Tumor necrosis factor alpha-induced protein 3 (TNFAIP3) is a multifunctional ubiquitin binding and editing enzyme that regulates inflammation. Genetic studies have implicated polymorphisms within the TNFAIP3 locus to the development of numerous immune-related diseases. This study evaluated the frequencies of single-nucleotide polymorphism (SNPs) within the exonic regions of the TNFAIP3 gene and an associated point mutation from the Illumina array among a predominantly Hispanic cohort.

Genomic DNA was obtained from 721 participants and sequencing of all TNFAIP3 exons and an intergenic point mutation (rs6920220) was performed. In-vitro functional assessment was performed by transfecting mutated TNFAIP3 constructs into TNFAIP3 knockout cells containing the NF-kB luciferase reporter and stimulating with TNFα. Comparative statistics were performed with Student’s t-test for continuous variables and chi-squared test for categorical variables.

Sequencing revealed two missense SNPs, rs146534657:A>G and rs2230926:T>G, both within exon 3 of TNFAIP3, which encodes the protein’s deubiquitinating enzymatic domain. Frequencies of all three point mutations differed significantly across racial groups (χ2-test, P = 0.014 to P < 0.001). Compared to Caucasians, rs146534657:A>G was overrepresented among Hispanics (odds ratio (OR) [95% CI] 4.05 [1.24−13.18]), and rs2230926:T>G was more prevalent among African-Americans (OR [95% CI] 3.65 [1.58−8.43]). In-vitro assays confirm rs146534657:A>G and rs2230926:T>G decrease the ability of TNFAIP3 to abrogate NF-κB activation by 2-fold (P < 0.01) and 1.7-fold (P < 0.01), respectively.

This study reports the frequency of rs146534657:A>G among Hispanics and is the first to evaluate its potential physiologic impact, establishing a basis for future research as a potential biomarker among this population.

The purpose of this research was to understand the preferences of patients receiving integrative medicine services for return of aggregate study results.

A brief online survey (survey 1) was sent to 341 cancer patients receiving integrative medicine interventions; subsequently, a minimally revised survey (survey 2) was sent to 812 individuals with various medical conditions who had been either research participants in integrative medicine studies (n = 446) or patients (n = 346) of mind–body medicine.

Feedback to a model plain language summary was elicited from survey 1 and survey 2 respondents. Seventy-seven survey recipients (23%) responded to survey 1, and 134 survey recipients (17%) responded to survey 2. The majority of respondents to the surveys were female and 51–70 years of age. Ninety percent of responders to survey 1 and 89% of responders to survey 2 indicated that researchers should share overall results of a study with participants. In terms of the means of result distribution, 37%–47% preferred email, while 22%–27% indicated that, as long as the results are shared, it did not matter how this occurred. Of 38 survey 1 respondents who had previously participated in a clinical trial, 37% had received the results of their study. In survey 2, 63 individuals indicated that they previously participated in clinical trials, but only 16% recalled receiving results.

These results confirm that the majority (89%–90%) of integrative medicine patients are interested in receiving the results of clinical trials. The majority (82%–94%) of respondents felt the model plain language summary of results provided was helpful.

This study employed the Delphi method, an exploratory method used for group consensus building, to determine the benefits and challenges associated with community engagement in patient-centered outcomes research.

A series of email surveys were sent to the Patient-Centered Outcomes Research Institute (PCORI)-funded researchers (n = 103) in New England. Consensus was achieved through gathering themes and engaging participants in ranking their level of agreement over three rounds. In round one, participant responses were coded thematically and then tallied. In round two participants were asked to state their level of agreement with each of the themes using a Likert scale. Finally, in round three, the group was asked to rank the round two themes based on potential impact.

Results suggested the greatest benefit of community engagement is that it brings multiple perspectives to the table, with 92% ranking it as the first or second most important contribution. Time was ranked as the most significant barrier to engaging community. Strategies to overcome barriers to community engagement include engaging key stakeholders early in the research, being kind and respectful and spending time with stakeholders. The most significant finding was that no researchers reported having specific measures to evaluate community engagement.

Community engagement can enhance both research relevance and methodology when researchers are engaged in meaningful collaborations. Advancing the science of community engagement will require the development of evaluation metrics to examine the multiple domains of partnership.

To identify potential participants for clinical trials, electronic health records (EHRs) are searched at potential sites. As an alternative, we investigated using medical devices used for real-time diagnostic decisions for trial enrollment.

To project cohorts for a trial in acute coronary syndromes (ACS), we used electrocardiograph-based algorithms that identify ACS or ST elevation myocardial infarction (STEMI) that prompt clinicians to offer patients trial enrollment. We searched six hospitals’ electrocardiograph systems for electrocardiograms (ECGs) meeting the planned trial’s enrollment criterion: ECGs with STEMI or > 75% probability of ACS by the acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI). We revised the ACI-TIPI regression to require only data directly from the electrocardiograph, the e-ACI-TIPI using the same data used for the original ACI-TIPI (development set n = 3,453; test set n = 2,315). We also tested both on data from emergency department electrocardiographs from across the US (n = 8,556). We then used ACI-TIPI and e-ACI-TIPI to identify potential cohorts for the ACS trial and compared performance to cohorts from EHR data at the hospitals.

Receiver-operating characteristic (ROC) curve areas on the test set were excellent, 0.89 for ACI-TIPI and 0.84 for the e-ACI-TIPI, as was calibration. On the national electrocardiographic database, ROC areas were 0.78 and 0.69, respectively, and with very good calibration. When tested for detection of patients with > 75% ACS probability, both electrocardiograph-based methods identified eligible patients well, and better than did EHRs.

Using data from medical devices such as electrocardiographs may provide accurate projections of available cohorts for clinical trials.