Practicing precision medicine with intelligently integrative clinical and multi-omics data analysis.

Precision medicine aims to empower clinicians to predict the most appropriate course of action for patients with complex diseases like cancer, diabetes, cardiomyopathy, and COVID-19. With a progressive interpretation of the clinical, molecular, and genomic factors at play in diseases, more effective and personalized medical treatments are anticipated for many disorders. Understanding patient's metabolomics and genetic make-up in conjunction with clinical data will significantly lead to determining predisposition, diagnostic, prognostic, and predictive biomarkers and paths ultimately providing optimal and personalized care for diverse, and targeted chronic and acute diseases. In clinical settings, we need to timely model clinical and multi-omics data to find statistical patterns across millions of features to identify underlying biologic pathways, modifiable risk factors, and actionable information that support early detection and prevention of complex disorders, and development of new therapies for better patient care. It is important to calculate quantitative phenotype measurements, evaluate variants in unique genes and interpret using ACMG guidelines, find frequency of pathogenic and likely pathogenic variants without disease indicators, and observe autosomal recessive carriers with a phenotype manifestation in metabolome. Next, ensuring security to reconcile noise, we need to build and train machine-learning prognostic models to meaningfully process multisource heterogeneous data to identify high-risk rare variants and make medically relevant predictions. The goal, today, is to facilitate implementation of mainstream precision medicine to improve the traditional symptom-driven practice of medicine, and allow earlier interventions using predictive diagnostics and tailoring better-personalized treatments. We strongly recommend automated implementation of cutting-edge technologies, utilizing machine learning (ML) and artificial intelligence (AI) approaches for the multimodal data aggregation, multifactor examination, development of knowledgebase of clinical predictors for decision support, and best strategies for dealing with relevant ethical issues.

Metabolomic insights into the mode of action of natural products in the treatment of liver disease.

The human population is burdened by morbidity and mortality from liver diseases that largely arise due to hepatitis virus infection, alcohol abuse, obesity, and diabetes. Despite 2 million global deaths per annum from liver disease, the number of drugs approved by the U.S. Food and Drug Administration (FDA) for the treatment of these disorders is sparse. Eastern medicine embodies a millennia long tradition in the use of natural product remedies for liver disease, which has attracted the interest of western medical practitioners and patients alike. Questions remain regarding the safety, efficacy, and quality of such natural products in a western medical context. Of particular concern is whether or not the mechanism of action of the product is known and, if the remedy has multiple natural constituents, how these interact at a biochemical, physiological, and clinical level. In this Commentary, we have examined the potential of metabolomics to help answer these queries, illustrated by investigations of yin chen hao tang, silymarin, and xiaozhang tie. In all cases, unique understandings of the mechanism of action of these natural products was obtained through metabolomic investigations in animal models, cell culture systems, and in clinical studies. Such mechanistic insights help assure the safety and efficacy of these natural product therapies.

Therapeutic targets of oxidative/nitrosative stress and neuroinflammation in ischemic stroke: Applications for natural product efficacy with omics and systemic biology.

Oxidative/nitrosative stress and neuroinflammation are critical pathological processes in cerebral ischemia-reperfusion injury, and their intimate interactions mediate neuronal damage, blood-brain barrier (BBB) damage and hemorrhagic transformation (HT) during ischemic stroke. We review current progress towards understanding the interactions of oxidative/nitrosative stress and inflammatory responses in ischemic brain injury. The interactions between reactive oxygen species (ROS)/reactive nitrogen species (RNS) and innate immune receptors such as TLR2/4, NOD-like receptor, RAGE, and scavenger receptors are crucial pathological mechanisms that amplify brain damage during cerebral ischemic injury. Furthermore, we review the current progress of omics and systematic biology approaches for studying complex network regulations related to oxidative/nitrosative stress and inflammation in the pathology of ischemic stroke. Targeting oxidative/nitrosative stress and neuroinflammation could be a promising therapeutic strategy for ischemic stroke treatment. We then review recent advances in discovering compounds from medicinal herbs with the bioactivities of simultaneously regulating oxidative/nitrosative stress and pro-inflammatory molecules for minimizing ischemic brain injury. These compounds include sesamin, baicalin, salvianolic acid A, 6-paradol, silymarin, apocynin, 3H-1,2-Dithiole-3-thione, (-)-epicatechin, rutin, Dl-3-N-butylphthalide, and naringin. We finally summarize recent developments of the omics and systematic biology approaches for exploring the molecular mechanisms and active compounds of Traditional Chinese Medicine (TCM) formulae with the properties of antioxidant and anti-inflammation for neuroprotection. The comprehensive omics and systematic biology approaches provide powerful tools for exploring therapeutic principles of TCM formulae and developing precision medicine for stroke treatment.

