Evidence map›Paper›PMID 40528258›Full record

ArticleGenome medicine2025

Longitudinal analysis of genetic and environmental interplay in human metabolic profiles and the implication for metabolic health.

Jing Wang, Alberto Zenere, Xingyue Wang, Göran Bergström, Fredrik Edfors, Mathias Uhlén, Wen Zhong

Erratum issuedAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Jing Wang *Department of Biomedical and Clinical Sciences (BKV), Linköping University, SE-581 83, Linköping, Sweden.
Alberto Zenere *Department of Biomedical and Clinical Sciences (BKV), Linköping University, SE-581 83, Linköping, Sweden.
Xingyue Wang *Department of Biomedical and Clinical Sciences (BKV), Linköping University, SE-581 83, Linköping, Sweden.
Göran BergströmDepartment of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Fredrik EdforsDepartment of Protein Science, Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden.
Mathias UhlénDepartment of Protein Science, Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden.
Wen ZhongDepartment of Biomedical and Clinical Sciences (BKV), Linköping University, SE-581 83, Linköping, Sweden. wen.zhong@liu.se.

Funding

Cancerfoden 24 3770 PjKnut och Alice Wallenbergs Stiftelse KAW 2020.0239Vetenskapsrådet #2022-01562
6 · The paper itself

Abstract

backgroundUnderstanding how genetics and environmental factors shape human metabolic profiles is crucial for advancing metabolic health. Variability in metabolic profiles, influenced by genetic makeup, lifestyle, and environmental exposures, plays a critical role in disease susceptibility and progression.

methodsWe conducted a two-year longitudinal study involving 101 clinically healthy individuals aged 50 to 65, integrating genomics, metabolomics, lipidomics, proteomics, clinical measurements, and lifestyle questionnaire data from repeat sampling. We evaluated the influence of both external and internal factors, including genetic predispositions, lifestyle factors, and physiological conditions, on individual metabolic profiles. Additionally, we developed an integrative metabolite-protein network to analyze protein-metabolite associations under both genetic and environmental regulations.

resultsOur findings highlighted the significant role of genetics in determining metabolic variability, identifying 22 plasma metabolites as genetically predetermined. Environmental factors such as seasonal variation, weight management, smoking, and stress also significantly influenced metabolite levels. The integrative metabolite-protein network comprised 5,649 significant protein-metabolite pairs and identified 87 causal metabolite-protein associations under genetic regulation, validated by showing a high replication rate in an independent cohort. This network revealed stable and unique protein-metabolite profiles for each individual, emphasizing metabolic individuality. Notably, our results demonstrated the importance of plasma proteins in capturing individualized metabolic variabilities. Key proteins related to individual metabolic profiles were identified and validated in the UK Biobank, showing great potential for metabolic risk assessment.

conclusionsOur study provides longitudinal insights into how genetic and environmental factors shape human metabolic profiles, revealing unique and stable individual metabolic profiles. Plasma proteins emerged as key indicators for capturing the variability in human metabolism and assessing metabolic risks. These findings offer valuable tools for personalized medicine and the development of diagnostics for metabolic diseases.

Indexed as

Gene-Environment InteractionMetabolomeAgedFemaleHumansLife StyleLongitudinal StudiesMaleMetabolomicsMiddle AgedProteomicsEnvironmentGeneticsHuman metabolismLifestyleMetabolic riskMetabolomicsProteomics

Identifiers

PMID40528258
PMCPMC12172340

What Socratic holds

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LicenceCC BY
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Registered trials

None linked

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 Socratic graph.