Journal Article

Transcriptional, epigenetic and metabolic signatures in cardiometabolic syndrome defined by extreme phenotypes

Cabassi, Alessandra, Sims, Matthew C., Bock, Christoph, Griffin, Julian L., Koulman, Albert, Vacca, Michele, Ergüener, Bekir, Langenberg, Claudia, Frontini, Mattia, Slingsby, Oliver, Farrow, Samantha, Kirk, Paul D. W., Kempster, Carly, Grassi, Luigi, Frary, Amy, D’Amore, Simona, Rehnstrom, Karola, Adams, Claire L., Downes, Kate, Seyres, Denis, Batista, Joana, Ng, Leong Loke, Wareham, Nicholas J., Savage, David B., Allison, Michael, Quinn, Paulene A., Burden, Frances, Park, Adrian, Lambourne, John J., Pietzner, Maik, Mocciaro, Gabriele, Stefanucci, Luca, Kreuzhuber, Roman, Cao, Thong Huy, McKinney, Harriet

2022

Overview

Background This work is aimed at improving the understanding of cardiometabolic syndrome pathophysiology and its relationship with thrombosis by generating a multi-omic disease signature. Methods/results We combined classic plasma biochemistry and plasma biomarkers with the transcriptional and epigenetic characterisation of cell types involved in thrombosis, obtained from two extreme phenotype groups (morbidly obese and lipodystrophy) and lean individuals to identify the molecular mechanisms at play, highlighting patterns of abnormal activation in innate immune phagocytic cells. Our analyses showed that extreme phenotype groups could be distinguished from lean individuals, and from each other, across all data layers. The characterisation of the same obese group, 6 months after bariatric surgery, revealed the loss of the abnormal activation of innate immune cells previously observed. However, rather than reverting to the gene expression landscape of lean individuals, this occurred via the establishment of novel gene expression landscapes. NETosis and its control mechanisms emerge amongst the pathways that show an improvement after surgical intervention. Conclusions We showed that the morbidly obese and lipodystrophy groups, despite some differences, shared a common cardiometabolic syndrome signature. We also showed that this could be used to discriminate, amongst the normal population, those individuals with a higher likelihood of presenting with the disease, even when not displaying the classic features.

• Publisher: BioMed Central,BioMed Central Ltd
• Subject: Analysis / Biomedical and Life Sciences / Biomedicine / Blood clot / Cardiovascular epigenetics / DNA Methylation / Epigenesis, Genetic / Epigenetic inheritance / Gene Function / Genetic aspects / Genetic transcription / Human Genetics / Humans / Lipodystrophy / Medical colleges / Metabolic Syndrome - genetics / Obesity / Obesity, Morbid - surgery / Phenotype / Surgery / Thrombosis