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Combinatorial, additive and dose-dependent drug-microbiome associations
Sofia K Forslund1,2,3,4,5,6, Rima Chakaroun7, Maria Zimmermann-Kogadeeva1
1Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
Nature
|December 9, 2021
Summary
Medications significantly alter the gut microbiome and host features more than cardiometabolic disease itself. Combined drug therapies can improve metabolome and microbiome health, offering new insights into drug-host-microbiome interactions.
Area of Science:
- Microbiome research
- Pharmacogenomics
- Metabolomics
Background:
- Cardiometabolic disease progression is linked to altered gut microbiome and metabolome.
- Heavy medication use in patients complicates biomarker discovery.
- Understanding drug effects on host-microbiome interactions is crucial.
Purpose of the Study:
- To disentangle the effects of drugs versus disease on host and gut microbiome features.
- To quantify the impact of single medications, combinations, and additive effects.
- To identify drug-host-microbiome signatures in cardiometabolic disease.
Main Methods:
- Integrated multi-omics analyses of 2,173 European residents (MetaCardis cohort).
- Computational framework to infer drug effects on host and microbiome variability.
- Quantification of medication effects, including combinations and additive impacts.
Main Results:
- Drug effects on host and microbiome variability exceed those of disease.
- Additive drug effects shift metabolome and microbiome towards a healthier state.
- Antibiotic use correlates with microbiome changes associated with cardiometabolic disease severity.
- Drug dosage shows a relationship with clinical marker improvement and microbiome composition.
Conclusions:
- A computational framework is presented to disentangle drug and disease effects in multimedicated individuals.
- Identified signatures offer new hypotheses for drug-host-microbiome interactions in cardiometabolic disease.
- Medications play a significant role in shaping the host-microbiome axis during disease progression.
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