Evidence map›Paper›PMID 40143821›Full record

ArticleInternational journal of epidemiology2025

Metabolic transition from childhood to adulthood based on two decades of biochemical time series in three longitudinal cohorts.

Ville-Petteri Mäkinen, Mika Kähönen, Terho Lehtimäki, Nina Hutri, Tapani Rönnemaa, Jorma Viikari, Katja Pahkala, Suvi Rovio, Harri Niinikoski, Juha Mykkänen and 2 more

Abstract read
In one paragraph

Article in International journal of epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Embracing non-linearity in human ageing.Nature reviews. Genetics · 2026
    Review
  3. Article
  4. Article
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

12 authors.

Ville-Petteri MäkinenFaculty of Medicine, Systems Epidemiology, Research Unit of Population Health, University of Oulu, Oulu, FI-90014, Finland.ORCID 0000-0002-7262-2656
Mika KähönenDepartment of Clinical Physiology, Tampere University Hospital, Tampere, FI-33521, Finland.
Terho LehtimäkiFinnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, FI-33014, Finland.
Nina HutriFaculty of Medicine and Health Technology, Tampere Centre for Skills Training and Simulation, Tampere University, Tampere, FI-33014, Finland.
Tapani RönnemaaDepartment of Medicine, University of Turku, Turku, FI-20014, Finland.
Jorma ViikariDepartment of Medicine, University of Turku, Turku, FI-20014, Finland.
Katja PahkalaResearch Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, FI-20014, Finland.
Suvi RovioResearch Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, FI-20014, Finland.
Harri NiinikoskiResearch Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, FI-20014, Finland.
Juha MykkänenResearch Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, FI-20014, Finland.
Olli RaitakariResearch Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, FI-20014, Finland.
Mika Ala-KorpelaFaculty of Medicine, Systems Epidemiology, Research Unit of Population Health, University of Oulu, Oulu, FI-90014, Finland.ORCID 0000-0001-5905-1206

Funding

Finnish Foundation for Cardiovascular ResearchResearch Council of Finland 357183Sigrid Juselius FoundationUK Medical Research Council and Wellcome 217065/Z/19/ZWellcome Trust
6 · The paper itself

Abstract

backgroundThis is the first large-scale longitudinal study of children that describes the temporal trajectories of an extensive collection of metabolic measures that are relevant for lifelong cardiometabolic risk. We also provide a comprehensive picture on how metabolism develops into mature adult sex-specific phenotypes.

methodsChildren born in 1962-92 were recruited by three European studies (n = 20 377 eligible). Biochemical data for ages 0-26 years were available for n = 14 958 participants (n = 8385 with metabolomics). Age associations for 168 metabolic measures (6 physiological traits, 6 clinical biomarkers, and 156 serum metabolomics measures) were determined by using curvilinear regression. Puberty effects were calculated by using logistic regression of biological sex for pre- and post-pubertal age strata.

resultsAge-specific concentrations were reported for all measures. Nonlinear age associations were typical, including insulin (R2 = 20.7% ±0.6% variance explained ±SE), glycerol (13.3% ±1.3%), glycoprotein acetyls (40.3% ±1.5%), and branched-chain amino acids (19.5% ±1.6%). Apolipoprotein B was not associated with age (0.7% ±0.4%). Multivariate modeling indicated that boys diverged from girls metabolically during ages 13-17 years. Puberty effects were observed for large high-density lipoprotein cholesterol (P = 8.5 × 10-288), leucine (P < 2.3 × 10-308), glutamine (P < 2.3 × 10-308), albumin (P = 1.7 × 10-161), docosahexaenoic acid (P = 5.2 × 10-50), and sphingomyelin (P = 4.4 × 10-90).

conclusionNovel associations between emerging cardiometabolic risk factors, such as amino acids and glycoprotein acetyls, and growth and puberty were observed. Conversely, apolipoprotein B was stable, which favors its utility for early assessments of lifetime cardiovascular risk.

Indexed as

Adolescent DevelopmentChild DevelopmentPubertyAdolescentAdultAge FactorsBiomarkersCardiometabolic Risk FactorsChildChild, PreschoolEuropeFemaleHumansInfantInfant, NewbornLogistic ModelsBiomarkersamino acidsapolipoprotein Bcardiovascular risk factorchildreninflammationinsulinlipidslongitudinalmetabolismpuberty

Identifiers

PMID40143821
PMCPMC11947525

What OpenQuestion holds

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LicenceCC BY
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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.