Free software tool aids doctors diagnosing rare genetic disorders


A tool that sorts the wheat from the chaff in genetic variation could bring relief to patients looking for answers, writes Dyani Lewis.


A perplexed doctor stares a computer.
A new online tool offers GPs help in diagnosing genetic illness.
Heath Korvola / getty

Everyone is born with a few hundred genetic typos studded throughout their genome. Most of these are inconsequential. But for a person with an unexplained genetic disease, these glitches could hold the answers to their mysterious condition.

A new software tool, developed by Raony Cardenas and colleagues at the Universidade Federal de Minas Gerais in Brazil, could help doctors to pinpoint which genetic glitch is responsible for a patient’s disease, according to a study published in PLoS Computational Biology.

Since the Human Genome Project announced it had decoded the 3.2 billion chemical letters of our genome in 2003, the price of genome sequencing has plummeted.

Hospitals now regularly sequence patients’ exomes – the roughly 1% of our genome that carries instructions for making proteins – in search of mutations that could explain diseases.

“The challenge for all health professionals is to glean robust and meaningful information from that data,” says clinical geneticist Sue White from the Murdoch Childrens Research Institute, who was not involved in the study.

This involves a two-step process. In the first, a patient’s exome – or, less commonly, their whole genome – is compared to a reference genome, to spot all instances where there’s a difference. This list can have thousands of entries.

The second step is to sort through the list, separating potentially meaningful changes – disease-causing mutations, perhaps – from trivial variations that occur naturally throughout different human populations.

The new open-source program, called Mendel,MD, tackles this second step. Doctors can upload a file containing a list of the genetic variants within a person’s genome. From this, Mendel,MD produces a shortlist of genes most likely to be the disease culprit by searching databases of known disease-causing mutations.

The team behind Mendel,MD tested the program’s mettle on 57 cases of suspected genetic disorders in Brazilian patients. In half of these cases, the program gave a definitive diagnosis, pinpointing the responsible gene mutation. Without exome sequencing, only around 1 in 10 cases are usually diagnosed, says White.

The program also identified the responsible gene mutation for 11 out of 42 cases of epilepsy at the Children’s University Hospital in Dublin, Ireland.

Importantly, you don’t need to be a computer programmer to use Mendel,MD. Clinicians, researchers and even graduate students were all able to use the online tool.

“We designed the software to be simple and intuitive enough to be used directly by physicians, even those who are not proficient in bioinformatics,” says Sérgio Pena, a co-author on the study.

A patient’s data can also be readily reanalysed as new information on disease-causing genes becomes available.

As a geneticist, White sleuths through mutations every day to diagnose genetic disorders. But it’s becoming increasingly important for other medical specialists – neurologists, immunologists, obstetricians – to be able to access this information. Easy-to-use tools like Mendel,MD could go some way to achieving this, she says.

That’s not to say that anyone can search through a list of their own genetic quirks. Direct-to-consumer genetic tests still keep a tight reign on what information is released to consumers. Getting your hands on a full list of your oddities would be very difficult.

And even with a full list, making sense of it isn’t easy.

“There’s still a tremendous amount of skill and clinical acumen that's involved in understanding for sure that something is causing a disease,” says Simon Sadedin, Head of Clinical Bioinformatics at the Victorian Clinical Genetics Services, who was also not involved in the study. “It’s quite a difficult thing to do.”

  1. http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005520
  2. http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005520
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