StemCell Therapy

-- Webcast conference call to be held on Monday, Sept. 28, 2020 at 8:30 a.m. Eastern Time --

-- Additional poster presentations at WMS will highlight data from Sareptas RNA and gene therapy programs --

CAMBRIDGE, Mass., Sept. 14, 2020 (GLOBE NEWSWIRE) -- Sarepta Therapeutics, Inc. (NASDAQ:SRPT), the leader in precision genetic medicine for rare diseases, today announced that new data from its most advanced gene therapy programs will be presented at the WMS25 Virtual Congress, the 25th International Annual Congress of the World Muscle Society, being held Sept. 28 Oct. 2.

Sarepta will host a webcast and conference call on Monday, Sept. 28, 2020 at 8:30 a.m. ET, to discuss the results, which include two-year functional data from Study 101 of SRP-9001 for Duchenne muscular dystrophy and 18-month functional results from Cohort 1 in the study of SRP-9003 for Limb-girdle muscular dystrophy Type 2E.

This will be webcast live under the investor relations section of Sarepta's website at https://investorrelations.sarepta.com/events-presentationsand will be archived there following the call for one year. Please connect to Sarepta's website several minutes prior to the start of the broadcast to ensure adequate time for any software download that may be necessary. The conference call may be accessed by dialing (844) 534-7313 for domestic callers and (574) 990-1451 for international callers. The passcode for the call is 6793650. Please specify to the operator that you would like to join the "Long-term Functional Data from Sareptas Gene Therapy Programs call.

In total, Sarepta will present 16 abstracts at this years meeting. All posters will be available on-demand throughout the Congress beginning on Monday, Sept. 28 at 7:00 a.m. EST. The full WMS25 Virtual Congress program is available here: https://www.wms2020.com/programme/.

Gene Therapy:

RNA Platform:

Natural history and other presentations:

Presentations will be archived under the events and presentations section of the Sarepta Therapeutics website at http://www.sarepta.comforone year following their presentation at WMS25.

AboutSarepta TherapeuticsAt Sarepta, we are leading a revolution in precision genetic medicine and every day is an opportunity to change the lives of people living with rare disease. The Company has built an impressive position in Duchenne muscular dystrophy (DMD) and in gene therapies for limb-girdle muscular dystrophies (LGMDs), mucopolysaccharidosis type IIIA, Charcot-Marie-Tooth (CMT), and other CNS-related disorders, with more than 40 programs in various stages of development. The Companys programs and research focus span several therapeutic modalities, including RNA, gene therapy and gene editing. For more information, please visitwww.sarepta.com or follow us on Twitter, LinkedIn, Instagram and Facebook.

Internet Posting of Information

We routinely post information that may be important to investors in the 'For Investors' section of our website atwww.sarepta.com. We encourage investors and potential investors to consult our website regularly for important information about us.

Source: Sarepta Therapeutics, Inc.

Sarepta Therapeutics, Inc.

Investors: Ian Estepan, 617-274-4052, iestepan@sarepta.com

Media: Tracy Sorrentino, 617-301-8566, tsorrentino@sarepta.com

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Long-term functional data from Sarepta Therapeutics' Most Advanced Gene Therapy Programs to be Presented at Upcoming Annual Congress of the World...

JAPAN

Japans official medical research funding agency Japan Agency for Medical Research and Development (AMED), reports that public financial support for university-based research in collaboration with industry into COVID-19 vaccines and treatments has ballooned since March.

Almost JPY113 billion (US$1.07 billion) in funds was allocated this fiscal year against a backdrop of increasing global competition for successful breakthroughs as second and third waves of the COVID-19 pandemic affect the economy, society and education, as well as being a serious health problem. Japan has enacted large supplementary budgets of trillions of yen to help the economy cope since the outbreak hit the country in March.

The global pandemic, which is very contagious and life-threatening, represents an emergency situation. Investment towards a cure is critical for public safety, said Atsuko Oshima, who is in charge of public relations at AMED.

Oshima explained that the government views COVID-19 and new infections as a new global challenge and has turned its attention towards strengthening research funds for pandemics.

For example, it is funding a university-led task force for joint COVID-19 research projects established by prominent Japanese universities, including the University of Tokyo, Keio University, Tokyo Institute of Technology, Kitasato University and Osaka University, with experts from diverse fields, including infectious diseases, virology, molecular genetics, genomic medicine and computational science.

In an initial project, the task force will use state-of-the-art genomic analysis technology to reveal the genetic basis for the mechanism that causes exacerbation of COVID-19 and will work to develop an effective mucosal vaccine to protect against the virus.

