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Dong, X. C.

Publications and source records attributed to Dong, X. C..

2 recordsLinked to original sources
bioRxiv2019

Mendelian Randomization Analysis Dissects the Relationship between NAFLD, T2D, and Obesity and Provides Implications to Precision Medicine

BackgroundNon-alcoholic fatty liver disease (NAFLD) is epidemiologically correlated with both type 2 diabetes (T2D) and obesity. However, the causal inter-relationships among the three diseases have not been completely investigated.\n\nAimWe aim to explore the causal relationships among the three diseases.\n\nDesign and methodsWe performed a genome-wide association study (GWAS) on fatty liver disease in [~]400,000 UK BioBank samples. Using this data as well as the largest-to-date publicly available summary-level GWAS data, we performed a two-sample bidirectional Mendelian Randomization (MR) analysis. This analysis tested the causal inter-relationship between NAFLD, T2D, and obesity, as well as the association between genetically driven NAFLD (with two well-established SNPs at the PNPLA3 and TM6SF2 loci) and glycemic and lipidemic traits, respectively. Transgenic mice expressing the human PNPLA3 I148I (TghPNPLA3-I148I) and PNPLA3 I148M (TghPNPLA3-I148M) isoforms were used to further validate the causal effects.\n\nResultsWe found that genetically instrumented hepatic steatosis significantly increased the risk for T2D (OR=1.3, 95% CI: [1.2, 1.4], p=8.3e-14) but not the intermediate glycemic phenotypes at the Bonferroni-adjusted level of significance (p<0.002). There was a moderate, but significant causal association between genetically driven hepatic steatosis and decreased risk for BMI ({beta}=- 0.027 SD, 95%CI: [-0.043, -0.01], p=1.3e-4), but an increased risk for WHRadjBMI (Waist-Hip Ratio adjusted for BMI) ({beta}=0.039 SD, 95%CI: [0.023, 0.054], p=8.2e-7), as well as a decreased level for total cholesterol ({beta}=-0.084 SD, 95%CI [-0.13, -0.036], p=6.8e-4), but not triglycerides ({beta}=0.02 SD, 95%CI [-0.023, 0.062], p=0.36). The reverse MR analyses suggested that genetically driven T2D (OR=1.1, 95% CI: [1.0, 1.2], p=1.7e-3), BMI (OR=2.3, 95% CI: [2.0, 2.7], p=1.4e-25) and WHRadjBMI (OR=1.5, 95% CI: [1.3, 1.8], p=1.1e-6) causally increase the NAFLD risk. In the animal study, as compared to the TghPNPLA3-I148I controls, the TghPNPLA3-I148M mice developed higher fasting glucose level and reduced glucose clearance. Meanwhile, the TghPNPLA3-I148M mice demonstrated a reduced body weight, increased central to peripheral fat ratio, decreased circulating total cholesterol as compared to the TghPNPLA3-I148I controls.\n\nConclusionThis large-scale bidirectional MR study suggests that lifelong, genetically driven NAFLD is a causal risk factor for T2D (hence potentially a \"NAFLD-driven T2D\" subtype) and central obesity (or \"NAFLD-driven obesity\" subtype), but protects against overall obesity; while genetically driven T2D, obesity, and central obesity also causally increase the risk of NAFLD, hence a \"metabolic NAFLD\". This causal relationship revealed new insights into disease subtypes and provided novel hypotheses for precision treatment or prevention for the three diseases.

epidemiology↗
bioRxiv2019

SliceIt: A genome-wide resource and visualization tool to design CRISPR/Cas9 screens for editing protein-RNA interaction sites in the human genome

Several protein-RNA cross linking protocols have been established in recent years to delineate the molecular interaction of an RNA Binding Protein (RBP) and its target RNAs. However, functional dissection of the role of the RBP binding sites in modulating the post-transcriptional fate of the target RNA remains challenging. CRISPR/Cas9 genome editing system is being commonly employed to perturb both coding and noncoding regions in the genome. With the advancements in genome-scale CRISPR/Cas9 screens, it is now possible to not only perturb specific binding sites but also probe the global impact of protein-RNA interaction sites across cell types. Here, we present SliceIt (http://sliceit.soic.iupui.edu/), a database of in silico sgRNA (single guide RNA) library to facilitate conducting such high throughput screens. SliceIt comprises of ~4.8 million unique sgRNAs with an estimated range of 2-8 sgRNAs designed per RBP binding site, for eCLIP experiments of >100 RBPs in HepG2 and K562 cell lines from the ENCODE project. SliceIt provides a user friendly environment, developed using advanced search engine framework, Elasticsearch. It is available in both table and genome browser views facilitating the easy navigation of RBP binding sites, designed sgRNAs, exon expression levels across 53 human tissues along with prevalence of SNPs and GWAS hits on binding sites. Exon expression profiles enable examination of locus specific changes proximal to the binding sites. Users can also upload custom tracks of various file formats directly onto genome browser, to navigate additional genomic features in the genome and compare with other types of omics profiles. All the binding site-centric information is dynamically accessible via \"search by gene\", \"search by coordinates\" and \"search by RBP\" options and readily available to download. Validation of the sgRNA library in SliceIt was performed by selecting RBP binding sites in Lipt1 gene and designing sgRNAs. Effect of CRISPR/Cas9 perturbations on the selected binding sites in HepG2 cell line, was confirmed based on altered proximal exon expression levels using qPCR, further supporting the utility of the resource to design experiments for perturbing protein-RNA interaction networks. Thus, SliceIt provides a one-stop repertoire of guide RNA library to perturb RBP binding sites, along with several layers of functional information to design both low and high throughput CRISPR/Cas9 screens, for studying the phenotypes and diseases associated with RBP binding sites.

bioinformatics↗