Gut Dysbiosis in Patients With Fontan Circulation
We have presented, for the first time, evidence of gut dysbiosis in patients with Fontan pathophysiology when compared with healthy controls. Importantly, we established that gut dysbiosis is independently associated with chronic systemic inflammation (as indicated by elevated levels of natural log‐transformed C‐reactive protein), which is closely associated with Fontan pathophysiology, including Fontan‐associated liver disease. Considering the unique hemodynamics of Fontan circulation, gut dysbiosis emerges as a potential mechanism contributing to the failure of Fontan circulation. 

We identified several genera that were closely linked to Fontan pathophysiology; future studies are necessary to validate the presence of gut dysbiosis in patients with Fontan pathophysiology compared with healthy individuals across diverse communities, as regional differences may influence gut microbiome composition. Additionally, investigating the effects of interventions, such as exercise training or dietary remedies, on the gut microbiome could offer insights into novel therapeutic strategies for patients with Fontan pathophysiology. 

The data that support the findings of this study are available from the corresponding author upon reasonable request. Patient Characteristics We included 155 consecutive patients with Fontan circulation (mean age, 25±9 years) admitted to our institution for a routine comprehensive assessment of Fontan status along with 44 healthy controls (mean age, 22±11 years) from August 2019 to August 2022. Patients and healthy controls who had received antibiotics within 3 months were excluded. Table provides detailed information on patient characteristics, clinical background, cardiac surgery–related variables, major complications (such as protein‐losing enteropathy [PLE] and pulmonary arteriovenous fistulae), hemodynamics, and medications. All patients with Fontan pathophysiology and healthy controls gave written informed consent in this study. The Ethics Committee of the National Cardiovascular Center approved the study protocol (Approval No. R19034‐3; granted on June 19, 2019). Fecal Sample Collection and DNA Extraction As previously described, we collected fecal samples using brush‐type collection kits containing guanidine thiocyanate solution (TechnoSuruga Laboratory, Shizuoka, Japan). These samples were transported at ambient temperature and subsequently stored at 4 °C. Following retrieval, DNA was extracted from fecal samples using a GENE PREP STAR PI‐480 (Kurabo, Osaka, Japan) according to the manufacturer's instructions. 16S rRNA Sequencing, Taxonomic Classification, and Data Processing DNA libraries were carefully prepared according to the Illumina 16S Metagenomic Sequencing Library Preparation Guide, using a specific primer set (27Fmod: 5′‐ GTT TGA TCM TGG CTC AG‐3′ and 338R: 5′‐ TGC CTC CCG TAG GAG T‐3′) targeting the V1 to V2 regions of the 16S rRNA gene. Subsequently, the amplicons were subjected to 251 bp paired‐end sequencing on an MiSeq system (Illumina, San Diego, CA) using the MiSeq 500‐cycle v2 kit. Paired‐end sequences were analyzed using the Qiime2 pipeline (version 2021.2). The sequences were demultiplexed and analyzed using the DADA2 pipeline. Taxonomic classification of the gut bacteria was performed using the SILVA v138 99% operational taxonomic unit (OTU) database. Bioinformatics Analysis α diversity indices, including the Shannon index, Faith's phylogenetic diversity, and observed OTUs, were computed, and the variations were evaluated using the Wilcoxon test. Each diversity index may be unique for the following reasons: OTUs reflect the total number of gut microbiomes, while the Shannon index reflects an imbalance or deviation of the relative component ratio of the gut microbiomes. Faith's phylogenetic diversity reflects the complexity of the genealogy of the gut microbiomes. Regarding ß diversity, principal coordinate analysis was employed to assess differences in bacterial composition between patients with Fontan pathophysiology and healthy controls. Linear discriminant analysis effect size was performed using the Galaxy computational tool ( http://huttenhower.sph.harvard.edu/galaxy/ ) to identify taxonomic features most likely responsible for the observed differences between the biological classes. These differences were further assessed using the unweighted UniFrac distance metrics. The statistical significance of compositional variances between sample sets was determined via permutational multivariate analysis of variance. Hemodynamics Cardiac catheterization was conducted for all patients with Fontan pathophysiology, and hemodynamic variables, including central venous pressure (CVP [mm Hg]) and cardiac index (L/min/m 2 ), were computed as previously described. Simpson's rule was applied to estimate the morphological right and left ventricular volumes for patients who underwent cineventriculography. The end‐diastolic ventricular volume divided by the body surface area yielded the end‐diastolic ventricular volume index, and the ejection fraction of the systemic ventricle was subsequently calculated. Hemodynamic Phenotype and Failed Fontan Circulation We classified patients into 2 CVP‐based subgroups: low (CVP<14) and high (CVP ≥14), and 2 cardiac index (L/min per m 2 )‐based subgroups: low (cardiac index <3.0) and high/preserved (cardiac index ≥3.0). We then classified all patients into 4 CVP‐ and cardiac index–based hemodynamic phenotypes (LH: low CVP with high/preserved cardiac index, LL: low CVP with low cardiac index, HL: high CVP with low cardiac index, HH: high CVP with high/preserved cardiac index). Patients with failed Fontan circulation were those who had high CVP (≥14), that is, belonged to 2 high‐CVP groups (HL and HH). Brain Natriuretic Peptide and C‐Reactive Protein Plasma levels of brain natriuretic peptide (pg/mL) and CRP (C‐reactive protein) (μg/dL; latex agglutination immunoassay) were determined. PLE and Pulmonary Arteriovenous Fistulae PLE was diagnosed on the basis of clinical manifestations (edema or ascites) accompanied by hypoproteinemia, where there was no evidence of deficient production or excessive loss from an organ other than the gastrointestinal tract. Additionally, a positive result on 99 Technetium‐labeled albumin bowel scintigraphy was a part of the diagnostic criteria. As previously described, patients with a history of PLE diagnosis and plasma levels of albumin ≥3.0 (g/dL) who had not been hospitalized for at least 1 year were considered to have inactive PLE status, whereas patients with PLE were considered to have active PLE status. Pulmonary arteriovenous fistulae were diagnosed using bubble contrast echocardiography during catheterization. Fontan‐Associated Liver Disease Biomarkers Plasma levels of albumin, total bilirubin, creatinine, and liver enzymes were assessed, and the model for end‐stage liver disease scores, excluding the international normalized ratio, were calculated. Additionally, plasma levels of Mac‐2 binding protein glycosylation isomer (n=154), a recognized marker of liver fibrosis, were measured, and the other liver fibrosis indices (n=155), the ratio of the aspartate aminotransferase level to the platelet count and fibrosis‐4 index score, were also calculated. Von Willebrand factor antigen (VWF‐Ag) (n=155), which is an indicator of bacterial translocation, was quantified. Liver Ultrasonography We assessed liver image findings using ultrasonography and focused on the following 6 findings by binary scoring and then arbitrarily rated the abnormal liver image with a total ultrasonography score (liver score) ranging from 0 to 6 (n=152): parenchymal echotexture (normal=0, coarse=1), surface irregularity (smooth=0, irregular=1), liver edge appearance (sharp=0, dull=1), ascites (nonsmall=0, moderate or larger=1) (if ascitic fluid accumulated in both Morison's pouch and the pouch of Douglas, the ascites was graded as moderate), number of hyperechoic spots (≥3 mm in diameter; none to a few=0, larger number≥moderate=1; if several hyperechoic spots were observed in a particular parenchymal area, the scale was arbitrarily graded as moderate), and space‐occupying lesions (no=0, yes=1). Exercise Capacity A total of 149 patients with Fontan pathophysiology participated in cardiopulmonary exercise testing using a treadmill within 4 weeks of cardiac catheterization. Peak oxygen uptake (mL/kg per min) was quantified, and the normal predicted value (%) was used to evaluate aerobic exercise capacity. Statistical Analysis Data are expressed as the mean±SD or median with interquartile range, as appropriate. Pearson's correlation or Spearman's rank correlation was used to assess the relationships between continuous variables, as appropriate. Log‐transformed variables were used for brain natriuretic peptide and CRP (natural log‐transformed brain natriuretic peptide and natural log‐transformed C‐reactive protein [ln‐CRP], respectively). We developed 3 multivariate regression models to evaluate an independent association of each α‐diversity index with ln‐CRP; specifically, models 1, 2, and 3 were created for observed OTUs, Shannon index, and Faith's phylogenetic diversity, respectively, because of the uniqueness of each index as described in the bioinformatics analysis. Differences in demographic and clinical information between the 2 groups were compared using the Wilcoxon test or Fisher's exact test. For >3 groups, the Kruskal–Wallis test with post hoc analysis of the Dunn test was used. A Cox proportional hazards model was used to predict the association of these clinical factors with HF‐associated hospitalization, encompassing new‐onset PLE, its relapse, and renal failure. The diagnosis of HF was established if at least 1 of the following symptoms was present: orthopnea, nocturnal dyspnea, pulmonary edema, increasing peripheral edema, or radiological signs. We performed logistic regression analysis using the α diversity index and CRP levels to evaluate the associations between these variables and HF hospitalization. Variables with a P value <0.20 were used for receiver operating characteristic curve analyses to determine their cutoff values for efficient prognostic prediction. The HF hospitalization‐free rate was estimated using the Kaplan–Meier method, and differences between groups were assessed using log‐rank tests. All statistical analyses were performed using JMP 12 Pro software (SAS Institute, Cary, NC) and STATA (Version IC 14.2, College Station, TX). P <0.05 was considered to indicate statistical significance. 

