Evidence map›Paper›PMID 32986697›Full record

ArticlePLoS biology2020

High-coverage plasma lipidomics reveals novel sex-specific lipidomic fingerprints of age and BMI: Evidence from two large population cohort studies.

Habtamu B Beyene, Gavriel Olshansky, Adam Alexander T Smith, Corey Giles, Kevin Huynh, Michelle Cinel, Natalie A Mellett, Gemma Cadby, Joseph Hung, Jennie Hui and 6 more

Erratum issuedOpen access · goldAbstract readValidation Study
In one paragraph

Article in PLoS biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 101 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
101citing papers in PubMed, 1 pooled it
9.6field-weighted citation impact, top 1% 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

101 citing papers in PubMed, 1 synthesis or guideline pooled it, 159 citations in OpenAlex.

  1. Pooled it
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  6. Observational
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  18. [Gender differences in acylcarnitine metabolism among patients with depression disorder].Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025
    Article
  19. Review
  20. Review

41 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 4 institutions in 1 country.

Habtamu B BeyeneBaker Heart and Diabetes Institute, Melbourne, Australia.
Gavriel OlshanskyBaker Heart and Diabetes Institute, Melbourne, Australia.ORCID 0000-0002-5122-5547
Adam Alexander T SmithBaker Heart and Diabetes Institute, Melbourne, Australia.ORCID 0000-0003-4593-3042
Corey GilesBaker Heart and Diabetes Institute, Melbourne, Australia.ORCID 0000-0002-6050-1259
Kevin HuynhBaker Heart and Diabetes Institute, Melbourne, Australia.ORCID 0000-0001-6170-2207
Michelle CinelBaker Heart and Diabetes Institute, Melbourne, Australia.
Natalie A MellettBaker Heart and Diabetes Institute, Melbourne, Australia.
Gemma CadbySchool of Population and Global Health, University of Western Australia, Perth, Australia.
Joseph HungMedical School, Faculty of Health and Medical Sciences, University of Western Australia, Perth, Australia.
Jennie HuiSchool of Population and Global Health, University of Western Australia, Perth, Australia.
John BeilbyPathWest Laboratory Medicine of Western Australia, Nedlands, Western Australia.
Gerald F WattsMedical School, Faculty of Health and Medical Sciences, University of Western Australia, Perth, Australia.
Jonathan E ShawBaker Heart and Diabetes Institute, Melbourne, Australia.
Eric K MosesMenzies Institute for Medical Research, University of Tasmania, Tasmania, Australia.
Dianna J MaglianoBaker Heart and Diabetes Institute, Melbourne, Australia.
Peter J MeikleBaker Heart and Diabetes Institute, Melbourne, Australia.ORCID 0000-0002-2593-4665
Baker Heart and Diabetes Institute · AUThe University of Western Australia · AUPathwest Laboratory Medicine · AUUniversity of Tasmania · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obesity and related metabolic diseases show clear sex-related differences. The growing burden of these diseases calls for better understanding of the age- and sex-related metabolic consequences. High-throughput lipidomic analyses of population-based cohorts offer an opportunity to identify disease-risk-associated biomarkers and to improve our understanding of lipid metabolism and biology at a population level. Here, we comprehensively examined the relationship between lipid classes/subclasses and molecular species with age, sex, and body mass index (BMI). Furthermore, we evaluated sex specificity in the association of the plasma lipidome with age and BMI. Some 747 targeted lipid measures, representing 706 molecular lipid species across 36 classes/subclasses, were measured using a high-performance liquid chromatography coupled mass spectrometer on a total of 10,339 participants from the Australian Diabetes, Obesity and Lifestyle Study (AusDiab), with 563 lipid species being validated externally on 4,207 participants of the Busselton Health Study (BHS). Heat maps were constructed to visualise the relative differences in lipidomic profile between men and women. Multivariable linear regression analyses, including sex-interaction terms, were performed to assess the associations of lipid species with cardiometabolic phenotypes. Associations with age and sex were found for 472 (66.9%) and 583 (82.6%) lipid species, respectively. We further demonstrated that age-associated lipidomic fingerprints differed by sex. Specific classes of ether-phospholipids and lysophospholipids (calculated as the sum composition of the species within the class) were inversely associated with age in men only. In analyses with women alone, higher triacylglycerol and lower lysoalkylphosphatidylcholine species were observed among postmenopausal women compared with premenopausal women. We also identified sex-specific associations of lipid species with obesity. Lysophospholipids were negatively associated with BMI in both sexes (with a larger effect size in men), whilst acylcarnitine species showed opposing associations based on sex (positive association in women and negative association in men). Finally, by utilising specific lipid ratios as a proxy for enzymatic activity, we identified stearoyl CoA desaturase (SCD-1), fatty acid desaturase 3 (FADS3), and plasmanylethanolamine Δ1-desaturase activities, as well as the sphingolipid metabolic pathway, as constituent perturbations of cardiometabolic phenotypes. Our analyses elucidate the effect of age and sex on lipid metabolism by offering a comprehensive view of the lipidomic profiles associated with common cardiometabolic risk factors. These findings have implications for age- and sex-dependent lipid metabolism in health and disease and suggest the need for sex stratification during lipid biomarker discovery, establishing biological reference intervals for assessment of disease risk.

Indexed as

LipidomicsSex CharacteristicsAdultAgedAged, 80 and overAgingBody Mass IndexCohort StudiesFemaleHumansLipid MetabolismLipidsMaleMenopauseMiddle AgedObesityLipids

Identifiers

PMID32986697
PMCPMC7544135
OpenAlexW3088813603

What OpenQuestion 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 OpenQuestion graph.