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Rare Diseases February 2019

Data-Driven Medicine is a big step forward for rare diseases

Rare disease diagnosis has been improved with the introduction of technologies such as genomics and artificial intelligence, which help clinicians analyse results more efficiently.


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Lewis Darnell

Clinical Scientist and Deputy Quality Manager, Molecular Genetics Department, Nottingham University Hospitals NHS Trust

“It’s impossible to overemphasise the importance of speedy diagnosis for anyone with a medical condition”, says Lewis Darnell, Clinical Scientist and Deputy Quality Manager in the Molecular Genetics Department within Nottingham University Hospitals NHS Trust. Unfortunately, in the area of rare disease, this can take a long time. “Until recently, approximately 30% of patients who see a specialist geneticist will usually receive a quick diagnosis, but many wait much longer, and it has been estimated that up to 50% won’t receive a diagnosis at all”.

This technology helps us work out where to direct our attention.

Being stranded in medical limbo takes an unbearable emotional toll. Parents of babies with rare diseases, for example, want a rapid diagnosis to relieve their worry and open up potential treatment options. “In my experience, people want to put a name to their condition — or their child’s condition — as soon as possible,” says Darnell.

Fear of the unknown creates anxiety

“An unnamed condition is an unknown condition, and fear of the unknown creates uncertainty and anxiety. For example, how might the condition progress? What other complications might arise? And if the patient is your child, how will you meet their future medical needs? How might you have to change your life in order to adapt to their condition? Or — frankly — how long will they live? It’s an emotional tightrope.”

Rare diseases can cost families huge sums

From a clinician’s point of view, it stands to reason that it’s a lot easier to treat patients who have an easily recognised condition. “If doctors aren’t sure what they are looking for, however, it means more hospital visits for patients, more monitoring and more tests,” says Darnell. “And that’s not a good situation for either the patients or their loved ones.” It can also be expensive, putting increased financial pressure on an already struggling health system.

Deep genome analysis is more efficient

In recent years, however, research into rare diseases has been transformed by genome sequencing — the mapping of a person’s entire genetic code. Before this science became available, clinicians could only test a few genes at a time, which was a lengthy process that often caused a delay in diagnosis. “But now genome sequencing allows us to gather information on nearly all of a patient’s genes in a single test,” says Darnell. “That’s been a big step forward.” It’s also a more financially sustainable solution.

There is a limited number of scientists to analyse all data

Even so, it did have a downside. As genome sequencing progressed, it began returning millions of genetic variations — or ‘variants’ — that might be responsible for causing a patient’s condition. That’s an unworkable amount of data for clinicians to study, particularly when only one or two variants might be the culprits. “Analysing that amount of information is quite impractical because there are a limited number of Clinical Scientists in the country,” says Darnell. “We simply don’t have the resources to look at thousands of variants individually.”

Artificial intelligence narrows the search

Thankfully, new AI technology is now available, which allows these results to be analysed and filtered more efficiently. “This technology helps us work out where to direct our attention,” explains Darnell, who points out that Data-Driven Medicine is beginning to make a big difference to patients on long “diagnostic odysseys” (clinician-speak for “length of time to diagnosis”). It’s also taking pressure off medical professionals who would otherwise have to rely solely on their own expertise to explore next steps with regard to diagnosis and treatment when, understandably, their knowledge may be limited in some rare disease areas.

Genomics is still in its infancy

“Genome-sequencing and AI technology applied to genomics is a hugely positive step for the world of medicine,” says Darnell. “I’ve been working in this field for around 12 years, but this type of technology has only become properly available to use in the NHS in the last few years, although it’s not widespread. Yet there’s definitely a place for large-scale sequencing. For one thing, clinicians now have the chance to study the genetics of tens of thousands of people, and therefore develop a greater understanding of which genetic variations are normal, and which cause disease.”

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