We included 155 consecutive patients with Fontan circulation (mean age, 25±9 years) admitted to our institution for a routine comprehensive assessment of Fontan status along with 44 healthy controls (mean age, 22±11 years) from August 2019 to August 2022. Patients and healthy controls who had received antibiotics within 3 months were excluded. Table provides detailed information on patient characteristics, clinical background, cardiac surgery–related variables, major complications (such as protein‐losing enteropathy [PLE] and pulmonary arteriovenous fistulae), hemodynamics, and medications. All patients with Fontan pathophysiology and healthy controls gave written informed consent in this study. The Ethics Committee of the National Cardiovascular Center approved the study protocol (Approval No. R19034‐3; granted on June 19, 2019). 

DNA Extraction As previously described, we collected fecal samples using brush‐type collection kits containing guanidine thiocyanate solution (TechnoSuruga Laboratory, Shizuoka, Japan). These samples were transported at ambient temperature and subsequently stored at 4 °C. Following retrieval, DNA was extracted from fecal samples using a GENE PREP STAR PI‐480 (Kurabo, Osaka, Japan) according to the manufacturer's instructions. 

Sequencing, Taxonomic Classification, and Data Processing DNA libraries were carefully prepared according to the Illumina 16S Metagenomic Sequencing Library Preparation Guide, using a specific primer set (27Fmod: 5′‐ GTT TGA TCM TGG CTC AG‐3′ and 338R: 5′‐ TGC CTC CCG TAG GAG T‐3′) targeting the V1 to V2 regions of the 16S rRNA gene. Subsequently, the amplicons were subjected to 251 bp paired‐end sequencing on an MiSeq system (Illumina, San Diego, CA) using the MiSeq 500‐cycle v2 kit. Paired‐end sequences were analyzed using the Qiime2 pipeline (version 2021.2). The sequences were demultiplexed and analyzed using the DADA2 pipeline. Taxonomic classification of the gut bacteria was performed using the SILVA v138 99% operational taxonomic unit (OTU) database. 

α diversity indices, including the Shannon index, Faith's phylogenetic diversity, and observed OTUs, were computed, and the variations were evaluated using the Wilcoxon test. Each diversity index may be unique for the following reasons: OTUs reflect the total number of gut microbiomes, while the Shannon index reflects an imbalance or deviation of the relative component ratio of the gut microbiomes. Faith's phylogenetic diversity reflects the complexity of the genealogy of the gut microbiomes. Regarding ß diversity, principal coordinate analysis was employed to assess differences in bacterial composition between patients with Fontan pathophysiology and healthy controls. Linear discriminant analysis effect size was performed using the Galaxy computational tool ( http://huttenhower.sph.harvard.edu/galaxy/ ) to identify taxonomic features most likely responsible for the observed differences between the biological classes. These differences were further assessed using the unweighted UniFrac distance metrics. The statistical significance of compositional variances between sample sets was determined via permutational multivariate analysis of variance. 

Cardiac catheterization was conducted for all patients with Fontan pathophysiology, and hemodynamic variables, including central venous pressure (CVP [mm Hg]) and cardiac index (L/min/m 2 ), were computed as previously described. Simpson's rule was applied to estimate the morphological right and left ventricular volumes for patients who underwent cineventriculography. The end‐diastolic ventricular volume divided by the body surface area yielded the end‐diastolic ventricular volume index, and the ejection fraction of the systemic ventricle was subsequently calculated. 

We classified patients into 2 CVP‐based subgroups: low (CVP<14) and high (CVP ≥14), and 2 cardiac index (L/min per m 2 )‐based subgroups: low (cardiac index <3.0) and high/preserved (cardiac index ≥3.0). We then classified all patients into 4 CVP‐ and cardiac index–based hemodynamic phenotypes (LH: low CVP with high/preserved cardiac index, LL: low CVP with low cardiac index, HL: high CVP with low cardiac index, HH: high CVP with high/preserved cardiac index). Patients with failed Fontan circulation were those who had high CVP (≥14), that is, belonged to 2 high‐CVP groups (HL and HH). 

