15289-s-bos

8 121 | Novel protein biomarker predictors of CAD in FH Keywords: • familial hypercholesterolaemia, • proteomics, • biomarkers, • atherosclerosis, • coronary artery disease Introduction Familial hypercholesterolemia (FH) is the most common and serious monogenic disorder of lipid metabolism 1, 2 with a worldwide prevalence of at least 1 in 300. 3 It is caused by mutations in the LDL receptor ( LDLR ) gene, the apolipoprotein B ( APOB ) gene, or the proprotein convertase subtilisin/kexin type 9 ( PCSK9 ) gene. 4-6 These mutations result in significantly elevated low-density lipoprotein (LDL) cholesterol levels that cause premature atherosclerotic coronary artery disease (CAD). 7 However, FH remains a frequently under diagnosed cause of CAD, and of those diagnosed, many are inadequately treated. 8 In addition, the incidence of CAD and life expectancy varies among patients with both treated and untreated FH. 9-11 Untreated, 50% of male FH patients and 20% of female FH patients develop fatal coronary heart disease by 60 years of age. While treatment with statins more than halves the risk of coronary events in adults with FH, 12 treated asymptomatic FHpatients display significant variability in the extent of subclinical coronary atherosclerosis despite the use of aggressive statin therapy. 9 Current known plasma biomarkers, in addition to classical risk factors, do not explain the residual CAD risk in people with FH. Indeed, the large variation in CAD incidence within the FH population suggests there are other factors, in addition to elevated cholesterol, that may play a role in development of atherosclerosis in FH. There is an urgent need for improved cardiovascular screening in asymptomatic individuals, however the development of novel markers to identify cardiovascular risk must add to the prognostic value provided by standard risk markers. 13, 14 Inthepastdecade,quantitativeproteomictechniquesincluding,isobarictagforrelative and absolute quantification (iTRAQ), have been used to identify novel biomarkers in several disease states, including CAD. 15,16 Using isotope labelledmolecules, iTRAQ allows for the quantification of multiple proteins from various sources, in a single experiment. 17 Previous iTRAQ studies have shown differences in expected CAD associated proteins,