Genetic control of the HDL proteome

Nathalie Pamir; Calvin Pan; Deanna L. Plubell; Patrick M. Hutchins; Chongren Tang; Jake Wimberger; Angela Irwin; Thomas Q. de Aguiar Vallim; Jay W. Heinecke; Aldons J. Lusis

The classic linear view of HDL genesis from discoidal, lipid-poor nascent particles to spherical, cholesterol-and phospholipid-rich particles packed with a combination of over 100 different proteins has been recently challenged by the finding that HDL is secreted directly from hepatocytes in 4 distinct sizes, with little interchange between them, and representing all of the plasma HDL subparticle pools (Mendivil et al., 2016) . Although our analyses do not incorporate the lipidome of HDL which can contribute to the orchestration of the composition of HDL sub populations, and our samples weren't stored with a cryoprotectant (HDL structure, function and proteome can be affected and proteome under represented (Holzer et al, 2017) a highly inter correlated proteome reveals the complexity of HDL particle composition. We captured a remarkable 2216 correlations among the proteins that survived multiple comparison correction and that explains at least 25% of the variation (R2>0.25). The hierarchical clustering of the correlated proteins regrouped the proteins according to their biological functions emphasizing the coordinated co-regulation. However, while applying the stringent statistical approach certain biological relationships were missed. For example, APOC3 significantly and exclusively negatively correlated with 36 other HDL proteins (Supplementary Table 2 ). In humans, }increased circulating APOC3 levels are associated with cardiovascular disorders, inflammation, and insulin resistance (Chan et al., 2008; Petersen et al., 2010) . On the other hand, humans with an APOC3 mutation benefit from a favorable lipoprotein profile, increased insulin sensitivity, lower incidence of hypertension, and protection against cardiovascular diseases (Atzmon et al., 2006; Jørgensen et al., 2014; Pollin et al., 2008) . The negative correlation of APOC3 with 36 other proteins, its association with plasma insulin levels, and HOMA-IR levels conforms to its newly appreciated role as a brake on the metabolic system. Efforts to identify the proteomic, lipidomic, and functional fingerprints of HDL subspecies are of critical importance and may open paths to novel pharmacological targets. Clinical and epidemiological studies show a robust, inverse association between HDL cholesterol (HDL-C) levels and CHD risk (D. J. Gordon and Rifkind, 1989; Wilson et al., 1988) . However, pharmacological interventions aimed at raising HDL cholesterol levels in humans showed no cardiovascular benefits (AIM-HIGH Investigators et al., 2011; Barter et al., 2007; Landray et al., 2014; Schwartz et al., 2012) . Since the collapse of the HDL-C hypothesis for atherosclerosis, a new generation of HDL metrics are under investigation to be used in clinic (Fazio and Pamir, 2016) . For example, greater HDL cholesterol efflux capacity (CEC), independent of levels of HDL-C and APOA1 (the major structural protein of HDL), is associated with a lower prevalence of atherosclerotic vascular disease (Khera et al., 2011; Li et al., 2013; Rohatgi et al., 2014) . Most changes in HDL function are likely to be a reflection of changes in the HDL proteome (Green et al., 2008; Vaisar et al., 2007) . Thus, identification of the protein signature responsible for loss of sterol efflux capacity could provide biomarkers of clinical validity to assess CHD risk. The interplay between HDL sterol efflux function, particle concentration, size and HDL proteome is still poorly understood. HDL-C levels correlated strongly