• Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, Maryland, United States of America.
• Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, Maryland, United States of America; Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France.
• Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, Maryland, United States of America.
• Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland.
• Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, Maryland, United States of America. Electronic address: rs221z@nih.gov.

BACKGROUND: Higher dietary quality is associated with lower disease risks and has not been examined extensively with lipidomic profiles.

OBJECTIVE: Our goal was to examine associations of the Healthy Eating Index (HEI)-2015, Alternate HEI-2010 (AHEI-2010), and alternate Mediterranean Diet Index (aMED) diet quality indices with serum lipidomic profiles.

METHODS: We conducted a cross-sectional analysis of HEI-2015, AHEI-2010 and aMED with lipidomic profiles from two nested case-control studies within the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO, n=627) and the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (ATBC, n=711). We used multivariable linear regression to determine associations of the indices, derived from baseline food frequency questionnaires (PLCO:1993-2001, ATBC:1985-1988) with serum concentrations of 904 lipid species and 252 fatty acids (FA) across 15 lipid classes and 28 total FAs, within each cohort and meta-analyzed results using fixed-effect models for lipids significant at Bonferroni-corrected threshold in common in both cohorts.

RESULTS: Adherence to HEI-2015, AHEI-2010 or aMED was associated positively with 31, 41, and 54 lipid species and 8, 6 and 10 class-specific FAs and inversely with 2, 8 and 34 lipid species and 1, 3 and 5 class-specific FAs, respectively. Twenty-five lipid species and 5 class-specific FAs were common to all indices, predominantly triacylglycerols, FA22:6 (docosahexaenoic acid [DHA])-containing species, and DHA. All indices were positively associated with total FA22:6. AHEI-2010 and aMED were inversely associated with total FA18:1 (oleic acid) and total FA17:0 (margaric acid), respectively. The identified lipids were most associated with components of seafood and plant proteins and unsaturated:saturated fat ratio in HEI-2015; eicosapentaenoic acid (EPA) plus DHA in AHEI-2010; and fish and monounsaturated:saturated fat ratio in aMED.

CONCLUSIONS: Adherence to HEI-2015, AHEI-2010 and aMED are associated with serum lipidomic profiles, mostly triacylglycerols or FA22:6-containing species, which are related to seafood and plant proteins, EPA-DHA, fish, or fat ratio index components.