TY - JOUR

T1 - Precision medicine in complex diseases - Molecular subgrouping for improved prediction and treatment stratification

AU - Johansson, Åsa

AU - Andreassen, Ole A.

AU - Brunak, Søren

AU - Franks, Paul W.

AU - Hedman, Harald

AU - Loos, Ruth J.F.

AU - Meder, Benjamin

AU - Melén, Erik

AU - Wheelock, Craig E.

AU - Jacobsson, Bo

N1 - Publisher Copyright: © 2023 The Authors. Journal of Internal Medicine published by John Wiley & Sons Ltd on behalf of Association for Publication of The Journal of Internal Medicine.

PY - 2023

Y1 - 2023

N2 - Complex diseases are caused by a combination of genetic, lifestyle, and environmental factors and comprise common noncommunicable diseases, including allergies, cardiovascular disease, and psychiatric and metabolic disorders. More than 25% of Europeans suffer from a complex disease, and together these diseases account for 70% of all deaths. The use of genomic, molecular, or imaging data to develop accurate diagnostic tools for treatment recommendations and preventive strategies, and for disease prognosis and prediction, is an important step toward precision medicine. However, for complex diseases, precision medicine is associated with several challenges. There is a significant heterogeneity between patients of a specific disease—both with regards to symptoms and underlying causal mechanisms—and the number of underlying genetic and nongenetic risk factors is often high. Here, we summarize precision medicine approaches for complex diseases and highlight the current breakthroughs as well as the challenges. We conclude that genomic-based precision medicine has been used mainly for patients with highly penetrant monogenic disease forms, such as cardiomyopathies. However, for most complex diseases—including psychiatric disorders and allergies—available polygenic risk scores are more probabilistic than deterministic and have not yet been validated for clinical utility. However, subclassifying patients of a specific disease into discrete homogenous subtypes based on molecular or phenotypic data is a promising strategy for improving diagnosis, prediction, treatment, prevention, and prognosis. The availability of high-throughput molecular technologies, together with large collections of health data and novel data-driven approaches, offers promise toward improved individual health through precision medicine.

AB - Complex diseases are caused by a combination of genetic, lifestyle, and environmental factors and comprise common noncommunicable diseases, including allergies, cardiovascular disease, and psychiatric and metabolic disorders. More than 25% of Europeans suffer from a complex disease, and together these diseases account for 70% of all deaths. The use of genomic, molecular, or imaging data to develop accurate diagnostic tools for treatment recommendations and preventive strategies, and for disease prognosis and prediction, is an important step toward precision medicine. However, for complex diseases, precision medicine is associated with several challenges. There is a significant heterogeneity between patients of a specific disease—both with regards to symptoms and underlying causal mechanisms—and the number of underlying genetic and nongenetic risk factors is often high. Here, we summarize precision medicine approaches for complex diseases and highlight the current breakthroughs as well as the challenges. We conclude that genomic-based precision medicine has been used mainly for patients with highly penetrant monogenic disease forms, such as cardiomyopathies. However, for most complex diseases—including psychiatric disorders and allergies—available polygenic risk scores are more probabilistic than deterministic and have not yet been validated for clinical utility. However, subclassifying patients of a specific disease into discrete homogenous subtypes based on molecular or phenotypic data is a promising strategy for improving diagnosis, prediction, treatment, prevention, and prognosis. The availability of high-throughput molecular technologies, together with large collections of health data and novel data-driven approaches, offers promise toward improved individual health through precision medicine.

KW - complex diseases

KW - genetic variations

KW - genomic medicine

KW - GWAS

KW - molecular profiling

KW - multi omics

KW - polygenic risk score (PRS)

KW - precision medicine

U2 - 10.1111/joim.13640

DO - 10.1111/joim.13640

M3 - Review

C2 - 37093654

AN - SCOPUS:85153517541

VL - 294

SP - 378

EP - 396

JO - Journal of Internal Medicine

JF - Journal of Internal Medicine

SN - 0955-7873

IS - 4

ER -