Abstract
Helminth infections are consistently associated with reduced cardiovascular disease (CVD) risk, yet the biological mechanisms underlying this relationship remain unclear. The gut microbiome and metabolome are key regulators of cardiometabolic health and may mediate infection-associated effects on host physiology. Here we show that Schistosoma mansoni infection associates with distinct gut microbial and metabolic profiles linked to CVD risk in people living in Uganda. In a cross-sectional study of 209 individuals living in communities with contrasting S. mansoni endemicity, we profile the gut microbiome using 16S rRNA gene sequencing and the faecal metabolome using liquid chromatography–mass spectrometry. S. mansoni infection associates with increased gut microbial diversity and distinct taxonomic signatures, including enrichment of taxa such as Treponema and depletion of Prevotella and Streptococcus. Several infection-associated microbial taxa statistically mediate the relationships between S. mansoni infection and cardiovascular disease risk. Faecal metabolomic profiling identifies infection-associated metabolites, and integrative analyses showed linked microbe–metabolite networks associated with cardiovascular risk.These findings identify gut microbiome and metabolome signatures associated with S. mansoni infection and cardiovascular disease risk in Uganda. Although causality cannot be inferred, this work provides insight into host–parasite–microbiome interactions and highlights microbial and metabolic pathways relevant to cardiometabolic health.
Data availability
The raw microbiome sequencing data generated in this study have been deposited in the NCBI BioProject database under accession code PRJNA1405921. The raw mass spectrometry–based faecal metabolomics data, together with relevant experimental metadata, have been deposited in the Metabolomics Workbench repository under Study ID ST004547 (Data track ID: 6961 and are assigned the digital object identifier https://doi.org/10.21228/M8Z255. The processed microbiome and metabolomics data generated in this study have been deposited in the Zenodo repository under the (https://doi.org/10.5281/zenodo.18186512) (https://doi.org/10.5281/zenodo.18186512). This DOI represents all versions of the dataset and will always resolve to the most recent version. The repository includes raw 16S rRNA gene sequencing data, processed microbiome data (including taxonomy assignments and abundance tables), and processed faecal metabolomics data. The raw sequencing data are provided in accordance with participant consent and applicable data protection regulations. The de-identified individual participant data that underlie the results reported in this article, including demographic information and other covariates, together with a data dictionary are stored in the LSHTM Data Compass repository under (https://doi.org/10.17037/DATA.00004919). Researchers who wish to access these data may submit a request through LSHTM Data Compass, detailing the data requested, the intended use, and evidence of relevant experience. Requests will be reviewed by the corresponding author(s) in consultation with the MRC/UVRI and LSHTM Uganda Research Unit Data Management Committee, with oversight from the UVRI and LSHTM ethics committees. Approved datasets will be provided with pseudonymised participant identifiers, enabling linkage to the microbiome and metabolomics datasets while maintaining participant confidentiality. Access is subject to execution of an appropriate data sharing agreement. A reporting summary for this article is available as a Supplementary Information file.
Code availability
All scripts used for data processing, statistical analysis, and figure generation are available via Zenodo under the DOI 10.5281/zenodo.18186513 (https://doi.org/10.5281/zenodo.18186513).The analyses were performed using a combination of R and Python scripts together with established bioinformatics software for microbiome, metabolomics, and multi-omics integration analyses. A full list of all software packages used, including version numbers and their analytical purpose, is provided in the Supplementary Information.
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Acknowledgements
We are grateful to Dr Gyaviira Nkurunungi, Ms Joy Kabagenyi and Mr Alfred Ssekagiri for their expert comments on the manuscript. BW is partially supported by GCRF collaborative Grant (R120442) from the Royal Society awarded to Professors Richard Grencis and Alison Elliott, and is also partially funded by the National Institute for Health Research (NIHR) under its Global Health Research Group on Vaccines for Vulnerable People in Africa (VAnguard) (Grant Reference Number: NIHR134531), using UK aid from the UK Government to support global health research. This project has also been supported by Wellcome Trust Investigator Award Z10661/Z/18/Z and the Wellcome Centre for Cell Matrix Research Grant 088785/Z/09/Z awarded to Professor Richard Grencis, and Wellcome Trust (grant number 095778) awarded to Professor Alison Elliott. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK Government. The MRC/UVRI and LSHTM Uganda Research Unit is jointly funded by the UK Medical Research Council (MRC) and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement. The funders were not involved in the conceptualisation of the study, writing of the paper and the decision to submit it for publication.
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B.W. Conceived the study, designed the experiments, conducted the parasitological, microbiome and metabolomics conducted the primary statistics and bioinformatics analyses, interpreted the results, prepared the figures, and wrote the first draft of the manuscript. M.A.E.L. Contributed to the microbiome and metabolomics experiments and analyses and contributed to critical manuscript revision. A.J.B. supported the microbiome and metabolomics experiments, and manuscript draughting and revision. J.N. Contributed to the parasitological, microbiome and metabolomics experiments, and contributed to manuscript revision. D.K.T. Contributed to metabolomics data annotation and offered guidance on how metabolomics analysis was done. G.T. Provided specialist support in metabolomics experiments and pathway analysis contributed to critical manuscript review. R.E.S. Oversaw clinical coordination of parent projects, supported data acquisition, and provided critical input on the interpretation of the cardiovascular risk outcomes. E.L.W. Supervised statistical analysis for the study, advised on analytical strategy, and contributed to manuscript review and editing. D.P.K. Provided supervision of project, contributed to and reviewed the manuscript. R.K.G. provided senior supervision of the project, funding acquisition for this study, contributed to study conceptualisation and provided critical manuscript revisions. A.M.E. Provided senior supervision throughout the study, supported study design of the parent projects, funding acquisition of both the parent and current studies, advised on epidemiological methods, and contributed to critical revision of the manuscript. All authors reviewed and approved the final manuscript.
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Walusimbi, B., Lawson, M.A., Bancroft, A.J. et al. The gut microbiome and metabolome associate with Schistosoma mansoni infection and cardiovascular disease risk in Uganda. Nat Commun (2026). https://doi.org/10.1038/s41467-026-68983-3
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DOI: https://doi.org/10.1038/s41467-026-68983-3