Advancing technologies, new genomic testing techniques, and championing for up-to-date health care policies are the focus of Dr. Yvonne Bombard and her lab. Dr. Bombard’s mission is shaping patient care with the fast-evolving health care tools of Medical Genomics.

Kevin Navarro Hernandez and James Sayre

A major aspect of the Canadian identity is its recognition and protection of historically marginalized groups. The protection of individuals based on gender, ethnicity, and physical ability have long been recognized in Canadian law – more recently joined by the protection of sexual orientation of individuals in 1996¹. These rights are at the heart of protecting individuals from direct discrimination on the bases of traits which are inherent to their personhood. From a biological perspective many of these protected traits– ethnicity, gender, physical ability, sexual orientation – are genetic at their root, but the protection against genetic discrimination was only ratified federally in 2017^2,3 thanks to the initiative of Dr. Bombard.

While observing patients being tested for Huntington’s disease during her PhD, Dr. Bombard witnessed genetic discrimination firsthand. A life-altering neurodegenerative disorder, Huntington’s disease is a rare genetic disorder that damages nerve cells, leading to reduced mobility, cognitive ability, and in some cases psychiatric disorders. One of the patients Dr. Bombard connected with shared how their employer upon learning of their diagnosis began to assign them fewer working hours, discriminately changed their job responsibilities and put the individual under surveillance at work.  The disease had not advanced to warrant such changes.  It was the employer’s knowledge of the diagnosis that prompted these actions making work much more difficult for the patient.

Dr. Bombard recalled: “I remember … phoning a legal scholar that I knew at the University of Toronto and asking for his advice; asking him, is this legal? Does this happen? Does Canada have any protections against this for their patients? And he said, no.”

Seeing there was no protection for those receiving rare disease genetic diagnoses, Dr. Bombard set about to describe a framework of protection for such patients.   Her vision was to develop a system for those found to be at greater risk of being diagnosed with a genetic disorder; a system that allowed them to not only navigate their test results but to also learn what would be considered as discriminatory towards them because of their diagnosis.  Dr. Bombard characterized this as a socio-medical relationship between patients and their employers, showing it to be fraught with difficult decisions, financial considerations, and emotional risks^4,5,6.

Catalyzed and determined by her work with Huntington’s, Dr. Bombard pivoted her doctoral work towards the development of legal protection of individuals on a genetic composition basis, using what she had seen with Huntington’s disease as a model. Working with academic colleagues, legal scholars, and political allies, Dr. Bombard was instrumental in introducing Bill S201 to federal parliament. Bill S201 passed on May 4, 2017, in the federal legislature bringing the Genetic Non-discrimination Act into Canadian law^2,3.  This act protects individuals from being forced to undergo genetic testing, protects the results of previous tests from disclosure to employers and insurance providers, and bolsters Canadian’s right to medical privacy.

Dr. Bombard’s Lab Mission

Dr. Bombard’s work on behalf of patients receiving genetic testing did not end there.  Dr. Bombard and her laboratory are in a constant race with the advances in genomics.  The field of genomics grows daily as technology quickly develops, improving research methods and implementation of treatments for various genetic diseases.

Genomic medicine is expanding from a focus on research and diagnosis to prevention at the population level. As technology progresses and test costs fall, screening pre-symptomatic individuals through public health-based approaches could become feasible^6,7. Recent studies found that restricting screening for patients who meet the family history-based criteria for breast cancer has missed more than 50% of individuals with pathogenic BRCA1 and BRCA2 (BRCA1/2) variants⁸. These findings are suggestive that population screening is the key towards preventative medicine. Being able to identify variants even in communities where there is no family history of rare diseases is bringing health care to everyone and a step towards making it universal.

Considerations for population genomics screening are whether to perform full gene sequencing or targeted variant testing. Other variables to consider are whether to test for novel variants or only known pathogenic ones, as well as performing deletion/duplication analysis in addition to sequence analysis. These kinds of decisions will have an impact on the test cost and cost-effectiveness effect on patients. Some of the most prevalent hereditary conditions that should be considered for population screening include familial hypercholesterolemia (FH), Lynch syndrome (LS), and hereditary breast and ovarian cancer syndrome (HBOC)⁸. These are some of the diseases that the Bombard lab is researching.

Issues with implementing population genomic screening include the optimal testing approach, penetrance of these conditions in the general population, clinical and cost-effectiveness, acceptability, health system capacity to implement such a program, ethical issues such as overdiagnosis, access challenges and equity^6,7. 

At the center of Dr. Bombard’s research, is a strong ethos of patient centric and collaborative care. As an extension of this ethos, part of her current work revolves around educating patients on the fundamentals of genetics. This opens the door to discussion about the implications of genetic testing, and describing how to best communicate results in a way that allows patients to make informed decisions about their care. This research has culminated in the development ofThe Genomics ADvISER (Genomics decision AiD about Incidental Sequencing Results), a platform designed to fill the gaps in contemporary care by offering education resources, exercises to help patients explore their values with regards to testing, and ultimately feel empowered in making their care decisions.

A common question is: What makes genetic testing different from other more common medical testing? Genetic testing can have unexpected and broader implications and responsibilities.  It has the potential to open up avenues of far reaching medical consequences.  Firstly, because genetic information is heritable, passed between parents and children, testing inherently provides information on related individuals. This can expand the implications of the testing beyond the individual for which it is intended.  Furthermore, secondary findings – findings during genetic testing which are not related to the primary purpose of testing – are becoming far more common with increases in the use of Next Generation Sequencing techniques, and whole genome sequencing which return huge amounts of genomic information. “we’re now just inundated, bombarded, if you will,…with a lot of data that we have to sift through”.  This is where the ADvISER platform helps bridge the gaps between this mass of information, physicians who are already stretched thin and patients who may be encountering the world of genomics for the first time, in potentially vulnerable states. Proponents for genomic medicine say that we should be sequencing everyone at birth, and while there is merit to this approach in terms of treatment, there is also subsequent fallout that is generated by secondary findings, implications for related individuals who are uninterested in genetic testing and the larger scale delivery of this information in a comprehensible form.

Dr. Bombard describes how “ ADvISER was actually also built, developed and then tested out of necessity because we were returning secondary findings…where we’re sequencing individuals and returning results”. Because of the untargeted nature of extensive genomic sequencing, like whole genome sequencing, secondary findings are an unavoidable product of genetic screening. Some sequence information can simply be overlooked, but what are physicians and patients supposed to do in cases where testing returns consequential and actionable secondary findings? This is where the ADvISER platform is intended to aid patients in the decision-making process to come to a conclusion which best aligns with their personal ethics around testing, treatment, and how to handle the potential uncertainties that comes with genetic testing^9,10.  Genetic testing has the potential of TMI (too much information).  ADvISER helps doctor, patient and medical system disseminate the results of the genetic testing in order to plot a way forward for patient care.

Dr. Bombard’s field of research and job are challenging.  In reply to what is the biggest challenge in policy research, Dr. Bombard said: “being mindful of the fact that there’s a fine line between being a scientist, a science advocate and a policy advocate”. The job comes with many responsibilities not only for her as an advocate, but also the responsibility of developing efficient policies that meet society’s needs. This is an ongoing process with no end in sight. During our interview with Dr. Bombard, she said: “the irony is that the technologies will constantly evolve and what we can bring into our system will have to evolve as well”. This means that even if the system is restructured and redesigned to serve the point in time we live in now, it will have to be reshaped to keep up with technological advances.  The world of genomic policy is rapidly growing and changing.  At the end of our interview, Dr. Bombard left us with this final quote about what her end goal as a pioneer of medical genomics in policy would look like: “I feel like mission complete is when we’ve structured our health care system for our patients via genomics and it is patient centered serving them in the way that they want and need”.

References

1. Government of Canada. Canada.ca (2022). Available at: https://www.canada.ca/en/canadian-heritage/services/rights-lgbti-persons.html. (Accessed: 10th April 2023)
2. Standing Senate Committee on Human Rights (41^st Parliament … – Sencanada, sencanada.ca/en/Content/Sen/committee/412/ridr/11ev-51620-e.
3. Branch, L. S. Consolidated federal laws of canada, Genetic Non-Discrimination Act. Genetic Non-Discrimination Act(2023). Available at: https://laws-lois.justice.gc.ca/eng/acts/G-2.5/page-1.html. (Accessed: 10th April 2023) 

4. Bombard, Y. et al. Managing genetic discrimination: Strategies used by individuals found to have the Huntington disease mutation. Clin. Genet. (2007).
5. Bombard, Yvonne et al. “Perceptions of genetic discrimination among people at risk for Huntington’s disease: a cross sectional survey.” BMJ (Clinical research ed.) (2009). doi:10.1136/bmj.b2175
6. “Why We Need a Law to Prevent Genetic Discrimination.” The Globe and mail, http://www.theglobeandmail.com/amp/opinion/why-we-need-a-law-to-prevent-genetic-discrimination/article31936476/.
7. Mighton, Chloe, et al. “From the Patient to the Population: Use of Genomics for Population Screening.” Frontiers in Genetics. (2022) https://doi.org/10.3389/fgene.2022.893832.
8. Manchanda, R., Loggenberg, K., Sanderson, S., Burnell,M.,Wardle, J., Gessler, S., et al. Population testing for cancer predisposing BRCA1/BRCA2 mutations in the ashkenazi-jewish community: A randomized controlled trial. J. Natl. Cancer Inst. (2015). https://doi:10.1093/jnci/dju379
9. Bombard, Y. et al. Genomics ADvISER: development and usability testing of a decision aid for the selection of incidental sequencing results. Eur. J. Hum. Genet. (2018).
10. Bombard, Yvonne et al. “Effectiveness of the Genomics ADvISER decision aid for the selection of secondary findings from genomic sequencing: a randomized clinical trial.” Genetics in medicine: official journal of the American College of Medical Genetics. (2020). doi:10.1038/s41436-019-0702-z
11. Shickh, Salma et al. “Genetics Adviser: a protocol for a mixed-methods randomised controlled trial evaluating a digital platform for genetics service delivery.” BMJ (Clinical research ed.) (2022). doi:10.1136/bmjopen-2022-060899

Lorin Crawford investigates the role of epistasis in complex trait architecture. His findings emphasize the importance of including diverse populations in genomics research – and the perils of neglecting them.

Nina Anggala and Solomiya Hnatovska

From our first correspondence, Lorin Crawford is effusive, warm, and quick to respond — the antithesis of what you might expect from a rising genetics superstar. We each phone in from the northeast coast, falling snow at our windows. By the end of the conversation, we are left reminiscing about childhoods under the California sun and shared vantages of the hills. Convenient opportunity to complain about the snow aside, charting the geography of his life also allows us to chart the evolution of his career, from an undergraduate in mathematics to a career as a lauded genome scientist.

We begin our discussion with Crawford’s latest venture: Marginal Epistatic Linkage Disequilibrium regression, or MELD¹. A software package three years in the making, MELD is a testament to his crossing of disciplines, an algorithm designed to detect non-additive interactions, or epistasis, in Genome-wide Association Studies (GWAS). The success they’ve found applying MELD to real-world data invites us to redefine our understanding of gene-to-gene interactions and, on a larger scale, confront the very foundations on which we’ve built these models.

The very word is anathema for many biology majors, but the seeds for MELD can inevitably be found in Crawford’s math undergrad, completed at Clark Atlanta University. When asked about his transition to genomics, he throws it all the way back to a summer research experience where his focus was group theory, “a pure math topic about trying to understand how groups of numbers are related to each other in different theoretical ways.” At the final poster presentation, he recalls a judge asking him about the practical applications of his group’s research—to which he replied, there were none.

Though she laughed it off, that singular interaction launched Crawford into deep introspection. In addition to having no practical applicability, he had found the whole experience largely isolating, with students working independently until they compiled their work. He realized that in order to find fulfillment in his work, it needed to have real world impact.

“So that following semester,” he tells us, “I took statistics.”

Statistics is a body of applied mathematics, integral to all the life sciences. Where we cannot ethically or feasibly control an individual’s environment, statistics is how we account for those confounding variables². He recalls two formative experiences in particular: a summer studying prostate cancer incidence rates in Atlanta’s African American population and a “life-changing” Differential Equations class. In the latter, he learned about modeling HIV mutation rates and how the rate of mutation impedes the search for a cure—what some have aptly described as a fraught arms race between virologist and virus.

“Every three days, you basically have a new disease,” he says, “I thought that was super fascinating – and you could study all that just using differential equations.” The contours of the career he wanted for himself were beginning to take form. (Intrusive thoughts of going to business school notwithstanding.)

As an aside, if there was ever any doubt that the way forward for Crawford was statistics, when asked whether he’d rather live through a zombie apocalypse or an alien invasion, he answers, “Man. I’m gonna say a zombie apocalypse because at least I know what I’m up against. An alien invasion sounds tough because there are a lot of unknowns there.” Affinity for known variables aside, Crawford is clearly adaptable enough to handle any (terrestrial) curveballs thrown his way.

Graduating summa cum laude – an achievement he didn’t volunteer himself, but that we dug up on Google – with a Bachelor’s in mathematics, he decided to pursue a doctorate in Statistical Sciences at Duke University, under the supervision of Sayan Mukherjee. Mukherjee in turn introduced him to Kris Wood, whose lab was attempting to model therapeutic resistance in cancer subtypes. Under their joint supervision, Crawford would spend his graduate education going back and forth between the Statistics Department and the wet lab.

