METHODS: The FIBRO-TARGETS (targeting cardiac fibrosis for heart failure treatment) consortium has merged data from 12 patient cohorts in 1 common database of > 12,000 patients. Three mutually exclusive main phenotypic groups were identified (\"cases\"): (1) \"hypertensive\"; (2) \"obese\"; and (3) \"diabetic\"; age-sex matched in a 1:2 proportion with \"healthy controls\" without any of these phenotypes. Proteomic associations were studied using a biostatistical method based on LASSO and confronted with machine-learning and complex network approaches.
RESULTS: The case:control distribution by each cardiovascular phenotype was hypertension (50:100), obesity (50:98), and diabetes (36:72). Of the 86 studied proteins, 4 were found to be independently associated with hypertension: GDF-15, LEP, SORT-1 and FABP-2; 3 with obesity: CEACAM-8, LEP and PRELP; and 4 with diabetes: GDF-15, REN, CXCL-1 and SCF. GDF-15 (hypertension + diabetes) and LEP (hypertension + obesity) are shared by 2 different phenotypes. A machine-learning approach confirmed GDF-15, LEP and SORT-1 as discriminant biomarkers for the hypertension group, and LEP plus PRELP for the obesity group. Complex network analyses provided insight on the mechanisms underlying these disease phenotypes where fibrosis may play a central role.
CONCLUSIONS: Patients with \"mutually exclusive\" phenotypes display distinct bioprofiles that might underpin different biological pathways, potentially leading to fibrosis. Plasma protein biomarkers and their association with mutually exclusive cardiovascular phenotypes: the FIBRO-TARGETS case-control analyses. Patients with \"mutually exclusive\" phenotypes (blue: obesity, hypertension and diabetes) display distinct protein bioprofiles (green: decreased expression; red: increased expression) that might underpin different biological pathways (orange arrow), potentially leading to fibrosis.