SNP eQTL status and eQTL density in the adjacent region of the SNP are associated with its statistical significance in GWA studies
Abstract Background Over the relatively short history of Genome Wide Association Studies (GWASs), hundreds of GWASs have been published and thousands of disease risk-associated SNPs have been identified. Summary statistics from the conducted GWASs are often available and can be used to identify SNP...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2019-11-01
|
| Series: | BMC Genetics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12863-019-0786-0 |
| _version_ | 1817987515184840704 |
|---|---|
| author | Ivan Gorlov Xiangjun Xiao Maureen Mayes Olga Gorlova Christopher Amos |
| author_facet | Ivan Gorlov Xiangjun Xiao Maureen Mayes Olga Gorlova Christopher Amos |
| author_sort | Ivan Gorlov |
| collection | DOAJ |
| description | Abstract Background Over the relatively short history of Genome Wide Association Studies (GWASs), hundreds of GWASs have been published and thousands of disease risk-associated SNPs have been identified. Summary statistics from the conducted GWASs are often available and can be used to identify SNP features associated with the level of GWAS statistical significance. Those features could be used to select SNPs from gray zones (SNPs that are nominally significant but do not reach the genome-wide level of significance) for targeted analyses. Methods We used summary statistics from recently published breast and lung cancer and scleroderma GWASs to explore the association between the level of the GWAS statistical significance and the expression quantitative trait loci (eQTL) status of the SNP. Data from the Genotype-Tissue Expression Project (GTEx) were used to identify eQTL SNPs. Results We found that SNPs reported as eQTLs were more significant in GWAS (higher -log10p) regardless of the tissue specificity of the eQTL. Pan-tissue eQTLs (those reported as eQTLs in multiple tissues) tended to be more significant in the GWAS compared to those reported as eQTL in only one tissue type. eQTL density in the ±5 kb adjacent region of a given SNP was also positively associated with the level of GWAS statistical significance regardless of the eQTL status of the SNP. We found that SNPs located in the regions of high eQTL density were more likely to be located in regulatory elements (transcription factor or miRNA binding sites). When SNPs were stratified by the level of statistical significance, the proportion of eQTLs was positively associated with the mean level of statistical significance in the group. The association curve reaches a plateau around -log10p ≈ 5. The observed associations suggest that quasi-significant SNPs (10− 5 < p < 5 × 10− 8) and SNPs at the genome wide level of statistical significance (p < 5 × 10− 8) may have a similar proportions of risk associated SNPs. Conclusions The results of this study indicate that the SNP’s eQTL status, as well as eQTL density in the adjacent region are positively associated with the level of statistical significance of the SNP in GWAS. |
| first_indexed | 2024-04-14T00:22:25Z |
| format | Article |
| id | doaj.art-02741c0eefc24822926837a2dbfa4557 |
| institution | Directory Open Access Journal |
| issn | 1471-2156 |
| language | English |
| last_indexed | 2024-04-14T00:22:25Z |
| publishDate | 2019-11-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Genetics |
| spelling | doaj.art-02741c0eefc24822926837a2dbfa45572022-12-22T02:22:53ZengBMCBMC Genetics1471-21562019-11-0120111210.1186/s12863-019-0786-0SNP eQTL status and eQTL density in the adjacent region of the SNP are associated with its statistical significance in GWA studiesIvan Gorlov0Xiangjun Xiao1Maureen Mayes2Olga Gorlova3Christopher Amos4The Geisel School of Medicine, Department of Biomedical Data Science, Dartmouth College, HB7936Department of Medicine, Baylor College of MedicineDepartment of Internal Medicine, Division of Rheumatology, University of Texas McGovern Medical SchoolThe Geisel School of Medicine, Department of Biomedical Data Science, Dartmouth College, HB7936Department of Medicine, Baylor College of MedicineAbstract Background Over the relatively short history of Genome Wide Association Studies (GWASs), hundreds of GWASs have been published and thousands of disease risk-associated SNPs