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The Vanderbilt Institute for Clinical and Translational Research piloted the development of Project PLACENTA (PathLink Acquired gEstatioNal Tissue bAnk). This project investigated the feasibility of a fresh gestational tissue biobank, which provides tissue linked to electronic medical records for investigators interested in maternal-fetal health.We developed a pipeline for collection of placental tissue from Labor and Delivery within approximately 30 minutes of delivery. An email alert was developed, to signal delivery, with the ability to specifically flag patients with certain phenotypic traits. Once collected, 4 to 8 mm punch biopsy cores were snap frozen and subsequently used for DNA, RNA and protein extraction. Tissue was also collected for Formalin Fixed Paraffin Embedded (FFPE) histology, flow cytometry, and quality control measures.Of 60 deliveries using the email notification system, 25 (42%) were sent to Pathology or assigned to other research protocols and were not available for collection, 10 (16%) were discarded prior to arrival at Labor and Delivery, and 25 (42%) were available for collection. Twenty placentas were collected and averaged 38 minutes per collection. DNA extraction yielded an average of 53 µg/µl per sample and RNA extraction yielded 679 ng/µl on average per sample. Proteomic studies showed no degradation of protein, abundant and similar quantities of protein across samples and differentiation between the amnion, decidua, and villi. Histological studies showed good quality for interpretation and occasional pathology including multifocal chronic villitis, meconium laden macrophages, and Stage 2 acute chorioamnionitis. Flow cytometry demonstrated good cell viability after isolation.

The formation of the National Center for Advancing Translational Sciences (NCATS) brings new promise for moving basic and discoveries to clinical practice, ultimately improving the health of the nation. The CTSA sites, now housed with NCATS, are organized and prepared to support in this endeavor. The CTSAs provide a foundation for capitalizing on such promise through provision of a disease-agnostic infrastructure devoted to C&T science, maintenance of training programs designed for C&T investigators of the future, by incentivizing institutional reorganization and by cultivating institutional support.

Introduction The eMERGE (electronic MEdical Records and GEnomics) Network is an NHGRI-supported consortium of five institutions to explore the utility of DNA repositories coupled to Electronic Medical Record (EMR) systems for advancing discovery in genome science. eMERGE also includes a special emphasis on the ethical, legal and social issues related to these endeavors. Organization The five sites are supported by an Administrative Coordinating Center. Setting of network goals is initiated by working groups: (1) Genomics, (2) Informatics, and (3) Consent & Community Consultation, which also includes active participation by investigators outside the eMERGE funded sites, and (4) Return of Results Oversight Committee. The Steering Committee, comprised of site PIs and representatives and NHGRI staff, meet three times per year, once per year with the External Scientific Panel. Current progress The primary site-specific phenotypes for which samples have undergone genome-wide association study (GWAS) genotyping are cataract and HDL, dementia, electrocardiographic QRS duration, peripheral arterial disease, and type 2 diabetes. A GWAS is also being undertaken for resistant hypertension in ≈2,000 additional samples identified across the network sites, to be added to data available for samples already genotyped. Funded by ARRA supplements, secondary phenotypes have been added at all sites to leverage the genotyping data, and hypothyroidism is being analyzed as a cross-network phenotype. Results are being posted in dbGaP. Other key eMERGE activities include evaluation of the issues associated with cross-site deployment of common algorithms to identify cases and controls in EMRs, data privacy of genomic and clinically-derived data, developing approaches for large-scale meta-analysis of GWAS data across five sites, and a community consultation and consent initiative at each site. Future activities Plans are underway to expand the network in diversity of populations and incorporation of GWAS findings into clinical care. Summary By combining advanced clinical informatics, genome science, and community consultation, eMERGE represents a first step in the development of data-driven approaches to incorporate genomic information into routine healthcare delivery.

Advances in genomic technologies and the promise of "personalised medicine" have spurred the interest of researchers, healthcare systems, and the general public. However, the success of population-based genetic studies depends on the willingness of large numbers of individuals and diverse communities to grant researchers access to detailed medical and genetic information. Certain features of this kind of research - such as the establishment of biobanks and prospective data collection from participants' electronic medical records - make the potential risks and benefits to participants difficult to specify in advance. Therefore, community input into biobank processes is essential. In this report, we describe community engagement efforts undertaken by six United States biobanks, various outcomes from these engagements, and lessons learned. Our aim is to provide useful insights and potential strategies for the various disciplines that work with communities involved in biobank-based genomic research.

Background : Genome-wide association studies, largely in research populations, have identified susceptibility single-nucleotide polymorphisms (SNPs) for a broad range of human diseases, including variants at 4q25 associated with atrial fibrillation (AF). However, no studies have evaluated the applicability of these data to practice-based settings. Methods : This study was conducted in the Vanderbilt DNA Databank, a repository that accrues 500 –900 new samples/week from routine outpatient blood draws, and included 37,335 samples as of June 2, 2008. The Databank is linked to a de-identified derivative of the electronic medial record (EMR), which includes data for the last 15 years on 1.4 million subjects. We used natural language processing techniques and billing code queries to extract AF cases and controls without AF from the first 10,000 subjects entering the Databank. Cases had AF recorded in the cardiologist report of an electrocardiogram (ECG). Controls had at least one ECG and no AF, other abnormal atrial rhythms, or atrioventricular nodal ablation in any portion of the EMR, including text documents, billing codes, and ECGs. We excluded subjects with heart transplants and non-Caucasian ethnicity. Subjects were genotyped at rs2200733 and rs10033464, both located at 4q25, previously associated with AF with odds ratios (ORs) of 1.75 and 1.42, respectively. Results : We identified 168 cases with AF and 1695 controls. The electronic algorithms had an accuracy of 98% for identifying cases and 100% for controls over a random sample of 100 subjects each. The minor allele frequencies (MAF) for rs2200733 were 0.1419 for cases and 0.1032 for controls; the MAF for rs10033464 were 0.1019 for cases and 0.908 for controls. rs2200733 was significantly associated with AF (OR [95% confidence interval], 1.44 [1.01–2.03], p=0.04). The effect of rs10033464 on AF was not significant (OR, 1.14 [0.78 –1.67], p=0.52); however, power calculations indicate that 993 cases with AF were needed to replicate this effect. Conclusion : This practice-based study replicated an association identified in research datasets between a 4q25 SNP and AF. These findings support the utility of Electronic Medical Records coupled to DNA collections as resources for genomic research.

Vaccinating millions of Americans depends, in part, on short vaccination times. During two intranasal influenza vaccine trials, times for six vaccination steps were recorded for 497 children. The total of mean times for the steps was 115 s, almost half spent explaining the vaccine and intranasal delivery. Intranasal influenza vaccination time showed little variation by patient age, was comparable to reported intramuscular vaccination times, and was a small fraction of the visit time. Total family visit time decreased by 64 s if the youngest child was receiving a second dose. Alternative delivery systems (e.g., group visits) are needed to take advantage of short vaccination times.