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.

Advancing Autism Research By Sharing Genomic Data Online: The Simons Simplex Collection

THE NEXTCODE Exchange is hosting the Simons Simplex Collection (SSC), a global resource for research on autism spectrum disorders comprising genomic data from nearly 2,800 families.

THE NEXTCODE Exchange is hosting the Simons Simplex Collection (SSC), a global resource for research on autism spectrum disorders comprising genomic data from nearly 2,800 families.

Autism research is underway around the world to better understand the genetic basis for the disease, which is difficult to diagnose and has limited treatment options. With vast amounts of data being generated, the answers to this challenging disease may lie in the consolidation of this global data.

The newly launched NextCODE Exchange (read the release here) may be a critical solution in changing how autism is diagnosed and treated. The Exchange is hosting the Simons Simplex Collection (SSC), a global resource for research on autism spectrum disorders comprising genomic data from nearly 2,800 families.

With the Exchange, the SSC will be accessible to the world’s autism researchers to harmonize the growing body of relevant genomic data. By enabling the rapid analysis of massive amounts of sequencing data followed by instant collaboration and validation of findings, the availability of the SSC and other hosted data will accelerate the pace of discovery in this field.

This simple concept is likely to help usher in a new era of genomic medicine, offering global access to data that can answer questions to some of today’s most challenging diseases.

Learn more about the NextCODE Exchange and the Simons Simplex Collection here.

Maintaining Momentum Post-ASHG: Maximizing the Value of Large Genomic Databases

The newly launched NextCODE Exchange provides a browser-based hub for multi-center sharing and collaboration on collective data from massive whole-genome databases like the Haplotype Reference Consortium (HRC).

The newly launched NextCODE Exchange provides a browser-based hub for multi-center sharing and collaboration on collective data from massive whole-genome databases like the Haplotype Reference Consortium (HRC).

The American Society of Human Genetics (ASHG) meeting convened this week in San Diego, bringing together genetics experts from around the world to discuss programs with great potential to advance genomic-based medicine in the years to come.

To maintain the momentum generated this week, we need to find ways to integrate these important ideas, insights and programs, and to maximize the use of the massive databases that have been launched to support research on cancer, rare diseases and other pressing health topics.

One of the databases unveiled during the meeting was the Haplotype Reference Consortium, which aims to become the world’s most comprehensive database of genetic variations. Large databases like the HRC, along with several others already underway, can be tremendously helpful to researchers finding answers to some of the most challenging diseases. But there remains a significant bottleneck: these large, cumbersome databases cannot easily be shared and manipulated, limiting their utility for broad, multi-center genomic research.

The solution lies in the newly launched NextCODE Exchange (see release here). This browser-based hub allows for the sharing and harmonizing of massive whole-genome databases like the HRC to accelerate research. The integrated architecture allows users to visually confirm and validate findings in raw sequences, collaborating and sharing with others around the world who may have complementary research underway.

The momentum generated during ASHG will be multiplied by sharing and learning from the world’s collective genomic data on the NextCODE Exchange. Learn more here.

Imagine the Potential: The World’s First Online Hub for Global Genomic Data Access

The NextCODE Exchange, a new browser-based hub, allows for real-time sharing of whole genome collections in a simple, consistent format.

The NextCODE Exchange, a new browser-based hub, allows for real-time sharing of whole genome collections in a simple, consistent format.

The field of genomic medicine is rapidly advancing as the research community becomes more comfortable manipulating genomic data with the goal of discovering insights about disease causes and risks. Yet each database is hosted within separate organizations, organized in unique ways and vastly too cumbersome to easily share with others who may be working on similar research.

This weekend a new tool launched to enable just that. The NextCODE Exchange (see release here), a new browser-based hub, allows for real-time sharing of whole genome collections in a simple, consistent format.

The availability of this Exchange is a critical advance in extending the utility of genomic data by allowing organizations around the world to access and harmonize large complementary datasets, potentially multiplying their study data sets to gain more reliable insights than ever before.

