Cross-country multi-modal evidence links Aspergillus to biliary atresia
Song-Wei Huang, Chia-Ray Lin, Ya-Hui Chang, Yen-Hsuan Ni, Huey-Ling Chen, Hong-Hsing Liu
TL;DR
This study suggests a possible link between gut fungi, specifically Aspergillus, and biliary atresia in infants, based on multi-country data and case evidence.
Contribution
The study presents cross-country multi-modal evidence linking Aspergillus in the gut to biliary atresia, a novel hypothesis in pediatric liver disease.
Findings
Gut Aspergillus was detected only in biliary atresia cases, suggesting it may be a trigger.
BA incidence correlated with Aspergillus infections in the UK, Taiwan, and Japan.
Antifungal treatment resolved cholangitis in a BA case, supporting the hypothesis.
Abstract
Biliary atresia (BA) is the leading cause of pediatric liver transplantation. It is characterized by progressive extrahepatic bile duct obstruction in young infants. Inspired by the success of antifungal treatment in a newborn with BA-related obstructive cholangitis, we explored a potential link between BA and fungi, particularly Aspergillus. Fecal DNA was analyzed using 18S ribosomal sequencing and validated with a published fecal metagenomic dataset. Epidemiological data from the UK, Taiwan, and Japan were also examined. Gut Aspergillus was exclusively detected in BA cases, suggesting it may be a potential trigger. Independent fecal metagenomic data from China and epidemiological correlations further supported this hypothesis. In the UK, BA presentations strongly correlated (r = 0.98, 95% CI [0.36, 1.0], p = 0.02) with Aspergillosis, but not with Candidiasis, during the COVID-19…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
Click any figure to enlarge with its caption.
Figure 1
Figure 2
Figure 3Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsGallbladder and Bile Duct Disorders · Pediatric Hepatobiliary Diseases and Treatments · Liver Diseases and Immunity
Introduction
Biliary atresia (BA) is a disease characterized by extrahepatic bile duct obliteration in young infants. It occurs either as an isolated form or as part of a syndrome, sometimes accompanied by laterality defects [1]. The syndromic form is far less common, and this study primarily focuses on the isolated form. Affected infants are typically asymptomatic at birth but develop signs such as prolonged jaundice and acholic stool between two and six weeks of age. Kasai portoenterostomy, which reroutes bile flow from the intrahepatic ducts to the intestine, remains the standard first-line treatment for BA [2]. Nevertheless, up to two-thirds of patients eventually require liver transplantation due to progressive bile duct obstruction and end-stage liver cirrhosis [3].
Multiple genetic factors have been linked to BA, including genes related to ciliopathy and hepatobiliary development, as well as those involved in inflammation and fibrogenesis [4]. A distinct BA variant has recently been identified in patients with null mutations of GSTM1, resulting in impaired detoxification of fungal aflatoxins [5]. Viral pathogens [6, 7] and plant toxins [8] have also been proposed as potential triggers. In summary, BA development likely involves multiple factors, potentially including environmental triggers and subsequent immune dysregulation in susceptible infants. Here, we provide evidence that gut Aspergillus spp. may serve as a distinctive trigger for BA, based on sequences identified in our cases and in an independent dataset of fecal shotgun metagenomes, where Aspergillus showed the largest mean difference between BA and controls among fungi with significant differences. Furthermore, correlations between BA occurrences and the clinical burdens of Aspergillus spp. observed in the UK, Taiwan, and Japan further support this hypothesis.
