The goal of this review is to present a comprehensive survey of the many intriguing facets of creatine (Cr) and creatinine metabolism, encompassing the pathways and regulation of Cr biosynthesis and degradation, species and tissue distribution of the enzymes and metabolites involved, and of the inherent implications for physiology and human pathology. Very recently, a series of new discoveries have been made that are bound to have distinguished implications for bioenergetics, physiology, human pathology, and clinical diagnosis and that suggest that deregulation of the creatine kinase (CK) system is associated with a variety of diseases. Disturbances of the CK system have been observed in muscle, brain, cardiac, and renal diseases as well as in cancer. On the other hand, Cr and Cr analogs such as cyclocreatine were found to have antitumor, antiviral, and antidiabetic effects and to protect tissues from hypoxic, ischemic, neurodegenerative, or muscle damage. Oral Cr ingestion is used in sports as an ergogenic aid, and some data suggest that Cr and creatinine may be precursors of food mutagens and uremic toxins. These findings are discussed in depth, the interrelationships are outlined, and all is put into a broader context to provide a more detailed understanding of the biological functions of Cr and of the CK system.

Metabolomics is the study of metabolism at the global level. This rapidly developing new discipline has important potential implications for pharmacologic science. The concept that metabolic state is representative of the overall physiologic status of the organism lies at the heart of metabolomics. Metabolomic studies capture global biochemical events by assaying thousands of small molecules in cells, tissues, organs, or biological fluids-followed by the application of informatic techniques to define metabolomic signatures. Metabolomic studies can lead to enhanced understanding of disease mechanisms and to new diagnostic markers as well as enhanced understanding of mechanisms for drug or xenobiotic effect and increased ability to predict individual variation in drug response phenotypes (pharmacometabolomics). This review outlines the conceptual basis for metabolomics as well as analytical and informatic techniques used to study the metabolome and to define metabolomic signatures. It also highlights potential metabolomic applications to pharmacology and clinical pharmacology.

Introduction The Alzheimer’s Disease Research Summits of 2012 and 2015 incorporated experts from academia, industry, and nonprofit organizations to develop new research directions to transform our understanding of Alzheimer’s disease (AD) and propel the development of critically needed therapies. In response to their recommendations, big data at multiple levels are being generated and integrated to study network failures in disease. We used metabolomics as a global biochemical approach to identify peripheral metabolic changes in AD patients and correlate them to cerebrospinal fluid pathology markers, imaging features, and cognitive performance. Methods Fasting serum samples from the Alzheimer’s Disease Neuroimaging Initiative (199 control, 356 mild cognitive impairment, and 175 AD participants) were analyzed using the AbsoluteIDQ-p180 kit. Performance was validated in blinded replicates, and values were medication adjusted. Results Multivariable-adjusted analyses showed that sphingomyelins and ether-containing phosphatidylcholines were altered in preclinical biomarker-defined AD stages, whereas acylcarnitines and several amines, including the branched-chain amino acid valine and α-aminoadipic acid, changed in symptomatic stages. Several of the analytes showed consistent associations in the Rotterdam, Erasmus Rucphen Family, and Indiana Memory and Aging Studies. Partial correlation networks constructed for Aβ1–42, tau, imaging, and cognitive changes provided initial biochemical insights for disease-related processes. Coexpression networks interconnected key metabolic effectors of disease. Discussion Metabolomics identified key disease-related metabolic changes and disease-progression-related changes. Defining metabolic changes during AD disease trajectory and its relationship to clinical phenotypes provides a powerful roadmap for drug and biomarker discovery.