Applications of mass spectrometry to metabolomics and metabonomics: Detection of biomarkers of aging and of age‐related diseases

Abstract

Every 5 years or so new technologies, or new combinations of old ones, seemingly burst onto the science scene and are then sought after until they reach the point of becoming commonplace. Advances in mass spectrometry instrumentation, coupled with the establishment of standardized chemical fragmentation libraries, increased computing power, novel data-analysis algorithms, new scientific applications, and commercial prospects have made mass spectrometry-based metabolomics the latest sought-after technology. This methodology affords the ability to dynamically catalogue and quantify, in parallel, femtomole quantities of cellular metabolites. The study of aging, and the diseases that accompany it, has accelerated significantly in the last decade. Mutant genes that alter the rate of aging have been found that increase lifespan by up to 10-fold in some model organisms, and substantial progress has been made in understanding fundamental alterations that occur at both the mRNA and protein level in tissues of aging organisms. The application of metabolomics to aging research is still relatively new, but has already added significant insight into the aging process. In this review we summarize these findings. We have targeted our manuscript to two audiences: mass spectrometrists interested in applying their technical knowledge to unanswered questions in the aging field, and gerontologists interested in expanding their knowledge of both mass spectrometry and the most recent advances in aging-related metabolomics.

Chronic caloric restriction partially protects against age-related alteration in serum metabolome

“…Global metabolomics strategies have been widely applied to study cancer, diabetes, neurological diseases, cardiovascular diseases, obesity, effects of nutrition and exercise, and for drug discovery and development (Nagrath et al 2011;Barderas et al 2011;Wishart 2008;Rezzi et al 2007;Kim et al 2010;Lewis et al 2010;Huang et al 2010;Mishur and Rea 2012). This methodology has also been applied in aging studies in several species including Caenorhabditis elegans, fruit fly, rodents, dogs, and humans (Kristal and Shurubor 2005;Mishur and Rea 2012). In mammalian studies, carnitines, fatty acids, and other metabolites associated with energy metabolism, lipid metabolism, nucleic acid metabolism, and oxidative stress were shown to be perturbed with age (Williams et al 2005;Granger et al 2007;Lu et al 2008;Lawton et al 2008).…”

“…Even though metabolomics has been applied to study aging and age-associated diseases (Mishur and Rea 2012), as well as to study effects of specific foods in aging animals (Fu et al 2011;Yang et al 2011;Yan et al 2009), the use of this methodology for studying effects of CR on aging has been limited at best. Comparison of urine metabolomic profiles in dogs (Nicholson et al 2007) and Sprague-Dawley rats (Zhang et al 2011) using nuclear magnetic resonance (NMR) and liquid chromatography-mass spectrometry (LC-MS)-based metabolomic strategies, respectively, indicate effects of CR on gut microbiotal metabolism, energy metabolism, and renal activity.…”

Prediction of embryo implantation potential by mass spectrometry fingerprinting of the culture medium

“…One of these commonly used procedures is the partial least squares discriminant analysis (PLS-DA), which is an aim-directed method of classification, which is performed in order to sharpen the separation between groups of observations. In PLS-DA analysis, the peaks in the spectra that contribute to the separation of the samples receive a higher weight, improving the understanding of which variables carry the class-separating information and thereby yielding a model with better discriminatory ability compared with unsupervised principal component analysis (PCA; Dill et al 2010, Mishur & Rea 2012.…”

Metabolomics Research with Tandem Mass Spectrometry

“…In addition to metabolite profiling characteristic to metabolomics, metabonomics describes the wide spectrum of metabolites changing under certain conditions, such as disease, interventions and functional gene changes. Since these two terms (metabolomics and metabonomics) used interchangeably in literature (Mishur and Rea, 2011), in future discussion we will use only metabolomics for describing both quantitative metabolic profiling and changes in response to stimulus. Biochemically, metabolomics is the ultimate endpoint measurement of biological events and capturing the influences of nutrition, environmental influences, responses to pharmaceuticals, and many more.…”