• Genetics
  • Can Africa now afford genome data?

    Two healthcare goals are personalised and more effective interventions. Advances in human genome sequencing offer considerable scope to achieve both. Affordability is a big challenge for Africa’s health systems. Over the early year of this century, unit costs’ve tumbled.

    The USA’s National Human Genome Research Institute (NHGRI) has tracked unit costs from 2001. The unit cost drop of sequencing centres funded by the Institute is enormous. NHGRI uses two measures.

    Cost per raw megabase DNA sequence is the cost of determining one megabase, so a million bases, of DNA sequence of a specified quality has dropped from US$10,000 in 2001 to less than US$0.1 in 2015. NHGRI’s graph shows the precipitous drop from trend around 2008.

    Cost per genome follows a similar trajectory. Sequencing a human-sized genome cost US$100m in 2001. In 2015, it cost about US$1,000.

    NHGRI compares the unit costs with a Moore’s Law curve. Moore's Law says a long-term computer hardware trend’s doubling compute power every two years. Matching it’s a sign of good performance. Exceeding it shows very good performance. Exceeding it on the scale of the NHGRI’s unit costs’s astonishing.

    The unit costs are for production activities that provide large volumes of quality DNA sequence data for public databases. They excluded costs of NHGRI’s Large-Scale Genome Sequencing Program, classified as a non-production activity.

    Even with the cost drop, which could continue, affordability’s always demanding for Africa’s health systems. Put alongside Africa’s health and healthcare challenges, theres a case for planning sustained investment in the skills and eHealth capacity for using genome data. It’ll have to take its place alongside other initiatives such as mHealth, predictive analytics and Big Data, but its opportunities are growing.

  • Capacity for more genome data's needed

    A team for universities and institutes in Seattle and Cambridge Massachusetts has tracked the family trees of individual cells in zebrafish. As more genome data becomes available for personalised care, eHealth will have to expand its capacity to hold and use the data. The findings are in Science

    It was already known that multicellular systems develop from single cells through specific lineages, but tracing methods scale poorly to entire, complex organisms. To improve on this, the team used genome editing for progressive and cumulative diverse mutations in a DNA barcode. They repeated it over numerous rounds of cell division.

    The barcode’s an array of Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/Cas9 target sites. It marks cells and enables elucidation of lineage relationships using mutation patterns mutations shared between cells. In cell culture and zebrafish, the team showed rates and patterns of editing as tunable, and that thousands of lineage-informative barcode alleles, gene variants, can be generated.

    Samples of hundreds of thousands of cells from individual zebrafish identified most cells in adult organs deriving from relatively few embryonic progenitors. Future genome editing of synthetic target arrays for lineage tracing using GESTALT can generate large-scale maps of cell lineage in multicellular systems for normal development and diseases.

    This type of genome data and knowledge seems set to keep expanding. Using it routinely for mainstream healthcare will need expanded eHealth capacity. It’s another investment stream for Africa’s health systems to consider for their eHealth strategies. They’re becoming more challenging.

  • Will genomes take off in a big way?

    As the genome project moves on, the complexity of the relationship between genes and diseases has become increasingly apparent. An article in The Economist says now, the genome era arrives, probably for real. Initial naivity about the links have been replaced by enhanced knowledge, including the range of genes that contribute to serious illnesses, expanded computer power and more sophisticated sequencing. An eHNA report on genome editing shows how can become more widely available.

    The need for huge volumes of data, especially clinical is vital, so appropriate, considerable investment in clinical ehealth systems’s essential to feed the large, sophisticated databases needed. One benefit from this is better drugs. The report says that almost one third of drugs in clinical development are linked either to known DNA variants or variants in the structures of specific proteins that can be traced to DNA. If these variants are present in or absent from patients, it informs drug developers are likely to be effective in individual patients. This’s seen as a new era of using genomes in medicine. 

    What should Africa’ eHealth do to keep up with genomes trajectory? A first step could be to follow the USA’s and UK’s lead. Supporting leading doctors by providing them with the eHealth tools they need, such as sustainable database tools and Clinical Decision Support (CDS) may be a start. This represents a new strategic direction to be added to each countries eHealth strategies.

  • Genome editing's more available and better

    In 1953, James Watson and Francis Crick discovered the double helix, the twisted-ladder structure of Deoxyribonucleic Acid (DNA). It opened the way for personalised healthcare and more effective medicine. DNA carries the genetic information in cells and some viruses and comprises two long chains of nucleotides twisted into a double helix and joined by hydrogen bonds.

