Look-alike humans identified by facial recognition algorithms show genetic similarities

• Published in: Cell reports (Cambridge) 2022-08, Vol.40 (8), p.111257, Article 111257
• Main Authors: Joshi, Ricky S., Rigau, Maria, García-Prieto, Carlos A., Castro de Moura, Manuel, Piñeyro, David, Moran, Sebastian, Davalos, Veronica, Carrión, Pablo, Ferrando-Bernal, Manuel, Olalde, Iñigo, Lalueza-Fox, Carles, Navarro, Arcadi, Fernández-Tena, Carles, Aspandi, Decky, Sukno, Federico M., Binefa, Xavier, Valencia, Alfonso, Esteller, Manel
• Format: Article
• Language: English
• Subjects: epigenome; face; genome; look-alike humans; microbiome; recognition algorithms
• ISSN: 2211-1247; 2211-1247
• DOI: 10.1016/j.celrep.2022.111257

The human face is one of the most visible features of our unique identity as individuals. Interestingly, monozygotic twins share almost identical facial traits and the same DNA sequence but could exhibit differences in other biometrical parameters. The expansion of the world wide web and the possibility to exchange pictures of humans across the planet has increased the number of people identified online as virtual twins or doubles that are not family related. Herein, we have characterized in detail a set of “look-alike” humans, defined by facial recognition algorithms, for their multiomics landscape. We report that these individuals share similar genotypes and differ in their DNA methylation and microbiome landscape. These results not only provide insights about the genetics that determine our face but also might have implications for the establishment of other human anthropometric properties and even personality characteristics. [Display omitted] •Facial recognition algorithms identify “look-alike” humans for multiomics studies•Intrapair look-alikes share common genetic sequences such as face trait variants•DNA methylation and microbiome profiles only contribute modestly to human likeness•The identified SNPs impact physical and behavioral phenotypes beyond facial features We recognize each other by relying on our face uniqueness. However, there are humans with uncanny resemblance. Joshi et al. reported that look-alike pairs identified by facial recognition algorithms share genotypes but not DNA methylomes and microbiomes. The identified SNPs also provide a readout of other anthropomorphic and behavioral characteristics.