Evidence map›Paper›PMID 41912555›Full record

ArticleNature communications2026

Lipidomic analyses of large cohort studies define the role of lipid metabolism in bridging diet and cardio-metabolic health.

Habtamu B Beyene, Tingting Wang, Michelle Cinel, Natalie A Mellett, Thy Duong, Matilda van Buuren-Milne, Alexandra N Faulkner, Jingqin Wu, Gavriel Olshansky, Jonathan E Shaw and 7 more

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Habtamu B BeyeneBaker Heart and Diabetes Institute, Melbourne, VIC, Australia.ORCID http://orcid.org/0000-0001-7075-6629
Tingting WangBaker Heart and Diabetes Institute, Melbourne, VIC, Australia.
Michelle CinelBaker Heart and Diabetes Institute, Melbourne, VIC, Australia.
Natalie A MellettBaker Heart and Diabetes Institute, Melbourne, VIC, Australia.
Thy DuongBaker Heart and Diabetes Institute, Melbourne, VIC, Australia.ORCID http://orcid.org/0000-0002-2521-078X
Matilda van Buuren-MilneBaker Heart and Diabetes Institute, Melbourne, VIC, Australia.
Alexandra N FaulknerBaker Heart and Diabetes Institute, Melbourne, VIC, Australia.
Jingqin WuBaker Heart and Diabetes Institute, Melbourne, VIC, Australia.ORCID http://orcid.org/0000-0002-2052-3875
Gavriel OlshanskyBaker Heart and Diabetes Institute, Melbourne, VIC, Australia.ORCID http://orcid.org/0000-0002-5122-5547
Jonathan E ShawBaker Heart and Diabetes Institute, Melbourne, VIC, Australia.ORCID http://orcid.org/0000-0002-6187-2203
Dianna J MaglianoBaker Heart and Diabetes Institute, Melbourne, VIC, Australia.ORCID http://orcid.org/0000-0002-9507-6096
Melissa C SouthyPrecision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.ORCID http://orcid.org/0000-0002-6313-9005
Roger L MilnePrecision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.ORCID http://orcid.org/0000-0001-5764-7268
Allison M HodgeCancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia.ORCID http://orcid.org/0000-0001-5464-2197
Corey GilesBaker Heart and Diabetes Institute, Melbourne, VIC, Australia.ORCID http://orcid.org/0000-0002-6050-1259
Kevin HuynhBaker Heart and Diabetes Institute, Melbourne, VIC, Australia. kevin.huynh@baker.edu.au.ORCID http://orcid.org/0000-0001-6170-2207
Peter J MeikleBaker Heart and Diabetes Institute, Melbourne, VIC, Australia. peter.meikle@baker.edu.au.ORCID http://orcid.org/0000-0002-2593-4665

Funding

Department of Health | National Health and Medical Research Council (NHMRC) 1074383Department of Health | National Health and Medical Research Council (NHMRC) 396414Department of Health | National Health and Medical Research Council (NHMRC) APP1101320
6 · The paper itself

Abstract

Diet is a key factor for many diseases, yet the underlying metabolic pathways involved remain poorly understood. We analyze data from 13,335 participants across two large Australian cohorts examining comprehensive lipidomic profiles in relation to diet. We also assess the link between metabolic signatures of dietary quality with cardiometabolic health and all-cause mortality. Here, using linear models and lipid set enrichment analysis, we report characteristic lipidomic profiles associated with dairy [sphingomyelins and lipids esterified with 14:0, 15:0, 17:0 or 17:1 fatty acid], red meat and poultry [alkyl- and alkenyl-phosphatidylcholine and phosphatidylethanolamine notably, with arachidonic acid], and fish intake [higher 22:6, and lower 22:4 fatty acids]. In a Cox proportional hazard regression, metabolic signatures of diet quality showed inverse associations with all-cause mortality with hazard ratios (95% confidence intervals) of 0.89 (0.84-0.93), 0.87 (0.83-0.92), and 0.88 (0.84-0.93) for the Australian Dietary Guideline Index (DGI), the Global Diet Quality Score (DGQS), and the Mediterranean-DASH (Dietary Approaches to Stop Hypertension) Intervention for Neurodegenerative Delay (MIND) score, respectively. Additionally, the intake of nuts (β = -0.07, p = 7.92 × 10⁻¹⁸) and the MIND score (β = -0.07, p = 1.51 × 10⁻¹⁸) were inversely associated with CVD risk. Our data provide new insights into how dietary exposure relates to lipid metabolism and metabolic health, opening avenues for future mechanistic studies and dietary interventions that can inform targeted strategies for the prevention of cardiometabolic diseases.

Indexed as

Cardiovascular DiseasesDietLipid MetabolismLipidomicsAnimalsAustraliaCohort StudiesFemaleHumansMaleProportional Hazards Models

Identifiers

PMID41912555
PMCPMC13199559

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.