As many U of T students were wrapping up classes in March, first-year engineering student Hannah Le and her team won the third Pioneer Tournament — a worldwide competition that rewards participants for developing innovative ideas — for their project that used machine learning to identify and understand human biomarkers that predispose individuals to certain diseases.

Competition participants submit their project online and post weekly progress updates. The project then earns points awarded by contestants, who vote on the updates. After three weeks, the project becomes eligible to win a weekly prize, which is awarded to the team that wins the highest number of points at the end of that week. A project that places as a finalist for three weeks wins the team a larger award.

Le and her team members — Samarth Athreya, 16, and Ayaan Esmail, 14 — earned a top spot on the leaderboard in March and were awarded $7,000 from Pioneer to put toward their project. 

How the team got together

“Samarth, Ayaan and I met each other at an organization called The Knowledge Society in 2017,” wrote Le to The Varsity. The Knowledge Society is a startup incubator that exposes high school students to emerging technologies, such as artificial intelligence (AI), virtual reality, and brain-computer interfaces.

When the three innovators met, Esmail was working on a project that could accurately pinpoint and target cancer cells, while Athreya was working with machine learning models. With Le’s interest in genetics, the three decided to team up and investigate whether there was a way to use metabolic data to predict the onset of a disease.   

“I became incredibly curious on how we can decode the 3 billion letters [of DNA] in every cell of our body to increase human lifespan and healthspan,” wrote Le.

“Inspired by my grandmother who passed away due to cancer, I started asking myself the question: [could] there possibly be a way for us to predict the onset of cancer before it happens, instead of curing it?”

How Le’s team developed a model for predicting the risk of cancer development

At its core, the team’s AI platform uses a patient’s biological information to predict their risk of developing certain forms of cancer.

Metabolites are molecules that play a key role in maintaining cellular function, and some studies have shown that high levels of certain metabolites can signal the progression of lung cancer. But to develop and test their model, the team needed a large amount of metabolic data.

“To overcome such [a] limitation, we had the fortune to reach out to mentors such as the Head of Innovation at JLABS, [a Johnson & Johnson incubator], for further guidance and advice,” wrote Le. “As our team cultivates a stronger database, we would be able to produce more reliable results.”

“As teenagers we were far from experts [in] the field — but we were really hungry to learn,” added Le.

As participants of the Pioneer Tournament, Le and her team received the opportunity to select a board of virtual advisors, who would provide guidance for their project.

“I recalled contacting Josh Tobin at OpenAI to ask him about the use of synthetic data in genomics research,” wrote Le. “[That enabled] us to understand both the strengths and weaknesses of such [an] approach, allowing us to pivot on what models to implement.”

The competition as a learning experience

Le remembers the Pioneer Tournament as an exciting chance to learn about different machine learning models and what made them effective as well as other projects that fellow participants were working on, all while attending courses at U of T.

“First year was an interesting journey of challenging course content, intertwined with unexpected personal growth,” wrote Le. “I learned how to strike a balance between working on personal projects, meeting interesting people, while completing my school work.”

And while Le is intrigued by the intersection of machine learning and genomics, she wrote, “I hope to keep an open mind and continue to be curious about the world around me.”

According to a recent study published in Nature Genetics, risky behaviour may be linked to genetics. The international collaborative project involved 96 co-authors and identified 124 independent genetic mutations associated with general risk tolerance in humans. 

Risk tolerance refers to a person’s willingness to take a risk, with the goal of attaining a reward. “People who have higher risk tolerance are more likely to start up their own business, to invest in risky stocks, to do risky sports, take social risks and so on,” said Dr. Jonathan Beauchamp, one of the senior principal investigators and Assistant Professor of Economics at U of T, at the 2018 Paul G. Allen Frontier Group Conference. 

Risk tolerance “is such a fundamental parameter in the behavioural sciences,” continued Beauchamp. “It’s really at the core of all the economic models, macroeconomics, and also labour market decisions.”

