Extended Data Fig. 8: Conditional independence network and clusters of all MLS lipids.
The network was derived using the PC-algorithm in the EPIC-Potsdam subcohort (n = 1,262) based on the lipids in the MLS. The nodes in this network correspond to the UFA-rich diet-affected lipids, and links correspond to correlations between a lipid pair that are robust against adjustment for any subset of other network lipids. Many links in this data-driven network connect lipid metabolites that contain the same fatty acid residual but belong to different lipid classes (for example, C12:0 in cholesteryl esters, phosphatidylcholines, triglycerides, and diglycerides; C18:0 in ceramides and hexosylceramides) or lipids of the same class with metabolically related fatty acid residuals (for example, C20:1 and C22:1 hexosylceramides). Based on this network, we used the Louvain modularity detection algorithm to derive data-driven lipid clusters. Cluster 1 was enriched in odd- and short-chain acyl chain-containing cholesterol esters and phospholipids. Cluster 2 mainly featured di- and triglycerides. Cluster 3 was primarily composed of medium to long-chain fatty acid-containing ceramides (including dihydro-, lactosyl-, and hexosyl-ceramides). Cluster 4 was primarily composed of medium to long-chain fatty acid-containing ceramides (including dihydro-, lactosyl-, and hexosyl-ceramides). Cluster 5 was dominated by phosphatidylethanolamines (including those with ether bonds). Abbreviations – MLS: multi-lipid score; HR, hazard ratio; UFA: unsaturated fatty acids; CVD: cardiovascular disease; T2D: type 2 diabetes.
