Publications

Clinical trials are one of the most valuable sources of scientific evidence for improving the practice of medicine. The Trial Bank project aims to improve structured access to trial findings by including formalized trial information into a knowledge base. Manually extracting trial information from published articles is costly, but automated information extraction techniques can assist. The current study highlights a single architecture to extract a wide array of information elements from full-text publications of randomized clinical trials (RCTs). This architecture combines a text classifier with a weak regular expression matcher. We tested this two-stage architecture on 88 RCT reports from 5 leading medical journals, extracting 23 elements of key trial information such as eligibility rules, sample size, intervention, and outcome names. Results prove this to be a promising avenue to help critical appraisers, systematic reviewers, and curators quickly identify key information elements in published RCT articles.

Clinical questions are often studied by randomized clinical trials (RCTs) of heterogeneous design. Systematic reviewers and trial designers need to compare the design and results across these trials. If trial information is available in computer processable form, computer-based visualization techniques can provide cognitive support for such comparisons. CTeXplorer offers systematic reviewers and trial designers a tool to better and more quickly understand design heterogeneity in RCTs. CTeXplorer supports dynamic queries on eligibility criteria, interventions, and outcomes in three linked views. We tested CTeXplorer for displaying 12 RCTs on prevention of mother-to-child transmission of HIV. Three target users found the representation and organization of information intuitive and easy to learn. They were able to use CTeXplorer to achieve a quick cognitive overview of a heterogeneous group of RCTs. This work shows the benefit of capturing trial information in computable form. Future work includes leveraging ontologies to enhance CTeXplorer visualizations.

BACKGROUND

The objective of the study was to evaluate the association between race/ethnic (r/e) discrimination and subclinical cardiovascular disease (CVD). Although r/e discrimination is a chronic stressor that might have negative health effects, cardiovascular data related to experiences with discrimination among different r/e groups in the United States remain sparse.

METHODS

Using data from the Dallas Heart Study, we assessed the association between perceived r/e discrimination and traditional CVD risk factors, C-reactive protein (CRP), aortic plaque area and wall thickness, and coronary calcium (CAC) score among black, white, and Hispanic participants. Prevalent CAC was defined as a CAC score > or =10 Agatston units; CRP elevation was defined as > or =3 mg/L. Participants were asked, "Have you ever been discriminated against due to your race/ethnicity? (responses: yes, no, or don't know)".

RESULTS

Blacks reported r/e discrimination more frequently than whites or Hispanics (P < .0001). Blacks who reported r/e discrimination were more likely to be college graduates, to have a family history of myocardial infarction, and to be more physically active than blacks who did not report r/e discrimination (each P < .05). Hispanics who reported r/e discrimination had a higher prevalence of smoking (P < .01) and were more likely to be born in the United States. In models that adjusted for traditional CVD risk factors and medication use, we generally found no association between reports of r/e discrimination and aortic wall thickness, aortic plaque area, prevalent CAC, or elevated CRP in any of the r/e groups. Among blacks, stratification by gender and education did not change the observed relationship between perceived r/e discrimination and CAC or CRP.

CONCLUSIONS

Although perceived r/e discrimination is associated with certain health characteristics that may result in negative health outcomes, in general, we found no association of r/e discrimination with either subclinical atherosclerosis as determined by CAC score, aortic wall thickness and aortic plaque area, or inflammation as assessed by elevated CRP levels.

OBJECTIVE

There is increasing physiological evidence in rodents connecting the neuropeptide galanin to triglyceride (TG) levels. We hypothesized that variation in the galanin preproprotein (GAL) gene may contribute to hypertriglyceridemia (HTG) in humans.

METHODS AND RESULTS

We investigated GAL as a TG candidate gene by genotyping 4 tagSNPs in Dutch, Finnish, and Mexican familial combined hyperlipidemia (FCHL) families as well as in white combined hyperlipidemia cases/controls (n=2471). The common allele of rs2187331, residing in the promoter region of GAL, was significantly associated with HTG (probability value=0.00038). In an unascertained population sample of 4463 Finnish males, the rare allele of rs2187331 was associated with higher TGs (probability value=0.0028 to 0.00016). We also observed an allele specific difference with rs2187331 in reporter gene expression and nuclear factor binding in vitro. Furthermore, we detected differential expression of many key lipid genes in adipose tissue based on rs2187331 genotypes.

CONCLUSIONS

The SNP rs2187331 is associated with HTG in FCHL and white combined hyperlipidemia cases/controls and influences TG levels in the population. Further studies are warranted to elucidate the allelic difference observed between FCHL and the general population. Functional evidence shows that rs2187331 has an allele specific cis-regulatory function and influences the expression of lipid related genes in adipose.