[Development of Plant Metabolomics and Medicinal Plant Genomics].

A variety of chemicals produced by plants, often referred to as 'phytochemicals', have been used as medicines, food, fuels and industrial raw materials. Recent advances in the study of genomics and metabolomics in plant science have accelerated our understanding of the mechanisms, regulation and evolution of the biosynthesis of specialized plant products. We can now address such questions as how the metabolomic diversity of plants is originated at the levels of genome, and how we should apply this knowledge to drug discovery, industry and agriculture. Our research group has focused on metabolomics-based functional genomics over the last 15 years and we have developed a new research area called 'Phytochemical Genomics'. In this review, the development of a research platform for plant metabolomics is discussed first, to provide a better understanding of the chemical diversity of plants. Then, representative applications of metabolomics to functional genomics in a model plant, Arabidopsis thaliana, are described. The extension of integrated multi-omics analyses to non-model specialized plants, e.g., medicinal plants, is presented, including the identification of novel genes, metabolites and networks for the biosynthesis of flavonoids, alkaloids, sulfur-containing metabolites and terpenoids. Further, functional genomics studies on a variety of medicinal plants is presented. I also discuss future trends in pharmacognosy and related sciences.

Recent developments in deuterium oxide tracer approaches to measure rates of substrate turnover: implications for protein, lipid, and nucleic acid research.

PURPOSE OF REVIEW: Methods that inform on dynamic metabolism that can be applied to clinical populations to understand disease progression and responses to therapeutic interventions are of great importance. This review perspective will highlight recent advances, development, and applications of the multivalent stable isotope tracer deuterium oxide (D2O) to the study of substrate metabolism with particular reference to protein, lipids, and nucleic acids, and how these methods can be readily applied within clinical and pharmaceutical research. RECENT FINDINGS: Advances in the application of D2O techniques now permit the simultaneous dynamic measurement of a range of substrates (i.e. protein, lipid, and nucleic acids, along with the potential for OMICs methodologies) with minimal invasiveness further creating opportunities for long-term 'free living' measures that can be used in clinical settings. These techniques have recently been applied to ageing populations and further in cancer patients revealing altered muscle protein metabolism. Additionally, the efficacy of numerous drugs in improving lipoprotein profiles and controlling cellular proliferation in leukaemia have been revealed. SUMMARY: D2O provides opportunities to create a more holistic picture of in-vivo metabolic phenotypes, providing a unique platform for development in clinical applications, and the emerging field of personalized medicine.

Exploring cancer metabolism using stable isotope-resolved metabolomics (SIRM).

Metabolic reprogramming is a hallmark of cancer. The changes in metabolism are adaptive to permit proliferation, survival, and eventually metastasis in a harsh environment. Stable isotope-resolved metabolomics (SIRM) is an approach that uses advanced approaches of NMR and mass spectrometry to analyze the fate of individual atoms from stable isotope-enriched precursors to products to deduce metabolic pathways and networks. The approach can be applied to a wide range of biological systems, including human subjects. This review focuses on the applications of SIRM to cancer metabolism and its use in understanding drug actions.

[Metabolomics research of medicinal plants].

Metabolomics is the comprehensively study of chemical processes involving small molecule metabolites. It is an important part of systems biology, and is widely applied in complex traditional Chinese medicine（TCM）system. Metabolites biosynthesized by medicinal plants are the effective basis for TCM. Metabolomics studies of medicinal plants will usher in a new period of vigorous development with the implementation of Herb Genome Program and the development of TCM synthetic biology. This manuscript introduces the recent research progresses of metabolomics technology and the main research contents of metabolomics studies for medicinal plants, including identification and quality evaluation for medicinal plants, cultivars breeding, stress resistance, metabolic pathways, metabolic network, metabolic engineering and synthetic biology researches. The integration of genomics, transcriptomics and metabolomics approaches will finally lay foundation for breeding of medicinal plants, R&D, quality and safety evaluation of innovative drug.