Methods
Aim, design, and setting of the study
Prompted by a clinical case in which antifungal therapy improved neonatal cholangitis, we investigated a potential association between gut fungal colonization, particularly by Aspergillus spp., and the development of BA in infants. We employed a comprehensive approach that integrated clinical case reviews, molecular sequencing, and validation using a publicly available fecal metagenomic dataset. Clinical samples were analyzed from two hospitals in Taiwan: National Taiwan University Children’s Hospital and En Chu Kong Hospital. Participant demographics and diagnostic information are summarized in Table 1. To further support our findings and assess environmental fungal exposure, we performed epidemiological analyses across Taiwan, the United Kingdom, and Japan.Table 1BLAST hits of nested 18S V7–V8 or V4–V8 sequencesSample^^^Age(mo)DiagnosisV7–V8 hits^^V4–V8 hits^^Fungi^†^D280.9CholangitisAspergillus spp.Aspergillus spp.Penicillium limosum**Penicillium spp.UD311.0CholangitisNo PCR bandsNo PCR bandsND381.3CholangitisNo PCR bandsGorilla gorilla**Pan troglodytesNBA011.7Biliary AtresiaCerrena spp.Cerrena spp.Cerrena spp.Cerrena spp.UBA021.1Biliary AtresiaNo PCR bandsNo PCR bandsNBA032.4Biliary AtresiaUncultured fungusCandida parapsilosisCandida parapsilosisCandida metapsilosisCBA043.9Biliary AtresiaNo PCR bandsHomo sapiens**Gorilla gorillaNBA050.6Biliary AtresiaAspergillus spp.Aspergillus spp.Aspergillus restrictus**Aspergillus cristatusUBA060.7Biliary AtresiaPCR bands not clonedHydnochaete duportii(4)**Phellinidium pouzarii(3)Uncultured fungus(3)**Aspergillus penicillioides(2)**Aspergillus flavus(1)Fungal spp.(1)Trichaptum abietinum(1)Skvortzovia pinicola(1)UBA071.3Biliary AtresiaNo PCR bandsNo PCR bandsNBA081.4Biliary AtresiaNo PCR bandsNo PCR bandsNBA092.2Biliary AtresiaNo PCR bandsNo PCR bandsNBA100.5Biliary AtresiaNo PCR bandsNo PCR bandsNControl011.0NormalNo PCR bandsNo PCR bandsNControl021.0NormalNo PCR bandsNo PCR bandsNControl032.0NormalUncultured fungusCandida parapsilosisCandida parapsilosisCandida metapsilosisCControl042.0NormalNo PCR bandsNo PCR bandsNControl051.0NormalCandida albicansCandida albicansCandida albicans**Candida albicansCControl062.0NormalCandida albicansCandida albicansCandida albicans**Candida albicansCControl071.0NormalUncultured fungusCandida parapsilosisCandida parapsilosisCandida metapsilosisCControl082.0NormalMalassezia furfurMalassezia furfurMalassezia furfur**Malassezia furfurCControl092.05β-Reductase DeficiencyUncultured fungusUncultured fungusGorilla gorilla**Kogia brevicepsNControl101.1Disorder of Bilirubin MetabolismNo PCR bandsNo PCR bandsNControl111.6CMV^‡^ InfectionNo PCR bandsPan paniscus**Pan troglodytesNControl122.3NICCD^‡^Uncultured fungusMalassezia arunalokeiUncultured fungusSelenicereus undatusCControl132.7Choledochal CystUncultured* MalasseziaMalassezia pachydermatisPan troglodytes**Pan troglodytesC^^^BA samples were collected prior to Kasai portoenterostomy.^^First and second hits against the NCBI nr/nt database are presented. For BA06, results are based on eight V4–V8 PCR clones, with hit counts shown in parentheses.^†^Fungal status designations for each sample: U = non-commensal fungi, C = commensal fungi, N = no PCR bands.^‡^CMV, cytomegalovirus; NICCD, neonatal intrahepatic cholestasis caused by citrin deficiency.
Molecular biology experiments
Detailed protocols for fecal DNA extraction, 16S/18S PCR, Sanger sequencing, and TA cloning are provided in the Supplementary Methods (Additional file 1).
Bioinformatic analyses
Sanger sequencing results were processed in SnapGene (Dotmatics, Boston, MA, USA; www.snapgene.com) for visualization and editing. Taxonomic identities were assigned through nucleotide BLAST [9] searches against the NCBI nr/nt database [10] using the NCBI web server. Data visualization was performed in the Python library seaborn [11]. For fungal taxonomic profiling, Kraken 2 [12] was employed. From each sample, 2 million sequence reads were randomly selected, and analyses were repeated five times. The averaged output from these replicates, totaling 10 million reads, was used to represent each sample. Forward and reverse reads were processed separately to ensure consistency and coverage.
