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Record W4386804605 · doi:10.1038/s41467-023-41515-z

Plasma metabolomic profiles associated with mortality and longevity in a prospective analysis of 13,512 individuals

2023· article· en· W4386804605 on OpenAlexfundno aff
Fenglei Wang, Anne‐Julie Tessier, Liming Liang, Clemens Wittenbecher, Danielle E. Haslam, Gonzalo Fernández-Duval, A. Heather Eliassen, Kathryn M. Rexrode, Deirdre K. Tobias, Jun Li, Oana A. Zeleznik, Francine Grodstein, Miguel Ángel Martínez‐González, Jordi Salas‐Salvadó, Clary B. Clish, Kyu Ha Lee, Qi Sun, Meir J. Stampfer, Frank B. Hu, Marta Guasch‐Ferré

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsnot available
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute on AgingNational Institute of Diabetes and Digestive and Kidney DiseasesInstituto de Salud Carlos IIICenters for Disease Control and PreventionNational Institutes of HealthNational Heart, Lung, and Blood InstituteScience for Life LaboratoryChalmers Tekniska HögskolaBroad InstituteNational Cancer InstituteBrigham and Women's HospitalUniversidad de NavarraInstitut d'Investigació Sanitària Pere VirgiliRush UniversityHarvard T.H. Chan School of Public HealthNovo Nordisk FondenUniversitat Rovira i VirgiliNovo Nordisk Foundation Center for Basic Metabolic ResearchNovo NordiskCanadian Institutes of Health ResearchAmerican Heart Association
KeywordsLongevityMetabolomicsMedicineBiologyBioinformaticsComputational biologyGerontology

Abstract

fetched live from OpenAlex

Experimental studies reported biochemical actions underpinning aging processes and mortality, but the relevant metabolic alterations in humans are not well understood. Here we examine the associations of 243 plasma metabolites with mortality and longevity (attaining age 85 years) in 11,634 US (median follow-up of 22.6 years, with 4288 deaths) and 1878 Spanish participants (median follow-up of 14.5 years, with 525 deaths). We find that, higher levels of N2,N2-dimethylguanosine, pseudouridine, N4-acetylcytidine, 4-acetamidobutanoic acid, N1-acetylspermidine, and lipids with fewer double bonds are associated with increased risk of all-cause mortality and reduced odds of longevity; whereas L-serine and lipids with more double bonds are associated with lower mortality risk and a higher likelihood of longevity. We further develop a multi-metabolite profile score that is associated with higher mortality risk. Our findings suggest that differences in levels of nucleosides, amino acids, and several lipid subclasses can predict mortality. The underlying mechanisms remain to be determined.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.011
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.353
Teacher spread0.309 · 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 teacher head, 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".

Quick stats

Citations68
Published2023
Admission routes1
Has abstractyes

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