Abstract
Observational experimental designs are usually employed in metabolomics to elucidate pathological mechanisms underlying disease development and to discover candidate biomarkers for diagnosis. However, intervention trials can also be a suitable starting point before performing a validation study in lager epidemiological cohorts, with a great potential in personalized medicine to investigate how different patients respond to similar stimuli. In the present work, we provide a review of the literature on the application of metabolomics to investigate metabolic alterations associated with diabetes, the diabetes predisposing state of insulin resistance and the oral glucose tolerance test as a case study to demonstrate the complementarity of observational and interventional study designs.
Keywords: Metabolomics, Diabetes, Oral glucose tolerance test, Insulin resistance, Study design, Observational study, Interventional study.
Graphical Abstract
Call for Papers in Thematic Issues
Adaptogens—History and Future Perspectives
Adaptogens are pharmacologically active compounds or plant extracts that are associated with the ability to enhance the body’s stability against stress. The intake of adaptogens is associated not only with a better ability to adapt to stress and maintain or normalise metabolic functions but also with better mental and physical ...read more
Addressing the Most Common Causes of Death with Niacin/NAD and Inositol Polyphosphates
The most common causes of death in the world are cardiovascular disease (CVD) and cancer. These are perhaps best addressed by reducing lipodystrophy and blockages with niacin and inositol polyphosphates (e.g., IP6+inositol) respectively when addressing CVD. Niacin serves as a vitamin by virtue of its role as a skeletal precursor ...read more
AlphaFold in Medicinal Chemistry: Opportunities and Challenges
AlphaFold, a groundbreaking AI tool for protein structure prediction, is revolutionizing drug discovery. Its near-atomic accuracy unlocks new avenues for designing targeted drugs and performing efficient virtual screening. However, AlphaFold's static predictions lack the dynamic nature of proteins, crucial for understanding drug action. This is especially true for multi-domain proteins, ...read more
Artificial intelligence for Natural Products Discovery and Development
Our approach involves using computational methods to predict the potential therapeutic benefits of natural products by considering factors such as drug structure, targets, and interactions. We also employ multitarget analysis to understand the role of drug targets in disease pathways. We advocate for the use of artificial intelligence in predicting ...read more
Related Journals
Anti-Cancer Agents in Medicinal Chemistry
Anti-Inflammatory & Anti-Allergy Agents in Medicinal Chemistry
Current Bioactive Compounds
Current Cancer Drug Targets
Combinatorial Chemistry & High Throughput Screening
Current Cancer Therapy Reviews
Current Diabetes Reviews
Current Drug Safety
Current Drug Targets
Current Drug Therapy
Related Books
Quality Assurance of Ethno-Herbals: Cultivating Confidence in Alternative Medicine
Traditional Medicine in North East Africa: Research on Traditional Healer Preparations and Herbs
Andrographolide and its Analogs: Botanical Sources, Phytochemistry, Pharmacology, and Biotechnology
Metabolites of Medicinal Plants: Insightful Approaches
Herbs for Disease Prevention and Treatment
Anthocyanins: Pharmacology and Nutraceutical Importance
Herbal Medicine for Autoimmune Diseases
Therapeutic Insights into Herbal Medicine through the Use of Phytomolecules
The Roles and Responsibilities of Clinical Pharmacists in Hospital Settings
Bioactive Compounds from Medicinal Plants for Cancer Therapy and Chemoprevention
35
3
