ArticleGenetics2018
Integration of Enhancer-Promoter Interactions with GWAS Summary Results Identifies Novel Schizophrenia-Associated Genes and Pathways.
Article in Genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
23 citing papers in PubMed.
- Multi-Omic Insight Into the Molecular Networks of Mitochondrial Dysfunction in the Pathogenesis of Schizophrenia.Schizophrenia bulletin · 2026Article
- RetroFun-RVS: A Retrospective Family-Based Framework for Rare Variant Analysis Incorporating Functional Annotations.Genetic epidemiology · 2025Article
- EPI-Trans: an effective transformer-based deep learning model for enhancer promoter interaction prediction.BMC bioinformatics · 2024Article
- Integrating 3D genomic and epigenomic data to enhance target gene discovery and drug repurposing in transcriptome-wide association studies.Nature communications · 2022Article
- Cis-regulatory hubs: a new 3D model of complex disease genetics with an application to schizophrenia.Life science alliance · 2022Article
- eSCAN: scan regulatory regions for aggregate association testing using whole-genome sequencing data.Briefings in bioinformatics · 2022Article
- InTACT: An adaptive and powerful framework for joint-tissue transcriptome-wide association studies.Genetic epidemiology · 2021Article
- Quantitative spatial and temporal assessment of regulatory element activity in zebrafish.eLife · 2021Article
- An integrative multiomics analysis identifies putative causal genes for COVID-19 severity.Genetics in medicine : official journal of the American College of Medical Genetics · 2021Article
- Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles.Briefings in bioinformatics · 2021Article
- A gene-level methylome-wide association analysis identifies novel Alzheimer's disease genes.Bioinformatics (Oxford, England) · 2021Article
- Mouse Genetic Reference Populations: Cellular Platforms for Integrative Systems Genetics.Trends in genetics : TIG · 2021Review
- Incorporating multiple sets of eQTL weights into gene-by-environment interaction analysis identifies novel susceptibility loci for pancreatic cancer.Genetic epidemiology · 2020Article
- Unravelling the complex genetics of common kidney diseases: from variants to mechanisms.Nature reviews. Nephrology · 2020Review
- Functional genomic approaches to elucidate the role of enhancers during development.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- Integrating DNA sequencing and transcriptomic data for association analyses of low-frequency variants and lipid traits.Human molecular genetics · 2020Article
- Genome-Wide Search for SNP Interactions in GWAS Data: Algorithm, Feasibility, Replication Using Schizophrenia Datasets.Frontiers in genetics · 2020Article
- Environment and Gene Association With Obesity and Their Impact on Neurodegenerative and Neurodevelopmental Diseases.Frontiers in neuroscience · 2020Review
- Article
- Integration of methylation QTL and enhancer-target gene maps with schizophrenia GWAS summary results identifies novel genes.Bioinformatics (Oxford, England) · 2019Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
It remains challenging to boost statistical power of genome-wide association studies (GWASs) to identify more risk variants or loci that can account for "missing heritability." Furthermore, since most identified variants are not in gene-coding regions, a biological interpretation of their function is largely lacking. On the other hand, recent biotechnological advances have made it feasible to experimentally measure the three-dimensional organization of the genome, including enhancer-promoter interactions in high resolutions. Due to the well-known critical roles of enhancer-promoter interactions in regulating gene expression programs, such data have been applied to link GWAS risk variants to their putative target genes, gaining insights into underlying biological mechanisms. However, their direct use in GWAS association testing is yet to be exploited. Here we propose integrating enhancer-promoter interactions into GWAS association analysis to both boost statistical power and enhance interpretability. We demonstrate that through an application to two large-scale schizophrenia (SCZ) GWAS summary data sets, the proposed method could identify some novel SCZ-associated genes and pathways (containing no significant SNPs). For example, after the Bonferroni correction, for the larger SCZ data set with 36,989 cases and 113,075 controls, our method applied to the gene body and enhancer regions identified 27 novel genes and 11 novel KEGG pathways to be significant, all missed by the transcriptome-wide association study (TWAS) approach. We conclude that our proposed method is potentially useful and is complementary to TWAS and other standard gene- and pathway-based methods.
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Registered trials
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