ReviewFrontiers in endocrinology2015
Connecting SNPs in Diabetes: A Spatial Analysis of Meta-GWAS Loci.
Review in Frontiers in endocrinology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Enlightening the molecular mechanisms of type 2 diabetes with a novel pathway clustering and pathway subnetwork approach.Turkish journal of biology = Turk biyoloji dergisi · 2022Article
- A Final Frontier in Environment-Genome Interactions? Integrated, Multi-Omic Approaches to Predictions of Non-Communicable Disease Risk.Frontiers in genetics · 2022Review
- Three-dimensional genome: developmental technologies and applications in precision medicine.Journal of human genetics · 2020Article
- Machine Learning SNP Based Prediction for Precision Medicine.Frontiers in genetics · 2019Review
- Sex-specific epigenetic mediators between early life social disadvantage and adulthood BMI.Epigenomics · 2018Article
- Precision Nutrition: A Review of Personalized Nutritional Approaches for the Prevention and Management of Metabolic Syndrome.Nutrients · 2017Review
- A potential role for genome structure in the translation of mechanical force during immune cell development.Nucleus (Austin, Tex.) · 2016Review
- Association of Family History of Type 2 Diabetes with Prostate Cancer: A National Cohort Study.Frontiers in oncology · 2016Article
- Epigenetics of Aging and Alzheimer's Disease: Implications for Pharmacogenomics and Drug Response.International journal of molecular sciences · 2015Review
- Article
Corrections and comments
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Authors and funding
2 authors.
Funding
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Abstract
Meta-analyses of genome-wide association studies (GWAS) have improved our understanding of the genetic foundations of a number of diseases, including diabetes. However, single nucleotide polymorphisms (SNPs) that are identified by GWAS, especially those that fall outside of gene regions, do not always clearly link to the underlying biology. Despite this, these SNPs have often been validated through re-sequencing efforts as not just tag SNPs, but as causative SNPs, and so must play a role in disease development or progression. In this study, we show how the 3D genome (spatial connections) and trans-expression Quantitative Trait Loci connect diabetes loci from different GWAS meta-analyses, informing the backbone of regulatory networks. Our findings include a three-way functional-spatial connection between the TM6SF2, CTRB1-BCAR1, and CELSR2-PSRC1 loci (rs201189528, rs7202844, and rs7202844, respectively) connected through the KCNIP3 and BCAR1/BCAR3 loci, respectively. These spatial hubs serve as an example of how loci in genes with little biological connection to disease come together to contribute to the diabetes phenotype.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.