ArticleNature communications2017
GWAS for male-pattern baldness identifies 71 susceptibility loci explaining 38% of the risk.
Article in Nature communications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 50 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
50 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Androgenetic alopecia risk in allergic rhinitis: A cohort study of immune and antihistamine effects.The World Allergy Organization journal · 2026Article
- Androgenetic Alopecia in Women: A Narrative Review of Pathophysiology, Clinical Evaluation, and Treatments.American journal of clinical dermatology · 2026Review
- The Polygenic Architecture of Human Diseases Affecting the Hair Follicle.The Journal of investigative dermatology · 2026Review
- Double Knockdown of the Androgen Receptor Target Genes DKK1 and SFRP1 Does Not Potentiate the Hair Growth-Promoting Effect of SFRP1 Silencing in Healthy Human Hair Follicles Ex Vivo.International journal of molecular sciences · 2026Article
- Federated single-cell QTL meta-analysis reveals novel disease mechanisms.bioRxiv : the preprint server for biology · 2026Article
- The Genetic Landscape of Androgenetic Alopecia: Current Knowledge and Future Perspectives.Biology · 2026Review
- Double Challenges for Scalp Health: A Review of the Pathogenesis and Treatment Strategies of Coexistence of Seborrheic Dermatitis and Androgenetic Alopecia.Dermatology research and practice · 2026Review
- Use of genetics in the prediction of success in male pattern hair loss therapy and mechanistic studies.Frontiers in pharmacology · 2026Review
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- High cell-type specificity of eQTLs revealed by single-nucleus analyses of brain and blood.bioRxiv : the preprint server for biology · 2025Article
- Androgenetic Alopecia and Risks of Overall and Aggressive Prostate Cancer: An Updated Systematic Review and Meta-Analysis.Cancers · 2025Review
- Androgenetic alopecia.Nature reviews. Disease primers · 2025Review
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- The polygenic architecture of hidradenitis suppurativa reveals signaling mechanisms that implicate epithelial remodeling.medRxiv : the preprint server for health sciences · 2025Article
- Single-Nucleus and Bulk RNA Sequencing Reveals the Involvement of Natural Killer and CD8Journal of inflammation research · 2025Article
- Hydrogel forming microneedles loaded with VEGF and Ritlecitinib/polyhydroxyalkanoates nanoparticles for mini-invasive androgenetic alopecia treatment.Bioactive materials · 2024Article
- Prioritizing susceptibility genes for the prognosis of male-pattern baldness with transcriptome-wide association study.Human genomics · 2024Article
- Association study reveals a susceptibility locus with male pattern baldness in the Han Chinese population.Frontiers in genetics · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
16 authors.
Funding
Abstract
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.
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