TY - JOUR
T1 - Broadcasters, receivers, functional groups of metabolites, and the link to heart failure by revealing metabolomic network connectivity
AU - Yazdani, Azam
AU - Mendez-Giraldez, Raul
AU - Yazdani, Akram
AU - Wang, Rui Sheng
AU - Schaid, Daniel J.
AU - Kong, Sek Won
AU - Hadi, M. Reza
AU - Samiei, Ahmad
AU - Samiei, Esmat
AU - Wittenbecher, Clemens
AU - Lasky-Su, Jessica
AU - Clish, Clary B.
AU - Muehlschlegel, Jochen D.
AU - Marotta, Francesco
AU - Loscalzo, Joseph
AU - Mora, Samia
AU - Chasman, Daniel I.
AU - Larson, Martin G.
AU - Elsea, Sarah H.
N1 - Publisher Copyright:
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
PY - 2024/8
Y1 - 2024/8
N2 - Background and Objective: Blood-based small molecule metabolites offer easy accessibility and hold significant potential for insights into health processes, the impact of lifestyle, and genetic variation on disease, enabling precise risk prevention. In a prospective study with records of heart failure (HF) incidence, we present metabolite profiling data from individuals without HF at baseline. Methods: We uncovered the interconnectivity of metabolites using data-driven and causal networks augmented with polygenic factors. Exploring the networks, we identified metabolite broadcasters, receivers, mediators, and subnetworks corresponding to functional classes of metabolites, and provided insights into the link between metabolomic architecture and regulation in health. We incorporated the network structure into the identification of metabolites associated with HF to control the effect of confounding metabolites. Results: We identified metabolites associated with higher and lower risk of HF incidence, such as glycine, ureidopropionic and glycocholic acids, and LPC 18:2. These associations were not confounded by the other metabolites due to uncovering the connectivity among metabolites and adjusting each association for the confounding metabolites. Examples of our findings include the direct influence of asparagine on glycine, both of which were inversely associated with HF. These two metabolites were influenced by polygenic factors and only essential amino acids, which are not synthesized in the human body and are obtained directly from the diet. Conclusion: Metabolites may play a critical role in linking genetic background and lifestyle factors to HF incidence. Revealing the underlying connectivity of metabolites associated with HF strengthens the findings and facilitates studying complex conditions like HF.
AB - Background and Objective: Blood-based small molecule metabolites offer easy accessibility and hold significant potential for insights into health processes, the impact of lifestyle, and genetic variation on disease, enabling precise risk prevention. In a prospective study with records of heart failure (HF) incidence, we present metabolite profiling data from individuals without HF at baseline. Methods: We uncovered the interconnectivity of metabolites using data-driven and causal networks augmented with polygenic factors. Exploring the networks, we identified metabolite broadcasters, receivers, mediators, and subnetworks corresponding to functional classes of metabolites, and provided insights into the link between metabolomic architecture and regulation in health. We incorporated the network structure into the identification of metabolites associated with HF to control the effect of confounding metabolites. Results: We identified metabolites associated with higher and lower risk of HF incidence, such as glycine, ureidopropionic and glycocholic acids, and LPC 18:2. These associations were not confounded by the other metabolites due to uncovering the connectivity among metabolites and adjusting each association for the confounding metabolites. Examples of our findings include the direct influence of asparagine on glycine, both of which were inversely associated with HF. These two metabolites were influenced by polygenic factors and only essential amino acids, which are not synthesized in the human body and are obtained directly from the diet. Conclusion: Metabolites may play a critical role in linking genetic background and lifestyle factors to HF incidence. Revealing the underlying connectivity of metabolites associated with HF strengthens the findings and facilitates studying complex conditions like HF.
KW - Causal networks
KW - Confounding metabolites
KW - Data-driven or Bayesian networks
KW - Genetic variation
KW - Heart failure
KW - Metabolomics
KW - Structural equation modeling
UR - http://www.scopus.com/inward/record.url?scp=85197691867&partnerID=8YFLogxK
U2 - 10.1007/s11306-024-02141-y
DO - 10.1007/s11306-024-02141-y
M3 - Article
C2 - 38972029
AN - SCOPUS:85197691867
SN - 1573-3882
VL - 20
JO - Metabolomics
JF - Metabolomics
IS - 4
M1 - 71
ER -