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Genetic Prediction of Male Pattern Baldness

Saskia P Hagenaars, W David Hill, Sarah E Harris, Stuart J Ritchie, Gail Davies, David C Liewald, Catharine R Gale, David J Porteous, Ian J Deary, Riccardo E Marioni
doi: https://doi.org/10.1101/072306
Saskia P Hagenaars
1Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
2Department of Psychology, University of Edinburgh, Edinburgh, UK
3Division of Psychiatry, University of Edinburgh, Edinburgh, UK
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W David Hill
1Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
2Department of Psychology, University of Edinburgh, Edinburgh, UK
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Sarah E Harris
1Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
4Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
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Stuart J Ritchie
1Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
2Department of Psychology, University of Edinburgh, Edinburgh, UK
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Gail Davies
1Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
2Department of Psychology, University of Edinburgh, Edinburgh, UK
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David C Liewald
1Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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Catharine R Gale
1Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
2Department of Psychology, University of Edinburgh, Edinburgh, UK
5Medical Research Council Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
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David J Porteous
1Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
4Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
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Ian J Deary
1Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
2Department of Psychology, University of Edinburgh, Edinburgh, UK
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Riccardo E Marioni
1Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
4Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
6Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
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Abstract

Male pattern baldness can have substantial psychosocial effects, and it has been phenotypically linked to adverse health outcomes such as prostate cancer and cardiovascular disease. We explored the genetic architecture of the trait using data from over 52,000 male participants of UK Biobank, aged 40-69 years. We identified over 250 independent novel genetic loci associated with severe hair loss. By developing a prediction algorithm based entirely on common genetic variants, and applying it to an independent sample, we could discriminate accurately (AUC = 0.82) between those with no hair loss from those with severe hair loss. The results of this study might help identify those at the greatest risk of hair loss and also potential genetic targets for intervention.

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Posted August 31, 2016.
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Genetic Prediction of Male Pattern Baldness
Saskia P Hagenaars, W David Hill, Sarah E Harris, Stuart J Ritchie, Gail Davies, David C Liewald, Catharine R Gale, David J Porteous, Ian J Deary, Riccardo E Marioni
bioRxiv 072306; doi: https://doi.org/10.1101/072306
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Genetic Prediction of Male Pattern Baldness
Saskia P Hagenaars, W David Hill, Sarah E Harris, Stuart J Ritchie, Gail Davies, David C Liewald, Catharine R Gale, David J Porteous, Ian J Deary, Riccardo E Marioni
bioRxiv 072306; doi: https://doi.org/10.1101/072306

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