HSP and ITP are characterized by purpura, resulting from small blood vessel bleeding into the skin and mucous membranes (Rodeghiero et al., 2009; Hetland et al., 2017). HSP, also known as IgA vasculitis, presents as a systemic vasculitis with palpable purpura, arthritis, gastrointestinal symptoms, and kidney involvement, while ITP manifests as thrombocytopenia due to immune-mediated platelet destruction, predisposing individuals to bleeding (Piel-Julian et al., 2018; Hahn et al., 2023). Despite their distinct clinical presentations, both disorders share common immunopathogenic mechanisms, hinting at potential etiological similarities (Zufferey et al., 2017). Children affected by HSP and ITP endure significant morbidity, including physical suffering and treatment-related adverse effects such as corticosteroid-induced weight gain and mood changes, which can cause psychological distress and impair overall health and quality of life (Kühne et al., 2003; Terrell et al., 2010; Weiss et al., 2010).

The human gut microbiota, which comprises a vast number of microorganisms residing in the gastrointestinal tract, is essential for supporting the immune system and metabolic balance in the host (Postler and Ghosh, 2017). Dysbiosis, or alterations in gut microbiota composition and function, has been implicated in various immune-mediated disorders, including HSP and ITP (Arrieta et al., 2014). Observational studies indicate a potential association between gut microbiota and HSP and ITP. For instance, Wang et al. (2018) found a significant negative association between IgA levels and Bifidobacterium in HSP children. Zhang et al. (2021) found that Escherichia Shigella has diagnostic value for HSP recurrence. Li et al. (2022) found that Proteobacteria and Actinobacteria are associated with organ involvement in HSP. In addition, Borody et al. (2011) reported a case of an ITP patient whose platelet levels returned to normal after receiving fecal microbiota transplantation. Further research on the gut microbiome could potentially aid in the management and therapy of HSP and ITP. However, establishing causality in such studies is challenging due to confounding factors and the potential for reverse causation (Rinninella et al., 2019).

MR offers a robust methodological approach to infer causal relationships and reduce confounding and reverse causation biases by utilizing genetic variants as instrumental variables (IVs), which are randomly allocated at conception and remain unchanged throughout life (Davies et al., 2018). To achieve valid results, MR analysis needs to satisfy three core IVs assumptions: (I) Relevance assumption: Genetic variations are closely associated with the exposure factor; (II) Independence assumption: Genetic variations are independent of any known or unknown confounding factors; (III) Exclusion restriction assumption: Genetic variations only affect the outcome through the exposure factor and not through any other direct causal pathways (Davey Smith and Hemani, 2014). In this study, we aim to investigate the bidirectional causal relationship between gut microbiota and HSP and ITP using a two-sample MR method. By integrating large-scale genetic data and summary statistics from GWAS of gut microbiota composition and HSP and ITP susceptibility, we will assess whether genetic predisposition to gut microbiota dysbiosis influences the risk of HSP and ITP, and conversely, whether genetic susceptibility to HSP and ITP impacts gut microbiota composition.

This study comprehensively evaluates the causal relationship between gut microbiota and two autoimmune diseases (HSP and ITP) from the perspective of genetic variation using a two-sample MR approach. Indeed, previous MR studies have extensively explored the relationship between the gut microbiota and autoimmune diseases such as type 1 diabetes, multiple sclerosis, Sjögren syndrome, systemic lupus erythematosus and inflammatory bowel disease (Liu et al., 2022; Xu et al., 2022; Cao et al., 2023; Luo et al., 2023). MR estimates revealed suggestive associations between specific bacterial taxa and HSP, specifically, Defluviitaleaceae, genus Defluviitaleaceae UCG01, genus Escherichia Shigella, genus Family XIII AD3011 group, genus Roseburia and species Bilophila wadsworthia are suggestively associated with increased risk of HSP, whereas genus Prevotella9, species Gordonibacter pamelaeae, species Clostridium asparagiforme and species Coprococcus comes are suggestively protective against HSP. Similarly, MR analysis demonstrated that family Alcaligenaceae and family Bacteroidales S24 7group had significant associations with ITP after strict correction, with the former acting as a risk factor and the latter as a protective factor. In addition, genus Allisonella, genus Coprococcus2, genus Eubacterium hallii group, genus Eubacterium ruminantium group, species Dialister invisus, species Bilophila unclassified, species Haemophilus parainfluenzae, species Bacteroides finegoldii and species Dorea unclassified had suggestive protective effects on ITP, while genus Escherichia Shigella and species Odoribacter splanchnicus had suggestive risk effects on ITP. It is worth noting that for the two significant associations mentioned above, the statistical power is 100 and 65%, respectively, indicating robust statistical significance at the 0.05 p-value threshold.