Plasma levels of brain natriuretic peptide (pg/mL) and CRP (C‐reactive protein) (μg/dL; latex agglutination immunoassay) were determined. 

and Pulmonary Arteriovenous Fistulae PLE was diagnosed on the basis of clinical manifestations (edema or ascites) accompanied by hypoproteinemia, where there was no evidence of deficient production or excessive loss from an organ other than the gastrointestinal tract. Additionally, a positive result on 99 Technetium‐labeled albumin bowel scintigraphy was a part of the diagnostic criteria. As previously described, patients with a history of PLE diagnosis and plasma levels of albumin ≥3.0 (g/dL) who had not been hospitalized for at least 1 year were considered to have inactive PLE status, whereas patients with PLE were considered to have active PLE status. Pulmonary arteriovenous fistulae were diagnosed using bubble contrast echocardiography during catheterization. 

Biomarkers Plasma levels of albumin, total bilirubin, creatinine, and liver enzymes were assessed, and the model for end‐stage liver disease scores, excluding the international normalized ratio, were calculated. Additionally, plasma levels of Mac‐2 binding protein glycosylation isomer (n=154), a recognized marker of liver fibrosis, were measured, and the other liver fibrosis indices (n=155), the ratio of the aspartate aminotransferase level to the platelet count and fibrosis‐4 index score, were also calculated. Von Willebrand factor antigen (VWF‐Ag) (n=155), which is an indicator of bacterial translocation, was quantified. Liver Ultrasonography We assessed liver image findings using ultrasonography and focused on the following 6 findings by binary scoring and then arbitrarily rated the abnormal liver image with a total ultrasonography score (liver score) ranging from 0 to 6 (n=152): parenchymal echotexture (normal=0, coarse=1), surface irregularity (smooth=0, irregular=1), liver edge appearance (sharp=0, dull=1), ascites (nonsmall=0, moderate or larger=1) (if ascitic fluid accumulated in both Morison's pouch and the pouch of Douglas, the ascites was graded as moderate), number of hyperechoic spots (≥3 mm in diameter; none to a few=0, larger number≥moderate=1; if several hyperechoic spots were observed in a particular parenchymal area, the scale was arbitrarily graded as moderate), and space‐occupying lesions (no=0, yes=1). Exercise Capacity A total of 149 patients with Fontan pathophysiology participated in cardiopulmonary exercise testing using a treadmill within 4 weeks of cardiac catheterization. Peak oxygen uptake (mL/kg per min) was quantified, and the normal predicted value (%) was used to evaluate aerobic exercise capacity. 

Plasma levels of albumin, total bilirubin, creatinine, and liver enzymes were assessed, and the model for end‐stage liver disease scores, excluding the international normalized ratio, were calculated. Additionally, plasma levels of Mac‐2 binding protein glycosylation isomer (n=154), a recognized marker of liver fibrosis, were measured, and the other liver fibrosis indices (n=155), the ratio of the aspartate aminotransferase level to the platelet count and fibrosis‐4 index score, were also calculated. Von Willebrand factor antigen (VWF‐Ag) (n=155), which is an indicator of bacterial translocation, was quantified. 

We assessed liver image findings using ultrasonography and focused on the following 6 findings by binary scoring and then arbitrarily rated the abnormal liver image with a total ultrasonography score (liver score) ranging from 0 to 6 (n=152): parenchymal echotexture (normal=0, coarse=1), surface irregularity (smooth=0, irregular=1), liver edge appearance (sharp=0, dull=1), ascites (nonsmall=0, moderate or larger=1) (if ascitic fluid accumulated in both Morison's pouch and the pouch of Douglas, the ascites was graded as moderate), number of hyperechoic spots (≥3 mm in diameter; none to a few=0, larger number≥moderate=1; if several hyperechoic spots were observed in a particular parenchymal area, the scale was arbitrarily graded as moderate), and space‐occupying lesions (no=0, yes=1). 

A total of 149 patients with Fontan pathophysiology participated in cardiopulmonary exercise testing using a treadmill within 4 weeks of cardiac catheterization. Peak oxygen uptake (mL/kg per min) was quantified, and the normal predicted value (%) was used to evaluate aerobic exercise capacity. 

Data are expressed as the mean±SD or median with interquartile range, as appropriate. Pearson's correlation or Spearman's rank correlation was used to assess the relationships between continuous variables, as appropriate. Log‐transformed variables were used for brain natriuretic peptide and CRP (natural log‐transformed brain natriuretic peptide and natural log‐transformed C‐reactive protein [ln‐CRP], respectively). We developed 3 multivariate regression models to evaluate an independent association of each α‐diversity index with ln‐CRP; specifically, models 1, 2, and 3 were created for observed OTUs, Shannon index, and Faith's phylogenetic diversity, respectively, because of the uniqueness of each index as described in the bioinformatics analysis. Differences in demographic and clinical information between the 2 groups were compared using the Wilcoxon test or Fisher's exact test. For >3 groups, the Kruskal–Wallis test with post hoc analysis of the Dunn test was used. A Cox proportional hazards model was used to predict the association of these clinical factors with HF‐associated hospitalization, encompassing new‐onset PLE, its relapse, and renal failure. The diagnosis of HF was established if at least 1 of the following symptoms was present: orthopnea, nocturnal dyspnea, pulmonary edema, increasing peripheral edema, or radiological signs. We performed logistic regression analysis using the α diversity index and CRP levels to evaluate the associations between these variables and HF hospitalization. Variables with a P value <0.20 were used for receiver operating characteristic curve analyses to determine their cutoff values for efficient prognostic prediction. The HF hospitalization‐free rate was estimated using the Kaplan–Meier method, and differences between groups were assessed using log‐rank tests. All statistical analyses were performed using JMP 12 Pro software (SAS Institute, Cary, NC) and STATA (Version IC 14.2, College Station, TX). P <0.05 was considered to indicate statistical significance. 

