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Exploring the interaction between SNP genotype and postmenopausal hormone therapy effects on stroke risk

Ying Huang1, Dennis G Ballinger2, Renee Stokowski3, Erica Beilharz2, Jennifer G Robinson4, Simin Liu5, Randal D Robinson6, Victor W Henderson7, Jacques E Rossouw8 and Ross L Prentice1*

Author Affiliations

1 Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109, USA

2 Complete Genomics, Inc, 2071 Stierlin Court, Mountain View, CA 94043, USA

3 Aria Diagnostics, 5945 Optical Court, San Jose, CA 95138, USA

4 Departments of Epidemiology and Medicine, University of Iowa, 200 Medicine Admin. Bldg, Iowa City, IA 52242, USA

5 School of Public Health, University of California at Los Angeles, 650 Charles E Young Dr. South, Los Angeles, CA 90095, USA

6 School of Medicine, UT Heath Science Center, 7703 Floyd Curl Drive, San Antonio, TX 78229, USA

7 Health Research & Policy (Epidemiology) and Neurology & Neurological Sciences, Stanford School of Medicine, 450 Serra Mall, Stanford, CA 94305, USA

8 Women's Health Initiative Project Office, National Heart, Lung, and Blood Institute, 6701 Rockledge Drive, Bethesda, MD 20892, USA

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Genome Medicine 2012, 4:57  doi:10.1186/gm358

Published: 13 July 2012

Abstract

Background

Genome-wide association studies have identified several genomic regions that are associated with stroke risk, but these provide an explanation for only a small fraction of familial stroke aggregation. Genotype by environment interactions may contribute further to such an explanation. The Women's Health Initiative (WHI) clinical trial found increased stroke risk with postmenopausal hormone therapy (HT) and provides an efficient setting for evaluating genotype-HT interaction on stroke risk.

Methods

We examined HT by genotype interactions for 392 SNPs selected from candidate gene studies, and 2,371 SNPs associated with changes in blood protein concentrations after hormone therapy, in analyses that included 2,045 postmenopausal women who developed stroke during WHI clinical trial and observational study follow-up and one-to-one matched controls. A two-stage procedure was implemented where SNPs passing the first stage screening based on marginal association with stroke risk were tested in the second stage for interaction with HT using case-only analysis.

Results

The two-stage procedure identified two SNPs, rs2154299 and rs12194855, in the coagulation factor XIII subunit A (F13A1) region and two SNPs, rs630431 and rs560892, in the proprotein convertase subtilisin kexin 9 (PCSK9) region, with an estimated false discovery rate <0.05 based on interaction tests. Further analyses showed significant stroke risk interaction between these F13A1 SNPs and estrogen plus progestin (E+P) treatment for ischemic stroke and for ischemic and hemorrhagic stroke combined, and suggested interactions between PCSK9 SNPs with either E+P or estrogen-alone treatment.

Conclusions

Genotype by environment interaction information may help to define genomic regions relevant to stroke risk. Two-stage analysis among postmenopausal women generates novel hypotheses concerning the F13A1 and PCSK9 genomic regions and the effects of hormonal exposures on postmenopausal stroke risk for subsequent independent validation.