In addition to establishing the causal links between gut microbiota composition and HSP and ITP, it is imperative to explore the potential mechanisms whereby the gut microbiota affects these autoimmune disorders. The gut microbiota is involved in shaping host immune responses and maintaining immune homeostasis through various mechanisms, including modulation of the intestinal barrier function, production of metabolites, and interaction with the host immune system (Belkaid and Hand, 2014; Rooks and Garrett, 2016). Alterations in composition and function of gut microbiota can dysregulate these regulatory mechanisms, leading to aberrant immune activation and autoimmunity (Wu and Wu, 2012; Manfredo Vieira et al., 2018). One potential mechanism by which the gut microbiota may contribute to the pathogenesis of HSP and ITP is through the modulation of mucosal barrier integrity (Saps et al., 2010). Intestinal epithelial cells create a physical barrier that separates luminal contents, including commensal microbes, from the underlying immune cells in the gut-associated lymphoid tissue (Abraham and Medzhitov, 2011). Dysbiosis-induced impairment of the intestinal barrier can lead to increased permeability, allowing translocation of microbial products and activation of mucosal immune responses (Buford et al., 2018). This chronic mucosal inflammation may promote systemic immune dysregulation and contribute to the development of autoimmune diseases such as HSP and ITP. Moreover, the gut microbiota plays a vital role in producing various metabolites, such as short-chain fatty acids (SCFAs), bile acids, and secondary metabolites derived from dietary components. These microbial metabolites can function as signaling molecules that regulate host immune function and inflammatory responses. SCFAs, mainly produced by gut bacteria through the fermentation of dietary fiber, have been demonstrated to have anti-inflammatory properties by promoting regulatory T cell differentiation and inhibiting pro-inflammatory cytokine production (den Besten et al., 2013; Park et al., 2015; Tan et al., 2016). Dysbiosis-induced changes in SCFA production may disrupt immune tolerance and promote autoimmune pathology in HSP and ITP. Specific bacterial taxa in the gut microbiota may interact directly with the host immune system, either by eliciting immune responses or by influencing immune cell development and function (Zhang et al., 2017). Certain pathogenic bacteria, such as Escherichia coli and Shigella species, have been linked to the development of autoimmune diseases through molecular mimicry. This occurs when microbial antigens resemble host antigens, leading to cross-reactive immune responses. In contrast, commensal bacteria, such as those found in the Clostridiales order, have been demonstrated to stimulate the production of regulatory T cells and promote immune tolerance, thereby providing protection against autoimmunity (Tremlett and Waubant, 2018; Zitvogel et al., 2018). It should be noted that the gut microbiota can also affect systemic inflammation and coagulation pathways, which may contribute to the vascular and hematological manifestations observed in HSP and ITP (Wang et al., 2021). Dysbiosis-induced inflammation and endothelial dysfunction may enhance platelet activation and aggregation, leading to purpura and thrombocytopenia, which are characteristic of HSP and ITP.

The gut microbiota has a multifaceted impact on host immunity and inflammatory pathways, influencing the pathogenesis of autoimmune diseases such as HSP and ITP (Aminov et al., 2006). Findings from this study suggest that specific gut microbiota compositions are associated with HSP and ITP. For instance, the family Alcaligenaceae has been identified as a risk factor for ITP, while the family Bacteroidales S24 7group appears to be a protective factor. These insights can inform the development of microbiota-based diagnostics, enabling earlier detection and intervention in clinical settings.

Leveraging the causal relationships established in this study, clinicians could adopt microbiota-targeted therapies, such as probiotics, prebiotics, or fecal microbiota transplantation, as part of a comprehensive treatment plan for patients with HSP and ITP. This approach could help in modulating the immune response, reducing inflammation, and potentially restoring immune balance more rapidly than current treatments, which primarily focus on symptom management rather than addressing underlying causes.

A recent study by Jiang et al. (2024) preliminarily explored the causal relationship between gut microbiota and HSP and ITP using MR. However, this study has several significant differences and advantages. First, in terms of data sources, the gut microbiota involved in this study was more comprehensive, covering the species level, and the R10 database had a larger sample size and more SNPs. More importantly, there is a significant discrepancy between the results of the two studies, which may be precisely the consequence of different data sources. IVs are crucial in MR analyses, and therefore MR estimates obtained by analyzing more recent and larger databases tend to be more representative of potential causal associations. Second, the positive results were supported by at least three powerful MR methods (IVW, ML, cML-MA) and met the criteria for Bonferroni correction. These measures reduced the likelihood of false-positive results and increased robustness. This study also has limitations. The genetic makeup of European populations differs from that of other ancestries. This lack of diversity can result in findings that are not generalizable to other populations. There are known geographical differences in gut microbiota composition due to diet, lifestyle, and other environmental factors. Findings based on European populations might not apply to other regions with different microbiota profiles. Differences in ancestry can lead to population stratification, which can confound the results if not properly adjusted for in the analysis. Factors such as age, body mass index, diet, and lifestyle are critical confounders in studies of gut microbiota. While MR aims to reduce these biases, complete control over all confounding factors is challenging. It is crucial for future studies to include more diverse populations to enhance the generalizability of the results.

Our study identified suggestive causal effects of gut microbiota on HSP and ITP. Particularly, family Alcaligenaceae and family Bacteroidales S24 7group have a significant association with ITP after Bonferroni correction. Further research using advanced molecular and immunological techniques is necessary to understand the complex interactions between the gut microbiota, host immune system, and autoimmune pathogenesis in HSP and ITP.

Publicly available datasets were analyzed in this study. GWAS summary statistics for mbQTLs are available at www.mibiogen.org. The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author/s.

JiawL: Writing – review & editing, Writing – original draft, Methodology, Formal analysis, Data curation, Conceptualization. JiaL: Writing – review & editing, Writing – original draft, Software, Investigation, Formal analysis. YuxL: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision. JZ: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision. YuaL: Writing – review & editing, Writing – original draft, Resources, Project administration. YW: Writing – review & editing, Writing – original draft, Resources, Project administration, Funding acquisition.