Changshui Wang

Bio: Changshui Wang is an academic researcher from Jining Medical University. The author has contributed to research in topics: Metabolite & Angiotensin II. The author has an hindex of 3, co-authored 5 publications receiving 18 citations.

Systematic impacts of chronic unpredictable mild stress on metabolomics in rats.

Abstract: Depression is the most common disabling psychiatric disease, with a high prevalence and mortality. Chronic unpredictable mild stress (CUMS) is a well-accepted method used to mimic clinical depression. Recent evidence has consistently suggested that the cumulative effects of CUMS could lead to allostatic overload in the body, thereby inducing systemic disorders; however, there are no previous systematic metabonomics studies on the main stress-targeted tissues associated with depression. A non-targeted gas chromatography–mass spectrometry (GC–MS) approach was used to identify metabolic biomarkers in the main stress-targeted tissues (serum, heart, liver, brain, and kidney) in a CUMS model of depression. Male Sprague–Dawley rats were randomly allocated to the CUMS group (n = 8) or a control group (n = 8). Multivariate analysis was performed to identify the metabolites that were differentially expressed between the two groups. There were 10, 10, 9, 4, and 7 differentially expressed metabolites in the serum, heart, liver, brain and kidney tissues, respectively, between the control and CUMS groups. These were linked to nine different pathways related to the metabolism of amino acids, lipids, and energy. In summary, we provided a comprehensive understanding of metabolic alterations in the main stress-targeted tissues, helping to understand the potential mechanisms underlying depression.

Metabolomic Profiling Revealed Potential Biomarkers in Patients With Moyamoya Disease.

Abstract: Metabolomics is increasingly used to observe metabolic patterns and disease-specific metabolic biomarkers. However, serum metabolite analysis of moyamoya disease (MMD) is rarely reported. We investigated serum metabolites in MMD and compared them with those of healthy controls (HCs) using a non-targeted gas chromatography-mass spectrometry (GC-MS) approach to identify metabolic biomarkers associated with MMD. Forty-one patients with MMD diagnosed by cerebral angiography and 58 HCs were recruited for our study. Comparative analyses (univariate, multivariate, correlation, heatmaps, receiver operating characteristi curves) were performed between MMD patients and HCs. Twenty-five discriminating serum metabolic biomarkers between MMD patients and HCs were identified. Compared with HCs, MMD patients had higher levels of phenol, 2-hydroxybutyric acid, L-isoleucine, L-serine, glycerol, pelargonic acid, L-methionine, myristic acid, pyroglutamic acid, palmitic acid, palmitoleic acid, stearic acid, octadecanamide, monoglyceride (MG) (16:0/0:0/0:0), and MG (0:0/18:0/0:0), and lower levels of L-alanine, L-valine, urea, succinic acid, L-phenylalanine, L-threonine, L-tyrosine, edetic acid, and oleamide. These metabolic biomarkers are involved in several pathways and are closely associated with the metabolism of amino acids, lipids, carbohydrates, and carbohydrate translation. A GC-MS-based metabolomics approach could be useful in the clinical diagnosis of MMD. The identified biomarkers may be helpful to develop an objective diagnostic method for MMD and improve our understanding of MMD pathogenesis.

Targeted metabolomics analysis of serum amino acid profiles in patients with Moyamoya disease.

Abstract: Amino acids are one of the main metabolites in the body, and provide energy for the body and brain. The purpose of this study is to provide a profile of amino acid changes in the serum of patients with Moyamoya disease (MMD) and identify potential disease biomarkers. In this paper, we quantitatively determined the serum amino acid metabolic profiles of 43 MMD patients and 42 healthy controls (HCs). T test, multivariate statistical analysis, and receiver operating characteristic (ROC) curve analysis were used to identify candidate markers. Thirty-nine amino acids were quantified, and 12 amino acid levels differed significantly between the MMD patients and HCs. Moreover, based on ROC curve analysis, four amino acid (L-methionine, L-glutamic acid, β-alanine and o-phosphoserine) biomarkers showed high sensitivity and specificity (AUC > 0.90), and showed the best sensitivity and specificity in MetaboAnalyst 5.0 using binary logistic regression analysis. We have provided serum amino acid metabolic profiles of MMD patients, and identified four potential biomarkers which may both provide clinicians with an objective diagnostic method for early detection of MMD and further our understanding of MMD pathogenesis.

