Perspectives on Data Analysis in Metabolomics: Points of Agreement and Disagreement from the 2018 ASMS Fall Workshop.

In November 2018, the American Society for Mass Spectrometry hosted the Annual Fall Workshop on informatic methods in metabolomics. The Workshop included sixteen lectures presented by twelve invited speakers. The focus of the talks was untargeted metabolomics performed with liquid chromatography/mass spectrometry. In this review, we highlight five recurring topics that were covered by multiple presenters: (i) data sharing, (ii) artifacts and contaminants, (iii) feature degeneracy, (iv) database organization, and (v) requirements for metabolite identification. Our objective here is to present viewpoints that were widely shared among participants, as well as those in which varying opinions were articulated. We note that most of the presenting speakers employed different data processing software, which underscores the diversity of informatic programs currently being used in metabolomics. We conclude with our thoughts on the potential role of reference datasets as a step towards standardizing data processing methods in metabolomics.

Emerging Applications of Metabolomics in Clinical Pharmacology.

Metabolic disturbances have been associated with many human diseases, including cancer, diabetes, and cardiovascular disease. Metabolomics, a rapidly growing member of the -omics family, investigates cellular metabolism by quantifying metabolites on a large scale and provides a link between metabolic pathways and the upstream genome that governs them. With the advances in analytical technologies, metabolomics is becoming a powerful tool for identifying diagnostic biomarkers of diseases, elucidating the pathological mechanisms, discovering novel drug targets, predicting drug responses, interpreting the mechanisms of drug action, as well as enabling precision treatment of patients. In this review, we highlight the recent advances of technologies and methodologies in metabolomics and their applications to the field of clinical pharmacology. Recent publications from 2013 to 2018 are covered in the review, and current challenges and potential future directions in the field are also discussed.

The Consortium of Metabolomics Studies (COMETS): Metabolomics in 47 Prospective Cohort Studies.

The Consortium of Metabolomics Studies (COMETS) was established in 2014 to facilitate large-scale collaborative research on the human metabolome and its relationship with disease etiology, diagnosis, and prognosis. COMETS comprises 47 cohorts from Asia, Europe, North America, and South America that together include more than 136,000 participants with blood metabolomics data on samples collected from 1985 to 2017. Metabolomics data were provided by 17 different platforms, with the most frequently used labs being Metabolon, Inc. (14 cohorts), the Broad Institute (15 cohorts), and Nightingale Health (11 cohorts). Participants have been followed for a median of 23 years for health outcomes including death, cancer, cardiovascular disease, diabetes, and others; many of the studies are ongoing. Available exposure-related data include common clinical measurements and behavioral factors, as well as genome-wide genotype data. Two feasibility studies were conducted to evaluate the comparability of metabolomics platforms used by COMETS cohorts. The first study showed that the overlap between any 2 different laboratories ranged from 6 to 121 metabolites at 5 leading laboratories. The second study showed that the median Spearman correlation comparing 111 overlapping metabolites captured by Metabolon and the Broad Institute was 0.79 (interquartile range, 0.56-0.89).

MS-based targeted metabolomics of eicosanoids and other oxylipins: Analytical and inter-individual variabilities.

Oxylipins, including the well-known eicosanoids, are potent lipid mediators involved in numerous physiological and pathological processes. Therefore, their quantitative profiling has gained a lot of attention during the last years notably in the active field of health biomarker discovery. Oxylipins include hundreds of structurally and stereochemically distinct lipid species which today are most commonly analyzed by (ultra) high performance liquid chromatography-mass spectrometry based ((U)HPLC-MS) methods. To maximize the utility of oxylipin profiling in clinical research, it is crucial to understand and assess the factors contributing to the analytical and biological variability of oxylipin profiles in humans. In this review, these factors and their impacts are summarized and discussed, providing a framework for recommendations expected to enhance the interlaboratory comparability and biological interpretation of oxylipin profiling in clinical research.

