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Record W4308543869 · doi:10.1101/2022.11.08.22282073

Evidence of a causal and modifiable relationship between kidney function and circulating trimethylamine <i>N</i> -oxide with implications for heart and kidney disorders

2022· preprint· en· W4308543869 on OpenAlexaff
Petros Andrikopoulos, Judith Aron‐Wisnewsky, Rima Chakaroun, Antonis Myridakis, Sofia K. Forslund, Trine Nielsen, Solia Adriouch, Bridget Holmes, Julien Chilloux, Sara Vieira‐Silva, Gwen Falony, Joe‐Elie Salem, Fabrizio Andreelli, Eugeni Belda, Julius Kieswich, Kanta Chechi, Francesc Puig‐Castellví, Mickaël Chevalier, Emmanuelle Le Chatelier, Michael Olanipekun, Lesley Hoyles, Renato Alves, Gérard Helft, Richard Isnard, Lars Køber, Luís Pedro Coelho, Christine Rouault, Dominique Gauguier, Jens Peter Gøtze, Edi Prifti, Jean‐Daniel Zucker, Fredrik Bäckhed, Henrik Vestergaard, Torben Hansen, Jean‐Michel Oppert, Matthias Blüher, Jens Nielsen, Jeroen Raes, Peer Bork, Muhammad Yaqoob, Michael Stümvoll, Oluf Pedersen, S. Dusko Ehrlich, Karine Clément, Marc‐Emmanuel Dumas

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsMcGill University and Génome Québec Innovation CentreMcGill Genome Centre
FundersInstitut de Cardiométabolisme et Nutrition
KeywordsTrimethylamine N-oxideRenal functionKidneyInternal medicineKidney diseaseMedicineEndocrinologyFibrosisMediationPhysiologyBiologyTrimethylamineBiochemistry

Abstract

fetched live from OpenAlex

Abstract Objectives The host-microbiota co-metabolite trimethylamine N -oxide (TMAO) is linked to increased thrombotic and cardiovascular risks. Here we, sought to i) characterize which host variables contribute to fasting serum TMAO levels in real-life settings ii) identify potential actionable therapeutic means related to circulating TMAO. Design We applied “explainable” machine learning, univariate-, multivariate- and mediation analyses of fasting plasma TMAO concentration and a multitude of bioclinical phenotypes in 1,741 adult Europeans of the MetaCardis study. We expanded and validated our epidemiological findings in mechanistic studies in human renal fibroblasts and a murine model of kidney fibrosis following TMAO exposure. Results Next to age, kidney function was the primary variable predicting circulating TMAO in MetaCardis, with microbiota composition and diet playing minor, albeit significant roles. Mediation analysis revealed a causal relationship between TMAO and kidney function decline that strengthened at more severe stages of cardiometabolic disease. We corroborated our findings in preclinical models where TMAO exposure augmented conversion of human renal fibroblasts into myofibroblasts and increased kidney scarring in vivo . Mechanistically, TMAO aggravated kidney fibrosis due to ERK1/2 hyperactivation synergistically with TGF-β1 signaling. Consistent with our findings, patients receiving next-generation glucose-lowering drugs with reno-protective properties, had significantly lower circulating TMAO when compared to propensity-score matched control individuals. Conclusion After age, kidney function is the major determinant of fasting circulating TMAO in adults. Our findings of lower TMAO levels in individuals medicated with reno-protective anti-diabetic drugs suggests a clinically actionable intervention for decreasing TMAO-associated excess cardiovascular risk that merits urgent investigation in human trials. Data availability statement Raw shotgun sequencing data that support the findings of this study have been deposited in the European Nucleotide Archive with accession codes PRJEB37249, PRJEB38742, PRJEB41311 and PRJEB46098. Serum NMR and urine NMR metabolome data have been uploaded to Metabolights with accession number MTBLS3429; serum GC-MS and isotopically quantified serum metabolites (UPLC–MS/MS) are available from MassIVE with accession numbers MSV000088042 and MSV000088043, respectively.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.092
GPT teacher head0.342
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations4
Published2022
Admission routes1
Has abstractyes

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