Digenic inheritance: a key mechanism for understanding rare diseases
27 August 2021

Approximately 30 million Americans and 30 million Europeans have a rare disease [1]. These pathologies represent a major challenge in medicine and account for huge healthcare costs worldwide. Additionally, there are enormous challenges for healthcare providers in establishing accurate diagnoses for patients because rare diseases are often related to complex forms of genetic inheritance.

What is a Digenic Inheritance?

Digenic inheritance (DI) is a mechanism that occurs when the interaction of two genes is required for the expression of a phenotype. In this situation, mutations in at least one copy of each gene are required for the expression of a phenotype, and may be the cause of the onset of a rare disease.

Over 50 years ago researchers suggested that there would be many human disease pedigrees showing reduced penetrance when treated in genetic analysis as monogenic, but that the inheritance could be explained more accurately by a two-locus model [2].

For this reason, modern medicine requires experimental and computational tools in order to be able to correctly detect the interaction between two different genes.

The impact of digenic inheritance on rare diseases

There are many situations that fit the definition of digenic inheritance. 

“True” digenic inheritance occurs if the patient will only manifest the disease when 2 mono-allelic mutations, on separate genes, are co-inherited. This means that the single mutation does not correspond to a pathologic phenotype, which is found only if the two mutations happen simultaneously.

In a slightly different scenario, called “composite” digenicity, inheritance of a single primary mutation is the main reason behind the manifestation of the disease, and a second mutation exacerbates the clinical picture, often causing a broad phenotypic spectrum related to the second mutation’s features. 

Finally, there’s a chance that independent segregation of 2 mutations in separate linked or unlinked genes associated with distinct monogenic diseases, happens at the same time, resulting in a new phenotype [3]. These cases are referred to as “dual diagnosis”. Given the complexity of the human genome, most of the time the classification isn’t so simple and rigorous, as the borders of the different scenarios may be blurred.

The discovery of the impact of digenic inheritance on rare disease is relatively recent: the first report of DI in a human disease was in 1994 for retinitis pigmentosa, a degenerative disorder causing progressive loss of vision caused by mutations in two unlinked loci: the photoreceptor-specific genes ROM1 and peripherin/RDS, in which only double heterozygotes develop retinitis pigmentosa [4]. 

The inclusion of data from multiple pedigrees, and the known interaction between the protein expressed by the studied genes made the hypothesis convincing.

In the last 25 years there have been many reports of disease caused by digenic inheritance, and it’s worth mentioning the two most important examples.

The first one is Bardet–Biedl syndrome, a genetically heterogeneous disorder characterized by multiple clinical features that include pigmentary retinal dystrophy, polydactyly, obesity, developmental delay, and renal defects [5]. The latter is deafness, which is an excellent candidate for the study of digenic inheritance because there is a great amount of known genes that exhibit both monogenic and digenic inheritance. 

Additionally, considerable information is known about protein complexes that function in the inner ear: for this reason, pairs of proteins in these complexes are good candidates.  Many different combinations of mutations related to deafness were found, and perhaps the most compelling among these is the combination of CDH23 and PCDH15 causing digenic Usher syndrome, resulting in a combination of hearing loss and visual impairment [6].

The revolution of Next generation Sequencing technologies

There is no doubt that the emergence of Next Generation Sequencing technologies (NGS) have been a turning point for the advancement in our understanding of rare diseases. 

The emergence of NGS radically changed the diagnostic workflow by providing a quick, powerful, and low-cost alternative for genetic analysis. In less then a few weeks NGS-based tools can identify a single causative gene, or, with a slightly greater difficulty, a couple of genes, and help to establish an accurate and fast diagnosis.

This new workflow has drastically reduced waiting times, shortening the quest that many patients had to embark on to find a prognosis [1]. Nowadays it is common to use these powerful tools as part of routine diagnostic processes.

The power of next generation sequencing to define the whole spectrum of variants of a phenotype will be crucial for the discovery of causes for digenic disease. After identifying the mutation that appears to be the main and only reason for the expression of the disease, additional analyses can be carried out with the huge amount of data already available in order to find possible interaction between different genes. In other words, NGS makes it possible to sequence many genes simultaneously thus disease-relevant mutations in two genes can be discovered in a single experiment.

NGS does not solve the problem of deciding which mutations are relevant to the phenotype, and doing so is more difficult when the inheritance is digenic as compared to monogenic. It remains to be proven that the combination of two mutations is, indeed, the cause of disease rather than the simple co-occurrence of two mutations by chance [7].

A glimpse into the future of treatment for rare genetic diseases

Despite the difficulties in the discovery and treatment of pathologies caused by digenic inheritance, progress and innovation in the field of sequencing and bioinformatics technologies will continue to offer new resources for the millions of patients affected by rare diseases. 

Digenic Variant Interpretation

enGenome is at the cutting edge of new science and technology for understanding digenic variants. Our algorithm called DIVAs, the (Digenic Variant Interpreter,) implements an innovative AI-based approach to identify and interpret digenic variants.

If you are interested in DIVAs you can watch our live presentation at ESHG21 on Saturday, August 28th at 1:45 PM CEST. enGenome’s Chief Science Officer, Dr. Susanna Zucca will present a special session on the DIVAs algorithm.

Written by Tommaso Zanoni


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