<p>Urinary biomarkers for diagnosing poststroke depression in patients with type 2 diabetes mellitus</p>

Abstract

Background Depression can seriously affect the quality of life of type 2 diabetes mellitus (T2DM) patients after stroke. However, there were still no objective methods to diagnose T2DM patients with poststroke depression (PSD). Therefore, we conducted this study to deal with this problem. Methods Gas chromatography-mass spectroscopy (GC-MS)-based metabolomics profiling method was used to profile the urinary metabolites from 83 nondepressed T2DM patients after stroke and 101 T2DM patients with PSD. The orthogonal partial least-squares discriminant analysis was conducted to explore the metabolic differences in T2DM patients with PSD. The logistic regression analysis was performed to identify the optimal and simplified biomarker panel for diagnosing T2DM patients with PSD. The receiver operating characteristic curve analysis was used to assess the diagnostic performance of this biomarker panel. Results In total, 23 differential metabolites (7 decreased and 16 increased in T2DM patients with PSD) were found. A panel consisting of pseudouridine, malic acid, hypoxanthine, 3,4-dihydroxybutyric acid, fructose and inositol was identified. This panel could effectively separate T2DM patients with PSD from nondepressed T2DM patients after stroke. The area under the curve was 0.965 in the training set and 0.909 in the validation set. Meanwhile, we found that the galactose metabolism was significantly affected in T2DM patients with PSD. Conclusion Our results could be helpful for future development of an objective method to diagnose T2DM patients with PSD and provide novel ideas to study the pathogenesis of depression.

Urinary Metabolite Signatures for Predicting Elderly Stroke Survivors with Depression

“…Therefore, to obtain more accurate potential biomarkers for PSD, researchers have done many wonderful works to successfully identify several differential urinary metabolites. 14 , 15 Meanwhile, Xie et al identified some potential metabolite biomarkers for middle-aged PSD subjects. 16 However, these identified potential biomarkers could not effectively separate elderly PSD subjects from elderly non-depressed subjects.…”

“…The procedure of GC-MS analysis and samples was extracted from the previous studies. 14 , 15 The global metabolome analysis was used here. In total, 59 urinary metabolites were analyzed, and the analysis was done in Nanchang University.…”

“…13 Some studies have identified several urinary biomarkers for PSD. [14][15][16] But none of these previous studies have taken age-based differences into consideration, especially considering that elderly stroke survivors are more likely to be depressed. 1 In recent decades, metabolomics is widely used to find potential biomarkers for many diseases.…”

Does urinary metabolite signature act as a biomarker of post-stroke depression?

“…Liang et al’s study ( 49 ) included 101 patients with PSD and 83 non-depressed patients after stroke. All the recruited patients were also diagnosed with type 2 diabetes mellitus (T2DM).…”

“…Another study found that several specified metabolites could act as predictors of depression recovery (46,47). Of note, recent studies (48)(49)(50)(51) showed that GC-MS-identified urinary metabolite biomarkers could significantly distinguish PSD from stroke survivors, which could be used as an objective diagnostic tool for PSD.…”