The findings of this study provide examples of the many insights that can be gained from genome-wide association studies, which scan the genomes of many people in an attempt to associate genetic variants with particular outcomes. 

Genetic information and self-reported answers to questions regarding risk tolerance were collected from 12 different genetic databases, including UK Biobank and 23andMe. The study involved over one million people of European ancestry.

Once the researchers completed the data collection, genetic variants were matched with their respective risk tolerance profiles, and associations were made between various behaviours.

The 124 identified genetic variants play a small role in influencing risk tolerance when assessed individually. But together, the associations can help explain the genetic basis of risky behaviour. 

When the effects from all 124 variants were combined, a polygenic score, or numerical value that accounts for all variants in a single distinct genome, was created.

The polygenic score can explain up to about 1.6 per cent of variation in risk tolerance across a population. While this score does not have predictive value to determine the risk tolerance of a certain individual, it can be put to use in social science studies, which focus on the behaviour of a population.

The study also points to the high genetic association between risk preferences and risky behaviours. 

“There’s a debate in economics as to whether there is domain-general or domain-specific risk preferences, meaning whether your risk preference for health is correlated to your risk tolerance for driving fast or investing and so on,” said Beauchamp. “Some people have concluded that it seems they’re not correlated… but we find that, at the genetic level, there really seems to be a genetic component that affects risk preferences across domains.” 

The researchers found no support for the involvement of the main biochemical pathways previously thought to be related to risk tolerance, which included dopamine, serotonin, cortisol, estrogen, and testosterone. 

Instead, they found a role for the main excitatory and inhibitory neurotransmitters in genetically determined risk tolerance, glutamate and GABA respectively.

Beauchamp explained that this lack of corroboration is likely due to the relatively small sample sizes of previous studies. 

“To date… nearly all published studies attempting to discover the genetic variants associated with risk tolerance have been ‘candidate-gene studies’ conducted in relatively small samples ranging from a few hundred to a few thousand individuals.” 

As a result, the sample sizes from the candidate-gene studies were too small to identify genetic variants involved in risk-tolerance.

In part, this issue fostered Beauchamp’s support and involvement in the Social Science Genetic Association Consortium, which pools samples of genetic information so that researchers can look into genetic links using large sample sizes.

However, with all the media hype around genetics, Beauchamp warned not to neglect ‘nurture’ when it comes to human behaviour. 

“I think it’s important to emphasize that environment also matters, so we’re not saying that genes are the only thing important for risk,” said Beauchamp. 

Professor Ben Blencowe and his team at U of T have uncovered a network of around 200 genes that are linked to autism. Blencowe and his team published these findings in a study in Molecular Cell.

Autism spectrum disorder (ASD) comprises a range of conditions that affect social interaction, behaviour, and communication skills.

Because autism is not a single disorder but a spectrum of related conditions, there is no one discernible cause for it. Instead, a combination of biological, environmental, and genetic factors can be attributed to ASD.

There is also evidence of a strong genetic component in individuals with autism. Previous studies have found that in a family with one autistic child, the chance of having another autistic child is higher than the general population. Identical twins are also more likely to both develop autism than fraternal twins.

Most gene variations affect neural development and produce ASD symptoms through interactions with other genetic and environmental factors.

To determine a genetic link to autism, Blencowe and his team used a CRISPR-based method — a powerful gene editing tool — to identify neuronal microexons that are commonly misregulated in individuals with autism.

Microexons are small protein-coding regions in a gene locus, and are often involved in alternative splicing. Alternative splicing codes for different proteins in the same gene through different combinations of exons — protein-coding sequences — and removing different introns — non-coding sequences — from the messenger RNA (mRNA) transcript.

The altered versions of the mRNA transcript are then translated into several different types of proteins.

According to lead researcher Dr. Thomas Gonatopoulos-Pournatzis, the study was based on the team’s previous research which showed “that a network of neuron-specific microexons is frequently disrupted in the brains of autistic individuals.”

In other words, disruptions in alternative splicing affect how proteins communicate with one another, and could explain the molecular basis of autism.

