Format

Send to

Choose Destination
Genome Med. 2018 Jan 29;10(1):7. doi: 10.1186/s13073-018-0513-x.

An integrative functional genomics framework for effective identification of novel regulatory variants in genome-phenome studies.

Zhao J1, Cheng F2,3, Jia P1, Cox N4,5, Denny JC5,6, Zhao Z7,8.

Author information

1
Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin St. Suite 820, Houston, TX, 77030, USA.
2
Center for Cancer Systems Biology and Department of Cancer Biology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, 02215, USA.
3
Center for Complex Networks Research, Northeastern University, Boston, MA, 02215, USA.
4
Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA.
5
Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA.
6
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, 37232, USA.
7
Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin St. Suite 820, Houston, TX, 77030, USA. zhongming.zhao@uth.tmc.edu.
8
Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA. zhongming.zhao@uth.tmc.edu.

Abstract

BACKGROUND:

Genome-phenome studies have identified thousands of variants that are statistically associated with disease or traits; however, their functional roles are largely unclear. A comprehensive investigation of regulatory mechanisms and the gene regulatory networks between phenome-wide association study (PheWAS) and genome-wide association study (GWAS) is needed to identify novel regulatory variants contributing to risk for human diseases.

METHODS:

In this study, we developed an integrative functional genomics framework that maps 215,107 significant single nucleotide polymorphism (SNP) traits generated from the PheWAS Catalog and 28,870 genome-wide significant SNP traits collected from the GWAS Catalog into a global human genome regulatory map via incorporating various functional annotation data, including transcription factor (TF)-based motifs, promoters, enhancers, and expression quantitative trait loci (eQTLs) generated from four major functional genomics databases: FANTOM5, ENCODE, NIH Roadmap, and Genotype-Tissue Expression (GTEx). In addition, we performed a tissue-specific regulatory circuit analysis through the integration of the identified regulatory variants and tissue-specific gene expression profiles in 7051 samples across 32 tissues from GTEx.

RESULTS:

We found that the disease-associated loci in both the PheWAS and GWAS Catalogs were significantly enriched with functional SNPs. The integration of functional annotations significantly improved the power of detecting novel associations in PheWAS, through which we found a number of functional associations with strong regulatory evidence in the PheWAS Catalog. Finally, we constructed tissue-specific regulatory circuits for several complex traits: mental diseases, autoimmune diseases, and cancer, via exploring tissue-specific TF-promoter/enhancer-target gene interaction networks. We uncovered several promising tissue-specific regulatory TFs or genes for Alzheimer's disease (e.g. ZIC1 and STX1B) and asthma (e.g. CSF3 and IL1RL1).

CONCLUSIONS:

This study offers powerful tools for exploring the functional consequences of variants generated from genome-phenome association studies in terms of their mechanisms on affecting multiple complex diseases and traits.

KEYWORDS:

Enhancer; Genome-wide association study (GWAS); Human disease; Phenome-wide association study (PheWAS); Promoter; Regulatory variants

PMID:
29378629
PMCID:
PMC5789733
DOI:
10.1186/s13073-018-0513-x
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for BioMed Central Icon for PubMed Central
Loading ...
Support Center