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Genetic prediction of male pattern baldness.

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.

SUBMITTER: Hagenaars SP

PROVIDER: S-EPMC5308812 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Genetic prediction of male pattern baldness.

Hagenaars Saskia P SP Hill W David WD Harris Sarah E SE Ritchie Stuart J SJ Davies Gail G Liewald David C DC Gale Catharine R CR Porteous David J DJ Deary Ian J IJ Marioni Riccardo E RE

PLoS genetics 20170214 2

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 develo ...[more]

PMID: 28196072

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Genetic prediction of male pattern baldness based on large independent datasets.

Project description:Genetic prediction of male pattern baldness (MPB) is important in science and society. Previous genetic MPB prediction models were limited by sparse marker coverage, small sample size, and/or data dependency in the different analytical steps. Here, we present novel models for genetic prediction of MPB based on a large set of markers and large independent subsample sets drawn among 187,435 European subjects. We selected 117 SNP predictors within 85 distinct loci from a list of 270 previously MPB-associated SNPs in 55,573 males of the UK Biobank Study (UKBB). Based on these 117 SNPs with and without age as additional predictor, we trained, by use of different methods, prediction models in a non-overlapping subset of 104,694 UKBB males and tested them in a non-overlapping subset of 26,177 UKBB males. Estimates of prediction accuracy were similar between methods with AUC ranges of 0.725-0.728 for severe, 0.631-0.635 for moderate, 0.598-0.602 for slight, and 0.708-0.711 for no hair loss with age, and slightly lower without, while prediction of any versus no hair loss gave 0.690-0.711 with age and slightly lower without. External validation in an early-onset enriched MPB dataset from the Bonn Study (N = 991) showed improved prediction accuracy without considering age such as AUC of 0.830 for no vs. any hair loss. Because of the large number of markers and the large independent datasets used for the different analytical steps, the newly presented genetic prediction models are the most reliable ones currently available for MPB or any other human appearance trait.

| S-EPMC9995341 | biostudies-literature

Prediction of male-pattern baldness from genotypes.

Project description: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.

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Dissection of genetic variation and evidence for pleiotropy in male pattern baldness.

Project description:Male pattern baldness (MPB) is a sex-limited, age-related, complex trait. We study MPB genetics in 205,327 European males from the UK Biobank. Here we show that MPB is strongly heritable and polygenic, with pedigree-heritability of 0.62 (SE = 0.03) estimated from close relatives, and SNP-heritability of 0.39 (SE = 0.01) from conventionally-unrelated males. We detect 624 near-independent genome-wide loci, contributing SNP-heritability of 0.25 (SE = 0.01), of which 26 X-chromosome loci explain 11.6%. Autosomal genetic variance is enriched for common variants and regions of lower linkage disequilibrium. We identify plausible genetic correlations between MPB and multiple sex-limited markers of earlier puberty, increased bone mineral density (rg = 0.15) and pancreatic β-cell function (rg = 0.12). Correlations with reproductive traits imply an effect on fitness, consistent with an estimated linear selection gradient of -0.018 per MPB standard deviation. Overall, we provide genetic insights into MPB: a phenotype of interest in its own right, with value as a model sex-limited, complex trait.

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Male-pattern baldness susceptibility locus at 20p11.

Project description:We conducted a genome-wide association study for androgenic alopecia in 1,125 men and identified a newly associated locus at chromosome 20p11.22, confirmed in three independent cohorts (n = 1,650; OR = 1.60, P = 1.1 x 10(-14) for rs1160312). The one man in seven who harbors risk alleles at both 20p11.22 and AR (encoding the androgen receptor) has a sevenfold-increased odds of androgenic alopecia (OR = 7.12, P = 3.7 x 10(-15)).

| S-EPMC2672151 | biostudies-literature

Male pattern baldness and its association with coronary heart disease: a meta-analysis.