The researchers isolated SRRM4, a protein that regulates splicing in neural cells, and found that mice with lowered SRRM4 expression displayed ASD-like traits.

The study reports that SRRM4 disruption in the brain has been found in one third of individuals with autism and has been identified as a convergent mechanism for the disorder.

“A critical challenge emerging from these findings is to identify the full repertoire of factors and pathways that converge on SRRM4 to control microexon splicing,” wrote Gonatopoulos-Pournatzis in an email to The Varsity.

In particular, SRRM4 is critical during embryonic development. It helps differentiate neural cells and promotes the development and proper functioning of a working adult nervous system.

In this study, the CRISPR-based screening identified and targeted specific DNA regions using a genome-wide approach.

“[It] systematically [inactivated] all protein-coding genes,” and tagged and isolated cells with altered microexon splicing levels. Then, high throughput sequencing identified “genes responsible for controlling micro-exon splicing,” wrote Gonatopoulos-Pournatzis.

“The screen performance exceeded our expectations and we captured over ~200 regulators that affect microexon splicing by direct or indirect mechanisms. Interestingly, these genes are enriched for genetic links to autism,” he added.

Uncovering “a core set of factors that are critical for microexon splicing” has implications beyond autism. Such factors could help inform researchers developing treatments for neurodevelopment disorders, including through the potential restoration of microexon splicing in misregulated cells.

In the future, the researchers hope to determine the association of microexon misregulation to specific behaviours characteristic to autism, and the roles of individual microexons.

When the human genome was first sequenced in 2003, scientists were optimistic that a medical revolution was on the horizon. The promise of personalized medicine seemed within reach. 

But 15 years later, this revolution hasn’t materialized and researchers are still uncovering the meaning of the genome. 

The research bias

Although the human genome has about 20,000 genes, researchers have focused most work on a small minority of genes. 

In 2011, Gary Bader, a professor at the Donnelly Centre for Cellular and Biomolecular Research, and his colleagues contributed to an article in Nature that highlighted this gap in research. 

More recently, a study led by Thomas Stoeger at Northwestern University reported that the gap remains and scientists are still studying only a fraction of the genome. 

Based on Stoeger’s work, approximately one quarter of genes have never been studied by a full publication and remain poorly characterized.

Gene trends through the decades 

Different genes have been popular over the decades, falling in and out of fashion with time. The National Library of Medicine (NLM) in the United States has been tracking publications on genes in its PubMed database, which revealed these trends. 

In the early 1980s, a significant chunk of genetic research focused on HBB, a gene critical for the development of hemoglobin, the molecule responsible for carrying oxygen in red blood cells.

Interest in hemoglobin was spurred by the work of researchers in the 1940s and 1950s who discovered the role of abnormal hemoglobin in sickle cell disease, a disorder in which individuals are at risk of developing multiple infections and pain episodes over their lifetime. 

But hemoglobin’s popularity was short-lived. The 1980s brought about new medical concerns that shifted genetic research to different diseases. 

In particular, an unknown immune system disease that was striking apparently healthy individuals at alarming rates and overwhelmingly affecting gay men shook the public and the medical community to its core. 

Scientists soon discovered that the mysterious illness was attributed to human immunodeficiency virus (HIV), a virus that targets CD4 cells, which are a type of mature T cell that help coordinate the immune response to an infection. 

The outbreak of HIV across the world garnered attention from politicians, policymakers, and the research community. By 1987, the CD4 gene dominated genetic research and retained its popularity until the mid-1990s. 

By 2000, the TP53 gene was gaining traction. Dubbed the ‘guardian of the genome’ by some, the TP53 gene is a tumour suppressor gene and mutates in nearly half of all human cancers. 

While completing his doctoral studies at the University of Vienna, Peter Kerpedjiev sifted through the NLM records and generated a list of the most studied genes. His work showed that TP53 is not the only popular cancer gene: four out of the top 10 most studied genes of all time — TP53, TNF, EGFR and ESR1 — all play some role in cancer development or are targets for cancer drugs.

