@article {Seyres2020.03.06.961805, author = {Denis Seyres and Alessandra Cabassi and John J Lambourne and Frances Burden and Samantha Farrow and Harriet McKinney and Joana Batista and Carly Kempster and Maik Pietzner and Oliver Slingsby and Thong Huy Cao and Paulene A Quinn and Luca Stefanucci and Matthew C Sims and Karola Rehnstrom and Claire L Adams and Amy Frary and Bekir Erg{\"u}ener and Roman Kreuzhuber and Gabriele Mocciaro and Simona D{\textquoteright}Amore and Albert Koulman and Luigi Grassi and Julian L Griffin and Leong Loke Ng and Adrian Park and David B Savage and Claudia Langenberg and Christoph Bock and Kate Downes and Nicholas J Wareham and Michael Allison and Michele Vacca and Paul DW Kirk and Mattia Frontini}, title = {Transcriptional, epigenetic and metabolic signatures in cardiometabolic syndrome defined by extreme phenotypes}, elocation-id = {2020.03.06.961805}, year = {2021}, doi = {10.1101/2020.03.06.961805}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Improving the understanding of cardiometabolic syndrome pathophysiology and its relationship with thrombosis are ongoing healthcare challenges. Using plasma biomarkers analysis coupled with the transcriptional and epigenetic characterisation of cell types involved in thrombosis, obtained from two extreme phenotype groups (obese and lipodystrophy) and comparing these to lean individuals and blood donors, the present study identifies the molecular mechanisms at play, highlighting patterns of abnormal activation in innate immune phagocytic cells and shows 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, six months after bariatric surgery shows the loss of the patterns of abnormal activation of innate immune cells previously observed. However, rather than reverting to the gene expression landscape of lean individuals, this occurs via the establishment of novel gene expression landscapes. Netosis and its control mechanisms emerge amongst the pathways that show an improvement after surgical intervention. Taken together, by integrating across data layers, the observed molecular and metabolic differences form a disease signature that is able to discriminate, amongst the blood donors, those individuals with a higher likelihood of having cardiometabolic syndrome, even when not presenting with the classic features.Competing Interest StatementThe authors have declared no competing interest.}, URL = {https://www.biorxiv.org/content/early/2021/03/04/2020.03.06.961805}, eprint = {https://www.biorxiv.org/content/early/2021/03/04/2020.03.06.961805.full.pdf}, journal = {bioRxiv} }