“The way I learned about genomics really was being in [Wood’s] group,” he tells us. “It was kind of the equivalent of, I would say, living in a different country. And then you have to learn the language of that country, right? The best way to do this is to actually embed yourself in that culture.”

Although not a genomicist by trade yet, Crawford was uniquely suited for this project. The same principles govern therapeutic resistance in cancer and HIV: the disease evolves, and researchers must find a way to track these mutations and respond accordingly. “It presented me a way to approach that problem from a purely statistical modeling perspective,” he says. “His lab didn’t have anyone computational, so it really gave me the opportunity to grow in that space.”

He would go on to present his thesis on the use of machine learning in statistical genetics and cancer genomics, topics that would fuel the beginnings of MELD when he arrived in Providence – where he now holds an Associate Professorship at Brown University and works as a Principal Researcher with Microsoft Research New England.

Crawford soon turned his eye to the goliath of big data statistics: GWAS. GWAS involves sequencing the genomes of a large sample of people, in an attempt to find statistically significant correlations between variants present in that population and a phenotype of interest (Fig. 1)³. This technique is most useful when studying relatively common traits, as innocuous as height or as widespread as diabetes. In these cases, you expect to see modest contributions from many variants, culminating in your phenotype of interest. An additive model of trait architecture, which describes the genetic underpinning of a phenotype, sums these contributions⁴.

“There’s a theory that additive effects are primarily the types of effects that drive the variation across traits,” Crawford tells us. “There are a lot of different reasons for this line of thinking … but the simple answer is, you would imagine that humans are going to take the easiest path towards evolution.”

The fault in the additive theory is not that it is theoretically unsound, but that it’s been treated as universal even though these inferences have only ever been validated in an exclusive subset of people – “The databases that we study are heavily skewed towards one type of person,” Crawford tells us. “Over 90% of the samples in some of these databases only represent roughly 19% of the human population” – and despite evidence for significant contributions from non-additive interactions^{6, 7}. In a non-additive interaction, two or more loci modulate each other’s expression to produce a phenotype; for example, inheriting the allele for baldness would supersede the effect of alleles for hair colour. This is what we refer to as epistasis, wherein the effect of a mutation depends on the genetic background in which it is present⁸.

“If I changed my viewpoint on different groups of individuals, I might see different types of effects start to arise as being important,” Crawford says. “Computationally speaking, we’ve bought so much into this linear additive theory, we don’t even build models anymore to investigate the nonlinear portions.”

The fruits of the Crawford lab’s labor came once they applied MELD, which had been trained and tested on simulated data, on the UK and Japan BioBanks. By including non-additive effects in the MELD algorithm, they were better able to quantify the variation and heritability of 23 out of 25 complex traits they studied, such as height and cholesterol levels¹. These results challenge the long-standing belief that epistatic interactions are negligible and provide evidence that epistasis is much more widespread than previously thought.

Crawford also notes that their findings are ultimately “aligned with long standing theories.” Rather than a reinvention of the wheel, his group patches fault lines in the spokes by adding to the assumptions baked into previous models. He hopes to carry this philosophy into future research projects, which he says will center around two major focal points: redefining diversity as a descriptor that exists along many different axes – “not just along the lines of ancestry, which can sometimes be conflated with race and ethnicity” – and encouraging the use of machine learning to tackle increasingly large, -omics level data sets.

“The biggest impact I hope that we have,” Crawford says, “is this notion of thinking about what it means to have our understanding of trait architecture be for all people.” His research aims are integral to achieving equality in precision medicine, which will remain out of reach until the field reaches a more nuanced understanding of diversity and identity.

Realizing this goal will require larger, more diverse human datasets (this is where machine learning comes into play), though Crawford urges caution, citing the pervasiveness of helicopter science. Helicopter science is a manifestation of predatory inclusion: an ongoing approach to collecting genomic data, wherein researchers descend on lower income communities without forming meaningful collaborations⁹. Comprehensive datasets benefit everyone, but the inclusion of an individual’s genome doesn’t guarantee them the resources or infrastructure to access the knowledge their information yields. Emphasizing the need for an ethical, human-oriented approach to genomics research, Crawford sees the future of genomics, and indeed all data science, in interdisciplinary collaborations across math, genetics, and social sciences.

When it comes to research in underrepresented communities, Crawford envisions “an almost complete marriage” of research groups: between specialists coming from the outside and experts within those populations, with the goal of building infrastructures to support their study and its aftermath. These are all hallmarks of community building initiatives, which Crawford points out is difficult to do with only geneticists. “You work across these lines where it looks like we don’t have anything in common,” he says. “And so, each person is bringing a unique perspective to the field.”

Crawford is, without doubt, a brilliant mind, able to tackle some of the biggest questions in genetics, but he is made even more admirable by his humility and pathos. He emphasizes that his work is rewarding, because it is inherently collaborative: MELD was initially an idea he dreamed up with Sohini Ramachandran when he first arrived at Brown and was brought to fruition in collaboration with the Ramachandran lab.

“I’ve been really fortunate to work with people who are insanely smart,” he says, “who like to ask really hard questions, are super humble and don’t take themselves too seriously. I’m always the least knowledgeable person in the room.”

Whether he’s deserving of that superlative or not, Crawford has been inducted as a member of The Root’s 100 Most Influential African Americans, was featured in Forbes’ 30 Under 30, and is the recipient of numerous prestigious fellowships, including the David & Lucile Packard Foundation Fellowship for Science and Engineering. We ask him which of his achievements he is most proud of and he answers, without hesitation, “I graduated four people last year. Those are my first four students that I graduated.”

The joy he finds in pedagogy and collaboration belies an even deeper inclination – to work at the bleeding edge without leaving anyone behind. Crawford embodies a future wherein scientific inquiry lights the way forward for those who are most vulnerable. A throughline in his academic career, since that fateful summer, has been a desire for his research to have real word application; MELD presents a more complete understanding of complex human genetics and in doing so lays the groundwork for the development of precision medicine for all.

But Crawford doesn’t ordain himself a revolutionary.  “I got into this because I loved the notion of having autonomy,” he says. “And that’s always kind of been my North Star, being in a space where I get to define what’s cool.” 

Cool, after all, is the very highest accolade any scientist can hope to achieve – we humbly submit that, for a guy from Chino Hills, Lorin Crawford is pretty cool.

References

1. Darnell, G., Smith, S. P., Udwin, D., Ramachandran, S. & Crawford, L. Partitioning tagged non-additive genetic effects in summary statistics provides evidence of pervasive epistasis in complex traits. bioRxiv (2022). doi:10.1101/2022.07.21.501001
2. Willcox, W. F. The founder of Statistics. Revue de l’Institut International de Statistique / Review of the International Statistical Institute 5, 321 (1938).
3. Uffelmann, E. et al. Genome-wide association studies. Nature Reviews Methods Primers 1 (2021).
4. Understanding genetics: A district of columbia guide for patients and Health Professionals. National Center for Biotechnology Information (2010). Available at: https://pubmed.ncbi.nlm.nih.gov/23586106/. (Accessed: 12th March 2023)
5. Genome-wide association studies fact sheet. National Human Genome Research Institute (2020). Available at: https://www.genome.gov/about-genomics/fact-sheets/Genome-Wide-Association-Studies-Fact-Sheet. (Accessed: 12th March 2023)
6. Visscher, P. M. & Goddard, M. E. From R.A. Fisher’s 1918 paper to GWAS a century later. Genetics 211, 1125–1130 (2019).
7. Zuk, O., Hechter, E., Sunyaev, S. R. & Lander, E. S. The mystery of missing heritability: Genetic interactions create phantom heritability. Proceedings of the National Academy of Sciences 109, 1193–1198 (2012).
8. Gros, P.-A., Le Nagard Hervé & Tenaillon, O. The evolution of epistasis and its links with genetic robustness, complexity and drift in a phenotypic model of adaptation. Genetics 182, 277–293 (2009).
9. Adame, F. Meaningful collaborations can end ‘helicopter research’. Nature (2021) doi:10.1038/d41586-021-01795-1.

Dr. Charles Boone already rocked the world of yeast genomics in 2018 with the yeast gene interaction map. His work foretells that a gene interaction map for humans may be possible within the year. 

Thomas Barbazuk, Lise Cinq-Mars, and Pooja Kiran Ravi

A little over 20 years ago, two yeast biologists came up with an idea that to most would sound crazy. Dr. Charles Boone and his colleague, Dr. Brenda Andrews wanted to find out which genes were essential to the survival of yeast by systematically knocking out genes in sets of two. Considering that yeast has about 6000 genes, anyone would assume this would be an incredibly lengthy project. Nearly two decades later, Dr. Charles Boone and Dr. Brenda Andrews in collaboration with Dr. Chad Meyers published a gene interaction map of yeast (Figure 1), setting off a storm in the field of genetics.  

A principal investigator and Professor at the University of Toronto’s Donnelly Center for Cellular and Biomolecular Research, Dr. Charles Boone is a monolithic figure within yeast genomics. He completed his Bachelor of Science in Chemistry and Math at Queens University. He subsequently went to McGill University to obtain a Ph.D. in Biology and the University of Oregon where he was a research fellow at the Institute of Molecular Biology. Having been involved in the yeast genetics community for three decades, Dr. Boone has adapted with the ever-changing field of genetics, constantly pursuing a deeper understanding of the fundamentals of life. Yeast provides spectacular insights into cellular processes and gene interactions, whilst remaining a much more tractable organism to work with in a laboratory setting than others. The beauty of studying yeast is that much of it is scalable to human genetics and can be used as a practical model to study human cellular interactions. Eleven Nobel laureates have come from breakthrough discoveries in cancer and cell function by using yeast as a model organism, validating yeast as one of the most thoroughly explored model organisms in the world.  Together with Dr. Brenda Andrews (Professor and Principal Investigator at the University of Toronto and the Donnelly Center respectively¹), Dr Boone has mapped yeast genetic interactions on an unprecedented scale by using their very own automated approach to mapping called Synthetic Genetic Array (SGA) analysis². The method has allowed for the analysis of millions of mutant yeast strains, successfully teasing out gene to gene interactions and their corresponding biological processes to explore the fundamentals of life. 

The yeast genetic interaction network is very informative in addition to being colorful and beautiful (Figure 1). It helps us to understand the complexity of the cell by organizing genes in a categorical manner. It also shows us the genes in the yeast DNA that are similar to humans which could indicate those that are required for survival. The advantage of studying these genes in yeast, in addition to learning about a new organism, is that we can recognize approximately a thousand that are essential to cell function in humans​³​. Any changes to them or a combination of changes can result in cell death​³. Furthermore, the DNA regions are categorized into modules with similar functions which have ways of communicating with each other and any changes to this communication can result in the overall disruption of each cell. For example, the region that controls response for misfolded protein in the endoplasmic reticulum is a large segment of DNA that involves many genes​⁴​.  Introducing different combinations of mutations into yeast DNA shows us that what causes cell death in yeast can affect cells in all organisms. This is the basic principle behind Synthetic genetic array analysis (SGA) technology that is used extensively in Dr. Boone’s lab. 

While some of the immediate implications of such findings are in human medicine, we could also see maps where we understand where our different traits come from such as intelligence, behavior, etc. Dr. Boone noted that “Human genetics is … fundamental to our understanding of human health … and since we don’t know how to interpret it, I think this is the [era] of Human Genetics… That translates into personal medicine. So, I think the most obvious thing is medically related. But … what goes along with Human Genetics is all kinds of stuff [like] behavior, … intelligence, there’s going to be all kinds of things about humans that we will probably be able to quantify.” 

When Dr. Boone entered the field of yeast genetics, the yeast genome was not yet sequenced but there were known regions of genes that helped propel forward an age of genetic experiments with studies in conservation of function. Once the sequence of yeast genome was revealed, it was easier to design microarrays that studied functions since a similar experiment in humans would be much more difficult to design and understand.  

Dr. Boone showed concern that the world is moving its eyes away from Yeast research because “There’s this bias against model organisms in general, even though they’ve basically fueled a lot of biology. And so, it’s harder to get a model Organism grant.” Dr. Boone feels “The biggest problem facing in genetics today is that we don’t understand the general rules yet.” He believes “the genotype phenotype problem for an individual is what’s going to … allow us to figure out personalized medicine.” Given that this is quite complex and that variation in each person’s genome only adds to the complexity, he wants to build a human cell map (much like the one he built for yeast) that would fundamentally change our ability to interpret human genomes.  

“No one’s made a human cell map, so we should be able to do that.” 

This would show us the connections between our 20,000 known genes and help physicians determine how variation in an individual’s genome (genotype) could translate into an altered manifestation of a trait (phenotype).

Another setback for the field is that “the big leaders have all retired… they were like superstar hero humans that span[ed] that transition from phage to yeast and they created this community.” The pioneers of the field were also very helpful in fostering community spirit even while competing against each other. He also mentioned that it was also easy to collaborate and work together in the yeast labs. Dr. Boone and other labs at the Donnelly Centre for Cellular and Biomolecular Research now carry on the tradition of nourishing teamwork.  It also shows when he is proud that his lab is “open concept” which allows for easy collaboration with other researchers – Dr. Tim Hughes and Dr. Brenda Andrews. 

