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

August, 2022

Highlights

• 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

Summary

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.