Evidence map›Paper›PMID 38374592›Full record

ReviewSe pu = Chinese journal of chromatography2024

[Application of multiomics mass spectrometry in the research of chemical exposome].

Yuan-Yuan Song, Zeng-Hua Qi, Zong-Wei Cai

Abstract readReviewEnglish Abstract
In one paragraph

Review in Se pu = Chinese journal of chromatography, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

3 citing papers in PubMed.

  1. [Metabolomic alterations in preterm infants with bronchopulmonary dysplasia].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2025
    Article
  2. Article
  3. Review
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.

Yuan-Yuan SongState Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong 999077, China.
Zeng-Hua QiSchool of Environmental Science and Engineering, Guangdong University of Technology, Guangzhou 510006, China.
Zong-Wei CaiState Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong 999077, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Environmental factors, such as environmental pollutants, behaviors, and lifestyles, are the leading causes of chronic noncommunicable diseases. Estimates indicate that approximately 50% of all deaths worldwide can be attributed to environmental factors. The exposome is defined as the totality of human environmental (i.e., all nongenetic) exposures from conception, including general external exposure (e.g., climate, education, and urban environment), specific external exposure (e.g., pollution, physical activity, and diet), and internal exposure (e.g., metabolic factors, oxidative stress, inflammation, and protein modification). As a new paradigm, this concept aims to comprehensively understand the link between human health and environmental factors. Therefore, a comprehensive measurement of the exposome, including accurate and reliable measurements of exposure to the external environment and a wide range of biological responses to the internal environment, is of great significance. The measurement of the general external exposome depends on advances in environmental sensors, personal-sensing technologies, and geographical information systems. The determination of exogenous chemicals to which individuals are exposed and endogenous chemicals that are produced or modified by external stressors relies on improvements in methodology and the development of instrumental approaches, including colorimetric, chromatographic, spectral, and mass-spectrometric methods. This article reviews the research strategies for chemical exposomes and summarizes existing exposome-measurement methods, focusing on mass spectrometry (MS)-based methods. The top-down and bottom-up approaches are commonly used in exposome studies. The bottom-up approach focuses on the identification of chemicals in the external environment (e.g., soil, water, diet, and air), whereas the top-down approach focuses on the evaluation of endogenous chemicals and biological processes in biological samples (e.g., blood, urine, and serum). Low- and high-resolution MS (LRMS and HRMS, respectively) have become the most popular methods for the direct measurement of exogenous and endogenous chemicals owing to their superior sensitivity, specificity, and dynamic range. LRMS has been widely applied in the targeted analysis of expected chemicals, whereas HRMS is a promising technique for the suspect and unknown screening of unexpected chemicals. The development of MS-based multiomics, including proteomics, metabolomics, epigenomics, and spatial omics, provides new opportunities to understand the effects of environmental exposure on human health. Metabolomics involves the sum of all low-molecular-weight metabolites in a living system. Nontargeted metabolomics can measure both endogenous and exogenous chemicals, which would directly link exposure to biological effects, internal dose, and disease pathobiology, whereas proteomics could play an important role in predicting potential adverse health outcomes and uncovering molecular mechanisms. MS imaging (MSI) is an emerging technique that provides unlabeled in-depth measurements of endogenous and exogenous molecules directly from tissue and cell sections without changing their spatial information. MSI-based spatial omics, which has been widely applied in biomarker discovery for clinical diagnosis, as well as drug and pollutant monitoring, is expected to become an effective method for exposome measurement. Integrating these response measurements from metabolomics, proteomics, spatial omics, and epigenomics will enable the generation of new hypotheses to discover the etiology of diseases caused by chemical exposure. Finally, we highlight the major challenges in achieving chemical exposome measurements.

Indexed as

Environmental PollutantsExposomeEnvironmental ExposureHumansMass SpectrometryMultiomicsEnvironmental Pollutantsexpotomicsmass spectrometry imaging (MSI)mass spectrometry (MS)metabolomicsproteomicsreview

Identifiers

PMID38374592
PMCPMC10877483

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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.