 With the interdisciplinary nature of the life sciences now, collaboration is a crucial component to success as a researcher. A paradigm shift has occurred within scientific research in the last thirty years towards massive collaborative projects; whereas independent work used to be hailed and applauded as the gold standard. To quote Dr. Boone, “The perfect researcher was formerly one who conducted all facets of the experiment and analysis on their own and the ‘single author’ paper was supposedly the best paper”. With improvements in communication technology and increases in scientific understanding, contemporary science encourages individuals to specialize in specific areas to foster a deeper understanding in their respective fields. Now, experts exist and communicate together regularly, as it remains a necessity due to the multi-faceted nature of the life sciences.  

“Working in systems biology today usually means you need, biologists, computational scientists, and likely engineers, so you’re forced into collaboration, right? And but that’s the most fun part because then you get to do three times as much.” 

In the context of genomics, there is a need for computational scientists as well as wet-bench scientists, not to mention the multitude of very expensive laboratory tools that are not typically found in every research laboratory within a university. Multi-institutional projects are commonplace as scientists each focus on their respective areas to address biological questions with more robust publications. Dr. Boone emphasizes the importance of collaboration in modern science, especially in the context of his research lab. He heavily emphasized that strong collaboration with Dr. Brenda Andrews has been a fundamental part of his laboratory’s success. Dr. Boone also mentioned crucial and regular collaboration with Dr. Chad Meyers (Professor and Co-Director of Graduate Studies for Bioinformatics and Computational Biology at the University of Minnesota⁵) as well as Dr. Jason Moffat (Professor and Principal Investigator at the University of Toronto and the Donnelly Center respectively⁶ & Program Head of Genetics and Genome Biology at the Hospital for Sick Children⁷). Dr. Chad Meyer’s research focuses on integrating complex genomic data to make inferences about biological networks. Dr. Jason Moffat is currently collaborating with the Boone lab on a project that involves mapping human cancer cell interactions by using the Boone labs yeast genetic interaction network as the framework. The Moffat lab harnesses CRISPR gene editing technology to deliberately induce isolated genetic changes in human cells, allowing for the observation of cellular relationships. The course of this experiment will help to explore the disparity between genotype and phenotype in human cancers, allowing for further insights into cancer biology that are fundamental in the development of novel treatment strategies. Dr. Boone emphasized that successful collaboration is largely reliant of finding like-minded individuals with a shared drive for discovery. Dr. Boone stated that trust on all levels is fundamental in successful collaboration such that everyone gets credit for their work. He alluded to the importance of a team-based approach and hinted that successful collaboration with a drive for discovery is what the Donnelly Center is all about.  

“It’s about making sure everyone gets credit and feels like they are part of the discovery while working together to solve a problem as a team.” 

Dr. Boone continues his collaborations in Japan where he is the Leader of the Molecular Ligand Target Research Team at the RIKEN Centre for Sustainable Resource Science. Dr Boone admitted that he truly doesn’t have a lot of freetime since he enjoys his research so much. But in his spare time, he enjoys canoeing & fishing all around the world, including the Arctic, and traveling to Japan to continue his research at the RIKEN Institute. 

Dr. Boone hopes to pull some more focus back to model organisms, such as Yeast, as he believes they will be instrumental in producing a much needed “toolkit” for interpretation of the human genome. Additionally, he and his team are currently studying how the background effects of a genetic network may give answers to the different levels of penetrance in human disease. In 2020, Dr. Boone was named the inaugural Banting & Best Distinguished Scholar which recognizes top researchers at the Temerty Faculty of Medicine who are having life-changing impact through their discoveries. As we wait for the time when Dr. Boone is ready to publish a human cell map, illustrating the complex interactions between all our genes, we can only hope the rest of the world will recognize how this yeast biologist will have changed our lives. Providing a map for the most complex instructions to life and how we function will become the basis of all personalized medicine and undoubtably change the field of medicine forever.    

 References

1.        Donnelly Centre for Cellular and Biomolecular Research – University of Toronto. Brenda Andrews. https://thedonnellycentre.utoronto.ca/faculty/brenda-andrews (2023).

2.        Hin, A., Tong, Y. & Boone, C. Synthetic Genetic Array (SGA) Analysis in Saccharomyces cerevisiae Running head: Synthetic Genetic Array (SGA) Analysis. Yeast Protocols, Second Edition. Methods in Molecular Biology 313, 171- 192 (The Humana Press Inc., Totowa, NJ, U. S. A.) (2005).

3.        Segal, E. et al. Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data. Nat. Genet. 34, 166-176 (2003).

4.        Kincaid, M. M. & Cooper, A. A. Misfolded Proteins Traffic from the Endoplasmic Reticulum (ER) Due to ER Export Signals. Mol. Biol. Cell/ 18, 455–463 (2007).

5.        Department of Computer Science & Engineering – University of Minnesota. Chad L. Myers. https://cse.umn.edu/cs/chad-myers (2023).

6.        Donnelly Centre for Cellular and Biomolecular Research – University of Toronto. Jason Moffat. https://thedonnellycentre.utoronto.ca/faculty/jason-moffat (2023).

7.        The Hospital for Sick Children. Jason Moffat. https://www.sickkids.ca/en/staff/m/jason-moffat/ (2022).

EpiSign establishes itself as a promising first tier test for diagnosing rare disorders through the unique features of epigenetic signatures in combination with the immense computational power of machine learning algorithms.

Ilham Abbasi, Sean Williams, and Mailoan Panchalingam

Rare diseases make up a significant health concern, both in Canada and globally, reaching a total estimated prevalence of 3.5% to 5.9% worldwide¹. This vast and heterogeneous group of disorders often have poor prognoses, leading to chronic illness, decline in function, disability, and early death. Although genetic testing can provide answers for 25–35% of undiagnosed rare disease patients², many are left with inconclusive results and unresolved questions. This results in a long diagnostic odyssey of doctor visits and medical testing, accompanied by an increasing financial burden. Fortunately, with advances in genomics and technology, the field of epigenomics has brought about several breakthroughs in diagnosing rare diseases¹.

When we think about genetics, we often focus on the physical blueprint of the DNA code. However, there are also complex chemical changes that occur on the DNA sequence to influence gene expression – these are known as epigenetic modifications³. Epigenetic modifications take place without any alterations to the raw DNA sequence itself, and can be influenced by environment, diet, and lifestyle choices⁴. One of the most prominent epigenetic mechanisms is DNA methylation, which involves adding a methyl group to specific sites in the DNA sequence, known as CpG sites. DNA methylation is critical for many biological processes, including development, ageing, and illness³. Not suprisingly, a number of diseases have been associated with abnormal DNA methylation patterns in the epigenome, including cancers and neurodevelopmental disorders. These reproducible  DNA methylation patterns, also known as episignatures, can be used as biomarkers for the early identification and diagnosis of various diseases¹.

At the forefront of epigenomics is Dr. Bekim Sadikovic, the founder of EpiSign. Dr. Sadikovic’s passion for the field began during his Ph.D. studies at the London Health Sciences Centre (LHSC) and Western University, where he studied the epigenomics of cancer. He chose to work in this trailblazing field because he “felt strongly that genomics and epigenomics and big data are going to make an important impact in the diagnostic field”. Following his postdoctoral studies and clinical training, he joined LHSC as a laboratory director, where a majority of his time has been devoted to translational research in genomics and epigenomic diagnostic biomarkers. As the program head of the molecular diagnostics program, Dr. Sadikovic oversees the implementation of molecular diagnostics with large genomic databases into clinical care, which has opened up new avenues for patient diagnostics, treatments, and disease prevention.

The defining moment when Dr. Sadikovic knew epigenomics could transform patient diagnostics and clinical care occurred over a decade ago. While analyzing data for a research study, he noticed that two patients with the same genetic disorder had strikingly similar genomic DNA methylation patterns. This discovery sparked a question for Dr. Sadikovic – could epigenomic patterns be used to diagnose new patients with the same disorder? Fast forward to today, we commonly know these unique but reproducible patterns as “episignatures”. This was only the beginning of many “aha” moments in Dr. Sadikovic’s career that eventually led to the inception of EpiSign – the first clinically validated test that can analyze whole genome methylation signatures for the diagnosis of rare genetic disorders. Not only has EpiSign impacted the field of epigenomics, but it has impacted the healthcare system on a global scale:

“We became the first lab in the world to actually use genome-wide methylation data, that are built on artificial intelligence algorithms, to officially start diagnosing patients, which was a big deal.”

EpiSign primarily relies on machine learning AI algorithms that use DNA methylation patterns as biomarkers to diagnose patients with rare genetic conditions (Fig. 1)^1. The computational process of defining an episignature occurs through two steps. First, is identifying which CpG sites in patients with a particular condition are differentially methylated compared to healthy individuals. This is known as probe selection, and it requires large patient cohorts and a vast amount of genomic data to ensure that the analysis is accurate and predictive. Once the differentially methylated sites have been determined and statistically validated, machine learning algorithms are used to distinguish between the methylation patterns that come from rare disease patients and healthy individuals. This is used to develop a mathematical model called a classifier, which can be used to diagnose patients with a particular disorder based on their DNA methylation profile.

In the clinic, a rare disease patient’s journey with epigenetic testing starts when they have undergone genetic testing and receive unambiguous results known as variants of uncertain significance (VUSs). These VUSs make it difficult to narrow down diagnosis for a single genetic condition, since their impact on disease is unclear. But, as Dr. Sadikovic puts it, “it’s not because these patients don’t have genetic conditions. It’s very likely that many of them do. It’s because our ability to understand the human genome is still very limited”. To resolve these ambiguous findings, a patient may be referred to Pathology and Laboratory Medicine at LHSC for EpiSign testing. In other cases, a patient is directly referred for EpiSign testing as a first-tier test because they are suspected to have clinical features associated with an epigenomic-related syndrome.

The DNA methylation profiles of these patients are then screened against known episignatures housed in the EpiSign Knowledge Database – the world’s largest data methylation profile database for rare disorders, developed by Dr. Sadikovic and his research group (Fig. 2)⁵. If a VUS occurs in a genomic region which has been epigenetically mapped, the patient’s DNA methylation profile can be compared to defined episignatures in this region that are known to be associated with a particular condition. For patients with no genetic testing results, their DNA methylation profile is typically screened against all syndromes in the EpiSign Knowledge Database. Not only can this reclassify inconclusive and negative genetic testing results in 20 – 30% of cases, but it can rule out more than 70 epigenomic-related syndromes as well⁵. However, as Dr. Sadikovic points out, a negative EpiSign test result does not necessarily mean that a patient does not have a genetic condition, or that the VUS is not associated with the disease:

 “We know we haven’t mapped all episignatures. We don’t know what’s not there…there may be variants that produce an alternate type of methylation signature that we just haven’t mapped.”

To date, EpiSign has mapped out episignatures for over 90 genetic conditions and 96 different genes, and this number only continues to grow. Currently, Dr. Sadikovic’s group is mapping out episignatures for over 500 different conditons in a collaborative effort with over 200 institutions across 30 countries – a major impact on healthcare both nationally and globally. When asked about what the future holds for EpiSign, Dr. Sadikovic explains how the development of novel technologies will improve genetic testing within the healthcare system. His lab is working with multiple research groups and industry partners to create technology that will bridge the gap between genomic variant detection and epigenetic signatures simultaneously in a single test. This will ultimately benefit both patients and the healthcare system in two ways – firstly, patients can gain a significant amount of information from a single test, reducing the amount of genetic testing required by a patient. Secondly, the cost burden for both patients and the healthcare system will be minimized by decreasing the need for further genetic testing among patients who initially received inconclusive results.

Dr. Sadikovic further elaborates on the implications that episignatures and patient DNA methylation profiles will have on the development of drug therapies. He believes that the identification of common episignatures within DNA methylation profiles of patients with rare disorders may one day be exploited to develop more effective drug therapeutics. Conventional personalized genomic medicine sees a single drug developed to treat a single patient with a single variant, whereas through modifying epigenetic patterns, a broader spectrum of patients may be able to benefit from targeted drugs. Dr. Sadikovic then goes on to describe the enormous cost and health benefit of developing drug therapeutics that are based on DNA methylation profiles:

“Development processes can cost 10s to 100s of $1,000,000 for a single drug that sometimes impacts a single patient. So, if we’re able to start identifying and unifying things in patients with rare disorders, being disruptive epigenomic regions, we might want to start thinking about how can we develop potential drugs to change those epigenetic patterns.”

EpiSign has shown that epigenetic signatures serve as a strong source for a first-tier diagnostic test for rare genetic disorders and will likely play a greater role in clinical care, beyond diagnostics. For example, we may see episignatures being used in the near future to predict prognostic outcomes and treatment interventions for patients with rare disorders. This demonstrates a pressing need for more research and innovation in epigenomic testing and technology, which is further exemplified by a fitting final statement by Dr. Sadikovic as he mentions his dreams and goals for the future EpiSign and epigenomics as a whole:

“My goal, and I guess my ambition and my dream, is to see epigenomic profiling for every patient with a suspected hereditary genetic condition.”

References

1. Haghshenas, S., Bhai, P., Aref-Eshghi, E. & Sadikovic, B. Diagnostic Utility of Genome-Wide DNA Methylation Analysis in Mendelian Neurodevelopmental Disorders. International Journal of Molecular Sciences 2020, Vol. 21, Page 9303 21, 9303 (2020).

2. Marwaha, S., Knowles, J. W. & Ashley, E. A. A guide for the diagnosis of rare and undiagnosed disease: beyond the exome. Genome Medicine 2022 14:1 14, 1–22 (2022).

