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Estimating narrow-sense heritability from genome-wide data in admixed populations

Georgios Athanasiadis, Doug Speed, Mette K. Andersen, Emil V. R. Appel, Niels Grarup, Ivan Brandslund, Marit Eika Jørgensen, Christina Viskum Lytken Larsen, Peter Bjerregaard, Torben Hansen, Anders Albrechtsen
doi: https://doi.org/10.1101/581389
Georgios Athanasiadis
1Department of Biology, Section for Computational and RNA Biology, University of Copenhagen, Copenhagen, Denmark
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  • For correspondence: yorgos.athanasiadis@gmail.com albrecht@binf.ku.dk
Doug Speed
2Aarhus Institute of Advanced Studies, Aarhus University, Aarhus, Denmark
3Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
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Mette K. Andersen
4Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Emil V. R. Appel
4Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Niels Grarup
4Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Ivan Brandslund
5Department of Clinical Immunology and Biochemistry, Lillebaelt Hospital, Vejle, Denmark
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Marit Eika Jørgensen
6Steno Diabetes Center Copenhagen, Gentofte, Denmark
7Greenland University, Ilisimatusarfik, Nuuk, Greenland
8National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
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Christina Viskum Lytken Larsen
8National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
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Peter Bjerregaard
8National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
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Torben Hansen
4Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Anders Albrechtsen
1Department of Biology, Section for Computational and RNA Biology, University of Copenhagen, Copenhagen, Denmark
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  • For correspondence: yorgos.athanasiadis@gmail.com albrecht@binf.ku.dk
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Abstract

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.

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Posted March 18, 2019.
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Estimating narrow-sense heritability from genome-wide data in admixed populations
Georgios Athanasiadis, Doug Speed, Mette K. Andersen, Emil V. R. Appel, Niels Grarup, Ivan Brandslund, Marit Eika Jørgensen, Christina Viskum Lytken Larsen, Peter Bjerregaard, Torben Hansen, Anders Albrechtsen
bioRxiv 581389; doi: https://doi.org/10.1101/581389
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Estimating narrow-sense heritability from genome-wide data in admixed populations
Georgios Athanasiadis, Doug Speed, Mette K. Andersen, Emil V. R. Appel, Niels Grarup, Ivan Brandslund, Marit Eika Jørgensen, Christina Viskum Lytken Larsen, Peter Bjerregaard, Torben Hansen, Anders Albrechtsen
bioRxiv 581389; doi: https://doi.org/10.1101/581389

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