Sexually-dimorphic targeting of functionally-related genes in COPD
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Updated: Apr 20, 2026
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Published on: August 25, 2017
Kimberly Glass1,2,3, John Quackenbush4,5,6, Edwin K Silverman7,8
1Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA. rekrg@channing.harvard.edu.
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.
Insights
Researchers identified sex-specific gene regulatory networks in Chronic Obstructive Pulmonary Disease (COPD) using an ensemble network approach. This method reveals potential mechanisms driving sex differences in disease not seen with gene expression alone.
Area of Science:
- Genomics
- Systems Biology
- Network Medicine
Background:
- Growing evidence suggests diseases manifest and respond differently in males and females.
- Sex-specific structures in gene regulatory networks may drive this variability.
- Limited methods exist to identify and characterize these network differences, hindering understanding of sexual dimorphism.
Purpose of the Study:
- To develop and apply a novel method for identifying sex-specific gene regulatory network structures.
- To investigate mechanisms underlying sexual dimorphism in Chronic Obstructive Pulmonary Disease (COPD).
Main Methods:
- Applied an integrative network inference method, PANDA (Passing Attributes between Networks for Data Assimilation).
- Modeled sex-specific networks using blood and sputum samples from COPD subjects.
- Employed a jack-knifing approach to build an ensemble of networks for each sex and adapted statistical methods for comparison.
Main Results:
- Identified strong differential-targeting patterns linked to functionally related gene sets, including those in mitochondrial function and energy metabolism.
- Discovered potential sex- and disease-specific transcriptional regulators influencing these pathways.
- Revealed insights into COPD sexual dimorphism mechanisms not apparent from gene expression analysis alone.
Conclusions:
- Network analysis provides valuable insights into sex-specific regulatory relationships in COPD.
- The ensemble network approach offers a principled method for capturing sex-specific regulatory patterns.
- This methodology can be broadly applied to study sex differences in gene regulation across various diseases.
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