Estimations of fungal burdens from published data
To estimate case numbers from published figures, Fig. 1 in Sung et al. [13] was digitally enlarged by approximately 330%, establishing a visual scale in which 5 cm represented 300 cases of Aspergillosis and 4 cm represented 100 cases of Candidiasis. The vertical heights of plotted data points, corresponding to monthly data from March to June across 2018–2021, were measured manually with a ruler. Similarly, incidence estimates for Aspergillus spp. were derived from Fig. 1 in Hsiue et al. [14], where 1 mm equaled 1 case per 1,000 hospital admissions and 5.3 cm represented 20% of total cancer admissions. To ensure reproducibility and minimize measurement bias, manual measurements were independently repeated by five additional individuals, including three non-authors, each using randomly adjusted image scales. Correlation coefficients showed excellent consistency across raters: UK-Aspergillus (mean r = 0.985, standard deviation [SD] = 0.002, coefficient of variation [CV] = 0.2%), UK-Candida (mean r = 0.55, SD = 0.028, CV = 5.2%), and TW-Aspergillus (mean r = 0.77, SD = 0.019, CV = 2.5%). Here, SD represents the dispersion of values around the mean, and CV (SD ÷ mean × 100%) indicates relative variability. These results demonstrate that the manual measurement approach is highly reproducible (Fig 3 and Figure S2, Additional file 1). For Japan, incidence data were extracted from published tables by Kume et al. [15] and Suzuki et al. [16], and directly retrieved from the Japanese Biliary Atresia Registry (https://jbas.net/registration-historicaldata).Fig. 1. Clinical presentation of the index cholangitis case. (A) Platelet and WBC profiles differed between the early gastroenteritis phase (D8–D11) and the later cholangitis phase (D27–D40), with high and low C-reactive protein (CRP) values, respectively. Shaded areas along WBC trajectories indicate eosinophil counts. (B) Blood bilirubin and γ-GT levels declined following fluconazole treatment. (C) Perianal dermatophytosis initially coincided with acholic stool. Sequential stool phenotypes and abdominal ultrasonography demonstrated resolution of bile duct obstruction
Statistics
Statistical analyses were performed to assess associations and differences between groups. Fisher’s exact test was used to evaluate the presence of non-commensal fungi uniquely detected in cases compared with controls. Correlation analyses were conducted using the pearsonr function in SciPy [17], with Pearson’s r, 95% confidence intervals, and p-values reported. Regression plots display analytically calculated 95% confidence bands around the fitted line. Differences in fungal genus abundance between groups were assessed using Student’s t-test (two-sample, equal variances), with mean differences (Δ), 95% confidence intervals, and p-values reported. A two-sided p < 0.05 was considered statistically significant. All analyses and visualizations were performed in Python using NumPy, SciPy, pandas, seaborn, and matplotlib.
No a priori sample size or power calculations were performed due to the opportunistic, retrospective design. To guide prospective validation, we estimated required sample sizes from both observed and conservative effect sizes. For prevalence analyses of non-commensal fungi, planning around an absolute difference of 20–30% between BA and controls suggested that approximately 12–19 participants per group would be sufficient at 80% power and α = 0.05 (two-sample proportion test, assuming near-zero prevalence in controls). On a more conservative basis, allowing for a small background prevalence in controls and other planning safeguards, larger samples of approximately 22–36 per group may be advisable. For correlation analyses of annual BA incidence against Aspergillus burden, the observed effects (r ≈ 0.78–0.98 across countries) implied that ~8–11 annual observations would be sufficient for 80% power. Using a conservative target based on two standard deviations below the cross-country mean (r ≈ 0.67) required ~16 observations, while planning for a more moderate correlation (r ≈ 0.5) would necessitate ~30 observations. These estimates are intended to guide prospective confirmation and do not alter the exploratory nature of the present work.
Results
Fungicidal treatment for neonatal cholangitis
A male newborn was delivered via cesarean section at 39 weeks of gestation due to fetal distress. The infant experienced cardiac arrest and exhibited thick meconium staining at birth but was successfully resuscitated and transferred to the Neonatal Intensive Care Unit. Severe hypoglycemia (blood glucose < 2 mg/dL) was detected on admission. Continuous infusion of 10% glucose via peripheral lines only barely maintained blood glucose levels. Because central lines were unavailable, early oral feeding with 50% concentrated glucose solution was initiated on day 1 (D1) and continued for one week. Insulin and cortisol responses were within normal ranges on D3, and glucose levels were mostly maintained above 40 mg/dL thereafter, with exceptions on D8 (14 mg/dL) and D25 (39 mg/dL). No metabolic acidosis was observed. Alanine aminotransferase was elevated on D1 (389 IU/L) but returned to near-normal levels by D8 (44 IU/L). The patient’s vital signs remained stable, and no neurological complications were noted.
