The Quantitative Genetics of Human Disease: 3A Interactions—Correlation in State

Kiana Jodeiry; Andrew J. Bass; Michael P. Epstein; David J. Cutler

doi:10.47248/hpgg2505040008

Human Population Genetics and Genomics 2025;5(4):0008 | https://doi.org/10.47248/hpgg2505040008

Original Research Open Access

The Quantitative Genetics of Human Disease: 3A Interactions—Correlation in State

Kiana Jodeiry ^1,2 , Andrew J. Bass ^2,3,† , Michael P. Epstein ^2,3 , David J. Cutler ^2,3

1 Department of Psychology, Emory University, Atlanta, Georgia 30322, USA
2 Center of Computational and Quantitative Genetics, Emory University, Atlanta, Georgia 30322, USA
3 Department of Human Genetics, Emory University,Atlanta, Georgia 30322, USA

† Current address: Department of Medicine, University of Cambridge, Addenbrooke’s Hospital, Hills Road, Cambridge, UK

Correspondence: David J. Cutler

Academic Editor(s): Carina Schlebusch, Lounès Chikhi

Received: Oct 30, 2024 | Accepted: Dec 19, 2025 | Published: Dec 26, 2025

Cite this article: Jodeiry K, Bass AJ, Epstein MP, Cutler DJ. The Quantitative Genetics of Human Disease: 3A Interactions—Correlation in State. Hum Popul Genet Genom 2025; 5(4):0008. https://doi.org/10.47248/hpgg2505040008

Abstract

The third section of an anticipated four paper series distinguishes two different forms of genetic interactions. In this, the first paper of our discussion on genetic interactions, we describe interactions arising from correlation between genotypic and/or environmental states. In the second paper, we will describe interactions arising from non-additivity between uncorrelated factors (epistasis). We illustrate the ways in which correlations in allelic and genotypic state dramatically alter our intuitions and our quantitative genetic estimates, demonstrating why they must be explicitly accounted for. Departures from Hardy-Weinberg equilibrium are understood as a form of interaction caused by correlations in allelic state within a locus. We review the effects of ancestry on correlation in state within a locus and correlation in state between loci (linkage disequilibrium), with the latter contributing to test statistic inflation in association studies. Relatedness is understood as correlation in allelic state due to recent ancestry. Here we show that population structure, i.e., ancestry, is most simply understood as causing correlation in state between factors, and we demonstrate methods to estimate quantitative genetics quantities while accounting for the correlation in state of alleles induced by complex ancestry.

Keywords

quantitative genetics, human disease, genetic interactions, population structure, linkage disequilibrium

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