High preoperative blood oxaloacetate and 2-aminoadipic acid levels are associated with postoperative delayed neurocognitive recovery

Bioenergetic biomarkers as predictive indicators and their relationship with cognitive function in newly diagnosed, drug-naïve patients with bipolar disorder

Mitochondrial dysfunction and disrupted bioenergetic processes are critical in the pathogenesis of bipolar disorder (BD), with cognitive impairment being a prominent symptom linked to mitochondrial anomalies. The tricarboxylic acid (TCA) cycle, integral to mitochondrial energy production, may be implicated in this cognitive dysfunction, yet its specific association with BD remains underexplored. In this cross-sectional study, 144 first-episode, drug-naive BD patients and 51 healthy controls were assessed. Using liquid chromatography-tandem mass spectrometry (LC-MS/MS), serum TCA cycle metabolites were quantified, and cognitive function was evaluated through the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and the Stroop color-word test. The study found that BD patients exhibited significantly elevated serum levels of several TCA metabolites compared to healthy controls, alongside lower cognitive function scores. Correlational analyses revealed that certain bioenergetic metabolites were significantly positively associated with anxiety and negatively correlated with cognitive performance in BD patients. Notably, succinic acid, α-Ketoglutaric acid (α-KG), and malic acid emerged as independent risk factors for BD, with their combined profile demonstrating diagnostic utility. These findings underscore the potential of serum bioenergetic metabolites as biomarkers for BD, providing insights into the mitochondrial dysfunction underlying cognitive impairment and offering a basis for early diagnosis and targeted therapeutic strategies.

LC-MS-based serum metabolomics analysis and potential biomarkers for oxaliplatin induced neurotoxicity in colorectal cancer

Oxapliplatin-induced peripheral neuropathy (OIPN) is a significant adverse effect encountered in patients with colorectal cancer undergoing oxaliplatin therapy. However, the pathogenesis of OIPN remains unclear. This study aimed to identify potential diagnostic biomarkers for OIPN and discover the metabolic pathways associated with the disease. Serum samples were collected from 218 subjects, including patients with OIPN and control (CONT). The metabolite profiles were analyzed using nontargeted liquid chromatography-mass spectrometry (LC-MS) serum metabolomics method. Subsequently, differentially altered metabolites were identified and evaluated through multivariate statistical analyses. In this study, patients with OIPN and CONT were distinguished by ten significant metabolites. The levels of racemethionine, O-acetylcarnitine, stearolic acid, aminoadipic acid, iminoarginine, galactaric acid, and all-trans-retinoic acid were increased, whereas the levels of 3-methyl-L-tyrosine, 5-aminopentanoic acid, and erythritol compared were found to be diminished in patients with OIPN when compared to the CONT. Through receiver operating characteristic (ROC) curve analysis, racemethionine, stearolic acid, 5-aminopentanoic acid, erythritol, aminoadipic acid, and all-trans-retinoic acid were pinpointed as promising biomarkers for OIPN. Significantly altered pathways included amino acids (arginine biosynthesis, beta-alanine metabolism, arginine and proline metabolism, alanine, aspartate and glutamate metabolism, lysine degradation, and phenylalanine, tyrosine and tryptophan biosynthesis), lipid (linoleic acid metabolism and the biosynthesis of unsaturated fatty acids), and energy metabolism. This study, by identifying serum biomarkers and dissecting metabolic pathways, offers a groundbreaking perspective on the susceptibility mechanisms underlying OIPN. It stands as an invaluable resource for the adjunctive diagnosis of OIPN, with the potential to diminish the incidence of adverse reactions and to enhance the objectivity and reliability of clinical diagnoses of OIPN.

Lipidomics based on UHPLC/Q-TOF-MS to characterize lipid metabolic profiling in patients with newly diagnosed type 2 diabetes mellitus with dyslipidemia

Dyslipidemia often accompanies type 2 diabetes mellitus (T2DM). Elevated blood glucose in patients commonly leads to high levels of lipids. Lipid molecules can play a crucial role in early detection, treatment, and prognosis of T2DM with dyslipidemia. Previous lipid studies on T2DM mainly focused on Western diabetic populations with elevated blood glucose. In this research, we investigate both high blood sugar and high lipid levels to better understand changes in plasma lipid metabolism in newly diagnosed Chinese T2DM patients with dyslipidemia (NDDD). We used a plasma lipid analysis method based on ultra-high performance liquid chromatography coupled with mass spectrometry technology (UHPLC-MS) and statistical analysis to characterize lipid profiles and identify potential biomarkers in NDDD patients compared to healthy control (HC) subjects. Additionally, we examined the differences in lipid profiles between hyperlipidemia (HL) patients and HC subjects. We found significant changes in 15 and 23 lipid molecules, including lysophosphatidylcholine (LysoPC), phosphatidylcholine (PC), phosphatidylethanolamine (PE), sphingomyelin (SM), and ceramide (Cer), in the NDDD and HL groups compared to the HC group. These altered lipid molecules are associated with five metabolic pathways, with sphingolipid metabolism and glycerophospholipid metabolism being the most relevant to glucose and lipid metabolism changes. These lipid biomarkers are strongly correlated with traditional markers of glucose and lipid metabolism. Notably, Cer(d18:1/24:0), SM(d18:1/24:0), SM(d18:1/16:1), SM(d18:1/24:1), and SM(d18:2/24:1) were identified as essential potential biomarkers closely linked to clinical parameters through synthetic analysis of receiver operating characteristic curves, random forest analysis, and Pearson matrix correlation. These lipid biomarkers can enhance the risk prediction for the development of T2DM in individuals with dyslipidemia but no clinical signs of high blood sugar. Furthermore, they offer insights into the pathological mechanisms of T2DM with dyslipidemia.