Global priorities for large-scale biomarker-based prospective cohorts

Prospective study design and data analysis in UK Biobank

Population-based prospective studies, such as UK Biobank, are valuable for generating and testing hypotheses about the potential causes of human disease. We describe how UK Biobank's study design, data access policies, and approaches to statistical analysis can help to minimize error and improve the interpretability of research findings, with implications for other population-based prospective studies being established worldwide.

Are we ready for translational research based on material and data from the Danish CancerBiobank and can we gain new knowledge from biobank registration?

Bio-and GenomeBank, Denmark (RBGB) is a nationwide infra-structure. Danish CancerBiobank (DCB) is a biobank in RBGB. The aim is to describe the degree of biological material collected and stored in DCB for patients diagnosed with primary ovarian cancer registered in The Danish Gynecologic Cancer Database (DGCD). Furthermore, to investigate the concordance between predicted organ of disease registered in RBGB at time of sampling (presumed diagnosis) with final diagnosis for patient. Data extraction from DGCD and DCB. Biological materials are present for 1.347 (62%) of 2.172 patients with primary ovarian cancer (OC). The median age of OC patients were 68 years (range: 18-90 years). Median age of patients with biological material in DCB was 67 years and for patients without biological material in DCB 69 years (p ≤ 0.0001). The histological subtypes for the 1347 OC patients with biological material were 911 (68%) serous adenocarcinoma, 97 (7%) endometrioid adenocarcinoma, 80 (6%) mucinous adenocarcinoma, 58 (4%) clear cell carcinoma, and for 201 (15%) no information were registered. For 327 patients (24%), the presumed diagnosis was hematological with a final diagnosis of OC. Using clinical data and biological material including pre-analytical data regarding the biological material the possibility for translational research is optimal. Furthermore, information registered through daily working procedures may propose the need for additional biomarkers to aid clinicians to stratify patients to treatment in correct fast-track packages.

A FinnGen pilot clinical recall study for Alzheimer's disease

Successful development of novel therapies requires that clinical trials are conducted in patient cohorts with the highest benefit-to-risk ratio. Population-based biobanks with comprehensive health and genetic data from large numbers of individuals hold promise to facilitate identification of trial participants, particularly when interventions need to start while symptoms are still mild, such as for Alzheimer's disease (AD). This study describes a process for clinical recall studies from FinnGen. We demonstrate the feasibility to systematically ascertain customized clinical data from FinnGen participants with ICD10 diagnosis of AD or mild cognitive disorder (MCD) in a single-center cross-sectional study testing blood-based biomarkers and cognitive functioning in-person, computer-based and remote. As a result, 19% (27/140) of a pre-specified FinnGen subcohort were successfully recalled and completed the study. Hospital records largely validated registry entries. For 8/12 MCD patients, other reasons than AD were identified as underlying diagnosis. Cognitive measures correlated across platforms, with highest consistencies for dementia screening (r = 0.818) and semantic fluency (r = 0.764), respectively, for in-person versus telephone-administered tests. Glial fibrillary acidic protein (GFAP) (p < 0.002) and phosphorylated-tau 181 (pTau-181) (p < 0.020) most reliably differentiated AD from MCD participants. We conclude that informative, customized clinical recall studies from FinnGen are feasible.