Category Archives: Genome

The University of Vermont Health Network, along with partners Invitae and LunaPBC, launched a pilot project on November 1, to offer the Genomic DNA Test as part of its clinical care. The test will provide information for 147 genes that are indicators of increased risk for certain diseases including hereditary cancers, cardiovascular conditions, and other medically important disorders for which clinical treatment guidelines are established. The test also screens for carrier status for other diseases.

Our overall health and longevity are determined about 30% by genetics, said Debra Leonard, M.D, Ph.D., chair, Pathology and Laboratory Medicine at UVM Health in a press release. But until now, most of our clinical health care decisions have been made without understanding the differences in each individuals DNA that could help guide those decisions.

The Genomic DNA Test will be offered over the next year to 1,000 patients who are over 18 years old, are treated by a UVM Health Network Family Medicine provider, are not pregnant, or the partner of someone who is currently pregnant, and are part of the OneCare Vermont Accountable Care Organization (ACO). The testing will be conducted by Invitae on healthy individuals who opt in to the pilot and will be provided with information about their potential risk of developing diseases like cancer or heart disease based on their genetic make-up, with the potential to adjust their healthcare and lifestyle to help mitigate some of these risks.

Nearly one-in-six healthy individuals exhibit a genetic variant for which instituting or altering medical management is warranted, said Robert Nussbaum, M.D., Invitaes chief medical officer in a prepared statement. Genetic screening like the Genomic DNA Test in a population health setting can help identify these risk factors so clinicians can better align disease management and prevention strategies for each patient.

The test and any pre- and post-test genetic counseling services will be provided to pilot project participants at no charge and results will become a part of each patients medical record and available to the patient and all of his or her healthcare providers.

In addition to providing patient-specific information that can help determine health and wellness decisions, patient genomic data can also be used in for broader research applications that are helping to unravel the genetic basis for a number of diseases.

Patients who are interested in making their data available for research purposes can share their data through LunaDNA, the sharing platform of pilot project partner LunaPBC. Patients who choose to share their data with researchers will become shareholders in LunaPBC, a public benefit corporation owned by the individuals who provide their genomic data to the company. Data provided by LunaDNA to researchers I de-identified to protect the privacy of its member-owners. In the future the patients will also be able to shareand receive additional LunaPBC share forlifestyle, nutrition and environmental data.

Vermonters who choose to share their genomic data for research will play a leading role in the advancement of precision medicine, said Dawn Barry, LunaPBC president and co-founder. This effort puts patients first to create a virtuous cycle for research that doesnt sacrifice patients control or privacy.We are proud to bring our values as a public benefit corporation and community-owned platform to this partnership.

According to UVM Health, the pilot program, run through the ACO is a step toward moving to a value-based healthcare system.

Vermont and other states are moving away from fee-for-service health care and toward a system that emphasizes prevention, keeping people healthy, and treating illness at its earliest stages, Leonard said. Integrating genetic risks into clinical care will help patients and providers in their decision-making.

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UVM Health Taps LunaPBC, Invitae on Genomic Testing Pilot Project - Clinical OMICs News

By Michael Le Page

Beverley Thain / EyeEm/Getty Images

A project to sequence the genomes of 60,000 species of animals, plants, fungi and complex cells such as amoeba found in the British Isles is about to get under way. The Darwin Tree of Life project has raised the 9 million needed to collect and barcode the first 8000 species, and to sequence 2000 of them.

Barcoding involves finding distinctive DNA features so species can be identified by simple, quick tests. The Wellcome charity, which aims to improve health, is providing the funding because it thinks the work could have many benefits for people as well as wildlife, from finding new treatments for diseases to helping to feed a growing population.

To start with, the project aims to sequence one organism from each of the 4000 families of plants, animals, fungi and protists complex single cells in the British Isles, says Mark Blaxter, who is leading the Tree of Life programme at the UKs Wellcome Sanger. Species will also be chosen on the basis of how important, interesting and iconic they are, he says.

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Read more: Biologys moonshot: The mission to decode the DNA of all life

The first set will include badgers, red squirrels, all 59 British butterflies, 40 moths and a set of beach animals and seaweeds used in climate studies.

The project is part of a larger international push to sequence the genomes of the 1.5 million species of complex life on the planet, the Earth BioGenome project, formally launched last year. The organisers say it can be done for around $5 billion or around $3000 per species. Critics say simply getting samples of rare species could cost this much.

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The grand plan to sequence the genomes of 66,000 UK and Irish species - New Scientist News

Foodborne illnesses are not only an unpleasant personal experience for millions of Americans each year, theyre a logistical concern for businesses, with the potential to drive and keep people (and their dollars) away for good. As our food supply becomes increasingly global, the ability to accurately and quickly identify the source of any pathogen causing a foodborne illness has become exponentially more difficult. To ensure the safety of what we eat, the Food and Drug Administration (FDA) plans to build upon its early success with digital technology and whole-genome sequencing for its New Era of Smarter Food Safety.

Whole-genome sequencing

At its simplest, a genome is the information a cell needs to create an organism. Since an organisms genome is as unique as a fingerprint, sequencing that genome is the first step in being able to quickly identify just what is making a person sick. Scientists generate the sequence by gathering samples of a particular food in a sterile environment, mashing it up, and conducting the genome analysis. The result is the fingerprint for that specific entity.

The problem is, having this information on hand at the local level is useful only under very limited circumstances. For instance, it would be enough if a group of people became ill after eating a single meal with food sourced locally, in a single sitting at a single event. With a few calls, it might be possible to identify the food causing the illness and take steps to keep it from being shipped to new locations.

More common is the case in which a number of people with nothing in common at first become ill within days of one another. Making a match between the pathogen causing the illness and the pathogen in each food involved is still fairly straightforward if everything is sourced locally. But what if some of the food comes from sources across the globe? How are the fingerprints for those foods going to be of use in stopping the spread of the illness to additional locations when there is no way to readily communicate with other localities?

