Human face is the mirror to our brains. Face is an important part of the body. We identify ourselves
and others based on the facial characteristics. Human face gives identity to an individual. The embryonic
development of human face involves complex interplay of large number of developmental events. Hence it is but
obvious that face development would be affected in dysmorphic syndromes resulting from mutations in
developmental genes. Most of the human dysmorphic syndromes have typical facial characteristics as an important
component. The classic text on dysmorphic syndromes by Gorlin has been suitably titled as “Syndromes of
Head and Neck”. Most descriptions of dysmorphic syndromes include subjective information provided by
individual investigators and this leads to lot of confusion for use in clinical practice. There have been many
efforts to standardize the terms used in dysmorphology including the special issue of American Journal of
Medical Genetics on “Elements of morphology”. However the ‘subjectiveness’ in the assessment is always a
confounding factor. Hence there have been efforts towards introducing ‘objectiveness’ in dysmorphic feature
reporting. The initial attempts involved use of two dimensional photographs of individuals. Landmarks
were plotted on the photographs at identifiable sites like ‘corner of mouth’, ‘tip of nose’ etc. and then a
complex statistical analysis would be used to differentiate between ‘normal’ and ‘dysmorphic’ facies. Later the
investigators used three dimensional images and landmark acquisition which further refined this technique.
Recently a mobile application called Face2Gene has been extensively used for facial recognition of various
dysmorphic syndromes. Facial gestalt recognition is an art perfected over years of practice but beginners can be
significantly benefitted by the use of such apps/software which can aid in diagnosis as well as plan for genetic
investigations.
The ability to include ‘objectiveness’ in face recognition has opened a Pandora’s box of possibilities.
Face recognition has been used in mobile phones as passwords as well as by law enforcement agencies to
track and find criminals. The idea that study of human genetic makeup could help in prediction of ‘human
face’ appears to be science fiction but the same has been recently demonstrated in an article published in
Proceedings of National Academy of Sciences (PNAS), USA. The authors have used genetic information
from whole genome sequencing data to predict the facial phenotype as well as other demographic details
of an individual like eye colour, skin colour, ethnicity, etc with considerable accuracy. This has resulted
in renewed discussions about privacy of human genomic data and possible misuse of such techniques for
unlawful activities as well as for planning of ‘designer babies’ with beautiful facial characteristics. As is
true with any new breakthrough in science, it remains to be seen how the technology shapes itself in the
future.
As clinicians and medical geneticists, it is our responsibility to shape such discussions in future so that the new
developments are used for better care of patients and families. ‘Genetic clinics’ is an effort towards achieving this goal
through dissemination of useful and accurate information from the complex world of human genetics to the clinicians in
practice.
