Evidence map›Paper›PMID 26508577›Full record

ArticleEuropean journal of human genetics : EJHG2016

Prediction of male-pattern baldness from genotypes.

Fan Liu, Merel A Hamer, Stefanie Heilmann, Christine Herold, Susanne Moebus, Albert Hofman, André G Uitterlinden, Markus M Nöthen, Cornelia M van Duijn, Tamar Ec Nijsten and 1 more

Open access · bronzeAbstract read
In one paragraph

Article in European journal of human genetics : EJHG, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 65 citations in OpenAlex.

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  14. Male-pattern hair loss: Comprehensive identification of the associated genes as a basis for understanding pathophysiology.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 5 institutions in 3 countries.

Fan LiuDepartment of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.ORCID 0000-0001-9241-8161
Merel A HamerDepartment of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.
Stefanie HeilmannDepartment of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany.
Christine HeroldGerman Center for Neurodegenerative Disease (DZNE), Bonn, Germany.
Susanne MoebusInstitute of Medical Informatics, Biometry, and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany.
Albert HofmanDepartment of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.
André G UitterlindenDepartment of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.
Markus M NöthenDepartment of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany.
Cornelia M van DuijnDepartment of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.
Tamar Ec NijstenDepartment of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.
Manfred KayserDepartment of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.
Erasmus MC · NLUniversity of Bonn · DEChinese Academy of Sciences · CNGerman Center for Neurodegenerative Diseases · DEUniversity of Duisburg-Essen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

GenotypeAdultAgedAlopeciaCase-Control StudiesGenetic LociHumansMaleMiddle AgedPolymorphism, Single Nucleotide

Identifiers

PMID26508577
PMCPMC4867459
OpenAlexW1851760373

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.