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Biomarkers in Toxicology pp 1–25Cite as

LC-MS-Based Metabolomics in the Identification of Biomarkers Pertaining to Drug Toxicity: A New Narrative

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Abstract

The evaluation of adverse drug effects is essential for drug approval and clinical therapy. Safe and reliable biomarkers play important roles in the prediction, detection, and management of drug-induced toxicity in the preclinical and clinical studies. Identifying a highly specific, accurate, sensitive, and biologically or clinically relevant biomarker is very challenging. For instance, highly specific and accurate biomarkers for drug-induced liver injury are still not available. Nevertheless, the latest technology “omics” offer novel possibilities to develop the biomarkers pertaining to drug toxicity. Metabolomics is the systemic identification and quantification process of small biological molecules, and it serves as the downstream platform for other “omics” approaches like genomics, transcriptomics, and proteomics. Metabolomics alone, or together with other omics, has been successfully used for the identification of biomarkers in various fields, including drug toxicity. Various platforms, including nuclear magnetic resonance (NMR), gas chromatography or liquid chromatography-mass spectrometry (GC/LC-MS), and newly emerging mass spectrometry imaging (MSI), are employed in metabolomics. At present, LC-MS platform is a workhorse in metabolomics and other research fields, e.g., drug metabolism and pharmacokinetics. In some cases, drug metabolism is critical when the metabolite of a drug can be utilized as a valuable biomarker for toxicity. This review provides examples of advances in the field of metabolomics and emphasizes the application of metabolomics in biomarker discovery, drug metabolism, and mechanistic studies of drug toxicity. The challenges, opportunities, and future direction of metabolomics in biomarker discovery are highlighted as well.

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Abbreviations

AFB1:

Aflatoxin B1

ALT:

Alanine transaminase

APCI:

Atmospheric pressure chemical ionization

API:

Atmospheric pressure ionization

APPI:

Atmospheric pressure photoionization

AST:

Aspartate transaminase

AUC:

Area under the curve

BUN:

Blood urea nitrogen

CE:

Capillary electrophoresis

CI:

Chemical ionization

CPB2:

Carboxypeptidase B2

CPK:

Creatine phosphokinase

CYP:

Cytochrome P450

DILI:

Drug-induced hepatotoxicity

EI:

Electron ionization

ESI:

Electrospray ionization

FMO:

Flavin-containing monooxygenases

FT-ICR:

Fourier transform ion cyclotron resonance

GC:

Gas chromatography

GNMT:

Glycine N-methyltransferase

GSH:

Glutathione

HCC:

Hepatocellular carcinoma

HLM:

Human liver microsomes

HMDB:

HUMAN Metabolome Database

HRMS:

High-resolution mass spectrometers

IC:

Ion chromatography

IPA:

Ingenuity Pathway Analysis

LC:

Liquid chromatography

MALDI:

Matrix-assisted laser desorption/ionization

MetPA:

Metabolomics Pathway Analysis

mGWAS:

Metabolite genome-wide association studies

miRNAs:

microRNAs

MRM:

Multiple reaction monitoring

MS:

Mass spectrometry

MSI:

Mass spectrometry imaging

NAc:

N-acetylcysteine

NMR:

Nuclear magnetic resonance

OPLS-DA:

Orthogonal projections to latent structures discriminant analysis

Orbitrap:

Orbital ion traps

PCA:

Principal components analysis

QC:

Quality control

QQQ-MS:

Triple quadruple mass spectrometry

Q-TOF:

Quadrupole time of flight

ROC:

Receiver operating characteristic

ROS:

Reactive oxygen species

Scr:

Serum creatinine

SFC:

Supercritical fluid chromatography

SPE:

Solid-phase extraction

TOF:

Time of flight

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Acknowledgments

This work was supported by the National Institute of Diabetes and Digestive and Kidney (R01-DK121970).

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Authors and Affiliations

  1. Center for Drug Discovery, Department of Pathology & Immunology, Baylor College of Medicine, Houston, TX, USA

    Xuan Qin, John M. Hakenjos & Feng Li

  2. NMR and Drug Metabolism Core, Advanced Technology Cores, Baylor College of Medicine, Houston, TX, USA

    Feng Li

  3. Department of Pharmacology & Chemical Biology, Baylor College of Medicine, Houston, TX, USA

    Feng Li

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  1. Xuan Qin
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  2. John M. Hakenjos
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  3. Feng Li
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Correspondence to Feng Li .

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Editors and Affiliations

  1. Department of Biomedical Sciences, University of Westminster, London, UK

    Vinood B. Patel

  2. Sch Biomed & Health Sci, Wilkins Bldg, King's College London Franklin, London, UK

    Victor R. Preedy

  3. Department of Medicine, King Abdulaziz Med City, Riyadh, Saudi Arabia

    Rajkumar Rajendram

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Qin, X., Hakenjos, J.M., Li, F. (2022). LC-MS-Based Metabolomics in the Identification of Biomarkers Pertaining to Drug Toxicity: A New Narrative. In: Patel, V.B., Preedy, V.R., Rajendram, R. (eds) Biomarkers in Toxicology. Biomarkers in Disease: Methods, Discoveries and Applications. Springer, Cham. https://doi.org/10.1007/978-3-030-87225-0_34-1

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