Genomics Offers Game-Changing Solution to Rare Disease Diagnosis, Costs

Hannes Smarason Wuxi NextCODE

As genomics is used more and supported by ever-more robust analysis and interpretation, its potential to offer a solution to diagnosing rare diseases is truly game-changing.

I believe strongly and have previously blogged on the potential for genomics to shift the care paradigm for rare diseases, and here I’d like to detail in particular the huge potential value genomics can add to rare disease diagnosis. According to the National Institutes of Health (NIH), there are over 7,000 rare diseases affecting between 25 and 30 million Americans, which is nearly 1 in 10 people, making the overall prevalence of rare diseases significant. Rare diseases can be chronic, progressive, debilitating, disabling, severe, and life-threatening.

When a patient presents with a spectrum of unusual symptoms, a costly scramble naturally begins to diagnose the patient’s disease. Some people refer to this diagnosis process for rare diseases as a “diagnostic odyssey,” as patients and their families are subjected to test after test while being handed from one doctor to another, oftentimes to medical centers far from their home. Too often, this odyssey yields no concrete diagnosis or—worse—misdiagnosis. The direct medical costs can be significant, and the indirect costs—the frustration and disillusion felt by the patients and the family—can be extraordinary.

Since NIH believes that approximately 80 percent of rare diseases have genetic origins, the potential for genomic sequencing, interpretation, and analysis to offer a solution here is truly game-changing. A recent article in Bloomberg BusinessWeek highlighted medical histories of two patients who recently received a diagnosis informed by genomics. In both these examples, genomic analyses provided an end to the burden, cost, and stress of their multidecade-long diagnostic odyssey:

  • Jackie Smith, 35, spent the 32 years from age 3 unable to receive a correct diagnosis that could account for her weak limbs and turned-in ankles, despite seeing many doctors on numerous occasions. Indeed, Jackie’s parents were told to “take the 3-year-old girl home and enjoy her while they could”…”[her disease] would probably kill her before she was old enough to drive.”  This past February, using genomic interpretation and analyses from Wuxi NextCODE, Claritas Genomics definitively identified her condition as centronuclear myopathy in less than three weeks.
  • Dustin Bennett, 24, would tremble and violently jerk for hours or days at a time and had been developmentally delayed since childhood. After dozens of doctor visits and incorrect diagnoses—seizures, muscle disorders, mental health problems—a Mayo Clinic genomic-based analysis showed he has episodic ataxia type I, a neurological disease characterized by hours-long attacks with no clear trigger. Dustin, a 24-year-old who functions at a first-grade level, is now on the second round of a medication doctors say should help reduce the frequency and severity of his episodes.

As genomics is used more and supported by ever-more robust analysis and interpretation, I expect these types of clear successes to become even more commonplace. And the value to the healthcare system and the patient is clear, expressed powerfully in the Bloomberg BusinessWeek piece:

While there isn’t yet a cure, Smith is participating in research that may one day lead to treatments or more supportive care. “Just being connected feels good. I felt alone for a long time,” she says. “And I want to do it for the bigger picture, too. Not just for myself, but so I can be counted.”



A New Era, New Vision for WuXi and NextCODE Health


WuXi PharmaTech has acquired NextCODE Health to create WuXi NextCODE Genomics, a global leader in genomic medicine. Pairing WuXi’s technology and existing reach with NextCODE’s leading analytics and database promises to advance the pace of genomics research today.

In the fast-paced genomics community, we continually look for new opportunities and strategies to enhance the value of genomics and use the increasingly robust body of genomic data for the advancement of clinical medicine.

We’re excited to announce a new, ambitious vision to do just that, with WuXi’s acquisition of NextCODE Health. NextCODE will be merged with WuXi’s existing Genome Center in wholly-owned subsidiary called WuXi NextCODE Genomics, with unique, comprehensive and global capabilities for using genomic data to deliver better medicine and improve healthcare.

WuXi, a Shanghai-based genomic laboratory service partner for companies in the pharma and biotech community, has already been collaborating with NextCODE to provide analysis services to customers of the WuXi Genome Center. Now, with the in-house capability to analyze, store, and manage the vast amount of genomic data, NextCODE’s industry-leading genome sequence analysis platform will expand WuXi’s core next-generation sequencing benefits and services.

Pairing WuXi’s technology and existing reach with NextCODE’s leading analytics and database promises to advance the pace of genomics research today. More importantly, however, this new era for NextCODE brings exciting opportunities to maximize the most advanced tools available today and contribute to major advances in genomic medicine.