3. Jin, B., Li, Y. & Robertson, K. D. DNA Methylation. Genes Cancer 2, 607–617 (2011).

4. Gibney, E. R. & Nolan, C. M. Epigenetics and gene expression. Heredity 105, 4–13 (2010).

5. LHSC Epigenetics. https://episign.lhsc.on.ca/index.html.

“By the age of three, the child who would have succumbed to Menkes disease was now climbing through stairs and developing normally like other children.”

Syed A K Shifat Ahmed, Nowrin Aman, and Kamalika Bhandari Deka

In the present era, the cost of sequencing an entire genome of an individual is around $1000 with a turnaround time of one week¹. By contrast, in 2003, creating a reference genome for the human genome project took $3 billion and 15 years². With advancement in sequencing tools and improved understanding of human genomics we can now quickly investigate any novel disease or gene- but this was not the case even until the 1990s.  In a time when molecular based diagnosis and treatment were not well established, it required deeper understanding of disease biochemistry and innovative treatment solutions to tackle rare genetic diseases. Dr Bibudhendra Sarkar is one such pioneer scientist who made a novel discovery to treat patients with a rare genetic condition causing neurodegeneration, known as the Menkes Disease.

In 1937 two Australian veterinary scientists first recognized that sheep grazed in copper-deficient pastures stumbled³. Later in the 1960s, researchers approached the Australia Wool Research Laboratories to investigate possible links between copper deficient diet and defective hair formation in sheep³, although any conclusive links remained unsubstantiated then⁴. Two years later five male infants from English Irish heritage were diagnosed with a progressive neurodegenerative disorder and clinical manifestations that included epileptic seizures, developmental regression, and unusual thin “kinky” hair⁴. The disease was called Menkes, a rare inherited disease named after the pediatric neurologist Dr. John Hans Menkes, who first described it in 1962⁴. Later in 1972-73, Dr. David M Danks in a series of landmark publications connected the mystery of “kinky” hairs in sheep and Menkes patients to copper deficiency⁵.

Currently a Senior Scientist Emeritus at the Research Institute of the Hospital for Sick Children (SickKids) and Professor Emeritus, Department of Biochemistry at the University of Toronto, Dr. Bibudhendra Sarkar recalled that research at that time was limited.  Although the Research Institute in SickKids was established in 1954, the only research that was conducted was from a case study perspective. Sarkar was a biochemist with a strong background in biophysics and mathematics, but he had no clinical training. Despite that, he was hired at SickKids and that made him the first basic scientist at the hospital in 1964. It all started with an invitation for a talk from Dr. Andrew Sass-Kortsak, who met Sarkar at a meeting in Chicago. Sass-Kortsak was a physician in genetic metabolic diseases at the Hospital for Sick Children. He specialized in Wilson disease which causes toxic accumulation of copper in vital organs ⁶.

This was Sarkar’s first visit to Canada, and he fondly recalls the talk as spontaneously attended by medical doctors, academicians and students who were greatly enthused by the presentation of his research. The success of the talk was such that Sarkar was offered a Staff Scientist position in the Genetic Metabolic Research Program. Decades later when reflecting what motivated him to leave the US and take the offer at SickKids, an uncommon move in those days for a basic scientist, Sarkar says “I remember after the talk that day, I visited the hospital ward with Sass-Kortsak and seeing the faces of the sick children I felt a human connection that I could never feel in the boundaries of my laboratory and among the inanimate experimental tools.”

In research, collaboration is very important and great scientific ideas are often conceived through discussions with experts. Although not medically trained, Sarkar learned about medical sciences from attending regular clinical rounds and frequent conversations with Sass-Kortsak. It was during one such discussion with Sass-Kortsak about Wilson disease, the idea of copper removal therapy was mentioned. Wilson disease is a genetic disease that leads to overaccumulation of copper in vital organs like the brain, kidney, and liver and a straight-forward therapeutic approach was to remove excess copper⁶. The discussion then moved on to blood in general. According to Sass-Kortsak, the concentration of copper in blood was due to copper bound mainly to proteins and a small amount remained freely suspended in blood to which the biochemist Sarkar disagreed. He knew from his inorganic biochemistry background that copper had a high affinity for nitrogen, and it was unlikely for copper to remain free when there are so many other nitrogenous substances in blood. To prove his hypothesis, he experimented with his own blood and after a thorough investigation he was able to demonstrate it being bound to an amino acid histidine in blood. He recalled, “I could not believe my own discovery, therefore I looked for the same in blood samples of residents staff too.” They happily gave him their blood samples because in return he would measure their iron levels. He is grateful for the help from the staff members which tremendously helped to confirm his findings. This seminal discovery of isolation of copper-histidine in human blood was published in 1966⁷ and it acted as a catalyst for the development of copper-histidine therapy for a genetic disease called Menkes Disease.

The first Menkes patient to receive copper-histidine therapy

Menkes disease is a neurodegenerative disease resulting in early death by the age of three years, but contrary to Wilson disease, it is characterized by copper deficiency³. In 1972 during a scientific conference in Paris, Sarkar met the eminent pediatric neurologist Dr. David M Danks. His discovery on the unique association of Menkes patients and sheep in relation to copper deficiency intrigued Sarkar which led him to explore the possibility of copper imbalance treatments.

In 1976, the first Menkes case was diagnosed at SickKids. The patient was prematurely born, and the blood copper levels were dropping alarmingly. Considering Sarkar’s experience in copper, Sass-Kortsak asked for his advice in this case. Based on his extensive research on copper exchange kinetics with albumin in blood and copper-histidine function as biological transporter, Sarkar suggested administration of copper-histidine for this Menkes patient. “Since I knew copper will not be absorbed from the gut if given orally in Menkes disease and with  intravenous administration was not feasible in this case ;  therefore, the only option was to inject copper-histidine subcutaneously”, Sarkar explained. 

Realizing the complexity of the situation, Sass-Kortsak presented this novel treatment option to the Clinical Investigation Unit (CIU), now known as the Research Ethics Board. The CIU took into consideration that since copper-histidine is a biological component already present in human blood, it was less likely to get rejected and would only require strict dose monitoring. With no other option available, the committee approved the copper-histidine formulation as an experimental therapy for Menkes disease. With consent of the patient’s family, the copper-histidine formulation was subcutaneously injected. The dosage was controlled and strictly monitored for safety. The experimental drug worked in bringing the copper level to normalcy^8,9.   Sarkar ecstatically recalls “By the age of three, the child who would have succumbed to Menkes disease was now climbing through stairs and developing normally like other children”. This clinical intervention happened at a time when patenting was not common and funding for rare diseases was difficult to obtain, therefore research on diseases like Menkes was challenging, Sarkar recalls. Furthermore it was  difficult to diagnose rare genetic diseases because of lack of genetic testing conducted on those days, making the treatment more difficult.

Another Menkes patient was administered the same formulation soon after birth to normalise the copper level. It was later found through genetic studies that both the patients had a lethal form of Menkes gene defect. It was soon understood that the timing of the dose administration and the nature of genetic mutation played a critical role in determining the treatment efficacy^10,11. Following the publication of Menkes treatment, Sarkar received requests for the drug formulation from different parts of the world. The formulation of copper-histidine was shared free of cost and soon this innovative therapy was being clinically applied to Menkes patients around the world.

The discovery of the Menkes disease gene 

Initially, Menkes disease was diagnosed by biochemical analysis based on intracellular accumulation of copper supported by clinical manifestations of the disease. Things changed with isolation of the Menkes disease gene in 1993¹¹.  Sarkar says “previously we missed a lot of Menkes patients because of our lack of knowledge on rare diseases and also due to limitations in early diagnosis but with isolation of the gene ATP7A that codes for copper transporting ATPase, prenatal screening became possible”. The gene identification and improvement in genetics tools allowed doctors to offer treatments right from birth that helped in management of diseases symptoms. While sharing his views on genetic testing, Sarkar recalled an experience from his visit to Japan in early 1990s, he said “I saw two brothers both of whom had Menkes disease, but the elder brother, around 5 years of age looked weak and  had to be carried around while his younger brother who was prenatally tested with Menkes gene defect and given copper-histidine treatment from birth was seen running and jumping around just like any 3-year-old.” Hence Sarkar expressed early genetic testing can lead to timely treatment that can improve the quality of life in Menkes patients. 

While the discovery of the Menkes gene was helping in early detection of cases, it had to be supported by effective treatments. Sarkar decided to do a long-term follow-up study on the clinical course of four Menkes patients from Canada, Switzerland and Australia who were treated with copper-histidine from early infancy. The findings showed favourable effects on the neurological symptoms and concluded the treatment was effective if administered early in life¹³. Sarkar says, “Copper-histidine is not a cure for Menkes disease but like most treatments for genetic diseases, it helps to ameliorate the sufferings of patients and provide them with a comparatively longer lives”.

Spirit of collaboration

Sarkar briefly mentioned how the outlook on collaboration had changed over the years. During his time, scientists mostly worked in isolation but now with the emphasis on translational research, there is a lot of collaboration among peers from different departments. Sarkar says “When I first joined SickKids, one of the first things I wanted to introduce was “bench-to-bedside” research, now commonly called as translational research and the Peter Gilgan Centre for Research and Learning  (PGCRL) tower at SickKids is a result of that spirit”.  He proudly mentions SickKids as the birthplace of Cystic Fibrosis (CF) gene discovery. “SickKids is very powerful, not just because of the CF gene, but so many other genes were discovered at SickKids. The CF gene discovery is the pinnacle of our success.”

Sarkar mentioned an aspect he gained during his time at SickKids, his relationship with Menkes patients. He talked about his attachment with patients following years of consultations and follow-ups. He got emotional talking about a particular Menkes Disease patient who died of a severe urinary tract infection. Sarkar felt devastated but found solace when patient’s mother reminded him for his timely therapy, which in turn gave the parents a few additional years of happiness with their son. He recalled the patient’s resilience and a quote from him to his mother where he said, “ You know what mom? None of us get made quite right, until we get to heaven.” Sarkar presented the quote and dedicated his talk to this patient in an International Meeting in Brazil in 1998. He highlights the perils of such rare disease patients and the need to find an early therapy .

It has been over 20 years since Sarkar retired. But he still goes to SickKids where he has his office. He meets people there and answers their questions on Menkes and Wilson diseases’. But what he still loves the most is the stories he collects when he goes to meet the children and their parents in the wards. Sarkar believes humility is the ultimate character of a great scientist. He came from a period when the human genome project was still in its infancy and his stories highlight even in times of adversity the collaborative spirit in science can lead to make miracles.

References:

1.        Dondorp, W. J. & de Wert, G. M. W. R. The ‘thousand-dollar genome’: an ethical exploration. European Journal of Human Genetics 21, S6–S26 (2013).

2.        Human Genome Project Information Archive 1990–2003. Accessed March 9, 2023

3.        Prasad, A. N. & Ojha, R. Menkes disease: what a multidisciplinary approach can do.
J Multidiscip Healthc 9, 371–385 (2016).

4.        Menkes, J. H., Alter, M., Steigleder, G. K., Weakley, D. R. & Sung, J. H. A sex-linked recessive disorder with retardation of growth, peculiar hair, and focal cerebral and cerebellar degeneration. Pediatrics 29, 764–79 (1962).

5.        Danks, D. M., Campbell, P. E., Stevens, B. J., Mayne, V. & Cartwright, E. Menkes’s kinky hair syndrome. An inherited defect in copper absorption with widespread effects. Pediatrics 50, 188–201 (1972).

6.        Wilson disease – About the Disease – Genetic and Rare Diseases Information Center. https://rarediseases.info.nih.gov/diseases/7893/wilson-disease.
Accessed March 12, 2023

7.        B.Sarkar & T.Kruck. Copper-amino acid complexes in human serum. Academic Press, New York 183–196 (1966).

8.        Sherwood, G., Sarkar, B. & Kortsak, A. S. Copper histidinate therapy in Menkes’ disease: prevention of progressive neurodegeneration. J Inherit Metab Dis 12 Suppl 2, 393–6 (1989).

9.        Sarkar, B., Lingertat-Walsh, K. & Clarke, J. T. Copper-histidine therapy for Menkes disease. J Pediatr 123, 828–30 (1993).

10.      Tümer, Z. et al. Early copper-histidine treatment for Menkes disease. Nat Genet 12, 11–3 (1996).

11.      Chelly, J. et al. Isolation of a candidate gene for Menkes disease that encodes a potential heavy metal binding protein. Nat Genet 3, 14–9 (1993).

12.      Møller, L. B., Mogensen, M. & Horn, N. Molecular diagnosis of Menkes disease: genotype-phenotype correlation. Biochimie 91, 1273–7 (2009).

13.      Christodoulou, J. et al. Early treatment of Menkes disease with parenteral copper-histidine: long-term follow-up of four treated patients. Am J Med Genet 76, 154–64 (1998).

Lupus is a highly variable disease with relevant environmental and genetic causality. Dr. Linda Hiraki sits down to discuss the issues this presents from a research perspective, focusing on the lack of genetic diversity in data and the need for scientific collaboration.

Brooke Coe, Vivian Hong, and Kajeetha Sarvananthan

The events that occur in our childhood have a stark ability to shape our adult lives. Such is the case with Dr. Linda Hiraki, a Clinician-Scientist with The Hospital for Sick Children (SickKids), who was a teenager when her sister was diagnosed with a life-altering chronic illness, Systemic Lupus Erythematosus (SLE or lupus). Dr. Hiraki was in medical school when she became impassioned to understand the complex disease that “had such a big impact on [her] sister’s life and [her] whole family.” This connection is what drove Dr. Hiraki to the top of her field as an expert in pediatric lupus. Recalling the events of her past, Dr. Hiraki acknowledges the importance of making a connection between one’s personal and professional life, stating “it [is] what gives our work meaning… And I think it [is] important to feel like our work is meaningful.” She now finds herself at the forefront of pediatric SLE research, working to understand the complex genetic differences underpinning lupus development, to improve physical and mental health experiences for patients, and to address the lack of ethnic diversity in data.