However, ileus developed later in spite of full antibiotic coverage. Severe thrombocytopenia was observed on D8 and D11, while white blood cell (WBC) counts remained normal (Fig. 1A). A fungal infection was suspected, and intravenous (IV) fluconazole was initiated on D11. Clinical improvement was immediate, and fluconazole was discontinued on D19. However, leukocytosis developed (20,400/μL on D15; 28,300/μL on D19), prompting another course of IV antibiotics (D19–D26), which did not improve clinical parameters (D27, Fig. 1A).
During this period, eosinophilia (D27–D30; shades of WBC, Fig. 1A) and direct hyperbilirubinemia with elevated gamma-glutamyltransferase (γ-GT) were noted (D27, Fig. 1B). The patient also developed perianal dermatophytosis that responded to topical clotrimazole, along with the presence of light-colored stool (D26, Fig. 1C). Suspecting fungal cholangitis, IV amphotericin B was given from D27 to D29 (Fig. 1B). Because bilirubin levels did not improve, antifungal therapy was switched to oral fluconazole on D30 (Fig. 1B). Interestingly, stool color normalized the following day (D31, Fig. 1C), with sustained improvement thereafter (D38, Fig. 1C). Hyperbilirubinemia gradually resolved (Fig. 1B), and abdominal ultrasound revealed a well-distended gallbladder without bile duct obstruction (D40, Fig. 1C).
The patient was discharged on D41 while continuing oral fluconazole. Follow-up monitoring of blood counts, bilirubin, and γ-GT values remained normal (D55–D108, Fig. 1A–B). Oral fluconazole was tapered and discontinued. At two and a half years of age, the most recent evaluation showed that the child had normal growth and development.
Non-commensal fungi in the bowel
Fungal cultures of blood and stool samples collected during hospitalization were all negative. We used fungal ribosomal 18S PCR [18, 19] to assess suspected fungal colonization from fecal DNA, with bacterial 16S V1–V9 PCR [19] as an internal control (Figure S1A, Additional File 1). A clear 18S V1–V8 band was amplified from the D28 fecal sample (Figure S1A, Additional File 1), despite IV amphotericin B administration from D27 to D29 (Fig. 1B). This V1–V8 band was no longer detectable on D31 and D38 following the start of oral fluconazole on D30 (Fig. 1B). PCR products from the V1–V8 region were further amplified for V7–V8 taxonomic classification by semi-nested PCR (red arrow, Figure S1A, Additional File 1). Sequencing identified Aspergillus spp. by nucleotide BLAST against the nr/nt database (Table 1; Figure S1B, Additional File 1).
Aspergillus spp. is not considered a typical commensal fungus of the gastrointestinal tract [20]. We hypothesized that BA, a disease often preceded by obstructive cholangitis, might also be associated with colonization by unusual fungi in the bowel. To test this, we examined archived fecal DNA from five BA cases and four healthy controls using 18S V1–V8 and semi-nested V7–V8 PCR (Figure S1C, Additional File 1). Four samples (BA01, BA03, BA05, and Control03) yielded positive results (Table 1; Figure S1C, red arrow, Additional File 1). Sequences from BA01 mapped to Cerrena spp. (Figure S1D, Additional File 1), while Aspergillus spp. was also identified in BA05. Control03 and BA03 were associated with Candida. Because both the cholangitis case and BA05 were linked to bowel colonization by Aspergillus spp., we aligned their 18S V7–V8 sequences. At least two loci showed distinct T vs. C nucleotide polymorphisms (red arrow, Figure S1E, Additional File 1), suggesting that the two patients were colonized by different Aspergillus species.
We expanded our investigation of fecal 18S sequences using semi-nested V4–V8 PCR. Five additional BA samples (BA06–BA10, Table 1), four normal controls (Control05–Control08, Table 1), and five cholestatic disease controls (Control09–Control13, Table 1) were included. Due to sequence heterogeneity in BA06, PCR products were cloned before Sanger sequencing. BLAST analysis revealed multiple fungi in BA06, including Aspergillus spp. (BA06, Table 1). Using the longer sequence span from V4–V8 PCR, the D28 sample from the index cholangitis patient mapped to Penicillium spp. (D28, Table 1), which is taxonomically related to Aspergillus spp. [21]. Among the four additional normal controls and five cholestatic controls, three yielded sequences from Candida and three from Malassezia (Control05–Control13, Table 1). In summary, three of ten BA samples contained non-commensal fungi, whereas none of the controls did (Table 1). Patients with BA or cholangitis were therefore significantly more likely to harbor non-commensal fungi than controls (Fisher’s exact test, p = 0.0311), with Aspergillus spp. detected repeatedly.