Genetics-Based Advances in Rare Diseases: Ideas into Action

NextCODE Health-Claritas Genomics

Claritas Genomics and NextCODE have established a collaboration to support rare disease clinical care.  Combining robust sequencing with integrated diagnostic capabilities, the partnership aims to accelerate and augment the services provided to leading pediatric care organizations.

Today we have a tremendous opportunity to use the data being generated from genome sequencing to address the mysteries of rare genetic diseases affecting children. Though these diseases individually are rare, according to Global Genes, an estimated 7,000 different types of rare diseases affect more than 30 million people in the U.S., roughly half of whom are children.

To conduct diagnostic testing for pediatric genetic disorders, leading children’s hospitals are collaborating with specialized laboratories, including Claritas Genomics, a recognized leader in specialized pediatric genetic testing affiliated with Boston Children’s Hospital, part of the Harvard Medical School system.

The real opportunity lies in the analysis of raw genomic sequence data to identify patterns or markers of a rare disease. While it has been theoretically possible to use genomic sequencing to diagnose most rare diseases, a major hurdle has been in integrating dynamic informatics tools that can quickly interpret the data into accurate diagnostic insights and, ultimately, treatment options.

This is why Claritas Genomics and NextCODE have today established a collaboration, enhancing their collective capabilities to support rare disease clinical care. Combining robust sequencing with integrated diagnostic capabilities, the partnership will aim to accelerate and augment the services provided to leading pediatric care organizations.  Claritas has established a wide range of tests for genes known to be associated with pediatric disorders, which NextCODE is integrating into its clinical interface, resulting in accurate, reliable clinical reports. Learn more about NextCODE’s pioneering activities here.

Enabling this rapid, integrated approach to genomics-based care for rare diseases holds great promise for the community and for the many families who are anxiously seeking answers to these mysterious diseases.

Global Projects Move Genomic Medicine to the Next Level


NextCODE takes top marks in Genomics England analysis and interpretation “bake-off:” NextCODE’s proven population-scale platform delivered the best results in rare disease and cancer clinical interpretation, as well as secondary analysis and variant refinement.

New genomics-based technologies and tools are making their way into a range of exciting research programs and clinical studies around the world. Leading-edge organizations are quickly adopting hardware for sequencing and systems for collecting genomic data. Now, the focus has turned to analysis and interpretation – the critical component necessary to gain the insights from the sequence data that will transform medicine.

Earlier this year, Genomics England announced investments for broad sequencing and analysis of 100,000 human genomes. At the time, Genomics England had selected Illumina as its sequencing partner and was coordinating resources and centers to support the effort, including resourcing for analysis and interpretation. [See blog post here]. Other initiatives, such as the Qatar genomics program and the initiatives by Longevity and Regeneron also represent the accelerated progress in seeking medical advancements from genomic data insights. [See blog post here.]

This week, Genomics England announced a select group of companies with advanced capabilities to move to the next stage of evaluation to provide clinical interpretation for the 100K Genomes Project. At the tip top was NextCODE, which received top marks by Genomics England for its analytical capabilities across all the categories evaluated: rare disease interpretation, secondary pipeline analysis and cancer interpretation. [See press release here.] The company’s advanced Genomically-Ordered Relational database, or GOR, combined with its clinical and discovery interfaces offer the most advanced and reliable capabilities to support the ambitious tasks undertaken by Genomics England, and are already proven at population scale. [Read more on the GOR database here.]

The coming months will be a very exciting time for genomic medicine, with interpretation taking the spotlight as we take leaps toward the next stage of personalized medicine.

Genome Data Interpretation: How to Ease the Bottleneck

Bloomberg NextCODE Hannes Smarason

Bloomberg BNA Business’ “Diagnostic Testing & Emerging Technologies,” highlights how NextCODE is providing a qualitatively different way to store and analyze genomic information to meet growing opportunities in personalized medicine.

With advances in sequencing technology and reduced costs, more and more data are generated every day on the genetic basis of disease. The challenge has become how to derive meaningful information from these mountains of data.

While various systems have been established in recent years to store the large amounts of genomic data from patients’ DNA, a remaining obstacle is to “break the bottleneck” so that researchers can process the vast data in multiple human genomes in order to identify and isolate a small, useful piece of information about disease. Conventional databases and algorithms have not been able to efficiently and reliably identify subset information among the millions of genetic markers in order to inform clinical decisions. This has become a major data management roadblock.

