We provide a mini-review of how biobanks can support clinical genetics in the era of personalized medicine. We discuss types of biobanks, including disease specific and general biobanks not focused on one disease. We present considerations in setting up a biobank, including consenting and governance, biospecimens, risk factor and related data, informatics, and linkage to electronic health records for phenotyping. We also discuss the uses of biobanks and ongoing considerations, including genotype-driven recruitment, investigations of gene–environment associations, and the re-use of data generated from studies. Finally, we present a brief discussion of some of the unresolved issues, such as return of research results and sustaining biobanks over time. In summary, carefully designed biobanks can provide critical research and infrastructure support for clinical genetics in the era of personalized medicine.

We examined the Institutional Review Board (IRB) process at 9 academic institutions in the electronic Medical Records and Genomics (eMERGE) Network, for proposed electronic health record-based genomic medicine studies, to identify common questions and concerns. Sequencing of 109 disease related genes and genotyping of 14 actionable variants is being performed in ~28,100 participants from the 9 sites. Pathogenic/likely pathogenic variants in actionable genes are being returned to study participants. We examined each site’s research protocols, informed-consent materials, and interactions with IRB staff. Research staff at each site completed questionnaires regarding their IRB interactions. The time to prepare protocols for IRB submission, number of revisions and time to approval ranged from 10–261 days, 0–11, and 11–90 days, respectively. IRB recommendations related to the readability of informed consent materials, specifying the full range of potential risks, providing options for receiving limited results or withdrawal, sharing of information with family members, and establishing the mechanisms to answer participant questions. IRBs reviewing studies that involve the return of results from genomic sequencing have a diverse array of concerns, and anticipating these concerns can help investigators to more effectively engage IRBs.

Objectives: To identify clinically actionable genetic variants from targeted sequencing of 68 disease-related genes, estimate their penetrance, and assess the impact of disclosing results to participants and providers. Patients and Methods: The Return of Actionable Variants Empirical (RAVE) Study investigates outcomes following the return of pathogenic/likely pathogenic (P/LP) variants in 68 disease-related genes. The study was initiated in December 2016 and is ongoing. Targeted sequencing was performed in 2533 individuals with hyperlipidemia or colon polyps. The electronic health records (EHRs) of participants carrying P/LP variants in 36 cardiovascular disease (CVD) genes were manually reviewed to ascertain the presence of relevant traits. Clinical outcomes, health care utilization, family communication, and ethical and psychosocial implications of disclosure of genomic results are being assessed by surveys, telephone interviews, and EHR review. Results: Of 29,208 variants in the 68 genes, 1915 were rare (frequency <1%) and putatively functional, and 102 of these (60 in 36 CVD genes) were labeled P/LP based on the American College of Medical Genetics and Genomics framework. Manual review of the EHRs of participants (n=73 with P/LP variants in CVD genes) revealed that 33 had the expected trait(s); however, only 6 of 45 participants with non–familial hypercholesterolemia (FH) P/LP variants had the expected traits. Conclusion: Expected traits were present in 13% of participants with P/LP variants in non-FH CVD genes, suggesting low penetrance; this estimate may change with additional testing performed as part of the clinical evaluation. Ongoing analyses of the RAVE Study will inform best practices for genomic medicine.

Background/Aims: The Sangre Por Salud (Blood for Health; SPS) Biobank was created for the purpose of expanding precision medicine research to include underrepresented Latino patients. It is the result of a unique collaboration between Mayo Clinic and Mountain Park Health Center, a federally qualified community health center in Phoenix, Arizona. This report describes the rationale, development, implementation, and characteristics of the SPS Biobank. Methods: Latino adults (ages 18-85 years) who were active patients within Mountain Park Health Center's internal medicine practice in Phoenix, Ariz., and had no history of diabetes were eligible. Participants provided a personal and family history of chronic disease, completed a sociodemographic, psychosocial, and behavioral questionnaire, underwent a comprehensive cardiometabolic risk assessment (anthropometrics, blood pressure and labs), and provided blood samples for banking. Laboratory results of cardiometabolic testing were returned to the participants and their providers through the electronic health record. Results: During the first 2 years of recruitment into theSPS Biobank, 2,335 patients were approached and 1,432 (61.3%) consented to participate; 1,354 (94.5%) ultimately completed all requisite questionnaires and medical evaluations. The cohort is primarily Spanish-speaking (72.9%), female (73.3%), with a mean age of 41.3 ± 12.5 years. Most participants were born outside of the US (77.9%) and do not have health insurance (77.5%). The prevalence of overweight (35.5%) and obesity (45.0%) was high, as was previously unidentified prediabetes (55.9%), type 2 diabetes (7.4%), prehypertension (46.8%), and hypertension (16.2%). The majority of participants rated their health as good to excellent (72.1%) and, as a whole, described their overall quality of life as high (7.9/10). Conclusion: Collaborative efforts such as the SPS Biobank are critical for ensuring that underrepresented minority populations are included in precision medicine initiatives and biomedical research that seeks to improve human health and reduce the burdens of disease.

Dynamic consent has been proposed as a strategy for addressing the limitations of traditional, broad consent for biobank participation. Although the argument for dynamic consent has been made on theoretical grounds, empirical studies evaluating the potential utility of dynamic consent are needed to enhance deliberations about the merits of dynamic consent. Few studies have assessed such considerations as whether donor preferences may change over time or if participants would use a dynamic consent mechanism to modify preferences when they change. We administered a 66-item survey to participants in a large DNA biobank. The survey sought to gauge the stability of donor preferences specified at the time of biobank enrollment, specifically the stability of donors’ preference regarding posthumous availability of biospecimens to next-of-kin. We received 1164 completed surveys for a response rate of 72%. Forty percent of respondents indicated a preference regarding sample availability on the survey (T2) that was inconsistent with the preference they had expressed when they enrolled in the biobank (T1). Most (94%) individuals with inconsistent preferences regarding sample availability had initially restricted sample availability at T1 but were comfortable with broader availability when asked at the time of the survey (T2). Our findings demonstrate that preferences regarding sample use expressed at the time of enrollment in a DNA biobank may not be reliable indicators of donor preferences over time. These findings lend empirical support to the case for a dynamic consent model in which biobank participants are approached over time to clarify their views regarding sample use.