GenomeTrakr

So, to bring whole-genome information into play on a global scale, the FDA created a United States-based open-source distributed network of labs in 2013. The result is GenomeTrakr the stuff of foodie-sci-fi. It makes whole-genome sequences from foods around the world available globally. Any health agency, anywhere on the network, can upload data from a pathogen causing illness in their locality and receive information about entities that match or closely approximate that sequence. In effect, the power of the digital fingerprinting and related DNA sampling now in use in law enforcement can be put to work for foodborne illness outbreaks by either making a match or reporting that the match is likely to be found within a certain cluster of related genome sequences. This game-changing use of whole-genome sequencing has already helped to halt the spread of global foodborne pathogens several times.

A digital framework

But global genome sequencing is still not all that is needed to safeguard the food supply and your health. Being able to readily access a whole-genome sequence can tell you which food is the culprit, but how do you know where the food originated, what path it took from field to plate, and where any additional product is currently located on its journey from field to plate?

The FDAs remedy to this part of the challenge is to digitize the records kept at each step of a foods journey through the global system. Rather than filling out a paper form that remains local or creating a paper-based dossier that travels with a food shipment, each step along the way will be documented in a globally accessible, digital format. The result will be a system that complements the GenomeTrakr by making it possible to trace the source of a foodborne pathogen to its point of origin in minutes rather than weeks or months.

Why does it matter? It matters because ready access to the genome, the origin, and the trail it traveled will make it possible to stop the flow of this food through the system: It will keep additional people from becoming ill.

A blueprint

As the first step in the FDAs Strategic Blueprint for this New Era of Smarter Food Safety, agencies and companies from all parts of the food sector met in October to discuss the logistics of the new approach and offer input. Considerations ranging from ownership of the data to concerns about data transfer were among the many raised. These issues are not not only vital to the integrity of the data in the system, but will also result in a system we can count on when we sit down to eat.

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When it Comes to Identifying the Source of Foodborne Illness, The Future is Now - The Spoon

Anxious couples are approaching fertility doctors in the US with requests for a hotly debated new genetic test being called 23andMe, but on embryos.

The baby-picking test is being offered by a New Jersey startup company, Genomic Prediction, whose plans we first reported on two years ago.

The company says it can use DNA measurements to predict which embryos from an IVF procedure are least likely to end up with any of 11 different common diseases. In the next few weeks it's set to release case studies on its first clients.

Handed report cards on a batch of frozen embryos, parents can use the test results to try to choose the healthiest ones. The grades include risk estimates for diabetes, heart attacks, and five types of cancer.

According to flyers distributed by the company, it will also warn clients about any embryo predicted to become a person who is among the shortest 2% of the population, or who is in the lowest 2% in intelligence.

The test is straight out of the science fiction film Gattaca, a movie thats one of the inspirations of the startups CEO, Laurent Tellier. The companys other cofounders are testing expert Nathan Treff and Stephen Hsu, a Michigan State University administrator and media pundit.

So far, fertility centers have not leaped at the chance to offer the test, which is new and unproven. Instead, prospective parents are learning about the designer baby reports through word of mouth or news articles and taking the companys flyer to their doctors.

One such couple recently turned up at New York Universitys fertility center in Manhattan, says David Keefe, who is chairman of obstetrics and gynecology there. Right off the bat it raises all kind of questions about eugenics, he says.

Keefe, who has seven children, worries that couples who think they can choose kids from a menu could be disappointed. Its fraught with parenting issues, he says. So many couples just need to feel they have done enough.

Picking your baby

The companys project remains at a preliminary stage. While some embryos have been tested by the company, Tellier, the CEO, says he is unsure if any have yet been used to initiate a pregnancy.

The test is carried out on a few cells plucked from a days-old IVF embryo. Then Genomic Prediction measures its DNA at several hundred thousand genetic positions, from which it says it can create a statistical estimate, called a polygenic score, of the chance of disease later in life.

Genomic prediction

In October, the company pitched the test, which it calls LifeView, from a trade-show booth at the annual meeting of fertility doctors in Philadelphia. A promotional banner read: She has your partners ears and smile. Just not their risk of diabetes.

Criticism of the company from some genetics researchers has been intense.

It is irresponsible to suggest that the science is at the point where we could reliably predict which embryo to select to minimize the risk of disease. The science simply isnt there yet, says Graham Coop, a geneticist at the University of California, Davis, and a frequent critic of the company on Twitter.

The company has raised several million dollars in venture capital from investors including People Fund, Arab Angel, Passport Capital, and Sam Altman, the chairman of Y Combinator and CEO of OpenAI.

At an investor event last April, Genomic Prediction compared itself to 23andMe for IVF clinics and boasted it was preparing for a massive marketing push.

Our reporting suggests the company has struggled both to validate its predictions and to interest fertility centers in them. Its customers so far seem to be a scattering of individuals from around the world with specific family health worries. The company declined to name them, citing confidentiality.

The company is expected to soon present its first case reports, describing clients and their embryo test results. One case involves a married gay couple who have begun IVF using donor eggs and plan to employ a surrogate mother. That couple wants a child with a low risk for breast cancer.

How will it be used?

Genomic Prediction thinks it can piggyback on the most common type of preimplantation embryo test, which screens days-old embryos for major chromosome abnormalities, called aneuploidies. Such testing has become widespread in fertility centers for older mothers and is already employed in nearly a third of IVF attempts in the US. The new predictions could be added to it.

Fertility centers can also order tests for specific genetic diseases, such as cystic fibrosis, where a gene measurement will give a definite diagnosis of what embryo inherited the problem The new polygenic tests are more like forecasts, estimating risk for common diseases on the basis of variations in hundreds or thousands of genes, each with a small effect.