TP53 was briefly dethroned by APOE, a gene that was initially associated with cholesterol but whose popularity exploded when researchers made a link between variants in the gene to a risk of Alzheimer’s disease. 

Kerpedjiev’s work showed that both genes remain popular in research today. 

Why are some genes more popular than others?

“Researchers usually first study these genes since they seem most important, and this is the answer why only a ‘minority’ have been studied so far,” wrote Stephen Scherer, director of U of T’s  McLaughlin Centre and The Centre for Applied Genomics at The Hospital for Sick Children, in an email to The Varsity. 

Steven Narod, Director of the Familial Breast Cancer Research Unit at Women’s College Hospital, whose research focuses on BRCA1 and BRCA2, two well-characterized genes, proposed that other factors could also be at play, such as the prevalence of mutations in the genes. 

He further explained that research tends to focus on genes “where the clinical implications are clear and the interpretation [of mutations] is straightforward.” 

There are also significant barriers that deter novice researchers from studying unknown genes, according to Bader. In an email, he explained that “it can be difficult for researchers to take risks and explore new territory because if they don’t succeed, they may not be able to continue being funded.” 

Based on Bader’s commentary, funding agencies are generally risk-averse and are less likely to support studies on lesser-known genes, which poses challenges to researchers interested in studying such genes. 

What does the future of genomics hold?

Scherer is hopeful that change will come over time. 

“[The genes] will all be studied but there are only so many resources (human and financial) available, and this will take some time,” wrote Scherer. 

Bader stressed that funding agencies can be part of the shift, by encouraging researchers to explore unknown regions of the human genome.  

For example, the US National Institutes of Health has established funding opportunities targeted at researchers investigating poorly characterized genes. 

The advances in genomic technologies will also likely play a role in the future. 

“New genomics technologies are accelerating progress and making it easier to discover interesting genes,” wrote Bader. He also encouraged researchers to “consider devoting a percentage of their time to exploring new territory, if they are not already doing this, in addition to the major projects that they work on.”

With advancing technologies and support from granting agencies, perhaps the rest of the human genome will become less of a mystery.

An ever-growing list of companies including the likes of 23andMe and Ancestry.com are offering the general public the opportunity to get to know themselves by testing their DNA and offering feedback on results.

The commercial is familiar to fastidious viewers of American broadcast television: a young woman travels the world while a cover of the Broadway show tune “Getting to Know You” plays in the background.

Helpful pop-ups indicate the actress’ ethnic make-up as she crosses the landscapes; “29% East Asian” flashes under the neon lights of a metropolis, “3% Scandinavian” appears among the glaciers.

The ad ends with the tempting offer that you, too, could discover what makes you you just by sending 23andMe a saliva sample.

Such advertisements are indicative of a flourishing industry.

But the self-knowledge they are selling to consumers is no longer restricted solely to an individual’s past.

The latest trend in personalized genomics is in its predictive potential: forecasting an individual’s likelihood of developing conditions like cancer, diabetes, and other diseases someone may be genetically predisposed to.

How do genetic tests work?

According to Dr. Stephen Scherer, Professor of Medicine and Director of the University of Toronto McLaughlin Centre and The Centre for Applied Genomics at Sick Kids Hospital, the tests have a microarray — microscope slides that are printed with thousands of tiny spots in defined positions — with a mix of genetic markers, or DNA sequences with known physical locations on chromosomes.

Depending on the company, each test contains around one million genetic markers.

“They then assay a DNA sample that was derived from saliva sent in a DNA spit kit,” wrote Scherer in an email to The Varsity. “They do some laboratory modifications to the DNA and put it on the microarray and test for presence or absence of a given genetic marker and then use this information to predict the medical outcomes.”

“They utilize the information from published large-scale studies where they provide an estimated risk of disease development for certain genetic variants,” wrote Dr. Ryan Yuen, Assistant Professor of Molecular Genetics, in an email to The Varsity. “These companies will then report the estimated risk for those variants if they are also detected in the subject.”

