbiota (PERMANOVA p\u0026thinsp;=\u0026thinsp;0.001), reflecting distinct community structures.\u003c/p\u003e \u003cp\u003eOverall, the gut microbiota of AL amyloidosis patients is characterised by taxonomic signatures associated with impaired intestinal barrier function and systemic inflammation. The enrichment of Akkermansia and Bifidobacterium, coupled with the depletion of Faecalibacterium, suggests that a dysbiotic pattern potentially contributes to disease progression. These findings further support the relevance of microbiota-derived signatures as non-invasive biomarkers for the cardiac amyloid burden in AL patients. A summary of microbial taxa associated with cardiac biomarkers, structural metrics, and functional outcomes across the included studies is presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTaxa\u0026ndash;phenotype associations across studies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTaxon\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAssociated Cardiac Phenotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDirection\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eClostridia\u003c/em\u003e spp.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChen et al. (2024)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigher α-diversity; \u0026uarr; cardiac uptake on PYP scan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026uarr; in ATTRv\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStreptococcus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRissato et al. (2025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026uarr; Troponin I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026uarr; in ATTRv (V142I)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHungatella\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRissato et al. (2025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026uarr; BNP, GI symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026uarr; in cardiac ATTRv\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIntestinimonas\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRissato et al. (2025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026uarr; LV mass, \u0026darr; 6MWT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026uarr; in V142I carriers\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLachnospiraceae UCG-003\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRissato et al. (2025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026darr; BNP, \u0026darr; LA volume\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026uarr; in noncardiac ATTRv\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAkkermansia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYan et al. (2022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBarrier thinning; systemic inflammation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026uarr; in AL\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFaecalibacterium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYan et al. (2022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSCFA-producing; anti-inflammatory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026darr; in AL\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Shared and Divergent Microbial Alterations in Cardiac Amyloidosis Subtypes\u003c/h2\u003e \u003cp\u003eAcross the three studies included in this review, distinct gut microbial profiles were observed in patients with different forms of CA, highlighting both shared dysbiotic features and subtype-specific divergences that may reflect differences in cardiac pathophysiology, systemic involvement, and disease burden. In ATTRv, particularly among A97S carriers with confirmed cardiac uptake via 99mTc-PYP SPECT imaging, Chen et al. reported a significant increase in microbial α diversity compared with that of age-matched controls. This increase\u0026mdash;quantified by amplicon sequence variant (ASV) richness (p\u0026thinsp;=\u0026thinsp;0.046) and Shannon effective numbers (p\u0026thinsp;=\u0026thinsp;0.049)\u0026mdash;was most pronounced in patients with greater myocardial amyloid burden (visual score 3), suggesting that increased microbial diversity may cooccur with, or even influence, the progression of cardiac involvement. Taxonomically, the ATTRv microbiota was characterised by enrichment in Firmicutes, particularly members of the \u003cem\u003eClostridia\u003c/em\u003e class (including \u003cem\u003eEubacterium\u003c/em\u003e, \u003cem\u003eLachnospiraceae NK4A136\u003c/em\u003e, and \u003cem\u003eOscillospira\u003c/em\u003e), whereas Bacteroidetes were significantly depleted. These compositional shifts may indicate microbial participation in inflammatory or metabolic pathways relevant to cardiac tissue stress, although causality remains undetermined.