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Posted on Tuesday, April 11, 2017

Dr. Donald Vinh (left), a researcher at the RI-MUHC and Steven Francis. Finally knowing makes me super happy and excited. Cant wait to see what will come next, says Steven Francis.

By solving one patients case, doctors develop a molecular therapy that could help many

By MUHC Communications

Researchers have identified the genetic mutation responsible for one patients serious health problems, finally solving a medical mystery that has endured for over 30 years. Thanks to this discovery, the researcher developed a therapy that could also help a lot of people who have problems related to the immune system, whether they are genetic or due to a transplant or an illness.

In the laboratory, we demonstrated that a molecule called Morpholino Antisense Oligonucleotide could correct this kind of genetic anomaly and allow the patients immune system to function properly, explains Dr. Donald Vinh, a researcher at the Research Institute of the McGill University Health Centre (RI-MUHC) and the principal author of the study published in the Journal of Allergy and Clinical Immunology.

As a child, I often had to miss school and it was difficult to make friends. I was often mad. It is hard not knowing why you are sick, says Steven Francis

Steven Francis, the MUHC patient at the centre of this discovery, has dealt with significant health issues his whole life. Followed at the MUHC since childhood, he has faced sinus infections, fungal infections, inflammations of the colon, shingles, respiratory problems, renal issues, and impeded growth, throughout all of which doctors were unable to discover an underlying cause; they suspected that it was genetic, but were unable to prove it. His family went so far as to consult specialists in the United States without success.

The tide finally turned in his favour when Dr. Vinh examined his case in 2012. When this patient was referred to me, I went over his entire file in detail, covering some 30 years and literally filling two large cardboard boxes. I also looked at his family history. Since the 1980s, many new immune deficiencies have been identified, and I was able to apply the knowledge from these advances to solve the case, he explains.

Dr. Vinh discovered that Francis had a mutation on a gene that is critical for the proper function of the immune system, called ZAP70. It serves to synthesize a protein of the same name that helps activate our T cells. Without the ZAP70 protein, the body cant defend itself effectively against most infections.

A mutation on this gene is known to be fatal, and the only treatment available up until now has been a bone marrow transplant that must take place before the age of five. With this new discovery, we have found out that genetic mutations of this kind are also found in adults, which could lead to tremendous advances in research. Solving this mystery has opened a new door into the way that the scientific community will look at immune system deficiencies, says Dr. Vinh. The discovery is all the more remarkable considering this gene cannot be studied in mice.

Francis is now 35 years old. In his case, Dr. Vinh and his team now understand exactly where to find the mutation and how it behaves. His specific mutation subtly affects the slicing of the gene and doesnt affect the amino acid sequence that synthesizes the ZAP70 protein. Inspired by a little known treatment used in cases of hypercholesterolemia, Dr. Vinh successfully developed a molecule that exclusively blocks the mutation while allowing the protein to be synthesized.

In the process of helping Francis, the researchers have shown in their laboratory that it is possible to create a molecular therapy that might improve the human immune system.

For Dr. Vinh, the battle is still only half won: while all the pieces of the puzzle might be found, they havent yet been fully put together. There are definitely more steps to take before we can test this treatment. For one thing, we have to convince the industry to support us. When Steven can finally get the benefit of the treatment, Ill be able to count this as a victory.

Dr. Vinh: on the genetics trail

Dr. Vinh studies genetic defects of the immune system. He seeks to understand why the genetic make-up of certain individuals leaves them more vulnerable to rare, severe or recurrent infections.

In his clinic and in his laboratory, he receives patients with complicated health problems that seem to be linked to their immune system. He treats what are called rare and orphan diseases affecting less than 1 person in 2000.

Dr. Vinh knows that there are people like Francis all across Canada they are getting sick but nobody knows why. His team is specialized in finding answers for complicated cases and more importantly, finding new solutions. It doesnt matter if you are in Montreal, Halifax or northern Qubec he wants people to know they are here for them. Patients are referred to him from all of Eastern Canada.

Dr. Vinh is sometimes compared to Dr. Gregory House of the popular television series. Like House, Dr. Vinh has a reputation across the country for his interest in the most atypical medical conditions within his field of practice. I may have a few things in common with him, but Id like to think people find me a nicer person than he is! he jokes.

Category: In Focus

Tag: Donald Vinh, genetics, molecular therapy

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On the genetics trail - McGill Reporter

D

r. Maximilian Muenke has a superpower: He can diagnose disease just by looking at a persons face.

Specifically, he can spot certain genetic disorders that make telltale impressions on facial features.