Project description:ObjectiveTo confirm the association between male pattern baldness and coronary heart disease (CHD).DesignMeta-analysis of observational studies.Data sourcesMedline and the Cochrane Library were searched for articles published up to November 2012 using keywords that included both 'baldness' and 'coronary heart disease' and the reference lists of those studies identified were also searched.Study selectionObservational studies were identified that reported risk estimates for CHD related to baldness. Two observers independently assessed eligibility, extracted data and assessed the possibility of bias.Data synthesisThe adjusted relative risk (RR) and 95% CI were estimated using the DerSimonian-Laird random-effect model.Results850 possible studies, 3 cohort studies and 3 case-control studies were selected (36 990 participants). In the cohort studies, the adjusted RR of men with severe baldness for CHD was 1.32 (95% CI 1.08 to 1.63, p=0.008, I(2)=25%) compared to those without baldness. Analysis of younger men (<55 or ?60 years) showed a similar association of CHD with severe baldness (RR 1.44, 95% CI 1.11 to 1.86, p=0.006, I(2)=0%). In three studies employing the modified Hamilton scale, vertex baldness was associated with CHD and the relation depended on the severity of baldness (severe vertex: RR 1.48 (1.04 to 2.11, p=0.03); moderate vertex: RR 1.36 (1.16 to 1.58, p<0.001); mild vertex: RR 1.18 (1.04 to 1.35, p<0.001)). However, frontal baldness was not associated with CHD (RR 1.11 (0.92 to 1.32, p=0.28)).ConclusionsVertex baldness, but not frontal baldness, is associated with an increased risk of CHD. The association with CHD depends on the severity of vertex baldness and also exists among younger men. Thus, vertex baldness might be more closely related to atherosclerosis than frontal baldness, but the association between male pattern baldness and CHD deserves further investigation.

| S-EPMC3641488 | biostudies-literature

Evidence for a functional interaction of WNT10A and EBF1 in male-pattern baldness.

Project description:More than 300 genetic risk loci have been identified for male pattern baldness (MPB) but little is known about the exact molecular mechanisms through which the associated variants exert their effects on MPB pathophysiology. Here, we aimed at further elucidating the regulatory architecture of the MPB risk locus on chromosome (chr.) 2q35, where we have previously reported a regulatory effect of the MPB lead variant on the expression of WNT10A. A HaploReg database research for regulatory annotations revealed that the association signal at 2q35 maps to a binding site for the transcription factor EBF1, whose gene is located at a second MPB risk locus on chr. 5q33.3. To investigate a potential interaction between EBF1 and WNT10A during MPB development, we performed in vitro luciferase reporter assays as well as expression analyses and immunofluorescence co-stainings in microdissected human hair follicles. Our experiments confirm that EBF1 activates the WNT10A promoter and that the WNT10A/EBF1 interaction is impacted by the allelic expression of the MPB risk allele at 2q35. Expression analyses across different hair cycle phases and immunhistochemical (co)stainings against WNT10A and EBF1 suggest a predominant relevance of EBF1/WNT10A interaction for hair shaft formation during anagen. Based on these findings we suggest a functional mechanism at the 2q35 risk locus for MPB, where an MPB-risk allele associated reduction in WNT10A promoter activation via EBF1 results in a decrease in WNT10A expression that eventually results in anagen shortening, that is frequently observed in MPB affected hair follicles. To our knowledge, this study is the first follow-up study on MPB that proves functional interaction between two MPB risk loci and sheds light on the underlying pathophysiological mechanism at these loci.

| S-EPMC8432770 | biostudies-literature

GWAS for male-pattern baldness identifies 71 susceptibility loci explaining 38% of the risk.

Project description:Male pattern baldness (MPB) or androgenetic alopecia is one of the most common conditions affecting men, reaching a prevalence of ~50% by the age of 50; however, the known genes explain little of the heritability. Here, we present the results of a genome-wide association study including more than 70,000 men, identifying 71 independently replicated loci, of which 30 are novel. These loci explain 38% of the risk, suggesting that MPB is less genetically complex than other complex traits. We show that many of these loci contain genes that are relevant to the pathology and highlight pathways and functions underlying baldness. Finally, despite only showing genome-wide genetic correlation with height, pathway-specific genetic correlations are significant for traits including lifespan and cancer. Our study not only greatly increases the number of MPB loci, illuminating the genetic architecture, but also provides a new approach to disentangling the shared biological pathways underlying complex diseases.

| S-EPMC5691155 | biostudies-literature

Male pattern baldness and risk of incident skin cancer in a cohort of men.