Yuen also explained how similar methods are used to determine the ancestry of an individual: “They compare the genetic variants detected in the subject with many other sequenced individuals (both internally and externally). The more similar the genotypes are between individuals, the more likely they are related to each other.”

Scherer explained that conclusions for common diseases like heart disease, high blood pressure, or diabetes are made using statistical probabilities and that nothing is definitive.   

“For some rare genetic mutations that are quite predictive of a medical outcome (like cystic fibrosis) the ability to predict risk is much higher,” wrote Scherer.

So, how reliable are these tests?

A cardinal rule of observational data is that correlation does not necessarily imply causation, and therefore the reliability of genetic tests is questionable.

“Although these tests can seem exciting, its important that consumers are informed and understand the limitations of these types of tests,” wrote Salma Shickh, a certified Genetic Counsellor who is pursuing a PhD in Genomics Health Services and Policy Research at U of T, in an email to The Varsity.

“Most of these tests only look at… specific regions of the DNA code and so the risk they provide may not be based on complete information,” explained Shickh. “These tests are often offered without proper education and counselling for patients- which is important because they’re giving consumers information about their health.”

Scherer echoed Shickh’s sentiments. Scherer said that it’s important that consumers realize the results are completed in laboratories, and that companies that sell genetic tests must generate a profit margin, doing so by analyzing many samples at a time.

Consequently, the results are typically, but not always, accurate. In other words, consumers should interpret the results with a grain of salt.

“We believe here that the tests are useful if the data is interpreted by genetic counsellors to help the doctors and families understand what it means, and equally important what it does not mean. Most companies do not use genetic counsellors, they just send the data to you,” wrote Scherer. “If you do this kind of testing seek genetic counselling assistance to help interpret the results.”

What’s the future of genetic tests?

Though genetic tests are not perfect, Scherer noted that their value should not be dismissed.

“[The tests today are] typically not much better than knowing your family history, but as the data grows to compare against, it should get better and better,” wrote Scherer.

“I liken the field today to the early days when GPS units came out. As more and more maps went online (and then Google maps) the predictability kept getting better and better.”

Obesity is a global pandemic, affecting millions of people in North America alone. It has been associated with medical conditions, such as cardiovascular complications and type 2 diabetes.

A recent study published in JAMA Pediatrics suggests that diet may not be the primary cause of obesity. Rather, the presence of a certain gene in women may also be a contributing factor.

Researchers at McGill University recently discovered that the fat intake of women is influenced by a gene called the DRD4 VNTR repeat 7. Although this gene alone does not cause women to become obese, the way that the gene affects the fat intake of the body depends on the environment that the carrier of the gene grew up in.

In particular, the presence of the DRD4 repeat 7 gene, present in approximately 20 per cent of the population, is informed by the carrier’s socioeconomic background. Women who carry the gene will have increased or healthier than average fat intake, if they grew up in a poorer or richer household, respectively. Lead author Laurette Dubê believes that the higher fat intake is due to the carrier’s food choices, rather than due to an underlying metabolic mechanism.

The study focused on 200 Canadian children, aged four, from Montreal, Quebec and Hamilton, Ontario. The researchers calculated the percentages of fat, protein, and carbohydrates the children had consumed based on diaries kept by their parents, while saliva tests were used to determine which children were carriers of the DRD4 repeat 7 gene. The quality of their socio-economic environment was estimated using family income.

“We found that among girls raised in poorer families, those with DRD4 repeat 7 had a higher fat intake than other girls from the same socio-economic background,” said Laurette Dubé.

Conversely, wealthier girls with the same gene variant had a lower fat intake than other girls in the same economic conditions. “This suggests that it’s not the gene acting by itself, but rather how the gene makes an individual more sensitive to environmental conditions that determines […] a child’s preference for fat and consequent obesity as the years pass by.”