Once youve done it for a certain amount of years, you walk into a room and its like, oh, that child has Williams syndrome, he said, referring to a genetic disorder that canaffecta persons cognitive abilities and heart.

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And thats an incredibly useful skill, even as genetic sequencing becomes more widespread. For one thing, it can be the factor that sends someone to get a genetic test in the first place. For another, people in many parts of the world dont have access to genetic tests at all.

Thats inspired years of effort to train a computer to do the same thing. Software that analyzes a patients face for signs of disease could help clinicians better diagnose and treat people withgenetic syndromes.

Some older attempts at facial analysis relied on large, clunky scanners a tool better suited to a lab, not the field. Now, in the era of smartphones, such efforts have a whole new promise. Face2Gene, a program developed by Boston-based startup FDNA, has a mobile app that clinicians can use to snap photos of their patients and get a list of syndromes they might have.

FDA approves sale of genetic tests for risk of Alzheimers and other diseases

Meanwhile, Muenke and his colleagues at the NIH last month published an important advance: the ability to diagnose disease in a non-Caucasian face.

Its a promising preliminary sign. But if facial recognition software is to be widely useful for diagnoses, software developers and geneticists will need to work together to overcome genetics systemic blind spots.

Thealgorithms in general work on the same principles: measuring the size of facial features and their placement to detect patterns. Theyre both trained on databases of photographs doctors take of their patients. The NIH works with partners around the world to collect their photos; FDNA accepts photos uploaded to Face2Gene.

But they differ in a key way: Whereas the algorithm the NIH uses can predict if someone has a given genetic disorder, the Face2Gene algorithm spits out not diagnoses, but probabilities. The app describes photos as being a certain percent similar to photos of people with one of the 2,000 disorders for which Face2Gene has image data, based on the overall look of the face as well as the presence of certain features. However, the app wont give clinicians a yes or no answer to the question of, Does my patient have a genetic disorder?

Thats intentional. Face2Gene is meant to be more like a search engine for diseases a means to an end.

We are not a diagnostic tool, and we will never be a diagnostic tool, said FDNA CEODekel Gelbman.

Drawing that bright line between Face2Gene and a diagnostic tool allows FDNA to stay compliant with FDA regulations governing mobile medical apps while avoiding some of the regulatory burden associated with smartphone-based diagnostic tools.

The algorithm the NIH uses developed by scientists atChildrens National Health System in Washington, D.C., seems to work pretty well so far: In 129 cases ofDown syndrome, it accurately detected the disorder94 percent of the time. For DiGeorge syndrome, the numbers were even higher: It had a 95 percent accuracy rate across all 156 cases.

Face2Gene declined to provide similar numbers for their technology. Since Face2Gene is a search and reference informational tool, the terms sensitivity and specificity are difficult to apply to our output, Gelbman cautioned.

But theres one big stumbling block for both of them, a problem that has dogged medical genetics for decades: Data for non-white populations is sorely lacking.

Should biologists stop grouping us by race?

In every single textbook, the ones we had [when I trained] in Germany and the major textbooks here in the US, there are photos of individuals of northern European descent, Muenke said. When I told this to my boss, he said there have to be atlases for children from diverse backgrounds. And there arent.There just arent. (Today there is that resource, based on Muenke and the NIHs work.)

So diagnosing diseases from a face alone presents an additional challenge in countries where the majority of the population isnt of northern European descent, because some facial areas that vary with ethnic background can often overlap with areas that signify a genetic disorder. Eventually, the software will also have to be able to tackle people with mixed ethnic backgrounds, too. We have thought about it but havent gone there yet, Muenke said.

For example, children with Down syndrome often have flat nasal bridges as do typically developing African or African-American children. Across different races and ethnicities of children there were only tworeliable identifiers that could be used to diagnose Down syndrome the angles between landmark points on the childs nose and eye, according to a paper Muenke and Marius Linguraru at Childrens National published with their colleagues earlier this year. All of the other typical features werent significantly more likely to show up when childrenwere compared toethnically matched controls.

In fact, using a Caucasian face as a reference can sometimes be the least representative choice. One of the findings that Im very interested in [in] our recent study was that the population that we found to be most different from the others, in terms of facial patterns characteristic of DiGeorge syndrome, was the Caucasian population, Linguraru said.

To continue to fix this problem, both the NIH and Face2Gene need help from more researchers who can upload more patients faces but thats easier said than done. Confirming a suspected disorder with genetic tests is standard practice today, and there are no genetic labs based in Africa registered in the NIHs Genetic Testing Registry. Asia and South America are also relatively underserved.

