Limits...
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

High density of fetal heart DNase I hypersensitivity reads in LV enhancers is robustly informative for identifying enriched sets of sub-threshold loci.Top: Enrichment of DHS reads in GWAS enhancers. Middle: Example comparison of sub-threshold locus enrichment in active LV enhancers vs. active LV enhancers with high DHS read density. Bottom: Y-axis of graphs corresponds to fold enrichment of sub-threshold loci in enhancers taken at three p-value cutoffs (10-4, 10-5 and 10-6). X-axis represents enrichments plotted for different subsets of enhancers chosen by varying DHS read density cutoffs.DOI:http://dx.doi.org/10.7554/eLife.10557.009
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4862755&req=5

fig3s1: High density of fetal heart DNase I hypersensitivity reads in LV enhancers is robustly informative for identifying enriched sets of sub-threshold loci.Top: Enrichment of DHS reads in GWAS enhancers. Middle: Example comparison of sub-threshold locus enrichment in active LV enhancers vs. active LV enhancers with high DHS read density. Bottom: Y-axis of graphs corresponds to fold enrichment of sub-threshold loci in enhancers taken at three p-value cutoffs (10-4, 10-5 and 10-6). X-axis represents enrichments plotted for different subsets of enhancers chosen by varying DHS read density cutoffs.DOI:http://dx.doi.org/10.7554/eLife.10557.009

Mentions: Current GWAS loci collectively explain only a small fraction of the estimated heritability of a complex trait in part due to strict Bonferroni thresholds for multiple hypothesis testing (p<5x10-8) and the limited statistical power of existing studies to discover variants with modest effect sizes (Maher, 2008; Yang et al., 2011). We hypothesized that knowledge of the genomic properties associated with existing GWAS loci can guide the search for additional genetic signals that cannot be detected without increasing GWAS cohort sizes, and that these loci with weaker 'sub-threshold' p-values (i.e. 0.05>p>5x10-8) might reveal novel genes and biological pathways that contribute to complex disease. To test this idea, we used SNP summary statistics from the Arking et al. (2014) QT interval GWAS study we had earlier held out as a validation dataset (Arking et al., 2014). These summary statistics include the 112 QT/QRS loci identified by prior GWASs (red dots, bottom,Figure 3), as well as loci that reach genome-wide significance in the larger meta-analysis cohort but were not discovered in any previous GWAS (and therefore were not included in the 112 QT/QRS loci used for enrichment analyses above, gold dots, bottom,Figure 3). We observed that active LV enhancers are strongly enriched for loci harboring SNPs with p-values between 1x10-4 and 5x10-8 (Figure 3a, black line). Furthermore, the combination of functional features identified for above-threshold QT/QRS enhancers (Figure 2) substantially improves sub-threshold locus enrichment across a wide range of p-value thresholds (Figure 3a, colored lines, Figure 3—figure supplement 1).10.7554/eLife.10557.008Figure 3.Cardiac enhancers harbor additional sub-threshold QT loci.


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)

High density of fetal heart DNase I hypersensitivity reads in LV enhancers is robustly informative for identifying enriched sets of sub-threshold loci.Top: Enrichment of DHS reads in GWAS enhancers. Middle: Example comparison of sub-threshold locus enrichment in active LV enhancers vs. active LV enhancers with high DHS read density. Bottom: Y-axis of graphs corresponds to fold enrichment of sub-threshold loci in enhancers taken at three p-value cutoffs (10-4, 10-5 and 10-6). X-axis represents enrichments plotted for different subsets of enhancers chosen by varying DHS read density cutoffs.DOI:http://dx.doi.org/10.7554/eLife.10557.009
© Copyright Policy
Related In: Results  -  Collection

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

fig3s1: High density of fetal heart DNase I hypersensitivity reads in LV enhancers is robustly informative for identifying enriched sets of sub-threshold loci.Top: Enrichment of DHS reads in GWAS enhancers. Middle: Example comparison of sub-threshold locus enrichment in active LV enhancers vs. active LV enhancers with high DHS read density. Bottom: Y-axis of graphs corresponds to fold enrichment of sub-threshold loci in enhancers taken at three p-value cutoffs (10-4, 10-5 and 10-6). X-axis represents enrichments plotted for different subsets of enhancers chosen by varying DHS read density cutoffs.DOI:http://dx.doi.org/10.7554/eLife.10557.009
Mentions: Current GWAS loci collectively explain only a small fraction of the estimated heritability of a complex trait in part due to strict Bonferroni thresholds for multiple hypothesis testing (p<5x10-8) and the limited statistical power of existing studies to discover variants with modest effect sizes (Maher, 2008; Yang et al., 2011). We hypothesized that knowledge of the genomic properties associated with existing GWAS loci can guide the search for additional genetic signals that cannot be detected without increasing GWAS cohort sizes, and that these loci with weaker 'sub-threshold' p-values (i.e. 0.05>p>5x10-8) might reveal novel genes and biological pathways that contribute to complex disease. To test this idea, we used SNP summary statistics from the Arking et al. (2014) QT interval GWAS study we had earlier held out as a validation dataset (Arking et al., 2014). These summary statistics include the 112 QT/QRS loci identified by prior GWASs (red dots, bottom,Figure 3), as well as loci that reach genome-wide significance in the larger meta-analysis cohort but were not discovered in any previous GWAS (and therefore were not included in the 112 QT/QRS loci used for enrichment analyses above, gold dots, bottom,Figure 3). We observed that active LV enhancers are strongly enriched for loci harboring SNPs with p-values between 1x10-4 and 5x10-8 (Figure 3a, black line). Furthermore, the combination of functional features identified for above-threshold QT/QRS enhancers (Figure 2) substantially improves sub-threshold locus enrichment across a wide range of p-value thresholds (Figure 3a, colored lines, Figure 3—figure supplement 1).10.7554/eLife.10557.008Figure 3.Cardiac enhancers harbor additional sub-threshold QT loci.

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