PT  - JOURNAL ARTICLE
AU  - Georgios Athanasiadis
AU  - Doug Speed
AU  - Mette K. Andersen
AU  - Emil V. R. Appel
AU  - Niels Grarup
AU  - Ivan Brandslund
AU  - Marit Eika Jørgensen
AU  - Christina Viskum Lytken Larsen
AU  - Peter Bjerregaard
AU  - Torben Hansen
AU  - Anders Albrechtsen
TI  - Estimating narrow-sense heritability from genome-wide data in admixed populations
AID  - 10.1101/581389
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 581389
4099  - http://biorxiv.org/content/early/2019/03/18/581389.short
4100  - http://biorxiv.org/content/early/2019/03/18/581389.full
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.