Project description:We examined the association between male-pattern baldness and risk of incident skin cancer, including invasive melanoma, invasive squamous cell carcinoma (SCC), and basal cell carcinoma (BCC) in a prospective analysis, based on 36,032 participants from the Health Professionals' Follow-up Study. In 1992, participants reported their status of male-pattern baldness at age 45 years by choosing from five crown-view pictograms based on Norwood's classification. Diagnosis of skin cancers was reported biennially and information on melanoma and SCC was pathologically confirmed. We identified 327 melanoma cases, 1324 SCC cases, and 8438 BCC cases during the follow-up. Male-pattern baldness was not significantly associated with risk of incident melanoma, but was significantly associated with increased risk of SCC and BCC. The multivariate-adjusted hazard ratio (HR) (95% confidence interval, CI) for the highest category of baldness (frontal plus severe vertex baldness) was 1.33 (1.06-1.68) for SCC (ptrend = 0.001) and 1.23 (1.12-1.35) for BCC (ptrend < 0.0001), compared with no baldness. Analyses by body sites found significant associations between frontal plus moderate to severe vertex baldness and risk of melanoma (HR = 1.83, 95% CI: 1.01-3.34) and SCC (HR = 1.30, 95% CI: 1.02-1.66) at head and neck. The associations were particularly stronger for scalp melanoma (HR = 7.15, 95% CI: 1.29-39.42) and scalp SCC (HR = 7.09, 95% CI: 3.84-13.08), but not for non-scalp head and neck sites. Information on body sites was not available for BCC. In conclusion, male pattern baldness may be associated with increased risk of skin cancer, but the associations may only exist for those occurring at head and neck, particularly at scalp.

| S-EPMC5061600 | biostudies-literature

Genome-wide association data on male-pattern baldness

Project description:The study comprises 1000Genomes imputed data for 581 MPB cases and 416 male controls. Cases are selected for age<40 and Hamilton-Norwood grade V-VII. Control include 270 males >60 years no signs of AGA (Hamilton-Norwood grade I).

| EGAS00001001354 | EGA

Evaluation of DNA variants associated with androgenetic alopecia and their potential to predict male pattern baldness.

Project description:Androgenetic alopecia, known in men as male pattern baldness (MPB), is a very conspicuous condition that is particularly frequent among European men and thus contributes markedly to variation in physical appearance traits amongst Europeans. Recent studies have revealed multiple genes and polymorphisms to be associated with susceptibility to MPB. In this study, 50 candidate SNPs for androgenetic alopecia were analyzed in order to verify their potential to predict MPB. Significant associations were confirmed for 29 SNPs from chromosomes X, 1, 5, 7, 18 and 20. A simple 5-SNP prediction model and an extended 20-SNP model were developed based on a discovery panel of 305 males from various European populations fitting one of two distinct phenotype categories. The first category consisted of men below 50 years of age with significant baldness and the second; men aged 50 years or older lacking baldness. The simple model comprised the five best predictors: rs5919324 near AR, rs1998076 in the 20p11 region, rs929626 in EBF1, rs12565727 in TARDBP and rs756853 in HDAC9. The extended prediction model added 15 SNPs from five genomic regions that improved overall prevalence-adjusted predictive accuracy measured by area under the receiver characteristic operating curve (AUC). Both models were evaluated for predictive accuracy using a test set of 300 males reflecting the general European population. Applying a 65% probability threshold, high prediction sensitivity of 87.1% but low specificity of 42.4% was obtained in men aged <50 years. In men aged ?50, prediction sensitivity was slightly lower at 67.7% while specificity reached 90%. Overall, the AUC=0.761 calculated for men at or above 50 years of age indicates these SNPs offer considerable potential for the application of genetic tests to predict MPB patterns, adding a highly informative predictive system to the emerging field of forensic analysis of externally visible characteristics.

| S-EPMC4441445 | biostudies-literature

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