RDL logo
About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User Guide
​
​
Sign inGet started
​
​

About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User Guide

Sign inGet started
RDL logo

Verified research datasets. Instant access. Built for collaboration.

Navigation

About

Aims and Scope

Advisory Board Members

More

Who We Are?

Add Raw Data

User Guide

Legal

Privacy Policy

Terms of Service

Support

Got an issue? Email us directly.

Email: info@rawdatalibrary.netOpen Mail App
​
​

© 2025 Raw Data Library. All rights reserved.
PrivacyTerms
  1. Raw Data Library
  2. /
  3. Publications
  4. /
  5. Genome-Wide Association Studies of Asthma in Population-Based Cohorts Confirm Known and Suggested Loci and Identify an Additional Association near HLA

Verified authors • Institutional access • DOI aware
50,000+ researchers120,000+ datasets90% satisfaction
Article
en
2012

Genome-Wide Association Studies of Asthma in Population-Based Cohorts Confirm Known and Suggested Loci and Identify an Additional Association near HLA

0 Datasets

0 Files

en
2012
Vol 7 (9)
Vol. 7
DOI: 10.1371/journal.pone.0044008

Get instant academic access to this publication’s datasets.

Create free accountHow it works

Frequently asked questions

Is access really free for academics and students?

Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.

How is my data protected?

Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.

Can I request additional materials?

Yes, message the author after sign-up to request supplementary files or replication code.

Advance your research today

Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.

Get free academic accessLearn more
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaboration
Access Research Data

Join our academic network to download verified datasets and collaborate with researchers worldwide.

Get Free Access
Institutional SSO
Secure
This PDF is not available in different languages.
No localized PDFs are currently available.
Paul M Ridker
Paul M Ridker

Harvard University

Verified
Mika Kähönen
Kay‐Tee Khaw
Jaana Laitinen
+43 more

Abstract

Rationale Asthma has substantial morbidity and mortality and a strong genetic component, but identification of genetic risk factors is limited by availability of suitable studies. Objectives To test if population-based cohorts with self-reported physician-diagnosed asthma and genome-wide association (GWA) data could be used to validate known associations with asthma and identify novel associations. Methods The APCAT (Analysis in Population-based Cohorts of Asthma Traits) consortium consists of 1,716 individuals with asthma and 16,888 healthy controls from six European-descent population-based cohorts. We examined associations in APCAT of thirteen variants previously reported as genome-wide significant (P<5x10−8) and three variants reported as suggestive (P<5×10−7). We also searched for novel associations in APCAT (Stage 1) and followed-up the most promising variants in 4,035 asthmatics and 11,251 healthy controls (Stage 2). Finally, we conducted the first genome-wide screen for interactions with smoking or hay fever. Main Results We observed association in the same direction for all thirteen previously reported variants and nominally replicated ten of them. One variant that was previously suggestive, rs11071559 in RORA, now reaches genome-wide significance when combined with our data (P = 2.4×10−9). We also identified two genome-wide significant associations: rs13408661 near IL1RL1/IL18R1 (PStage1+Stage2 = 1.1x10−9), which is correlated with a variant recently shown to be associated with asthma (rs3771180), and rs9268516 in the HLA region (PStage1+Stage2 = 1.1x10−8), which appears to be independent of previously reported associations in this locus. Finally, we found no strong evidence for gene-environment interactions with smoking or hay fever status. Conclusions Population-based cohorts with simple asthma phenotypes represent a valuable and largely untapped resource for genetic studies of asthma.

How to cite this publication

Mika Kähönen, Kay‐Tee Khaw, Jaana Laitinen, Peter N. Le Souëf, Terho Lehtimäki, Pamela A. F. Madden, Guy B. Marks, Nicholas G. Martin, Melanie C. Matheson, Nicholette D. Palmer, Aarno Palotie, Anneli Pouta, Colin F. Robertson, Jorma Viikari, Elisabeth Widén, Matthias Wjst, Deborah Jarvis, Grant W. Montgomery, Philip J. Thompson, Nicholas J. Wareham, Johan G. Eriksson, Pekka Jousilahti, Tarja Laitinen, Juha Pekkanen, Olli T. Raitakari, George O'connor, Veikko Salomaa, Paul M Ridker, Joel N. Hirschhorn, Adaikalavan Ramasamy, Mikko Kuokkanen, Sailaja Vedantam, Zofia K. Z. Gajdos, Alexessander Couto Alves, Helen N. Lyon, Manuel A. R. Ferreira, David P. Strachan, Jing Hua Zhao, Michael J. Abramson, Matthew A. Brown, Lachlan Coin, Shyamali C. Dharmage, David L. Duffy, Tari Haahtela, Andrew C. Heath, Christer Janson (2012). Genome-Wide Association Studies of Asthma in Population-Based Cohorts Confirm Known and Suggested Loci and Identify an Additional Association near HLA. , 7(9), DOI: https://doi.org/10.1371/journal.pone.0044008.

Related publications

Why join Raw Data Library?

Quality

Datasets shared by verified academics with rich metadata and previews.

Control

Authors choose access levels; downloads are logged for transparency.

Free for Academia

Students and faculty get instant access after verification.

Publication Details

Type

Article

Year

2012

Authors

46

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1371/journal.pone.0044008

Join Research Community

Access datasets from 50,000+ researchers worldwide with institutional verification.

Get Free Access