Comparison of Relative Abundance and Diversity of Gut Microbiome Between Patients With Fontan Pathophysiology and Healthy Volunteers Phylum Level In healthy controls, the dominant taxon was Firmicutes (60.1%), followed by Bacteroidetes (32.0%), Actinobacteria (4.3%), and Proteobacteria (2.8%) (Figure ). A similar trend was observed in patients with Fontan pathophysiology, with corresponding abundances of 56.4%, 36.3%, 3.1%, and 3.0%, respectively (Figure ). However, the percentage of Bacteroidetes was higher in patients with Fontan pathophysiology than in healthy controls (36% [32%–44%] versus 32% [26%–38%]; P =0.009), and the percentage of Firmicutes was lower in patients with Fontan pathophysiology than in healthy controls (56% [49%–62%] versus 60% [54%–71%]; P =0.043). Consequently, the Bacteroidetes/Firmicutes ratio was higher in patients with Fontan pathophysiology than in healthy controls (0.70 [0.65–0.75] versus 0.56 [0.47–0.65]; P =0.006). Genus Level Figure shows taxonomic differences between the Fontan and control groups. Linear discriminant analysis with a cutoff score of 3.0 revealed that the abundance of 8 genera was increased and that of 13 genera was decreased in patients with Fontan pathophysiology. Diversity of Gut Microbiota The α diversity indices of OTUs and Shannon index were significantly lower in patients with Fontan pathophysiology than in healthy controls (Figure through ) ( P <0.01 for both), and Faith's phylogenetic diversity tended to be lower ( P =0.09). ß diversity was also lower in patients with Fontan ( P <0.001; Figure ). Associations of Gut Dysbiosis With Fontan Pathophysiology α Diversity We focused on the α diversity of the gut microbiota to elucidate GD. Table presents associations of α diversity with Fontan pathophysiology. Hemodynamics and HF Severity There were only a few correlations between hemodynamic and HF severity variables and α diversity. Regarding the hemodynamic phenotype, both failed Fontan phenotypes (n=13, HL and HH) showed reduced α diversity in all indices ( P <0.01 for all; Table ). A comparison of the OTUs is shown in Figure . For the HF prognosis, according to logistic regression analysis with P <0.20, the cutoff values of all indices of α diversity were determined: 171, 5.64, and 21.4 for OTUs, Shannon index, and Faith's phylogenetic diversity, respectively. After classifying our patients with these cutoff values, we found that patients with low α diversity had a significant ( P <0.01 for OTUs and Shannon index) or marginal ( P =0.052 for Faith's phylogenetic diversity) high risk of hospitalization for HF. A comparison of the HF hospitalization‐free curves between Fontan patients divided by the OTU cutoff value of 171 is shown in Figure . CRP and VWF ‐Ag All α‐diversity indices were significantly associated with ln‐CRP and VWF‐Ag levels ( P <0.05–0.001) (Table ). Complications We had 18 patients with PLE, comprising 14 active and 4 inactive patients at the time of fecal sample collection, and 1 patient with active PLE also had pulmonary arteriovenous fistulae. There were no differences in all indices of α diversity between patients with and without PLE when patients with active and inactive PLE were analyzed as 1 group (Table ). Although all α‐diversity indices were lower in patients with active PLE (n=14) than in those without active PLE (n=4; P <0.05–0.01), these indices were not different from those of patients without PLE (n=137). A comparison of the OTUs is shown in Figure . The α diversity of patients with pulmonary arteriovenous fistulae (n=9) was not different from that of those without pulmonary arteriovenous fistulae (n=146), except for the Shannon index (5.5±0.8 versus 6.0±0.5; P =0.011; Table ). Regarding FALD, although most liver variables, including liver score, were not associated with the α diversity, some liver fibrosis indices (Mac‐2 binding protein glycosylation isomer and aspartate aminotransferase‐to‐platelet ratio index) were associated with the reduced α diversity (Table ). Association Between CRP Levels and Fontan Pathophysiology The associations between the clinical variables and ln‐CRP levels are presented in Table . Male sex, increased body mass index, reduced α diversity, HF severity, VWF‐Ag levels, and some hemodynamic variables were associated with high ln‐CRP levels. We developed 3 multivariate regression models to evaluate an association of each α‐diversity index with ln‐CRP; specifically, models 1, 2, and 3 were created for observed OTUs, Shannon index, and Faith's phylogenetic diversity, respectively (Table ). Based on these models, along with high VWF‐Ag levels, increased body mass index, and hypoxia, all reduced α‐diversity indices were independently associated with high ln‐CRP. Correlations between ln‐CRP levels and OTUs, arterial oxygen saturation, and VWF‐Ag levels are shown in Figure through . In addition, high ln‐CRP levels were predictive of a high risk of HF hospitalization (hazard ratio, 1.64 [95% CI, 1.17–2.26]; P =0.004), and patients with high ln‐CRP levels ≥4.25 (0.07 mg/dL) had a 3.68 times higher risk of HF hospitalization ( P =0.002; Figure ). Regarding FALD, ln‐CRP was inversely correlated with albumin and positively correlated with γ‐glutamyl transpeptidase, aspartate aminotransferase, and Mac‐2 binding protein glycosylation isomer ( P <0.05–0.01; Figure ). Interestingly, ln‐CRP was strongly associated with liver imaging abnormalities, that is, liver score ( r =0.31, P <0.001; Figure ). Thus, chronic systemic inflammation is closely linked to Fontan pathophysiology, including FALD and HF prognosis, and GD is an independent determinant of systemic inflammation. Associations Between the Relative Abundance of Genus and Fontan Pathophysiology Among the 392 genera identified, patients with Fontan pathophysiology showed a different relative abundance of 21 genera compared with the healthy controls (Figure ). Of these, particular attention was given to 4 genera, Clostridium sensu stricto 1 , Veillonella, Ruminococcaceae UCG_002 , and Agathobacter , in terms of significant associations of abundance with high CVP (Figure ), characterizing Fontan hemodynamics (Table ). Increased abundance was observed in the first 2 genera, whereas decreased abundance was observed in the latter 2 genera. CRP and VWF ‐Ag A reduced relative abundance of Ruminococcaceae UCG_002 and Agathobacter was significantly associated with high ln‐CRP and VWF‐Ag levels ( P <0.05 for both). Complications Patients with active PLE showed lower relative abundances of Ruminococcaceae UCG_002 ( P =0.026) and higher abundances of Clostridium sensu stricto 1 ( P =0.037) than those without PLE. The abundance of Agathobacter tended to be lower in patients with active PLE ( P =0.066). There was no difference in the abundance of the 4 genera between patients with and without pulmonary arteriovenous fistulae. With regard to FALD, an increased relative abundance of Clostridium sensu stricto 1 was associated with low fibrosis‐4 index, and a decreased abundance of Ruminococcaceae UCG _002 was associated with high Mac‐2 binding protein glycosylation isomer levels (Table ). HF pathophysiology The relative abundance of Agathobacter was positively correlated with peak oxygen uptake ( P =0.032; Table ), and the decreased abundance of Agathobacter and Ruminococcaceae UCG_002 was associated with a high risk of HF hospitalization (Figure and ). 

Phylum Level In healthy controls, the dominant taxon was Firmicutes (60.1%), followed by Bacteroidetes (32.0%), Actinobacteria (4.3%), and Proteobacteria (2.8%) (Figure ). A similar trend was observed in patients with Fontan pathophysiology, with corresponding abundances of 56.4%, 36.3%, 3.1%, and 3.0%, respectively (Figure ). However, the percentage of Bacteroidetes was higher in patients with Fontan pathophysiology than in healthy controls (36% [32%–44%] versus 32% [26%–38%]; P =0.009), and the percentage of Firmicutes was lower in patients with Fontan pathophysiology than in healthy controls (56% [49%–62%] versus 60% [54%–71%]; P =0.043). Consequently, the Bacteroidetes/Firmicutes ratio was higher in patients with Fontan pathophysiology than in healthy controls (0.70 [0.65–0.75] versus 0.56 [0.47–0.65]; P =0.006). Genus Level Figure shows taxonomic differences between the Fontan and control groups. Linear discriminant analysis with a cutoff score of 3.0 revealed that the abundance of 8 genera was increased and that of 13 genera was decreased in patients with Fontan pathophysiology. Diversity of Gut Microbiota The α diversity indices of OTUs and Shannon index were significantly lower in patients with Fontan pathophysiology than in healthy controls (Figure through ) ( P <0.01 for both), and Faith's phylogenetic diversity tended to be lower ( P =0.09). ß diversity was also lower in patients with Fontan ( P <0.001; Figure ). 

