Publication: Examination of previously identified associations within the Genetic Analysis Workshop 19 data
Issued Date
2016-01-01
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17536561
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2-s2.0-85015984653
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Mahidol University
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SCOPUS
Bibliographic Citation
BMC Proceedings. Vol.10, (2016)
Suggested Citation
Richard A.J. Howey, Jakris Eu-Ahsunthornwattana, Rebecca Darlay, Heather J. Cordell Examination of previously identified associations within the Genetic Analysis Workshop 19 data. BMC Proceedings. Vol.10, (2016). doi:10.1186/s12919-016-0012-2 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/43147
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Title
Examination of previously identified associations within the Genetic Analysis Workshop 19 data
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Abstract
© 2016 The Author(s). We investigate the possible replication of "known" associated single-nucleotide polymorphisms (SNPs) with blood pressure and expression phenotypes. Previous studies have provided a list of 95 SNPs thought to be associated with blood pressure phenotypes, of which 44 were present in the Genetic Analysis Workshop 19 (GAW19) family-imputed genome-wide association studies (GWAS) data and 4 in the GAW19 unrelateds sequence data. Using only the real (not simulated) GAW19 data, we show through the use of statistical tests that account for family relatedness, using FaST-LMM (Factored Spectrally Transformed Linear Mixed Model), that none of our candidate SNPs yields a significant p value. Furthermore, a study of epistasis, aiming to detect statistical interactions between loci with respect to their association with transcription levels has provided a list of 30 associated interacting SNP pairs, of which 13 are present in the GAW19 family GWAS and expression data. We show for this set of results, using the program GEMMA (genome-wide efficient mixed-model analysis) to account for family relatedness, that there is evidence of replication within the real GAW19 data. Two individual SNP pairs reach significance, and the set of remaining results give a combined p value of 0.017 that at least 1 of these remaining SNP pairs interacts to influence an expression phenotype.