Raw Data Library
About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User Guide
Green Science
​
​
EN
Kurumsal BaşvuruSign inGet started
​
​

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

Language

Kurumsal Başvuru

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?

Contact

Add Raw Data

User Guide

Legal

Privacy Policy

Terms of Service

Support

Got an issue? Email us directly.

Email: info@rawdatalibrary.netOpen Mail App
​
​

© 2026 Raw Data Library. All rights reserved.
PrivacyTermsContact
  1. Raw Data Library
  2. /
  3. Publications
  4. /
  5. Stratifying Type 2 Diabetes Cases by BMI Identifies Genetic Risk Variants in LAMA1 and Enrichment for Risk Variants in Lean Compared to Obese Cases

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

Stratifying Type 2 Diabetes Cases by BMI Identifies Genetic Risk Variants in LAMA1 and Enrichment for Risk Variants in Lean Compared to Obese Cases

0 Datasets

0 Files

en
2012
Vol 8 (5)
Vol. 8
DOI: 10.1371/journal.pgen.1002741

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.
Frank B Hu
Frank B Hu

Harvard University

Verified
John R. B. Perry
Benjamin F. Voight
Loïc Yengo
+71 more

Abstract

Common diseases such as type 2 diabetes are phenotypically heterogeneous. Obesity is a major risk factor for type 2 diabetes, but patients vary appreciably in body mass index. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI<25 Kg/m²) compared to obese cases (BMI≥30 Kg/m²). We performed two case-control genome-wide studies using two accepted cut-offs for defining individuals as overweight or obese. We used 2,112 lean type 2 diabetes cases (BMI<25 kg/m²) or 4,123 obese cases (BMI≥30 kg/m²), and 54,412 un-stratified controls. Replication was performed in 2,881 lean cases or 8,702 obese cases, and 18,957 un-stratified controls. To assess the effects of known signals, we tested the individual and combined effects of SNPs representing 36 type 2 diabetes loci. After combining data from discovery and replication datasets, we identified two signals not previously reported in Europeans. A variant (rs8090011) in the LAMA1 gene was associated with type 2 diabetes in lean cases (P = 8.4×10⁻⁹, OR = 1.13 [95% CI 1.09-1.18]), and this association was stronger than that in obese cases (P = 0.04, OR = 1.03 [95% CI 1.00-1.06]). A variant in HMG20A--previously identified in South Asians but not Europeans--was associated with type 2 diabetes in obese cases (P = 1.3×10⁻⁸, OR = 1.11 [95% CI 1.07-1.15]), although this association was not significantly stronger than that in lean cases (P = 0.02, OR = 1.09 [95% CI 1.02-1.17]). For 36 known type 2 diabetes loci, 29 had a larger odds ratio in the lean compared to obese (binomial P = 0.0002). In the lean analysis, we observed a weighted per-risk allele OR = 1.13 [95% CI 1.10-1.17], P = 3.2×10⁻¹⁴. This was larger than the same model fitted in the obese analysis where the OR = 1.06 [95% CI 1.05-1.08], P = 2.2×10⁻¹⁶. This study provides evidence that stratification of type 2 diabetes cases by BMI may help identify additional risk variants and that lean cases may have a stronger genetic predisposition to type 2 diabetes.

How to cite this publication

John R. B. Perry, Benjamin F. Voight, Loïc Yengo, Najaf Amin, Josée Dupuis, Martha Ganser, Harald Grallert, Pau Navarro, Man Li, Lu Qi, Valgerður Steinthórsdóttir, Robert A. Scott, Peter Almgren, Dan E. Arking, Yurii S. Aulchenko, Beverley Balkau, Rafn Benediktsson, Richard N. Bergman, Eric Boerwinkle, Lori L. Bonnycastle, Noël P. Burtt, Harry Campbell, G. Charpentier, Francis S. Collins, Christian Gieger, Todd J. Green, Samy Hadjadj, Andrew T. Hattersley, Christian Herder, Albert Hofman, Andrew D. Johnson, Anna Köttgen, Peter Kraft, Yann Labrune, Claudia Langenberg, Alisa K. Manning, Karen L. Mohlke, Andrew P. Morris, Ben A. Oostra, James S. Pankow, Ann-Kristin Petersen, Peter P. Pramstaller, Inga Prokopenko, Wolfgang Rathmann, W Rayner, Michael Roden, Igor Rudan, Denis Rybin, Laura J. Scott, Gunnar Sigurðsson, Robert Sladek, Guðmar Þorleifsson, Unnur Þorsteinsdóttir, Jaakko Tuomilehto, André G. Uitterlinden, Sidonie Vivequin, Michael N. Weedon, Alan F. Wright, Frank B Hu, Thomas Illig, Linda Kao, James B. Meigs, James F. Wilson, Kāri Stefánsson, Cornelia M. van Duijn, David M. Altschuler, Andrew D. Morris, Michael Boehnke, Mark I. McCarthy, Philippe Froguel, Nicholas J. Wareham, Leif Groop, Timothy M. Frayling, Stéphane Cauchi (2012). Stratifying Type 2 Diabetes Cases by BMI Identifies Genetic Risk Variants in LAMA1 and Enrichment for Risk Variants in Lean Compared to Obese Cases. , 8(5), DOI: https://doi.org/10.1371/journal.pgen.1002741.

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

74

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1371/journal.pgen.1002741

Join Research Community

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

Get Free Access