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Plasma protein biomarkers and their association with mutually exclusive cardiovascular phenotypes: the FIBRO-TARGETS
João Pedro Ferreira1,2,3, Anne Pizard4,5, Jean-Loup Machu4,5
1Université de Lorraine, Centre d'Investigation Clinique- Plurithématique Inserm CIC-P 1433, and Inserm U1116, CHRU Nancy Brabois, F-CRIN INI-CRCT (Cardiovascular and Renal Clinical Trialists), Nancy, France. j.ferreira@chru-nancy.fr.
Insights
Distinct protein biomarkers are associated with hypertension, obesity, and diabetes, potentially revealing pathways to fibrosis. These findings aid in understanding cardiovascular disease risk factors.
Area of Science:
- Cardiovascular disease research
- Proteomics and biomarker discovery
- Biostatistics and machine learning applications in health
Background:
- Hypertension, obesity, and diabetes are significant modifiable risk factors for cardiovascular diseases.
- Identifying specific biomarkers for these conditions is crucial for understanding pathophysiological mechanisms and tailoring treatments.
Purpose of the Study:
- To identify distinct plasma protein biomarkers associated with mutually exclusive phenotypes of hypertension, obesity, and diabetes.
- To explore the underlying biological pathways, including cardiac fibrosis, associated with these cardiovascular risk factors.
Main Methods:
- Data from over 12,000 patients across 12 cohorts were merged within the FIBRO-TARGETS consortium.
- Three distinct case groups (hypertensive, obese, diabetic) were age-sex matched with healthy controls.
- Proteomic associations were analyzed using LASSO biostatistics, machine learning, and complex network approaches.
Main Results:
- Specific proteins were associated with each phenotype: GDF-15, LEP, SORT-1, FABP-2 for hypertension; CEACAM-8, LEP, PRELP for obesity; and GDF-15, REN, CXCL-1, SCF for diabetes.
- GDF-15 and LEP were identified as shared biomarkers for hypertension with diabetes and obesity, respectively.
- Machine learning confirmed GDF-15, LEP, and SORT-1 as discriminators for hypertension, and LEP and PRELP for obesity. Network analyses suggested a central role for fibrosis.
Conclusions:
- Mutually exclusive cardiovascular phenotypes (hypertension, obesity, diabetes) exhibit distinct protein bioprofiles.
- These distinct profiles may indicate different biological pathways that could potentially lead to cardiac fibrosis.
- The identified plasma protein biomarkers offer insights into the mechanisms underlying these prevalent cardiovascular risk factors.
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. 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.
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