The Progress of Metabolomics Study in Traditional Chinese Medicine Research.

Traditional Chinese medicine (TCM) has played important roles in health protection and disease treatment for thousands of years in China and has gained the gradual acceptance of the international community. However, many intricate issues, which cannot be explained by traditional methods, still remain, thus, new ideas and technologies are needed. As an emerging system biology technology, the holistic view adopted by metabolomics is similar to that of TCM, which allows us to investigate TCM with complicated conditions and multiple factors in depth. In this paper, we tried to give a timely and comprehensive update about the methodology progression of metabolomics, as well as its applications, in different fields of TCM studies including quality control, processing, safety and efficacy evaluation. The herbs investigated by metabolomics were selected for detailed examination, including Anemarrhena asphodeloides Bunge, Atractylodes macrocephala Kidd, Pinellia ternate, etc.; furthermore, some valuable results have been obtained and summarized. In conclusion, although the study of metabolomics is at the early phase and requires further scrutiny and validation, it still provides bright prospects to dissect the synergistic action of multiple components from TCM. Overall, with the further development of analytical techniques, especially multi-analysis techniques, we expect that metabolomics will greatly promote TCM research and the establishment of international standards, which is beneficial to TCM modernization.

Novel therapeutic strategy in the management of COPD: a systems medicine approach.

Respiratory diseases including chronic-obstructive-pulmonary-disease (COPD) are globally increasing, with COPD predicted to become the third leading cause of global mortality by 2020. COPD is a heterogeneous disease with COPD-patients displaying different phenotypes as a result of a complex interaction between various genetic, environmental and life-style factors. In recent years, several investigations have been performed to better define such interactions, but the identification of the resulting phenotypes is still somewhat difficult, and may lead to inadequate assessment and management of COPD (usually based solely on the severity of airflow limitation parameter FEV1). In this new scenario, the management of COPD has been driven towards an integrative and holistic approach. The degree of complexity requires analyses based on large datasets (also including advanced functional genomic assays) and novel computational biology approaches (essential to extract information relevant for the clinical decision process and for the development of new drugs). Therefore, according to the emerging "systems/network medicine", COPD should be re.-evaluated considering multiple network(s) perturbations such as genetic and environmental changes. Systems Medicine (SM) platforms, in which patients are extensively characterized, offer a basis for a more targeted clinical approach, which is predictive, preventive, personalized and participatory ("P4-medicine"). It clearly emerges that in the next future, new opportunities will become available for clinical research on rare COPD patterns and for the identification of new biomarkers of comorbidity, severity, and progression. Herein, we overview the literature discussing the opportunity coming from the adoption of SMapproaches in COPD management, focusing on proteomics and metabolomics, and emphasizing the identification of disease sub-clusters, to improve the development of more effective therapies.

[Metabolome and mass spectrometry: new biomedical analysis perspectives]. / Métabolomique et spectrométrie de masse : de nouvelles perspectives en analyse biomédicale.

Metabolomics is defined as an integrative approach consisting in the comprehensive analysis of all of the small molecules of a biological system (the "metabolome"). The main objective of metabolomics in medecine is to discover metabolic biomarkers for diseases. Mass spectrometry (MS) coupled to liquid or gas chromatography is amongst major analytical tools used in metabolomics. However, the holistic approach used in metabolomics requires very good performances of the analytical system (chromatographic column and MS equipment) and the use of non-conventional validation strategies. Metabolomics workflow can be divided in three main steps: sample preparation, MS data acquisition and processing, and statistical analysis. Processing of the "raw" data (obtained after MS acquisition) is mostly required to normalise chromatographic conditions and to carry out accurate quantification of MS features. Features resulting from this processing may be identified later. The statistical analyses include typically multivariate techniques such as supervised and non-supervised methods. Supervised methods make use of the response variable (e.g., case/control) for model construction while non-supervised methods do not use this piece of information. When the study is focused on a particular set of metabolites, targeted metabolomics could be an interesting alternative to the holistic approach since it may allow absolute quantitation and be associated with a reduced cost.

