Proteomics and Population Biology in the Cardiovascular Health Study (CHS): design of a study with mentored access and active data sharing

Thomas R Austin*, Caitlin P McHugh, Jennifer A Brody, Joshua C Bis, Colleen M Sitlani, Traci M Bartz, Mary L. Biggs, Nisha Bansal, Petra Buzkova, Steven A Carr, Christopher R deFilippi, Mitchell SV Elkind, Howard A Fink, James S Floyd, Alison E. Fohner, Robert E Gerszten, Susan R Heckbert, Daniel H Katz, Jorge R Kizer, Rozenn N LemaitreW T Longstreth, Barbara McKnight, Hao Mei, Kenneth Jay Mukamal, Anne B Newman, Debby Ngo, Michelle C Odden, Ramachandran S Vasan, Ali Shojaie, Simon Noah Etkind, George Davey Smith, Neil M Davies, David S Siscovick, Nona Sotoodehnia, Russell P Tracy, Kerri L Wiggins, Jie Zheng, Bruce M Psaty

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

12 Citations (Scopus)
36 Downloads (Pure)

Abstract

Background
In the last decade, genomic studies have identified and replicated thousands of genetic associations with measures of health and disease and contributed to the understanding of the etiology of a variety of health conditions. Proteins are key biomarkers in clinical medicine and often drug-therapy targets. Like genomics, proteomics can advance our understanding of biology.

Methods and Results
In the setting of the Cardiovascular Health Study (CHS), a cohort study of older adults, an aptamer-based method that has high sensitivity for low-abundance proteins was used to assay 4979 proteins in frozen, stored plasma from 3188 participants (61% women, mean age 74 years). CHS provides active support, including central analysis, for seven phenotype-specific working groups (WGs). Each CHS WG is led by one or two senior investigators and includes 10 to 20 early or mid-career scientists. In this setting of mentored access, the proteomic data and analytic methods are widely shared with the WGs and investigators so that they may evaluate associations between baseline levels of circulating proteins and the incidence of a variety of health outcomes in prospective cohort analyses. We describe the design of CHS, the CHS Proteomics Study, characteristics of participants, quality control measures, and structural characteristics of the data provided to CHS WGs. We additionally highlight plans for validation and replication of novel proteomic associations.

Conclusion
The CHS Proteomics Study offers an opportunity for collaborative data sharing to improve our understanding of the etiology of a variety of health conditions in older adults.
Original languageEnglish
Pages (from-to)755–765
JournalEuropean Journal of Epidemiology
Volume37
DOIs
Publication statusPublished - 5 Jul 2022

Research Groups and Themes

  • Bristol Population Health Science Institute

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