RT Journal Article
SR Electronic
T1 Estimating narrow-sense heritability from genome-wide data in admixed populations
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 581389
DO 10.1101/581389
A1 Athanasiadis, Georgios
A1 Speed, Doug
A1 Andersen, Mette K.
A1 Appel, Emil V. R.
A1 Grarup, Niels
A1 Brandslund, Ivan
A1 Jørgensen, Marit Eika
A1 Lytken Larsen, Christina Viskum
A1 Bjerregaard, Peter
A1 Hansen, Torben
A1 Albrechtsen, Anders
YR 2019
UL http://biorxiv.org/content/early/2019/03/18/581389.abstract
AB Finding an efficient framework for estimating total narrow-sense heritability in admixed populations remains an open question. In this work, we used extensive simulations to evaluate existing linear mixed model frameworks in estimating total narrow-sense heritability in two population-based cohorts from Greenland and compared the results to data from unadmixed individuals from Denmark. When our analysis focused on Greenlandic sib pairs, the model with two relationship matrices, one capturing identity by descent and one capturing identity by state, returned heritability estimates close to the true simulated value, while using each of the two matrices alone led to downward biases. When phenotypes correlated with ancestry, heritability estimates were inflated. Based on these observations, we propose a post-estimation PCA-based adjustment that recovers successfully the true simulated heritability. We use this knowledge to estimate the heritability of ten quantitative traits from the two Greenlandic cohorts and report differences such as lower heritability for height in Greenlanders compared to Europeans. In conclusion, narrow-sense heritability in admixed populations is best estimated using a mixture of genetic relationship matrices on individuals with at least one first-degree relative included in the sample.