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Hum Mol Genet. 2018 Nov 1;27(21):3801-3812. doi: 10.1093/hmg/ddy269.

Whole exome sequencing analysis in severe chronic obstructive pulmonary disease.

Author information

1
Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America.
2
Department of Physics, Northeastern University, Boston, Massachusetts, United States of America.
3
Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America.
4
Center for Precision Health, School of Public Health and School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America.
5
Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America.
6
Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America.
7
Dan L. Duncan Comprehensive Cancer Center, Department of Medicine, Baylor College of Medicine, Houston, Texas, United States of America.
8
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States of America.
9
National Jewish Health, Denver, Colorado, United States of America.
10
Division of Allergy and Clinical Immunology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.
11
Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.
12
Division of Genetic Medicine, Department of Pediatrics, University of Washington and Seattle Children's Hospital, Seattle, Washington , United States of America.
13
University College London, London, United Kingdom.
14
Respiratory Institute, Hospital Clinic, IDIBAPS, University of Barcelona, CIBERES, Barcelona, Spain.
15
University of Liverpool.
16
Mondo Medico di I.F.I.M. srl, Multidisciplinary and Rehabilitation Outpatient Clinic, Borgomanero, Novara, Italy.
17
Department of Respiratory Medicine, Maastricht University Medical Center, AZ Maastricht, The Netherlands.
18
University of Manchester, Manchester, United Kingdom.
19
Respiratory Division, Department of Medicine, University of British Columbia, Vancouver, British Columbia V6T, Canada.
20
University of Nebraska Medical Center, Omaha, Nebraska, United States of America.
21
AstraZeneca, Cambridge CB2 0RE, United Kingdom.
22
GSK Research and Development, KingOf Prussia, Pennsylvania, United States of America.
23
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
24
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America.
25
Channing Division of Network Medicine, Longwood Avenue, Boston, MA, USA.

Abstract

Chronic obstructive pulmonary disease (COPD), one of the leading causes of death worldwide, is substantially influenced by genetic factors. Alpha-1 antitrypsin deficiency demonstrates that rare coding variants of large effect can influence COPD susceptibility. To identify additional rare coding variants in patients with severe COPD, we conducted whole exome sequencing analysis in 2543 subjects from two family-based studies (Boston Early-Onset COPD Study and International COPD Genetics Network) and one case-control study (COPDGene). Applying a gene-based segregation test in the family-based data, we identified significant segregation of rare loss of function variants in TBC1D10A and RFPL1 (P-value < 2x10-6), but were unable to find similar variants in the case-control study. In single-variant, gene-based and pathway association analyses, we were unable to find significant findings that replicated or were significant in meta-analysis. However, we found that the top results in the two datasets were in proximity to each other in the protein-protein interaction network (P-value = 0.014), suggesting enrichment of these results for similar biological processes. A network of these association results and their neighbors was significantly enriched in the transforming growth factor beta-receptor binding and cilia-related pathways. Finally, in a more detailed examination of candidate genes, we identified individuals with putative high-risk variants, including patients harboring homozygous mutations in genes associated with cutis laxa and Niemann-Pick Disease Type C. Our results likely reflect heterogeneity of genetic risk for COPD along with limitations of statistical power and functional annotation, and highlight the potential of network analysis to gain insight into genetic association studies.

PMID:
30060175
PMCID:
PMC6196654
[Available on 2019-11-01]
DOI:
10.1093/hmg/ddy269

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