    An organism’s complete set of DNA and its genes is a genome. Each genome contains all the information needed to build and maintain an organism. In humans, a copy of the entire genome has more than three billion DNA base pair contained in all cells that have a nucleus. Since 1953, the genome has many more opportunities for better medicine, and they’re expanding.

    W Daniel Hillis, a USA inventor, was right when he said “Your genome knows much more about your medical history than you do.” Editas Medicine aims to make sure that genomes have their say.

    Katrine Bosley, CEO at Editas, presented Editas’ achievements at the Royal Society of Medicine’s 12th Innovation Summit in April. It’s a transformative genome editing company translating a set of technologies into innovative human therapeutics so precise and corrective molecular modifications can be used to treat disease at genetic levels.

    The technologies are

    • Clustered, Regularly Interspaced Short Palindromic Repeats (CRISPR)
    • CRISPR-associated protein 9 (Cas9)
    • Transcription Activator-Like Effector Nucleases (TALENs).

    The first two combine into CRISPR/Cas9. Research into the techniques, together with TALENs has led to genome editing as one of the most exciting new areas of scientific research. Recent advances have enabled modifications to be achieved to almost any gene in the human body, so directly turn on, off or edit genes that cause diseases. Editas’ founders have published much of the research that’s elevated genome editing technology to a position where it can be used and developed for therapeutic use. 

    Three examples of research are in Development and Applications of CRISPR-Cas9 for Genome Engineering in 2014, and human T cells and Staphylococcus aureus, both in 2015.

    T cells are one of two primary types of lymphocytes, a small white blood cell, a leucocyte, with a single round nucleus, that’s found especially in lymphatic systems. They originate in bone marrow and mature in the thymus and determine the specificity of immune response to foreign substances, antigens, in people’s bodies. B cells are the other type. 

    There are over 30 types of the Staphylococcus bacteria, referred to as Staph. The aureus variety’s blamed for causing most Staph infections. It’s the bacteria in Methicillin Resistant Staphylococcus Aureus (MRSA) infection that's resistant to many antibiotics used to treat ordinary staph infections.

    Two core themes from Katrine’s presentation are: 

    • Using genome editing results in better clinical outcomes
    • Genome editing’s become cheaper, so more available.

    The Bill and Melinda Gates Foundation and Google Ventures support Editas. In February, it was the first publicly traded company specialising in genome editing. A change in emphasis from grants to revenue streams may follow on soon. Maybe Africa’s health systems can step up their genome editing strategies soon.

  • GENOMES and GENIE offer more hope for cancer patients

    Research into health matters is increasingly a global endeavour. Its scale and value’s illustrated by the American Association for Cancer Research (AACR) launch of AACR Project Genomics, Evidence, Neoplasia, Information, Exchange (GENIE). It’s an international collaborative and initiative that aims to now power clinical decision making and advance clinical and translational research. The project will aggregate participants’ clinical-grade sequencing data to improve patient treatment decisions and be a catalyst for clinical and translational research. 

    Phase one’s being conducted in partnership with seven global leaders in genomic sequencing for clinical utility and two informatics partners. The seven founding members of the consortium and phase 1 are:

    • The Center for Personalized Cancer Treatment, Utrecht, Netherlands
    • Dana-Farber Cancer Institute, Boston
    • Institut Gustave Roussy, Villejuif, France
    • Johns Hopkins University's Sidney Kimmel Comprehensive Cancer Center, Baltimore
    • Memorial Sloan Kettering Cancer Center, New York
    • Princess Margaret Cancer Centre, Toronto
    • Vanderbilt-Ingram Cancer Center, Nashville, Tennessee. 

    The two informatics partners are:

    • Sage Bionetworks, Seattle
    • cBioPortal, New York.

    Charles L. Sawyers, MD, AACR is the chair of the Project GENIE Steering Committee. He says that despite an increase in the amount of genomic data available for analysis, “These data are typically insufficient in number or lack the necessary clinical outcomes data to be clinically meaningful. Thus, to effectively benefit patients, the genomic and clinical outcomes data from as many institutions as is practical should be combined through a data-sharing initiative, such as AACR Project GENIE.”

    GENIE will achieve its goals by pooling Clinical Laboratory Improvement Amendments (CLIA) and International Organization for Standardization (ISO)-certified sequencing data from the members’ institutions into a single registry and linking these data with selected longitudinal clinical outcomes. All project data will be made open-access following defined periods of project exclusivity, and the initial genomic data set will be publicly available on Nov. 6, 2016.

    There are already over 17,000 genomic records in GENIE’s registry, which is unique in that it’s enriched in late-stage cancers and contains only clinical-grade sequencing data used for clinical decisions. The number of genomic records in GENIE’s registry will continue to grow as new patients are seen at each institution are added. Each of the seven members can keep working how it sees fit, while simultaneously contributing its data to the project. This will ensure that future participants can easily be added after the pilot phase project is completed.