In a legal disclaimer, the company says it cant guarantee anything about the resulting child and that the assessment is NOT a diagnostic test.

Santiago Munne, an embryo testing expert and entrepreneur, thinks patients already undergoing aneuploidy testing would likely want the add-on test, but that doctors could object if it introduces uncertainty: For monogenic disease, if the embryo is abnormal, we will tell you, and it is. With a risk score, it may be affected. And some patients will only have embryos with higher risks. Then what?

As well, he says it wont be possible with a test to optimize a child for many features at once: My personal opinion is once you start looking, some embryos will be brighter, some will be taller, some will have longevity, and none will have those qualities all together. And in an IVF cycle, you produce maybe six embryos on average. You wont be able to get all the traits that you want.

Despite such inherent limits, theres a bigger plan afoot. Treff, the startup's chief scientist, believes even fertile couples might begin to undergo IVF just so they can select the best child. I do believe this is going to be the future we can start to ... reduce the incidence of disease in humans through IVF, Treff told an audience at a conference in China last month.

How many people will be willing to go through the trouble of IVF if they dont need it to have a baby? IVF involves weeks of hormone shots and two medical procedures (one to collect eggs, another to implant the embryos) and typically costs around $15,000. Add to that the companys fee to test embryos, which is $1,000, plus $400 for each embryo scored.

If someone is fertile, unless there is a family history of disease, I dont think that it is going to be popular, says Munne.

Can you get a smarter baby?

Genomic Prediction has so far won the most attention for the possibility of using genetic scores to pick the most intelligent children from a petri dish. It has tried to distance itself from the controversial concept, but thats been difficult because Hsu, a cofounder, is frequently in the media discussing the idea.

Hsu told The Guardian this year that accurate IQ predictors will be possible if not in the next five years, the next 10 years certainly. He says other countries, or the ultra-wealthy, might be the first to try to boost IQ in their kids this way.

During his talk in China, Treff called improving intelligence via embryo selection an application that many people think is unethical." In private, Treff tells other scientists he thinks it's doable, but wants to promote the technology for medical purposes only.

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For now, the company is limiting itself to alerting parents to embryos it predicts will be the least intelligent, with the highest chance of an IQ which qualifies as intellectual disability according to psychiatric manuals.

Some experts see a transparent maneuver to avoid controversy. They say theyre going to test for the medical condition of intellectual disability, not for the smartest embryos, because they know people are going to object to that, says Laura Hercher, who trains genetic counselors at Sarah Lawrence College. They are trying to slide, slide into traits without admitting as much.

A May report from the Hebrew University of Jerusalem found that trying to pick the tallest or smartest embryos might not work particularly well. Researchers there estimated that using polygenic scores to locate the tallest or smartest child from a batch of sibling embryos would result in an average gain of 2.5 centimeters in height, and less than three IQ points.

They modeled what everyone is scared of happening, Treff said of that study. Its not what we are doing.

The predictions, however, could be more effective at helping people avoid children with specific diseases. Treff, during his speech in China, said that a couple choosing between two embryos would see, on average, a 45% reduction in risk for type 1 diabetes. That is a serious disease from which Treff suffers and which runs in families, although it has complex causes. The more embryos there are to choose from, he says, the more the risk will go down.

Demand for the test

Patients and doctors are mostly on their own when it comes to deciding if the tests really work. While federal and state agencies do oversee laboratory accuracy, the oversight is limited to whether analytes like DNA are correctly measured, not what they mean. So Genomic Prediction doesnt need to prove that the test is useful before selling it. In fact, it could take decades to ascertain if tested kids fare better than others.

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And its not only whether the test works or not. Uptake will depend on demand from patients and the degree of pushback from doctors and genetic counselors. In the US, tests for genderthat is, picking a boy or a girl embryoare accepted and relatively routine. But thats never become the case for choosing eye color, which is also possible. In terms of eye color, the pressure not to do it, to not offer it, was met with a weak market demand. So it doesnt exist, says Hercher.

Genomic Prediction provided a map of 12 fertility clinics it says will order its test, including five in the US and others in Nigeria, Peru, Thailand, and Taiwan.

MIT Technology Review was able to independently locate two IVF clinics where customers have recently requested the embryo predictions. Michael Alper, founder of Boston IVF, one of the worlds largest fertility clinics, says his center was approached by a couple a few weeks ago but he decided the request needs to be weighed by the centers ethics committee before he would agree to order it.

This is the first case we have had, says Alper. To me its a 23andMe type of prediction: theres a propensity, but how strong? That is the problem. We dont have any problem testing for cystic fibrosisthat is a lethal disease, it strikes young. But we are not there yet with these other tests. Its soft; its not that predictive.

At NYU, Keefe says the test raises profound questions. His center is in Midtown Manhattan, just blocks from a hub of finance and legal offices. He says his clientele are typically well-off professionals, people who have programmed everything in life and feel they are in control. They sometimes even ask out loud if a mere doctor is smart enough to help them.

The case he is working on involves a family that has two children with autism. They now want a child without the condition, and they hope the intelligence feature of the test will help them. Treff says he counseled the family that the Genomic Prediction test wasnt likely to helpautism can have specific genetic causes that the intelligence prediction isnt designed to capture.

Yet the family remains interested. They want to do whatever they can to have a healthy kid. Keefe says hes so far supporting their choice, but he is concerned by all that it implies. There is potential psychological harm to the kid, he says. God forbid the kids ends up with autism after spending this money.

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The world's first Gattaca baby tests are finally here - MIT Technology Review

11 November 2019

Twenty thousand babies are to have their genomes sequenced at birth in an NHS-based pilot announced by Matt Hancock on Monday 4 November at the Genomics England Research Conference.

The announcement by the Secretary of State for Health and Social Care did not receive the fanfare or focus it deserved. There has not been a press release from the Department of Health and Social Care, and it was only picked up by the papers on Wednesday 6 November, just before the government and the civil service entered the pre-election purdah period.

