Sexual dimorphism, age and fat mass are key phenotypic drivers of proteomic signatures

Research output: Contribution to journalJournal articleResearchpeer-review

  • Aoife M Curran
  • Colleen Fogarty Draper
  • Marie-Pier Scott-Boyer
  • Armand Valsesia
  • Helen M Roche
  • Miriam F Ryan
  • Michael J Gibney
  • Martina Kutmon
  • Chris T Evelo
  • Susan L Coort
  • Astrup, Arne
  • Wim H Saris
  • Lorraine Brennan
  • Jim Kaput

Validated protein biomarkers are needed for assessing health trajectories, predicting and sub-classifying disease, and optimizing diagnostic and therapeutic clinical decision-making. The sensitivity, specificity, accuracy, and precision of single or combinations of protein biomarkers may be altered by differences in physiological states limiting the ability to translate research results to clinically useful diagnostic tests. Aptamer based affinity assays were used to test whether low abundant serum proteins differed based on age, sex and fat mass in a healthy population of 94 males and 102 females from the MECHE cohort. The findings were replicated in 217 healthy male and 377 healthy female participants in the DiOGenes consortium. Of the 1129 proteins in the panel, 141, 51 and 112 proteins (adjusted p<0.1) were identified in the MECHE cohort and significantly replicated in DiOGenes for sexual dimorphism, age, and fat mass, respectively. Pathway analysis classified a subset of proteins from the 3 phenotypes to the complement and coagulation cascades pathways and to immune and coagulation processes. These results demonstrated that specific proteins were statistically associated with dichotomous (male v female) and continuous phenotypes (age, fat mass) which may influence the identification and use of biomarkers of clinical utility for health diagnosis and therapeutic strategies.

Original languageEnglish
JournalJournal of Proteome Research
Volume16
Issue number11
Pages (from-to)4122-4133
Number of pages12
ISSN1535-3893
DOIs
Publication statusPublished - 2017

    Research areas

  • Proteomics, Phenotype, Biomarker, Sex, Male, Female, Age, Fat mass, Protein, Pathway

ID: 184065674