Post-GWAS Prioritization Through Data Integration Provides Novel Insights on Chronic Obstructive Pulmonary Disease.
Rich collections of genomic and epigenomic annotations, availabilities of large population cohorts for genome-wide association studies (GWAS), and advancements in data integration techniques provide the unprecedented opportunity to accelerate discoveries in complex disease studies through integrative analyses. In this paper, we apply a variety of approaches to integrate GWAS summary statistics of chronic obstructive pulmonary disease (COPD) with functional annotations to illustrate how data integration could help researchers understand complex human diseases. We show that incorporating functional annotations can better prioritize GWAS signals at both the global and the local levels. Signal prioritization on severe COPD GWAS reveals multiple potential risk loci that are linked with pulmonary functions. Enrichment analysis provides novel insights on the pathogenesis of COPD and hints the existence of genetic contributions to muscle dysfuncion and chronic lung inflammation, two symptoms that are often co-morbid with COPD. Our results suggest that rich signals for COPD genetics are still buried under the Bonferroni-corrected genome-wide significance threshold. Many more biological findings are expected to emerge as more samples are recruited for COPD studies.
Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
Qiongshi
Q
Lu
Yale College, New Haven, CT, USA.
Chentian
C
Jin
Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
Jiehuan
J
Sun
National Jewish Health, Department of Medicine, Denver, CO, USA.
Russell
R
Bowler
Department of Biostatistics and Informatics, University of Colorado Denver, Denver, CO, USA.
Katerina
K
Kechris
Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA.
Naftali
N
Kaminski
Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA; Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; VA Cooperative Studies Program Coordinating Center, West Haven, CT, USA.
Hongyu
H
Zhao