Evidence map›Paper›PMID 38129841›Full record

ArticleBMC medicine2023

Longitudinal multi-omics study reveals common etiology underlying association between plasma proteome and BMI trajectories in adolescent and young adult twins.

Gabin Drouard, Fiona A Hagenbeek, Alyce M Whipp, René Pool, Jouke Jan Hottenga, Rick Jansen, Nikki Hubers, Aleksei Afonin, BIOS Consortium, BBMRI-N. L. Metabolomics Consortium, Gonneke Willemsen and 7 more

Abstract read
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Article in BMC medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

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  6. Longitudinal omics data analysis: approaches and applications.Computational and structural biotechnology journal · 2026
    Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors.

Gabin DrouardInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland. gabin.drouard@helsinki.fi.ORCID 0000-0002-3227-8483
Fiona A HagenbeekInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
Alyce M WhippInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
René PoolDepartment of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Jouke Jan HottengaDepartment of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Rick JansenDepartment of Psychiatry, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Nikki HubersDepartment of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Aleksei AfoninA.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland.
BIOS Consortium, BBMRI-N. L. Metabolomics Consortium
Gonneke WillemsenDepartment of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Eco J C de GeusDepartment of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Samuli RipattiInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
Matti PirinenInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
Katja M KanninenA.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland.
Dorret I BoomsmaDepartment of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Jenny van DongenDepartment of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Jaakko KaprioInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland. jaakko.kaprio@helsinki.fi.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe influence of genetics and environment on the association of the plasma proteome with body mass index (BMI) and changes in BMI remains underexplored, and the links to other omics in these associations remain to be investigated. We characterized protein-BMI trajectory associations in adolescents and adults and how these connect to other omics layers.

methodsOur study included two cohorts of longitudinally followed twins: FinnTwin12 (N = 651) and the Netherlands Twin Register (NTR) (N = 665). Follow-up comprised 4 BMI measurements over approximately 6 (NTR: 23-27 years old) to 10 years (FinnTwin12: 12-22 years old), with omics data collected at the last BMI measurement. BMI changes were calculated in latent growth curve models. Mixed-effects models were used to quantify the associations between the abundance of 439 plasma proteins with BMI at blood sampling and changes in BMI. In FinnTwin12, the sources of genetic and environmental variation underlying the protein abundances were quantified by twin models, as were the associations of proteins with BMI and BMI changes. In NTR, we investigated the association of gene expression of genes encoding proteins identified in FinnTwin12 with BMI and changes in BMI. We linked identified proteins and their coding genes to plasma metabolites and polygenic risk scores (PRS) applying mixed-effects models and correlation networks.

resultsWe identified 66 and 14 proteins associated with BMI at blood sampling and changes in BMI, respectively. The average heritability of these proteins was 35%. Of the 66 BMI-protein associations, 43 and 12 showed genetic and environmental correlations, respectively, including 8 proteins showing both. Similarly, we observed 7 and 3 genetic and environmental correlations between changes in BMI and protein abundance, respectively. S100A8 gene expression was associated with BMI at blood sampling, and the PRG4 and CFI genes were associated with BMI changes. Proteins showed strong connections with metabolites and PRSs, but we observed no multi-omics connections among gene expression and other omics layers.

conclusionsAssociations between the proteome and BMI trajectories are characterized by shared genetic, environmental, and metabolic etiologies. We observed few gene-protein pairs associated with BMI or changes in BMI at the proteome and transcriptome levels.

Indexed as

MultiomicsProteomeAdolescentAdultBody Mass IndexChildHumansLongitudinal StudiesTwins, MonozygoticYoung AdultProteomeBody mass index (BMI)Changes in BMILongitudinal twin studyMetabolomeMulti-omicsPolygenic risk scoresProteomeTranscriptome

Identifiers

PMID38129841
PMCPMC10740308

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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.