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MOESM1 of Peripheral blood proteomic profiling of idiopathic pulmonary fibrosis biomarkers in the multicentre IPF-PRO Registry

Authors :
Todd, Jamie
Neely, Megan
Overton, Robert
Durham, Katey
Mridu Gulati
Huang, Howard
Roman, Jesse
L. Newby
Flaherty, Kevin
Vinisko, Richard
Liu, Yi
Roy, Janine
Schmid, Ramona
Strobel, Benjamin
Hesslinger, Christian
Leonard, Thomas
Noth, Imre
Belperio, John
Palmer, Scott
Publisher :
figshare

Abstract

Additional file 1: Figure S1. Differential levels of circulating proteins in participants with IPF versus controls. Volcano plot of the Log2fold change in means by log10 of the corrected p Value for each protein. The horizontal line indicates the threshold for statistical significance. Figure S2. Histogram of the linear discriminant scores for each participant in the IPF and control cohort. Table S1. Summary statistics for all 1305 proteins assayed across the IPF and control cohorts. Protein data are reported in relative fluorescent units. Table S2. Operating characteristics of all models in the test set for the IPF versus control multivariable modelling. Table S3. Proteins designated as among the most influential in at least two of the eight multivariable models. Table S4. Proteins significantly associated with FVC % predicted (unadjusted and adjusted for anti-fibrotic treatment). Table S5. Proteins significantly associated with DLco % predicted (unadjusted and adjusted for anti-fibrotic treatment). Table S6. Proteins significantly associated with composite physiologic index (unadjusted and adjusted for anti-fibrotic treatment).

Subjects

Subjects :
respiratory system
3. Good health

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........cdc4886fae7f372daf796aa872334a34