Utilizing Genetic Programming to Enhance Polygenic Risk Score Calculation

Author(s)

Martin Hurta, Jana Schwarzerová, Thomas Nägele, Wolfram Weckwerth, Valentine Provaznik, Lukas Sekanina

Abstract

The polygenic risk score has proven to be a valuable tool for assessing an individual's genetic predisposition to phenotype (disease) within biomedicine in recent years. However, traditional regression-based methods for polygenic risk scores calculation have limitations that can impede their accuracy and predictive power. This study introduces an innovative approach to enhance polygenic risk scores calculation through the application of genetic programming. By harnessing the power of genetic programming, we aim to overcome the limitations of traditional regression techniques and improve the accuracy of polygenic risk scores predictions. Specifically, we showed that a polygenic risk score generated through Cartesian genetic programming yielded comparable or even more robust statistical distinctions between groups that we evaluated within three independent case studies.

Organisation(s)

Functional and Evolutionary Ecology, Research Platform Vienna Metabolomics Center

External organisation(s)

Brno University of Technology, Ludwig-Maximilians-Universität München, Universität Wien

Pages

3782

No. of pages

3787

Publication date

2023

Peer reviewed

Yes

Austrian Fields of Science 2012

102020 Medical informatics, 107007 Risk research

Keywords

ASJC Scopus subject areas

Biochemistry, Genetics and Molecular Biology (miscellaneous), Molecular Medicine, Plant Science, Health Informatics

Sustainable Development Goals

SDG 3 - Good Health and Well-being

Portal url

https://ucris.univie.ac.at/portal/en/publications/utilizing-genetic-programming-to-enhance-polygenic-risk-score-calculation(b817af67-1a40-4342-a713-8db11a53e311).html