Statistical methods and resources for biomarker discovery using metabolomics

Abstract

Metabolomics is a dynamic tool for elucidating biochemical changes in human health and disease. Metabolic profiles provide a close insight into physiological states and are highly volatile to genetic and environmental perturbations. Variation in metabolic profiles can inform mechanisms of pathology, providing potential biomarkers for diagnosis and assessment of the risk of contracting a disease. With the advancement of high-throughput technologies, large-scale metabolomics data sources have become abundant. As such, careful statistical analysis of intricate metabolomics data is essential for deriving relevant and robust results that can be deployed in real-life clinical settings. Multiple tools have been developed for both data analysis and interpretations. In this review, we survey statistical approaches and corresponding statistical tools that are available for discovery of biomarkers using metabolomics.

Metabolomic signature between diabetic and non-diabetic obese patients: A protocol for systematic review

“…To date, more than 4,000 metabolites have been confirmed in human samples using various metabolomics platforms and technologies [24]. The changes in metabolic profiles can indicate pathological mechanisms and provide potential biomarkers for the diagnosis and evaluation of several diseases [17]. Numerous studies have systematically evaluated the metabolic characteristics of osteoarthritis, obesity (including adults and children), metabolic syndrome, T2DM, and pre-diabetes, screening out new metabolic markers with significant diagnostic and therapeutic implications in the future [20,[25][26][27].…”

“…Metabolomics, a high-throughput technique for biomarker discovery, can profile an individual's metabolic state by analyzing small molecule metabolites (<1500 Da) in the internal environment [14,15]. The number of metabolites in humans ranges from 2,000 to 20,000 [16], and two primary analytical methods are primarily utilized for the quantification of metabolites (located in cells, tissues, or body fluids): nuclear magnetic resonance (NMR) and mass spectrometry (MS) [5][6][7], through a targeted or untargeted process [17]. Targeted analysis is a more quantitative approach, but it inevitably risks missing unknown or unexpected biomarkers.…”

Distinguishing IDH mutation status in gliomas using FTIR-ATR spectra of peripheral blood plasma indicating clear traces of protein amyloid aggregation

“…In metabolomics-based biomarker search, metabolites are selected using a threshold value of VIP > 1 in a linear regression model [54]. As clearly shown in Fig.…”

Multifunctional-separation-mode ion chromatography method for determining major metabolites during multiple parallel fermentation of rice wine

“…In recent years, liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS), and nuclear magnetic resonance (NMR) spectroscopy have been used for the analysis of metabolites in various fields, such as food, medicine, chemistry, pharmaceuticals, and agriculture. 1–8 The major analytes can be categorised as related to central carbon metabolism (energy metabolism) or metabolic pathways involving molecules such as amino acids, nucleic acids, and lipids. 9–12 This technique, which can provide insights into a broad range of reactions in various research areas, is of interest to not only major companies but also small- and medium-sized companies.…”