Pinpointing Rare Diseases with Facial Analysis and Phenotyping Technology

Phenotyping, describing the patient on a clinical level, has emerged as a necessary step in helping clinicians diagnose rare and ultra-rare genetic diseases. 

Dekel Gelbman

Diagnosing rare and ultra-rare genetic diseases can be extremely difficult for geneticists. The diagnostic odyssey, from the primary point of care, through the specialty clinics and to the molecular testing labs, can take up to 7.6 years to come to an appropriate diagnosis. According to recent survey results, patients living with rare diseases visit an average of 7.3 physicians before receiving an accurate diagnosis. This process can be compared to solving a mystery, with the geneticist playing the role of the detective, sifting through many clues to come to a final answer.

With over 7,000 rare diseases to consider, the task of diagnosing these diseases is daunting, even for specialists, let alone for physicians with no specific genetics training. Linking various, and seemingly unrelated, symptoms to an underlying genetic disorder is not a simple process. As a result, rare disease patients experience many years of frustration while searching for answers. Patients and families caught in this diagnostic odyssey suffer from emotional and financial distress, and perhaps most importantly, negative health outcomes. Early and broader identification of these diseases can improve the quality of life of rare disease patients, ultimately leading to better outcomes.


When it comes to diagnosing these rare and ultra-rare diseases, geneticists rely on their own experience, a vast sea of literature and genotypic data. With all the advances in genomic sequencing, we now have the ability to recognize thousands upon thousands of genetic variants that may be disease-causing. To analyze these results, the lab and clinician must sift through this list to find the most clinically relevant variants and, hopefully, the diagnosis.

To help with this process, phenotyping has emerged as a necessary step. Phenotypic information describes the patient on a clinical level, such as having a broad neck or cognitive delay. As it is typically a result of a patient’s genetic code, this phenotypic information is complementary to genotype information. It is almost impossible to identify which of the patient’s genes are being expressed and may be the root for disease symptoms without precise and comprehensive phenotypic information. Knowing the phenotypic information allows geneticists to highlight clinically relevant syndromes and genes for consideration.

All this new data, both genomic and phenotypic, has resulted in a need for ways to structure and store this information and technologies that can analyze it. In the rare disease space, facial analysis technology and Human Phenotyping Ontology (HPO) has become the standard approach for describing phenotypic features using a structured and controlled vocabulary. This has paved the way for researchers to find correlations between phenotypes, syndromes, and genes.

The work correlating phenotypic traits with disease-causing genetic variants is especially important. Labs and bioinformatics are sifting through the variants classified as high significance and then checking them one by one to match their clinical description and mode of inheritance. By integrating accurate and comprehensive phenotype information to the filtering and prioritization process, the clinician can narrow down the list to very few candidate causative variants to consider.

Phenotyping technologies support this work not only by capturing phenotypes in a structured way such as using HPO or facial analysis, but use the correlative data to highlight syndromes and clinically relevant genetic variants that are likely causes of the patient’s symptoms. When used in conjunction with molecular testing, this data increases confidence and saves time during diagnosis. For patients who have no access to molecular tests, phenotyping technologies also offer an affordable method for highlighting relevant syndromes to help the clinical evaluation of these patients, in turn providing answers to families and an end to the long diagnostic odyssey.

There is a great need for access to information about rare diseases, especially information that reveals correlations between phenotypic traits and disease-causing genetic variants. Phenotyping and facial analysis technologies are now being used to make progress in the genetics community to connect these dots, ultimately changing the lives of patients and the ways clinicians diagnose them. Marrying this data in a meaningful way will make significant strides in reducing the timeline of the diagnostic odyssey, giving families the crucial answers they need.

Dekel Gelbman is the CEO at FDNA, a Boston-based company that has developed the proprietary Facial Dysmorphology Novel Analysis technology. 


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