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:10.1371/journal.pgen.1006594

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

Research output: Contribution to journal › Article › peer-review

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 genetic loci associated with severe hair loss (P<5x10^-8). By splitting the cohort into a discovery sample of 40,000 and target sample of 12,000, we developed a prediction algorithm based entirely on common genetic variants that discriminated (AUC = 0.78, sensitivity = 0.74, specificity = 0.69, PPV = 59%, NPV = 82%) those with no hair loss from those with severe hair loss. The results of this study might help identify those at greatest risk of hair loss, and also potential genetic targets for intervention.

Original language	English
Article number	e1006594
Journal	PLoS Genetics
Volume	13
Issue number	2
DOIs	https://doi.org/10.1371/journal.pgen.1006594
Publication status	Published - 14 Feb 2017

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10.1371/journal.pgen.1006594Licence: Creative Commons: Attribution (CC-BY)

HagenaarsEtalPLOS2017GeneticPredictionOfMale
© 2017 Hagenaars et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Final published version, 1.76 MBLicence: Creative Commons: Attribution (CC-BY)

RA2661 Centre for Cognitive Ageing and Cognitive Epidemiology Phase 2. Main Budget.
Deary, I. (Principal Investigator), Gale, C. (Co-investigator), Holmes, M. (Co-investigator), Logie, P. (Co-investigator), Maclullich, A. (Co-investigator), Porteous, D. (Co-investigator), Seckl, J. (Co-investigator), Starr, J. (Co-investigator), Wardlaw, J. (Co-investigator) & Okely, J. (Researcher)
1/09/13 → 31/08/19
Project: Research

Data supporting Hagenaars & Hill et al. Genetic prediction of male pattern baldness. PLOS Genetics
Gale, C. (Creator), Porteous, D. (Creator), Deary, I. (Creator), Marioni, R. (Creator), Ritchie, S. (Creator), Hagenaars, S. (Creator), Hill, D. (Creator), Harris, S. (Creator), Davies, G. (Creator) & Liewald, D. (Creator), Edinburgh DataShare, 4 Jun 2019
DOI: 10.7488/ds/2564, https://doi.org/10.1371/journal.pgen.1006594
Dataset

Riccardo Marioni
- Centre for Genomic and Experimental Medicine
- Edinburgh Neuroscience
- School of Genetics and Cancer - Personal Chair of Molecular Epidemiology of Ageing
Person: Academic: Research Active

Cite this

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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 genetic loci associated with severe hair loss (P<5x10-8). By splitting the cohort into a discovery sample of 40,000 and target sample of 12,000, we developed a prediction algorithm based entirely on common genetic variants that discriminated (AUC = 0.78, sensitivity = 0.74, specificity = 0.69, PPV = 59%, NPV = 82%) those with no hair loss from those with severe hair loss. The results of this study might help identify those at greatest risk of hair loss, and also potential genetic targets for intervention.",

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AU - Gale, Catharine R.

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AU - Deary, Ian J.

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Genetic prediction of male pattern baldness

Abstract

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Projects

RA2661 Centre for Cognitive Ageing and Cognitive Epidemiology Phase 2. Main Budget.

Datasets

Data supporting Hagenaars & Hill et al. Genetic prediction of male pattern baldness. PLOS Genetics

Profiles

Riccardo Marioni

Cite this