What is Lupus?

Lupus is an autoimmune disease that causes inflammation that leads to tissue damage throughout the body, affecting many organ systems¹. Lupus can affect children, adolescents, and adults, with 20% of patients diagnosed in childhood². While akin to adult SLE, pediatric SLE (also known as childhood-onset SLE or cSLE) commonly results in more severe presentations and higher levels of organ involvement². In particular, the kidneys or the brain are commonly affected with inflammation that may cause damage, leading to life-threatening complications¹.

The presentation of lupus is highly heterogeneous with Dr. Hiraki sharing that it is also known as “the disease of a thousand faces,” meaning that both its clinical manifestations and causality are highly variable. Lupus development and progression is impacted by numerous environmental factors, including hormones, UV exposure, and infection. There is also evidence that genetics play a strong role in lupus predisposition³. Over 180 lupus susceptibility genes have been identified to date, primarily in European populations⁴. Many associated genes are involved in regulating immune response³. For most people, lupus is a consequence of interactions between genetic, environmental, and epigenetic factors^3,4. This results in a wide range of clinical manifestations called lupus as some patients have life-threatening disease while for others, lupus is comparatively mild. However, Dr. Hiraki iterates that although “we call them all the same thing, practically, they [are] very different!”

Despite the variability in presentation, the interplay of lupus risk factors results in the dysregulation of the body’s immune system. This is primarily due to the overproduction of self-attacking antibodies, called autoantibodies, that target proteins on normal, healthy cells as if they were foreign pathogens^1,5. This causes a positive feedback loop of inflammation where sustained attacks from autoantibodies creates inflammation that further dysregulates autoantibody activities, creating more inflammation, and eventually tissue and organ damage (figure 1)^1,5. The involvement of other immune cell populations and inflammatory intermediaries, such as cytokines, further perpetuates the cycle and severity of inflammation⁵. Such mediators are commonly linked to lupus in gene association studies, demonstrating the complex and multifactorial nature of the disease⁵.

Using her background in genetic epidemiology, Dr. Linda Hiraki studies genetic changes associated with different SLE signs, symptoms, and complications in children and adults. At its core, she hopes her work aids our understanding of the underlying biology of SLE, hoping to gain insight into “not so much who gets lupus, but what their lupus looks like – the genetics of different manifestations of the disease.” Dr. Hiraki is currently coordinating large international studies to identify associations between common or low-frequency genetic variants and disease traits. To accomplish these goals, Dr. Hiraki acknowledges two central themes: representation and collaboration.

Issues of Representation in Lupus Research

During our discussion with Dr. Hiraki, the need for broad and representative genetic research in lupus was a recurring theme. Genetic medicine in general, is historically over-representative of white, European populations, leaving other ethnic populations greatly under-represented. This is problematic due to an unaccounted for, yet well recognized, prevalence of lupus in non-European populations⁶. Ethnicity and geography play a significant role in SLE development. For example, in North America, the prevalence of SLE for Black and Hispanic populations is 3-4 times higher compared to Caucasian populations⁶. Clinical manifestations among non-white/non-European ancestral populations are also more severe, often showing increased organ damage⁶. For Dr. Hiraki, the issue is that the under-representation of non-European populations in SLE genetic studies exacerbates disparities in our understanding of SLE across populations, and thus impedes our ability to use genetic data broadly in clinical care.

While describing the lack of diversity in genetic data, Dr. Hiraki also discussed the societal inequities that confound this issue. A complex matter in its own right, Dr. Hiraki simplifies the discussion, stating “disparities in health care access and health outcomes fall along ethnic and socioeconomic lines”. Not only does the link between lower socioeconomic status and ethnicity affect health at a rudimentary level, such as poorer diet, but it affects how those people are treated within the healthcare system⁷. A historic lack of adequate, accessible, and ethical healthcare based on socioeconomic and ethnic status has resulted in deep mistrust of the healthcare system by some groups. In a follow up response, Dr. Hiraki explained how this affects the ability to conduct well-represented research for lupus:

“Engaging persons of all backgrounds in research continues to be a challenge. There is a complex relationship between the medical, scientific research community and different sectors of society… it’s understandable why certain groups may mistrust the medical community and be reluctant to participate in research.”

Beyond the difficulties of getting broad ethnic participation in research, lupus presentation and progression is linked to lower socioeconomic status and ethnicity⁷. Factors associated with inequities are so heavily associated with SLE that they are often considered predictive of SLE development and progression⁷. For Dr. Hiraki, this becomes a challenge of “trying to disentangle how much of th[e] disparities are a consequence of inequity when it comes to access to health care and how much of [it] is a reflection of genetics.”

As a clinician and researcher, Dr. Hiraki has made it her mission to proactively study underrepresented and admixed populations, stating “it [is] because of that imbalance in representation that we are inclusive in our recruitment.” True to her word, in 2009, Dr. Hiraki conducted one of the largest, single centers, transethnic cSLE studies out of SickKids in Toronto⁶. This study was done with the purpose of delineating ethnic involvement in cSLE as most multiracial studies prior had focused on adult SLE⁶. In contrast to predominant American studies that comprised of Caucasian, African American, and Hispanic sample groups, Dr. Hiraki’s team took advantage of Toronto’s multiculturalism and recruited Asian and South-Asian sample groups as well. This resulted in a majority non-Caucasian cohort. Overall, this diverse study agreed with the consensus in adult SLE research that non-Caucasian populations had higher disease prevalence and younger age of diagnosis⁶. However, severity and disease progression were independent of ethnicity⁶. More recently, Dr. Hiraki has focused more on neonatal SLE (cases where the patient has lupus at birth). Dr. Hiraki and her team found that ethnicity is not associated with lupus risk or a specific disease manifestation in neonatal SLE cases, suggesting gene loci that differ among different ethnicities are involved in a gene-environment dynamic that results in specific manifestations⁸. Such studies done by Dr. Hiraki and her team allow us to move forward to fully understanding the exact role of genetics in lupus versus that of the environment. Thus, there is a demonstrated need to account for ancestry in genetic association studies for lupus, while not discounting its potential involvement.

Furthermore, Dr. Hiraki’s research also demonstrates the value of including genetically diverse data in research. Another 2009 study described autoantibody differences among different ethnic populations⁹. This was the first study suggesting autoantibody clustering was linked to different clinical outcomes in cSLE. They found that Caucasian patients predominantly associated with autoantibodies that were linked to mild SLE and minimal organ damage, while non-Caucasians clustered with more severe manifestations and complications⁹. These types of classifications can provide important clinical context, suggesting that full autoantibody profiling could help predict disease progression and potential organ involvement. In line with what she hopes to accomplish, this and subsequent work provides valuable insights into lupus pathogenesis, making data “relevant not just for certain ancestral groups but making it relevant for everybody, irrespective of what their ancestral background is.”

The Future is Collaborative

When asked to identify the biggest hurdle(s) in lupus research, Dr. Hiraki reiterated the lack of inclusivity as a major obstacle, despite the push for representation over the last couple years. She describes “still having to generalize European [data] to non-European populations because there is no information” and how she “find[s] that very frustrating.”

This issue is demonstrated in one of Dr. Hiraki’s recent studies investigating the genetic link between schizophrenia and SLE in a multiethnic cohort. Here, the data on schizophrenia susceptibility genes was primarily from populations of European ancestry which affected the ability of the study to truly assess the link for non-Europeans¹⁰. This example demonstrates the sacrifices that are still being made in lupus research that potentially alter the conclusions made and subsequent clinical treatments.

Further discussing the issues in lupus research, Dr. Hiraki addressed the need for standardization and “speaking the same language” when it comes to the definition of lupus across research. Due to the variability in clinical presentation, lupus can be commonly misdiagnosed and misclassified (for example, lupus is commonly misdiagnosed as rheumatoid arthritis). Additionally, she explained “lupus is not only heterogeneous between people but it’s heterogeneous within a person over time.” That is, lupus involves periods of active inflammation and followed by periods of inactivity. Also, lupus manifestations can fluctuate over time, creating potential for new organ involvement years after the initial diagnosis.

To address these challenges, Dr. Hiraki urges collaboration, expressing:

“Science has evolved in such a way that we’re increasingly collaborative …By expanding [our] circle[s], not only [are we] connecting with people who have very different skill sets but again have different perspectives.”

The challenges of lupus, like the disease itself are complex and require unique troubleshooting that truly only arises from effective collaboration. On her end, Dr. Hiraki involves herself in international groups of lupus researchers aiming to ensure that data is being collected with consistent methods and definitions. By standardizing how research is done and data is collected, it will be easier to centralize and harmonize globally. Overall, this affords lupus researchers access to more diverse and usable data.

Much of her current work focuses on using these connections to coordinate large-scale, long-term, transethnic studies to delineate immunological profiles of individual patients. She is working to characterize single cell populations within lupus patients to distinguish inflammation over the course of a disease. In doing this, “the hope is as we have better characterization of each individual person’s disease and trajectory, [and] we’ll be able to treat them more effectively,” explains Dr. Hiraki. At the end of the day, Dr. Hiraki wants her research to provide broadly applicable data that translates to more personalized patient experiences.

Dr. Hiraki has established herself as a reputable powerhouse at the forefront of lupus research. Her research affords invaluable genetic context for a disease that is incredibly multifaceted and difficult to understand. Furthermore, her actions as an advocate for diversity in lupus research will have profound effects for patients worldwide. As the scientific community continues towards the trend of individualized medicine, Dr. Hiraki’s work will shine as a key driver of progression, exemplifying the need and value of inclusive and collaborative research.

References:

1. Pathak, S. & Mohan, C. Cellular and molecular pathogenesis of systemic lupus erythematosus: Lessons from animal models. Arthritis Research Therapy 13, 241 (2011).
2. Knight, A. M., Trupin, L., Katz, P., Yelin, E. & Lawson, E. F. Depression risk in young adults with juvenile- and adult-onset lupus: Twelve years of followup. Arthritis Care & Research 70, 475–480 (2018).
3. Kwon, Y., Chun, S., Kim, K., & Mak, A. Update on the genetics of systemic lupus erythematosus: Genome-wide association studies and beyond. Cells 8, 1180 (2019).
4. Elghzaly, A. A. et al. Genome-wide association study for systemic lupus erythematosus in an Egyptian population. Frontiers in Genetics 13, (2022).
5. Dema, B. & Charles, N. Autoantibodies in SLE: Specificities, isotypes and receptors. Antibodies 5, 2 (2016).
6. Hiraki, L. et al. Ethnic differences in pediatric systemic lupus erythematosus. The Journal of Rheumatology 36, 2539–2546 (2009).
7. Demas, K. L. & Costenbader, K. H. Disparities in lupus care and outcomes. Current Opinion in Rheumatology 21, 102–109 (2009).
8. Diaz, T. et al. Ethnicity and neonatal lupus erythematosus manifestations risk in a large multiethnic cohort. The Journal of Rheumatology 48, 1417–1421 (2021).
9. Jurencak, R. et al. Autoantibodies in pediatric systemic lupus erythematosus: Ethnic grouping, cluster analysis, and clinical correlations. The Journal of Rheumatology 36, 416–421 (2009).
10. Ulloa, A. C. et al. Schizophrenia genetics and neuropsychiatric features in childhood-onset systemic lupus erythematosus. The Journal of Rheumatology 49, 192–196 (2021).

The Care4Rare initiative has revolutionized the way we diagnose rare genetic disorders in Canada through providing access to genetic sequencing and other ‘-omics’ technologies. 

Kassandra Bisson, Radhika Mahajan, Paul McKay, and Hamid Farahmand

Imagine having a child who is sick and after years of tireless diagnostic testing and countless specialist appointments, their diagnosis remains inconclusive. That is usually the dilemma facing a parent whose child suffers from a rare disease. A disease is considered ‘rare’ if it affects less than 200,000 people.¹ However, rare disorders are, in fact, extremely common, impacting millions of people worldwide. These diseases are generally chronically debilitating and can even be life threatening.² In Canada, over a million people suffer from one or more of the 7,000 rare genetic diseases (RDs), in which a third have an unknown underlying genetic cause.³ In search of answers, Dr. Kym Boycott has been changing the game of rare disease patient care and diagnosis. Under the Department of Genetics at Children’s Hospital of Eastern Ontario (CHEO), Dr. Boycott has been a pioneer in improving patient care by understanding the molecular pathogenesis of rare diseases. In addition to her role as a Tier 1 Canada Research Chair in Rare Disease Precision Health, she is also a renowned Clinical Geneticist and a Senior Scientist at the CHEO Research Institute. 