In healthy controls, the dominant taxon was Firmicutes (60.1%), followed by Bacteroidetes (32.0%), Actinobacteria (4.3%), and Proteobacteria (2.8%) (Figure ). A similar trend was observed in patients with Fontan pathophysiology, with corresponding abundances of 56.4%, 36.3%, 3.1%, and 3.0%, respectively (Figure ). However, the percentage of Bacteroidetes was higher in patients with Fontan pathophysiology than in healthy controls (36% [32%–44%] versus 32% [26%–38%]; P =0.009), and the percentage of Firmicutes was lower in patients with Fontan pathophysiology than in healthy controls (56% [49%–62%] versus 60% [54%–71%]; P =0.043). Consequently, the Bacteroidetes/Firmicutes ratio was higher in patients with Fontan pathophysiology than in healthy controls (0.70 [0.65–0.75] versus 0.56 [0.47–0.65]; P =0.006). 

Figure shows taxonomic differences between the Fontan and control groups. Linear discriminant analysis with a cutoff score of 3.0 revealed that the abundance of 8 genera was increased and that of 13 genera was decreased in patients with Fontan pathophysiology. 

The α diversity indices of OTUs and Shannon index were significantly lower in patients with Fontan pathophysiology than in healthy controls (Figure through ) ( P <0.01 for both), and Faith's phylogenetic diversity tended to be lower ( P =0.09). ß diversity was also lower in patients with Fontan ( P <0.001; Figure ). 

α Diversity We focused on the α diversity of the gut microbiota to elucidate GD. Table presents associations of α diversity with Fontan pathophysiology. Hemodynamics and HF Severity There were only a few correlations between hemodynamic and HF severity variables and α diversity. Regarding the hemodynamic phenotype, both failed Fontan phenotypes (n=13, HL and HH) showed reduced α diversity in all indices ( P <0.01 for all; Table ). A comparison of the OTUs is shown in Figure . For the HF prognosis, according to logistic regression analysis with P <0.20, the cutoff values of all indices of α diversity were determined: 171, 5.64, and 21.4 for OTUs, Shannon index, and Faith's phylogenetic diversity, respectively. After classifying our patients with these cutoff values, we found that patients with low α diversity had a significant ( P <0.01 for OTUs and Shannon index) or marginal ( P =0.052 for Faith's phylogenetic diversity) high risk of hospitalization for HF. A comparison of the HF hospitalization‐free curves between Fontan patients divided by the OTU cutoff value of 171 is shown in Figure . CRP and VWF ‐Ag All α‐diversity indices were significantly associated with ln‐CRP and VWF‐Ag levels ( P <0.05–0.001) (Table ). Complications We had 18 patients with PLE, comprising 14 active and 4 inactive patients at the time of fecal sample collection, and 1 patient with active PLE also had pulmonary arteriovenous fistulae. There were no differences in all indices of α diversity between patients with and without PLE when patients with active and inactive PLE were analyzed as 1 group (Table ). Although all α‐diversity indices were lower in patients with active PLE (n=14) than in those without active PLE (n=4; P <0.05–0.01), these indices were not different from those of patients without PLE (n=137). A comparison of the OTUs is shown in Figure . The α diversity of patients with pulmonary arteriovenous fistulae (n=9) was not different from that of those without pulmonary arteriovenous fistulae (n=146), except for the Shannon index (5.5±0.8 versus 6.0±0.5; P =0.011; Table ). Regarding FALD, although most liver variables, including liver score, were not associated with the α diversity, some liver fibrosis indices (Mac‐2 binding protein glycosylation isomer and aspartate aminotransferase‐to‐platelet ratio index) were associated with the reduced α diversity (Table ). 

We focused on the α diversity of the gut microbiota to elucidate GD. Table presents associations of α diversity with Fontan pathophysiology. Hemodynamics and HF Severity There were only a few correlations between hemodynamic and HF severity variables and α diversity. Regarding the hemodynamic phenotype, both failed Fontan phenotypes (n=13, HL and HH) showed reduced α diversity in all indices ( P <0.01 for all; Table ). A comparison of the OTUs is shown in Figure . For the HF prognosis, according to logistic regression analysis with P <0.20, the cutoff values of all indices of α diversity were determined: 171, 5.64, and 21.4 for OTUs, Shannon index, and Faith's phylogenetic diversity, respectively. After classifying our patients with these cutoff values, we found that patients with low α diversity had a significant ( P <0.01 for OTUs and Shannon index) or marginal ( P =0.052 for Faith's phylogenetic diversity) high risk of hospitalization for HF. A comparison of the HF hospitalization‐free curves between Fontan patients divided by the OTU cutoff value of 171 is shown in Figure . CRP and VWF ‐Ag All α‐diversity indices were significantly associated with ln‐CRP and VWF‐Ag levels ( P <0.05–0.001) (Table ). Complications We had 18 patients with PLE, comprising 14 active and 4 inactive patients at the time of fecal sample collection, and 1 patient with active PLE also had pulmonary arteriovenous fistulae. There were no differences in all indices of α diversity between patients with and without PLE when patients with active and inactive PLE were analyzed as 1 group (Table ). Although all α‐diversity indices were lower in patients with active PLE (n=14) than in those without active PLE (n=4; P <0.05–0.01), these indices were not different from those of patients without PLE (n=137). A comparison of the OTUs is shown in Figure . The α diversity of patients with pulmonary arteriovenous fistulae (n=9) was not different from that of those without pulmonary arteriovenous fistulae (n=146), except for the Shannon index (5.5±0.8 versus 6.0±0.5; P =0.011; Table ). Regarding FALD, although most liver variables, including liver score, were not associated with the α diversity, some liver fibrosis indices (Mac‐2 binding protein glycosylation isomer and aspartate aminotransferase‐to‐platelet ratio index) were associated with the reduced α diversity (Table ). 

HF Severity There were only a few correlations between hemodynamic and HF severity variables and α diversity. Regarding the hemodynamic phenotype, both failed Fontan phenotypes (n=13, HL and HH) showed reduced α diversity in all indices ( P <0.01 for all; Table ). A comparison of the OTUs is shown in Figure . For the HF prognosis, according to logistic regression analysis with P <0.20, the cutoff values of all indices of α diversity were determined: 171, 5.64, and 21.4 for OTUs, Shannon index, and Faith's phylogenetic diversity, respectively. After classifying our patients with these cutoff values, we found that patients with low α diversity had a significant ( P <0.01 for OTUs and Shannon index) or marginal ( P =0.052 for Faith's phylogenetic diversity) high risk of hospitalization for HF. A comparison of the HF hospitalization‐free curves between Fontan patients divided by the OTU cutoff value of 171 is shown in Figure . 

and VWF ‐Ag All α‐diversity indices were significantly associated with ln‐CRP and VWF‐Ag levels ( P <0.05–0.001) (Table ). 