Conventional laboratory housing increases morbidity and mortality in research rodents: results of a meta-analysis

Abstract: Over 120 million mice and rats are used annually in research, conventionally housed in shoebox-sized cages that restrict natural behaviours (e.g. nesting and burrowing). This can reduce physical fitness, impair thermoregulation and reduce welfare (e.g. inducing abnormal stereotypic behaviours). In humans, chronic stress has biological costs, increasing disease risks and potentially shortening life. Using a pre-registered protocol ( https://atrium.lib.uoguelph.ca/xmlui/handle/10214/17955 ), this meta-analysis therefore tested the hypothesis that, compared to rodents in 'enriched' housing that better meets their needs, conventional housing increases stress-related morbidity and all-cause mortality.Comprehensive searches (via Ovid, CABI, Web of Science, Proquest and SCOPUS on May 24 2020) yielded 10,094 publications. Screening for inclusion criteria (published in English, using mice or rats and providing 'enrichments' in long-term housing) yielded 214 studies (within 165 articles, using 6495 animals: 59.1% mice; 68.2% male; 31.8% isolation-housed), and data on all-cause mortality plus five experimentally induced stress-sensitive diseases: anxiety, cancer, cardiovascular disease, depression and stroke. The Systematic Review Center for Laboratory animal Experimentation (SYRCLE) tool assessed individual studies' risks of bias. Random-effects meta-analyses supported the hypothesis: conventional housing significantly exacerbated disease severity with medium to large effect sizes: cancer (SMD = 0.71, 95% CI = 0.54-0.88); cardiovascular disease (SMD = 0.72, 95% CI = 0.35-1.09); stroke (SMD = 0.87, 95% CI = 0.59-1.15); signs of anxiety (SMD = 0.91, 95% CI = 0.56-1.25); signs of depression (SMD = 1.24, 95% CI = 0.98-1.49). It also increased mortality rates (hazard ratio = 1.48, 95% CI = 1.25-1.74; relative median survival = 0.91, 95% CI = 0.89-0.94). Meta-regressions indicated that such housing effects were ubiquitous across species and sexes, but could not identify the most impactful improvements to conventional housing. Data variability (assessed via coefficient of variation) was also not increased by 'enriched' housing.Conventional housing appears sufficiently distressing to compromise rodent health, raising ethical concerns. Results also add to previous work to show that research rodents are typically CRAMPED (cold, rotund, abnormal, male-biased, poorly surviving, enclosed and distressed), raising questions about the validity and generalisability of the data they generate. This research was funded by NSERC, Canada.

Conventional laboratory housing increases morbidity and mortality in research rodents: results of a meta-analysis

Abstract: Over 120 million mice and rats are used annually in research, conventionally housed in shoebox-sized cages that restrict natural behaviours (e.g. nesting and burrowing). This can reduce physical fitness, impair thermoregulation and reduce welfare (e.g. inducing abnormal stereotypic behaviours). In humans, chronic stress has biological costs, increasing disease risks and potentially shortening life. Using a pre-registered protocol ( https://atrium.lib.uoguelph.ca/xmlui/handle/10214/17955 ), this meta-analysis therefore tested the hypothesis that, compared to rodents in 'enriched' housing that better meets their needs, conventional housing increases stress-related morbidity and all-cause mortality.Comprehensive searches (via Ovid, CABI, Web of Science, Proquest and SCOPUS on May 24 2020) yielded 10,094 publications. Screening for inclusion criteria (published in English, using mice or rats and providing 'enrichments' in long-term housing) yielded 214 studies (within 165 articles, using 6495 animals: 59.1% mice; 68.2% male; 31.8% isolation-housed), and data on all-cause mortality plus five experimentally induced stress-sensitive diseases: anxiety, cancer, cardiovascular disease, depression and stroke. The Systematic Review Center for Laboratory animal Experimentation (SYRCLE) tool assessed individual studies' risks of bias. Random-effects meta-analyses supported the hypothesis: conventional housing significantly exacerbated disease severity with medium to large effect sizes: cancer (SMD = 0.71, 95% CI = 0.54-0.88); cardiovascular disease (SMD = 0.72, 95% CI = 0.35-1.09); stroke (SMD = 0.87, 95% CI = 0.59-1.15); signs of anxiety (SMD = 0.91, 95% CI = 0.56-1.25); signs of depression (SMD = 1.24, 95% CI = 0.98-1.49). It also increased mortality rates (hazard ratio = 1.48, 95% CI = 1.25-1.74; relative median survival = 0.91, 95% CI = 0.89-0.94). Meta-regressions indicated that such housing effects were ubiquitous across species and sexes, but could not identify the most impactful improvements to conventional housing. Data variability (assessed via coefficient of variation) was also not increased by 'enriched' housing.Conventional housing appears sufficiently distressing to compromise rodent health, raising ethical concerns. Results also add to previous work to show that research rodents are typically CRAMPED (cold, rotund, abnormal, male-biased, poorly surviving, enclosed and distressed), raising questions about the validity and generalisability of the data they generate. This research was funded by NSERC, Canada.