Evidence map›Paper›PMID 40440492›Full record

ArticleAging2025

Methods for joint modeling of longitudinal omics data and time-to-event outcomes: applications to lysophosphatidylcholines in connection to aging and mortality in the Long Life Family Study.

Konstantin G Arbeev, Olivia Bagley, Svetlana V Ukraintseva, Alexander Kulminski, Eric Stallard, Michaela Schwaiger-Haber, Gary J Patti, Yian Gu, Anatoliy I Yashin, Michael A Province

Abstract read
In one paragraph

Article in Aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Embracing non-linearity in human ageing.Nature reviews. Genetics · 2026
    Review
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Konstantin G ArbeevBiodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27708, USA.
Olivia BagleyBiodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27708, USA.
Svetlana V UkraintsevaBiodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27708, USA.
Alexander KulminskiBiodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27708, USA.
Eric StallardBiodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27708, USA.
Michaela Schwaiger-HaberDepartment of Chemistry, Washington University in St. Louis, St. Louis, MO 63130, USA.
Gary J PattiDepartment of Chemistry, Washington University in St. Louis, St. Louis, MO 63130, USA.
Yian GuTaub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA.
Anatoliy I YashinBiodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27708, USA.
Michael A ProvinceDivision of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA.

Funding

The Long Life Family StudyU19AG063893 · NIA · WASHINGTON UNIVERSITY · PI PAOLA SEBASTIANI · 2019 to 2026
$125.4M
Washington University Nutrition Obesity Research CenterP30DK056341 · NIDDK · WASHINGTON UNIVERSITY · PI Dominic N Reeds · 1999 to 2026
$30.2M
NIA NIH HHS U19 AG063893NIDDK NIH HHS P30 DK056341
6 · The paper itself

Abstract

Studying the relationships between longitudinal changes in omics variables and event risks requires specific methodologies for joint analyses of longitudinal and time-to-event outcomes. We applied two such approaches (joint models [JM], stochastic process models [SPM]) to longitudinal metabolomics data from the Long Life Family Study, focusing on the understudied associations of longitudinal changes in lysophosphatidylcholines (LPCs) with mortality and aging-related outcomes. We analyzed 23 LPC species, with 5,066 measurements of each in 3,462 participants, 1,245 of whom died during follow-up. JM analyses found that higher levels of the majority of LPC species were associated with lower mortality risks, with the largest magnitude observed for LPC 15:0/0:0 (hazard ratio: 0.71, 95% CI (0.64, 0.79)). SPM applications to LPC 15:0/0:0 revealed that the JM association reflects underlying aging-related processes: a decline in robustness to deviations from optimal LPC levels, higher equilibrium LPC levels in females, and the opposite age-related changes in the equilibrium and optimal LPC levels (declining and increasing, respectively), which lead to increased mortality risks with age. Our results support LPCs as biomarkers of aging and related decline in biological robustness, and call for further exploration of factors underlying age-related changes in LPC in relation to mortality and diseases.

Indexed as

AgingLongevityLysophosphatidylcholinesMetabolomicsMortalityAgedAged, 80 and overBiomarkersFemaleHumansLongitudinal StudiesMaleMiddle AgedBiomarkersLysophosphatidylcholinesaginglongitudinal omicslysophosphatidylcholinesmortalityrepeated measurements

Identifiers

PMID40440492
PMCPMC12151508

What Socratic holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.