Fig 1.
Statistical analysis workflow outlining the steps taken to find predictors of HF test performance using metabolomic and lipidomic data.
Stepwise MRA was validated with bootstrap 95% confidence interval of the main regression estimates. Search of published threshold references confirmed the clinical importance of the models. Pathway enrichment analysis revealed the main metabolic pathways and associated diseases enriched using the set of metabolites predicting HF performance. A metabolic network was derived from the analysis confirming several metabolic dysfunctions related to HF described in the literature.
Table 1.
Estimates of cardiorespiratory fitness and HF biomarkers and comparison with literature threshold references.
Table 2.
Demographics of the study cohort.
Table 3.
Predictors of cardiorespiratory fitness and traditional HF biomarkers selected by multivariate linear regression.
Fig 2.
Prediction plot of VE/VCO2 shows the changes in expected VE/VCO2 slope value when the predictor’s levels change.
When there are higher values of CE (22:4), CE (18:3) Acylcarnitine C18:2, hydroxyproline dipeptide, oxoproline,trans-4-hydroxyproline, and indole-3-acetate, as well as lower values of CE (22:5), LPC (18:0), 1-monoolein, propionic acid, xanthine, and phenylethylamine, the CPET test predicts poor performance. CE = cholesterol ester, LPC = lysophosphatidylcholine.
Fig 3.
Metabolic pathway enrichment analysis shows the main pathways involved in heart failure test performance.
The plot shows matched pathways according to the p-values from the pathway enrichment analysis and pathway impact values from pathway topology analysis. The pathways with the lowest p-values and highest match status (predictors present in the pathways) are listed in the table along with their FDR correction and impact score.
Fig 4.
Diseases associated sets enrichment shows the more important diseases presenting similar metabolic profile based in heart failure test performance.
The majority of the statistically significant enriched diseases are related to brain dysfunction. Lactic acidosis-related diseases were also found with high impact in the analysis.
Fig 5.
Intertwined metabolic network in heart failure.
The metabolic changes affecting heart failure patients based in heart failure test performance includes glutathione anti-oxidative pathway, branched-chain amino acid (BCAA) biosynthesis, pentose cycle, tricarboxylic acid cycle (TCA), fatty acid (FA) metabolism, sphingolipids and glycerophospholipids metabolism, and tryptophan metabolism. Arrow represents predicted elevation or decrease variables in poor test performance. Only predictors with coefficients higher than 0.3 were used. Some metabolites not detected in the analysis were included in the figure to complement the metabolic pathways. Direction of pathways are proposed based in the metabolic modulation found in the study. TCA = tricarboxylic acid; PC = phosphatidylcholine; DAG = diacylglycerol; PI = phosphatidylinositol; Cer = ceramide; CE = cholesteryl ester; FA = fatty acid; LPC = lysophosphatidylcholine R* = reactive oxygen species.