Confirmation of Aspergillus spp. in BA using public shotgun metagenomes
Building on these findings, we anticipated an expansion of Aspergillus populations, particularly in older BA cases. To validate this, we analyzed a publicly available dataset of fecal shotgun metagenomes from Song et al. [22], which revealed an unusual enrichment of Aspergillus in BA. The dataset comprised 16 BA cases and 10 matched controls, with half of the BA patients having undergone Kasai portoenterostomy. For each sample, two million forward reads were randomly selected for fungal taxonomic classification using Kraken 2 [12]. Five replicate subsamples were analyzed, totaling ten million reads per sample, and the average genus-level fungal abundance was used for comparisons.
In the forward reads, total fungal counts were comparable (p = 0.672) between BA (3543.5 ± 828.7 per two million reads, standard error [SE]) and controls (2983.6 ± 987.3 per two million reads, SE). Five genera were significantly more abundant in BA: Aspergillus, Kluyveromyces, Marasmius, Metarhizium, and Lachancea (Fig. 2A). In the reverse reads, four of these genera overlapped (Aspergillus, Kluyveromyces, Marasmius, and Metarhizium) (Fig. 2B). In both analyses, Aspergillus showed the largest mean difference between BA and controls, with nearly identical abundance distributions across read directions. For each comparison, mean differences (Δ) and 95% confidence intervals are displayed in the figure.Fig. 2. Fungal genera significantly enriched in BA. (A) Forward-read analysis. Each point represents the average of five replicates, each derived from two million randomly selected fecal shotgun metagenome reads. Jittered points are overlaid on violin plots for BA and control groups. Only genera with significantly higher abundance in BA are shown; Aspergillus spp. exhibited the largest mean difference (Δ). (B) Reverse-read analysis. A similar approach identified four overlapping genera (Aspergillus, Kluyveromyces, Marasmius, and Metarhizium). In both orientations, Aspergillus spp. showed the largest mean difference, with comparable distribution profiles. For all comparisons, mean differences (Δ) and 95% confidence intervals are reported
Significant correlations to the environmental burden of Aspergillus spp.
The exclusive detection of Aspergillus spp. in BA and cholangitis cases (Table 1), together with confirmation from an independent dataset (Fig 2), led us to hypothesize a potential role for this fungus as a trigger in BA development. A recent UK report indicated that BA presentations declined during COVID-19 lockdowns [23], while another reported a simultaneous decrease in hospitalized patients with aspergillosis [13]. This parallel observation suggests that Aspergillus spp. may represent a shared environmental trigger for both conditions. Accordingly, a strong correlation between BA incidence and hospitalizations for aspergillosis would be anticipated.
The first UK lockdown lasted from March to June 2020, prompting us to analyze patient numbers during the corresponding months of 2018–2021. Using data reported by Sung et al. [13], we estimated patient numbers for Aspergillosis and Candidiasis during these periods and compared them with January–June BA case reports from Arshad et al. [23]. Our analysis revealed a strong correlation between BA cases and hospitalizations for Aspergillosis (r = 0.98, p = 0.02; Fig. 3A), supporting our hypothesis of a shared environmental trigger. In contrast, no significant correlation was observed with Candidiasis (r = 0.60, p = 0.40; Fig. 3B).Fig. 3. Correlations between BA incidence and environmental burdens of Aspergillus spp. (A–B) January–June BA presentations (Arshad et al.) were compared with estimated patient numbers from Sung et al. during March–June of 2018–2021. Significant correlation was observed with Aspergillosis (r = 0.98, 95% CI [0.36, 1.0], p = 0.02) but not with Candidiasis (r = 0.60, 95% CI [–0.85, 0.99], p = 0.40). (C) In Taiwan, BA incidence from 2000–2009 paralleled Aspergillus-positive hospital isolates adjusted for cancer admissions (r = 0.78, 95% CI [0.29, 0.94], p = 0.01). (D–G) In Japan, BA cases reported by the national registry over 25 years strongly correlated with visceral Aspergillosis in autopsy cases (r = 0.85, 95% CI [0.37, 0.97], p = 0.01), but not with visceral Candidiasis (r = 0.54, 95% CI [–0.26, 0.90], p = 0.17), Cryptococcus (r = 0.42, 95% CI [–0.40, 0.87], p = 0.30), or Mucormycetes (r = 0.41, 95% CI [–0.41, 0.86], p = 0.31). For all correlations, shaded regions indicate 95% confidence bands around regression lines