The Sun, and the Times welcomed the news, sharing that 'around 3000 of the 660,000 babies born a year in England and Wales are thought to have a treatable, early-onset disease', while other coverage (Futurism, New Scientist)raised ethical challenges and privacy concerns.

It is not hyperbole to state that England will shortly lead the world in genomic diagnosis. The new NHS England Genomic Medicine service will offer all acutely ill children with a likely monogenic condition, and all children with cancer, a whole-genome sequence. The list of diagnostic grade genes on Genomics England's curated PanelApp which allows experts to review genes and the evidence for their relation to conditions, was at 3139 in August 2019 at PanelApp's fourth birthday, with 56,640 gene-disease curations.

In the UK we are in an unusual position. We are at the forefront of diagnosing people with rare diseases but are among the countries screening for fewest rare conditions at birth (see BioNews 1008). The announced pilot offers one route to bridge this disparity. We are behind most countries in Europe and other high-income countries when it comes to identification of babies at risk of genetic conditions at birth.

The UK National Screening Committee currently recommends that the NHS screens for nine conditions at birth few enough to list here: phenylketonuria (first screened for in 1969), congenital hypothyroidism (1981), sickle cell disease (2006), cystic fibrosis (1983 in Northern Ireland, 1997 in Wales, 2003 in Scotland and 2007 in England), and four further metabolic conditions: medium-chain acyl-CoA dehydrogenase deficiency, maple syrup urine disease, isovaleric acidaemia, glutaric aciduria type 1 and homocystinuria (all began in 2015 in England and Wales, and 2017 in Scotland, with no screening in Northern Ireland).

For comparison, Italy screens for 43 conditions, the Netherlands 34, Australia 28, the Czech Republic 20, while Spain screens for seven, Ireland six, and France five.

Diagnosis of symptomatic individuals and screening at birth are two different things: clinical diagnoses are performed with a combination of genomic information from testing and phenotypic information from consultation and a screening approach is clearly not appropriate for all conditions listed in PanelApp. While the disparity between the UK's adoption of each is so great, it can appear to our community that the NHS is waiting for children to get ill instead of intervening sooner.

The benefits of diagnosis to families affected by rare conditions are accepted, but the benefits of screening to identify these families in advance of symptoms developing are ignored. For the affected child, screening can prevent a future lengthy diagnostic odyssey, provide access to treatments that are best delivered before symptoms develop, enable participation in clinical trials and ensure the best possible quality of life by beginning care pathways at the optimum moment.

To the family, screening can identify a risk to future births and enable reproductive decision-making, as well as giving time to prepare for the expected condition. More broadly, newborn screening can improve our knowledge of the incidence and nature of rare conditions and enable research.

In July 2019, Genetic Alliance UK launched our Patient Charter on Newborn Screening: Fixing the Present, Building for the Future. Our community recommended that a pilot of newborn screening using genome sequencing should go ahead as soon as possible for the key reason that the number of conditions that can be identified is much greater than when using traditional metabolic screening technology, which relies on early metabolic indications of the condition. Genomic screening can identify future risk before there are any symptoms. The US-based research project BabySeq labelled 885 gene-disease pairs as having 'definitive or strong evidence to cause a highly penetrant childhood-onset disorder'.

The community also identified the challenges that must be addressed in a pilot. Some of these were picked up in concerns aired in reporting of the announcement. Futurist raised that: 'It would also mean that kids' entire genetic sequence will be mapped out long before they can understand what that means or agree to having it done. As genomic science develops, dilemmas about personal privacy and what happens to the data after its collected are still far from being sorted out.'

Our workshop participants noted that we 'are struggling to adequately inform patients and families about the screening done now within the NHS' but felt that 'we should press on, but recognise that communication and standards need to improve'.

The concern about children's health data being examined before they gain the capacity to understand the implications was one of the many concerns around this initiative that have already been dealt with in some form. Parental choice and how it affects children as they grow up is not a new issue, and the approaches taken to explore this question in the past will be applicable to this pilot.

New Scientist's coverage focused on the challenge of dealing with a screening result for a late-onset condition, which raises the question as to which conditions should be screened for and how they should be selected. Again, this is a question that has been solved before in a different context. The means by which the 100,000 Genomes Project identified whether to report findings and which additional findings to offer can be adapted to address this question.

Other familiar questions will need to be examined again from a different perspective: how to manage a parallel health and research consenting process, the ethics of storing genome sequences, and how genetic information will be shared within families.

New questions that need to be addressed in the pilot include where this methodology fits alongside the current newborn screening programme, and whether this approach is a good use of NHS resources.

The key element of what little we know about this initiative so far is that it is a pilot. Genomics has vast potential to deliver benefit to the currently undeserved community of people living with rare, genetic and undiagnosed conditions. We need to take every opportunity to find answers to the challenges instead of letting them hold us back.

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Let's grasp this opportunity to examine the potential future of screening - BioNews

New technology reduces amount of time spent preparing treatment plans in cancer genomic medicine by half in verification trials conducted with the Department of Hematology and Oncology

KAWASAKI, Japan, Nov 7, 2019 - (JCN Newswire) - Fujitsu has announced the results of a joint research project it has been conducting with the Institute of Medical Science at the University of Tokyo since April 2018. As part of this joint research, Fujitsu Laboratories Ltd. has successfully developed and verified AI technology to improve the efficiency of treatment planning in cancer genomic medicine, demonstrating its effectiveness through verification experiments at the Institute of Medical Science at the University of Tokyo.

In the field of cancer genomic medicine, creating treatment plans derived from genomic information remains a costly and time-consuming process. The newly developed technology extracts from a vast body of research and academic papers to generate a knowledge graph of cancer genomic medicine that can be used for creating treatment plans, including the effects of a given course of treatment. Verification trial experiments using this technology have allowed the Department of Hematology and Oncology at the Institute of Medical Science, the University of Tokyo to reduce the amount of work required to determine a treatment plan for acute myeloid leukemia by more than half, delivering improved efficiency.

