By Deborah Borfitz
July 6, 2020 | Rare diseases are just that—atypical conditions that physicians might never encounter and, if they did, would likely stump them about what to do next. But in the aggregate, rare diseases are inching closer to big-disease status as a result of strategic collaboration and whole genome sequencing (WGS), which has helped grow their cumulative number beyond (some posit well beyond) the 7,000 mark.
Unearthing disease-causing variants paradoxically creates the possibility of rare diseases afflicting a single individual and the specter of n-of-1 trials, or at the very least a highly personalized approach to treatment, says Christian Rubio, vice president of strategic advancement for the patient advocacy supergroup Global Genes. And this is precisely why a “platform mentality” is needed around both drug development and data collection.
The platform perspective approaches potential medical treatments “more like medical devices, where you can have one type of gene therapy applicable across several different types of diseases,” Rubio explains. A chief champion of the methodology is Christopher P. Austin, M.D., director of the National Center for Advancing Translational Sciences at the National Institutes of Health, and a featured speaker at the recent RARE Drug Development Symposium co-hosted by Global Genes.
Developing drugs for individual diseases, as is done today, would require about 2,000 years to cure the current rare disease backlog, he notes. Global Genes has been actively teaching patient advocacy organizations that they have “a key role to play in opening up data and larger, data-driven research collaborations” that can accelerate the cure path and the necessary first step of arriving at a diagnosis.
Rubio points to the EB Research Partnership, which has become the longitudinal research partner of more than two dozen data-sharing universities. It’s an example of how advocacy organizations can “ensure continuity of architecture for new researchers and clinical trials that spin up against a larger dataset.”
In a similar vein, the Castleman Disease Collaborative Network (CDCN) has organized a research community around the creation and updating of clinical and diagnostic guidelines specific to Castleman’s disease, says Rubio. Co-founder and Executive Director David Fajigenbaum, M.D., is a Castleman patient and associate director of patient impact for the Penn Orphan Disease Center. He also authored the national bestselling book, Chasing My Cure: A Doctor’s Race to Turn Hope Into Action, which describes a patient-centric model for developing medical guidelines, research protocols and diagnostics.
Both EB Research Partnership and CDCN have been mentors and instructors for Global Genes’ Data DIY program that includes a module on how patient advocates and organization leaders can develop collaborative research networks with clinicians and investigators to advance patient-centric research, Rubio says.
Patient advocacy organizations also have a starring role to play in ensuring emerging disease understanding gets turned into clinical guideline updates that are referenced by clinicians, he adds. “In our field, there isn’t necessarily a big dividing line between bench researchers and clinical researchers or translational researchers because… a clinical trial is often the only kind of treatment option a patient has.”
Promotion and publication of rare disease guidelines are crucial, Rubio says. “One of the big challenges downstream is educating clinicians to recognize the zebras among the horses.”
Tackling Equity
Over the coming decade, the focus of Global Genes will be squarely on bringing more equity to the research landscape, says Rubio. New treatments and diagnostics being approved by the Food and Drug Administration are rooted in clinical trials where people with rare diseases are among those who are poorly represented.
Two goals of Global Genes moving forward are to increase the number of rare diseases actively being researched and to enhance clinical pathways for rare diseases, which go hand-in-hand with improving diagnostics, says Rubio. Shortening the diagnostic odyssey for rare disease patients is the “first great hurdle to pass.”
Rare diseases currently take an average of 4.8 years to be accurately diagnosed and in many patient communities the wait is 15 years or longer. Literally millions of people struggle all of their life to be understood and have a diagnosis that makes sense, he says. Some die without ever getting answers.
As such, Global Genes is an ardent supporter of WGS in the neonatal intensive care unit (NICU). “The greater the number of patients, the faster we get to meaningful breakthroughs,” Rubio says. Great progress has been made in this arena by sequencing initiatives, such as Project Baby Bear at Rady Children’s Hospital that have resulted in fewer diagnostic tests and surgeries as well as shorter hospitalizations.
Studies have variably reported that between 25% and 40% of critically ill babies in a NICU might be candidates for WGS testing, Rubio continues. On a national or global scale, that could exponentially enlarge the number of known rare diseases—which gets back to the diagnostic paradox.
But the tsunami of data also has a big upside, he notes, by allowing for the discovery of what these rare diseases have in common. This will “fundamentally change” diagnostics from being phenotypic to being etiological in nature.
What Comes Next?
Uncovering the genetic cause of a disease is one thing; knowing how to act on it is quite another. Clinical genetics is a complex medical specialty where diagnostics factor in multiple disease-causing variants and interactions between them.
