Targeted metabolomics analysis of postoperative delirium

Abstract

Postoperative delirium is the most common complication among older adults undergoing major surgery. The pathophysiology of delirium is poorly understood, and no blood-based, predictive markers are available. We characterized the plasma metabolome of 52 delirium cases and 52 matched controls from the Successful Aging after Elective Surgery (SAGES) cohort (N = 560) of patients ≥ 70 years old without dementia undergoing scheduled major non-cardiac surgery. We applied targeted mass spectrometry with internal standards and pooled controls using a nested matched case-control study preoperatively (PREOP) and on postoperative day 2 (POD2) to identify potential delirium risk and disease markers. Univariate analyses identified 37 PREOP and 53 POD2 metabolites associated with delirium and multivariate analyses achieved significant separation between the two groups with an 11-metabolite prediction model at PREOP (AUC = 83.80%). Systems biology analysis using the metabolites with differential concentrations rendered "valine, leucine, and isoleucine biosynthesis" at PREOP and "citrate cycle" at POD2 as the most significantly enriched pathways (false discovery rate < 0.05). Perturbations in energy metabolism and amino acid synthesis pathways may be associated with postoperative delirium and suggest potential mechanisms for delirium pathogenesis. Our results could lead to the development of a metabolomic delirium predictor.

Figure 1

Experimental design workflow. Key steps in our experimental design included: sample preparation, mass spectrometric qualitative and quantitative analysis, data preprocessing, univariate and multivariate statistical analysis, systems analysis applied to the univariate findings, and predictive modeling using multivariate results.

Figure 2

Statistical approaches to discovering significant metabolites at PREOP and POD2. For (a, b), we applied both parametric [t-test (T)] and nonparametric [Wilcoxon Rank (W) and binomial (B)] statistical tests to account for the degree, direction, and rank of difference between delirium (DEL) and control (CNT) groups at both preoperatively (PREOP) and post-operative day 2 (POD2) time points. To correct for multiple hypothesis testing, we used the Benjamini–Hochberg (BH) procedure. A metabolite was considered to have differentially quantified concentrations if it had a BH-corrected p value < 0.05 in at least two statistical tests. (a) At PREOP, none of the metabolites met our strict criteria for differential concentration. Four metabolites had a BH-corrected p value < 0.05 only in the binomial test (see text). Systems biology was performed using the 37 metabolites that passed two or more tests with a nominal p value < 0.05. (b) At POD2, there were 53 metabolites that met our criteria for differential concentration. These metabolites were used as input for systems analysis. Score plots for the OPLS-DA analysis using the (c) PREOP and (d) POD2 data. Ellipses represent clustering based on the Mahalanobis distance for outlier detection (orange: delirium, blue: control, and black: all samples). Metabolites with the most extreme loadings (positive and negative) for (e) PREOP and (f) POD2 are noted. These metabolites had the greatest impact on the model.

Figure 3

Pathway analysis of metabolites with significant differentially quantified concentrations using MetaboAnalyst^–. Red indicates upregulation in DEL and green denotes downregulation. Grey represents metabolites not included in our targeted metabolomics protocol. Superscripts signify direction of change for the metabolites that did not exhibit significant differential concentrations. The +, −, and × superscripts indicate upregulated (in DEL), downregulated (in DEL), and signal too low or not present, respectively. (a) At PREOP, the valine, leucine, and isoleucine biosynthesis pathway was the only one with metabolites with significantly differentially quantified concentrations (FDR < 0.04). Dashed boxes represent the reactions that are specific to human. (b) At POD2, the citrate cycle pathway was the most significantly enriched.