    The GENIE registry is a tool that can be used to solve many clinical and research challenges. There are numerous ways that it can benefit patients. They include:

    • Validating gene signatures of drug response or prognosis
    • Identifying new patient populations for previously US. Food and Drug Administration (FDA)-approved drugs
    • Expanding patient populations that benefit from existing drugs
    • Identifying new drug targets and biomarkers.

    It’s a project that Africa’s health systems should follow closely. They should also invest in the eHealth that enables them to participate and thrive from the benefits GENIE offers to patients and communities.

  • e-Driver algorithm can detect protein changes in genes

    DNA carries genetic information. It’s the chemical instructions that tell our cells what to do. When DNA’s damaged and cells mutate, it can cause cancer. Exploring and learning more about the relationships between genes and cancers are high-priority research activities. Many people want to know more about the genetic risks they’re facing. In 2005, Eduard Porta-Pardo and Adam Godzik from Sanford-Burnham Medical Research Institute, California, described their e-Driver algorithm in e-Driver: A novel method to identify protein regions driving cancer. It can analyse the effect of proteins on different parts of a gene they affect. It added to the approach that focuses on a gene as an entire entity.

    Porta-Pardo and Godzik are part of the team that used e-Driver to produce A Pan-Cancer Catalogue of Cancer Driver Protein Interaction Interfaces. It’s published by PLOS Computational Biology. It starts from the position that some ten years after their e-Driver paper, the role of mutations on Protein-Protein Interaction (PPI) interfaces as cancer drivers hasn’t been studied systematically. 

    The team included Luz Garcia-Alonso from the European Bioinformatics Institute in Cambridge, UK and Thomas Hrabe, Joaquin Dopazo from Computational Genomics Department, Centro de Investigación Príncipe Felipe (CIPF) in Valenica, Spain. They used e-Driver to analyse the mutation patterns of the PPI interfaces from 10,028 proteins in a pan-cancer cohort of 5,989 tumours from 23 projects of The Cancer Genome Atlas (TCGA) to find interfaces enriched in missense mutations which can inhibit a protein’s function. The result was 103 PPI interfaces enriched in somatic cancer mutations, with 32 of them found in proteins coded by known cancer driver genes. The other 71 interfaces are found in proteins that weren’t identified as cancer drivers even though in most cases there’s extensive literature, suggesting they play an important role in cancer. 

    The study shows that algorithms and the considerable skills and knowledge to develop and use them can have an enormous impact in advancing healthcare’s knowledge research. Africa’s health systems should find a place for these activities as part their eHealth strategies. While it may only be a small part to begin with, it’ll increase in scale and importance.

  • Cloud, data, research partnership with Google to tackle Autism

    As EHRs and Big Data expand, they enhance the potential to provide data for research. A USA initiative between Google and Autism Speaks, a major autism research foundation, says a report by the Wall Street Journal. The project will store Google, Autism Speaks’ data on the sequencing of 10,000 complete genomes and other clinical data of children with autism and their siblings and parents. Researchers working on autism hope to accelerate their research.

    DNA databases need massive computing, storage and tools capacity that exceeds many universities’ and research hospitals’ facilities. Placing it with Google overcomes these limitation as part of AUT10K, the Autism Speaks genome-mapping programme. The plan is to provide researchers with a portal by June 2015. Access to raw data may be available earlier.

    There’s a considerable workload to structure the data for users. This accounts for the development time. There are also concerns over privacy and security: a common issue for new eHealth ventures. These need fixing before they become a problem.

    If the initiative succeeds, it provides a model for healthcare and health charities in African countries to work with their national and regional research bodies to pursue similar goals.

  • Whatever next for health technology?

    If it looks as though technology is racing ahead and there seems no end to it, there is nothing to worry about; it is. A report in MedCityNews sets out some of the changes that may follow on from eHealth and health technology topics like electronic medical records, DNA sequencing and big data that people are already grappling with. It sets out a few emerging features of technology trends in medicine and healthcare. They include:

    • Artificial intelligence and algorithm medicine
    • Internet of things
    • Micro-electro mechanical systems (MEMS)
    • Wearable medical devices
    • Natural language processing
    • Medical tricorder
    • Workflow automation.

    The article contains numerous hyperlinks to various sites that describe and explain these initiatives. For eHealth policy-makers, planners and decision-takers, it provides a neat look beyond the horizon and the range of choices for the way ahead. But, Zora Neale Hurston, the USA anthropologist said, “No matter how far a person can go the horizon is still way beyond you.” There is still more to come.