Evidence map›Paper›PMID 21197618›Full record

ArticleHuman genetics2011

Model-based prediction of human hair color using DNA variants.

Wojciech Branicki, Fan Liu, Kate van Duijn, Jolanta Draus-Barini, Ewelina Pośpiech, Susan Walsh, Tomasz Kupiec, Anna Wojas-Pelc, Manfred Kayser

Open access · hybridAbstract read
In one paragraph

Article in Human genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 1 pooled it
6.4field-weighted citation impact, top 3% 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

46 citing papers in PubMed, 1 synthesis or guideline pooled it, 197 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Forensic genetics in the omics era.Nature reviews. Genetics · 2026
    Review
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  17. LitGen: Genetic Literature Recommendation Guided by Human Explanations.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2020
    Article
  18. Review
  19. Article
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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

9 authors at 3 institutions in 2 countries.

Wojciech BranickiSection of Forensic Genetics, Institute of Forensic Research, Westerplatte 9, 31-033, Kraków, Poland.
Fan Liu
Kate van Duijn
Jolanta Draus-Barini
Ewelina Pośpiech
Susan Walsh
Tomasz Kupiec
Anna Wojas-Pelc
Manfred Kayser
Centralne Laboratorium Kryminalistyczne Policji · PLErasmus MC · NLJagiellonian University · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Predicting complex human phenotypes from genotypes is the central concept of widely advocated personalized medicine, but so far has rarely led to high accuracies limiting practical applications. One notable exception, although less relevant for medical but important for forensic purposes, is human eye color, for which it has been recently demonstrated that highly accurate prediction is feasible from a small number of DNA variants. Here, we demonstrate that human hair color is predictable from DNA variants with similarly high accuracies. We analyzed in Polish Europeans with single-observer hair color grading 45 single nucleotide polymorphisms (SNPs) from 12 genes previously associated with human hair color variation. We found that a model based on a subset of 13 single or compound genetic markers from 11 genes predicted red hair color with over 0.9, black hair color with almost 0.9, as well as blond, and brown hair color with over 0.8 prevalence-adjusted accuracy expressed by the area under the receiver characteristic operating curves (AUC). The identified genetic predictors also differentiate reasonably well between similar hair colors, such as between red and blond-red, as well as between blond and dark-blond, highlighting the value of the identified DNA variants for accurate hair color prediction.

Indexed as

AlgorithmsLogistic ModelsPolymorphism, Single NucleotideDNAFemaleGenotypeGuanine Nucleotide Exchange FactorsHair ColorHumansInterferon Regulatory Factor-4Interferon Regulatory FactorsMaleMonophenol MonooxygenaseOdds RatioPhenotypePolandDNAEXOC2 protein, humanGuanine Nucleotide Exchange FactorsHERC2 protein, humanInterferon Regulatory Factor-4Interferon Regulatory FactorsMonophenol MonooxygenaseReceptor, Melanocortin, Type 1Ubiquitin-Protein LigasesVesicular Transport Proteins

Identifiers

PMID21197618
PMCPMC3057002
OpenAlexW2070303561

What OpenQuestion holds

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LicenceCC BY-NC
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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.