Systematic Localization of Common Disease-Associated Variation in Regulatory DNA

By Matthew T. Maurano, R. Humbert, Eric Rynes, Robert E. Thurman, E. Haugen, Hao Wang, Alex P. Reynolds, R. Sandstrom, H. Qu, J. Brody and 22 more. Science, 2012

3,679 citations recorded by the source corpus.

Predictions of Genetic Disease Many genome-wide association studies (GWAS) have identified loci and variants associated with disease, but the ability to predict disease on the basis of these genetic variants remains small. Maurano et al. (p. 1190; see the Perspective by Schadt and Chang; see the cover) characterize the location of GWAS variants in the genome with respect to their proximity to regulatory DNA [marked by deoxyribonuclease I (DNase I) hypersensitive sites] by tissue type, disease, and enrichments in physiologically relevant transcription factor binding sites and networks. They found many noncoding disease associations in regulatory DNA, indicating tissue and developmental-specific regulatory roles for many common genetic variants and thus enabling links to be made between gene regulation and adult-onset disease. Genetic variants that have been associated with diseases are concentrated in regulatory regions of the genome. Genome-wide association studies have identified many noncoding variants associated with common diseases and traits. We show that these variants are concentrated in regulatory DNA marked by deoxyribonuclease I (DNase I) hypersensitive sites (DHSs). Eighty-eight percent of such DHSs are active during fetal development and are enriched in variants associated with gestational exposure–related phenotypes. We identified distant gene targets for hundreds of variant-containing DHSs that may explain phenotype associations. Disease-associated variants systematically perturb transcription factor recognition sequences, frequently alter allelic chromatin states, and form regulatory networks. We also demonstrated tissue-selective enrichment of more weakly disease-associated variants within DHSs and the de novo identification of pathogenic cell types for Crohn’s disease, multiple sclerosis, and an electrocardiogram trait, without prior knowledge of physiological mechanisms. Our results suggest pervasive involvement of regulatory DNA variation in common human disease and provide pathogenic insights into diverse disorders.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/98ac9cc09fd81741408ad5eba2c951bd86006ffc

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Citations in the corpus

A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease (2015, positive): “This phenomenon has previously been reported for other diseases and traits 48 and can guide candidate gene nomination and the design of future functional studies.”
Partitioning heritability by functional annotation using genome-wide association summary statistics (2015, methodology): “However, many current approaches that leverage functional information [3, 4] and GWAS data to inform disease biology use only SNPs in genome-wide significant loci [5–8], assume only one causal SNP per locus [9], or do not account for linkage disequilibrium (LD) [10].”
An expanded view of complex traits: from polygenic to omnigenic (2017, background): “A second surprise was that, in contrast to Mendelian diseases—which are largely caused by protein-coding changes (Botstein and Risch, 2003)—complex traits are mainly driven by noncoding variants that presumably affect gene regulation (Pickrell, 2014; Welter et al., 2014; Li et al., 2016).”
Enhanced Regulatory Sequence Prediction Using Gapped k-mer Features (2014, background): “Genetic variation in regulatory elements is increasingly thought to play a significant role in the etiology and heritability of common diseases, and surveys of Genome Wide Association Studies have highlighted the preponderance of significant variants in regulatory DNA [1,2].”
Sequential regulatory activity prediction across chromosomes with convolutional neural networks (2017, background): “Numerous lines of evidence suggest that many noncoding variants influence traits by changing gene expression (Finucane et al. 2015; O'Connor et al. 2017; Albert and Kruglyak 2015; Maurano et al. 2012).”
Beyond GWASs: illuminating the dark road from association to function. (2013, positive): “showed that GWAS signals were overrepresented in regulatory regions by assessing the frequency of variant occurrence in DHSs generated by the ENCODE and NIH Roadmap Epigenomics consortia.(45) Furthermore, assessment of putative functional variants at the 17q24.”
Joint analysis of functional genomic data and genome-wide association studies of 18 human traits (2013, background): “Further, in some cases, SNPs associated with a trait are enriched in gene regulatory regions in specific cell types [Cowper-Sal lari et al., 2012; Ernst et al., 2011; Gerasimova et al., 2013; Global Lipids Genetics Consortium et al., 2013; Hnisz et al., 2013; Karczewski et al., 2013; Maurano et al.,”