Moving forward, Fujitsu Laboratories will support the work of medical doctors by expanding the technology to deal with a greater range of cancer types and contribute to the overall advancement of cancer genomic medicine.

The technology will be on display at "Fujitsu Forum Munich 2019" in Munich, Germany, from Wednesday, November 6.

Development Background

The goal of cancer genomic medicine is to provide optimal medical care for each patient by identifying genomic mutations in cancer patients and predicting the likelihood of disease, as well as drug response and side effects. Starting from June 2019 in Japan, cancer gene panel testing has been covered by health insurance, and industry experts anticipate an increasing number of patients to seek further testing.

Presently, in the field of cancer genomic medicine, it remains necessary for specialist physicians to painstakingly search for relevant articles one by one from a database and determine appropriate treatment methods as well as their effects on the patient (Figure 1). To address these challenges, Fujitsu Laboratories and the Institute of Medical Science at the University of Tokyo's launched a joint AI research project beginning in April 2018 to improve the efficiency and sophistication of the work of physicians specializing in cancer genomics, subsequently conducting a verification trial for the technology.

Outline of the Verification Trials

1. Trial PeriodJuly 2018 to September 2019

2. Trial LocationDepartment of Hematology and Oncology, the Institute of Medical Science at the University of Tokyo

3. Developed technologyThe new technology automatically generates a database of knowledge on the relationship between gene mutations and therapeutic drugs, and the relationship between therapeutic drugs and their effects, drawing from medical papers. This is accomplished by integrating Fujitsu's AI technology for language processing, which identifies terms and phrases used in research papers from context, as well as insight of information needed to discuss treatment policies identified by the Institute of Medical Science at the University of Tokyo.

4. Verification Trial DetailsWith the newly developed technology, 2.4 million elements of relationships from 860,000 medical papers are automatically extracted as knowledge to construct a knowledge graph database for cancer genomic medicine.

In this study, the time required for 4 physicians specializing in hematological malignancies at the Institute of Medical Science at the University of Tokyo to search and examine papers using the technology based on past cases of acute myeloid leukemia is measured, and the efficiency of examination work with and without the newly developed technology is evaluated(1) (Fig. 2). For this verification experiment, a database developed by Fujitsu Limited in cooperation with the Japan Agency for Medical Research and Development as part of the "Program for an Integrated Database of Clinical and Genomic Information"(2) is used as part of the knowledge graph.

5. ResultsThe technology reduced the burden of reading the entire paper by presenting the knowledge extracted from each paper and enabled users to focus on pertinent aspects of research alone. As a result, it was confirmed that the new technology can reduce the amount of time spent on this task by more than half, compared with the average of about 30 minutes per each study it took in the past. At present, it is estimated that more than 12,000 people suffer from leukemia annually in Japan(3), and if genomic medical treatments are administered to all of them using this new technology, the 6,000 hours of examination work normally required for experts can be shortened to 3,000 hours or less, considerably expediting the process of determining the a treatment appropriate for each patient.

Future Plans

Technology developed at Fujitsu Laboratories to explain the reason and rationale behind AI decision-making(4) is to be used in conjunction with this technology in order to further improve the efficiency of the genomic mutation curation process. Fujitsu will further use the knowledge graph for precision medicine developed through this joint research to improve the efficiency of the study of gene mutations for a wide range of cancer types, and actively promote the development of cancer genomics in clinical practice.

Comment from our Research Partners

Professor Seiya Imoto, Health Intelligence Center, the Institute of Medical Science at the University of Tokyo

"The promise of new genomic medicine, which harness the wealth of information contained in the human genome, remains extremely difficult to fully exploit given the limited time of doctors. This trial demonstrates that AI technology can be used to support planning for treatments that target blood tumors, helping physicians to process the research literature that forms the basis of therapeutic best practices in less than half the time it has previously taken. We hope that the further development of AI technology for various genome-related medical contexts will enable more patients to receive precision medicine, contributing to the realization of medical care in Japan that can beat cancer."

(1) The efficiency of examination work with and without the newly developed technology is evaluatedIn the actual verification work, apart from searching relevant research papers, doctors engage in various additional work, such as interpreting sequence data, analyzing data, and creating reports.(2) The Japan Agency for Medical Research and Development as part of the "Program for an Integrated Database of Clinical and Genomic Information"A program based on the interim report of the Council for Promotion of Genome Medicine Implementation, to verify the relationship between genome information and disease specificity and clinical characteristics, to develop a database that comprehensively handles clinical information and genomic information that can be used for clinical and research purposes, and to promote advanced research and development that makes use of the research infrastructure.(3) At present, it is estimated that more than 12,000 people suffer from leukemia annually in JapanCancer Information Service, National Cancer Research Center "Cancer registry and statistics"(Source).(4) Press Release"Fujitsu Fuses Deep Tensor with Knowledge Graph to Explain Reason and Basis Behind AI-Generated Findings" (September 20, 2017)

About Fujitsu

Fujitsu is the leading Japanese information and communication technology (ICT) company, offering a full range of technology products, solutions, and services. Approximately 132,000 Fujitsu people support customers in more than 100 countries. We use our experience and the power of ICT to shape the future of society with our customers. Fujitsu Limited (Code: 6702) reported consolidated revenues of 4.0 trillion yen (US $36 billion) for the fiscal year ended March 31, 2019. For more information, please see http://www.fujitsu.com.

About Fujitsu Laboratories

Founded in 1968 as a wholly owned subsidiary of Fujitsu Limited, Fujitsu Laboratories Ltd. is one of the premier research centers in the world. With a global network of laboratories in Japan, China, the United States and Europe, the organization conducts a wide range of basic and applied research in the areas of Next-generation Services, Computer Servers, Networks, Electronic Devices, and Advanced Materials. For more information, please see http://www.fujitsu.com/jp/group/labs/en/.

