Lessons learned during the process of reporting individual genomic results to participants of a population-based biobank.

The return of individual genomic results (ROR) to research participants is still in its early phase, and insight on how individuals respond to ROR is scarce. Studies contributing to the evidence base for best practices are crucial before these can be established. Here, we describe a ROR procedure conducted at a population-based biobank, followed by surveying the responses of almost 3000 participants to a range of results, and discuss lessons learned from the process, with the aim of facilitating large-scale expansion. Overall, participants perceived the information that they received with counseling as valuable, even when the reporting of high risks initially caused worry. The face-to-face delivery of results limited the number of participants who received results. Although the participants highly valued this type of communication, additional means of communication need to be considered to improve the feasibility of large-scale ROR. The feedback collected sheds light on the value judgements of the participants and on potential responses to the receipt of genetic risk information. Biobanks in other countries are planning or conducting similar projects, and the sharing of lessons learned may provide valuable insight and aid such endeavors.

Effectiveness and feasibility of cardiovascular disease personalized prevention on high polygenic risk score subjects: a randomized controlled pilot study.

Aims: The aim of this study was to evaluate the effect of the intervention by proactively sharing a patient's high polygenic risk score (PRS) for coronary artery disease (CAD). Outcomes included: (i) reduction in cardiovascular disease (CVD) risk factors over 12 months; (ii) difference in purchased prescriptions of lipid-lowering and anti-hypertensive drugs between intervention group and control group subjects; and (iii) opinion of the participating physicians and subjects on PRS usefulness. Methods and results: This randomized controlled trial was conducted among middle-aged subjects with a top 20% CAD PRS in a family medicine setting. Participants were selected from 26 953 Estonian Biobank cohort participants. Subjects were informed and counselled about their PRS score and CAD risk using the visual tool at baseline (Visit I), counselling session (Visit II), and on the final Visit III at 12 months. The primary endpoint was not significantly different. However, the intervention group participants had a significantly higher probability of initiating statin treatment compared with the controls. Their levels of LDL-cholesterol (LDL-C) were significantly decreased compared with baseline on Visit III and significantly lower than in the control group. The vast majority of participating family physicians believe that finding out about genetic risks will affect the subject's lifestyle and medication compliance. Conclusion: Most of our outcome measures were in favour of this intervention. Participants achieved larger changes in cholesterol and blood pressure values. The vast majority (98.4%) of family physicians are interested in continuing to use genetic risk assessment in practice.

Identifying Cases of Type 2 Diabetes in Heterogeneous Data Sources: Strategy from the EMIF Project.

Due to the heterogeneity of existing European sources of observational healthcare data, data source-tailored choices are needed to execute multi-data source, multi-national epidemiological studies. This makes transparent documentation paramount. In this proof-of-concept study, a novel standard data derivation procedure was tested in a set of heterogeneous data sources. Identification of subjects with type 2 diabetes (T2DM) was the test case. We included three primary care data sources (PCDs), three record linkage of administrative and/or registry data sources (RLDs), one hospital and one biobank. Overall, data from 12 million subjects from six European countries were extracted. Based on a shared event definition, sixteeen standard algorithms (components) useful to identify T2DM cases were generated through a top-down/bottom-up iterative approach. Each component was based on one single data domain among diagnoses, drugs, diagnostic test utilization and laboratory results. Diagnoses-based components were subclassified considering the healthcare setting (primary, secondary, inpatient care). The Unified Medical Language System was used for semantic harmonization within data domains. Individual components were extracted and proportion of population identified was compared across data sources. Drug-based components performed similarly in RLDs and PCDs, unlike diagnoses-based components. Using components as building blocks, logical combinations with AND, OR, AND NOT were tested and local experts recommended their preferred data source-tailored combination. The population identified per data sources by resulting algorithms varied from 3.5% to 15.7%, however, age-specific results were fairly comparable. The impact of individual components was assessed: diagnoses-based components identified the majority of cases in PCDs (93-100%), while drug-based components were the main contributors in RLDs (81-100%). The proposed data derivation procedure allowed the generation of data source-tailored case-finding algorithms in a standardized fashion, facilitated transparent documentation of the process and benchmarking of data sources, and provided bases for interpretation of possible inter-data source inconsistency of findings in future studies.

Reporting incidental findings of genomic disorder-associated copy number variants to unselected biobank participants.

BACKGROUND: Procedural guidelines for disclosure of incidental genomic information are lacking. METHODS: We introduce a method and evaluated the impact of returning results to population biobank participants with 16p11.2 copy number variants, which are commonly associated with neurodevelopmental disorders and BMI imbalance. Of the 7877 participants, 11 carriers were detected. Eight participants were informed of their carrier status and surveyed 11-17 months later. RESULTS: All participants demonstrated preference for disclosure. Although two participants experienced worry, all five survey respondents rated receiving this information favorably. One participant reported modifications in treatment and three felt that their treatment/condition had since improved. CONCLUSION: This approach can be adapted and applied for the return of incidental findings to biobank participants.

Copy number variations and cognitive phenotypes in unselected populations.

