Evidence map›Paper›PMID 37697054›Full record

ArticleNature metabolism2023

Dynamic lipidome alterations associated with human health, disease and ageing.

Daniel Hornburg, Si Wu, Mahdi Moqri, Xin Zhou, Kevin Contrepois, Nasim Bararpour, Gavin M Traber, Baolong Su, Ahmed A Metwally, Monica Avina and 7 more

Registry-linked trialAbstract read
In one paragraph

Article in Nature metabolism, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07602023 (Triglyceride-rich LIPoproteins and INflammatory Cytokines After Oral FAT Loading as Potential Early Biomarkers of the Risk of Progression Towards DIABETES and Development of Complications. LIPINFAT Diabetes Study.), which is not on this map. Cited by 149 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
149citing papers in PubMed, 2 pooled it
–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.

NCT07602023 recruitingnot on this mapstarted 2024, after this paper: background citation

Triglyceride-rich LIPoproteins and INflammatory Cytokines After Oral FAT Loading as Potential Early Biomarkers of the Risk of Progression Towards DIABETES and Development of Complications. LIPINFAT Diabetes Study.

TypeobservationalSponsorAngelina PassaroRan2024 to 2028Enrolled150ConditionsPrediabetes / Type 2 DiabetesArmsOral Fat Load Test
3 · Its place in the literature

Who cites it

149 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  6. A targeted lipidomics workflow for high-throughput phenotyping and mechanism-based in vitro hepatotoxicity studies.Toxicology in vitro : an international journal published in association with BIBRA · 2026
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89 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

17 authors.

Daniel Hornburg *Department of Genetics, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-6618-7774
Si Wu *Department of Genetics, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-8050-7167
Mahdi MoqriDepartment of Genetics, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-6675-0566
Xin ZhouDepartment of Genetics, Stanford University, Stanford, CA, USA.
Kevin ContrepoisDepartment of Genetics, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-9678-5161
Nasim BararpourDepartment of Genetics, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-6244-8781
Gavin M TraberDepartment of Genetics, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-3494-9196
Baolong SuDepartment of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Ahmed A MetwallyDepartment of Genetics, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-0155-7412
Monica AvinaDepartment of Genetics, Stanford University, Stanford, CA, USA.
Wenyu ZhouDepartment of Genetics, Stanford University, Stanford, CA, USA.
Jessalyn M UbellackerDepartment of Genetics, Stanford University, Stanford, CA, USA.
Tejaswini MishraDepartment of Genetics, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-9931-1260
Sophia Miryam Schüssler-Fiorenza RoseDepartment of Genetics, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-6311-6671
Paula B KavathasDepartments of Laboratory Medicine and Immunobiology, Yale School of Medicine, New Haven, CT, USA.ORCID http://orcid.org/0000-0001-9371-152X
Kevin J WilliamsDepartment of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Michael P SnyderDepartment of Genetics, Stanford University, Stanford, CA, USA. mpsnyder@stanford.edu.ORCID http://orcid.org/0000-0003-0784-7987

Funding

Stanford Medicine Center for Longevity and Healthy Aging Research Education CoreP30AG059307 · NIA · STANFORD UNIVERSITY · PI ZOU, JAMES · 2018 to 2025
$4.9M
Integrating the Exposome into Longitudinal Multiomics ProfilingK08ES028825 · NIEHS · STANFORD UNIVERSITY · PI ROSE, SOPHIA MIRYAM SCHÜSSLER-FIORENZA · 2018 to 2022
$1.0M
NIA NIH HHS P30 AG059307NIEHS NIH HHS K08 ES028825
6 · The paper itself

Abstract

Lipids can be of endogenous or exogenous origin and affect diverse biological functions, including cell membrane maintenance, energy management and cellular signalling. Here, we report >800 lipid species, many of which are associated with health-to-disease transitions in diabetes, ageing and inflammation, as well as cytokine-lipidome networks. We performed comprehensive longitudinal lipidomic profiling and analysed >1,500 plasma samples from 112 participants followed for up to 9 years (average 3.2 years) to define the distinct physiological roles of complex lipid subclasses, including large and small triacylglycerols, ester- and ether-linked phosphatidylethanolamines, lysophosphatidylcholines, lysophosphatidylethanolamines, cholesterol esters and ceramides. Our findings reveal dynamic changes in the plasma lipidome during respiratory viral infection, insulin resistance and ageing, suggesting that lipids may have roles in immune homoeostasis and inflammation regulation. Individuals with insulin resistance exhibit disturbed immune homoeostasis, altered associations between lipids and clinical markers, and accelerated changes in specific lipid subclasses during ageing. Our dataset based on longitudinal deep lipidome profiling offers insights into personalized ageing, metabolic health and inflammation, potentially guiding future monitoring and intervention strategies.

Indexed as

Insulin ResistanceAgingCeramidesHumansInflammationLipidomicsCeramides

Identifiers

PMID37697054
PMCPMC10513930

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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 OpenQuestion graph.