We had 18 patients with PLE, comprising 14 active and 4 inactive patients at the time of fecal sample collection, and 1 patient with active PLE also had pulmonary arteriovenous fistulae. There were no differences in all indices of α diversity between patients with and without PLE when patients with active and inactive PLE were analyzed as 1 group (Table ). Although all α‐diversity indices were lower in patients with active PLE (n=14) than in those without active PLE (n=4; P <0.05–0.01), these indices were not different from those of patients without PLE (n=137). A comparison of the OTUs is shown in Figure . The α diversity of patients with pulmonary arteriovenous fistulae (n=9) was not different from that of those without pulmonary arteriovenous fistulae (n=146), except for the Shannon index (5.5±0.8 versus 6.0±0.5; P =0.011; Table ). Regarding FALD, although most liver variables, including liver score, were not associated with the α diversity, some liver fibrosis indices (Mac‐2 binding protein glycosylation isomer and aspartate aminotransferase‐to‐platelet ratio index) were associated with the reduced α diversity (Table ). 

CRP Levels and Fontan Pathophysiology The associations between the clinical variables and ln‐CRP levels are presented in Table . Male sex, increased body mass index, reduced α diversity, HF severity, VWF‐Ag levels, and some hemodynamic variables were associated with high ln‐CRP levels. We developed 3 multivariate regression models to evaluate an association of each α‐diversity index with ln‐CRP; specifically, models 1, 2, and 3 were created for observed OTUs, Shannon index, and Faith's phylogenetic diversity, respectively (Table ). Based on these models, along with high VWF‐Ag levels, increased body mass index, and hypoxia, all reduced α‐diversity indices were independently associated with high ln‐CRP. Correlations between ln‐CRP levels and OTUs, arterial oxygen saturation, and VWF‐Ag levels are shown in Figure through . In addition, high ln‐CRP levels were predictive of a high risk of HF hospitalization (hazard ratio, 1.64 [95% CI, 1.17–2.26]; P =0.004), and patients with high ln‐CRP levels ≥4.25 (0.07 mg/dL) had a 3.68 times higher risk of HF hospitalization ( P =0.002; Figure ). Regarding FALD, ln‐CRP was inversely correlated with albumin and positively correlated with γ‐glutamyl transpeptidase, aspartate aminotransferase, and Mac‐2 binding protein glycosylation isomer ( P <0.05–0.01; Figure ). Interestingly, ln‐CRP was strongly associated with liver imaging abnormalities, that is, liver score ( r =0.31, P <0.001; Figure ). Thus, chronic systemic inflammation is closely linked to Fontan pathophysiology, including FALD and HF prognosis, and GD is an independent determinant of systemic inflammation. 

Among the 392 genera identified, patients with Fontan pathophysiology showed a different relative abundance of 21 genera compared with the healthy controls (Figure ). Of these, particular attention was given to 4 genera, Clostridium sensu stricto 1 , Veillonella, Ruminococcaceae UCG_002 , and Agathobacter , in terms of significant associations of abundance with high CVP (Figure ), characterizing Fontan hemodynamics (Table ). Increased abundance was observed in the first 2 genera, whereas decreased abundance was observed in the latter 2 genera. CRP and VWF ‐Ag A reduced relative abundance of Ruminococcaceae UCG_002 and Agathobacter was significantly associated with high ln‐CRP and VWF‐Ag levels ( P <0.05 for both). Complications Patients with active PLE showed lower relative abundances of Ruminococcaceae UCG_002 ( P =0.026) and higher abundances of Clostridium sensu stricto 1 ( P =0.037) than those without PLE. The abundance of Agathobacter tended to be lower in patients with active PLE ( P =0.066). There was no difference in the abundance of the 4 genera between patients with and without pulmonary arteriovenous fistulae. With regard to FALD, an increased relative abundance of Clostridium sensu stricto 1 was associated with low fibrosis‐4 index, and a decreased abundance of Ruminococcaceae UCG _002 was associated with high Mac‐2 binding protein glycosylation isomer levels (Table ). HF pathophysiology The relative abundance of Agathobacter was positively correlated with peak oxygen uptake ( P =0.032; Table ), and the decreased abundance of Agathobacter and Ruminococcaceae UCG_002 was associated with a high risk of HF hospitalization (Figure and ). 

and VWF ‐Ag A reduced relative abundance of Ruminococcaceae UCG_002 and Agathobacter was significantly associated with high ln‐CRP and VWF‐Ag levels ( P <0.05 for both). 

Patients with active PLE showed lower relative abundances of Ruminococcaceae UCG_002 ( P =0.026) and higher abundances of Clostridium sensu stricto 1 ( P =0.037) than those without PLE. The abundance of Agathobacter tended to be lower in patients with active PLE ( P =0.066). There was no difference in the abundance of the 4 genera between patients with and without pulmonary arteriovenous fistulae. With regard to FALD, an increased relative abundance of Clostridium sensu stricto 1 was associated with low fibrosis‐4 index, and a decreased abundance of Ruminococcaceae UCG _002 was associated with high Mac‐2 binding protein glycosylation isomer levels (Table ). 

pathophysiology The relative abundance of Agathobacter was positively correlated with peak oxygen uptake ( P =0.032; Table ), and the decreased abundance of Agathobacter and Ruminococcaceae UCG_002 was associated with a high risk of HF hospitalization (Figure and ). 

