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Discovery and validation of sub-threshold genome-wide association study loci using epigenomic signatures.

Wang X, Tucker NR, Rizki G, Mills R, Krijger PH, de Wit E, Subramanian V, Bartell E, Nguyen XX, Ye J, Leyton-Mange J, Dolmatova EV, van der Harst P, de Laat W, Ellinor PT, Newton-Cheh C, Milan DJ, Kellis M, Boyer LA - Elife (2016)

Bottom Line: We apply functional criteria to identify loci associated with QT interval that do not meet genome-wide significance and are missed by existing studies.We experimentally validate the molecular, gene-regulatory, cellular and organismal phenotypes of these sub-threshold loci, demonstrating that most sub-threshold loci have regulatory consequences and that genetic perturbation of nearby genes causes cardiac phenotypes in mouse.Our work provides a general approach for improving the detection of novel loci associated with complex human traits.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Massachusetts Institute of Technology, Cambridge, United States.

ABSTRACT
Genetic variants identified by genome-wide association studies explain only a modest proportion of heritability, suggesting that meaningful associations lie 'hidden' below current thresholds. Here, we integrate information from association studies with epigenomic maps to demonstrate that enhancers significantly overlap known loci associated with the cardiac QT interval and QRS duration. We apply functional criteria to identify loci associated with QT interval that do not meet genome-wide significance and are missed by existing studies. We demonstrate that these 'sub-threshold' signals represent novel loci, and that epigenomic maps are effective at discriminating true biological signals from noise. We experimentally validate the molecular, gene-regulatory, cellular and organismal phenotypes of these sub-threshold loci, demonstrating that most sub-threshold loci have regulatory consequences and that genetic perturbation of nearby genes causes cardiac phenotypes in mouse. Our work provides a general approach for improving the detection of novel loci associated with complex human traits.

No MeSH data available.


Related in: MedlinePlus

DOI:http://dx.doi.org/10.7554/eLife.10557.025
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fig8: DOI:http://dx.doi.org/10.7554/eLife.10557.025

Mentions: However, to address the reviewers’ concern regarding the additional GWS loci, we have performed the same enrichment analysis after also excluding the held-out GWS and any SNPs within +/- 1Mb. The plot is included in Author response image 2, and we observe the same enrichment pattern as in Figure 3.10.7554/eLife.10557.025Author response image 2.


Discovery and validation of sub-threshold genome-wide association study loci using epigenomic signatures.

Wang X, Tucker NR, Rizki G, Mills R, Krijger PH, de Wit E, Subramanian V, Bartell E, Nguyen XX, Ye J, Leyton-Mange J, Dolmatova EV, van der Harst P, de Laat W, Ellinor PT, Newton-Cheh C, Milan DJ, Kellis M, Boyer LA - Elife (2016)

DOI:http://dx.doi.org/10.7554/eLife.10557.025
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4862755&req=5

fig8: DOI:http://dx.doi.org/10.7554/eLife.10557.025
Mentions: However, to address the reviewers’ concern regarding the additional GWS loci, we have performed the same enrichment analysis after also excluding the held-out GWS and any SNPs within +/- 1Mb. The plot is included in Author response image 2, and we observe the same enrichment pattern as in Figure 3.10.7554/eLife.10557.025Author response image 2.

Bottom Line: We apply functional criteria to identify loci associated with QT interval that do not meet genome-wide significance and are missed by existing studies.We experimentally validate the molecular, gene-regulatory, cellular and organismal phenotypes of these sub-threshold loci, demonstrating that most sub-threshold loci have regulatory consequences and that genetic perturbation of nearby genes causes cardiac phenotypes in mouse.Our work provides a general approach for improving the detection of novel loci associated with complex human traits.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Massachusetts Institute of Technology, Cambridge, United States.

ABSTRACT
Genetic variants identified by genome-wide association studies explain only a modest proportion of heritability, suggesting that meaningful associations lie 'hidden' below current thresholds. Here, we integrate information from association studies with epigenomic maps to demonstrate that enhancers significantly overlap known loci associated with the cardiac QT interval and QRS duration. We apply functional criteria to identify loci associated with QT interval that do not meet genome-wide significance and are missed by existing studies. We demonstrate that these 'sub-threshold' signals represent novel loci, and that epigenomic maps are effective at discriminating true biological signals from noise. We experimentally validate the molecular, gene-regulatory, cellular and organismal phenotypes of these sub-threshold loci, demonstrating that most sub-threshold loci have regulatory consequences and that genetic perturbation of nearby genes causes cardiac phenotypes in mouse. Our work provides a general approach for improving the detection of novel loci associated with complex human traits.

No MeSH data available.


Related in: MedlinePlus