Biomarkers: background, classification and guidelines for applications in nutritional epidemiology

One of the main problems in nutritional epidemiology is to assess food intake as well as nutrient/food component intake to a high level of validity and reliability. To help in this process, the need to have good biomarkers that more objectively allow us to evaluate the diet consumed in a more standardized, valid and precise way has often been commented upon. There are various definitions of biomarkers and also different classifications of the same. In general a biomarker can be defined as a characteristic that can objectively measure different biological samples and that can be evaluated as an exposure marker of normal or pathogenic biological processes or of responses to a certain intervention. The biological samples most commonly used in nutritional epidemiology are blood, red blood cells, plasma, serum, urine, nails, saliva, faeces and samples of different tissues. Exposure biomarkers (dietary intake), biomarkers of effects and biomarkers of disease status can be determined from these samples. In turn, exposure biomarkers can be temporarily categorized into markers of acute, medium term or chronic effects. Many difficulties arise in identifying good biomarkers. Currently, advances in omics are opening up new possibilities for obtaining new biomarkers of various kinds, using genomics, epigenomics, transcriptomics, lipidomics, proteomics and metabolomics. We shall review the present situation of biomarkers in nutritional epidemiology as well as the future trends of the new omic biomarkers (AU)

En los estudios de epidemiología nutricional uno de los principales problemas es conocer la ingestión de alimentos y sus componentes de manera válida y precisa. Para ayudar en este proceso se ha planteado repetidas veces la necesidad de contar con buenos biomarcadores, que de manera más objetiva nos permitan conocer de manera más estandarizada, válida y precisa la dieta consumida. Existen varias definiciones de biomarcador y también distintas clasificaciones de los mismos. En general un biomarcador es una característica que puede medir objetivamente en distintas muestras biológicas y que puede evaluarse como indicador de exposiciones, de procesos biológicos normales o patogénicos o de respuestas a una intervención determinada. Las muestras biológicas más utilizadas en epidemiología nutricional son sangre total, eritrocitos, plasma, suero, orina, uñas, saliva, heces y muestras de distintos tejidos. En estas muestras se pueden determinar biomarcadores de exposición (ingesta dietética), biomarcadores de efectos y biomarcadores de estado de enfermedad. A su vez los biomarcadores de exposición pueden categorizarse temporalmente en biomarcadores de efectos agudos, a medio plazo y crónicos. Existen muchas dificultades en la identificación de buenos biomarcadores. Actualmente los avances en las nuevas ómicas están abriendo nuevas posbilidades para la obtención de nuevos biomarcadores de distintos tipos utilizando genómica, epigenómica, transcriptómica, lipidó- mica, proteómica y metabolómica. Revisaremos el estado actual de los biomarcadores en epidemiología nutricional así como las tendencias futuras de los nuevos biomarcadores ómicos (AU)

Biomarcadores: antecedentes, clasificación y guía para su aplicación en epidemiología nutricional / Biomarkers: background, clasiffication and guidelines for applications in nuttritional epidemiology

En los estudios de epidemiología nutricional uno de los principales problemas es conocer la ingestión de alimentos y sus componentes de manera válida y precisa. Para ayudar en este proceso se ha planteado repetidas veces la necesidad de contar con buenos biomarcadores, que de manera más objetiva nos permitan conocer de manera más estandarizada, válida y precisa la dieta consumida. Existen varias definiciones de biomarcador y también distintas clasificaciones de los mismos. En general un biomarcador es una característica que puede medir objetivamente en distintas muestras biológicas y que puede evaluarse como indicador de exposiciones, de procesos biológicos normales o patogénicos o de respuestas a una intervención determinada. Las muestras biológicas más utilizadas en epidemiología nutricional son sangre total, eritrocitos, plasma, suero, orina, uñas, saliva, heces y muestras de distintos tejidos. En estas muestras se pueden determinar biomarcadores de exposición (ingesta dietética), biomarcadores de efectos y biomarcadores de estado de enfermedad. A su vez los biomarcadores de exposición pueden categorizarse temporalmente en biomarcadores de efectos agudos, a medio plazo y crónicos. Existen muchas dificultades en la identificación de buenos biomarcadores. Actualmente los avances en las nuevas ómicas están abriendo nuevas posibilidades para la obtención de nuevos biomarcadores de distintos tipos utilizando genómica, epigenómica, transcriptómica, lipidómica, proteómica y metabolómica. Revisaremos el estado actual de los biomarcadores en epidemiología nutricional así como las tendencias futuras de los nuevos biomarcadores ómicos (AU)

One of the main problems in nutritional epidemiology is to assess food intake as well as nutrient/food component intake to a high level of validity and reliability. To help in this process, the need to have good biomarkers that more objectively allow us to evaluate the diet consumed in a more standardized, valid and precise way has often been commented upon. There are various definitions of biomarkers and also different classifications of the same. In general a biomarker can be defined as a characteristic that can objectively measure different biological samples and that can be evaluated as an exposure marker of normal or pathogenic biological processes or of responses to a certain intervention. The biological samples most commonly used in nutritional epidemiology are blood, red blood cells, plasma, serum, urine, nails, saliva, faeces and samples of different tissues. Exposure biomarkers (dietary intake), biomarkers of effects and biomarkers of disease status can be determined from these samples. In turn, exposure biomarkers can be temporarily categorized into markers of acute, medium term or chronic effects. Many difficulties arise in identifying good biomarkers. Currently, advances in omics are opening up new possibilities for obtaining new biomarkers of various kinds, using genomics, epigenomics, transcriptomics, lipidomics, proteomics and metabolomics. We shall review the present situation of biomarkers in nutritional epidemiology as well as the future trends of the new omic biomarkers (AU)

Integrated genomics and metabolomics in nephrology.