In Taiwan, the annual incidence of BA from 2000 to 2009 [24, 25] closely paralleled the annual incidence of Aspergillus-positive isolates among hospital admissions adjusted for cancer-related cases [14], serving as a proxy for environmental fungal burden (*r *= 0.78, p = 0.01; Fig. 3C). In Japan, BA cases reported by the Biliary Atresia Registry [26] over 25 years strongly correlated with annual autopsy reports of visceral Aspergillosis [15, 16] (r = 0.85, p = 0.01; Fig. 3D), reflecting the community burden of Aspergillus. In contrast, no significant correlations were found with visceral Candidiasis (r = 0.54, p = 0.17; Fig. 3E), Cryptococcus (r = 0.42, p = 0.30; Fig. 3F), or Mucormycetes (r = 0.41, p = 0.31; Fig. 3G). For all correlations, the figures display both the 95% confidence intervals for Pearson’s r and shaded 95% confidence bands around the regression lines. These data underscore the distinct association of Aspergillus spp. in BA incidence.
Discussion
Inspired by the clinical response of the index cholangitis case to antifungal agents (Fig. 1), we found evidence for a previously unrecognized association between Aspergillus spp. and fecal samples from BA patients. This was supported by 18S-based sequencing of our own samples (Table 1) and taxonomic analyses of shotgun metagenomes from an independent dataset (Fig. 2). Epidemiological data from the UK, Taiwan, and Japan further reinforced this association (Fig. 3). These observations are consistent with proteomic data suggesting host–fungal interactions, as BA feces were reported to contain ~347-fold higher levels of CHI3L1 [27], a protein that binds fungal chitin and protects against allergic asthma induced by Aspergillus fumigatus [28].
Careful examination of the index case suggests that the initial gastroenteritis phase responded to IV fluconazole, whereas recovery from the subsequent cholangitis phase required oral fluconazole. This raises the possibility of a two-hit sequence, in which an early immune priming phase is followed by aberrant immune hypersensitivity, accompanied by eosinophilia, after exposure to Aspergillus spp. and/or fungal-derived molecules in the gastrointestinal lumen. Such a framework could help explain several clinical features of BA. The priming phase may occur prenatally or perinatally and may be more common in infants of mothers with preexisting diabetes [29]. The second hit may be triggered by viral infection [30] or by environments with persistent Aspergillus exposure, such as neonatal intensive care units [31]. This stage could develop only after fungi have had sufficient opportunity to populate the gastrointestinal lumen, potentially facilitated by ciliary dysfunction [32]. Thus, Aspergillus spp. may provide a plausible mechanistic link for BA occurrence, although confirmatory studies are needed to establish causality.
Song et al. [22] employed SAOPaligner [33] to align reads against known microbial genomes, a method that may be less sensitive than Kraken 2 [12], which we used for fungal detection. Moreover, the number of available genomes in 2021, when their dataset was published, was likely limited. While k-mer–based tools such as Kraken 2 can yield false positives, the consistent detection of Aspergillus in both forward and reverse reads, with nearly identical abundance profiles (Fig. 2), strengthens the evidence for an association. A recent report [34] also highlighted the importance of Bifidobacterium longum in preserving native liver function in BA patients following Kasai portoenterostomy. Because many Bifidobacterium strains antagonize Aspergillus spp. [35], the presence of B. longum in BA cases may contribute to preserving native liver by limiting the impact of Aspergillus spp.
Conclusion
In summary, our findings suggest an association between Aspergillus spp. and BA, supported by fecal sequencing, re-analysis of independent metagenomic data, and cross-country epidemiological correlations. These exploratory results are limited by small sample size, retrospective design, and lack of mechanistic validation, and should therefore be considered hypothesis-generating. Prospective and mechanistic studies will be required to confirm and extend these observations.
Supplementary Information
Additional file 1: Supplementary Methods, Figure S1A-E, Figure S2A-E