Recommendations for sample selection, collection and preparation for NMR-based metabolomics studies of blood

Abstract

Background: Metabolic profiling of blood metabolites, particularly in plasma and serum, is vital for studying human diseases, human conditions, drug interventions and toxicology. The clinical significance of blood arises from its close ties to all human cells and facile accessibility. However, patient-specific variables such as age, sex, diet, lifestyle and health status, along with pre-analytical conditions (sample handling, storage, etc.), can significantly affect metabolomic measurements in whole blood, plasma, or serum studies. These factors, referred to as confounders, must be mitigated to reveal genuine metabolic changes due to illness or intervention onset.

Review objective: This review aims to aid metabolomics researchers in collecting reliable, standardized datasets for NMR-based blood (whole/serum/plasma) metabolomics. The goal is to reduce the impact of confounding factors and enhance inter-laboratory comparability, enabling more meaningful outcomes in metabolomics studies.

Key concepts: This review outlines the main factors affecting blood metabolite levels and offers practical suggestions for what to measure and expect, how to mitigate confounding factors, how to properly prepare, handle and store blood, plasma and serum biosamples and how to report data in targeted NMR-based metabolomics studies of blood, plasma and serum.

Keywords: Blood; Metabolites; Metabolomics; NMR; Plasma; Serum; Standardization.

Fig. 1

Operative phases, confounding factors* and associated uncertainties (−)** for in-vitro metabolome studies in humans and animals. Animal testing as part of good laboratory practice (GLP) provide the highest level of controllability (+ +)**. Similar favorable conditions can be found in human clinical trials (CT) where the most important confounding variables can be well controlled. In human field studies, important parameters are placed in the test subjects' confidence range. This leads to uncertainties within a study, which can no longer be fully compensated for. Thus, good planning, extensive standardization, efficient quality management, and detailed collection and reporting of potential confounding variables is a guarantee for high-quality metabolome studies. There is currently no global standard for conducting metabolome studies. *the most critical factors are in bold; **rough estimate, whereby (−) indicates little controllable and ( +) well controllable; prep. = sample preparation; QM = quality management; HTP = high throughput

Fig. 2

Summary statistics of provided a clotting time, b centrifugation speed in [g], or c in [rpm], d centrifugation temperature, and e centrifugation time to obtain serum or plasma as reported in 100 selected metabolomics publications (see Supplementary Table S1). NA—not available or reported; RT—room temperature

Fig. 3

Summary statistics of a storage temperature or plasma or serum samplees, b storage time of plasma/serum samples at their respective temperatures, c time delay before samples were processed, d temperature before samples were processed and e temperature samples were processed using methanol for protein precipitation or organic solvents for lipid extraction reported in 100 selected metabolomics publications (see Supplementary Table S1). NA—not available or reported; RT—room temperature