Sexually-dimorphic targeting of functionally-related genes in COPD

Kimberly Glass, John Quackenbush, Edwin K. Silverman, Bartolome Celli, Stephen I. Rennard, Guo Cheng Yuan, Dawn L. DeMeo

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

BACKGROUND: There is growing evidence that many diseases develop, progress, and respond to therapy differently in men and women. This variability may manifest as a result of sex-specific structures in gene regulatory networks that influence how those networks operate. However, there are few methods to identify and characterize differences in network structure, slowing progress in understanding mechanisms driving sexual dimorphism.

RESULTS: Here we apply an integrative network inference method, PANDA (Passing Attributes between Networks for Data Assimilation), to model sex-specific networks in blood and sputum samples from subjects with Chronic Obstructive Pulmonary Disease (COPD). We used a jack-knifing approach to build an ensemble of likely networks for each sex. By adapting statistical methods to compare these network ensembles, we were able to identify strong differential-targeting patterns associated with functionally-related sets of genes, including those involved in mitochondrial function and energy metabolism. Network analysis also identified several potential sex- and disease-specific transcriptional regulators of these pathways.

CONCLUSIONS: Network analysis yielded insight into potential mechanisms driving sexual dimorphism in COPD that were not evident from gene expression analysis alone. We believe our ensemble approach to network analysis provides a principled way to capture sex-specific regulatory relationships and could be applied to identify differences in gene regulatory patterns in a wide variety of diseases and contexts.

Original languageEnglish (US)
Pages (from-to)118
Number of pages1
JournalBMC Systems Biology
Volume8
DOIs
StatePublished - 2014

Fingerprint

Pulmonary diseases
Electric network analysis
Chronic Obstructive Pulmonary Disease
Genes
Gene
Network Analysis
Ensemble
Jacks
Sex Characteristics
Gene expression
Statistical methods
Blood
Energy Metabolism
Gene Regulatory Networks
Gene Expression Analysis
Regulator Genes
Sputum
Data Assimilation
Gene Regulatory Network
Network Structure

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Glass, K., Quackenbush, J., Silverman, E. K., Celli, B., Rennard, S. I., Yuan, G. C., & DeMeo, D. L. (2014). Sexually-dimorphic targeting of functionally-related genes in COPD. BMC Systems Biology, 8, 118. https://doi.org/10.1186/s12918-014-0118-y

Sexually-dimorphic targeting of functionally-related genes in COPD. / Glass, Kimberly; Quackenbush, John; Silverman, Edwin K.; Celli, Bartolome; Rennard, Stephen I.; Yuan, Guo Cheng; DeMeo, Dawn L.

In: BMC Systems Biology, Vol. 8, 2014, p. 118.

Research output: Contribution to journalArticle

Glass, K, Quackenbush, J, Silverman, EK, Celli, B, Rennard, SI, Yuan, GC & DeMeo, DL 2014, 'Sexually-dimorphic targeting of functionally-related genes in COPD', BMC Systems Biology, vol. 8, pp. 118. https://doi.org/10.1186/s12918-014-0118-y
Glass K, Quackenbush J, Silverman EK, Celli B, Rennard SI, Yuan GC et al. Sexually-dimorphic targeting of functionally-related genes in COPD. BMC Systems Biology. 2014;8:118. https://doi.org/10.1186/s12918-014-0118-y
Glass, Kimberly ; Quackenbush, John ; Silverman, Edwin K. ; Celli, Bartolome ; Rennard, Stephen I. ; Yuan, Guo Cheng ; DeMeo, Dawn L. / Sexually-dimorphic targeting of functionally-related genes in COPD. In: BMC Systems Biology. 2014 ; Vol. 8. pp. 118.
@article{bf570fa7d53545169075511ed30ec02c,
title = "Sexually-dimorphic targeting of functionally-related genes in COPD",
abstract = "BACKGROUND: There is growing evidence that many diseases develop, progress, and respond to therapy differently in men and women. This variability may manifest as a result of sex-specific structures in gene regulatory networks that influence how those networks operate. However, there are few methods to identify and characterize differences in network structure, slowing progress in understanding mechanisms driving sexual dimorphism.RESULTS: Here we apply an integrative network inference method, PANDA (Passing Attributes between Networks for Data Assimilation), to model sex-specific networks in blood and sputum samples from subjects with Chronic Obstructive Pulmonary Disease (COPD). We used a jack-knifing approach to build an ensemble of likely networks for each sex. By adapting statistical methods to compare these network ensembles, we were able to identify strong differential-targeting patterns associated with functionally-related sets of genes, including those involved in mitochondrial function and energy metabolism. Network analysis also identified several potential sex- and disease-specific transcriptional regulators of these pathways.CONCLUSIONS: Network analysis yielded insight into potential mechanisms driving sexual dimorphism in COPD that were not evident from gene expression analysis alone. We believe our ensemble approach to network analysis provides a principled way to capture sex-specific regulatory relationships and could be applied to identify differences in gene regulatory patterns in a wide variety of diseases and contexts.",
author = "Kimberly Glass and John Quackenbush and Silverman, {Edwin K.} and Bartolome Celli and Rennard, {Stephen I.} and Yuan, {Guo Cheng} and DeMeo, {Dawn L.}",
year = "2014",
doi = "10.1186/s12918-014-0118-y",
language = "English (US)",
volume = "8",
pages = "118",
journal = "BMC Systems Biology",
issn = "1752-0509",
publisher = "BioMed Central",

