Comparing distributions of polygenic risk scores of type 2 diabetes and coronary heart disease within different populations

PLoS One. 2017 Jul 5;12(7):e0179238. doi: 10.1371/journal.pone.0179238. eCollection 2017.

Abstract

Polygenic risk scores are gaining more and more attention for estimating genetic risks for liabilities, especially for noncommunicable diseases. They are now calculated using thousands of DNA markers. In this paper, we compare the score distributions of two previously published very large risk score models within different populations. We show that the risk score model together with its risk stratification thresholds, built upon the data of one population, cannot be applied to another population without taking into account the target population's structure. We also show that if an individual is classified to the wrong population, his/her disease risk can be systematically incorrectly estimated.

Publication types

  • Comparative Study

MeSH terms

  • Africa
  • Americas
  • Asia
  • Asia, Eastern
  • Coronary Disease / genetics*
  • Diabetes Mellitus, Type 2 / genetics*
  • Estonia
  • Europe
  • Gene Frequency
  • Genetic Predisposition to Disease / genetics
  • Genetics, Population*
  • Humans
  • Models, Genetic
  • Multifactorial Inheritance / genetics*
  • Polymorphism, Single Nucleotide
  • Principal Component Analysis
  • Risk Assessment / methods
  • Risk Assessment / statistics & numerical data
  • Risk Factors

Grants and funding

This work was supported by the following: European Regional Development Funds for the Center of Excellence of Estonian ICT research EXCITE and Estonian Research Council grant IUT34-4: These funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The funders provided support in the form of salaries for authors JV, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section. Quretec Ltd.: The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The funder provided support in the form of salaries for authors JV and SR, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section. Software Technology and Applications Competence Centre: The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The funder provided support in the form of salaries for authors JV and SR, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.