Tissue-specific alternative splicing of TCF7L2

Common variants in the transcription factor 7-like 2 (TCF7L2) gene have been identified as the strongest genetic risk factors for type 2 diabetes (T2D). However, the mechanisms by which these non-coding variants increase risk for T2D are not well-established. We used 13 expression assays to survey mRNA expression of multiple TCF7L2 splicing forms in up to 380 samples from eight types of human tissue (pancreas, pancreatic islets, colon, liver, monocytes, skeletal muscle, subcutaneous adipose tissue and lymphoblastoid cell lines) and observed a tissue-specific pattern of alternative splicing. We tested whether the expression of TCF7L2 splicing forms was associated with single nucleotide polymorphisms (SNPs), rs7903146 and rs12255372, located within introns 3 and 4 of the gene and most strongly associated with T2D. Expression of two splicing forms was lower in pancreatic islets with increasing counts of T2D-associated alleles of the SNPs: a ubiquitous splicing form (P = 0.018 for rs7903146 and P = 0.020 for rs12255372) and a splicing form found in pancreatic islets, pancreas and colon but not in other tissues tested here (P = 0.009 for rs12255372 and P = 0.053 for rs7903146). Expression of this form in glucose-stimulated pancreatic islets correlated with expression of proinsulin (r2 = 0.84–0.90, P < 0.00063). In summary, we identified a tissue-specific pattern of alternative splicing of TCF7L2. After adjustment for multiple tests, no association between expression of TCF7L2 in eight types of human tissue samples and T2D-associated genetic variants remained significant. Alternative splicing of TCF7L2 in pancreatic islets warrants future studies. GenBank Accession Numbers: FJ010164–FJ010174

A genome-wide association study of type 2 diabetes in finns detects multiple susceptibility variants

Identifying the genetic variants that increase the risk of type 2 diabetes (T2D) in humans has been a formidable challenge. Adopting a genome-wide association strategy, we genotyped 1161 Finnish T2D cases and 1174 Finnish normal glucose-tolerant (NGT) controls with >315,000 single-nucleotide polymorphisms (SNPs) and imputed genotypes for an additional >2 million autosomal SNPs. We carried out association analysis with these SNPs to identify genetic variants that predispose to T2D, compared our T2D association results with the results of two similar studies, and genotyped 80 SNPs in an additional 1215 Finnish T2D cases and 1258 Finnish NGT controls. We identify T2D-associated variants in an intergenic region of chromosome 11p12, contribute to the identification of T2D-associated variants near the genes IGF2BP2 and CDKAL1 and the region of CDKN2A and CDKN2B, and confirm that variants near TCF7L2, SLC30A8, HHEX, FTO, PPARG, and KCNJ11 are associated with T2D risk. This brings the number of T2D loci now confidently identified to at least 10

A Logical Representation for Capturing the Context of Observations and Quantitative Information in Clinical Trial Reports

Clinical trial experimental studies are the gold standard for obtaining evidence related to interventions for a given disease or chronic condition, and currently results are documented in free-text reports. Due to the current free-text representation, utilizing knowledge from these studies and interpreting results remains an ongoing challenge. This dissertation proposes a bridge representation that transforms information in clinical trial reports from a free-text format to a representation that is computer understandable and capable of assisting answering high level queries from bio-statisticians and clinicians. The objectives of this work are: (1) to specify a representation that will concisely synthesize fragments of information found in clinical trial reports, so users can readily understand the context of numerical data, follow the flow of the study, and assess the quality of the study; and (2) to support queries related to assessment of study quality and estimation of contextualized probabilities derived from various sections within the report (e.g., survival curve, p-values, etc.). The representation is based on a hybrid structure combining several modeling paradigms to create an intuitive and standardized way of describing the conditions of the experiments, the data generated, the analysis methods and the results. Query processing and navigation methods have been designed to operate on the representation to answer common questions related to clinical research, from the clinical and biostatistics side. Such queries include defining the conditions of the patient cohort and interventions, providing context to numerical frequency information, and providing a comprehensive summary of the methods used to compute statistical significance. The focus of the dissertation has been in the clinical research domain of oncology. The dissertation work offers a value-added and time-saving solution to standardizing and organizing information from clinical trial reports and synthesizing knowledge to advance clinical research

Evaluating a Novel Summary Visualization for Clinical Trial Reports: A Usability Study.

Contributions of clinical trials are captured in published reports that are unstructured and often require extensive manual review to gain a deeper understanding of the study itself. Our goal is to increase comprehension and decrease the time necessary to understand these reports through the use of visualization tools. In this paper, we specify and evaluate the visualization of a previously developed representation as well as gain insight from user input for further development. The usability experiment consisted of a two-arm study with users either having or not having access to the visualization. A user questionnaire was used to measure time spent and accuracy in comprehension; intuitiveness and reproducibility of the visualization; and preferences. We found that having the visualization required on average 28.1% less time (25.8&nbsp;min vs. 35.8&nbsp;min, p=0.01) while maintaining similar accuracy (73.7% vs. 67.0%). Users were then asked to create their own visualizations, with their visualizations averaging 86.1% similar to the gold standard. All participants either preferred the visualization over the status quo or preferred both equally. These results demonstrate that novel visualizations for trial reports could provide time savings and achieve similar accuracy as reviewing the paper itself. Understanding the strength and quality of clinical trials can be alleviated with a visualization that makes content explicit

A formal representation for numerical data presented in published clinical trial reports.

Assessing the quality of and integrating clinical trial reports are necessary to practice evidence-based medicine. In particular, the numerical data is essential to understanding the strength and quality of the clinical trial study. In this paper, we present a formal representation for standardizing numerical data in published clinical trial reports, and our efforts towards developing computational tools to capture and visualize this representation. The approach includes two aspects: a process model used to precisely define experimental context behind the numerical value; and a spreadsheet, an intuitive and familiar tool used to organize numerical data. We demonstrated this representation using clinical trial reports on non-small cell lung cancer (NSCLC). We performed a preliminary evaluation to determine the usefulness of this formalism for identifying the characteristics, quality and significance of a clinical trial. Our initial results demonstrate that the representation is sufficiently expressive to capture reported numerical information in published papers

Discovery-based science education: functional genomic dissection in Drosophila by undergraduate researchers.

How can you combine professional-quality research with discovery-based undergraduate education? The UCLA Undergraduate Consortium for Functional Genomics provides the answe

Discovery-Based Science Education: Functional Genomic Dissection in Drosophila by Undergraduate Researchers

Discovery-Based Science Education: Functional Genomic Dissection in Drosophila by Undergraduate Researcher

Example of the Type of Data Available from the Online Database (http://www.bruinfly.ucla.edu)

<p>Example of the Type of Data Available from the Online Database (<a href="http://www.bruinfly.ucla.edu" target="_blank">http://www.bruinfly.ucla.edu</a>)</p