Key points
- Epistasis describes interactions between genes that change how at least one gene is expressed.
- These changes to genes influence our physical traits, including our predisposition to diseases like Alzheimer’s, cardiovascular disease, diabetes, and cancer.
- Our researchers are working to advance epistasis detection to uncover more interactions and understand their role in complex diseases.
Imagine your doctor calls you to discuss the results of your genetic testing. They tell you your results indicate you are highly likely to develop Alzheimer’s disease. But not to worry, because they caught it early, you can start a personalised course of treatment tailored to your unique genetic makeup right away.
As strange as it sounds, scientists believe this future could within an arm’s reach. The study of epistasis – the interaction between genes that influences our physical traits – holds the key to unlocking new possibilities in medicine.
Studying epistasis could explain why some complex diseases often seem to affect people in random and unpredictable ways. It could also lead to more effective treatments for common complex diseases.
Researchers from our Australian e-Health Research Centre (AEHRC) are advancing our understanding of epistasis and its role in complex diseases.
Epistasis has therefore become a hot topic among geneticists.
Gene expression 101
To understand epistasis, it helps to know the basics of how genes work.
Genes are the blueprints for all living things. They are made up of DNA, passed from parent to child. This DNA contains instructions on how an organism should grow and function.
Humans have about 20,000 genes responsible for deciding our physical and biological traits.
Each gene carries the code for a specific function or trait, such as eye colour or blood type. While genes determine the possibilities for these traits, it is alleles that determine the specific expression of those traits.
Although the terms gene and allele are often used interchangeably, there is a difference. Alleles are subvariants of the same gene. Each person typically receives two alleles for every gene – one allele from their mother and one from their father.
These alleles work together to determine the resulting physical trait. For example, you might inherit an allele for brown eyes from your mother and one for blue eyes from your father. These alleles interact with each other to influence what colour eyes you will have – brown in this case, as brown eyes are a dominant trait.
These kinds of interactions between dominant, non-dominant and recessive alleles (known as non-epistatic gene interactions) are well studied and understood.
Epistatic interactions, on the other hand, are less well understood.
Epistasis: The secret life of genes
In epistatic interactions, the effects of one or more genes are suppressed or modified.
These changes in the way genes are expressed can influence an organism’s physical traits.
For example, all labrador retrievers inherit genes giving them either a brown or black coat, but a common epistatic interaction preventing their coat colour genes from being expressed gives some Labrador retrievers golden coats.
But not all epistatic interactions turn out to be this adorable.
Epistatic interactions have also been linked to human diseases like Alzheimer’s and cardiovascular disease, diabetes, and cancer.
Researchers believe studying more epistatic interactions will help them finally explain why some people develop diseases, while others who are genetically similar do not.
This mystery, known as the missing heritability problem, has plagued geneticists for decades.
The mystery of missing heritability
The missing heritability problem describes the fact that scientists still don’t know exactly how genes contribute to traits and diseases.
It’s also still unclear why some people develop diseases like Alzheimer’s, while others with similar genes do not.
To try and answer this question, scientists have conducted both twin and genome-wide association studies (GWAS).
GWAS involve analysing the genome (the whole set of DNA) of a large group of people in search of specific genes (called candidate genes). These are usually genes suspected of influencing a disease.
These studies aim to find a correlation between people with candidate genes and people with a disease.
Over time, however, scientists have found that the presence of candidate genes is not a reliable indication that someone will develop a disease.
Similarly, in twin studies, which analyse the DNA of closely related individuals (like twins), scientists have been unable to explain why one might develop a disease, while the other will not.
All of this strongly indicates that our predisposition to disease is determined by a combination of many different genes and their interactions.
From research to revolution
Epistasis research has potential to unlock incredible breakthroughs in medicine.
Studying epistatic interactions could help researchers find reliable genetic markers for common diseases.
This knowledge would allow health professionals to provide patients with precision care (highly individualised treatment) tailored to their unique genetic data.
It would also become easier for clinicians to identify patients’ predisposition to genetic diseases early, possibly even before symptoms emerge. This would help people diagnosed with genetic diseases access early treatment, intervention, and support.
However, researchers still have a long way to go.
Finding new epistatic interactions is extremely challenging due to the sheer number of gene combinations and statistical possibilities researchers must consider. After all, humans have 20,000 genes and endless possible combinations of epistatic interactions.
Researchers long considered it impossible to discover epistatic interactions responsible for common diseases. But advancements in technology like artificial intelligence (AI) and machine learning (ML) have renewed their hopes.
Detecting epistasis with cutting-edge tech
Our Genome Insights team are using the latest technologies to advance epistasis detection and bring us closer to understanding missing heritability.
In 2021 the team used ML to develop a pioneering software tool named BitEpi capable of processing large amounts of genomic data to map epistatic interactions between up to 4 genes.
So far, BitEpi and VariantSpark, a cloud-based genome analysis platform, have helped the team identify two new genetic variants associated with Alzheimer’s disease. They’ve also unearthed 95 new gene interactions that could influence the effects of variants in Alzheimer’s.
The team has united global epistasis experts to evaluate the most effective methods of epistasis detection, while fostering the free exchange of knowledge and collaboration.
Big challenges, even bigger possibilities
Although epistasis research still faces many challenges, our researchers are determined to find innovative solutions. As new technologies emerge, the promise of epistasis to revolutionise disease prediction, prevention and treatment will only increase.