Those numbers also reflect the general patterns of distribution for medical geneticists.Most practitioners are located in North America and Europe, Gelbman said. Nigeria, for example, doesnt have a singlemedical geneticist in the entire country.

Its possible that might change, with time and effort. In addition to his work as a researcher, Muenke directs a program that brings health care professionals from developing countriesto the US for a month-long crash course in medical genetics. (The program is funded by the NIHs Fogarty International Center; President Trump eliminated funding for the center in his 2018 skinny budget proposal announced in March.)

For now, both algorithms have shown that they can handle a diverse patient set.FDNA scientists published a paper in January showing that their algorithm could better identify Down syndrome after being trained with a more diverse set of faces, andMuenke and Linguraru have also published papersthis yeardemonstrating their algorithms ability to identify genetic disorders correctly in children acrossa variety of ethnicbackgrounds.

As both groups work on recruiting more researchers, they are also working to push their tech forward. FDNA is working on establishing partnerships with pharmaceutical companies to start their commercial outreach. In theory, these partnerships could contribute to precision medicine efforts or help companies develop new therapies for rare diseases.

Meanwhile, Linguraru has his eyes on eventual FDA approval for the algorithm the NIH has used. The ultimate goal would be a simple tool that any doctor could use anywhere to get fast results and better diagnose their patients.

Kate Sheridan can be reached at kate.sheridan@statnews.com Follow Kate on Twitter @sheridan_kate

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Facial-recognition software finds new use: diagnosing genetic ... - Stat - STAT

The Teagasc INZAC flock, consisting of 180 ewes, is entering into its second full year of production.

The flock is comprised of 120 Irish Suffolk and Texel ewes split 50:50 between each breed and a flock of 30 New Zealand Texel and 30 New Zealand Suffolk ewes.

Dr. Fiona McGovern gave pedigree sheep breeders a run through of the operation earlier today, as part of a Sheep Ireland industry meeting.

McGovern, a UCD graduate, said the trial was established to validate the Replacement Index and to compare the difference between Irish and New Zealand ewe genetics.

As part of the trial, she said, the performance of Irish one-star (low) and five-star (elite) ewes under the Replacement Index is being compared.

Although the trial is primarily focused on maternal traits, data on a number of terminal traits is also being collected due to the overlapping nature of both indices.

These include lamb birth, 60-day and weaning weights. The length of time it takes the ewes progeny to reach slaughter or Days to Slaughter is also measured under the study.

McGovern added that the first of the animals involved in the study were brought onto the farm in 2014. 2016 was the first full year of the trial.

Currently the ewes are being grazed as three separate groups. These include an elite flock, consisting of 60 Irish Suffolk and Texel ewes all of which are five-star rated on the Replacement Index.

The trial also features a low flock, consisting of a mixture of 60 Irish Texel and Suffolk ewes. All of these ewes are rated as being one-star on the Replacement Index.

The third group the New Zealand ewes is also comprised of a mixture of Texel and Suffolk animals.

Each of the groups are split 50:50 between Suffolk and Texel genetics.

The three groups are grazed on a 15ha platform, which is subdivided into a 5ha farmlet for each individual group. Each farmlet carries 12 ewes/ha and receives 150kg of nitrogen/ha/year.

Early trial results show that the New Zealand flock had better performance in a number of areas, but it must be noted that the results presented are only from the first year of a four-year trial.

The trial results show that more New Zealand ewes held to the first service at breeding, while there was no significant difference between the low and elite ewe groups.

Looking at other key breeding metrics, there was no difference in the barren percentage, scan rate or lambing rate between the three ewe groups.

However, the New Zealand flock did produce more lambs (number of lambs born) when compared to the Irish low and elite flocks, which had almost identical results.

Interestingly, the New Zealand group had less lambing difficulty (dystocia) than either of the two Irish flocks, which once again posted similar performance figures.

From a production point of view, there was no difference between the birth, 40-day, weaning and drafting weights between the progeny of either group.

However, the lambs produced from the New Zealand and elite flocks did reach slaughter weight earlier than the low group.

The New Zealand and elite lambs took 155 days and 164 days respectively, to reach slaughter weight meaning that there was no significant difference between both groups. However, it took the low lambs 178 days to come to slaughter.

McGovern added that the last of the low lambs were sold off-farm in November and required concentrates to finish, while the last of the New Zealand lambs were drafted in September after 96% of these animals had received a grass-only diet.

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New Zealand genetics delivering the goods in Athenry - Agriland