[Perspective and application of metabonomics in modern study of traditional Chinese medicine].

Metabonomics is a new method to study on the metabolic network and the relationship between body and environment, which conforms to the way of traditional Chinese medicine (TCM) research. In the study process of modernization of traditional Chinese medicine, effectively conjunction with metabonomics method will facilitate the integration of TCM with modern biological science and technology, and promote the modernization of TCM. This paper introduce the application of metabonomics in the research of toxicity mechanism of TCM, compatibility mechanism of TCM formula, pharmacology effect of TCM and processing mechanism of TCM. This paper summarize the problems in the TCM metabonomics research and prospect its bright future.

The impact of DNA methylation technologies on drug toxicology.

INTRODUCTION: Drug toxicology is central to drug development. Despite improvements in our understanding of molecular and cell biology, high attrition rates in drug development continue, speaking to the difficulties of developing unequivocal methods to predict the efficacy and safety of drugs. AREAS COVERED: In this review, the authors provide a short overview of the 'omics' technologies that have been applied to drug toxicology, with an emphasis on a whole-genome DNA methylation analysis. Preliminary results from DNA methylation analysis technologies that may help in predicting response and efficacy of a drug are discussed. EXPERT OPINION: Currently, we cannot fully contextualize the application of epigenetics to the field of drug toxicology, as there are still many challenges to overcome before DNA methylation-based biomarkers can be effectively used in drug development. Comprehensive whole-genome DNA methylation methods for a unbiased analysis based on either microarray or next-generation sequencing need to be evaluated in drug toxicology in an intensive and systematic manner. Additionally, robust analysis systems need to be developed to decode the large amounts of data generated by whole-genome DNA methylation analyses as well as protocol standardization for reproducibility to develop meaningful databases that can be applied to drug toxicology.

An emerging role for metabolomics in nutrition science.

Nutritional research is undergoing a remarkable transformation driven by new technological tools. Because of the complexity of the components present in food and how they may interact with the biochemical networks of living organisms, nutrition cannot be considered a reductionist discipline. More holistic approaches, which are capable of gathering comprehensive, high-throughput amounts of data, appear to best enhance our understanding of the role of food in health and disease. In this context, global metabolite analysis, or 'metabolomics', is becoming an appealing research tool for nutrigenomics and nutrigenetics scientists. The purpose of the present review is to highlight some potential applications of metabolomics in nutrition research.

Emerging applications of metabolomics in studying chemopreventive phytochemicals.

Phytochemicals from diet and herbal medicines are under intensive investigation for their potential use as chemopreventive agents to block and suppress carcinogenesis. Chemical diversity of phytochemicals, together with complex metabolic interactions between phytochemicals and biological system, can overwhelm the capacity of traditional analytical platforms, and thus pose major challenges in studying chemopreventive phytochemicals. Recent progresses in metabolomics have transformed it to become a robust systems biology tool, suitable for examining both chemical and biochemical events that contribute to the cancer prevention activities of plant preparations or their bioactive components. This review aims to discuss the technical platform of metabolomics and its existing and potential applications in chemoprevention research, including identifying bioactive phytochemicals in plant extracts, monitoring phytochemical exposure in humans, elucidating biotransformation pathways of phytochemicals, and characterizing the effects of phytochemicals on endogenous metabolism and cancer metabolism.

[Advance of studies on metabolic fingerprinting analytical techniques and data processing methods].

Metabolomics is an emerging discipline subsequent to genomics, transcriptomics and proteomics, aiming for systematically studying the regularity of changes in metabolite to revealing organism's nature of movement and metabolism. It is especially important in modern pharmacological studies. Metabolic fingerprinting analysis is a method for metabolic analysis on high throughput of all metabolites, studying changes in drugs, organisms and endogenic metabolites caused by drugs and finding out related biomarkers to reflect dynamic changes inside organisms more directly and explain the mechanism of drugs and their effects on diseases. This essay summarizes some new metabolic fingerprint analytical methods and data processing methods used for metabolic fingerprint, elaborates their advantages and disadvantages and looks ahead to their combination with studies on traditional Chinese medicines, providing room for the development of new methods and new approaches for studies on complexity theory system of traditional Chinese medicines.