have been identified. Summary statistics from the conducted GWASs are often available and can be used to identify SNP features associated with the level of GWAS statistical significance. Those features could be used to select SNPs from gray zones (SNPs that are nominally significant but do not reach the genome-wide level of significance) for targeted analyses. Methods We used summary statistics from recently published breast and lung cancer and scleroderma GWASs to explore the association between the level of the GWAS statistical significance and the expression quantitative trait loci (eQTL) status of the SNP. Data from the Genotype-Tissue Expression Project (GTEx) were used to identify eQTL SNPs. Results We found that SNPs reported as eQTLs were more significant in GWAS (higher -log10p) regardless of the tissue specificity of the eQTL. Pan-tissue eQTLs (those reported as eQTLs in multiple tissues) tended to be more significant in the GWAS compared to those reported as eQTL in only one tissue type. eQTL density in the ±5 kb adjacent region of a given SNP was also positively associated with the level of GWAS statistical significance regardless of the eQTL status of the SNP. We found that SNPs located in the regions of high eQTL density were more likely to be located in regulatory elements (transcription factor or miRNA binding sites). When SNPs were stratified by the level of statistical significance, the proportion of eQTLs was positively associated with the mean level of statistical significance in the group. The association curve reaches a plateau around -log10p ≈ 5. The observed associations suggest that quasi-significant SNPs (10− 5 < p < 5 × 10− 8) and SNPs at the genome wide level of statistical significance (p < 5 × 10− 8) may have a similar proportions of risk associated SNPs. Conclusions The results of this study indicate that the SNP’s eQTL status, as well as eQTL density in the adjacent region are positively associated with the level of statistical significance of the SNP in GWAS.http://link.springer.com/article/10.1186/s12863-019-0786-0Genome wide association studies (GWASs)Expression quantitative trait loci (eQTL)Statistical significanceCancerGene expression |
| spellingShingle | Ivan Gorlov Xiangjun Xiao Maureen Mayes Olga Gorlova Christopher Amos SNP eQTL status and eQTL density in the adjacent region of the SNP are associated with its statistical significance in GWA studies BMC Genetics Genome wide association studies (GWASs) Expression quantitative trait loci (eQTL) Statistical significance Cancer Gene expression |
| title | SNP eQTL status and eQTL density in the adjacent region of the SNP are associated with its statistical significance in GWA studies |
| title_full | SNP eQTL status and eQTL density in the adjacent region of the SNP are associated with its statistical significance in GWA studies |
| title_fullStr | SNP eQTL status and eQTL density in the adjacent region of the SNP are associated with its statistical significance in GWA studies |
| title_full_unstemmed | SNP eQTL status and eQTL density in the adjacent region of the SNP are associated with its statistical significance in GWA studies |
| title_short | SNP eQTL status and eQTL density in the adjacent region of the SNP are associated with its statistical significance in GWA studies |
| title_sort | snp eqtl status and eqtl density in the adjacent region of the snp are associated with its statistical significance in gwa studies |
| topic | Genome wide association studies (GWASs) Expression quantitative trait loci (eQTL) Statistical significance Cancer Gene expression |
| url | http://link.springer.com/article/10.1186/s12863-019-0786-0 |
| work_keys_str_mv | AT ivangorlov snpeqtlstatusandeqtldensityintheadjacentregionofthesnpareassociatedwithitsstatisticalsignificanceingwastudies AT xiangjunxiao snpeqtlstatusandeqtldensityintheadjacentregionofthesnpareassociatedwithitsstatisticalsignificanceingwastudies AT maureenmayes snpeqtlstatusandeqtldensityintheadjacentregionofthesnpareassociatedwithitsstatisticalsignificanceingwastudies AT olgagorlova snpeqtlstatusandeqtldensityintheadjacentregionofthesnpareassociatedwithitsstatisticalsignificanceingwastudies AT christopheramos snpeqtlstatusandeqtldensityintheadjacentregionofthesnpareassociatedwithitsstatisticalsignificanceingwastudies |