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Clinical Trial
. 2020 Oct 21;5(5):e00314-20.
doi: 10.1128/mSphere.00314-20.

Distinct Fecal and Plasma Metabolites in Children with Autism Spectrum Disorders and Their Modulation after Microbiota Transfer Therapy

Dae-Wook Kang  1 , James B Adams  2 , Troy Vargason  3   4 , Marina Santiago  5 , Juergen Hahn  3   4   6 , Rosa Krajmalnik-Brown  1   7   8
Affiliations
Clinical Trial

Distinct Fecal and Plasma Metabolites in Children with Autism Spectrum Disorders and Their Modulation after Microbiota Transfer Therapy

Dae-Wook Kang et al. mSphere. .

Abstract

Accumulating evidence has strengthened a link between dysbiotic gut microbiota and autism. Fecal microbiota transplant (FMT) is a promising therapy to repair dysbiotic gut microbiota. We previously performed intensive FMT called microbiota transfer therapy (MTT) for children with autism spectrum disorders (ASD) and observed a substantial improvement of gastrointestinal and behavioral symptoms. We also reported modulation of the gut microbiome toward a healthy one. In this study, we report comprehensive metabolite profiles from plasma and fecal samples of the children who participated in the MTT trial. With 619 plasma metabolites detected, we found that the autism group had distinctive metabolic profiles at baseline. Eight metabolites (nicotinamide riboside, IMP, iminodiacetate, methylsuccinate, galactonate, valylglycine, sarcosine, and leucylglycine) were significantly lower in the ASD group at baseline, while caprylate and heptanoate were significantly higher in the ASD group. MTT drove global shifts in plasma profiles across various metabolic features, including nicotinate/nicotinamide and purine metabolism. In contrast, for 669 fecal metabolites detected, when correcting for multiple hypotheses, no metabolite was significantly different at baseline. Although not statistically significant, p-cresol sulfate was relatively higher in the ASD group at baseline, and after MTT, the levels decreased and were similar to levels in typically developing (TD) controls. p-Cresol sulfate levels were inversely correlated with Desulfovibrio, suggesting a potential role of Desulfovibrio on p-cresol sulfate modulation. Further studies of metabolites in a larger ASD cohort, before and after MTT, are warranted, as well as clinical trials of other therapies to address the metabolic changes which MTT was not able to correct.IMPORTANCE Despite the prevalence of autism and its extensive impact on our society, no U.S. Food and Drug Administration-approved treatment is available for this complex neurobiological disorder. Based on mounting evidences that support a link between autism and the gut microbiome, we previously performed a pioneering open-label clinical trial using intensive fecal microbiota transplant. The therapy significantly improved gastrointestinal and behavioral symptoms. Comprehensive metabolomic measurements in this study showed that children with autism spectrum disorder (ASD) had different levels of many plasma metabolites at baseline compared to those in typically developing children. Microbiota transfer therapy (MTT) had a systemic effect, resulting in substantial changes in plasma metabolites, driving a number of metabolites to be more similar to those from typically developing children. Our results provide evidence that changes in metabolites are one mechanism of the gut-brain connection mediated by the gut microbiota and offer plausible clinical evidence for a promising autism treatment and biomarkers.

Keywords: autism spectrum disorder (ASD); clinical trial; fecal microbiota transplant (FMT); gut bacteria; metabolites; microbiome; microbiota transplant therapy (MTT).