Technical ContactsFujitsu Laboratories Ltd.Artificial Intelligence LaboratoryE-mail: qa_fy2019@ml.labs.fujitsu.com

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Fujitsu Improves Efficiency in Cancer Genomic Medicine in Joint AI Research with the Institute of Medical Science at the University of Tokyo -...

REDWOOD CITY, Calif., Nov. 7, 2019 /PRNewswire/ --Genomic Health, Inc.(NASDAQ: GHDX) announced that its stockholders voted to approve the company's proposed combination with Exact Sciences Corp (NASDAQ: EXAS) at a special meeting held earlier today.

As previously announced, on July 29, 2019, Genomic Health and Exact Sciences entered into the merger agreement by which Exact Sciences will acquire Genomic Health in a cash and stock transaction. With the receipt of the required stockholder approval, Genomic Health and Exact Sciences expect to close the transaction on Friday, November 8 subject to satisfaction of the remaining customary closing conditions.

Final vote tallies from the Genomic Health special meeting of stockholders are subject to certification by the Company's inspector of elections and will be included in a report to be filed by the Company with the Securities and Exchange Commission (the "SEC").

AboutGenomic HealthGenomic Health, Inc. (NASDAQ: GHDX) is the world's leading provider of genomic-based diagnostic tests that help optimize cancer care, including addressing the overtreatment of the disease, one of the greatest issues in healthcare today. With its Oncotype IQGenomic Intelligence Platform, the company is applying its world-class scientific and commercial expertise and infrastructure to lead the translation of clinical and genomic data into actionable results for treatment planning throughout the cancer patient journey, from diagnosis to treatment selection and monitoring. The Oncotype IQ portfolio of genomic tests and services currently consists of the company's flagship line of Oncotype DXgene expression tests that have been used to guide treatment decisions for over 1 million cancer patients worldwide.Genomic Healthis expanding its test portfolio to include additional liquid- and tissue-based tests, including the Oncotype DXAR-V7 Nucleus Detecttest. The company is based inRedwood City,California,with international headquarters inGeneva,Switzerland. For more information, please visitwww.GenomicHealth.comand follow the company on Twitter:@GenomicHealth,Facebook,YouTubeandLinkedIn.

This press release contains statements, including statements regarding the merger that are forward-looking statements within the meaning of Section 21E of the Securities Exchange Act of 1934, as amended, that are intended to be covered by the "safe harbor" created thereby. Forward-looking statements, which are based on certain assumptions and describe future plans, expectations and events, can generally be identified by the use of forward-looking terms such as "believe," "expect," "may," "will," "should," "would," "could," "seek," "intend," "plan," "anticipate" or other comparable terms. All statements other than statements of historical facts included in this press release regarding the expected closing of the merger are forward-looking statements. Forward-looking statements are neither historical facts nor assurances of future performance or events. Instead, they are based only on current beliefs, expectations and assumptions regarding future business developments, future plans and strategies, projections, anticipated events and trends, the economy and other future conditions. Because forward-looking statements relate to the future, they are subject to inherent uncertainties, risks and changes in circumstances that are difficult to predict and many of which are outside of Genomic Health's control. Actual results, conditions and events may differ materially from those indicated in the forward-looking statements. Therefore, you should not rely on any of these forward-looking statements. Important factors that could cause actual results, conditions and events to differ materially from those indicated in the forward-looking statements include, among others, the following: the ability of the parties to satisfy the remaining closing conditions in order to close the proposed merger with Exact Sciences Corporation and other risks as detailed from time to time in Genomic Health's reports filed with the SEC, including its annual report on Form 10-K, quarterly reports on Form 10-Q, current reports on Form 8-K and other documents filed with the SEC.

There can be no assurance that the merger or any other transaction described will in fact be completed in the manner described or at all. Any forward-looking statement speaks only as of the date on which it is made, and Genomic Health assumes no obligation to update or revise such statement, whether as a result of new information, future events or otherwise, except as required by applicable law. Readers are cautioned not to place undue reliance on any of these forward-looking statements.

GHDX-F

SOURCE Genomic Health, Inc.

http://www.GenomicHealth.com

Original post:
Genomic Health Stockholders Approve Proposed Acquisition by Exact Sciences - PRNewswire

For 1.5 billion years, the mitochondrial and nuclear genomes have been coevolving. Over this time, the mitochondrial genome became reduced, retaining only 37 genes in most animal species, and growing reliant on the nuclear genome to fulfill the organelles primary functionto produce ATP by oxidative phosphorylation. Mitochondrial gene products interact with those encoded in nuclear genes, and sometimes with the nuclear genome itself. Because the mitochondrial genome mutates faster than the nuclear genome, it takes the lead in the mitonuclear evolutionary dance, while the nuclear genome follows, evolving compensatory mutations to maintain coadapted gene complexes. Researchers are now coming to appreciate that this has consequences for physiology and even macroevolution.

Researchers have long known that many proteins are made of several components, some of which are coded for in the mitochondrial genome, and others being coded for in the nuclear genome. Cytochrome oxidase, the last enzyme in the respiratory electron transport chain, is one example.

Mitochondria require nuclear gene products to continually produce energy for the cell. For example, mitochondrial protein translation requires aminoacyl tRNA synthetases (aaRS) encoded by the nuclear genome to attach amino acids to the corresponding tRNAs encoded by the mitochondrial genome.

Mitochondrial gene products can influence the expression of nuclear genes, though the mechanisms are as yet unclear.

The intimate relationship between the mitochondrial and nuclear genomes comes into play as populations evolve. For example, the relatively fast mutation rate of mitochondrial DNA (mtDNA) means that the nuclear genome (nDNA) has had to evolve compensatory mutations to keep pace and maintain collaborative functionality. This process causes populations to drift apart due to mitonuclear incompatibilities.

