Background
Mitochondrial function is a major determinant of outcome in critical illness. Circulating mitochondrial damage-associated molecular patterns (DAMPs), such as cell-free mitochondrial DNA (mtDNA), contain unmethylated CpG and formylated peptides that activate immune responses through Toll-like receptor 9 and formyl peptide receptors, respectively [
1‐
4].
Plasma mtDNA is measurable in critically ill patients, with increasing levels associated with sepsis, sepsis disease severity, and mortality [
5‐
7]. The primary factors in the extracellular release of mtDNA are cell stress and necrosis [
3]. Experimental data published in abstract form showed an increase in extracellular mtDNA by induction of endothelial cell necroptosis following transfusion [
8]. Mitochondria-related DAMPs from damaged, dying, or dead cells appear to be important for the early systemic endothelial response to sepsis [
9]. mtDNA is shown to increase endothelial cell permeability, either directly or through interactions with endothelial cells and polymorphonuclear leukocytes [
9]. These findings suggest that plasma mtDNA levels could reflect the level of injury and may also reflect the level of dysfunction or damage that mitochondria undergo in response to physiologic stress [
10].
Because metabolic homeostasis is often disrupted in critical illness, substantial alterations of several intrinsic pathways can be expected in septic patients [
11]. To date, a number of metabolomic studies have been published in experimental sepsis models [
12], pediatric sepsis [
13], and adult critically ill patients [
14‐
17]. Circulating metabolic signatures showing alteration in fatty acids, lipids, and tryptophan pathways are prominent in cohorts of septic patients [
14‐
17].
Existing data support that mtDNA is related to the activation of inflammation and organ dysfunction [
18]. However, there is limited understanding of the metabolic alterations associated with elevated mtDNA levels in critical illness. Therefore, we analyzed metabolite profiles with regard to NADH dehydrogenase 1 (ND1) mtDNA levels in a prospective study of adult patients with systemic inflammatory response syndrome (SIRS) and sepsis [
19]. The ND1 protein is a subunit of NADH dehydrogenase found in the inner membrane of mitochondria [
20]. We hypothesized that the metabolomic profile of critically ill patients near intensive care unit (ICU) admission differs in patients with elevated ND1 mtDNA levels and that this difference can illuminate important biologic pathways related to the response to mitochondrial DAMPs.
Discussion
In the present study, our goal was to determine if metabolite signatures in critically ill patients would be distinct relative to cell-free plasma ND1 mtDNA levels. Using high-resolution metabolomics, we demonstrated substantial differences in glycerophospholipid and acylcarnitine family member metabolism based on the level of ND1 mtDNA liberated in the plasma. Specifically, patients with high levels of plasma ND1 mtDNA, indicative of cellular damage, have very low levels of multiple glycerophosphocholine esters and increased levels of several short-chain acylcarnitines.
In cohorts of septic patients, alterations in circulating kynurenines, fatty acids, lysophosphatidylcholines, and/or carnitine esters [
14‐
17] indicate a substantial disturbance in energy and lipid homeostasis that occurs with increasing severity of illness. Large decreases in glycerophosphocholines are demonstrated in patients with experimental infection with
Bacillus anthracis spores [
36], bacteremia [
37], and sepsis [
17] and appear to correlate with sepsis mortality [
38]. Glycerophosphocholines are water-soluble compounds formed in the breakdown of phosphatidylcholine via phospholipase A1 and phospholipase A2 activities, and they are degraded by glycerophosphodiester phosphodiesterases [
39]. Glycerophosphocholines are essential components of biological membranes that modulate membrane trafficking and control cell viability [
39]. Glycerophosphocholines function in glycerophospholipid, prostaglandin, and leukotriene metabolism; are important in energy storage, signal transduction, and membrane physiology; provide mitochondrial support; and are neutrophil-activating factors [
36].
