Evidence map›Paper›PMID 42401771›Full record

ReviewAdvances in experimental medicine and biology2026

LC-MS-Based Metabolomics and Proteomics Sample Preparation of Urine: Methods and Multi-Omics Integration.

Muath Khairi Mousa, Nelson C Soares, Hugo M Santos

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In one paragraph

Review in Advances in experimental medicine and biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Muath Khairi MousaBIOSCOPE Research Group, LAQV-REQUIMTE, Department of Chemistry, NOVA School of Science and Technology, Universidade NOVA de Lisboa, Caparica, Portugal.
Nelson C SoaresCollege of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU), Dubai Health, Dubai, United Arab Emirates.
Hugo M SantosBIOSCOPE Research Group, LAQV-REQUIMTE, Department of Chemistry, NOVA School of Science and Technology, Universidade NOVA de Lisboa, Caparica, Portugal. hms14862@fct.unl.pt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Urine is an ideal biological fluid due to the highly metabolomic and proteomic information it provides and its easy collection in large amounts. Urinary biomarkers reported for different types of diseases included the urological tract and systemic diseases. Although the most common approach in omics is single-omics studies, combining multi-omics biomarkers such as metabolomics, proteomics, transcriptomics, and genomics can improve diagnostic accuracy and provide deeper insights into disease mechanisms than single biomarkers. The gold standard technique for bioanalysis is liquid chromatography coupled to mass spectrometry (LC-MS/MS) due to its high sensitivity, specificity, and selectivity for the analysis of metabolites and proteins in complex biological samples. One of the most important aspects in metabolomics and proteomics is sample extraction and preparation before the analysis. Different types of metabolites and protein extraction methods can be used effectively for urine samples, including protein precipitation, liquid-liquid extraction, and solid-phase extraction. However, in the multi-omics approach integrating metabolomics and proteomics, sample preparation could be either individual for each or simultaneous for both from a single sample. In this chapter, we discuss aspects of LC-MS-based metabolomics and proteomics sample preparation, as well as their integration for a multi-omics approach. In clinical practice, the reported sample preparation methods for bladder cancer metabolomics and proteomics were also discussed.

Indexed as

Liquid Chromatography-Mass SpectrometryMetabolomeMetabolomicsProteomicsTandem Mass SpectrometryUrinalysisUrinary Bladder NeoplasmsBiomarkersBiomarkers, TumorChromatography, LiquidHumansMultiomicsBiomarkersBiomarkers, TumorBladder cancerLC-MSMetabolomicsMulti-omicsProteomicsSample preparationUrinary biomarkers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.