Utilizing Genetic Programming to Enhance Polygenic Risk Score Calculation

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

Publications: Contribution to bookContribution to proceedingsPeer Reviewed

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.
Original languageEnglish
Title of host publication2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
PublisherIEEE
Pages3782-3787
Number of pages6
ISBN (Electronic)979-8-3503-3748-8
ISBN (Print)979-8-3503-3749-5
DOIs
Publication statusPublished - 2023
Event2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023 - Istanbul, Turkey
Duration: 5 Dec 20238 Dec 2023

Publication series

SeriesIEEE International Conference on Bioinformatics and Biomedicine

Conference

Conference2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023
Country/TerritoryTurkey
CityIstanbul
Period5/12/238/12/23

Austrian Fields of Science 2012

  • 106005 Bioinformatics

Keywords

  • evolution biology
  • plants biology
  • sociology
  • genetic programming
  • data models
  • medical services
  • computational biology
  • polygenic risc source

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