Application of metabolomics approaches to the study of respiratory diseases.

Metabolomics is the global unbiased analysis of all the small-molecule metabolites within a biological system, under a given set of conditions. These methods offer the potential for a holistic approach to clinical medicine, as well as improving disease diagnosis and understanding of pathological mechanisms. Respiratory diseases including asthma and chronic obstructive pulmonary disorder are increasing globally, with the latter predicted to become the third leading cause of global mortality by 2020. The root causes for disease onset remain poorly understood and no cures are available. This review presents an overview of metabolomics followed by in-depth discussion of its application to the study of respiratory diseases, including the design of metabolomics experiments, choice of clinical material collected and potentially confounding experimental factors. Particular challenges in the field are presented and placed within the context of the future of the applications of metabolomics approaches to the study of respiratory diseases.

Recent highlights of metabolomics for traditional Chinese medicine.

Systems biology is an emerging science of the 21st century and has developed in recent years from a technology-driven enterprise to a new strategic tool in life sciences as well as its method and design resemble those of traditional Chinese medicine (TCM), a holistic approach to health that attempts to bring the body, mind and spirit into harmony. The technology platforms of systems biology, especially metabolomics could provide useful tools for facilitating drug discovery and development of TCM. Metabolomes of medicinal herbal medicine are particularly a valuable natural resource for the evidence-based TCM. Metabolomics adopts a 'top-down' strategy to reflect the function of organisms from terminal symptoms of metabolic network and understand metabolic changes of a complete system caused by interventions in holistic context. Its property consists with the holistic thinking of TCM, may beneficially provide an opportunity to scientifically express the meaning of evidence-based Chinese medicine, will greatly benefit both drug discovery and development for TCM research. Some successful metabolomic applications in important TCM field related to drug discovery and development from natural sources aims at raising the potential of metabolomics in reducing the gap between TCM and modern drug discovery demand, highlight the key role of biomarkers for drug discovery and development of traditional oriental medicine.

Pharma-metabolomics in neonatology: is it a dream or a fact?

The 'omics' technologies represent analytical approaches that have a holistic view on molecules such as genes, transcripts, proteins and metabolites constituting a cell, tissue or organism. The profiling of genes, transcripts and proteins has been referred to as genomics, transcriptomics and proteomics. Finally, there is the youngest and most rapidly increasing of the "omics" disciplines: metabolomics. Metabolomics appears to be a new, very useful tool in neonatology, especially in the fields of pharma-metabolomics and nutri- metabolomics. Since it appears to be predictive and preventive, it can be considered the 'new clinical chemistry' for personalized neonatal medicine. At present, the use of metabolomics in neonatology is still in the pioneering phase. In clinical practice, only a limited number of metabolites are routinely measured in the biofluids of newborns by conventional analytical methods to study the metabolic status of the organism. However, the management of sick or preterm newborns might be improved if more information on perinatal/ neonatal maturational processes and their metabolic background were available. The aim of this review, after a general introduction on pharma-metabolomics, is to present the potential of NMR-based metabolomic analysis of newbom urine in neonatology in the field of pharmacology.

Recent and potential developments of biofluid analyses in metabolomics.

Metabolomics, one of the 'omic' sciences in systems biology, is the global assessment and validation of endogenous small-molecule metabolites within a biologic system. Analysis of these key metabolites in body fluids has become an important role to monitor the state of biological organisms and is a widely used diagnostic tool for disease. A majority of these metabolites are being applied to metabolic profiling of the biological samples, for example, plasma and whole blood, serum, urine, saliva, cerebrospinal fluid, synovial fluid, semen, and tissue homogenates. However, the recognition of the need for a holistic approach to metabolism led to the application of metabolomics to biological fluids for disease diagnostics. A recent surge in metabolomic applications which are probably more accurate than routine clinical practice, dedicated to characterizing the biological fluids. While developments in the analysis of biofluid samples encompassing an important impediment, it must be emphasized that these biofluids are complementary. Metabolomics provides potential advantages that classical diagnostic approaches do not, based on following discovery of a suite of clinically relevant biomarkers that are simultaneously affected by the disease. Emerging as a promising biofocus, metabolomics will drive biofluid analyses and offer great benefits for public health in the long-term.