Our study revealed several novel findings related to patients with Fontan circulation: (1) the presence of GD, that is, reduced α diversity, was associated with the CVP‐based hemodynamic phenotype; (b) this GD, along with bacterial translocation and hypoxia, was independently linked to high ln‐CRP levels; the elevated ln‐CRP is closely correlated with Fontan pathophysiology, including FALD and HF prognosis; and (3) GD, characterized by changes in the relative abundance of certain genera, was associated with CVP and an increased risk of hospitalization due to HF. These results imply that GD is a contributing factor to chronic systemic inflammation and plays a role in both Fontan pathophysiology and its progression. Consequently, understanding the relationships, including causality, between the gut microbiome and Fontan pathophysiology could enhance our comprehension of these complex conditions and pave the way for the development of novel therapeutic strategies and unique biomarkers. HF Pathophysiology and GD Intestinal edema or ischemia due to volume retention or low perfusion compromises the integrity of the intestinal wall, leading to gut barrier dysfunction. This dysfunction manifests as increased intestinal permeability, commonly referred to as “leaky gut,” facilitating the translocation of pathogenic bacteria (bacterial translocation) and their metabolites from the gut into the systemic circulation. Such translocations trigger local and systemic immunological and inflammatory responses, playing a significant role in the pathophysiology and progression of HF. , , Short‐chain fatty acids, that is, active metabolites produced by the gut microbiome, may play a crucial role in maintaining intestinal wall integrity and barrier function. For instance, a decrease in the levels of short‐chain fatty acids due to GD has been associated with the development of a leaky gut. , Apart from edema and hypoperfusion affecting the intestinal wall, hypoxia may represent another cause of GD. , This may be due to the substantial impact of hypoxia on the originally low‐oxygenated institutional condition, where both the intestine and gut microbiome consume oxygen. , Notably, associations between preoperative and perioperative hypoxia and GD have been speculated in children with unrepaired tetralogy of Fallot. , According to this evidence, it is no wonder that patients with Fontan pathophysiology show GD because the pathophysiology is usually characterized by high CVP, low cardiac output, and mild hypoxia. The present study, for the first time, demonstrates a comparable GD in patients with Fontan pathophysiology and elucidates the associated pathophysiology, mirroring observations in patients with HF who had reduced left ventricular ejection fraction or those experiencing hypoxia. However, it is important to acknowledge that GD may not be exclusive to patients with Fontan circulation. In patients with HF, GD is typically characterized by a decreased abundance of Firmicutes, an increased abundance of Bacteroidetes, and a high Bacteroidetes/Firmicutes ratio at the phylum level. , In addition, elevated levels of Proteobacteria may contribute to increased lipopolysaccharides in the blood, exacerbating systemic inflammation in patients with severe HF. Several features of GD observed in our patients with Fontan pathophysiology align with these patterns. At the genus level, patients with Fontan pathophysiology exhibit a similar GD profile reminiscent of HF. Specifically, proinflammatory genera, like Ruminococcusgnavus_group , Veillonella , and Fusobacteria , show increased relative abundance, whereas short‐chain fatty acid–producing genera, such as Ruminococcus, Fusicatenibacter, Lachnospira , and Roseburia , demonstrate decreased abundance. Given that these short‐chain fatty acid–producing genera, particularly those belonging to the Clostridium cluster IV/XIVa, play a crucial role in butyric acid production and stabilizing intestinal barrier function, it is plausible that patients with Fontan pathophysiology experience impaired gut barrier function, that is, a leaky gut. Notably, VWF‐Ag, an indicator of bacterial translocation, exhibited an increase and demonstrated a positive correlation with ln‐CRP. In addition, previous studies demonstrated elevated levels of high‐sensitivity CRP and inflammatory cytokines, including interleukin‐6. These findings suggest the existence of a gut–heart axis in patients with Fontan pathophysiology. Additionally, as mentioned earlier, hypoxia may exert an additional impact on this intricate interplay within the gut–heart axis. Interestingly, we found some specific genera that were closely linked to Fontan pathophysiology (Table ). In particular, the increased relative abundance of short‐chain fatty acid–producing genera, that is, Agathobacter and Ruminococcaceae UCG _002 , exhibited an association with a favorable Fontan status (Figure ). Consequently, these genera hold promise as potential biomarkers for Fontan circulation, a prospect that warrants further investigations. Fontan Complications and GD Intriguingly, despite significant differences in CVP (12±3 versus 10±3; P <0.01) and VWF‐Ag levels (214±36 versus 137±40; P <0.001) between patients with Fontan pathophysiology with active PLE and those without PLE, there was little disparity in GD concerning the relative abundance of the microbiome or α diversity. These findings differ from those of a previous study in which reduced α diversity and significant differences in some genera, such as an increase in the abundance of Granulicatella , in patients with active PLE were described. These findings suggest that despite more pronounced leaky gut characteristics in patients with PLE, GD may not be the primary cause of this complication but could modify its pathophysiology. Similarly, no significant difference in GD was observed between patients with and without pulmonary arteriovenous fistulae despite notable differences in arterial oxygen saturation (90%±4% versus 94%±4%; P =0.005). Thus, GD may not be the main cause of these 2 complications, although it may influence their pathophysiology. Further studies with a large number of these affected patients may be necessary to clarify these issues. Regarding FALD, we found that α diversity was associated with the marker of liver fibrosis despite no association of diversity with liver synthetic function, congestion, or imaging abnormalities. In contrast, ln‐CRP was associated with variables such as liver synthetic function, congestion, fibrosis markers, and image severity. Thus, considering the independent association of α diversity with ln‐CRP, GD could be a contributing factor to FALD progression. Patients with Fontan pathophysiology share certain GD features commonly observed in patients with liver cirrhosis, such as an increased abundance of Veillonella and a decreased abundance of short‐chain fatty acid–producing genera. These results suggest that the gut–liver axis plays a role in the progression of FALD, similar to that observed in patients with liver cirrhosis. Therefore, in conjunction with unique hemodynamics, neurohumoral activations, and cardiac autonomic abnormalities, the systemic inflammation associated with GD and probably arising from a leaky gut could be a crucial mechanism contributing to the failing process of Fontan pathophysiology. This may be particularly evident in the progression of FALD, possibly through the gut–liver or gut–heart axis. Study Limitations The present study has some limitations. First, the cross‐sectional nature of the study design precluded the establishment of causality between GD and Fontan pathophysiology. Second, we did not collect data on dietary intake or lifestyles, with a particular gap in information related to dietary fiber intake. Research has shown that dietary habits, medications, and daily exercises significantly impact GD. Thus, the generalizability of our results may be limited, as the composition of the gut microbiome varies significantly between residential regions and races. Third, owing to the 16S rRNA analysis employed, we could not analyze the gut microbiome at the species level or assess the functions of the microbiome. Fourth, CRP levels may only be indicative of inflammation, although it is the most common biomarker to identify patients with heightened systemic inflammation. Future studies should aim to measure inflammatory cytokines such as interleukin‐6 and microbiome‐derived metabolites to clarify the mechanisms of GD‐related systemic inflammation and the causality between GD and Fontan pathophysiology. Fifth, liver fibrosis was estimated on the basis of biomarkers and liver ultrasonography (liver score), not biopsy specimens. Sixth, because of the small sample size and number of heart failure events, some hazard ratios or their variance might be inflated. As mentioned in the discussion of major complications and GD, large‐scale multicenter studies may be necessary to confirm the prognostic significance of GD in the future. Finally, the collection of feces in tubes containing guanidine thiocyanate solution may have influenced the gut microbiome. In conclusion, our findings revealed that patients with Fontan pathophysiology exhibited GD compared with their healthy counterparts. GD is not only linked to failed Fontan hemodynamics but is also independently associated with systemic inflammation. Importantly, in conjunction with bacterial translocation and hypoxia, GD may play a pivotal role in the process of Fontan pathophysiology failure, including FALD, which occurs through GD‐associated systemic inflammation possibly mediated by the gut–liver or gut–heart axis. 