When asked about what sparked her career path, Dr. Boycott stated that it was a lecture given by Dr. Patrick McLeod during her undergraduate degree that ignited her interest in human genetics. Dr. Boycott stated, “When you look back at your life at my age, you will see those forks in the road and that was one of them.” Her experience working with both clinicians and researchers motivated her to pursue a PhD and MD, followed by FRCPC training in Medical Genetics at the University of Calgary. Throughout the course of her academic journey, one of the most prominent turning points she experienced was in 2011 when she, alongside her colleagues, launched a national network entitled the Finding of Rare Disease Genes in Canada (FORGE Canada) project. This project primarily used next generation sequencing technology (NGS) to study rare diseases⁴. In the context of diagnosing rare diseases using NGS, she mentioned, “These [were] amongst the first exomes done for rare disease in Canada at scale.” To her surprise, a bioinformatics masters’ student at that time, Jeremy Schwartzentruber, interpreted the genomic data and identified candidate genes for several of the syndromes on the first sequencing runs. She candidly stated, “It had taken me six years to find my first gene. And during this one afternoon in 2011, we’d found six genes for syndromes that had been without a known genetic cause for decades in 1 hour. […] This is going to be something really important for genetics.” With this major advent in NGS technology over the past decade, Dr. Boycott has led genomic sequencing initiatives worldwide, including FORGEand Care4Rare in Canada, in combination with various ‘-omics’ technologies to unlock the secrets behind rare diseases.

What Is Care4Rare?

One of Dr. Boycott’s greatest milestones is the Care4Rare project (Figure 1)⁵,which focuses on finding diagnoses for individuals with rare diseases that remain undiagnosed. Founded in 2011, Care4Rare is a pan-Canadian consortium consisting of clinicians, bioinformaticians, scientists, and researchers. The consortium is exploring ways to improve the care of patients with rare diseases in Canada and around the world. In addition to its headquarters at CHEO, Care4Rare has 21 academic sites across the country, and is recognized internationally as a pioneer in genomics and personalized medicine.

Care4Rarehas two main goals: 1) access and 2) understanding. The first goal strives to provide access to exome (ES) or genome sequencing (GS) for all eligible individuals with a suspected rare genetic disease in Canada. The second goal aims to better understand how genetic variation contributes to diseases. Over a 10-year period, Care4Rarehas studied more than 5000 families. When asked about Care4Rare’s proudest accomplishment Dr. Boycott cited, “The fact that all of those 5000 families got the opportunity to access this sequencing technology before it was available in the clinic.” Over 50% of those families have already received answers from this research, while the remaining 50% are still being investigated after inconclusive genomic sequencing results. Dr. Boycott expects that within the next few years, genomic sequencing will become incorporated early on in the diagnostic care pathway for individuals with suspected rare genetic syndromes. Dr. Boycott explained further, “The more we can push it to the front of the diagnostic pathway, the better.” The early integration of genetic sequencing will likely shorten the diagnostic timeline and avoid other inconclusive testing and specialist referrals. 

The type of sequencing most appropriate for clinical use is hotly debated. Dr. Boycott stated, “genome sequencing provides about a 5% increase in diagnostic yield over exome sequencing. [There is] not much ‘genome’ can find that an exome didn’t already find for you, especially if you’ve had a microarray done, but our understanding of the genome will improve over time.” She did acknowledge the importance of genome sequencing in playing a critical role in revealing mutational mechanisms and ‘hidden answers’ not accessible by exome sequencing alone. These revelations will push genomic understanding further and make the data produced by ES/GS much more medically actionable⁶.

Integrating The ‘-omics’ Technologies

Care4Rare – SOLVE, the third phase of the project, is currently focussing on optimizing the delivery of both clinical genome-wide sequencing and multi ‘-omics’ approaches⁶. This is alongside global data sharing and new bioinformatics, facilitating delivery of innovative diagnostic care for rare diseases. Any individual still undiagnosed after ES, with no candidate variants identified, likely has a complex disease mechanism which will be challenging to detect. For example, a disease mechanism involving long range genomic interactions or heterogeneity in the genetic makeup of the affected tissue means that ‘deeper digging’ is often required to uncover a diagnosis⁶. For families who failed to receive a clear diagnosis from initial ES, Care4Rare’s clinical laboratory teams will follow-up by supplementing this genomic data with multi ‘-omics’ technologies (Figure 2)^6,7,8. The integration of these newer ‘-omics’ technologies is a current focus of Care4Rare, with the hope that this can help ‘solve’ the underlying disease mechanism in individuals or families that were undiagnosed after clinical ES⁶. Dr. Boycott particularly emphasized the impact of using long-read genome sequencing, transcriptomics, methylomics, metabolomics and lipidomics methodologies in rare disease diagnostics⁶. Due to their relative novelty, understanding these technologies is a primary focus. Care4Rare subsequently hopes to develop a decision-making tool for determining which ‘-omics’ technologies to use next in the clinical diagnostic pathway based on the suspected disease mechanism. Combining these technologies generates valuable data which increases the potential for clinical actionability⁶. From this increased understanding of genomic variation and disease, novel therapeutic targets can be elucidated allowing the development of more precise treatment approaches tailored to an individual. 

When asked about any potential barriers in the current expansion of the Care4Rare initiative, Dr. Boycott said the only real challenge recently has been the impact of the COVID-19 pandemic restrictions. Particularly, their ability to readily collect samples and therefore the recruitment had been reduced, however, this has been improving as restrictions are being lifted. At CHEO, the aim is to set up a clinic for undiagnosed patients supported by the collaboration between clinical research staff, clinical geneticists, and genetic counselors. Since various sample types can be required for use in other ‘-omics’ technologies, the clinic’s mission is to provide a central location for families to undergo multi-sample collection. This clinic will thereby help to ease the length of time in the research and testing process and ultimately further Care4Rare’s main goal of improving access to genetic testing.

The RareConnect Platform 

The RareConnectplatform, initially set up by EURODIS (Rare Diseases Europe), accompanies the research of Care4Rare.⁹ It offers a private, supportive, and safe social network platform in 13 languages for families that have ultra-rare diseases who wish to connect, ask questions, and share their experiences and stories.⁹ The RareConnectplatformis divided into disease specific online discussion groups and communities based on topics pertaining to many disease areas.⁹ It also offers a community for those without a current diagnosis.⁹  Dr. Kym Boycott pointed out, “These tools have helped address the isolation that families often experience when they have a rare disease”. The CHEO initiatives led by Dr. Boycott have helped thousands of individuals reach a diagnosis for their rare genetic disease, oftentimes providing families affected by rare genetic disease with immediately actionable therapeutic avenues upon finally receiving their highly elusive diagnosis. 

Future Prospects for Medical Genomics 

The Care4Rare initiative has been a pioneering project leading the way for integration of medical genomics into clinical practice. This project has demonstrated the usefulness of ES/GS alongside multiple ‘-omics’ technologies in diagnosing individuals and families with rare genetic diseases⁶. Identification of new disease-causing genes will help clinicians and researchers better understand what causes a rare disease and may inform approaches to development of subsequent therapeutics⁶. While there is currently limited knowledge regarding the epidemiology, diagnosis, and treatment of RDs, global efforts are ongoing to increase awareness, treatment options, and education. 

When asked about why she thinks medical genomics research is so important, Dr. Boycott stated, “I think it’s so important because we don’t understand the medical genome – and this impacts patient care – its clinical utility will only increase with our increased understanding”.  Dr. Boycott emphasized the importance of medical genomics research in impacting rare diseases and cancer management in the future. As the integration of genomics/other ‘-omics’ becomes more widely used,  all that data produced will need to be interpreted. She also noted how interesting it will be to see how “ultimately patients’ treatment might change.” As the Care4Rare initiative has demonstrated, this advancement of genomic and other ‘-omics’ technologies greatly increases the necessity for individuals and researchers that are trained in the medical genomics field. Overall, Care4Rare serves as a fantastic model for other rare genetic disease research and will pave the way for novel research, therapeutic approaches, and diagnostic care.

References

1.         Diseases | Genetic and Rare Diseases Information Center (GARD) – an NCATS Program. https://rarediseases.info.nih.gov/diseases (Accessed 2022).

2.         Boycott, K. M., Vanstone, M. R., Bulman, D. E. & MacKenzie, A. E. Rare-disease genetics in the era of next-generation sequencing: discovery to translation. Nat. Rev. Genet. 14, 681–691 (2013).

3.         Care4Rare Canada: Harnessing multi-omics to deliver innovative diagnostic care for rare genetic diseases in Canada (C4R-SOLVE) | Genome Canada. https://www.genomecanada.ca/en/care4rare-canada-harnessing-multi-omics-deliver-innovative-diagnostic-care-rare-genetic-diseases/ (Accessed 2022).

4. Beaulieu, C. L. et al. FORGE Canada Consortium: Outcomes of a 2-Year National Rare-Disease Gene-Discovery Project. Am. J. Hum. Genet. 94, 809–817 (2014).

5.         CARE for RARE. CARE for RARE http://care4rare.ca/ (Accessed 2022).

6. Driver, HG. et al. Genomics4RD: An integrated platform to share Canadian deep-phenotype and multiomic data for international rare disease gene discovery. Hum Mutat. doi: 10.1002/humu.24354. Epub ahead of print. PMID: 35181971 (2022).

7.         Computational Multi-Omics. Computational Multi-Omics https://comics.dcv.fct.unl.pt/ (Accessed 2022).

8.         Labory, J. et al. Multi-Omics Approaches to Improve Mitochondrial Disease Diagnosis: Challenges, Advances, and Perspectives. Front. Mol. Biosci. 7, 590842 (2020).

9.         RareConnect. https://www.rareconnect.org/en/ (Accessed 2022).

Dr. Faghfoury, a prominent clinical geneticist at SickKids, shares her expertise on all things medical genomics; including her professional journey, misconceptions, and challenges of genetic testing.

George Guirguis, Yasmeen Kurdi, and Anahita Bahreini-Esfahani

Imagine being in medical school after years of hard work and dedication only to find yourself not drawn to any of its disciplines. Most medical disciplines are categorized based on organ groups. Dr. Hanna Faghfoury found herself in this specific situation – not drawn to any particular organ system, she was uncertain whether she would find a suitable specialty. This doubt changed to passion and excitement when she enrolled in a Medical Genetics elective. “After the  first day, I called my parents, and I said I found what I want to do for the rest of my life.” What really stood out to Dr. Faghfoury was that a medical geneticist is not focused on a single organ system, yet was not considered to be a generalist. More importantly, medical geneticists had the ability to follow patients longitudinally – from birth and throughout the patient’s life. After getting accepted into the medical genetics residency at the University of Toronto (UofT), she enrolled in an elective of which she has never heard before in medicine- Metabolics. Having completed an undergraduate degree in biochemistry was helpful – despite the often dry and seemingly irrelevant delivery of biochemical pathways as Dr. Faghfoury highlighted. In light of genetics, metabolic pathways made more sense, as they provided clearly actionable targets of intervention. This intensified Dr. Faghfoury’s passion for medical genetics and she pursued this specialty for her career. Today, Dr. Faghfoury is the post-graduate director of the Medical Genetics and Genomics program at UofT, where she also holds an associate professor position at the Temerty Faculty of Medicine.

The completion of the Human Genome project in 2003 ushered in a new era of modern medicine and led to the advent of sophisticated technologies used to sequence DNA. These advances have since transformed the landscape of clinical diagnostics and management of genetic disorders. Contemporary medical genetics has become an expansive subspecialty of medicine, entailing the use of genetic principles such as inheritance and gene mapping in the diagnosis of management of disease. Previously, a geneticist’s expertise in recognizing dysmorphological features was a pivotal factor in identifying candidates for genetic testing¹. Furthermore, genetic testing was widely inaccessible due to the slow turnaround times of lab results processing and the astronomically high cost of sequencing. Fast forward to 2011 when the FDA approved next generation sequencing for application in clinical diagnosis²– this marked a paradigm shift in clinical assessment. As genetic testing became cheaper and more accessible, geneticists increasingly integrated these sequencing technologies into their practice, slowly moving away from strictly assessing clinical presentation, or phenotyping, to identify or rule out disease. Dr. Faghfoury notes that as technological and financial barriers surrounding genetic testing decrease over time, the need for phenotyping will decrease – which is what clinical geneticists have been traditionally trained for. She notes that this gradual shift poses somewhat of a professional identity crisis for clinical geneticists in terms of distinguishing the profession from that of a genetic counselor. That being said, medical geneticists have distinct skills from lab personnel and counselors because they are trained in patient management. One limitation that prevents geneticists from broadening the scope of their practice is constraints in capacity and resources that can be attributed to the current model of care. Addressing these limitations will require a systemic re-imagination of the role and scope of medical geneticists in the rapidly changing era of genomics. Despite these capacity and resource constraints, medical geneticists, like Dr. Faghfoury, maintain an invaluable role in patient care.

