0
Obstructive Lung Diseases: Novel Predictors of COPD Outcomes |

Data-Driven Identification of Novel Molecular Subclasses of COPD

Eric Reed, MS; David Bray, BS; Stephen Lam; Maarten van den Berge; Gang Liu; Xiaohui Zhang; Yuriy Alekseyev; Avrum Spira; Marc Lenburg; Katrina Steiling
Author and Funding Information

Boston University School of Medicine, Boston, MA


Copyright 2016, American College of Chest Physicians. All Rights Reserved.


Chest. 2016;150(4_S):916A. doi:10.1016/j.chest.2016.08.1016
Text Size: A A A
Published online

Extract

SESSION TITLE: Novel Predictors of COPD Outcomes

SESSION TYPE: Original Investigation Slide

PRESENTED ON: Sunday, October 23, 2016 at 01:30 PM - 03:00 PM

PURPOSE: Chronic obstructive pulmonary disease (COPD) is characterized by an irreversible obstruction to airflow and affects 14.8 million people in the United States alone. Treatment options are currently limited to therapies that variably manage disease symptoms without permanently reversing airflow obstruction. The lack of disease-modifying therapies for COPD could be explained in part by our current lack of understanding the multitude of molecular mechanisms underlying the pathobiology of COPD. Our prior studies have identified a 98-gene expression signature of COPD and disease severity using airway epithelial brushings, but also significant variation in the expression of this signature among individuals with COPD. We therefore sought to explore this molecular heterogeneity by applying an unsupervised learning approach to sub-classify patients with COPD.

First Page Preview

View Large
First page PDF preview

Sign In to Access Full Content

MEMBER & INDIVIDUAL SUBSCRIBER

Want Access?

NEW TO CHEST?

Become a CHEST member and receive a FREE subscription as a benefit of membership.

Individuals can purchase this article on ScienceDirect.

Individuals can purchase a subscription to the journal.

Individuals can purchase a subscription to the journal or buy individual articles.

Learn more about membership or Purchase a Full Subscription.

INSTITUTIONAL ACCESS

Institutional access is now available through ScienceDirect and can be purchased at myelsevier.com.

Sign In to Access Full Content

MEMBER & INDIVIDUAL SUBSCRIBER

Want Access?

NEW TO CHEST?

Become a CHEST member and receive a FREE subscription as a benefit of membership.

Individuals can purchase this article on ScienceDirect.

Individuals can purchase a subscription to the journal.

Individuals can purchase a subscription to the journal or buy individual articles.

Learn more about membership or Purchase a Full Subscription.

INSTITUTIONAL ACCESS

Institutional access is now available through ScienceDirect and can be purchased at myelsevier.com.

Figures

Tables

References

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Sign In to Access Full Content

MEMBER & INDIVIDUAL SUBSCRIBER

Want Access?

NEW TO CHEST?

Become a CHEST member and receive a FREE subscription as a benefit of membership.

Individuals can purchase this article on ScienceDirect.

Individuals can purchase a subscription to the journal.

Individuals can purchase a subscription to the journal or buy individual articles.

Learn more about membership or Purchase a Full Subscription.

INSTITUTIONAL ACCESS

Institutional access is now available through ScienceDirect and can be purchased at myelsevier.com.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Find Similar Articles
CHEST Journal Articles
PubMed Articles
  • CHEST Journal
    Print ISSN: 0012-3692
    Online ISSN: 1931-3543