Please use this identifier to cite or link to this item: https://repository.monashhealth.org/monashhealthjspui/handle/1/58102
Title: Lipidomic analyses of large cohort studies define the role of lipid metabolism in bridging diet and cardio-metabolic health.
Authors: Beyene H.B.;Wang T.;Cinel M.;Mellett N.A.;Duong T.;Buuren-Milne M.V.;Faulkner A.N.;Wu J.;Olshansky G.;Shaw J.E.;Magliano D.J.;Southy M.C.;Milne R.L.;Hodge A.M.;Giles C.;Huynh K.;Meikle P.J.
Monash Health Department(s): Monash University - School of Clinical Sciences at Monash Health
Institution: (Beyene, Wang, Cinel, Mellett, Duong, Buuren-Milne, Faulkner, Wu, Olshansky, Shaw, Magliano, Giles, Huynh, Meikle) Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
(Southy, Milne, Hodge) Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia
(Southy, Milne, Hodge) Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia
(Shaw, Magliano, Southy, Milne, Meikle) Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia
(Beyene, Wang, Wu, Olshansky, Giles, Huynh, Meikle) Baker Department of Cardiometabolic Health, Melbourne University, Melbourne, VIC, Australia
(Beyene, Wang, Giles, Huynh, Meikle) Baker Department of Cardiovascular Research, Translation and Implementation, La Trobe University, Melbourne, VIC, Australia
Issue Date: 8-Apr-2026
Copyright year: 2026
Place of publication: United Kingdom
Publication information: Nature communications. (no pagination), 2026. Date of Publication: 30 Mar 2026.
Journal: Nature communications
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 (beta = -0.07, p = 7.92 x 10-18) and the MIND score (beta = -0.07, p = 1.51 x 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.Copyright © 2026. The Author(s).
DOI: https://dx.doi.org/10.1038/s41467-026-71133-4
PubMed URL: 41912555
URI: https://repository.monashhealth.org/monashhealthjspui/handle/1/58102
Type: Article In Press
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