Ling Kong

Metabolomics approach to explore the effects of Kai-Xin-San on Alzheimer's disease using UPLC/ESI-Q-TOF mass spectrometry.

Alzheimers disease (AD) is a multifactorial neurodegenerative disease that influences elderly populations, with no effective method for its treatment so far. To improve its diagnosis and treatment, changes of small molecule metabolite during AD should be elucidated. Kai-Xin-San (KXS) is an herbal formulae that has been widely used to treat mental disorders, especially amnesia and depression in China. Experimental AD was induced in rats by an intraperitoneal injection of d-galactose (d-gal) and administered intragastrically with aluminum chloride (AlCl3) simultaneously for 105 days. Morris water maze task as a behavior test was used for testing the effects of KXS on AD model and pathological changes to the brain were assessed by hematoxylin-eosin staining and immunohistochemistry. The levels of Bcl-2 and ChAT in hippocampus were evaluated by western-blot. Furthermore, metabolite profiling of AD was performed through ultra-performance liquid chromatography/electrospray ionization quadruple time-of- flight-high-definition mass spectrometry (UPLC/ESI-Q-TOF/HDMS) combined with pattern recognition approaches and pathway analysis. d-gal and AlCl3-treated caused a decline in spatial learning and memory, hippocampal histopathological abnormalities and increased Aβ1-40 levels in the brain cortex and hippocampus along with decreased Bcl-2 and ChAT expression in the hippocampus. KXS significantly improved the cognitive impairment induced by d-gal and AlCl3, attenuated hippocampal histopathological abnormalities, reduced Aβ1-40 levels and increased Bcl-2 and ChAT expression in the hippocampus. A total of 48 metabolites were considered as potential biomarkers of AD, and 36 metabolites may correlate with the regulation of KXS treatment on AD. Changes in AD metabolic profiling were close to normal states through regulating multiple perturbed pathways after KXS treatment. This study has revealed the potential biomarkers and metabolic networks of AD, illuminated the biochemistry mechanism of AD and the metabolic pathways influenced by KXS.

An integrated chinmedomics strategy for discovery of effective constituents from traditional herbal medicine

Traditional natural product discovery affords no information about compound structure or pharmacological activities until late in the discovery process, and leads to low probabilities of finding compounds with unique biological properties. By integrating serum pharmacochemistry-based screening with high-resolution metabolomics analysis, we have developed a new platform, termed chinmedomics which is capable of directly discovering the bioactive constituents. In this work, the focus is on ShenQiWan (SQW) treatment of ShenYangXu (SYX, kidney-yang deficiency syndrome) as a case study, as determined by chinmedomics. With serum pharmacochemistry, a total of 34 peaks were tentatively characterised in vivo, 24 of which were parent components and 10 metabolites were detected. The metabolic profiling and potential biomarkers of SYX were also investigated and 23 differential metabolites were found. 20 highly correlated components were screened by the plotting of correlation between marker metabolites and serum constituents and considered as the main active components of SQW. These compounds are imported into a database to predict the action targets: 14 importantly potential targets were found and related to aldosterone-regulated sodium reabsorption and adrenergic signaling pathways. Our study showed that integrated chinmedomics is a powerful strategy for discovery and screening of effective constituents from herbal medicines.

Serum metabolomics strategy for understanding pharmacological effects of ShenQi pill acting on kidney yang deficiency syndrome.

Kidney yang deficiency syndrome, a diagnostic pattern in Chinese medicine, is similar with clinical features of the glucocorticoid withdrawal syndrome. The aim of this present study was to explore low molecular mass differentiating metabolites between control group and model group of kidney yang deficiency rats induced with corticosterone as well as the therapeutic effect of Shen Qi Pill, a classic traditional Chinese medicine formula for treating Kidney yang deficiency syndrome in China. This study utilized ultra-performance liquid chromatography coupled with electrospray ionization synapt quadrupole time-of-flight high definition mass spectrometry (UPLC/ESI-SYNAPT-QTOF-HDMS) to identify the underlying biomarkers for clarifying mechanism of Shen Qi Pill in treating Kidney yang deficiency syndrome based on metabolite profiling of the serum samples and in conjunction with multivariate and pathway analysis. Meanwhile, blood biochemistry assay and histopathology were examined to identify specific changes in the model group rats. Distinct changes in the pattern of metabolites were observed by UPLC-HDMS. The changes in metabolic profiling were restored to their baseline values after treatment with Shen Qi Pill according to the combined with a principal component analysis (PCA) score plots. Altogether, the current metabolomics approach based on UPLC-HDMS and orthogonal projection to latent structures discriminate analysis (OPLS-DA) demonstrated 27 ions (18 in the negative mode, 9 in the positive mode, 17 ions restored by Shen Qi Pill). These results indicated that effectiveness of Shen Qi Pill in Kidney yang deficiency syndrome rats induced a substantial change in the metabolic profiles by regulating the biomarkers and adjusting the metabolic disorder. It suggested that the metabolomics approach was a powerful approach for elucidation of pathologic changes of Chinese medicine syndrome and action mechanisms of traditional Chinese medicine.

