A2 Refereed review article in a scientific journal
Technological readiness and implementation of genomic-driven precision medicine for complex diseases
Authors: Franks PW, Melen E, Friedman M, Sundstrom J, Kockum I, Klareskog L, Almqvist C, Bergen SE, Czene K, Hägg S, Hall P, Johnell K, Malarstig A, Catrina A, Hagström H, Benson M, Smith JG, Gomez MF, Orho-Melander M, Jacobsson B, Halfvarson J, Repsilber D, Oresic M, Jern C, Melin B, Ohlsson C, Fall T, Rönnblom L, Wadelius M, Nordmark G, Johansson Å, Rosenquist R, Sullivan PF
Publisher: WILEY
Publication year: 2021
Journal: Journal of Internal Medicine
Journal name in source: JOURNAL OF INTERNAL MEDICINE
Journal acronym: J INTERN MED
Volume: 290
Issue: 3
First page : 602
Last page: 620
Number of pages: 19
ISSN: 0954-6820
eISSN: 1365-2796
DOI: https://doi.org/10.1111/joim.13330
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/66658542
The fields of human genetics and genomics have generated considerable knowledge about the mechanistic basis of many diseases. Genomic approaches to diagnosis, prognostication, prevention and treatment - genomic-driven precision medicine (GDPM) - may help optimize medical practice. Here, we provide a comprehensive review of GDPM of complex diseases across major medical specialties. We focus on technological readiness: how rapidly a test can be implemented into health care. Although these areas of medicine are diverse, key similarities exist across almost all areas. Many medical areas have, within their standards of care, at least one GDPM test for a genetic variant of strong effect that aids the identification/diagnosis of a more homogeneous subset within a larger disease group or identifies a subset with different therapeutic requirements. However, for almost all complex diseases, the majority of patients do not carry established single-gene mutations with large effects. Thus, research is underway that seeks to determine the polygenic basis of many complex diseases. Nevertheless, most complex diseases are caused by the interplay of genetic, behavioural and environmental risk factors, which will likely necessitate models for prediction and diagnosis that incorporate genetic and non-genetic data.
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