Evidence map›Paper›PMID 30799310›Full record

ArticleAging2019

Longitudinal plasma metabolomics of aging and sex.

Burcu F Darst, Rebecca L Koscik, Kirk J Hogan, Sterling C Johnson, Corinne D Engelman

Open access · greenAbstract read
In one paragraph

Article in Aging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 140 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
140citing papers in PubMed, 1 pooled it
8.6field-weighted citation impact, top 2% of its field
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

140 citing papers in PubMed, 1 synthesis or guideline pooled it, 192 citations in OpenAlex.

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  18. The selenium-enrichedFrontiers in microbiology · 2026
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80 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Burcu F DarstDepartment of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI 53726, USA.
Rebecca L KoscikWisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Madison, WI 53726, USA.
Kirk J HoganWisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Madison, WI 53726, USA.
Sterling C JohnsonWisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Madison, WI 53726, USA.
Corinne D EngelmanDepartment of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI 53726, USA.
University of Wisconsin–Madison · USWilliam S. Middleton Memorial Veterans Hospital · US

Funding

University of Wisconsin Institute for Clinical and Translational ResearchUL1TR002373 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI ELIZABETH S BURNSIDE, Allan R. Brasier · 2017 to 2026
$75.9M
Wisconsin Registry for Alzheimer's Prevention: Sex Differences in DNA MethylationR01AG027161 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Nathaniel Ark Chin, Sterling C Johnson · 2007 to 2026
$35.6M
Institutional Clinical and Translational Science AwardUL1TR000427 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2012 to 2016
$32.2M
Research Training for Computation and Informatics in Biology and MedicineT15LM007359 · NLM · UNIVERSITY OF WISCONSIN-MADISON · PI Mark W. Craven, Colin Noel Dewey · 2002 to 2026
$22.6M
Wisconsin Registry for Alzheimer's PreventionRF1AG027161 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI JOHNSON, STERLING C · 2018 to 2018
$18.8M
Wisconsin Alzheimer's Disease Research CenterP50AG033514 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI HART, MICHAEL N · 2009 to 2018
$16.2M
Scientific and Technical CoreP2CHD047873 · NICHD · UNIVERSITY OF WISCONSIN-MADISON · PI Katherine J. Curtis · 2014 to 2026
$5.1M
Genomic and Metabolomic Data Integration in a Longitudinal Cohort at Risk for Alzheimer's DiseaseR01AG054047 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI ENGELMAN, CORINNE D. · 2016 to 2020
$3.6M
NCATS NIH HHS UL1 TR000427NCATS NIH HHS UL1 TR002373NIA NIH HHS P50 AG033514NIA NIH HHS R01 AG027161NIA NIH HHS R01 AG054047NIA NIH HHS RF1 AG027161NICHD NIH HHS P2C HD047873NLM NIH HHS T15 LM007359
6 · The paper itself

Abstract

Understanding how metabolites are longitudinally influenced by age and sex could facilitate the identification of metabolomic profiles and trajectories that indicate disease risk. We investigated the metabolomics of age and sex using longitudinal plasma samples from the Wisconsin Registry for Alzheimer's Prevention (WRAP), a cohort of participants who were dementia free at enrollment. Metabolomic profiles were quantified for 2,344 fasting plasma samples among 1,212 participants, each with up to three study visits. Of 1,097 metabolites tested, 623 (56.8%) were associated with age and 695 (63.4%) with sex after correcting for multiple testing. Approximately twice as many metabolites were associated with age in stratified analyses of women versus men, and 68 metabolite trajectories significantly differed by sex, most notably including sphingolipids, which tended to increase in women and decrease in men with age. Using genome-wide genotyping, we also report the heritabilities of metabolites investigated, which ranged dramatically (0.2-99.2%); however, the median heritability of 36.2% suggests that many metabolites are highly influenced by a complex combination of genomic and environmental influences. These findings offer a more profound description of the aging process and may inform many new hypotheses regarding the role metabolites play in healthy and accelerated aging.

Indexed as

MetabolomicsAgedAgingCohort StudiesFemaleHumansLongitudinal StudiesMaleMiddle AgedSex Characteristicsaginggenomicsheritabilitylipidomicsmetabolomicssex

Identifiers

PMID30799310
PMCPMC6402508
OpenAlexW2949617913

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.