\u003c/p\u003e \u003cp\u003eThe study by Rissato et al. further revealed a microbial link to the cardiac phenotype in ATTRv, specifically among patients carrying the V142I mutation, which is known to preferentially affect the heart. Although α- and β-diversity metrics did not significantly differ between patients with and without cardiac involvement, genus-level associations revealed meaningful patterns. In patients with echocardiographic and biomarker-confirmed disease, a higher relative abundance of \u003cem\u003eStreptococcus\u003c/em\u003e was associated with elevated troponin I, and \u003cem\u003eHungatella\u003c/em\u003e correlated with increased BNP levels and gastrointestinal symptom severity. In contrast, \u003cem\u003eLachnospiraceae UCG-003\u003c/em\u003e\u0026mdash;another SCFA-producing taxon\u0026mdash;was inversely associated with BNP and left atrial volume, implying a potential protective role against cardiac remodelling. Most notably, \u003cem\u003eIntestinimonas\u003c/em\u003e was enriched in V142I carriers and was significantly associated with increased cardiac mass index, elevated troponin, and impaired functional capacity on the six-minute walk test. These correlations suggest that microbial composition may not only reflect systemic disease burden but also track the structural and functional cardiac phenotype. Although causation cannot be established, such findings support the hypothesis that gut dysbiosis may participate in or respond to disease processes involving myocardial strain, neurohormonal activation, or systemic inflammation in genetically susceptible individuals.\u003c/p\u003e \u003cp\u003eIn contrast, AL amyloidosis presents a distinct microbiota signature, which is consistent with its fundamentally different pathogenesis involving monoclonal light chain deposition and systemic endothelial toxicity. Yan et al. demonstrated that AL patients\u0026mdash;81.5% of whom had cardiac involvement on the basis of elevated NT-proBNP and cTnT\u0026mdash;had a relatively high relative abundance of Actinobacteria and specific enrichment of \u003cem\u003eBifidobacterium\u003c/em\u003e and \u003cem\u003eAkkermansia\u003c/em\u003e, alongside a marked depletion of \u003cem\u003eFaecalibacterium\u003c/em\u003e. While α diversity did not differ significantly from that of the controls, beta diversity revealed clear compositional segregation (PERMANOVA p\u0026thinsp;=\u0026thinsp;0.001). The loss of \u003cem\u003eFaecalibacterium\u003c/em\u003e, a major producer of butyrate and anti-inflammatory metabolites, may contribute to impaired gut barrier integrity and systemic inflammatory signalling, which in turn could exacerbate cardiac tissue vulnerability to amyloid light chain toxicity. The associations between specific microbial taxa and Mayo cardiac staging, NT-proBNP, and cTnT further support the hypothesis that the gut microbiota may reflect or amplify the severity of cardiac dysfunction in AL. The construction of a POD index from eight discriminatory genera, with an AUC of 0.95, also raises the possibility that microbiota profiling could serve as a non-invasive biomarker for cardiac amyloid burden.\u003c/p\u003e \u003cp\u003eWhile Firmicutes-to-Bacteroidetes ratios are often discussed in the literature as broad markers of gut health, the direction of phylum-level shifts in CA is not consistent across subtypes. Firmicutes were enriched in ATTRv (Chen), particularly among Clostridial taxa, whereas they were depleted in AL (Yan), suggesting that phylum-level interpretations may obscure more relevant genus-level or function-specific changes. The role of SCFA metabolism appears central, particularly given the depletion of \u003cem\u003eFaecalibacterium\u003c/em\u003e in AL and the correlation of \u003cem\u003eLachnospiraceae UCG-003\u003c/em\u003e with favourable cardiac markers in ATTRv. These observations point toward microbial contributions to cardiomyocyte stress responses, inflammation, or fibrotic remodelling, although whether such patterns are primary drivers or downstream markers of systemic disease remains to be determined. Nevertheless, the strong correlation of microbiota shifts with structural (e.g., LV mass), biochemical (NT-proBNP, troponin), and functional (6MWT) cardiac parameters across studies suggests that the gut microbiome could represent a relevant component of disease expression in cardiac amyloidosis and warrants further investigation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Immune, barrier, and cardiometabolic pathways\u003c/h2\u003e \u003cp\u003eThe interplay between the gut microbiota and host immunity is increasingly recognised as a key driver of systemic diseases, including cardiac conditions. In CA, where chronic inflammation and endothelial dysfunction contribute to myocardial vulnerability and fibrotic progression, microbiota-derived pathways may represent both upstream modulators and downstream amplifiers of disease activity. The findings from this review suggest distinct immunometabolic profiles across amyloidosis subtypes, with implications for both