Evidence for a polygenic contribution to androgenetic alopecia

被引:24
作者
Heilmann, S. [1 ,2 ]
Brockschmidt, F. F. [1 ,2 ]
Hillmer, A. M. [3 ]
Hanneken, S. [4 ]
Eigelshoven, S.
Ludwig, K. U. [1 ,2 ]
Herold, C. [5 ]
Mangold, E. [1 ]
Becker, T. [5 ,6 ]
Kruse, R.
Knapp, M. [6 ]
Noethen, M. M. [1 ,2 ]
机构
[1] Univ Bonn, Inst Human Genet, Bonn, Germany
[2] Univ Bonn, Dept Genom, Life & Brain Ctr, Bonn, Germany
[3] Genome Inst Singapore, Singapore, Singapore
[4] Univ Dusseldorf, Dept Dermatol, Dusseldorf, Germany
[5] German Ctr Neurodegenerat Dis DZNE, Bonn, Germany
[6] Univ Bonn, Inst Med Biometry Informat & Epidemiol, Bonn, Germany
关键词
MALE-PATTERN BALDNESS;
D O I
10.1111/bjd.12443
中图分类号
R75 [皮肤病学与性病学];
学科分类号
100206 ;
摘要
BackgroundMale pattern baldness (androgenetic alopecia, AGA) is a highly heritable trait and the most common form of hair loss in humans. Eight genome-wide significant risk loci for AGA have been identified. ObjectivesTo determine whether a polygenic component contributes to the genetic risk for AGA. MethodsThis study used a German case-control sample for AGA, which comprised 581 severely affected patients and 617 controls, to determine the contribution of polygenic variance to AGA risk. The sample was divided evenly into discovery and test samples. An additive polygenic risk score was calculated from risk alleles with increasingly liberal P-values in the discovery dataset, which was then used to test for the enrichment of AGA risk score alleles in the independent test samples. ResultsThe polygenic score analysis provided significant evidence for a polygenic contribution to AGA where the amount of variance explained was 1<bold>4</bold>-4<bold>5</bold>%. ConclusionThis study provides evidence for the specific contribution of a polygenic component to the overall heritable risk for AGA. To some degree, the polygenic architecture of AGA might reflect the complexity of the biological pathways involved. Further analyses and strategies that complement conventional genome-wide association studies are needed to identify these factors. These may include pathway-based analyses, the analysis of functional candidate genes and tests for epistatic effects with known loci.
引用
收藏
页码:927 / 930
页数:4
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