The limitations of large-scale volunteer databases to address inequalities and global challenges in health and aging

Large-scale volunteer databanks (LSVD) have emerged from the recognized value of cohorts, attracting substantial funding and promising great scientific value. A major focus is their size, with the implicit and sometimes explicit assumption that large size (thus power) creates generalizability. We contend that this is open to challenge. In the context of aging and age-related disease research, LSVD typically have limitations such as healthy volunteer, white ethnicity and high-education biases, and they omit early and late life stages critical for understanding aging. Their outputs are heavily focused on biomedical pathways of single chronic diseases. LSVD outputs increasingly dominate the funding and the publication landscapes. This Perspective discusses LSVD limitations and calls for more transparent reporting in LSVD research, as well as a greater reflection on the value of LSVD in relation to resources consumed. We invite funders and researchers to examine whether LSVD do actually contribute knowledge needed for our acute global health challenges including inequalities. Carol Brayne and Terrie Moffit discuss the limitations of large-scale volunteer databanks (LSVD) for understanding aging and disease, call for further evaluation of their value and offer their thoughts on how to make the reporting of LSVD studies more transparent.

Automated summary

Large-scale volunteer databanks have significant scientific value but also have limitations such as biases and neglect of certain life stages. Transparent reporting and further evaluation of their value are needed.