“Just because you can map a disorder back to a faulty gene doesn’t mean you have a clear path to treat it,” says Rubio. “At the same time, whole-genome sequencing is a lot faster and in the end a lot cheaper than a lifetime of struggling with different approaches.”
WGS is also now a consumer product that doesn’t come with an instruction manual. If healthcare providers hope to engage in meaningful shared decision-making with patients over genetic test results, education will be needed on both the general public and clinician side, Rubio says.
A recent study in the U.K. found that clinicians are learning about clinical genetics in medical school but primarily through introductory or required courses. “Most physicians still have to Google a certain genetic disorder or rely on information that comes with a test result to understand exactly what they’re looking at,” he says. “A genetic diagnosis can span a variety of different therapeutic silos and, as we’ve learned in cancer, the immune system plays a much more central role than we’ve given it credit for over the years.”
The answer? Continuing medical education in clinical genetics certainly, says Rubio, but also greater recognition that earlier diagnoses and more tailored, scalable treatment plans make care systems more affordable. Ideally, WGS will become a more frequently reimbursed service that is integrated into the workflow of physicians.
Physicians are trained with “what if” scenarios in mind, continues Rubio, including the possibility that patients’ WGS results might reveal genetic conditions for which nothing can be done. They tend to take on those burdens as if they were theirs to own. “The reality is that in a patient-centered world the patient always needs to know. They will always be better off having a diagnosis over not having one.”
Enlightened practitioners, including Timothy Yu, M.D., Ph.D., (Boston Children’s Hospital) and Wendy Chung, M.D., Ph.D., (New York-Presbyterian Hospital/Columbia University Medical Center) “understand there is a better way… because they are actively doing research as well,” Rubio says.
Clinical researchers, more so than pure clinicians, can “see the light down the tunnel and it tends to influence their outlook on diagnostics,” he says. But Global Genes, through its RARE Compassion Project, is helping to rear up a new generation of physicians with eyes wide open to the realities of having a rare disease.
The idea here is not only to inspire careers in rare diseases, he adds, but also “to understand the importance of storytelling and really good patient notes. From a diagnostic standpoint, the better listening doctors are and the better their notes that go into an electronic health record, the better the potential for artificial intelligence and other emerging tools to potentially spot a rare disease.”
Roles For All
Developers of diagnostics and clinical laboratories have a role to play in improving the detection rate for rare diseases, says Rubio, by welcoming collaboration with advocacy organizations to understand the patient experience with testing. Arriving at a diagnosis “isn’t a journey but an odyssey for patients” and some of the tests can be quite unpleasant.
Regulators, for their part, need to uphold high standards for the accuracy of genetic tests so payers are willing to reimburse for them, a bigger patient population gets diagnosed and more trials launch, Rubio says.
Biopharma companies and contract research organizations (CROs) need to be engaging the rare disease community early and often to ensure the patient experience is considered throughout the drug development process—as over 100 are already doing as corporate partners of Global Genes, says Rubio. The supporters include Horizon Therapeutics and Amicus Therapeutics.
CROs, for the most part, still have “a long way to go in redesigning their relationships with advocacy organizations to be more collaborative… beyond just recruiting patients,” Rubio says. For CROs as well as diagnostic companies and labs, payment models and data flow channels could both use some serious tweaks, he adds. “There is a lot of opportunity in that space to treat patients as owners of their data and experts in their disease more explicitly, and to engage them more directly.”
Data Reanalysis
A better framework for the reanalysis of genetic data could go a long way toward improving the rare disease diagnostic rate—by as much as 32%, according to the calculation of Australian researchers at the Murdoch Children's Research Institute (MCRI) and the University of Melbourne. The study, recently published (DOI: 10.1007/s10689-020-00172-7) in Familial Cancer, found considerable variation in the ways that reanalysis of patient data gets initiated, says lead researcher Danya Vears, a social scientist at the University of Melbourne.
The reanalysis process is critical because it can reveal new genes associated with particular conditions and new variants in genes previously reported, she says. Previous studies have shown that despite the high diagnostic yield associated with genomic sequencing (up to 68%, depending on the genetic condition), a sizable proportion of patients still do not receive a genetic diagnosis at the time of the initial analysis.
Existing literature also suggests the process for re-contacting patients after new knowledge emerges is “haphazard,” Vears continues, so the researchers decided to talk to genetic health professionals directly about their experiences with initiating reanalysis of genomic sequence data. After 31 interviews, it became clear that opinions were mixed about the responsibilities of laboratories and clinicians, as well as patients' abilities to advocate for themselves.