Pathophysiology and GD Intestinal edema or ischemia due to volume retention or low perfusion compromises the integrity of the intestinal wall, leading to gut barrier dysfunction. This dysfunction manifests as increased intestinal permeability, commonly referred to as “leaky gut,” facilitating the translocation of pathogenic bacteria (bacterial translocation) and their metabolites from the gut into the systemic circulation. Such translocations trigger local and systemic immunological and inflammatory responses, playing a significant role in the pathophysiology and progression of HF. , , Short‐chain fatty acids, that is, active metabolites produced by the gut microbiome, may play a crucial role in maintaining intestinal wall integrity and barrier function. For instance, a decrease in the levels of short‐chain fatty acids due to GD has been associated with the development of a leaky gut. , Apart from edema and hypoperfusion affecting the intestinal wall, hypoxia may represent another cause of GD. , This may be due to the substantial impact of hypoxia on the originally low‐oxygenated institutional condition, where both the intestine and gut microbiome consume oxygen. , Notably, associations between preoperative and perioperative hypoxia and GD have been speculated in children with unrepaired tetralogy of Fallot. , According to this evidence, it is no wonder that patients with Fontan pathophysiology show GD because the pathophysiology is usually characterized by high CVP, low cardiac output, and mild hypoxia. The present study, for the first time, demonstrates a comparable GD in patients with Fontan pathophysiology and elucidates the associated pathophysiology, mirroring observations in patients with HF who had reduced left ventricular ejection fraction or those experiencing hypoxia. However, it is important to acknowledge that GD may not be exclusive to patients with Fontan circulation. In patients with HF, GD is typically characterized by a decreased abundance of Firmicutes, an increased abundance of Bacteroidetes, and a high Bacteroidetes/Firmicutes ratio at the phylum level. , In addition, elevated levels of Proteobacteria may contribute to increased lipopolysaccharides in the blood, exacerbating systemic inflammation in patients with severe HF. Several features of GD observed in our patients with Fontan pathophysiology align with these patterns. At the genus level, patients with Fontan pathophysiology exhibit a similar GD profile reminiscent of HF. Specifically, proinflammatory genera, like Ruminococcusgnavus_group , Veillonella , and Fusobacteria , show increased relative abundance, whereas short‐chain fatty acid–producing genera, such as Ruminococcus, Fusicatenibacter, Lachnospira , and Roseburia , demonstrate decreased abundance. Given that these short‐chain fatty acid–producing genera, particularly those belonging to the Clostridium cluster IV/XIVa, play a crucial role in butyric acid production and stabilizing intestinal barrier function, it is plausible that patients with Fontan pathophysiology experience impaired gut barrier function, that is, a leaky gut. Notably, VWF‐Ag, an indicator of bacterial translocation, exhibited an increase and demonstrated a positive correlation with ln‐CRP. In addition, previous studies demonstrated elevated levels of high‐sensitivity CRP and inflammatory cytokines, including interleukin‐6. These findings suggest the existence of a gut–heart axis in patients with Fontan pathophysiology. Additionally, as mentioned earlier, hypoxia may exert an additional impact on this intricate interplay within the gut–heart axis. Interestingly, we found some specific genera that were closely linked to Fontan pathophysiology (Table ). In particular, the increased relative abundance of short‐chain fatty acid–producing genera, that is, Agathobacter and Ruminococcaceae UCG _002 , exhibited an association with a favorable Fontan status (Figure ). Consequently, these genera hold promise as potential biomarkers for Fontan circulation, a prospect that warrants further investigations. 

GD Intriguingly, despite significant differences in CVP (12±3 versus 10±3; P <0.01) and VWF‐Ag levels (214±36 versus 137±40; P <0.001) between patients with Fontan pathophysiology with active PLE and those without PLE, there was little disparity in GD concerning the relative abundance of the microbiome or α diversity. These findings differ from those of a previous study in which reduced α diversity and significant differences in some genera, such as an increase in the abundance of Granulicatella , in patients with active PLE were described. These findings suggest that despite more pronounced leaky gut characteristics in patients with PLE, GD may not be the primary cause of this complication but could modify its pathophysiology. Similarly, no significant difference in GD was observed between patients with and without pulmonary arteriovenous fistulae despite notable differences in arterial oxygen saturation (90%±4% versus 94%±4%; P =0.005). Thus, GD may not be the main cause of these 2 complications, although it may influence their pathophysiology. Further studies with a large number of these affected patients may be necessary to clarify these issues. Regarding FALD, we found that α diversity was associated with the marker of liver fibrosis despite no association of diversity with liver synthetic function, congestion, or imaging abnormalities. In contrast, ln‐CRP was associated with variables such as liver synthetic function, congestion, fibrosis markers, and image severity. Thus, considering the independent association of α diversity with ln‐CRP, GD could be a contributing factor to FALD progression. Patients with Fontan pathophysiology share certain GD features commonly observed in patients with liver cirrhosis, such as an increased abundance of Veillonella and a decreased abundance of short‐chain fatty acid–producing genera. These results suggest that the gut–liver axis plays a role in the progression of FALD, similar to that observed in patients with liver cirrhosis. Therefore, in conjunction with unique hemodynamics, neurohumoral activations, and cardiac autonomic abnormalities, the systemic inflammation associated with GD and probably arising from a leaky gut could be a crucial mechanism contributing to the failing process of Fontan pathophysiology. This may be particularly evident in the progression of FALD, possibly through the gut–liver or gut–heart axis. 

The present study has some limitations. First, the cross‐sectional nature of the study design precluded the establishment of causality between GD and Fontan pathophysiology. Second, we did not collect data on dietary intake or lifestyles, with a particular gap in information related to dietary fiber intake. Research has shown that dietary habits, medications, and daily exercises significantly impact GD. Thus, the generalizability of our results may be limited, as the composition of the gut microbiome varies significantly between residential regions and races. Third, owing to the 16S rRNA analysis employed, we could not analyze the gut microbiome at the species level or assess the functions of the microbiome. Fourth, CRP levels may only be indicative of inflammation, although it is the most common biomarker to identify patients with heightened systemic inflammation. Future studies should aim to measure inflammatory cytokines such as interleukin‐6 and microbiome‐derived metabolites to clarify the mechanisms of GD‐related systemic inflammation and the causality between GD and Fontan pathophysiology. Fifth, liver fibrosis was estimated on the basis of biomarkers and liver ultrasonography (liver score), not biopsy specimens. Sixth, because of the small sample size and number of heart failure events, some hazard ratios or their variance might be inflated. As mentioned in the discussion of major complications and GD, large‐scale multicenter studies may be necessary to confirm the prognostic significance of GD in the future. Finally, the collection of feces in tubes containing guanidine thiocyanate solution may have influenced the gut microbiome. In conclusion, our findings revealed that patients with Fontan pathophysiology exhibited GD compared with their healthy counterparts. GD is not only linked to failed Fontan hemodynamics but is also independently associated with systemic inflammation. Importantly, in conjunction with bacterial translocation and hypoxia, GD may play a pivotal role in the process of Fontan pathophysiology failure, including FALD, which occurs through GD‐associated systemic inflammation possibly mediated by the gut–liver or gut–heart axis. 

This study was supported by a research grant from the Japanese Ministry of Health, Labor, and Welfare (22K07905, 24FC1014, Miyata Cardiac Research Promotion Foundation to H.O.) and JSR (Y.N.). 

None. 

Table S1 

