Impact of methods used to express levels of circulating fatty acids on the degree and direction of associations with blood lipids in humans. Issue 2 (30th November 2015)

• Record Type: Journal Article
• Authors: Sergeant, Susan; Ruczinski, Ingo; Ivester, Priscilla; Lee, Tammy C.; Morgan, Timothy M.; Nicklas, Barbara J.; Mathias, Rasika A.; Chilton, Floyd H.
• Is Part Of: British journal of nutrition. Volume 115:Issue 2(2016)
• Page Start: 251
• Page End: 261
• Publication Date: 2015-11-30
• Subjects: PUFA, -- Lipid biomarkers, -- Linoleic acid, -- Arachidonic acid; Nutrition -- Periodicals; 572.4
• DOI: 10.1017/S0007114515004341
• Languages: English
• ISSNs: 0007-1145

Abstract

Abstract: Numerous studies have examined relationships between disease biomarkers (such as blood lipids) and levels of circulating or cellular fatty acids. In such association studies, fatty acids have typically been expressed as the percentage of a particular fatty acid relative to the total fatty acids in a sample. Using two human cohorts, this study examined relationships between blood lipids (TAG, and LDL, HDL or total cholesterol) and circulating fatty acids expressed either as a percentage of total or as concentration in serum. The direction of the correlation between stearic acid, linoleic acid, dihomo- γ -linolenic acid, arachidonic acid and DHA and circulating TAG reversed when fatty acids were expressed as concentrations v . a percentage of total. Similar reversals were observed for these fatty acids when examining their associations with the ratio of total cholesterol:HDL-cholesterol. This reversal pattern was replicated in serum samples from both human cohorts. The correlations between blood lipids and fatty acids expressed as a percentage of total could be mathematically modelled from the concentration data. These data reveal that the different methods of expressing fatty acids lead to dissimilar correlations between blood lipids and certain fatty acids. This study raises important questions about how such reversals in association patterns impact the interpretation of numerous association studies evaluating fatty acids and their relationships with disease biomarkers or risk.