cardiac stress and systemic amyloidogenesis. For hereditary ATTRv, Chen et al. reported enrichment of \u003cem\u003eClostridia\u003c/em\u003e-class taxa, particularly \u003cem\u003eEubacterium oxidoreducens\u003c/em\u003e and \u003cem\u003eOscillibacter\u003c/em\u003e, in patients with a high cardiac amyloid burden. These taxa were inversely correlated with neuropathy severity, suggesting that their metabolites\u0026mdash;such as secondary bile acids or anti-inflammatory SCFAs\u0026mdash;may exert neuroprotective and potentially cardioprotective effects. In contrast, Rissato et al. reported that \u003cem\u003eStreptococcus\u003c/em\u003e and \u003cem\u003eHungatella\u003c/em\u003e, which are enriched in patients with cardiac involvement, were positively correlated with troponin I and BNP. These taxa have been previously linked to systemic inflammation and gut permeability, suggesting that they play a role in exacerbating myocardial stress through immune activation or microbial translocation [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe strongest evidence for gut barrier dysfunction and immune-metabolic disturbance emerged in AL amyloidosis. Yan et al. reported an increased abundance of \u003cem\u003eAkkermansia\u003c/em\u003e, a mucin-degrading genus associated with epithelial thinning, and depletion of \u003cem\u003eFaecalibacterium\u003c/em\u003e, a major SCFA producer known to support mucosal integrity. These changes are consistent with a loss of anti-inflammatory capacity and greater potential for systemic translocation of microbial products such as LPS or peptidoglycan [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Butyrate, produced by genera such as \u003cem\u003eFaecalibacterium\u003c/em\u003e, regulates tight junction integrity and suppresses proinflammatory cytokine expression via TLR signalling pathways [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Its loss could amplify low-grade inflammation and increase endothelial susceptibility to amyloid deposition. This gut\u0026ndash;cardiac axis is well established in other cardiovascular diseases. In heart failure, elevated plasma levels of TMAO\u0026mdash;a gut microbial metabolite of dietary choline and carnitine\u0026mdash;have been associated with vascular inflammation, myocardial fibrosis, and worse clinical outcomes [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. While TMAO was not evaluated in the studies included here, its mechanistic relevance supports the plausibility of microbiota-mediated pathways in CA. Additionally, microbial ligands such as LPS may activate Toll-like receptor 4 on cardiomyocytes, promoting profibrotic and apoptotic signalling cascades. These effects could converge with amyloid toxicity to accelerate cardiac dysfunction.\u003c/p\u003e \u003cp\u003eTaken together, the immunometabolic alterations associated with gut dysbiosis in CA\u0026mdash;particularly in AL\u0026mdash;suggest that microbial imbalance is not merely an epiphenomenon but may also contribute to disease progression via systemic inflammation, barrier failure, and cardiometabolic stress. Future studies should incorporate targeted measurements of immune and barrier markers, alongside microbiota and cardiac phenotyping, to delineate causal relationships and identify potential points of therapeutic intervention.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Clinical and Translational Implications\u003c/h2\u003e \u003cp\u003eThe emerging gut microbial signatures identified in patients with CA carry significant translational potential, particularly as non-invasive biomarkers and adjunctive therapeutic targets. Among the most compelling findings is the construction of a POD classifier by Yan et al., which is based on eight discriminatory genera. This model achieved an AUC of 0.95 and showed strong correlations with Mayo cardiac stage, NT-proBNP levels, and troponin T concentrations, highlighting its potential value in risk stratification for AL amyloidosis. While formal classifiers have not yet been developed for ATTRv, several microbial taxa have shown reproducible associations with clinically relevant phenotypes. For example, Intestinimonas was linked to cardiac mass and impaired six-minute walk test performance, whereas \u003cem\u003eLachnospiraceae UCG-003\u003c/em\u003e correlated with lower BNP and left atrial volume, suggesting potential utility in identifying more favourable cardiac remodelling phenotypes. These findings raise the possibility of using microbiota-based metrics to complement imaging and serum biomarkers in risk stratification, particularly in genotype-positive individuals with early or subclinical disease.