Dr. Faghfoury’s day-to-day work is dynamic and varied given her multitude of roles. However, a constant part of her work is patient education, where she addresses hesitancies and misconceptions surrounding genetic testing. In pre-test consultations with patients, she emphasizes that “there isn’t a one size fits all for genetic testing”, and that a myriad of tests can offer varied insights that together aid in clinical evaluation. A type of genetic test routinely used in genetic clinics, such as the Fred A Litwin Family Centre in Genetic Medicine where Dr. Faghfoury works as a geneticist, is whole exome sequencing (WES). This technique made its way into clinical diagnostics around the year 2011, and applies next generation sequencing to determine variation in coding regions of genes, also known as exons. About 85% of disease-causing mutations in Mendelian disorders- disorders caused by mutations in only one gene- are contained in exons³. One example of a disease where WES provides a high level of sensitivity and specificity to identify or rule out disease is Wilson’s disease – a genetic disorder that interferes with the body’s ability to remove excess copper. One important limitation of WES is that it only examines one percent of the human genome⁴. At times, this limitation may render WES ineffective at determining a genetic cause for a patient’s suspected disorder. This is because regulatory regions that modulate expression of genes- essentially turning them on/off- exist outside of exons⁵. For example, in malformations of cortical development disorders, many patients have no mutations in their genes, but rather in the regulatory regions surrounding them⁶. For example, intronic repeat expansions have been shown to cause brain disorders such as epilepsy⁷. The mutations present in these patients are often missed with the use of WES. This is why Dr. Faghfoury educates her patients that a normal WES result does not equate to a negative result, rather it is inconclusive.  “I don’t call a negative result negative, I say ‘it’s inconclusive’ because we just haven’t found the cause of [the] problem”. On the contrary, many patients believe that genetic testing is the be-all-end-all, and that it will always provide answers. “The misconceptions either fall in the category of overvaluing genetic testing or undervaluing it”. Whole genome sequencing (WGS), on the other hand, captures virtually the entire genome, including regulatory regions. Because of this, WGS can provide a more conclusive result. Alongside the advantage of capturing immensely more of the genome, WGS requires extensively more analysis. In addition, WGS is more accurate than WES⁴.Regrettably, for most Ontario patients, WGS is not currently requestable by physicians. Instead, it is conducted randomly in lieu of WES.

There are many challenges facing the field of clinical genetics, where limited resources represent an especially pertinent challenge. Ideally, a clinical geneticist would diagnose a patient and continually follow-up with them long term. Unfortunately in Canada, there are only seven genetics residency programs in the country that graduate a handful of students each year, creating a high demand for geneticists with a low supply. Because there are not enough clinical geneticists to go around, patients are often followed up by their family physician post diagnosis. This can pose potential issues as clinical genetics is a rapidly evolving specialty and family physicians may not have the specific expertise to follow up with patients diagnosed with genetic disorders. This led to coinage of the term ‘diagnose and adios’ by clinical geneticists, who oftentimes find themselves disengaged from patient management. This is an area in the current medical system that requires more advocacy and change. Not all patients diagnosed with a genetic disorder follow-up with their family physician, however. For certain genetic disorders, there are clinics where clinical geneticists follow-up with their patients, such as the GoodHope clinic (for Ehlers-Dalnos syndrome) and the Genometabolic clinic, where Dr Faghfoury practices. Unfortunately for many patients, this is an equity problem. For example, a patient with a certain genetic disorder will not find a clinic with clinical geneticists to follow-up with, and must do so with their family physician. “Why is it their fault that their mutation happened to be in a gene that didn’t have a subspecialty clinic attached to it? It’s not fair.” This inequity between patients with different genetic disorders is a target for many genetic professionals, whose goal is to ensure that all patients get the best care possible.

The future of the field of clinical genetics looks promising. Recent developments in the field of genetics such as whole-genome sequencing and whole exome sequencing have drastically changed the landscape of managing genetic disorders. An exciting paradigm shift for clinical geneticists mentioned by Dr. Faghfoury is straying away from strictly depending on phenotyping for clinical identification thanks to genetic testing. One example of this shift can be seen with the rapidly expanding field of pharmacogenomics, the study of how genes affect an individual’s response to drugs. Cytochrome P450 2D6 (CYP2D6) is an important gene involved in the metabolism of about 20% of commonly prescribed drugs (Taylor 2020). Interestingly, CYP2D6 is highly variable across different populations, which can directly influence drug metabolism in individuals carrying such variants. To date, 72 different drugs have CYP2D6 clinical guidelines mentioned within their FDA-approved product labels (Taylor 2020). Instead of the trial and error approach typically needed to assess drug efficacy in patients, genetic testing of CYP2D6 can identify individuals that may experience adverse reactions or reduced efficiency, to tailor therapeutic doses accordingly (Taylor 2020). While pharmacogenomics offers exciting potential for personalizing medicine, barriers remain to clinical implementation. Such barriers include the necessary educational and equipment infrastructure to perform and interpret such tests. Moving forward, there will be a greater need for expertise to efficiently integrate genetic testing into commonplace clinical practice. As Dr. Faghfoury puts it,  “right now we need all hands on deck” to effectively usher in this new and rapidly evolving era of healthcare.

References

1. Tromans, E., Barwell, J. Clinical genetics: past, present and future. Eur J Hum Genet (2022). https://doi.org/10.1038/s41431-022-01041-w
2. Efthymiou, S., Manole, A., & Houlden, H. Next-generation sequencing in neuromuscular diseases. Current opinion in neurology, 29(5), 527–536. (2016). https://doi.org/10.1097/WCO.0000000000000374
3. Rabbani, B., Tekin, M. & Mahdieh, N. The promise of whole-exome sequencing in medical genetics. J Hum Genet 59, 5–15 (2014). https://doi.org/10.1038/jhg.2013.114
4. Belkadi, A., et al. Whole-genome sequencing is more powerful than whole-exome sequencing for detecting exome variants. Proc Natl Acad Sci U S A. 112(17), 5473–5478. (2015). https://doi.org/10.1073/pnas.1418631112
5. Barrett, L. W., Fletcher, S., & Wilton, S. D. Regulation of eukaryotic gene expression by the untranslated gene regions and other non-coding elements. Cellular and molecular life sciences : CMLS, 69(21), 3613–3634. (2012). https://doi.org/10.1007/s00018-012-0990-9
6. Perenthaler, E., Yousefi, S., Niggl, E., & Barakat, T. S. Beyond the Exome: The Non-coding Genome and Enhancers in Neurodevelopmental Disorders and Malformations of Cortical Development. Frontiers in cellular neuroscience, 13, 352. (2019). https://doi.org/10.3389/fncel.2019.00352
7. Scheffer IE. The Key to FAME: Intronic Repeat Expansions Cause Human Epilepsies. Epilepsy Curr. 2018;18(4):238-239. doi:10.5698/1535-7597.18.4.238
8. Goh, G., Choi, M. Application of Whole Exome Sequencing to identify Disease-Causing Variants in Inherited Human Disease. Genomics Inform. 10(4):214-219. (2014).
9. Taylor C, Crosby I, Yip V, Maguire P, Pirmohamed M, Turner RM. A Review of the Important Role of CYP2D6 in Pharmacogenomics. Genes (Basel). 2020;11(11):1295. Published 2020 Oct 30. doi:10.3390/genes11111295

Genetic disorders often present with a puzzling array of symptoms, making diagnosis challenging. Fortunately, clinical geneticists are on the case! Dr. Marjan Nezarati takes us through the process of providing her patients and their families with answers.

Meredith Laver & Alex Margaritescu

The Clinical Genetics department at NYGH sees a wide variety of cases that span a few main categories. Generally, a person is referred to clinical genetics if they are suspected of having a genetic disorder, either because of a family history, or because they are presenting symptoms. Children are often referred for developmental delay combined with one or more dysmorphic features. Prenatal cases are referred when a parent has an unusual screening test such as an ultrasound, or a family history of genetic disorders. NYGH also runs a hereditary cancer clinic which sees individuals with a familial history of cancer. Dr. Nezarati laments lengthy wait times and explains that they “really don’t have the resources”, given the number of referrals they receive. After a referral is accepted, the patient is scheduled to see a clinical geneticist like Dr. Nezarati. She then gets a detailed picture of the patient’s family history and gives a preliminary overview of possible findings. Most cases require additional testing to elucidate physical symptoms, or to investigate genetic causes. 

Dr. Nezarati has access to a toolkit of genetic tests to help identify the molecular causes of disease. Genetic tests look for the presence of potentially disease-causing changes in a patient’s DNA. Prenatal cases receive either non-invasive prenatal screening (NIPS) or invasive prenatal testing (IPT). Prenatal testing is time-sensitive as parents must make informed decisions and prepare for health challenges before a child is born. Although IPT is faster and provides more information, some parents opt for NIPS first because of the small risk of miscarriage associated with IPT⁴. One of two common IPT methods, chorionic villus sampling (CVS) or amniocentesis, is used to acquire a sample of fetal DNA. CVS harvests a small tissue sample of the chorion which is a membrane enveloping the fetus, and amniocentesis harvests the amniotic fluid which surrounds the fetus⁴. The DNA derived from these samples can then be tested for common disease-causing mutations and chromosomal abnormalities.

In contrast, children and adults who present with suspected genetic syndromes usually receive microarray testing of blood samples. Microarrays detect duplications or deletions of specific genomic regions. If a particular condition is suspected, a microarray is ordered which tests at sites at which duplications or deletions are known to cause that condition. Since microarrays have become fairly common tests, geneticists are now trying to encourage family physicians and specialists to order them independently, instead of submitting a genetics referral.

If microarray testing doesn’t reveal a diagnosis, and a genetic syndrome is still suspected, Dr. Nezarati will often order either a gene sequencing panel or whole exome sequencing (WES). Sequencing identifies the DNA sequence of a portion of the genome. Gene panels involve sequencing only the genes which are commonly associated with a specific disorder or symptom, and are typically used to confirm a clinical diagnosis. WES looks at the entire exome, which is the portion of the genome that contains instructions to make cellular products such as proteins. Although the exome makes up only 1% of the genome, approximately 85% of disease-causing mutations are located in these areas⁵. It can be much more cost effective to sequence the entire exome than to run multiple gene panels if the first is inconclusive, making WES a good diagnostic test for patients whose clinical diagnosis remains elusive⁵.

In some cases, the usual genetic tests fail to identify a causative mutation, leaving patients and families without answers. Geneticists can bridge the gap between emerging research and clinical practice by submitting these especially puzzling cases to research studies. This practice helps to provide patients with a diagnosis, and uncover new molecular signatures of disease. Dr. Nezarati is the primary investigator at NYGH for two research studies which use expanded testing methods to investigate undiagnosed cases: Care4Rare–SOLVE and EpiSign.

Care4Rare is a consortium that was founded in 2011 to unite researchers and clinicians across Canada in providing care for individuals with rare diseases⁶. The current iteration of the project is called Care4Rare–SOLVE and is focused on identifying the molecular causes of rare genetic conditions⁶. Clinical researchers like Dr. Nezarati collect and share data to help expedite patient diagnosis and the classification of new disorders. Patients enrolled in Care4Rare receive access to whole exome and genome sequencing, as well as expanded testing methods which include RNA sequencing⁶. Dr. Nezarati signed a young girl up for an early form of Care4Rare after a battery of standard tests failed to produce a diagnosis. They entered the patient’s phenotype and genotype data into a knowledge sharing database called Matchmaker Exchange and suddenly the pieces began falling into place. There was “someone from Australia and another person from the US, and they [had] patients with mutations in the same gene.” Researchers and clinicians around the world were able to work together to formally classify a new rare genetic disorder and begin to build a knowledge base⁷. Around half of the individuals enrolled in Care4Rare have received a diagnosis for their rare disease⁶. A formal diagnosis can help patients and families to seek appropriate healthcare, inform family planning decisions, and allow them to connect with others through shared experiences. 

Even advanced DNA testing methods can sometimes fail to produce a diagnosis. In these cases, patients can be enrolled in EpiSign for epigenetic analysis. Genetic and environmental differences create changes in the way that DNA regions are packaged and read. Epigenetics is a branch of genetics that looks at how these differences impact gene expression. Certain genetic disorders such Fragile X, Prader-Willi, or Kabuki Syndromes are associated with recognizable epigenetic signatures⁸. EpiSign analyzes a patient’s epigenetic pattern in order to identify these signatures and connect them to a diagnosis⁸.

So how does a patient qualify for submission to a research study? “Really, it’s when we are highly suspicious…that it’s a syndromic diagnosis that we’re not catching by routine testing. And sometimes it’s individuals who have a clinical diagnosis”, Dr. Nezarati explains. “So I’m looking at this person and I think they have Kabuki syndrome, let’s just say, and we do the [sequencing] panel of Kabuki genes and we don’t find a hit. Then that would be a case where you could say, well, let’s submit this to Care4Rare–SOLVE or even to EpiSign to see if the epigenetic signature matches the epigenetic signature for Kabuki syndrome.” The interest and consent of the family is also paramount – “if they don’t want to do it, that’s the end of the discussion.”

In some cases, clinical geneticists are able to collaborate with researchers around the world to help assess the impact of new mutations. “I find most of the time when I’ve reached out to people internationally, even big names… I hear back from them”, Dr. Nezarati recounts. “Geneticists are generally… very, very generous with their time.” One couple who had lost multiple pregnancies was looking for an answer. Often in these cases, recurrent mutations in the fetus are responsible. Genetic testing identified mutations in the fetus and parents in a gene which had not been formally recognized as disease-causing. Dr. Nezarati reached out to a group researching the gene to help solve the case. The researchers recreated the mutations in yeast and found that this particular combination of mutations completely disabled the gene. Fortunately, the couple was able to receive prenatal testing for these mutations in future pregnancies.

Nevertheless, a clinical geneticist’s job isn’t all thrilling detective work and happy endings. Even if a diagnosis can be found, many genetic disorders lack therapy options which address the root cause; patients rely on treatments to manage each individual symptom. Families may also face hurdles from the medical system; Dr. Nezarati describes how one child’s mother “had to really fight to get a referral.” Nonetheless, Dr. Nezarati finds that many patients and families take comfort in understanding their situation, and in feeling understood. “Sometimes I really find I’m sort of just a listener. Sometimes I make very little difference and it’s just the willingness, and having the time to sit and listen to someone. That may be all I can do for them, but sometimes that’s helpful.”