Copepods on the Pacific coast of North America are the best-known example of this phenomenon. Researchers have successfully bred animals from different tide pools, and while the first-generation hybrids do fine, second-generation individuals develop slower and have fewer offspring.

When F2 hybrids are backcrossed to the paternal line, they show no improvement in fitness. When they are backcrossed to their maternal line, however, their fitness is rescued, most likely because the backcross in this direction reintroduces the nuclear genome to the mitochondrial background it is co-adapted with.

F2 hybrid females crossed with paternal line, where mitochondria types do not match, leads to no fitness improvement:

F2 hybrid females crossed with maternal line, which carries the same mitochondrial type, improves fitness:

Read thefull story.

Correction (November 5): The illustration in this story has been updated to correctly label the red copepods as coming from San Diego.The Scientistregrets the error.

Read more from the original source:
Infographic: How the Mitochondrial and Nuclear Genomes Interact - The Scientist

Looking for broad exposure to the Healthcare - Biotech segment of the equity market? You should consider the Invesco Dynamic Biotechnology & Genome ETF (PBE), a passively managed exchange traded fund launched on 06/23/2005.

Passively managed ETFs are becoming increasingly popular with institutional as well as retail investors due to their low cost, transparency, flexibility and tax efficiency. They are excellent vehicles for long term investors.

Sector ETFs also provide investors access to a broad group of companies in particular sectors that offer low risk and diversified exposure. Healthcare - Biotech is one of the 16 broad Zacks sectors within the Zacks Industry classification. It is currently ranked 2, placing it in top 13%.

Index Details

The fund is sponsored by Invesco. It has amassed assets over $227.92 M, making it one of the average sized ETFs attempting to match the performance of the Healthcare - Biotech segment of the equity market. PBE seeks to match the performance of the Dynamic Biotechnology & Genome Intellidex Index before fees and expenses.

This is comprised of stocks of 30 U.S. biotechnology and genome companies. These are companies that are principally engaged in the research, development, manufacture and marketing and distribution of various biotechnological products, services and processes and companies that benefit significantly from scientific and technological advances in biotechnology and genetic engineering and research.

Costs

Expense ratios are an important factor in the return of an ETF and in the long term, cheaper funds can significantly outperform their more expensive counterparts, other things remaining the same.

Annual operating expenses for this ETF are 0.57%, making it on par with most peer products in the space.

Sector Exposure and Top Holdings

While ETFs offer diversified exposure, which minimizes single stock risk, a deep look into a fund's holdings is a valuable exercise. And, most ETFs are very transparent products that disclose their holdings on a daily basis.

This ETF has heaviest allocation in the Healthcare sector--about 100% of the portfolio.

Looking at individual holdings, Biogen Inc (BIIB) accounts for about 6.52% of total assets, followed by Vertex Pharmaceuticals Inc (VRTX) and Celgene Corp (CELG).

The top 10 holdings account for about 49.20% of total assets under management.

Performance and Risk

The ETF has added roughly 10.04% so far this year and is down about -3.11% in the last one year (as of 11/05/2019). In that past 52-week period, it has traded between $43.44 and $56.26.

The ETF has a beta of 1.43 and standard deviation of 23.63% for the trailing three-year period, making it a high risk choice in the space. With about 30 holdings, it has more concentrated exposure than peers.

Alternatives

Invesco Dynamic Biotechnology & Genome ETF carries a Zacks ETF Rank of 3 (Hold), which is based on expected asset class return, expense ratio, and momentum, among other factors. Thus, PBE is a reasonable option for those seeking exposure to the Health Care ETFs area of the market. Investors might also want to consider some other ETF options in the space.

SPDR S&P Biotech ETF (XBI) tracks S&P Biotechnology Select Industry Index and the iShares Nasdaq Biotechnology ETF (IBB) tracks Nasdaq Biotechnology Index. SPDR S&P Biotech ETF has $3.81 B in assets, iShares Nasdaq Biotechnology ETF has $7.02 B. XBI has an expense ratio of 0.35% and IBB charges 0.47%.

Bottom Line

To learn more about this product and other ETFs, screen for products that match your investment objectives and read articles on latest developments in the ETF investing universe, please visit Zacks ETF Center.

Want the latest recommendations from Zacks Investment Research? Today, you can download 7 Best Stocks for the Next 30 Days. Click to get this free reportInvesco Dynamic Biotechnology & Genome ETF (PBE): ETF Research ReportsiShares Nasdaq Biotechnology ETF (IBB): ETF Research ReportsSPDR S&P Biotech ETF (XBI): ETF Research ReportsCelgene Corporation (CELG) : Free Stock Analysis ReportVertex Pharmaceuticals Incorporated (VRTX) : Free Stock Analysis ReportBiogen Inc. (BIIB) : Free Stock Analysis ReportTo read this article on Zacks.com click here.Zacks Investment Research

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Should You Invest in the Invesco Dynamic Biotechnology & Genome ETF (PBE)? - Yahoo Finance

All right, lets do this one last time. My name is CRISPR. I was made from a bacterial defense system, and for years Ive been the one and only gene editing wunderkind. Im pretty sure you know the rest. Im relatively cheap to make, easy to wield, and snip out genes pretty on target. Im going into clinical trials. Im reviving the entire field of gene therapy. Theres only one CRISPR. And youre looking at it.

Well, just as Spider-Man was way off, so is the idea of a single CRISPR to rule them all. This month, Dr. David Liu at the Broad Institute of MIT and Harvard in Cambridge, MA, introduced an upgrade that in theory may correct nearly 90 percent of all disease-causing genetic variations. Rather than simply deactivating a gene, CRISPR-based prime editing is a true search-and-replace editor for the human genome. With a single version, it can change individual DNA letters, delete letters, or insert blocks of new letters into the genome, with minimal damage to the DNA strand.