\u003c/p\u003e \u003cp\u003eMicrobial profiling could also be integrated into longitudinal care, potentially serving as a tool to track disease progression or treatment response in patients receiving TTR stabilisers or immunosuppressive therapy. In ambiguous clinical scenarios, especially where cardiac involvement is uncertain, microbiota composition may increase diagnostic certainty when used alongside conventional parameters. Therapeutically, microbiota-targeted interventions\u0026mdash;such as dietary modulation, SCFA restoration, prebiotics, or faecal microbiota transplantation (FMT)\u0026mdash;could, in theory, modulate immune responses and restore gut barrier function. Although not yet trialled in amyloidosis, such approaches have shown efficacy in models of heart failure, atherosclerosis, and hypertension, where microbial manipulation reduces myocardial fibrosis, oxidative stress, and neurohormonal activation [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Given the parallels in endothelial dysfunction and systemic inflammation, these strategies warrant exploration in CA, beginning with mechanistic studies and preclinical models.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Limitations and Future Directions\u003c/h2\u003e \u003cp\u003eDespite promising associations between the gut microbiota and CA subtypes, the current evidence remains preliminary and should be interpreted with caution. All included studies were modest in scale, with sample sizes ranging from 27 to 39 participants, limiting their statistical power and precluding stratified analysis by clinically relevant variables such as genotype, disease stage, or treatment status. This is particularly important given the interpersonal variability of the gut microbiome and the heterogeneity of CA phenotypes.\u003c/p\u003e \u003cp\u003eGeographic and ethnic restrictions further limit generalisability. Each study was single-centre and conducted in East Asia or South America, with limited ethnic or dietary diversity. As the gut microbial composition is shaped by environmental, genetic, and cultural factors, replication in multiethnic, geographically diverse cohorts is essential to validate both taxonomic patterns and biomarker potential.\u003c/p\u003e \u003cp\u003eMethodological heterogeneity also complicates interpretation. Differences in 16S rRNA variable regions, sequencing platforms, bioinformatic pipelines, and statistical analysis frameworks reduce comparability across studies. None of the included investigations employed shotgun metagenomics, metabolomic profiling, or host\u0026ndash;microbiome integration, nor did they incorporate advanced cardiac phenotyping such as MRI or positron emission tomography -based amyloid quantification. This limits both mechanistic interpretation and clinical translatability.\u003c/p\u003e \u003cp\u003eCritically, all studies were cross-sectional and observational in design, precluding causal inference. Confounding variables such as diet, medications, and comorbidities likely influence gut microbial composition and may obscure true biological associations. The dynamic nature of the microbiome also demands longitudinal validation in ethnically and geographically diverse populations before clinical application. Without such longitudinal data, it remains unclear whether dysbiosis precedes cardiac involvement, evolves in parallel, or results from amyloid-induced systemic dysfunction.\u003c/p\u003e \u003cp\u003eIn summary, while preliminary, current evidence supports further investigation into the use of gut microbiota profiling for diagnostic augmentation, risk stratification, and potentially therapeutic modulation in cardiac amyloidosis. Future research must adopt prospective, multicentre designs with harmonised sequencing protocols and comprehensive cardiac phenotyping. Stratification by genotype, sex, and amyloid subtype will be key to uncovering clinically meaningful associations. Integration of microbiome data with host immune, proteomic, and imaging biomarkers will enable a systems-level understanding of gut\u0026ndash;heart interactions in CA. Experimental models\u0026mdash;including germ-free or humanised microbiota mice\u0026mdash;may also help clarify causal mechanisms and evaluate microbiota-targeted interventions before clinical translation.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis systematic review provides emerging evidence that the composition of the gut microbiota is altered in CA and may reflect, amplify, or modulate disease expression across subtypes. In ATTRv, distinct microbial profiles, particularly those involving \u003cem\u003eClostridia\u003c/em\u003e, \u003cem\u003eIntestinimonas\u003c/em\u003e, and \u003cem\u003eLachnospiraceae\u003c/em\u003e, appear to track cardiac remodelling and biomarker elevation, suggesting their relevance to myocardial strain and functional reserve. In AL amyloidosis, enrichment of \u003cem\u003eAkkermansia\u003c/em\u003e and depletion of \u003cem\u003eFaecalibacterium\u003c/em\u003e indicate that gut barrier dysfunction, systemic inflammation, and endothelial vulnerability are possible drivers of cardiac toxicity. These subtype-specific microbial patterns, and their associations with established cardiac biomarkers and structural indices, support the potential of the gut microbiome as a novel non-invasive tool for disease stratification, risk assessment, and monitoring. Moreover, the integration of microbial data into personalised care models could complement current diagnostic and therapeutic strategies, especially in genotype-positive or early-stage cases.