The study confirms that DRD4 repeat 7 belongs to a larger class of plasticity genes, which increase or decrease the risk of certain medical conditions depending on an individual’s environment. The study confirmed that DRD4 repeat 7 was indeed a plasticity gene. These results provide a clearer explanation of the underlying causes of diseases like obesity, changing the  focus from the gene to the environment.

Boys with the DRD4 repeat 7 gene were not affected. Perhaps it is because girls need to be prepared to gain more weight to reproduce. Or perhaps it is too early to see the effects of the gene in boys at the tender age of four. Boys and girls gain weight at different stages in this age.

The outcomes of this study have further advanced our knowledge of obesity. Rather than merely blaming genetics, it is now evident that the environment in which one is raised plays a significant role on the development of obesity. It is therefore necessary to focus on both genetic and environmental factors to adequately prevent the pandemic.

Picture this: U of T transfers you out because of your DNA. While it may sound like a twisted joke to most, this is exactly what happened to a Californian student back in 2012. He was told that because of his genes, he could no longer attend his middle school.

Although he was allowed back to school after his parents took this act of ‘genetic discrimination’ to court, it seems farfetched that a ruling was ever needed to resolve the issue in the first place. “It feels like I’m being bullied in a way that is not right,” he commented in an interview with NBCNews TODAY. It is worth noting that the decision was made because of a potential health risk to two students suffering from cystic fibrosis.

Bill S-201 is currently going through committee revision in the senate, after its second reading. It was first introduced in 2013 as S-218 and subsequently tabled, only to be reintroduced as the Genetic Non-Discrimination Bill by its sponsor Nova Scotia senator James Cowan, a long-standing liberal and lawyer by trade.

Dubbed as “an Act to prohibit and prevent genetic discrimination,” it was first referred to the Standing Senate Committee on Legal and Constitutional Affairs and later to the Standing Senate Committee on Human Rights. S-201 prohibits “genetic testing of any person as a condition in exchange for ‘providing goods or services to that individual’” (3.1a) or as part of a contract. This ensures that the results of genetic testing cannot be collected or used without written consent, though it does not apply to healthcare industry professionals such as physicians, pharmacists, or researchers.

The legislation pertains to giving citizens and employees the right to refuse genetic testing, the choice to disclose results of genetic testing, and the need for written consent if results are to be disclosed. This law would be enforced by a fine of up to $1 million and/or five years jail time if indicted; or up to $300, 000  and/or up to 12 months in jail for a summary conviction.

It also includes provisions to various conventions including the Canada Labour Code, the Privacy Act, the Canadian Human Rights Act, and the Personal Information Protection and Electronic Documents Act. According to the bill, this is done: to extend the aforementioned rights to employees; to incorporate these rights into our human rights; to ensure our personal information now includes our genetic material; and to classify information from genetic testing as personal health information.

According to experts and officials, we are currently lagging behind in terms of legal protection. In contrast, our neighbours to the south have already imposed a Genetic Information Nondiscrimination Act in 2008 and anti-discrimination laws for genetics and health insurance in most states. There are exceptions such as Alabama, which only prohibits the use of genetic information for denying coverage for applicants with sickle cell anemia, because it outlaws considering a “predisposition for cancer in risk selection or risk classification.”

In a 2014 Second Reading Debate, senator Cowan made reference to various pediatricians, geneticists, and even celebrities, notably Angelina Jolie, in an effort to convince his fellow senators that advancement in personalized genetic medicine and research will be beneficial to adults and children alike, but it was being hindered by fears of consequences in insurance and employment. Citing Dr. Ronald Cohn, co-director of Sick Kids Centre for Genetic Medicine, Cowan emphasized that the lack of protection against genetic discrimination was “preventing many Canadians from benefiting from extraordinary advances in medical research.”

On a separate occasion, prominent scholars and researchers have also voiced their concerns for the urgent need for protection against genetic discrimination, including bioethicist Kerry Bowman of the University of Toronto.

