ArticleNucleic acids research2016
Explaining the disease phenotype of intergenic SNP through predicted long range regulation.
Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Avirulence genes identified through linkage mapping and region-specific association studies in the wheat leaf rust pathogen Puccinia triticina.BMC genomics · 2026Article
- A prevalent disease-associated SNP in the humanNAR molecular medicine · 2026Article
- Characterisation of the role played by ELMO1, GPR141 and the intergenic polymorphism rs918980 in Fuchs' dystrophy in the Indian population.FEBS open bio · 2025Article
- Association of the Immunity Genes with Type 1 Diabetes Mellitus.Current diabetes reviews · 2025Review
- Identification of Novel Genetic Loci Affecting Age at Onset of Parkinson's Disease: A Genome-wide Association Study.Movement disorders : official journal of the Movement Disorder Society · 2025Article
- Unravelling the Oral-Gut Axis: Interconnection Between Periodontitis and Inflammatory Bowel Disease, Current Challenges, and Future Perspective.Journal of Crohn's & colitis · 2024Review
- A Multi-Dimensional Approach to Map Disease Relationships Challenges Classical Disease Views.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Why does the X chromosome lag behind autosomes in GWAS findings?PLoS genetics · 2023Article
- Disrupted long-range gene regulations elucidate shared tissue-specific mechanisms of neuropsychiatric disorders.Molecular psychiatry · 2022Article
- Review
- Intergenic SNPs in Obstructive Sleep Apnea Syndrome: Revealing Metabolic, Oxidative Stress and Immune-Related Pathways.Diagnostics (Basel, Switzerland) · 2021Article
- A global overview of genetically interpretable multimorbidities among common diseases in the UK Biobank.Genome medicine · 2021Article
- Combining artificial intelligence: deep learning with Hi-C data to predict the functional effects of non-coding variants.Bioinformatics (Oxford, England) · 2021Article
- The Use of Whole Genome and Exome Sequencing for Newborn Screening: Challenges and Opportunities for Population Health.Frontiers in pediatrics · 2021Review
- Genetic and expression variations of cell cycle pathway genes in brain tumor patients.Bioscience reports · 2020Article
- Cancer-specific expression quantitative loci are affected by expression dysregulation.Briefings in bioinformatics · 2020Article
- Genome-Wide Association Study and Fine Mapping Reveals Candidate Genes for Birth Weight of Yorkshire and Landrace Pigs.Frontiers in genetics · 2020Article
- HPO-Shuffle: an associated gene prioritization strategy and its application in drug repurposing for the treatment of canine epilepsy.Bioscience reports · 2019Article
- Genetic determinants of gut microbiota composition and bile acid profiles in mice.PLoS genetics · 2019Article
- Impact of Long Non-Coding RNAJournal of clinical medicine · 2019Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Thousands of disease-associated SNPs (daSNPs) are located in intergenic regions (IGR), making it difficult to understand their association with disease phenotypes. Recent analysis found that non-coding daSNPs were frequently located in or approximate to regulatory elements, inspiring us to try to explain the disease phenotypes of IGR daSNPs through nearby regulatory sequences. Hence, after locating the nearest distal regulatory element (DRE) to a given IGR daSNP, we applied a computational method named INTREPID to predict the target genes regulated by the DRE, and then investigated their functional relevance to the IGR daSNP's disease phenotypes. 36.8% of all IGR daSNP-disease phenotype associations investigated were possibly explainable through the predicted target genes, which were enriched with, were functionally relevant to, or consisted of the corresponding disease genes. This proportion could be further increased to 60.5% if the LD SNPs of daSNPs were also considered. Furthermore, the predicted SNP-target gene pairs were enriched with known eQTL/mQTL SNP-gene relationships. Overall, it's likely that IGR daSNPs may contribute to disease phenotypes by interfering with the regulatory function of their nearby DREs and causing abnormal expression of disease genes.
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