The observed substantial decreases in glycerophosphocholines during sepsis may be related to increased glycerophosphocholine hydrolysis [
37]. Circulating phospholipase A2 activity is found in sepsis [
40]. Additionally, endothelial cells secrete the phospholipase endothelial lipase (EL) involved in phospholipid homeostasis [
41,
42]. EL is produced by macrophages in addition to the endothelium in response to plasma inflammation markers [
43]. In human experimental models of low-dose endotoxemia, significant augmentation of plasma EL concentrations has been shown [
44]. The combination of circulating phospholipase A2 and EL activity may be responsible for the low glycerophosphocholine metabolites observed in our study.
Lipidomic alterations are prominent in sepsis and critically ill patients [
45‐
48]. We have shown that carnitine esters, important for immune response to pathogens [
49], are the most pronounced metabolites that differed between sepsis nonsurvivors and survivors [
17]. Alterations of acylcarnitines are found in studies of severe sepsis/septic shock [
45], the prediction of death in sepsis [
17], and an integrative omics study in primates that was validated also in human patient cohorts [
50].
In critical illness, metabolic pathways are altered to preferentially catabolize fatty acids and amino acids. Substantive literature demonstrates that an early indicator of critical illness outcomes is mitochondrial biogenesis [
51‐
54]. Elevated short-chain acylcarnitines found in plasma are due to incomplete mitochondrial fatty acid β-oxidation downstream of carnitine palmitoyltransferase I and are suggestive of impaired mitochondrial function [
55‐
57]. The increase in plasma short-chain acylcarnitines with elevated ND1 mtDNA in our study may reflect less efficient fatty acid β-oxidation, potentially thorough worsening of mitochondrial bioenergetics.
Accelerated tryptophan catabolism along the kynurenine pathway occurs with sepsis. The enzyme responsible for kynurenine production is upregulated by bacterial products and is critically involved in CD4
+ and CD8
+ effector T-cell suppression as well as in generation and activation of regulatory T cells [
58,
59]. We and others have found that modulation of kynurenine is associated with 28-day mortality in sepsis [
14,
15]. Increased production of kynurenine has been proposed to contribute to hypotension in sepsis [
60] and has been associated with dysregulated immune response and impaired microvascular reactivity [
61].
Strengths of the present study include using cell-free plasma for ND1 mtDNA measurement. Because platelets secrete their mitochondria following activation during inflammation and sepsis, they may serve as a source of extracellular mtDNA [
62]. Using cell-free plasma allowed us to draw the inference that the source of ND1 mtDNA is more likely the endothelium. Further, we employed several types of statistical procedures, and data visualization processes were used to identify differential metabolites, including Student’s
t test [
63], Pearson correlation, volcano plot, bipartite graph, SAM [
27], OPLS-DA, and MetPA [
32].
The present study is not without potential limitations. Metabolites were measured early in the ICU course of severe critical illness, from a relatively small number of patients, at a single time point, and from a single biofluid (plasma). Our assumption that plasma is an integrative biofluid may not account for tissue- or organ-specific metabolism. Our observational study included patients who were critically ill for various reasons, creating a heterogeneous study sample with high severity of illness. Further, selection bias may be present because we analyzed only a subset of patients of the RoCI cohort who had ND1 mtDNA determined. We are unable to account for the impact of race on metabolic profiles because our cohort was mostly white. Because our study was performed on a convenience sample and not replicated in other cohorts, our results may not be generalizable to all critically ill patients. Our bioinformatics approaches, while robust, are not without risk of introducing sources of bias. Single–time point metabolomics provides important information but does not capture the dynamic changes over time [
64]. We were not able to determine the stability of metabolites over storage time [
65]. Although OPLS-DA is well-suited for metabolomic data with much larger numbers of predictors than observations and multicollinearity, it is prone to overfitting; however, permutation testing indicated a low likelihood of seeing results this strong by chance (
p ≤ 0.05) [
29,
30]. Like in our study, mapping the metabolite data onto the HMDB [
33] does not always result in HMDB number assignment to each metabolite. Finally, we cannot fully account for potential confounding, reverse causation, and the lack of a randomly distributed exposure [
66].