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. 2023 Jan 3;14(1):136.
doi: 10.3390/genes14010136.

Advancement in Human Face Prediction Using DNA

Aamer Alshehhi  1   2 , Aliya Almarzooqi  3 , Khadija Alhammadi  3 , Naoufel Werghi  4 , Guan K Tay  2   5   6 , Habiba Alsafar  1   2   7
Affiliations

Advancement in Human Face Prediction Using DNA

Aamer Alshehhi et al. Genes (Basel). .

Abstract

The rapid improvements in identifying the genetic factors contributing to facial morphology have enabled the early identification of craniofacial syndromes. Similarly, this technology can be vital in forensic cases involving human identification from biological traces or human remains, especially when reference samples are not available in the deoxyribose nucleic acid (DNA) database. This review summarizes the currently used methods for predicting human phenotypes such as age, ancestry, pigmentation, and facial features based on genetic variations. To identify the facial features affected by DNA, various two-dimensional (2D)- and three-dimensional (3D)-scanning techniques and analysis tools are reviewed. A comparison between the scanning technologies is also presented in this review. Face-landmarking techniques and face-phenotyping algorithms are discussed in chronological order. Then, the latest approaches in genetic to 3D face shape analysis are emphasized. A systematic review of the current markers that passed the threshold of a genome-wide association (GWAS) of single nucleotide polymorphism (SNP)-face traits from the GWAS Catalog is also provided using the preferred reporting items for systematic reviews and meta-analyses (PRISMA), approach. Finally, the current challenges in forensic DNA phenotyping are analyzed and discussed.

Keywords: face landmarks; forensic DNA phenotyping (FDP); genome wide association studies (GWAS); single nucleotide polymorphism (SNP).

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Conflict of interest statement

The authors declare that they have no competing interest.

Figures

Figure 1
Figure 1
Literature review stages using PRISMA approach.
Figure 2
Figure 2
Population ancestries in 19 research studies investigating SNP-face morphology [91,146,154,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172]. These percentages include both discovery and replication samples.
Figure 3
Figure 3
Percentage of SNPs that met the GWAS significance threshold in the GWAS Catalog according to six facial regions (Face, forehead, nose, mouth, lip, and chin/lower face). “Face” indicates traits that were associated with multiple facial regions. Numbers on each bar reflect the number of the associations for each facial region.
See this image and copyright information in PMC

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