Higher Plasma Kynurenine to Tryptophan Correlates with Increased Incidence of Mild Cognitive Impairment in Treated Metabolic Syndrome Patients
Description
An increase in cognitive impairment has been observed in metabolic syndrome (MetS) patients. Although alterations in metabolomic profiles have been identified as potential plasma/serum biomarkers of mild cognitive impairment (MCI) and MetS, findings remain inconsistent— likely due to the heterogeneity among MetS patients and the lack of subsequent validation using targeted analysis after initial untargeted analysis. In this study, we validated mass spectrometry-based quantitation methods and quantified amino acids, fatty acids, and tryptophan metabolites in the kynurenine pathway in plasma of ninety-five treated MetS patients with and without MCI assessed by Montreal cognitive assessment. We found that MCI was positively associated with kynurenine to tryptophan ratio (KTR) after the adjustment for age, gender, and BMI, as well as were negatively associated with C20:3 [all-Z-8,11,14] and lysine. One-unit increase in KTR resulted in increased probability of developing MCI by 371%. In contrast, one-unit increases in C20:3 and lysine were associated with decreased odds of developing MCI by 81% and 78%, respectively. Our finding underscores the prominent neuroinflammation, beyond normal aging, in MetS patients, even under ongoing clinical treatment. It also points to the potential of KTR as a risk marker for MCI, offering a valuable complement to the existing cognitive assessments that may be influenced by educational background. In addition, the validated metabolite data is an useful resource for future research. It can facilitate comparisons across different studies, contribute to large-scale analyses, and be used in machine learning models for discovering and validating new biomarkers.
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Amino acid analysis 30 µL of plasma was extracted with 1 mL of pre-cooled mixture of ACN/IPA/H2O (3:3:2), containing IS. The extracts were shaken at 2,000 rpm for 2 min using before being kept at -20 ºC for 1 h. The extracts were then centrifuged for 10 min at 4 ºC and 19,600 ×g. A 450-µL aliquot of supernatant was evaporated to dryness then resuspended in 450 µL ACN/H2O (50:50), followed by centrifugation at 14,000 ×g and RT for 2 min. The supernatant was transferred to a new tube and dried at 50 ºC before being reconstituted in 450 µL ACN/H2O (50:50) and centrifuged at 14,000 ×g for 2 min at RT. The supernatant was evaporated to dryness. The dried samples were derivatized with 50 µL MTBSTFA + 1% TBDMSCl and 50 µL ACN, followed by incubating at 100 ºC for 4 h. The quantification was carried out using a GC-TOFMS using a Rxi-5sil MS column. The MS data were acquired using ChromaTOF software. Total fatty acid analysis To convert fatty acids to FAMEs, a 50-µL aliquot of a plasma sample was mixed in a pyrex tube with 0.5 mL of BF3 and surrogate. The sample mixture was heated at 100 ºC for 1 h. After heating, the extract was allowed to cool down to RT before adding 1 mL n-hexane and brief vortexing. 1 µL of Milli-Q water was then added to the extract followed by vortexing for 20 s. The extract was centrifuged at 1,847 ×g, 20 ºC for 15 min. The supernatant was dried under N2 and reconstituted in 500 µL hexane containing IS. The analysis was carried out using a GC-TOFMS using on a DB-FastFAME. The MS data were acquired using ChromaTOF software. Analysis of tryptophan metabolites 50 µL of plasma was mixed with 200 µL of MeOH containing 100 ng of IS then vortexed. The sample mixture was sonicated for 10 min at RT and stored at -20 ºC overnight. The sample was centrifuged at 13,000 rpm at 4 ºC for 15 min. The supernatant was evaporated to dryness before being resuspended in 100 µL H2O with 0.1% formic acid, followed by a brief vortex and sonication at RT. After centrifugation at 13,000 rpm, 4 ºC for 15 min. The analysis was carried out using a Waters Acquity I-Class UPLC coupled with a Xevo TQ-Absolute MS/MS. The target compounds were separated on a HSS T3 column, 2.1 × 100 mm, 1.8 mM column. LC-TQMS data was processed using MassLynx. Data process and data analysis Metabolite concentrations were presented as medians (and IQR). Statistical differences were tested by Mann-Whitney U test. Concentrations below LOQs were replaced by LOQs. Metabolites with missing values greater than 30% of the total number of samples in each group were removed. The missing values were imputed by median concentrations of the metabolites within each group, followed by log2 transformation. Mann-Whitney U test, and Spearman’s correlation analyses of the combined dataset were carried out using SPSS software v.18. The multivariate analysis was performed using Metabox2 R package. The odd ratios were calculated from binary regression models using the R package version 4.4.3.
Institutions
- Mahidol University