How to design a national genomic project—a systematic review of active projects

Abstract

An increasing number of countries are investing efforts to exploit the human genome, in order to improve genetic diagnostics and to pave the way for the integration of precision medicine into health systems. The expected benefits include improved understanding of normal and pathological genomic variation, shorter time-to-diagnosis, cost-effective diagnostics, targeted prevention and treatment, and research advances.We review the 41 currently active individual national projects concerning their aims and scope, the number and age structure of included subjects, funding, data sharing goals and methods, and linkage with biobanks, medical data, and non-medical data (exposome). The main aims of ongoing projects were to determine normal genomic variation (90%), determine pathological genomic variation (rare disease, complex diseases, cancer, etc.) (71%), improve infrastructure (59%), and enable personalized medicine (37%). Numbers of subjects to be sequenced ranges substantially, from a hundred to over a million, representing in some cases a significant portion of the population. Approximately half of the projects report public funding, with the rest having various mixed or private funding arrangements. 90% of projects report data sharing (public, academic, and/or commercial with various levels of access) and plan on linking genomic data and medical data (78%), existing biobanks (44%), and/or non-medical data (24%) as the basis for enabling personal/precision medicine in the future.Our results show substantial diversity in the analysed categories of 41 ongoing national projects. The overview of current designs will hopefully inform national initiatives in designing new genomic projects and contribute to standardisation and international collaboration.

Increasing Genomic Literacy Through National Genomic Projects

“…The 41 currently active national genomic projects were identified and analyzed through a systematic on-line search as previously described ( Kovanda et al, 2021 ). As reviewed previously, the currently active national projects are very diverse and reflect the needs and resources of individual countries ( Kovanda et al, 2021 ).…”

“…The 41 currently active national genomic projects were identified and analyzed through a systematic on-line search as previously described ( Kovanda et al, 2021 ). As reviewed previously, the currently active national projects are very diverse and reflect the needs and resources of individual countries ( Kovanda et al, 2021 ). The main aims of these projects are determining normal genomic variation (90%), pathological genomic variation (71%), improving infrastructure (59%), and achieving personalized medicine (37%).…”

“…The projects with educational aims had three primary target groups; the general public (nine projects), patients (six projects), and professionals involved in genomics (all 16 projects; Figure 1 ), reflecting the projects’ general aims ( Kovanda et al, 2021 ).…”

“…To speed up the process of implementing personalized medicine, individual countries have established national genomic projects with various goals as previously reviewed ( Kovanda et al, 2021 ). In order to achieve the main aims of genomic projects, such as determining normal and pathological genomic variation, improving infrastructure and finally implementing personalized medicine, it is crucial to increase genomic literacy among the public, patients, and professionals on relevant scientific and ethical issues ( Bennett et al, 2017 ; Nakamura et al, 2017 ; Goetz and Schork, 2018 ; Ha et al, 2018 ; Hyland and Dasgupta, 2019 ; Sabatello et al, 2019 ; Wright et al, 2019 ; Whitley et al, 2020 ).…”

Computational Tools to Assess the Functional Consequences of Rare and Noncoding Pharmacogenetic Variability

“…As discussed before, 20 systematic experimental methods, such as deep mutational scanning, could provide a useful means to increase the amount of available high‐quality pharmacogenomic training data and such a strategy already has promising results for the improvement of genome‐wide prediction models 98 . Furthermore, there are at least 41 active national biobank projects of which the majority offer data sharing with plans on linking genomic data to longitudinal medical records 99 . These efforts are likely to provide important resources for the identification of naturally occurring functional variants, thereby further increasing the extent of available training data, particularly for transfer learning.…”