Clinical Metabolomics Applications in Genetic Diseases [E-Book]

Chapter 1. The advanced technology and clinical application in metabolomics -- Chapter 2. Mass Spectrometry-Based Metabolomics for the Clinical Laboratory -- Chapter 3. Metabolomics: a pipeline for biomarker discovery in genetic diseases -- Chapter 4. Bioinformatics Tools for Clinical Metabolomics -- Chapter 5. Untargeted Metabolomics in Newborn Screening -- Chapter 6. Untargeted Metabolomics, Targeted Care: The Clinical Utilities of Bedside Metabolomics -- Chapter 7. Metabolomics in the Study of Human Mitochondrial Diseases -- Chapter 8. Metabolomics of Rare endocrine, genetic disease- A focus on the Pituitary gland -- Chapter 9. Metabolomics and genetics of rare endocrine disease - adrenal, parathyroid glands, and cystic fibrosis -- Chapter 10. Metabolomics role in personalized medicine: An update -- Chapter 11. Lipidomic Profiling in Clinical Practice Using LC-MS -- Chapter 12. Bringing Human Serum Lipidomics to the Forefront of Clinical Practice: Two Clinical Diagnosis Success Stories -- Chapter 13. LC-MS based population metabolomics: a mini-review of recent studies and challenges from sample collection to data processing -- Chapter 14. Metabolomics and transcriptomics approach to understand the pathophysiology of interstitial lung disease -- Chapter 15. Transferring metabolomics to portable diagnostic devices- Trending in biosensors.

This book helps readers discover the forefront of personalized medicine on clinical metabolomics and its applications in genetic diseases. This comprehensive guide offers a functional relationship map between cell components and genetic variations in various diseases, providing insights that can be applied to personalized medicine. The book covers the latest developments in metabolomics for health, with practical guidance for clinical experts looking to advance their laboratory techniques and career. The metabolomics profile is a powerful tool that has revolutionized our understanding of the relationship between genetics, clinical readouts, and disease outcomes. By integrating metabolomics with genomics and clinical phenotypes, the authors have developed diagnostic and prediction models that have vastly improved patient outcomes and deepened the understanding of disease mechanisms. This model has been successfully applied in various conditions, including inborn errors of metabolism, primary immunodeficiency, and endocrine disorders. However, integrating metabolomics with other omics datasets and clinical phenotypes requires careful study design, analytical tools, and data analysis and interpretation. This groundbreaking new book provides essential guidance for researchers, students, and professionals looking to leverage metabolomics in their own work, including biochemical and clinical geneticists, pharmacogenomics and pharmacometabolomics experts, pharmaceutics and diagnostic researchers, medical scientists, clinical dietitians, metabolic engineers, clinical chemists, and personalized medicine specialists. .