Already, numerous organizations are participating in the NextCODE Exchange to add and share their genomic data, including clinicians and researchers affiliated with Boston Children’s Hospital, University College Dublin, Queensland Institute of Medical Research (Australia), and Saitama Medical University (Japan).

As new institutions look to the Exchange to share genomic data, this hub holds significant potential to help advance progress in genomic-based medicine.

Learn more about the NextCODE Exchange here.

Global Projects Move Genomic Medicine to the Next Level

nextcode-genomics-england-hannes-smarason

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.

Population-Scale Research Efforts Enabled by Progress in Sequencing

population-scale genomics

Significant insights gained from population-scale genomic studies, based on the knowledge of genetic variation and disease causation, will help to enable a new reality of personalized medicine and treatment.

The ability to sequence whole genomes quickly and economically is driving interest in population-scale sequencing efforts that can reveal meaningful insights on a much more systematic basis than previous approaches. A range of large initiatives announced recently are prime examples of the trend in population sequencing, including industry programs by Regeneron and Human Longevity, and the 100,000 Genomes Project by Genomics England. Perhaps better than any other effort since the founding of deCODE in Iceland, the establishment of a high-throughput Genomics Center at Sidra Medical and Research Center in Qatar embodies the movement toward these types of population studies. The eventual goal of the project is to sequence the entire Qatari population of some 300,000 people. But from the beginning, the Sidra facility will help advance genetic mapping projects, including the creation of Arab consensus genome to obtain a better understanding of genetic variants that influence health across Arab populations and, indeed, beyond. In addition to these efforts, the center will focus on uncovering the causes of rare genetic diseases. The significant insights that can be gained from population-scale studies, based on the knowledge of genetic variation and disease causation, will help to enable a new reality of personalized medicine and treatment. And this is where efficient, powerful and industrial-scale analysis will become critical. NextCODE’s analytics and interpretation systems have already been tested at such scale, as they are based on the world’s first and largest population genomics effort—that of deCODE. [see blog post] Our systems will be useful tools to efficiently deliver insights based on the vast amount of data that will be generated by these major population-based efforts to improve the state of global healthcare.

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.

Trends in Sequencing and Analysis Today Leading to Tomorrow’s Clinical Advances

The insights we’re gaining from sequencing and analysis techniques are delivering new advances in healthcare with ever greater speed and precision.

The challenge for programs seeking to accelerate their research discoveries with genomic data is how to analyze the wealth of information—to make it clinically relevant and rapidly deliver reliable insights to better inform patient care.

The insights we’re gaining from sequencing and analysis techniques are delivering new advances in healthcare with ever greater speed and precision. It’s a particularly exciting time to be a part of this evolving industry, with continual opportunities for new clinical applications of these technologies and platforms.

Companies like Illumina and others who are delivering next-generation sequencing technologies are gaining global exposure. New partnerships and programs are placing these advanced techniques into the hands of the world’s leading clinicians and researchers, who are then applying them to some of today’s greatest medical challenges.  Recently, plans to integrate sequencing technologies have been announced by world renowned organizations like the Baylor College of Medicine in the U.S., Genomics England, and Sidra Medical and Research Center in Qatar.

The challenge for these and other programs seeking to accelerate their research discoveries with genomic data is how to analyze this wealth of information – to make it clinically relevant and rapidly deliver reliable insights to better inform patient care.

NextCODE Health is working to advance this piece of the puzzle with its Genomically Ordered Relational (GOR) database and its clinical and discovery interfaces (the Clinical Sequence Analyzer​™ and Sequence Miner™).  Combining next-generation sequencing techniques with increasingly robust analysis tools, NextCODE Health is helping to accelerate global research progress today to deliver unprecedented advances in patient care in the years just ahead.

Genomics and Rare Diseases: Hope for Solving Unanswered Questions

genomics and rare diseases

Leading institutions around the world are leveraging the power of advanced sequencing technology to solve some of the greatest unanswered questions in medicine.

As we learn more about disease biology and uncover new insights thanks to the availability of genomic technologies, we are making meaningful progress in identifying means to address many rare diseases for which there is little medical hope today.