The senator ended his speech by raising questions of his own: “Does it achieve its objectives? Are there unanticipated consequences we should be aware of? And of course, are there ways in which the bill could be improved?”

While this bill will be beneficial in advancing genetic research and personalized medicine as it is intended, cautions remain in the broader political landscape.

In 2012, the naturally occurring Cas9 enzyme was shown to be able to edit DNA sequences from a number of organisms by researchers at the Zhang Lab at MIT.

While this new powerful genetic editing tool holds great promise for treating an array of genetic disorders, such as HIV, cancers, and lesser known disorders like Duchenne muscular dystrophy; it also raises a number of ethical questions. When do we allow DNA editing in humans? To what extent will we allow for DNA editing to modify our genomes? Are we getting in the way of evolution, and what dangers could modifying our DNA bring about?  Most importantly, how will these changes to our genome get passed down to our offspring?

Due to these important and deeply controversial questions, scientists worldwide agreed to a moratorium on CRISPR-Cas9 gene-editing research in humans. For now, scientists have agreed to allow for clinical gene-editing research in all human cells, but have banned research that edits the germline — a scientific term for the DNA that is passed on from parent to offspring.

There is merit to this stance. The state of CRISPR-Cas9 research is still in its infancy, and needs to be perfected before it can be used in human therapeutics, and must pass a number of tests before it can be used to edit the human germline. CRISPR-Cas9 is not the first technology capable of editing DNA — its predecessors were zinc finger nucleases and TALENs, among other technologies — but so far it is the most promising. That said, biological techniques are not foolproof, and the CRISPR-Cas9 is not immune to off-target effects in the genome.

To put this in perspective, imagine that someone designs a computer program to edit the operating system on your computer. The program used is usually effective and edits the code it intends to. Although every once in a while, it modifies the code of something you need to function (for instance, Microsoft Word). But unlike a computer program or operating system, we cannot simply uninstall and then reinstall the program with the defective code. Instead, we are stuck with something dysfunctional, and the possibility that the defective code will actually interfere with other things that previously were working. To extend the analogy now, we’re left with a computer that cannot do basic word processing, and, scariest of all, cannot be fixed. To make matters worse, off-target effects in germline editing will likely be permanent not only in a single generation, but for generations to come.

The difficulty with CRISPR-Cas9 is that it holds so much promise, that researchers around the world are all racing to incorporate the technology into their work. As this race gets more competitive, the likelihood that someone will attempt something dangerous in the process of conducting ground breaking research increases. Thus the ban on germline editing.

Although CRISPR-Cas9 is possibly very dangerous, research cannot and should not be stopped. If we’re able to solve some of humanity’s most pressing concerns, such as HIV/AIDS, then we have a moral obligation to try. For that reason, the CRISPR-Cas9 gene-editing system might be the latest biomedical advancement to offer serious hope to millions. As long as scientists worldwide ensure that they conduct their research with caution and within certain limits, gene-editing research will be able to make significant advancements safely.

Recently, The Varsity had a chance to attend a discussion with Dr. Feng Zhang of the Zhang Lab, hosted by the Neuroscience Association for Undergraduate Students.

At the event, one student asked, the researcher about his opinion on using the CRISPR-Cas9 system to edit the germline. Dr. Zhang replied, stating that the importance of germline editing varies between groups of people, such as potential parents and policy-makers. As a researcher, he suggested that “we are not ready to use this  [CRISPR-Cas9 gene-editing] for medical treatment, because there are issues with specificity and efficiency,” citing the possibility of off-target effects. He highlighted the possibility of off-target effects causing other disorders, like cancer.

While the CRISPR-Cas9 system is undoubtedly one of the greatest biomedical breakthroughs of the past fifty years, if not the past century, it is not ready for public consumption. While nearly everyone wants this technology to be perfected, it cannot and should not be used until it is. When that day comes, the possibilities for treating disease and improving lives will be endless. It is for that reason, that CRISPR-Cas9 and gene-editing research needs to keep moving at its current pace, while being constrained by a few necessary rules.