Applying 'omics' approaches such as genome-wide association studies (GWAS) and metabolome analyses, genes and metabolites have been identified to be associated with renal pathophysiology. Meta-analyses of GWAS from large epidemiologic cohorts uncovered several novel loci linked with estimated glomerular filtration rate and chronic kidney disease (CKD). Sophisticated analytical technologies, including mass spectrometry and nuclear magnetic resonance spectroscopy, allow the analyses of up to 4000 targeted and non-targeted metabolites in plasma, serum and urine. Several uraemic toxins were found that were increased in CKD. Among them, arginine derivatives like asymmetric dimethylarginine or tryptophane metabolites have been identified as promising candidates to target mechanisms of kidney disease progression. This review aims to summarize recent findings in clinical kidney diseases research revealed by 'omics' approaches with a clear focus on recent genomics and metabolomics efforts.

La proteómica y la metabolómica: los mecanismos de la enfermedad cardiovascular y el descubrimiento de biomarcadores / Proteomics and metabolomics for mechanistic insights and biomarker discovery in cardiovascular disease

En la última década, la proteómica y la metabolómica han realizado aportaciones sustanciales al conocimiento de las enfermedades cardiovasculares. La evaluación no sesgada de los procesos fisiopatológicos sin partir de presunciones establecidas a priori complementa otras técnicas de biología molecular que se emplean en la actualidad con un enfoque reduccionista. En la presente revisión, se resaltan algunos de los métodos de las ciencias «ómicas» que se emplean para evaluar los cambios de las proteínas y los metabolitos en la enfermedad cardiovascular. Es muy infrecuente que una función biológica específica discreta se atribuya a una sola molécula; es más habitual que se lleve a cabo con la aportación combinada de muchas proteínas. A diferencia del enfoque reduccionista, en el que se estudia individualmente las moléculas, las plataformas «ómicas» permiten el estudio de interacciones más complejas en sistemas biológicos. La combinación de la proteómica y la metabolómica para cuantificar los cambios de los metabolitos y sus correspondientes enzimas hará avanzar nuestro conocimiento de los mecanismos fisiopatológicos y facilitará la identificación de nuevos biomarcadores de enfermedad cardiovascular (AU)

In the last decade, proteomics and metabolomics have contributed substantially to our understanding of cardiovascular diseases. The unbiased assessment of pathophysiological processes without a priori assumptions complements other molecular biology techniques that are currently used in a reductionist approach. In this review, we highlight some of the «omics» methods used to assess protein and metabolite changes in cardiovascular disease. A discrete biological function is very rarely attributed to a single molecule; more often it is the combined input of many proteins. In contrast to the reductionist approach, in which molecules are studied individually, «omics» platforms allow the study of more complex interactions in biological systems. Combining proteomics and metabolomics to quantify changes in metabolites and their corresponding enzymes will advance our understanding of pathophysiological mechanisms and aid the identification of novel biomarkers for cardiovascular disease (AU)

Quality assessment of ginseng by (1)H NMR metabolite fingerprinting and profiling analysis.

Metabolite profiling and fingerprint analysis by (1)H NMR spectroscopy were used to identify potential biomarkers capable of distinguishing different ginseng species, varieties, and commercial products with the aim of establishing quality control code protocol based on biochemical phenotype. Principal component (PC) analyses of (1)H NMR spectra reliably discriminated between the various ginseng samples, demonstrating the potential utility of metabolomics in the natural health products industry. Four Asian ginseng varieties separated along the PC1 and PC2 axes, and four different Korean ginseng products were divided into two groups by PC1. A strong separation was also revealed between Asian ginseng (Panax ginseng) and American ginseng (Panax quinquefolius). Glutamine, arginine, sucrose, malate, and myo-inositol were the major metabolites in ginseng samples tested in this study. Combined metabolite fingerprinting and profiling suggested that several compounds including glucose, fumarate, and various amino acids could serve as biomarkers for quality assurance in ginseng.