PEDF a Pleiotropic WTC-LI Biomarker: Machine Learning Biomarker Identification and Validation

Details

• Personal Author:
  Crowley G ; Kim J ; Kwon S ; Lam R ; Liu M ; Nolan A ; Prezant DJ
• Description:
  RATIONALE Metabolic Syndrome biomarkers expressed soon after exposure to World Trade Center-particulate matter (WTC· PM) predict future WTC-Lung Injury (WTC-LI), an obstructive airways disease. Previous panel-based investigation identified metabolic and inflammatory serum biomarkers of WTC-ll. However, there remains unaddressed multiocollinearity in our panel-based and high-throughput platform datasets used to assess phenotype proximal to WTC-exposure. This study demonstrates the use of an automated, machine-learning-based. high-dimensional data pruning technique. and validates identified biomarkers in a larger cohort. METHODS Male, never-smoking WTC·LI cases (FEV1%Pred
• Subjects:
  Biomarkers Cardiovascular Diseases Cardiovascular System Immune System Lung Occupational Health Particulate Matter Respiratory System Safety September 11 Terrorist Attacks
• Keywords:
  Cardiovascular Disease Cytokines Immune Reaction Lung Function Particulates Respiratory Irritants World Trade Center WTC
• ISSN:
  1073-449X
• Document Type:
  Text
• Funding:
  Cooperative Agreement
• Genre:
  Abstract or Summary
• Place as Subject:
  New York ; OSHA Region 2
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  201
• NIOSHTIC Number:
  nn:20066340
• Citation:
  Am J Respir Crit Care Med 2020 May; 201(Abstract Issue):A7124
• Email:
  george.crowley@nyumc.org
• Federal Fiscal Year:
  2020
• Performing Organization:
  New York University School of Medicine
• Peer Reviewed:
  False
• Start Date:
  20170701
• Source Full Name:
  American Journal of Respiratory and Critical Care Medicine
• Supplement:
  Abstract Issue
• End Date:
  20260630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:daaf2c7f361d42fea027816c8cd7fed63078f7ec81f327a4f5b6a1d6427645e26e723fac269379b5f867390a34693f846534d9706a3636eac848848f23f7ad55
• Download URL:
  https://stacks.cdc.gov/view/cdc/212808/cdc_212808_DS1.pdf
• File Type:
  [PDF - 184.72 KB ]