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Figures

FIG 1
FIG 1
Clinical trial timeline, principal-component analysis (PCA), and heat map profile with dendrogram with plasma and fecal samples at different time points. (a) The timeline consists of 10-week microbiota transfer therapy (MTT) and an 8-week follow-up observation period. (b and d) Seventy-three plasma metabolites whose levels were relatively different at baseline between two groups (unadjusted P < 0.05) were included in the PCA and heat map. (c) Distances from the ASD group to TD group were measured by pairwise PERMANOVA. In heat map profiles, the top line indicates diagnosis, with red for ASD and green for TD. The second line indicates time (pink, baseline; green, week 3; orange, week 10; blue, week 18). The colors for each point in the heat maps indicate either higher levels (red) or lower normalized relative intensity (blue). (d) Plasma metabolites in the heat map were clustered when their initial levels at baseline were higher (clusters 1 and 2) or lower (clusters 3, 4, and 5) at baseline and whether they increased/decreased (clusters 1, 3, and 4) or were maintained (clusters 2 and 5) after MTT. Clusters 1, 3, and 4 displayed metabolites whose levels generally became more similar to levels in TD samples after MTT at week 10, whereas metabolites in clusters 2 and 5 did not change significantly after treatment. The plasma metabolites discussed in the text are highlighted (red). (e and f) 26 fecal metabolites whose levels were relatively different at baseline between the two groups (unadjusted P < 0.05) were included in the PCA and heat map.
FIG 1
FIG 1
Clinical trial timeline, principal-component analysis (PCA), and heat map profile with dendrogram with plasma and fecal samples at different time points. (a) The timeline consists of 10-week microbiota transfer therapy (MTT) and an 8-week follow-up observation period. (b and d) Seventy-three plasma metabolites whose levels were relatively different at baseline between two groups (unadjusted P < 0.05) were included in the PCA and heat map. (c) Distances from the ASD group to TD group were measured by pairwise PERMANOVA. In heat map profiles, the top line indicates diagnosis, with red for ASD and green for TD. The second line indicates time (pink, baseline; green, week 3; orange, week 10; blue, week 18). The colors for each point in the heat maps indicate either higher levels (red) or lower normalized relative intensity (blue). (d) Plasma metabolites in the heat map were clustered when their initial levels at baseline were higher (clusters 1 and 2) or lower (clusters 3, 4, and 5) at baseline and whether they increased/decreased (clusters 1, 3, and 4) or were maintained (clusters 2 and 5) after MTT. Clusters 1, 3, and 4 displayed metabolites whose levels generally became more similar to levels in TD samples after MTT at week 10, whereas metabolites in clusters 2 and 5 did not change significantly after treatment. The plasma metabolites discussed in the text are highlighted (red). (e and f) 26 fecal metabolites whose levels were relatively different at baseline between the two groups (unadjusted P < 0.05) were included in the PCA and heat map.
FIG 1
FIG 1
Clinical trial timeline, principal-component analysis (PCA), and heat map profile with dendrogram with plasma and fecal samples at different time points. (a) The timeline consists of 10-week microbiota transfer therapy (MTT) and an 8-week follow-up observation period. (b and d) Seventy-three plasma metabolites whose levels were relatively different at baseline between two groups (unadjusted P < 0.05) were included in the PCA and heat map. (c) Distances from the ASD group to TD group were measured by pairwise PERMANOVA. In heat map profiles, the top line indicates diagnosis, with red for ASD and green for TD. The second line indicates time (pink, baseline; green, week 3; orange, week 10; blue, week 18). The colors for each point in the heat maps indicate either higher levels (red) or lower normalized relative intensity (blue). (d) Plasma metabolites in the heat map were clustered when their initial levels at baseline were higher (clusters 1 and 2) or lower (clusters 3, 4, and 5) at baseline and whether they increased/decreased (clusters 1, 3, and 4) or were maintained (clusters 2 and 5) after MTT. Clusters 1, 3, and 4 displayed metabolites whose levels generally became more similar to levels in TD samples after MTT at week 10, whereas metabolites in clusters 2 and 5 did not change significantly after treatment. The plasma metabolites discussed in the text are highlighted (red). (e and f) 26 fecal metabolites whose levels were relatively different at baseline between the two groups (unadjusted P < 0.05) were included in the PCA and heat map.
FIG 2
FIG 2
Correlation-based network analysis and correlation tests. Correlation-based network analysis with plasma metabolites associated with clinical assessment scores (highlighted in green) (a) and metabolite pairs that are significantly correlated with nicotinamide riboside and IMP (b). Blue and red lines between metabolites indicate positive and negative correlations, respectively (Spearman correlation coefficient |r| > 0.5). Rank-based plots to show strong correlations between GSRS and IMP (c) and PGI-R and methylsuccinate (d). P and r values are for rank-based Spearman correlation tests.
FIG 3
FIG 3
Correlation-based network analysis and correlation tests between fecal metabolites, clinical measurements, and bacterial components in stool. (a) Correlation-based network associated with p-cresol sulfate, clinical measurements, and key significant bacteria of Bifidobacterium, Prevotella, and Desulfovibrio. (b to d) Sulfate-reducing Desulfovibrio, p-cresol sulfate, and sulfate levels were significantly correlated (Spearman correlation, P < 0.005).
FIG 4
FIG 4
Possible metabolic features that microbiota transfer therapy (MTT) induced for the improvement on gastrointestinal and behavioral symptoms in children with ASD.
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