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Metabolomics can be significantly influenced by a range of pre-analytical factors, such as sample collection, pre-processing, aliquoting, transport, storage and thawing. This therefore shows the crucial need for standardizing the pre-analytical phase with the aim of minimizing the inter-sample variability driven by these technical issues, as well as for maintaining the metabolic integrity of biological samples to ensure that metabolomic profiles are a direct expression of the in vivo biochemical status. This review article provides an updated literature revision of the most important factors related to sample handling and pre-processing that may affect metabolomics results, particularly focusing on the most commonly investigated biofluids in metabolomics, namely blood plasma/serum and urine. Finally, we also provide some general recommendations and best practices aimed to standardize and accurately report all these pre-analytical aspects in metabolomics research.

Metabolomics based on direct mass spectrometry (MS) analysis, either by direct infusion or flow injection of crude sample extracts, shows a great potential for metabolic fingerprinting because of its high-throughput screening capability, wide metabolite coverage and reduced time of analysis. Considering that numerous metabolic pathways are significantly perturbed during the initiation and progression of diseases, these metabolomic tools can be used to get a deeper understanding about disease pathogenesis and discover potential biomarkers for early diagnosis. In this work, we describe the most common metabolomic platforms used in biomedical research, with special focus on strategies based on direct MS analysis. Then, a comprehensive review on the application of direct MS fingerprinting in clinical issues is provided.

Alzheimer's disease is a complex neurodegenerative disorder characterized by a multi-factorial etiology, not completely understood to date. In this context, the application of metabolomics is emerging in the last years because of its potential to monitor molecular alterations associated with disease pathogenesis and progression, as well as to discover candidate diagnostic biomarkers. However, the huge heterogeneity and dynamism of the human metabolome makes impossible the simultaneous determination of the entire set of metabolites from complex biological samples. Thus, the most common strategy to get a comprehensive overview of the organism's phenotypic expression is the combined use of complementary metabolomic platforms. In this review, we summarize the advantages and limitations of the most important analytical techniques usually employed in metabolomics, including nuclear magnetic resonance, direct infusion mass spectrometry and hyphenated approaches based on the coupling of orthogonal separation mechanisms (i.e. liquid chromatography, gas chromatography, capillary electrophoresis) with mass spectrometry. Moreover, the suitability of metabolomics to unravel the complex pathology underlying to Alzheimer's disease is also presented.