Facial morphology is highly variable, both within and among human populations, and a sizable portion of this variation is attributable to genetics. Genetic factors play an important role in shaping human facial features.
A new study of the genetics underlying facial features finds that East Africans have some unique facial genetics and some that are shared with Europeans. The findings, published August 19th in PLOS Genetics, add to our understanding of how genetics shape the human face.
Over the last decade, studies have identified numerous genes associated with various facial traits. The vast majority of these studies have focused on European or Asian populations, while African populations have been underrepresented.
Map of East Africa
The Study: Genetic Basis of Facial Morphology in East Africans
In the present study, we applied the global-to-local phenotyping approach to a previously collected East African sample reported by Cole et al. [18]. We performed GWAS of facial morphology in 2,595 East Africans and compared results with those from an independent GWAS of 8,246 European-ancestry participants.
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To date, at least 17 genome-wide association studies (GWAS) of facial traits have been performed, including 11 in European [3-13], two in Asian [14-16], one in Latin American [17], one in African [18], and two in mixed-ancestry populations [19,20].
- Tanzania discovery cohort: Written informed consent was obtained from all Tanzanian study participants or their parents as appropriate.
- European replication cohorts: Institutional review board approval was obtained at each recruitment site.
The African cohort included 3,555 participants from the Mwanza region of Tanzania comprising 1,582 males and 1,973 females aged 3 to 21 years (S1 Fig). A total of 960 participants were excluded from analysis based on exclusion criteria, resulting in 2,595 unrelated participants that were retained for the genetic analysis.
The team analyzed 2,595 3D facial images collected from Tanzanian children and scanned their genomes to find genetic sites linked to specific features.
Phenotyping and Genetic Analysis
Phenotyping was performed using the pipeline described in Claes et al. [10]. The 3D surface images were imported into Matlab in wavefront.obj format, and processed using the “MeshMonk” open-source package [21].
To generate facial shape phenotypes for genetic analysis, we performed a global-to-local facial segmentation process. This phenotyping method resulted in 63 partially overlapping facial segments arranged across five levels in a bifurcated hierarchical manner (S3A Fig).
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The genetic association between each SNP and variation in each of the 63 facial segments (each represented by a set of PCs) was tested using canonical correlation analysis (CCA) under the additive genetic model as implemented in the “canoncorr” function in Matlab.
Genome scans of these multivariate shape phenotypes revealed significant (p < 2.5 × 10−8) signals at 20 loci, which were enriched for active chromatin elements in human cranial neural crest cells and embryonic craniofacial tissue, consistent with an early developmental origin of the facial variation.
The researchers identified 20 regions on the genome associated with face shape. Several of these genetic variants play a role in embryonic cells that give rise to facial structures very early in life -- around 3 to 6 weeks after conception.
Genetics: It's Written On Your Face
Cross-Population Comparisons and Shared Genetic Basis
Cross-population comparisons indicated 10 association signals were shared with Europeans (seven sharing the same associated SNP), and facilitated fine-mapping of causal variants at previously reported loci.
Increasing the diversity of these analyses can reveal novel associations and cross-population analyses can help deepen our understanding of known genetic associations. We therefore performed a genome scan of 3D facial features in African children from Tanzania and then compared our results to Europeans.
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We found 20 regions of the genome associated with facial shape in Tanzanian children, 10 of which were also present in Europeans, indicating evidence for a partly shared genetic basis for human facial shape across populations.
Shaffer adds, "Our findings confirm that the genes connected to human facial features are basically the same across populations. Observed differences were mostly explained by how frequently an allele occurs in a given population.
In addition, about half of the genetic associations observed in Tanzanians were not present in Europeans, and some of the shared signals differed between populations in the specific genetic variants associated or specific facial traits affected.
Facial Variation
Implications and Further Understanding
The new study in Tanzanians uncovered novel sites and genes potentially related to face shape and also advanced the understanding of sites that were already recognized in Europeans. Overall, these findings shed light on the genetic and biological basis underpinning the diversity of human facial structures.
Weinberg adds, "Most published genetic studies of human facial traits have been limited to individuals of predominantly European ancestry, and African populations have been particularly under-represented in this field.
By comparing populations, we were able to uncover genetic signals that would otherwise remain obscured and narrow the field of genetic variants that are functionally impacting facial traits.”