Even within their own genetic service, health professionals reported that a diversity of models were being implemented, says Vears, as well as a “huge reliance on patients reinitiating contact with the clinical team.” A subset of interviewees thought the patient-initiated model worked fairly well, since some patients would return every year or two to learn if any new knowledge had accrued in the field since their last visit.
But quite a few healthcare professionals raised concerns about relying on patients, not all of whom are comfortable taking the lead or even know the meaning of a “variant of significance,” Vears says. Patients may also lack good access to healthcare, making exacerbation of existing health inequities an additional concern.
A few systems relied more heavily than the others on clinicians remembering and keeping track of who needed to be re-contacted and when, she says. Some geneticists reported using their clinical judgement about conditions more likely to have a genetic cause and flagging those patients sooner rather than later for reanalysis of their sequencing data. But, as a rule, they’re too busy to advocate for call-back protocols that would add to their workload.
“One model worth considering is more laboratory initiated,” says Vears, where labs have a biometrics platform in place as part of their analysis system that either routinely reanalyzes the data every year or two—at minimum on the “unsolved” patient cases. Such a model does not appear to have been reached the implementation stage.
Even this model has its challenges, since “not every patient may continue to want a diagnosis,” Vears adds, for example parents of children who have died from their genetic condition. Springing a diagnosis on patients not previously involved in the process might also be a disconcerting experience.
Despite the potential drawbacks, says Vears, the lab-initiated model is likely to be better than one relying on patients to reinitiate contact from the standpoint of “justice in access” to data reexamination.
Pros and Cons
Until there’s proof that a genetic variant is causative of a phenotype, the associations generally don’t get published in the literature. In the interim, laboratory scientists could opt to use the GeneMatcher database to see if variants they discover might also have been found by labs elsewhere, says Vears. That isn’t a routine practice and wouldn’t in any case normalize routine data reanalysis by laboratories.
Genomic sequencing started out in the research realm around cancer and rare diseases but is now much more integrated into clinical care, Vears notes. The problem is that the ordering specialists—including oncologists, nephrologists, and neurologists—don’t have genetics training. That means they often don’t understand the type of sequencing they’re requesting or the results they’re getting back. “They’re not really able to advocate for their patients in a way a clinical geneticist does.”
Embedding clinical genetics into clinical practice could solve the problem, and there are several potential models for this, Vears continues. One is to upskill the nongenetic specialist through educational services, as is happening in Australia thanks to the efforts of the Australian Genomics Health Alliance.
Genetic counselors are also important players in the field, in terms of educating nongenetic specialists and integrating them in specialty clinics to do some of the translational work, she adds. But in many places (including the U.S. and Australia), they aren’t allowed to order genetic lab tests—that still requires a medical license.
Overall, Australia as well as Europe has taken a “much more cautious approach” than the U.S. when it comes to sharing genomic test results outside the context of discreet clinical questions, Vears says. She wonders about the litigation risk of the tell-all approach when the reliability and meaning of information in patients’ genetic profile may well be unknown.
On the other hand, actively searching for variants unrelated to a genetic diagnosis has an upside. People might identify healthier ways to live their life, and drug developers might find they can enlarge the number and scope of diseases they can tackle with new treatments.
Expanding Pediatric Testing
Late-breaking research news in JAMA (DOI: 10.1001/jama.2020.7671) points to the game-changing potential of clinical genomics to speed the diagnosis of critically ill babies and children with suspected monogenic conditions. In the first 108 patients tested through the Australian Genomics Acute Care study, exome sequencing results were issued on average three days after sample receipt while the program was scaling up to 12 hospitals.
A diagnosis was achieved in 51% of participants and, for three-fourths of that group, it precipitated a change in management, according to Zornitza Stark, the study’s clinical lead who is a clinical geneticist with MCRI’s Victorian Clinical Genetics Services. The study provides a blueprint for a national rapid genomic diagnosis program in Australia, for which researchers have recently received funding through the federal government’s Genomics Health Futures Mission. The program will be expanded nationally beginning in July.
“This study is a huge step forward in improving the timely diagnosis of rare disease,” says Stark. “We have demonstrated it is possible to consistently deliver genomic results within the urgent timeframes required in intensive care to enable families and physicians to make real-time decisions based on genomic information.”
Formation of a collaborative multidisciplinary network—including clinical geneticists, genetic counselors, intensive care specialists, bioinformaticians, and laboratory scientists—was central to successful delivery of the program, Stark adds. Professionals worked collaboratively across multiple sites to change practices and share experiences.