The levels of specific proteins in human blood are important indicators for assessing health status. Investigating how genetic and other factors shape the plasma proteome is of great significance for biomarker discovery and drug development. At present, large-scale cohort studies rely mainly on affinity-based proteomics technologies to explore the relationship between blood protein levels and these factors. Although mass spectrometry (MS)-based proteomics offers higher specificity in both identification and quantification, studies using it remain relatively rare.
On 19 February, Matthias Mann's team, a leading group in proteomics, together with the team of Torben Hansen, used MS-based plasma proteomics to investigate in depth the influence of genetic variation, demographic characteristics and health factors on plasma protein levels. The findings were published under the title "Plasma proteome variation and its genetic determinants in children and adolescents" in the authoritative international journal Nature Genetics (IF: 31.7).
|Experimental Design|
Discovery cohort:2,147 children and adolescents aged 5–20 years, of whom 45% came from the general population and 55% were patients at obesity clinics.
Validation cohort:558 patients aged 19–82 years with alcohol-related liver disease (ALD), together with 1,000 children and adolescents aged 5–20 years.
Variables analysed:
genetic data: information on 5.2 million SNPs;
plasma DIA proteomics data: 1,216 proteins;
clinical information: age, sex, BMI and more.
Study workflow
|Key Results|
► Influence of non-genetic factors
The dynamic variation of plasma proteins is shaped by non-genetic factors, laying an important foundation for the discovery of potential biomarkers and the construction of protein molecular clocks.
The levels of 58% of proteins were significantly influenced by age, sex or BMI, among which:
● 40% of proteins were associated with age (proteins that change with age, such as F9, RBP4 and COL1A1);
● 32% were associated with sex (sex-differential proteins such as PZP, BCHE and CD5L);
● 22% were associated with BMI (obesity-related proteins such as the inflammatory markers C3, CRP and APCS).
Protein levels predicted age (with an error of ±1.2 years) and BMI accurately, providing an important reference for biomarker research.
Analysis of plasma proteins associated with age, sex and BMI-SDS
► Influence of genetic factors
The regulation of protein expression by genetic factors remains stable across age groups, laying a foundation for the discovery of markers for early disease diagnosis.
The study identified 1,947 protein quantitative trait loci (pQTLs), including 310 newly discovered loci. These pQTLs regulate 443 different proteins, of which 62% are located in cis-regulatory regions (adjacent to the gene) and 38% in trans-regulatory regions (distal regions).
●Effect sizes differ markedly:some pQTLs change protein levels by 2–30 fold (such as LBP and HLA-C);
●High reproducibility:91% of the pQTLs were validated in a cohort of 558 adults, with consistent effect directions (Pearson's r > 0.97).
Reproducibility of pQTLs in children and adults
|Conclusions|
This study is the first to comprehensively dissect the influence of genetic and non-genetic factors on the plasma proteome in a paediatric population. The results confirm that the impact of genetic regulation on plasma proteins runs not only throughout childhood but on into adulthood as well, providing a valuable resource for deeper understanding of disease mechanisms, the development of biomarkers and the validation of drug targets.
