In the field of genetics, the concept of heritability refers to the proportion of variations of a biological trait or disease that can be explained by genetic factors. Quantifying the heritability of a disease is a fundamental challenge in human genetics, especially when the causes are plural and not clearly identified. Although the literature regarding heritability estimation for binary traits is less rich than for quantitative traits, several methods have been proposed to estimate the heritability of complex diseases. However, to the best of our knowledge, the existing methods are not supported by theoretical grounds. Moreover, most of the methodologies do not take into account a major specificity of the data coming from medical studies, which is the oversampling of the number of patients compared to controls. We propose in this paper to investigate the theoretical properties of the Phenotype Correlation Genotype Correlation (PCGC) regression developed by Golan, Lander and Rosset (2014), which is one of the major techniques used in statistical genetics and which is very efficient in practice, despite the oversampling of patients. Our main result is the proof of the consistency of this estimator, under several assumptions that we will state and discuss. We also provide a numerical study to compare two approximations leading to two heritability estimators.
"Heritability estimation in case-control studies." Electron. J. Statist. 12 (1) 1662 - 1716, 2018. https://doi.org/10.1214/18-EJS1424