Procalcitonin metabolomics in the critically ill reveal relationships between inflammation intensity and energy utilization pathways

Abstract

Procalcitonin is a biomarker of systemic inflammation and may have importance in the immune response. The metabolic response to elevated procalcitonin in critical illness is not known. The response to inflammation is vitally important to understanding metabolism alterations during extreme stress. Our aim was to determine if patients with elevated procalcitonin have differences in the metabolomic response to early critical illness. We performed a metabolomics study of the VITdAL-ICU trial where subjects received high dose vitamin D₃ or placebo. Mixed-effects modeling was used to study changes in metabolites over time relative to procalcitonin levels adjusted for age, Simplified Acute Physiology Score II, admission diagnosis, day 0 25-hydroxyvitamin D level, and the 25-hydroxyvitamin D response to intervention. With elevated procalcitonin, multiple members of the short and medium chain acylcarnitine, dicarboxylate fatty acid, branched-chain amino acid, and pentose phosphate pathway metabolite classes had significantly positive false discovery rate corrected associations. Further, multiple long chain acylcarnitines and lysophosphatidylcholines had significantly negative false discovery rate corrected associations with elevated procalcitonin. Gaussian graphical model analysis revealed functional modules specific to elevated procalcitonin. Our findings show that metabolite differences exist with increased procalcitonin indicating activation of branched chain amino acid dehydrogenase and a metabolic shift.

Figure 1

Rain plot of metabolites significantly increased with increased Procalcitonin. Repeated measures metabolomics data (day 0, 3 and 7) relative to procalcitonin level. Correlations between procalcitonin levels and individual metabolite abundance at day 0, 3 or 7 were determined utilizing linear regression models correcting for age, sex, SAPS II, admission diagnosis, 25(OH)D at day 0 and for absolute change in 25(OH)D level at day 3. The magnitude of beta coefficient estimates is shown by a color fill scale and the corresponding significance level (− log10(q-value)) is represented by size of the circle. The intensity of the red fill color represents an increase in effect size for that metabolite relative to procalcitonin level. All metabolites shown are significant by a q-value threshold of 0.05. All respective β coefficients and q-values can be found in tabular form in Supplementary Data S3. (A) Short-chain acylcarnitines (B) Medium-chain acylcarnitines (C) BCAA metabolites (D) Dicarboxylate fatty acids.

Figure 2

Rain plot of metabolites significantly decreased with increased Procalcitonin. Correlations between procalcitonin levels and individual metabolite abundance at day 0, 3 or 7 were determined utilizing linear regression models correcting for age, SAPS II, admission diagnosis, 25(OH)D at day 0 and for absolute change in 25(OH)D level at day 3. The magnitude of beta coefficient estimates is shown by a color fill scale and the corresponding significance level (− log₁₀(q-value)) is represented by size of the circle. The intensity of the blue fill color represents a decrease in effect size for that metabolite relative to procalcitonin level. All metabolites shown are significant by a q-value threshold of 0.05. All respective β coefficients and q-values can be found in tabular form in Supplementary Data S3. (A) Lysophosphatidylcholines (B) Long chain acylcarnitines.