Microbiome and metabolome features of the cardiometabolic disease spectrum

Author:

Fromentin Sebastien,Forslund Sofia K.ORCID,Chechi Kanta,Aron-Wisnewsky Judith,Chakaroun Rima,Nielsen TrineORCID,Tremaroli Valentina,Ji BoyangORCID,Prifti EdiORCID,Myridakis AntonisORCID,Chilloux JulienORCID,Andrikopoulos Petros,Fan YongORCID,Olanipekun Michael T.,Alves RenatoORCID,Adiouch Solia,Bar Noam,Talmor-Barkan Yeela,Belda Eugeni,Caesar RobertORCID,Coelho Luis Pedro,Falony Gwen,Fellahi Soraya,Galan Pilar,Galleron Nathalie,Helft Gerard,Hoyles LesleyORCID,Isnard Richard,Le Chatelier EmmanuelleORCID,Julienne Hanna,Olsson LisaORCID,Pedersen Helle Krogh,Pons Nicolas,Quinquis Benoit,Rouault Christine,Roume Hugo,Salem Joe-ElieORCID,Schmidt Thomas S. B.ORCID,Vieira-Silva SaraORCID,Li PeishunORCID,Zimmermann-Kogadeeva MariaORCID,Lewinter Christian,Søndertoft Nadja B.ORCID,Hansen Tue H.ORCID,Gauguier Dominique,Gøtze Jens Peter,Køber LarsORCID,Kornowski Ran,Vestergaard HenrikORCID,Hansen TorbenORCID,Zucker Jean-Daniel,Hercberg Serge,Letunic Ivica,Bäckhed Fredrik,Oppert Jean-Michel,Nielsen JensORCID,Raes Jeroen,Bork Peer,Stumvoll Michael,Segal EranORCID,Clément KarineORCID,Dumas Marc-EmmanuelORCID,Ehrlich S. DuskoORCID,Pedersen OlufORCID

Abstract

AbstractPrevious microbiome and metabolome analyses exploring non-communicable diseases have paid scant attention to major confounders of study outcomes, such as common, pre-morbid and co-morbid conditions, or polypharmacy. Here, in the context of ischemic heart disease (IHD), we used a study design that recapitulates disease initiation, escalation and response to treatment over time, mirroring a longitudinal study that would otherwise be difficult to perform given the protracted nature of IHD pathogenesis. We recruited 1,241 middle-aged Europeans, including healthy individuals, individuals with dysmetabolic morbidities (obesity and type 2 diabetes) but lacking overt IHD diagnosis and individuals with IHD at three distinct clinical stages—acute coronary syndrome, chronic IHD and IHD with heart failure—and characterized their phenome, gut metagenome and serum and urine metabolome. We found that about 75% of microbiome and metabolome features that distinguish individuals with IHD from healthy individuals after adjustment for effects of medication and lifestyle are present in individuals exhibiting dysmetabolism, suggesting that major alterations of the gut microbiome and metabolome might begin long before clinical onset of IHD. We further categorized microbiome and metabolome signatures related to prodromal dysmetabolism, specific to IHD in general or to each of its three subtypes or related to escalation or de-escalation of IHD. Discriminant analysis based on specific IHD microbiome and metabolome features could better differentiate individuals with IHD from healthy individuals or metabolically matched individuals as compared to the conventional risk markers, pointing to a pathophysiological relevance of these features.

Publisher

Springer Science and Business Media LLC

Subject

General Biochemistry, Genetics and Molecular Biology,General Medicine

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