Longitudinal protein profiling of blood during childhood into early adulthood

Sofia Bergström1, Sophia Björkander2, María Bueno Álvez1

  • 1Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden.

Nature Communications
|April 22, 2026
PubMed

Insights

This study tracked 3509 plasma proteins in 100 individuals from childhood to adulthood, revealing dynamic age and sex-related changes. These proteomic shifts offer insights into healthy human development and potential disease biomarkers.

Area of Science:

  • Human physiology
  • Proteomics
  • Developmental biology

Background:

  • Understanding healthy human development is crucial for identifying disease etiology.
  • Longitudinal protein profiling in childhood and early adulthood is underexplored.
  • Plasma proteomic changes during human development inform physiological understanding.

Purpose of the Study:

  • To longitudinally map plasma protein levels from childhood to early adulthood.
  • To identify age- and sex-related protein trajectories during human development.
  • To provide a resource for understanding physiological development and future biomarker research.

Main Methods:

  • Longitudinal measurement of 5416 plasma proteins using Olink Explore HT.
  • Analysis of 3509 proteins in 100 subjects at ages 4, 8, 16, and 24 years.
  • Statistical analysis to identify age- and sex-associated proteins and developmental trajectories.

Main Results:

  • 54% of measured proteins showed significant associations with age.
  • Distinct protein trajectories were observed from childhood to adulthood.
  • Identified proteins related to bone, neural function, drug metabolism, and hormonal control.
  • Pronounced sex-related differences emerged in late adolescence and early adulthood.

Conclusions:

  • Plasma protein levels undergo dynamic, age- and sex-dependent changes throughout the first two decades of life.
  • These findings provide a valuable resource for human developmental biology and disease etiology.
  • The study highlights the potential of proteomic data for future biomarker discovery.

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