The key is to find new approaches for databases and algorithms that accommodate the unique ways that genomic information is analyzed and interpreted. As discussed in Bloomberg BNA, Diagnostic Testing & Emerging Technologies, NextCODE is already easing this bottleneck by providing a qualitatively different way to store and analyze genomic information and apply it to meet the growing opportunities for personalized medicine.

NextCODE’s Genomically Ordered Relational (or GOR) database infrastructure is a truly different way of storing this huge amount of data. The principle is very simple: rather than store sequence and reference data in vast unwieldy files, it ties data directly to its specific genomic position. As a result, the algorithms are vastly more efficient compared to a traditional relational database because they can isolate by location in the genome. That makes analysis faster, more powerful, and radically more efficient, both in terms of clinicians’ and researchers’ time, as well as computer infrastructure, I/O, and CPU usage.

This holistic approach applies broadly to the priorities of genome scientists around the world, helping them eliminate the data management bottleneck to identify more culprits to many inherited diseases, more quickly and cost effectively.

Read more about NextCODE’s work here.

Four Factors for Improving Genomic Data for Personalized Medicine

advancing the use of genomic data for personalized medicine

The pace of progress has been astounding with advances in the use of genomic information to provide faster, more accurate, and more in-depth information to enable personalized patient care.

We’ve come a long way in improving the way that a patient’s genome sequence data is analyzed and interpreted to realize the full potential of personalized medicine. Here are four factors helping to overcome barriers and achieve new milestones for using genomic data to provide faster, more accurate, and more in-depth information to guide clinicians in delivering personalized care for patients.

Factor #1: Fast database query of the genome

Problem: Relational database architectures make it possible to store large quantities of sequencing data, but querying whole genome data can be time-consuming and take days to weeks.

Solution: The GOR (Genomic Ordered Relations) database is able to query whole-genome sequences in real time. The reason is that GOR understands the genome in terms of chromosomes, its natural structure, rather than as a continuous string of sequence. That’s both intuitive and innovative. When searching for a variant, tools in the GOR architecture don’t have to scan each individual’s entire sequence; they retrieve the variant straight from its location. Annotation data – information on what diseases or conditions variants have been linked to – are also stored in the same way. The GOR database was pioneered a decade ago by deCODE genetics, one of the first organizations to manage truly large genetic datasets, and is now being used by NextCODE for clinical applications of genomic data.

Factor #2: Fast, reliable identification of disease-causing variants

Problem: Many sequencing analysis pipelines are only powered to process data in a compressed format called Variant Call Format (VCF) files. These comprise only a tiny fraction of the genome, and being working only with VCF files makes it difficult to correct common alignment and allele-calling errors. That can result in both false positive and negative results, or to missing the key causative variants altogether.

Solution: The foundation for improved sensitivity and specificity is the ability to use VCF data on top of the raw sequence data from which it was derived. NextCODE’s pipeline and clinical interfaces, powered by GOR, give users the ability to go back to and visualize raw sequence data at a click. This approach enables genomic analysis and interpretation by seeking out disease-causing genetic variants, either in specific patients, or for research studies in a clinical setting.

Factor #3: Patient genomic information at the fingertips of the clinician

Problem: Many of today’s genomic interpretation tools are too complex and difficult to use by clinicians who may have minimal experience with genetic informatics tools.

Solution: All of the complex informatics required by a clinical analysis tool should disappear at the fingertips of a clinician. It starts by having a robust foundation to the informatics platform, and using the GOR database architecture enables rapid cycling between personal sequence data and broad clinical knowledge. The result is the Clinical Sequence Analyzer (CSA) in which clinicians can simply type in a patient’s symptoms, and CSA will search the patient’s whole genome for variants that may be relevant.

Factor #4: Applying the full power of whole-genome sequencing to cancer tumor analysis

Problem: Many of today’s approaches to the analysis of cancer genomes only look at the immediate next step for a course of treatment, an important capability but only part of a holistic view of a the genetic profile of a patient’s cancer and what can be done to fight it.

Solution: The Tumor Mutation Analyzer makes a more holistic approach possible, analyzing a whole exome or whole genome sequence from a patient’s own genome and from tumor cells. Comparing the two it is possible to isolate the variants likely to be cancer drivers. The distinguishing feature of TMA is the depth of the data it stores and the unprecedented level of detail it provides to more accurately identify variations. This level of detail is especially important in cancer genetics, where the chances of finding previously unknown variants are very high, and even if a mutation is successfully targeted with a course of treatment, another potential driver is often waiting in the wings.

The pace of progress has been astounding with advances in the use of genomic information for patient care. How will the path continue in the future? Stay tuned.