}

TY - JOUR

T1 - Sexually-dimorphic targeting of functionally-related genes in COPD

AU - Glass, Kimberly

AU - Quackenbush, John

AU - Silverman, Edwin K.

AU - Celli, Bartolome

AU - Rennard, Stephen I.

AU - Yuan, Guo Cheng

AU - DeMeo, Dawn L.

PY - 2014

Y1 - 2014

N2 - BACKGROUND: There is growing evidence that many diseases develop, progress, and respond to therapy differently in men and women. This variability may manifest as a result of sex-specific structures in gene regulatory networks that influence how those networks operate. However, there are few methods to identify and characterize differences in network structure, slowing progress in understanding mechanisms driving sexual dimorphism.RESULTS: Here we apply an integrative network inference method, PANDA (Passing Attributes between Networks for Data Assimilation), to model sex-specific networks in blood and sputum samples from subjects with Chronic Obstructive Pulmonary Disease (COPD). We used a jack-knifing approach to build an ensemble of likely networks for each sex. By adapting statistical methods to compare these network ensembles, we were able to identify strong differential-targeting patterns associated with functionally-related sets of genes, including those involved in mitochondrial function and energy metabolism. Network analysis also identified several potential sex- and disease-specific transcriptional regulators of these pathways.CONCLUSIONS: Network analysis yielded insight into potential mechanisms driving sexual dimorphism in COPD that were not evident from gene expression analysis alone. We believe our ensemble approach to network analysis provides a principled way to capture sex-specific regulatory relationships and could be applied to identify differences in gene regulatory patterns in a wide variety of diseases and contexts.

AB - BACKGROUND: There is growing evidence that many diseases develop, progress, and respond to therapy differently in men and women. This variability may manifest as a result of sex-specific structures in gene regulatory networks that influence how those networks operate. However, there are few methods to identify and characterize differences in network structure, slowing progress in understanding mechanisms driving sexual dimorphism.RESULTS: Here we apply an integrative network inference method, PANDA (Passing Attributes between Networks for Data Assimilation), to model sex-specific networks in blood and sputum samples from subjects with Chronic Obstructive Pulmonary Disease (COPD). We used a jack-knifing approach to build an ensemble of likely networks for each sex. By adapting statistical methods to compare these network ensembles, we were able to identify strong differential-targeting patterns associated with functionally-related sets of genes, including those involved in mitochondrial function and energy metabolism. Network analysis also identified several potential sex- and disease-specific transcriptional regulators of these pathways.CONCLUSIONS: Network analysis yielded insight into potential mechanisms driving sexual dimorphism in COPD that were not evident from gene expression analysis alone. We believe our ensemble approach to network analysis provides a principled way to capture sex-specific regulatory relationships and could be applied to identify differences in gene regulatory patterns in a wide variety of diseases and contexts.

UR - http://www.scopus.com/inward/record.url?scp=84964312497&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84964312497&partnerID=8YFLogxK

U2 - 10.1186/s12918-014-0118-y

DO - 10.1186/s12918-014-0118-y

M3 - Article

VL - 8

SP - 118

JO - BMC Systems Biology

JF - BMC Systems Biology

SN - 1752-0509

ER -