With these new genomic tools and insights, a wide range of opportunities has emerged to improve diagnosis and treatment of rare diseases. Over the past few years, DNA sequencing has begun to uncover the causes of rare diseases and, at the heart of each case solved is a patient and a family that has gained new understanding about their condition. With time, these success stories in diagnosis will lead to more successes in treatment.

Now more than ever, there is more hope that identifying the key mutations will lead to better understanding of the biology of disease and then to novel therapies. Better and faster technologies are being promoted by leaders in the field of genomics that are enabling much more rapid analysis and interpretation of a patient’s genome to find answers. The critical first step is to obtain sufficient data to analyze, compare it against a robust database of reference data, and gain an accurate understanding of potential mutations associated with these rare conditions.

As researchers focus on specific areas, new partnerships are extending access to data and accelerating progress with rare diseases around the world. Recently, genomic analysis collaborations were initiated by ACoRD at University College Dublin to implement NextCODE’s proprietary database and analytical tools to mine whole genome data for variants linked to autism spectrum disorders. [See blog post here]. Another genomic analysis program with ANZAC in Australia applies advanced sequencing analysis technology to better understand X-linked Charcot-Marie-Tooth Syndrome, a rare and progressively debilitating neurodegenerative disorder. [See blog post here] More collaborations are in the works and we’ll be talking about them as soon as we can.

We look forward to the results of these and other collaborations as leading institutions around the world make efforts to leverage the power of advanced sequencing technology to solve some of the greatest unanswered questions in medicine.

A Standard Database Architecture Will Build a Stronger Foundation for Genome Discoveries

big data genome sequencing hannes smarason

The general adoption of the Genomically-Ordered Relational database (GOR) as a data standard for storing genomic data may greatly accelerate the spread of sequencing and its effectiveness as a tool for advancing medicine.

It is widely accepted that the ability to share the analysis and insights from DNA sequencing will be a key driver of discovery and innovation. But one current limitation to extending this knowledge is that sequencing and analysis platforms, as well as samples, are often proprietary to and stored at different institutions. Perhaps more important, the structures and formats in which genomic data has customarily been stored—the relational databases developed by the likes of IBM and Oracle—make it unwieldy to analyze as the amount of data grows, and very difficult to share. The upshot is that institutions cannot easily share and consolidate information to generate more robust analyses and clinically relevant insights. This presents a serious hurdle to discovery both in rare disorders, where samples need to be gathered in order to generated adequate analytical power, and in complex ones, where truly massive studies can tease apart different facets of disease and reveal their causes.

Over the past decade, a novel and comprehensive database model has been developed to solve this bottleneck, offering a flexible and fast means to overcome these problems. It is called the Genomically-Ordered Relational database, or GOR, and was designed to manage and query the detailed genomic data amassed by deCODE genetics in Iceland – the world’s first and still by far largest and most comprehensive population-based genomic database.

The thinking behind the GOR is as simple as it is revolutionary. Genomic data is a sort of big data but one with an important difference: It is divided up in distinct packets—the chromosomes—and then arranged within each chromosome in linear fashion. The GOR makes use of this by storing and querying sequence data according to its unique position in the genome, rather than as huge files as long as the sequence. This radically reduces the data burden of querying even large numbers of whole genomes, at the same time making it possible to store and visualize instantly the raw sequence underlying an analysis.

In practice, the GOR thereby enables researchers to home in on specific variants without having first to call up entire patient genomes, and separates raw data from annotations to focus in on only the most relevant search components. It’s these types of functions and features that can be consistently applied across data storing systems to allow for more multi-institutional, collaborative research and consistency in outcomes worldwide.

Leaders in the genomic research community are now beginning to create coalitions and working groups to underpin and coordinate the adoption of standards for sharing genomic data. As these groups create flexible and efficient policy frameworks, the GOR is tested and ready to support the fundamental data requirements of global data sharing and the acceleration of discoveries in genome-based medicine. The general adoption of the GOR as a data standard for storing genomic data may greatly accelerate the spread of sequencing and its effectiveness as a tool for advancing medicine around the world.