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Registry Data Set - Proteomic Models in Preeclampsia.xlsx (6.75 MB)

Proteomic Models in Preeclampsia

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posted on 2019-04-19, 02:07 authored by Mohammad S. Ghaemi, Adi L. Tarca, Roberto Romero, Natalie Stanley, Ramin Fallahzadeh, Athena Tanada, Anthony Culos, Kazuo Ando, Xiaoyuan Han, Yair J. Blumenfeld, Maurice L. Druzin, Yasser Y. El-Sayed, Ronald S. Gibbs, Virginia D. Winn, Kevin Contrepois, Xuefeng B. Ling, Ronald J. Wong, Gary M. Shaw, David K. Stevenson, Brice Gaudilliere, Nima Aghaeepour, Martin S. AngstMartin S. Angst

The study aim was to discover bio-signatures predicting the risk of preeclampsia in two independent cohorts (Stanford and Detroit) of pregnant women using a highly-multiplexed and aptamer-based proteomic array (SomaLogic).

Two spreadsheets contain patient data listed separately for the two cohorts, namely patient ID (de-identified), group (preeclampsia or control), age, body mass index, race, gravidity, and parity.

Two additional spreadsheets contain proteomic data listed separately for the two cohorts. Columns A to C list patient ID (de-identified), group (preeclampsia or control), and gestational age at the time of sampling. Subsequent columns list relative plasma concentrations (florescence units) for specific proteins. Rows 1 to 5 indicate SomaLogic ID, full protein name, UniProt ID, Gene ID, and gene symbol for each protein.

Funding

March of Dimes, Bill and Melinda Gates Foundation, Stanford Child Health Research Institute, Mary L Johnson Research Fund, Doris Duke Charitable Foundation, and Charles and Marie Robertson’s Foundation

History