Nuclear Magnetic Resonance and Statistical Analysis

Abstract

The impressive high resolution of nuclear magnetic resonance (NMR), its large dynamic range, and especially robust reproducibility lend themselves to advanced statistical methods that can be harnessed to analyze a large variety of complex samples. The primary example of this approach is in the rapidly expanding field of metabolomics that is focused on better understanding systems biology and for the identification of biomarkers of various biological states. In metabolomics, a large number of small‐molecule metabolites from body fluids or tissues are detected quantitatively in a single step, and then analyzed with multivariate statistical methods to yield information that is essential for systems biology, drug discovery, early disease diagnosis, toxicology, food and nutrition sciences, and other studies. NMR‐based metabolomic studies have been very successful due to the high quality and reliability of the methodology. In this article, we summarize the major experimental and statistical methods used in combining NMR and advanced statistical analyses especially in metabolomics along with a description of some important applications.

Biomarker Discovery and Translation in Metabolomics

“…Importantly, the non-invasive nature of NMR provides unique opportunities to translate in vitro findings to clinical applications in vivo . The latest technological advancements in NMR such as strong magnetic fields, cryogenic probes and micro-coils, and automation have improved the detection limit, throughput and enabled detection of over hundred quantifiable metabolites from single NMR experiment in biological mixtures [24]. …”

“…To date, significant progress has been made in the discovery of metabolite based biomarkers for these diseases [3, 24, 58–66]. A selected set of studies that illustrate this progress and breadth of the investigations are provided below.…”

“…Investigations of diseases of inborn errors of metabolism (IEM) are among the early studies focused on metabolite based biomarker discovery, and essentially predate the field of metabolomics [3, 24, 67]. An IEM is generally characterized by a single genetic defect, which deleteriously affects the function of a specific enzyme [68].…”

“…Ever since the early investigations of altered metabolite levels in serum, plasma and urine from diabetic patients [72], a vast number of studies have focused on discovering additional biomarkers for diabetes beyond glucose and insulin, resulting in the identification of numerous potential bio-markers for both Type 1 and Type 2 diabetes [3,24, 73]. The investigations have utilized NMR and MS, either individually or in combination, to identify biomarkers in blood plasma/serum, urine, and tissue from humans as well as animal models.…”

“…Numerous studies focused on the search for small molecule metabolites as biomarkers for underlying cardio vascular (CVD) and coronary heart diseases have found a number of metabolites to be of potential diagnostic value [3, 24, 59, 78, 79]. To cite a few examples, an MS based metabolomics study of more than 2000 patients undergoing cardiac catheterization finds five baseline metabolic factors to be associated with mortality due to CVD, independent of the standard predictors; they are medium-chain acylcarnitines, short-chain dicarboxylacylcarnitines, long-chain dicarboxylacylcarnitines, branched-chain amino acids and fatty acids [79].…”