References

1. Baird, P. A., Anderson, T. W., Newcombe, H. B. & Lowry, R. B. Genetic disorders in children and young adults: a population study. Am J Hum Genet 42, 677–693 (1988).

2. Basel, D. Dysmorphology in a Genomic Era. Clin Perinatol 47, 15–23 (2020).

3. About CORD | Canadian Organization for Rare Disorders. https://www.raredisorders.ca/about-cord/.

4. Beta, J., Zhang, W., Geris, S., Kostiv, V. & Akolekar, R. Procedure-related risk of miscarriage following chorionic villus sampling and amniocentesis. Ultrasound in Obstetrics & Gynecology 54, 452–457 (2019).

5. Choi, M. et al. Genetic diagnosis by whole exome capture and massively parallel DNA sequencing. Proc Natl Acad Sci U S A 106, 19096–19101 (2009).

6. Osmond, M. et al. Outcome of over 1500 matches through the Matchmaker Exchange for rare disease gene discovery: The 2-year experience of Care4Rare Canada. Genetics in Medicine 24, 100–108 (2022).

7. White, S. M. et al. A DNA repair disorder caused by de novo monoallelic DDB1 variants is associated with a neurodevelopmental syndrome. Am J Hum Genet 108, 749–756 (2021).

8. Sadikovic, B. et al. Clinical epigenomics: genome-wide DNA methylation analysis for the diagnosis of Mendelian disorders. Genet Med 23, 1065–1074 (2021).

Understanding the mechanism of repeat expansion has allowed Dr. Christopher E. Pearson and colleagues to target unique disease-associated mutagenic DNA structures as a potential therapeutic avenue.

Elvira Mukharryamova, Sornnujah Kathirgamanathan, and Tanvi Anadampillai

            The progressive neurodegeneration (loss of brain cells) in individuals with Huntington Disease (HD) highlights the limits of modern medicine in relation to prognosis and cure. As a condition that worsens over time, HD individuals become entirely reliant on others for their daily living. The characteristic neurodegeneration in HD individuals is due to a curious mutation of DNA, called tandem repeat expansions, in the protein-coding gene HTT, which is involved in brain development. These repeat expansions consist of nucleotide sequence units, such as CAG in the case of HD, that occur in tandem (‘CAG CAG CAG…’). For example, healthy individuals carry a repeat tract lengths of 5-35 ‘CAG’ units in the HTT gene. Individuals with 35-39 copies are at an increased risk for HD, while those with 40 or more copies will develop HD earlier in life¹ (Fig. 1A). Importantly, Pearson says “As patients age, the mutation continues in their brains and their disease worsens. For example, ‘THE CAT ATE THE FAT FAT RAT’ mutates to ‘THE CAT ATE THE FAT FAT FAT RAT,’ which eventually mutates to ‘THE CAT ATE THE FAT FAT FAT FAT FAT RAT,’ and so on.” The number of tandem repeats in functionally relevant genes – also referred to as repeat length – is negatively correlated with symptom age-of-onset and positively correlated with disease progression and severity  (Fig. 1B). Generally, longer repeat lengths lead to an earlier age-of-onset with a more severe disease phenotype². “Essentially, for therapy we would like to put that RAT on a diet, which should delay onset and slow progression”, says Pearson. Tandem repeat expansions also cause 69 other serious disorders³

            When it comes to elucidating the underlying mechanisms of disease-associated repeat expansions, it is difficult to find someone with a higher level of expertise than Dr. Christopher E. Pearson – a Canada Research Chair in Disease-Associated Genome Instability, a Senior Scientist at The Hospital for Sick Children, and a Full-Professor at the University of Toronto. In a career that spans nearly three decades, Dr. Pearson has published 97 publications largely focusing on tandem repeat DNA sequences and the mechanism of disease-causing repeat expansion. Looking back on his decision to pursue what Dr. Pearson calls “dynamic mutations” back in 1993, he considers himself fortunate to have discovered something that has captured his curiosity and become increasingly relevant all these years. 

The inspiring work of Dr. Pearson and his team has contributed greatly to our current understanding of repeat expansions. His recent publications featured here, have catapulted the field closer to developing a treatment that can potentially reverse repeat-associated neurodegenerative diseases.

Repeat expansions as a driver of disease

            In molecular genetics, the adage “you can’t harvest what you haven’t planted” holds true. One cannot design a treatment for a complex genetic disorder without first understanding the molecular mechanisms of its pathogenicity⁴. In HD, the root cause of disease is the inheritance and ongoing expansion of tandem repeats, where the repeats expand throughout an individual’s life, causing symptoms to worsen². Although the exact mechanism of expansion has remained elusive, several factors involved in repeat instability have been established. They include repeat length, slipped-DNA structures, and the influence of DNA repair proteins⁵.

A distinguishing feature of disease genes with expanded repeats is the presence of unusual slipped-DNA structures. Slipped-DNAs form at expanded repeats when unwound DNA attempts to reanneal but does so incorrectly, “much like a mis-aligned zipper”, says Pearson (Fig. 2). Slipped-DNAs occur only if the gene contains a threshold number of tandem repeat units, where greater number of repeats enhances slip-out formation. Slipped-DNAs are critical because they act as mutagenic intermediates of instability by attracting DNA repair proteins, which ultimately drive further repeat expansion, which enhances slip-DNA formation…leading to a compounding cycle of expansion mutations. These DNA repair proteins introduce additional repeats through the error-prone attempts to repair the slipped-DNAs – in this manner, rather than protecting against mutation the repair proteins are driving mutations (Fig. 2)⁶.

            Dr. Pearson remembers identifying slipped-DNAs by accident during his time as a post-doctoral fellow. He recalls thinking at that moment that these unusual structures must be important and might even be the key to novel therapeutics. Lo and behold, Dr. Pearson’s suspicions turned out to be right.

Overview of mutation-centric therapeutic targets

            Multiple therapeutic approaches can target various downstream pathogenic aspects of HD, such as lowering the mutant repeat RNA transcript or mutant protein aggregates. Current approaches looking to treat repeat expansion disorders at the root-cause, the DNA mutation, have either targeted the repeat sequences themselves, or the DNA repair proteins involved in repeat expansions⁴. However, a significant limitation of these approaches is that they lack the specificity required to treat only the disease-causing gene in affected cells, while avoiding the normal gene and other off-target effects. Dr. Pearson provides the example of potentially targeting MSH3 or FAN1, DNA repair proteins that drive or supress CAG expansions⁶. Key features of these proteins is their DNA structure-specificity, meaning they only recognize and process unusual structures like slipped-DNAs. MSH3 and FAN1 can modulate repeat stability by either promoting or inhibiting repeat expansion^5,7. Additionally, certain variations in the MSH3 and FAN1 genes can alter the age-of-onset and progression of various repeat expansion disorders, including HD. Taken together, altering levels of MSH3 or FAN1 could therapeutically modulate expanded pathogenic repeats. However, due to the involvement of MSH3 and FAN1 in maintaining the integrity of the entire genome through DNA repair, targeting these proteins would certainly affect their actions elsewhere beyond the mutant CAG tract. One can expect modulating the levels or activities of MSH3 and FAN1 will cause widespread DNA abnormalities, possibly resulting in cancer.  This lack of specificity could be worrisome.

A novel molecule targets slip-out structures to reverse repeat expansion 

            Hoping to find an alternative therapeutic avenue that can address the challenge of specificity, Dr. Pearson and colleagues designed the small molecule DNA ligand Naphthyridine–Azaquinolone (NA). This molecule has a high degree of specificity to slip-out structures within expanded CAG repeats, effectively providing a means of differentiating between normal and pathogenic alleles, as well as the rest of the genome⁸. This feature of NA reduces its off-target effects and can be attributed to Dr. Pearson’s unique appreciation for the importance of structure-specificity: “Slipped-DNAs only form at the disease repeats that are long and unstable, this provides exact specificity of NA to only the disease gene.”

            Although the discovery of a molecule that could recognize and bind pathogenic CAG repeats was exciting, Dr. Pearson admits that the group had no prior knowledge of whether this molecule could prevent repeat expansions, let alone induce contractions. He adds “It was a blind experiment…stabilized repeats would be good, contractions would be even better, but enhanced expansions would be really bad”. Subsequent work by Dr. Pearson and colleagues demonstrated that in addition to its binding specificity, NA stabilized and shortened the expanded repeats in affected brain cells. “We were ecstatic that NA induced CAG contractions in the brain to less than what the HD mice inherited”, explains Dr. Pearson. NA is believed to obstruct the processing of slip-out structures by FAN1, thus inducing CAG contractions, but details of this obstruction remain to be elucidated. 

            Dr. Pearson explains that in addition to having spectacular specificity, NA induces contractions in the majority of treated brain cells in HD mice. This is astounding feat considering that NA must cross both cellular and nuclear membranes to reach its target DNA. Moreover, Dr. Pearson and colleagues observed an improvement in motor coordination of these mice after only four weeks of treatment with NA⁹. Assuming the effects in mouse models can be translated into humans, the effectiveness of NA in treating repeat expansion disorders is extremely promising. Given the complexity and progressive degeneration of these conditions, NA’s rapid and effective onset of action, makes the molecule an attractive treatment option for HD individuals. While direct delivery to the central nervous system is an option, the ability for NA to cross the blood-brain barrier, which is unknown, would facilitate delivery. Further studies are needed to enhance delivery, and characterize this molecule’s tissue distribution and safety profile.

The Future of HD Therapeutics: Just Keep Fishing

            According to Dr. Pearson, the first-of-its-kind approach of targeting slip-out-structures with NA has advanced the field of HD therapeutic development. However, as this approach is still in its infancy, whether NA will survive the “valley of death” – a term used to describe the hurdles of drug development – is still unknown. Dr. Pearson intends to continue improving the druggability and safety profile of NA up until its translation to the bedside: “We will do what we can to improve delivery and safety – we’re working on that now.”

            Dr. Pearson’s team are investigating other potential therapeutic avenues centered upon targeting expansions – or in his terms, “fishing in multiple waters”. These approaches include identifying new DNA repair proteins involved in expansions, screening for inhibitors/modifiers of MSH3, FAN1 or other DNA repair proteins. Dr. Pearson emphasizes that “Fishing in multiple waters increases the likelihood that one of these approaches will cross the long, wide and deep valley of death” and go on to become an approved treatment for HD. Were more than one approach to succeed, combinatorial therapeutic regimens could be developed to further enhance patient outcomes. Despite current excitement and hope, Dr. Pearson acknowledges that crossing this valley is a long and challenging journey and credits the young, bright, and intelligent students and fellows in his lab for taking up the challenge.

The applicability of NA in treating repeat expansion disorders

            Might the discovery of NA be applied to other repeat expansion disorders? That NA targets CAG slip-outs suggests it could act on the other 15 CAG-expansion disorders, including spinocerebellar ataxias and dentatorubral-pallidoluysian syndrome (DRPLA). Dr. Pearson and his team recently revealed that NA contracted CAG repeats and improved motor coordination in a mouse model of DRPLA⁸, validating the broad applicability of this approach. 

                  Looking to the future, Dr. Pearson is expanding his focus to other repeat expansion disorders, such as amyotrophic lateral sclerosis, frontotemporal dementia, and schizophrenia. Dr. Pearson claims, “the likelihood that other repeat sequences causing other diseases are forming unusual mutagenic structures is extremely high, which is why we are searching for ligands to those”. As the field of repeat expansion disorders continues to advance, Dr. Pearson is ready to face new questions that will arise for him and his team to address. 

Hoping to motivate young minds, Dr. Pearson concludes our interview by thoughtfully reminding us of the importance of pursuing interests, not career paths: “follow your nose, follow what excites your curiosity”. 

References:

1.        Lu, X. H. & Yang, X. W. ‘ Huntingtin Holiday’ : Progress toward an Antisense Therapy for Huntington’s Disease. Neuron 74, 964–966 (2012).

2.        Flower, M. D. & Tabrizi, S. J. A small molecule kicks repeat expansion into reverse. Nat. Genet. 52, 136–137 (2020).

3.        Gall-Duncan, T., Sato, N., Yuen, R. K. C. & Pearson, C. E. Advancing genomic technologies and clinical awareness accelerates discovery of disease-associated tandem repeat sequences. Genome Res. 32, 1–27 (2022).

4.        Malik, I., Kelley, C. P., Wang, E. T. & Todd, P. K. Molecular mechanisms underlying nucleotide repeat expansion disorders. Nat. Rev. Mol. Cell Biol. 22, 589–607 (2021).

5.        Deshmukh, A. L. et al. FAN1, a DNA Repair Nuclease, as a Modifier of Repeat Expansion Disorders. J. Huntingtons. Dis. 10, 95–122 (2021).

6.        Deshmukh, A. L. et al. FAN1 exo- not endo-nuclease pausing on disease-associated slipped-DNA repeats: A mechanism of repeat instability. Cell Rep. 37, 110078 (2021).

7.        Porro, A. et al. FAN1-MLH1 interaction affects repair of DNA interstrand cross-links and slipped-CAG/CTG repeats. Sci. Adv. 7, 1–13 (2021).

8.        Hasuike, Y. et al. CAG repeat-binding small molecule improves motor coordination impairment in a mouse model of Dentatorubral–pallidoluysian atrophy. Neurobiol. Dis. 163, 105604 (2022).

9.        Nakamori, M. et al. A slipped-CAG DNA-binding small molecule induces trinucleotide-repeat contractions in vivo. Nat. Genet. 52, 146–159 (2020).