Metabolomics, the profiling of small molecules globally in a given systems biology, is an emerging technological platform. Recently, metabolomics has shown tremendous potential to understand the mechanisms of underlying medical conditions such as diabetes and cardiovascular diseases. The metabolomics with other upstream omics readouts integration (i.e., proteomics, transcriptomics, and genomics) help identify novel pathways and disease mechanisms. Metabolic biomarkers have shown great potential to be integrated with known genetic and clinical variations to provide solid diagnostic and risk prediction models. Metabolites create a connection between the genotype and phenotype, which is a great tool for stratifying patients with multiple clinical conditions. Populations' genome project has introduced ample genetic and phenotypic information. Utilizing the clinical genomics project's concrete setup from the technical and bioinformatics platform has allowed mass spectrometry (MS) and nuclear magnetic resonance (NMR) based metabolomics to be integrated for better health outcomes.
Metabolomics has shown a significant association and integration with the genomics and clinical readouts for developing diagnostic and prediction models for each disease. This unique integration has improved the patients' health outcomes by promptly précising the diagnosis and providing scientists with a better understanding of the disease mechanism. The primary objective of this Research Topic is to introduce a global map of functional relationships between diseases' cell components and their personalized medicine variations for genetic and endocrinological diseases. However, the study design, analytical tools, data analysis, and interpretation are the significant points considered in this Research Topic to successfully integrate metabolomics with another omics dataset and clinical phenotypes.
This Research Topic aims to cover recent advances in metabolomics and their applications in genetic and endocrinological diseases. We accept all types of manuscript submissions, including Original Research, Review, Hypothesis and Theory, Methods, Mini-Review, and Perspective. Topics of interest include, but are not limited to, the following themes:
• Metabolomics and Lipidomics methodological development
• Metabolomics-wide association study (MWAS) in genetic diseases
• Metabolomics biomarker discovery in genetics and endocrinological diseases
• Application of metabolomics and Lipidomics in endocrinology diseases
• Investigation of drug administration at metabolomics level.
• Investigation of environmental exposures on the cellular metabolism
Metabolomics, the profiling of small molecules globally in a given systems biology, is an emerging technological platform. Recently, metabolomics has shown tremendous potential to understand the mechanisms of underlying medical conditions such as diabetes and cardiovascular diseases. The metabolomics with other upstream omics readouts integration (i.e., proteomics, transcriptomics, and genomics) help identify novel pathways and disease mechanisms. Metabolic biomarkers have shown great potential to be integrated with known genetic and clinical variations to provide solid diagnostic and risk prediction models. Metabolites create a connection between the genotype and phenotype, which is a great tool for stratifying patients with multiple clinical conditions. Populations' genome project has introduced ample genetic and phenotypic information. Utilizing the clinical genomics project's concrete setup from the technical and bioinformatics platform has allowed mass spectrometry (MS) and nuclear magnetic resonance (NMR) based metabolomics to be integrated for better health outcomes.
Metabolomics has shown a significant association and integration with the genomics and clinical readouts for developing diagnostic and prediction models for each disease. This unique integration has improved the patients' health outcomes by promptly précising the diagnosis and providing scientists with a better understanding of the disease mechanism. The primary objective of this Research Topic is to introduce a global map of functional relationships between diseases' cell components and their personalized medicine variations for genetic and endocrinological diseases. However, the study design, analytical tools, data analysis, and interpretation are the significant points considered in this Research Topic to successfully integrate metabolomics with another omics dataset and clinical phenotypes.
This Research Topic aims to cover recent advances in metabolomics and their applications in genetic and endocrinological diseases. We accept all types of manuscript submissions, including Original Research, Review, Hypothesis and Theory, Methods, Mini-Review, and Perspective. Topics of interest include, but are not limited to, the following themes:
• Metabolomics and Lipidomics methodological development
• Metabolomics-wide association study (MWAS) in genetic diseases
• Metabolomics biomarker discovery in genetics and endocrinological diseases
• Application of metabolomics and Lipidomics in endocrinology diseases
• Investigation of drug administration at metabolomics level.
• Investigation of environmental exposures on the cellular metabolism