IMPORTANCE: The association of copy number variations (CNVs), differing numbers of copies of genetic sequence at locations in the genome, with phenotypes such as intellectual disability has been almost exclusively evaluated using clinically ascertained cohorts. The contribution of these genetic variants to cognitive phenotypes in the general population remains unclear. OBJECTIVE: To investigate the clinical features conferred by CNVs associated with known syndromes in adult carriers without clinical preselection and to assess the genome-wide consequences of rare CNVs (frequency ≤0.05%; size ≥250 kilobase pairs [kb]) on carriers' educational attainment and intellectual disability prevalence in the general population. DESIGN, SETTING, AND PARTICIPANTS: The population biobank of Estonia contains 52,000 participants enrolled from 2002 through 2010. General practitioners examined participants and filled out a questionnaire of health- and lifestyle-related questions, as well as reported diagnoses. Copy number variant analysis was conducted on a random sample of 7877 individuals and genotype-phenotype associations with education and disease traits were evaluated. Our results were replicated on a high-functioning group of 993 Estonians and 3 geographically distinct populations in the United Kingdom, the United States, and Italy. MAIN OUTCOMES AND MEASURES: Phenotypes of genomic disorders in the general population, prevalence of autosomal CNVs, and association of these variants with educational attainment (from less than primary school through scientific degree) and prevalence of intellectual disability. RESULTS: Of the 7877 in the Estonian cohort, we identified 56 carriers of CNVs associated with known syndromes. Their phenotypes, including cognitive and psychiatric problems, epilepsy, neuropathies, obesity, and congenital malformations are similar to those described for carriers of identical rearrangements ascertained in clinical cohorts. A genome-wide evaluation of rare autosomal CNVs (frequency, ≤0.05%; ≥250 kb) identified 831 carriers (10.5%) of the screened general population. Eleven of 216 (5.1%) carriers of a deletion of at least 250 kb (odds ratio [OR], 3.16; 95% CI, 1.51-5.98; P = 1.5e-03) and 6 of 102 (5.9%) carriers of a duplication of at least 1 Mb (OR, 3.67; 95% CI, 1.29-8.54; P = .008) had an intellectual disability compared with 114 of 6819 (1.7%) in the Estonian cohort. The mean education attainment was 3.81 (P = 1.06e-04) among 248 (≥250 kb) deletion carriers and 3.69 (P = 5.024e-05) among 115 duplication carriers (≥1 Mb). Of the deletion carriers, 33.5% did not graduate from high school (OR, 1.48; 95% CI, 1.12-1.95; P = .005) and 39.1% of duplication carriers did not graduate high school (OR, 1.89; 95% CI, 1.27-2.8; P = 1.6e-03). Evidence for an association between rare CNVs and lower educational attainment was supported by analyses of cohorts of adults from Italy and the United States and adolescents from the United Kingdom. CONCLUSIONS AND RELEVANCE: Known pathogenic CNVs in unselected, but assumed to be healthy, adult populations may be associated with unrecognized clinical sequelae. Additionally, individually rare but collectively common intermediate-size CNVs may be negatively associated with educational attainment. Replication of these findings in additional population groups is warranted given the potential implications of this observation for genomics research, clinical care, and public health.

Linking a population biobank with national health registries-the estonian experience.

The Estonian population-based biobank, with 52,000 participants' genetic and health data, is the largest epidemiological cohort in the Baltic region. Participants were recruited through a network of medical professionals throughout Estonia (population 1.34 million). Unique legislation as well as a broad consent form give the Estonian Genome Center, a research institute of the University of Tartu, permission to re-contact participants and to retrieve participants' data from national registries and databases. In addition to two re-contacting projects to update the health data of participants, extensive clinical characterizations have been retrieved from national registries and hospital databases regularly since 2010. Acquiring data from electronic health records and registries has provided a means to update and enhance the database of the Genome Center in a timely manner and at low cost. The resulting database allows a wide spectrum of genomic and epidemiological research to be conducted with the aim of benefitting public health. Future plans include linking the genome center database with the national health information system through X-road and exchanging data in real time, as well as using the genetic data and the technical infrastructure available for piloting personalized medicine in Estonia.

Cohort Profile: Estonian Biobank of the Estonian Genome Center, University of Tartu.

The Estonian Biobank cohort is a volunteer-based sample of the Estonian resident adult population (aged ≥18 years). The current number of participants-close to 52000--represents a large proportion, 5%, of the Estonian adult population, making it ideally suited to population-based studies. General practitioners (GPs) and medical personnel in the special recruitment offices have recruited participants throughout the country. At baseline, the GPs performed a standardized health examination of the participants, who also donated blood samples for DNA, white blood cells and plasma tests and filled out a 16-module questionnaire on health-related topics such as lifestyle, diet and clinical diagnoses described in WHO ICD-10. A significant part of the cohort has whole genome sequencing (100), genome-wide single nucleotide polymorphism (SNP) array data (20 000) and/or NMR metabolome data (11 000) available (http://www.geenivaramu.ee/for-scientists/data-release/). The data are continuously updated through periodical linking to national electronic databases and registries. A part of the cohort has been re-contacted for follow-up purposes and resampling, and targeted invitations are possible for specific purposes, for example people with a specific diagnosis. The Estonian Genome Center of the University of Tartu is actively collaborating with many universities, research institutes and consortia and encourages fellow scientists worldwide to co-initiate new academic or industrial joint projects with us.