| Title |
Genetics of the human face: Identification of large-effect single gene variants
|
|---|---|
| Published in |
Proceedings of the National Academy of Sciences of the United States of America, January 2018
|
| DOI | 10.1073/pnas.1708207114 |
| Pubmed ID | |
| Authors | |
| Abstract |
To discover specific variants with relatively large effects on the human face, we have devised an approach to identifying facial features with high heritability. This is based on using twin data to estimate the additive genetic value of each point on a face, as provided by a 3D camera system. In addition, we have used the ethnic difference between East Asian and European faces as a further source of face genetic variation. We use principal components (PCs) analysis to provide a fine definition of the surface features of human faces around the eyes and of the profile, and chose upper and lower 10% extremes of the most heritable PCs for looking for genetic associations. Using this strategy for the analysis of 3D images of 1,832 unique volunteers from the well-characterized People of the British Isles study and 1,567 unique twin images from the TwinsUK cohort, together with genetic data for 500,000 SNPs, we have identified three specific genetic variants with notable effects on facial profiles and eyes. |
Login to access the Attention Digest and the Sentiment Analysis related to this output.
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 20% |
| India | 3 | 10% |
| United Kingdom | 3 | 10% |
| Ukraine | 1 | 3% |
| Netherlands | 1 | 3% |
| Japan | 1 | 3% |
| Spain | 1 | 3% |
| Papua New Guinea | 1 | 3% |
| Unknown | 13 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 22 | 73% |
| Scientists | 7 | 23% |
| Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 137 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 23 | 17% |
| Student > Ph. D. Student | 17 | 12% |
| Student > Master | 17 | 12% |
| Student > Bachelor | 14 | 10% |
| Other | 7 | 5% |
| Other | 20 | 15% |
| Unknown | 39 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 34 | 25% |
| Agricultural and Biological Sciences | 23 | 17% |
| Medicine and Dentistry | 17 | 12% |
| Computer Science | 5 | 4% |
| Neuroscience | 4 | 3% |
| Other | 11 | 8% |
| Unknown | 43 | 31% |