\u003c/p\u003e \u003cp\u003eNonetheless, the current literature is limited by small sample sizes, methodological heterogeneity, and a lack of longitudinal or mechanistic studies. Future research should focus on validating these findings in larger, multiethnic cohorts, applying harmonised metagenomic pipelines, and incorporating host transcriptomic, immunologic, and imaging markers. Experimental studies in preclinical amyloidosis models will be critical to establishing causality and testing the feasibility of microbiota-targeted interventions.\u003c/p\u003e \u003cp\u003eOverall, the gut\u0026ndash;heart axis represents a promising and underexplored frontier in the pathophysiology and clinical management of cardiac amyloidosis. As the field advances, multidisciplinary research integrating cardiology, immunology, and microbiology will be key to translating these insights into therapeutic impact.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eAL\u003c/strong\u003e: Light-chain amyloidosis\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eASV\u003c/strong\u003e: Amplicon sequence variant\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eATTR\u003c/strong\u003e: Transthyretin amyloidosis\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eATTRv\u003c/strong\u003e: Hereditary transthyretin amyloidosis\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eATTRwt\u003c/strong\u003e: Wild-type transthyretin amyloidosis\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAUC\u003c/strong\u003e: Area under the curve\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eBNP\u003c/strong\u003e: B-type natriuretic peptide\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eCA\u003c/strong\u003e: Cardiac amyloidosis\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ecTnT\u003c/strong\u003e: Cardiac troponin T\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eHFpEF\u003c/strong\u003e: Heart failure with preserved ejection fraction\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eNT-proBNP\u003c/strong\u003e: N-terminal pro–B-type natriuretic peptide\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ePOD\u003c/strong\u003e: Probability of disease\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003erRNA\u003c/strong\u003e: Ribosomal ribonucleic acid\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eSCFA\u003c/strong\u003e: Short-chain fatty acid\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eSPECT\u003c/strong\u003e: Single-photon emission computed tomography\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eTMAO\u003c/strong\u003e: Trimethylamine-N-oxide\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eTLR\u003c/strong\u003e: Toll-like receptor\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eVS\u003c/strong\u003e: Visual score\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthics approval was waived, as this study was a systematic review of previously published studies and did not involve direct human or animal research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData sharing is not applicable to this article, as no new datasets were generated or analysed during the current study. All the data analysed during this study are included in this published article and its referenced source materials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors received no specific funding for this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eT.B. conceived the study, designed the review protocol, performed the literature search, conducted the data analysis, and drafted the manuscript. Z.N. and D.W. contributed as second authors by performing data extraction, proofreading the manuscript, and independently reviewing and verifying the extracted data. All the authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eKittleson MM, Maurer MS, Ambardekar AV, et al. Cardiac amyloidosis: evolving diagnosis and management: a scientific statement from the American Heart Association. Circulation. 2020;142(1):e7\u0026ndash;e22.\u003c/li\u003e\n \u003cli\u003eFalk RH, Alexander KM, Liao R, Dorbala S. AL (light-chain) cardiac amyloidosis: a review of diagnosis and therapy. J Am Coll Cardiol. 2016;68(12):1323\u0026ndash;1341.\u003c/li\u003e\n \u003cli\u003eDispenzieri A, Gertz MA, Kyle RA, et al. Serum cardiac troponins and N-terminal pro\u0026ndash;brain natriuretic peptide: a staging system for primary systemic amyloidosis. J Clin Oncol. 2004;22(18):3751\u0026ndash;3757.\u003c/li\u003e\n \u003cli\u003eRuberg FL, Berk JL. 