For now, prime editing has only been tested in cultured cells. But its efficacy is off the charts. Early experiments found it could correct single-letter misspellings in sickle cell disease, snip out four superfluous letters that underlie Tay-Sachs, and insert three missing letters to correct a genomic typo that leads to cystic fibrosis. In all, the tool worked remarkably well in over 175 edits in both human and mouse cells.

The excitement has been palpable, said Dr. Fyodor Urnov at the University of California, Berkeley, who was not involved in the research. I cant overstate the significance of this.

Given all of the existing CRISPR upgrades, why are scientists head over heels about prime editing?

CRISPR 1.0 generally refers to the classic version, which snips open the double helix to get rid of a certain gene. But as a tool, todays CRISPR is less like genetic scissors and more similar to a Swiss Army knife, one that scientists keep on improving. There are variants that, rather than destroying a gene, insert one or change one genetic letter to another, or ones that can target thousands of genetic spots at the same time. There are also spin-offs that hunt down RNAthe messenger that carries DNAs genetic code to the greater cellular universe, rather than the genetic code itself. Its truly a CRISPR multiverse out there.

Yet for all of CRISPRs upgrades, the tool has serious issues. For one, its very rough on the genome. Cas9, the protein scissor component of CRISPR, doesnt surgically cut out a gene. Rather, editing is in fact the cell detecting damage to the double helix, and trying its best to patch the broken strands back up. Just as scars form on our skin, this process can often introduce errors in the repairing processadding or missing a letter or two. Scientists often take advantage of this botched repair to destroy a gene that causes disease, or sneak in some additional code.

The problem? This process is basically genome vandalism, said Dr. George Church, a CRISPR pioneer at Harvard who wasnt involved in the new work. Its great when the repair goes according to plan; when it doesnt, the repair can introduce unwantedor downright dangerousmutations.

Lius idea for prime editing grew from his work on base editors. Here, the CRISPR machinery doesnt chop up the double helix. Rather, it uses the blood hound guide RNA to shuttle a new protein component to the target DNA sequence. This component then performs a single letter swap: C to T, or G to A.

Although considered much safer than traditional cut-and-glue CRISPR, base editors are limited in the number of genetic diseases they can treat. Its like editing on a broken keyboardsome misspellings just cant be fixed.

Prime editing circumvents these problems by heavily upgrading both components. The altered Cas9, for example, only snips a single strand of the double helix, rather than chomping through both. The new guide, pegRNA, both tethers the entire machinery to the target site, and encodes the desired edit.

Then comes the third component that magically ties everything together: a protein dubbed reverse transcriptase, which can make DNA sequences based on the blueprint in pegRNA, to insert into the nicked target site.

Still confused? Picture the DNA double helix as a laddertwo strands with connecting rungs in the middle. Prime editing cuts one strand using its neutered Cas9. This creates an opening for the other two components to insert a new gene into the severed spot; meanwhile, the original DNA sequence is snipped off. Now, rather than the original X, X (for example), the cell has X, Y.

The prime editor then performs a second snip at the opposing, non-edited strand. This alerts the cell of DNA damage, which it then tries to fixusing the new gene as a template. The end result is the cell goes from disease-causing X, X to normal, healthy Y, Y.

Several reasons.

One, because it doesnt cut both DNA strands, it doesnt immediately activate the cells repair system that is prone to errors. This means that scientists have far better control over the type of edit they want, and its no longer left to chance.

Two, prime is remarkably multi-purpose. Previously, the consensus among genome scientists was that a separate CRISPR tool was required for each specific type of edit: delete a gene, insert new DNA code, or DNA letter substitutions. In contrast, prime can achieve all three functions without additional modification. For experiments, it means less setup. For development into gene therapy, it means less overhead investment.

Three, prime editing can swap any of the DNA letters into any other, meaning it can now target an enormous amount of inherited diseases. For example, sickle cell disease, which causes oxygen-carrying blood cells to deform into sharp sickle-like shapes, requires changing a T into an A at a precise spot. Base editors cant do that. Prime editing can. Thats about 7,000 genetic disorders now amenable to gene therapy.

Four, prime editing also works in cells that no longer divide to renew themselves, such as neurons and muscle cells. Because these cells cant pass on their therapeutic DNA edit to daughter cells, to fix genetic deficits scientists have to be able to efficiently correct mutations in a large population. With prime editing, thats now possible.

Finally, prime editing can remove an exact number of letters from a given spot on the genome, at least up to 80. This allows scientists to precisely dictate the DNA sequences they want out, rather than relying on chance.

Early experiments with prime editing in cells show the tool is incredibly accurate. Off-target nicks were below 10 percent, and less than one-tenth of edited cells had unwanted changes to their genome, compared to up to 90 percent for first-gen CRISPR systems.

Nevertheless, the tool will have to go through rigorous testing before its widely accepted. Working in a few types of human cells is one thing; having it perform equally well inside a living body is something else completely. Most of primes tricks so far can be replicated using CRISPR 1.0, though at lower efficacy and with higher chances of off-target failures. Unlike prime editing, however, the original version has years of experience and plenty of clinical trials underwaycongenital blindness, sickle cell diseaseto back it up.

Whats more, prime is massive in terms of molecular tools. Getting it into cells will be a struggle. Getting it to the brain, which is protected by a dense wall of cells, will be even harder. To get the editor to their target, scientists will likely rely on gene therapy, itself a budding industry.

If CRISPR is like scissors, base editors are like a pencil. Then you can think of prime editors like a word processor, capable of precise search and replace, said Liu. All will have rolesThis is the beginning rather than the end.

Image Credit:petarg/Shutterstock.com

Read more:
Everything You Need to Know About Superstar CRISPR Prime Editing - Singularity Hub