tetano
Editor, Senior Moderator
Front Pediatr
. 2026 Sep 21:14:1881538.
doi: 10.3389/fped.2026.1881538. eCollection 2026.
J Agrimbau Vázquez # 1 2 , C Boggio Marzet # 2 3 , R Peralta # 4 5 , R Taussig 4 , P Lopez 6 , D Viale 1 , C Alonso 1 , T Curtti 1 , M L Perez Gagni 1 , M L Cassará 7 , L Urrutia 1 2 , J P Bustamante 4 5 8
Affiliations Expand
Background: Pediatric Inflammatory Multisystem Syndrome (PIMS), also known as MIS-C (Multisystem inflammatory syndrome in children), is a severe post-infectious inflammatory condition associated with SARS-CoV-2 in children. While coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, primarily affects the respiratory system, growing evidence highlights gastrointestinal involvement and the relevance of the gut-lung axis in systemic inflammation. However, the taxonomic and, particularly, the functional landscape of the gut microbiome in children with PIMS remains insufficiently characterized.
Methods: This exploratory study analyzed fecal samples from pediatric patients diagnosed with PIMS and age-matched clinically healthy controls using shotgun metagenomic sequencing. Taxonomic profiling was performed with MetaPhlAn4, and functional and metabolic pathway analyses were conducted using HUMAnN3. Alpha and beta diversity metrics were assessed, and differential abundance analyses were applied to identify microbial taxa and putative functional pathways associated with PIMS.
Results: 12 pediatric patients diagnosed with PIMS and 11 age-matched clinically healthy controls were included. Alpha diversity indices did not differ significantly between groups, although consistently lower mean values were observed in children with PIMS. In contrast, beta diversity analysis demonstrated a significant separation in microbial community composition between patients with PIMS and controls (PERMANOVA, p = 0.01). Children with PIMS exhibited increased relative abundance of Prevotella copri clade C, Duodenibacillus massiliensis, Phascolarctobacterium succinatutens, and Enterocloster bolteae, alongside a relative reduction of several commensal taxa. Putative functional profiling revealed significant differences in enzyme-coding genes and metabolic pathways, including increased metagenomic abundance of aconitate hydratase and other functions potentially relevant to inflammatory and immunomodulatory processes in the PIMS group.
Conclusion: These findings suggest an association between gut microbiota unbalance, potential microbial functional alterations, and PIMS, supporting the need for further investigation of the gut microbiome in post-COVID-19 systemic inflammation in pediatric populations. Given the exploratory nature of this study, these observations require validation in larger, longitudinal cohorts before microbial biomarkers or therapeutic implications can be established.
Keywords: COVID-19; MIS-C; PIMS; SARS-CoV-2; gut microbiota; gut–lung axis; metagenomics; pediatric inflammatory multisystem syndrome.
. 2026 Sep 21:14:1881538.
doi: 10.3389/fped.2026.1881538. eCollection 2026.
Altered gut microbial functional landscape in children with pediatric inflammatory multisystem syndrome following SARS-CoV-2 infection: an exploratory metagenomic study
J Agrimbau Vázquez # 1 2 , C Boggio Marzet # 2 3 , R Peralta # 4 5 , R Taussig 4 , P Lopez 6 , D Viale 1 , C Alonso 1 , T Curtti 1 , M L Perez Gagni 1 , M L Cassará 7 , L Urrutia 1 2 , J P Bustamante 4 5 8
Affiliations Expand
- PMID: 42836017
- PMCID: PMC13636897
- DOI: 10.3389/fped.2026.1881538
Abstract
Background: Pediatric Inflammatory Multisystem Syndrome (PIMS), also known as MIS-C (Multisystem inflammatory syndrome in children), is a severe post-infectious inflammatory condition associated with SARS-CoV-2 in children. While coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, primarily affects the respiratory system, growing evidence highlights gastrointestinal involvement and the relevance of the gut-lung axis in systemic inflammation. However, the taxonomic and, particularly, the functional landscape of the gut microbiome in children with PIMS remains insufficiently characterized.
Methods: This exploratory study analyzed fecal samples from pediatric patients diagnosed with PIMS and age-matched clinically healthy controls using shotgun metagenomic sequencing. Taxonomic profiling was performed with MetaPhlAn4, and functional and metabolic pathway analyses were conducted using HUMAnN3. Alpha and beta diversity metrics were assessed, and differential abundance analyses were applied to identify microbial taxa and putative functional pathways associated with PIMS.
Results: 12 pediatric patients diagnosed with PIMS and 11 age-matched clinically healthy controls were included. Alpha diversity indices did not differ significantly between groups, although consistently lower mean values were observed in children with PIMS. In contrast, beta diversity analysis demonstrated a significant separation in microbial community composition between patients with PIMS and controls (PERMANOVA, p = 0.01). Children with PIMS exhibited increased relative abundance of Prevotella copri clade C, Duodenibacillus massiliensis, Phascolarctobacterium succinatutens, and Enterocloster bolteae, alongside a relative reduction of several commensal taxa. Putative functional profiling revealed significant differences in enzyme-coding genes and metabolic pathways, including increased metagenomic abundance of aconitate hydratase and other functions potentially relevant to inflammatory and immunomodulatory processes in the PIMS group.
Conclusion: These findings suggest an association between gut microbiota unbalance, potential microbial functional alterations, and PIMS, supporting the need for further investigation of the gut microbiome in post-COVID-19 systemic inflammation in pediatric populations. Given the exploratory nature of this study, these observations require validation in larger, longitudinal cohorts before microbial biomarkers or therapeutic implications can be established.
Keywords: COVID-19; MIS-C; PIMS; SARS-CoV-2; gut microbiota; gut–lung axis; metagenomics; pediatric inflammatory multisystem syndrome.