Combined genome-wide association study of facial traits in Europeans increases explained variance and improves prediction

Facial appearance, one of the most recognizable and heritable human traits, exhibits substantial variation across individuals within and between populations due to its complex genetic underpinning, which remains largely elusive. Here, we report a combined genome-wide association study (C-GWAS) of 946 facial features derived from 44 landmarks obtained from 3D digital facial images of 11,662 individuals of European descent. We identify 253 unlinked single nucleotide polymorphisms (SNPs) across 188 distinct genetic loci significantly associated with facial variation, including 64 SNPs at 62 novel loci and 33 novel SNPs within 29 previously reported face loci that are in very low LD with the previously reported top SNPs. Together, these SNPs account for up to 7.9% of the facial variation per trait, marking an average 2.25-fold increase over previous estimates. Cross-ancestry replication in 9,674 Chinese confirms the effect of 70% of these SNPs. A 382-SNPs prediction model of five nose traits achieves an AUC of 0.67 for individual re-identification from nose images. DNA predicted faces of archaic humans differ more from those of Europeans than from Africans. In genetically modelled Neanderthal faces, 15 of 16 DNA-predicted facial features are in line with skull evidence. Ten DNA-predicted facial features differentiate Neanderthals from Denisovans. Overall, this study substantially enhances our genetic understanding of human facial variation and provides improvements of genetic face prediction in modern and archaic humans.

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Publication Details

Journal
Nature Communications
Published
2025-07-16
DOI
https://doi.org/10.1038/s41467-025-61761-7
Citations
4
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
7.27

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article

Combined genome-wide association study of facial traits in Europeans increases explained variance and improves prediction

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4 citations
Nature Communications
Genetic Associations and Epidemiology
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article

Combined genome-wide association study of facial traits in Europeans increases explained variance and improves prediction

Tim D. Spector, Tamar E. C. Nijsten, Luba M. Pardo, Ziyi Xiong, Pirro G. Hysi, Fernando Rivadeneira, Stephen Richmond, Gennady V. Roshchupkin, André G. Uitterlinden, M. Arfan Ikram, Xianjing Liu, Manfred Kayser, Eppo B. Wolvius, Mohsen Ghanbari, Fan Liu, Sijia Wang, Yi Li, Haojie Lu
article en
4 citations

Abstract

Facial appearance, one of the most recognizable and heritable human traits, exhibits substantial variation across individuals within and between populations due to its complex genetic underpinning, which remains largely elusive. Here, we report a combined genome-wide association study (C-GWAS) of 946 facial features derived from 44 landmarks obtained from 3D digital facial images of 11,662 individuals of European descent. We identify 253 unlinked single nucleotide polymorphisms (SNPs) across 188 distinct genetic loci significantly associated with facial variation, including 64 SNPs at 62 novel loci and 33 novel SNPs within 29 previously reported face loci that are in very low LD with the previously reported top SNPs. Together, these SNPs account for up to 7.9% of the facial variation per trait, marking an average 2.25-fold increase over previous estimates. Cross-ancestry replication in 9,674 Chinese confirms the effect of 70% of these SNPs. A 382-SNPs prediction model of five nose traits achieves an AUC of 0.67 for individual re-identification from nose images. DNA predicted faces of archaic humans differ more from those of Europeans than from Africans. In genetically modelled Neanderthal faces, 15 of 16 DNA-predicted facial features are in line with skull evidence. Ten DNA-predicted facial features differentiate Neanderthals from Denisovans. Overall, this study substantially enhances our genetic understanding of human facial variation and provides improvements of genetic face prediction in modern and archaic humans.

Nature CommunicationsVol. 16(1)
King's College London (GB), Chinese Academy of Sciences (CN), Erasmus MC (NL), Shanghai Institute of Nutrition and Health (CN), Cardiff University (GB), Erasmus University Rotterdam (NL)
European Commission, University of Bristol, ZonMw, Erasmus Universiteit Rotterdam, Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Medical Research Council
Openalex Percentile: Top 3%
Genetic Associations and Epidemiology
7.27
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