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 S.V. 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 J. Mukamal, Anne B. Newman, Debby Ngo, Michelle C. Odden, Ramachandran S. Vasan, Ali Shojaie, Noah Simon, George Davey Smith, Neil M. Davies, David S. Siscovick, Nona Sotoodehnia, Russell P. Tracy, Kerri L. Wiggins, Jie Zheng, Bruce M. Psaty

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

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 (US)
Pages (from-to)755-765
Number of pages11
JournalEuropean Journal of Epidemiology
Volume37
Issue number7
DOIs
StatePublished - Jul 2022

Bibliographical note

Funding Information:
This research was supported by contracts 75N92021D00006, HHSN268201200036C, HHSN268200800007C, HHSN268201800001C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086 and R01HL132320, and grants U01HL080295, U01HL130114, and HL144483 from the National Heart, Lung, and Blood Institute (NHLBI), with additional contribution from RF1AG063507 from the national Institute of Aging, and from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided by R01AG023629 from the National Institute on Aging (NIA). A full list of principal CHS investigators and institutions can be found at CHS‐NHLBI.org. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health (NIH). ND and GDS work in a Unit supported by the Medical Research Council (MC_UU_00011/1) and the University of Bristol. JZ is supported by the Academy of Medical Sciences (AMS) Springboard Award, the Wellcome Trust, the Government Department of Business, Energy and Industrial Strategy (BEIS), the British Heart Foundation and Diabetes UK (SBF006\1117).

Funding Information:
This research was supported by contracts 75N92021D00006, HHSN268201200036C, HHSN268200800007C, HHSN268201800001C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086 and R01HL132320, and grants U01HL080295, U01HL130114, and HL144483 from the National Heart, Lung, and Blood Institute (NHLBI), with additional contribution from RF1AG063507 from the national Institute of Aging, and from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided by R01AG023629 from the National Institute on Aging (NIA). A full list of principal CHS investigators and institutions can be found at CHS‐NHLBI.org. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health (NIH). ND and GDS work in a Unit supported by the Medical Research Council (MC_UU_00011/1) and the University of Bristol. JZ is supported by the Academy of Medical Sciences (AMS) Springboard Award, the Wellcome Trust, the Government Department of Business, Energy and Industrial Strategy (BEIS), the British Heart Foundation and Diabetes UK (SBF006\1117).

Publisher Copyright:
© 2022, Springer Nature B.V.

Keywords

  • Cardiovascular Disease
  • Cohort Study
  • Genomics
  • Proteomics

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