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Front Immunol. 2022;13:973760. https://doi.org/10.3389/fimmu.2022.973760\u003c/li\u003e\n \u003cli\u003eKarlsson FH, Tremaroli V, Nookaew I, et al. Gut metagenome in European women with normal, impaired and diabetic glucose control. Nature. 2013;498(7452):99\u0026ndash;103.\u003c/li\u003e\n \u003cli\u003eEverard A, Belzer C, Geurts L, et al. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity. Proc Natl Acad Sci U S A. 2013;110(22):9066\u0026ndash;9071.\u003c/li\u003e\n \u003cli\u003eFurusawa Y, Obata Y, Fukuda S, et al. Commensal microbe-derived butyrate induces the differentiation of colonic regulatory T cells. Nature. 2013;504(7480):446\u0026ndash;450.\u003c/li\u003e\n \u003cli\u003eTang WHW, Wang Z, Levison BS, et al. Intestinal microbial metabolism of phosphatidylcholine and cardiovascular risk. N Engl J Med. 2013;368(17):1575\u0026ndash;1584.\u003c/li\u003e\n \u003cli\u003eLau E, Carvalho D, Freitas P. Gut microbiota: Association with NAFLD and metabolic disturbances. Biomedicines. 2017;5(3):48.\u003c/li\u003e\n \u003cli\u003eMarques FZ, Nelson E, Chu PY, et al. High-fibre diet and acetate supplementation change the gut microbiota and prevent the development of hypertension and heart failure in DOCA-salt hypertensive mice. Circulation. 2018;137(9):964\u0026ndash;977.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Cardiac amyloidosis, gut microbiota, ATTRv, AL amyloidosis, dysbiosis, heart failure, NT-proBNP, microbial biomarkers, systemic inflammation, gut–heart axis","lastPublishedDoi":"10.21203/rs.3.rs-6638994/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6638994/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCardiac amyloidosis is an underdiagnosed infiltrative cardiomyopathy caused by the extracellular deposition of misfolded proteins. The two principal subtypes\u0026mdash;light-chain (AL) amyloidosis and transthyretin (ATTR) amyloidosis\u0026mdash;differ in pathogenesis and clinical course. Growing evidence implicates the gut microbiota in cardiovascular diseases through immune, inflammatory, and metabolic pathways. However, its potential role in cardiac amyloidosis remains unexplored.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis systematic review was conducted in accordance with the PRISMA 2020 and PRISMA-S guidelines. A comprehensive search of PubMed, EMBASE, and Web of Science was performed from inception to April 2025. Eligible studies included original human research evaluating the gut microbiota in the context of AL or ATTR cardiac amyloidosis via validated molecular techniques such as 16S rRNA sequencing. Titles, abstracts, and full texts were screened by two reviewers, and key variables were extracted and synthesised narratively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThree studies met the inclusion criteria. In a case\u0026ndash;control study of hereditary ATTR (ATTRv), patients presented increased microbial α diversity and enrichment of Clostridia-class taxa, particularly those with increased myocardial amyloid burden. A cross-sectional study of ATTRv patients carrying the V142I mutation revealed that Streptococcus and Hungatella were associated with elevated cardiac biomarkers, whereas Intestinimonas was linked to increased left ventricular mass and impaired physical performance. Conversely, in AL amyloidosis, patients showed enrichment of Akkermansia and Bifidobacterium alongside depletion of Faecalibacterium\u0026mdash;microbial signatures suggestive of impaired gut barrier integrity and systemic inflammation. A machine learning classifier based on gut microbial taxa achieved a diagnostic accuracy with an AUC of 0.95 in distinguishing AL patients from controls. Across studies, specific genera correlated with cardiac markers such as NT-proBNP, troponin, and left atrial volume.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDespite limited sample sizes and methodological heterogeneity, current evidence supports a potential link between gut dysbiosis and cardiac amyloidosis. Microbial signatures may serve as non-invasive biomarkers of disease severity and progression. Further research in larger, multiethnic, and longitudinal cohorts is warranted to validate these associations and explore their therapeutic implications.\u003c/p\u003e","manuscriptTitle":"Unveiling the Gut–Heart Axis in Cardiac Amyloidosis: A Systematic Review of Emerging Evidence","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-14 09:26:53","doi":"10.21203/rs.3.rs-6638994/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e745ebdf-fcbd-443b-bbe1-2b089c97a842","owner":[],"postedDate":"May 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-14T09:26:54+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-14 09:26:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6638994","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6638994","identity":"rs-6638994","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}