Andrea Baragetti,A. Alieva,Liliana Grigore,Fabio Pellegatta,Andrea Lupi,C. Scrimali,Angelo B. Cefalù,Barbara A. Hutten,Albert Wiegman,Paul Knaapen,Michiel J. Bom,Nick S. Nurmohamed,Olga Reutova,А. О. Конради,Е. V. Shlyakhto,Erik S.G. Stroes,Maurizio Averna,Alberico L. Catapano
Identification of individuals affected by familial hypercholesterolaemia (FH) is suboptimal when genetic tests are unavailable. Relying only on low-density lipoprotein cholesterol (LDL-C) is challenging as it may not allow distinguishing individuals with FH from hypercholesterolaemic (HC) individuals from the general population. The aim of this study was to determine whether biomarkers associated with cardiovascular disease and/or inflammation identify FH individuals and distinguish them from HC individuals. A panel of 264 proteins in plasma was measured and machine learning was used to search for those that can distinguish FH individuals, either genetically proven (genFH) or clinically diagnosed (clinFH) from HC and control individuals. Both genFH and clinFH had elevated plasma levels of fibroblast growth factor 5 (FGF-5) compared with controls (mean area under the curve [AUC] > .990 for both, P < .001) or HC individuals (mean AUC >.990, P < .001), even after matching for LDL-C levels. An immunoenzymatic assay confirmed that FGF-5 was elevated in genFH and clinFH in all cohorts analysed. This analysis suggests that FGF-5 could be a biomarker to discriminate individuals living with FH from HC individuals.