Journal Article

DZNE-2020-04877

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Prediction of male-pattern baldness from genotypes.

Liu, F. ; Hamer, M. A. ; Heilmann, S. ; Herold, C.DZNE* ; Moebus, S. ; Hofman, A. ; Uitterlinden, A. G. ; Nöthen, M. M. ; van Duijn, C. M. ; Nijsten, T. E. ; Kayser, M. (Corresponding author)

2016
Stockton Press Basingstoke

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Please use a persistent id in citations: doi:10.1038/ejhg.2015.220

Abstract: The global demand for products that effectively prevent the development of male-pattern baldness (MPB) has drastically increased. However, there is currently no established genetic model for the estimation of MPB risk. We conducted a prediction analysis using single-nucleotide polymorphisms (SNPs) identified from previous GWASs of MPB in a total of 2725 German and Dutch males. A logistic regression model considering the genotypes of 25 SNPs from 12 genomic loci demonstrates that early-onset MPB risk is predictable at an accuracy level of 0.74 when 14 SNPs were included in the model, and measured using the area under the receiver-operating characteristic curves (AUC). Considering age as an additional predictor, the model can predict normal MPB status in middle-aged and elderly individuals at a slightly lower accuracy (AUC 0.69-0.71) when 6-11 SNPs were used. A variance partitioning analysis suggests that 55.8% of early-onset MPB genetic liability can be explained by common autosomal SNPs and 23.3% by X-chromosome SNPs. For normal MPB status in elderly individuals, the proportion of explainable variance is lower (42.4% for autosomal and 9.8% for X-chromosome SNPs). The gap between GWAS findings and the variance partitioning results could be explained by a large body of common DNA variants with small effects that will likely be identified in GWAS of increased sample sizes. Although the accuracy obtained here has not reached a clinically desired level, our model was highly informative for up to 19% of Europeans, thus may assist decision making on early MPB intervention actions and in forensic investigations.

Keyword(s): Adult (MeSH) ; Aged (MeSH) ; Alopecia: genetics (MeSH) ; Case-Control Studies (MeSH) ; Genetic Loci (MeSH) ; Genotype (MeSH) ; Humans (MeSH) ; Male (MeSH) ; Middle Aged (MeSH) ; Polymorphism, Single Nucleotide (MeSH)

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Contributing Institute(s):

1. GenomMathematik in der Neuroepidemiologie (AG Becker)

Research Program(s):

1. 345 - Population Studies and Genetics (POF3-345) (POF3-345)

Appears in the scientific report 2016

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Database coverage:
; BIOSIS Previews ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; Ebsco Academic Search ; IF < 5 ; JCR ; NCBI Molecular Biology Database ; PubMed Central ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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