Plasma Proteome Variation and its Genetic Determinants in Children and Adolescents

The levels of specific proteins in human blood are the most commonly used indicators of potential health-related problems[1][1]. Understanding the genetic and other determinants of the human plasma proteome can aid in biomarker research and drug development. Diverse factors including genetics, age, sex, body mass index (BMI), growth and development including puberty can affect the circulating levels of proteins[2][2]–[5][3]. Affinity-based proteomics can infer the relationship between blood protein levels and these factors at a large scale[6][4]–[10][5]. Compared to these methods, mass spectrometry (MS)-based proteomics provides much higher specificity of identification and quantification[11][6]–[13][7], but existing studies are limited by small sample sizes or low numbers of quantified proteins[14][8]–[17][9]. Here we aim to elucidate to which extent genomic variation affects plasma protein levels across diverse age ranges and cohort characteristics. Employing a streamlined and highly quantitative MS-based plasma proteomics workflow, we measured the plasma proteome of 2,147 children and adolescents. Levels of 90% of these proteins were significantly associated with age, sex, BMI or genetics. More than 1,000 protein quantitative trait loci (pQTLs) – a third of which were novel – regulated protein levels between a few percent and up to 30-fold. These replicated excellently in an independent cohort of 558 adults, with highly concordant effect sizes (Pearson’s r > 0.97). We developed a framework to eliminate artefactual pQTLs due to protein-altering variants, paving the way for large-scale interrogation of pQTLs using MS-based proteomics. Our data reveal unexpectedly extensive genetic impacts on plasma protein levels, consistent from childhood into adulthood. These findings have implications for biomarker research and drug development. Highlights 1. First large-scale proteome-wide and genome-wide association study in children and adolescents 2. MS-based proteomics achieves very high specificity and quantitative accuracy 3. Robust plasma protein trajectories during development predict age and body mass index 4. Largest set of pQTLs for plasma proteome by MS-based proteomics 5. pQTLs are highly replicable between children and adults 6. Large-scale pQTL identification enables generic drug target validation ### Competing Interest Statement M.M. is an indirect investor in Evosep. ### Funding Statement This study was funded by the Novo Nordisk Foundation for the Clinical Proteomics Group (grant no. NNF15CC0001 to M.M.), the Challenge Program (grant no. NNF15OC0016692 to the MicrobLiver consortium), the Innovation Fund Denmark (grant no. 0603-00484B to T.H.), and the Novo Nordisk Foundation (grant no. NNF15OC0016544), while the European Union Horizon 2020 research and innovation program (grant no. 668031 to the GALAXY consortium) funded the GALAXY cohorts in the ALD study. Additionally, L.N. and S.R. received support from the Novo Nordisk Foundation (grant no. NNF14CC0001 and NNF21SA0072102 to S.R.), M.T. from the Novo Nordisk Foundation (grant no. NNF20OC0059393), C.E.F. received support from the BRIDGE - Translational Excellence Program (grant no. NNF18SA0034956) and the Region Zealand Health and Medical Research Foundation (grant no. R32-A1191). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics committee for the Region Zealand and Region of Southern Denmark in Denmark gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The datasets produced in the present study are available upon reasonable request to the authors. All analysis results are available as supplementary tables. Searchable results are available online at proteomevariation.org [1]: #ref-1 [2]: #ref-2 [3]: #ref-5 [4]: #ref-6 [5]: #ref-10 [6]: #ref-11 [7]: #ref-13 [8]: #ref-14 [9]: #ref-17