Two decades of new drug discovery and development for Alzheimer's disease

Alzheimers disease is a progressive and irreversible neurodegenerative disease, associated with a decreased cognitive function and severe behavioral abnormalities. Due to its complex pathophysiological characteristics, complicated interactions with a large number of genes and proteins, there is still no effective drug treatment of the disease. Amyloid cascade aggregation of senile plaques and hyperphosphorylation of Tau protein to form neurofibrillary tangles are the main pathological features of Alzheimers disease, other mechanisms, such as oxidative stress, lack of central cholinergic neurotransmitters, inflammatory reaction and toxic metal ions have also been involved. The purpose of this review is to briefly introduce the progress of the development of the therapeutic agents based on their main mechanisms of action.

High-throughput chinmedomics-based prediction of effective components and targets from herbal medicine AS1350

This work was designed to explore the effective components and targets of herbal medicine AS1350 and its effect on “Kidney-Yang Deficiency Syndrome” (KYDS) based on a chinmedomics strategy which is capable of directly discovering and predicting the effective components, and potential targets, of herbal medicine. Serum samples were analysed by UPLC-MS combined with pattern recognition analysis to identify the biomarkers related to the therapeutic effects. Interestingly, the effectiveness of AS1350 against KYDS was proved by the chinmedomics method and regulated the biomarkers and targeting of metabolic disorders. Some 48 marker metabolites associated with alpha-linolenic acid metabolism, fatty acid metabolism, sphingolipids metabolism, phospholipid metabolism, steroid hormone biosynthesis, and amino acid metabolism were identified. The correlation coefficient between the constituents in vivo and the changes of marker metabolites were calculated by PCMS software and the potential effective constituents of AS1350 were also confirmed. By using chinmedomics technology, the components in AS1350 protecting against KYDS by re-balancing metabolic disorders of fatty acid metabolism, lipid metabolism, steroid hormone biosynthesis, etc. were deduced. These data indicated that the phenotypic characterisations of AS1350 altering the metabolic signatures of KYDS were multi-component, multi-pathway, multi-target, and overall regulation in nature.

Metabolomics‐proteomics profiles delineate metabolic changes in kidney fibrosis disease

Kidney fibrosis (KF) is a common process that leads to the progression of various types of kidney disease including kidney‐yang deficiency syndrome, however, little is known regarding the underlying biology of this disorder. Fortunately, integrated omics approaches provide the molecule fingerprints related to the disease. In an attempt to address this issue, we integrated metabolomics–proteomics profiles analyzed pathogenic mechanisms of KF based on rat model. A total 37 serum differential metabolites were contributed to KF progress, involved several important metabolic pathways. Using iTRAQ‐based quantitative proteomics analysis, 126 differential serum proteins were identified and provide valuable insight into the underlying mechanisms of KF. These proteins appear to be involved in complement and coagulation cascades, regulation of actin cytoskeleton, MAPK signaling pathway, RNA transport, etc. Interestingly, pathway/network analysis of integrated proteomics and metabolomics data firstly reveals that these signaling pathways were closely related with KF. It further indicated that most of these proteins play a pivotal role in the regulation of metabolism pathways.

Identifying quality-markers from Shengmai San protects against transgenic mouse model of Alzheimer's disease using chinmedomics approach

BACKGROUND Shengmai San (SMS), a Chinese classic herbal formula, has been widely used for the treatment of Qi-Yin deficiency syndrome in Asia. Modern pharmacological studies have shown that SMS improves the cognitive function. However, the quality markers (Q-markers) for SMS still need further research. PURPOSE Using chinmedocmics strategy to systematically evaluate the efficacy of SMS in the treatment of APPswe/PS1dE9 (APP/PS1) transgenic model of Alzheimers disease (AD) and to discover the efficacy-related Q-markers. METHODS The effect of SMS on APP/PS1 mice was evaluated by behavioral test, immunohistochemistry and urine metabolic profile, and the urine marker metabolites associated with SMS treatment of AD were characterized using metabolomics method. In the premise of efficacy, Serum Pharmacochemistry of Traditional Chinese Medicine was applied to investigate the in vivo constituents of SMS. A correlation analysis between marker metabolites of therapeutic effects and serum constituents was completed by chinmedomics approach. RESULTS SMS had a therapeutic effect on APP/PS1 mice, and 34 potential urine biomarkers were reversed by SMS treatment. A total of 17 in vivo constituents were detected, including 14 prototype components and 3 metabolites. The correlation analysis showed that eight constituents were extremely correlated with protective effects of SMS in AD, and considered as potential Q-markers of SMS, including schisandrin, isoschisandrin, angeloylgomisin Q, gomisin D, angeloylgomisin H, gomisin M2, ginsenoside F1, 20(R)-ginsenoside Rg3. CONCLUSION This study has demonstrated that chinmedomics is novel strategy for discovering the potential effective constituents from herbal formula, which are recognized as Q-markers.

