PT  - JOURNAL ARTICLE
AU  - Haiman, Christopher A.
AU  - Fesinmeyer, Megan D.
AU  - Spencer, Kylee L.
AU  - Bůžková, Petra
AU  - Voruganti, V. Saroja
AU  - Wan, Peggy
AU  - Haessler, Jeff
AU  - Franceschini, Nora
AU  - Monroe, Kristine R.
AU  - Howard, Barbara V.
AU  - Jackson, Rebecca D.
AU  - Florez, Jose C.
AU  - Kolonel, Laurence N.
AU  - Buyske, Steven
AU  - Goodloe, Robert J.
AU  - Liu, Simin
AU  - Manson, JoAnn E.
AU  - Meigs, James B.
AU  - Waters, Kevin
AU  - Mukamal, Kenneth J.
AU  - Pendergrass, Sarah A.
AU  - Shrader, Peter
AU  - Wilkens, Lynne R.
AU  - Hindorff, Lucia A.
AU  - Ambite, Jose Luis
AU  - North, Kari E.
AU  - Peters, Ulrike
AU  - Crawford, Dana C.
AU  - Le Marchand, Loic
AU  - Pankow, James S.
TI  - Consistent Directions of Effect for Established Type 2 Diabetes Risk Variants Across Populations
AID  - 10.2337/db11-1296
DP  - 2012 Jun 01
TA  - Diabetes
PG  - 1642--1647
VI  - 61
IP  - 6
4099  - http://diabetes.diabetesjournals.org/content/61/6/1642.short
4100  - http://diabetes.diabetesjournals.org/content/61/6/1642.full
SO  - Diabetes2012 Jun 01; 61
AB  - Common genetic risk variants for type 2 diabetes (T2D) have primarily been identified in populations of European and Asian ancestry. We tested whether the direction of association with 20 T2D risk variants generalizes across six major racial/ethnic groups in the U.S. as part of the Population Architecture using Genomics and Epidemiology Consortium (16,235 diabetes case and 46,122 control subjects of European American, African American, Hispanic, East Asian, American Indian, and Native Hawaiian ancestry). The percentage of positive (odds ratio [OR] >1 for putative risk allele) associations ranged from 69% in American Indians to 100% in European Americans. Of the nine variants where we observed significant heterogeneity of effect by racial/ethnic group (Pheterogeneity < 0.05), eight were positively associated with risk (OR >1) in at least five groups. The marked directional consistency of association observed for most genetic variants across populations implies a shared functional common variant in each region. Fine-mapping of all loci will be required to reveal markers of risk that are important within and across populations.