Plasma protein biomarkers and their association with mutually exclusive cardiovascular phenotypes: the FIBRO-TARGETS case-control analyses

Joao Pedro Ferreira*, Anne Pizard, Jean-Loup Machu, Emmanuel Bresso, Hans-Peter Brunner-La Rocca, Nicolas Girerd, Celine Leroy, Arantxa Gonzalez, Javier Diez, Stephane Heymans, Marie-Dominique Devignes, Patrick Rossignol, Faiez Zannad, FIBRO-TARGETS investigators

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

16 Citations (Web of Science)


Background Hypertension, obesity and diabetes are major and potentially modifiable "risk factors" for cardiovascular diseases. Identification of biomarkers specific to these risk factors may help understanding the underlying pathophysiological pathways, and developing individual treatment. 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. Conclusion Patients with "mutually exclusive" phenotypes display distinct bioprofiles that might underpin different biological pathways, potentially leading to fibrosis.

Graphic abstract

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.



Original languageEnglish
Pages (from-to)22-33
Number of pages12
JournalClinical research in cardiology
Issue number1
Publication statusPublished - Jan 2020


  • Cardiovascular diseases
  • Phenotypes
  • Proteomics
  • Decision tree
  • Complex networks
  • RISK

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