High-Throughput Metabolomics for Discovering Potential Metabolite Biomarkers and Metabolic Mechanism from the APPswe/PS1dE9 Transgenic Model of Alzheimer’s Disease

Alzheimers disease (AD), a neurodegenerative disorder, is the major form of dementia. As AD is an irreversible disease, it is necessary to focus on earlier intervention. However, the potential biomarkers of preclinical AD are still not clear. In this study, urinary metabolomics based on ultra-high-performance liquid chromatography coupled with quadruple time-of-flight mass spectrometry was performed for delineating the metabolic changes and potential early biomarkers in APPswe/PS1dE9 (APP/PS1) transgenic mice. A total of 24 differentially regulated metabolites were identified when comparing transgenic mice to wild-type mice using multivariate statistical analysis. Among them, 10 metabolites were significantly upregulated and 14 metabolites were downregulated. On the basis of these potential biomarkers, metabolic pathway analysis found that pentose and glucuronate interconversions, glyoxylate and dicarboxylate metabolism, starch and sucrose metabolism, the citrate cycle, tryptophan metabolism, and arginine and proline metabolism were disturbed in APP/PS1 mice. Our study revealed that levels of endogenous metabolites in the urine of APP/PS1 mice changed prior to the emergence of learning and cognitive impairment, which may be associated with abnormal nitric oxide production pathways and metabolic disorders of monoaminergic neurotransmitters. In conclusion, this study showed that metabolomics provides an early indicator of disease occurrence for AD.

Rapid discovery of quality-markers from Kaixin San using chinmedomics analysis approach

BACKGROUND Alzheimers disease (AD), a progressive neurodegenerative disease, is more common disease of dementia among the elderly by multiple factors and presents enormous challenges in terms of diagnosis and treatment. Kaixin San (KXS), is a classic prescription for the treatment of memory decline and applied for AD nowadays. However, the quality-markers of KXS for the treatment of AD remain unclear. PURPOSE To investigate the effects and potential quality-markers of KXS against an APP/PS1 transgenic mouse model of AD. METHODS Two month old APP/PS1 transgenic model mice of AD were orally given KXS for 10 month to intervene. Through the novel object recognition (NOR), the classic Morris water maze (MWM), immunohistochemistry detection of Aβ1-42, Hematoxylin-eosin staining (HE), blood metabolic profiling evaluated the therapeutic effect of KXS on AD. PCMS software was applied to analysis correlations between biomarkers and serum constituents and became a powerful tool for excavating effective material basis. Behavior, histopathology and Chinmedomics were applied for assessing the efficacy and discovering potential quality-markers. RESULTS The result of MWM showed oral KXS could shorten the escape latency and increased the times of crossing the platform. The result of NOR showed oral KXS increased discrimination index (DI). Though the histopathology, KXS reduced the necrosis of neuron in brain tissue and the deposition of Aβ1-42. Chinmedomics strategy was used to analyze the biomarkers and blood components. KXS called back 20 biomarkers of AD. The effective material basis of KXS was ginsenoside Rf, ginsenoside F1, 20-O-glucopyranosyl ginsenoside Rf, dehydropachymic acid and E-3, 4, 5-trimethoxycinnamic acid. CONCLUSION This study demonstrate that KXS significantly improved cognitive function of transgenic mice of AD, repaired the damage caused by Aβ, regulated amino acid metabolism and lipid metabolism abnormalities and determined the effective material basis of KXS treating AD. Clarifying the quality-markers of KXS can establish scientific quality standard to reflect the safety and effectiveness of Traditional Chinese Medicine (TCM).

Advances in mass spectrometry-based metabolomics for investigation of metabolites

Metabolomics is the systematic study of all the metabolites present within a biological system, which consists of a mass of molecules, having a variety of physical and chemical properties and existing over an extensive dynamic range in biological samples. Diverse analytical techniques are needed to achieve higher coverage of metabolites. The application of mass spectrometry (MS) in metabolomics has increased exponentially since the discovery and development of electrospray ionization and matrix-assisted laser desorption ionization techniques. Significant advances have also occurred in separation-based MS techniques (gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, capillary electrophoresis-mass spectrometry, and ion mobility-mass spectrometry), as well as separation-free MS techniques (direct infusion-mass spectrometry, matrix-assisted laser desorption ionization-mass spectrometry, mass spectrometry imaging, and direct analysis in real time mass spectrometry) in the past decades. This review presents a brief overview of the recent advanced MS techniques and their latest applications in metabolomics. The software/websites for MS result analyses are also reviewed.