Academics view the COVID-19 crisis as a landmark event for multidisciplinary university research. With the novel coronavirus affecting millions of people around the world, scientists and medical communities face intense pressure to develop potential solutions, noted Takafumi Ueno, biomolecular research specialist at the leading Tokyo Institute of Technology.

The university, famous for technology development, is participating in collaborative research with the private sector and other universities, including participating in the task force.

Ueno referred to pressure to respond to the large amount of public funds poured into coronavirus-related research. With taxpayer funds available, researchers are intensely mindful that results must provide for the betterment of society, he said.

Joint research between academia and the private sector is not a new development. But COVID-19 has provided a boost against a backdrop of rising funding and pressure for swift results.

Shinzo Abe, who stepped down as prime minister on 28 August, pledged to make a vaccine available for every Japanese person.

Push for locally developed vaccine

The government is pushing for a home-grown vaccine. A special measure aimed at securing vaccines as quickly as possible was enacted in late August to exempt Japanese and foreign pharmaceutical companies and other concerned parties from liability against compensating people whose health is damaged due to vaccination against COVID-19. Instead, the government will be responsible for any redress.

Japans Kyodo News service reported in late August that the government plans to submit related bills for this measure in the Diet, the Japanese parliament, in October.

Among the slew of ongoing domestic projects to prevent COVID-19 infections, Osaka City University Hospital reported in June that it conducted the first clinical trials on humans of a DNA vaccine.

According a June news release from AnGes, this type of vaccine will inject genetically engineered circular DNA (plasmid) that produces spike proteins, which are characteristic of coronavirus. When the pathogen proteins are made, the bodys immune system is stimulated to make antibodies against the virus.

DNA vaccines are produced using an inactivated virus which only uses the genetic information of the virus rather than the virus itself, and can be manufactured faster than protein-based vaccines, according to the company statement.

However, globally to date no DNA vaccine has yet been approved for use in humans, requiring more time to determine safety and efficacy before it can be rolled out for general use.

The project is owned by AnGes Inc, a medical start-up venture by Osaka University in partnership with Japanese biotech company Takara Bio Inc. Takara Bio has production facilities and manufacturing experience with plasmid DNA products and will be responsible for vaccine production.

Special cooperation model

Yasufumi Kaneda, vice-president of Osaka University and an expert on DNA therapy, leads the industry-academia Co-creation group at the university that oversees the collaborative project. He explained to University World News that AnGess venture a separate entity affiliated with the university represents a rare set up in collaborative research.

The venture acts as a bridge between academic research and the final deployment of the product with a drug maker. By collecting and analysing information, its role is to ensure the safety of the vaccine before large-scale manufacturing for public use. The venture eases the risk faced when defining the final product, he said.

Kaneda explained that the basic research sector collaboration with cross-industry vaccine and treatment is spearheaded by universities with the private sector leading mass manufacturing and dissemination.

The success of the final product demands a high element of risk taking. While COVID-19 research is the exception, it is common practice in Japan for big companies to shun investment in projects that do not indicate clear results, he said, adding that the university-industry venture system can narrow the gap.

The role of providing concrete and appropriate data and scientific facts of the project to companies strengthens understanding and investment for the final product, he said.

The AnGes vaccine trial is now concentrating on the antibody reaction observed in patients. A separate clinical trial is planned at the Osaka hospital as another critical step to obtain government approval in 2021.

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Vaccine research deepens university-industry collaboration - University World News

Myotonic dystrophy type I (DM1) is the most common type of adult-onset muscular dystrophy. DM1 is caused by mutations in the DMPK gene. A normal DMPK gene has 3 to 37 repetitions of the CTG sequence, while in DM1, there are hundreds to thousands of repetitions of this sequence. When a DMPK gene with too many CTG repeats is transcribed, the resulting RNA is too long. This abnormally long RNA is toxic to cells, and those affected experience progressive muscle wasting and weakness.

CRISPR-Cas9 is a technique increasingly used in efforts to correct the genetic defects that cause a variety of diseases. Now a research team from the University of California, San Diego (UCSD), School of Medicine, reports they redirected the technique to modify RNA in a method they call RNA-targeting Cas9 (RCas9), to eliminate the toxic RNA and almost fully reverse symptoms in a mouse model of myotonic dystrophy.

Their findings, The sustained expression of Cas9 targeting toxic RNAs reverses disease phenotypes in mouse models of myotonic dystrophy type 1, was published in Nature Biomedical Engineering and led by Gene Yeo, PhD, professor of cellular and molecular medicine at UCSD School of Medicine.

Myotonic dystrophy is part of a group of inherited disorders called muscular dystrophies. There are two major types of myotonic dystrophy: type 1 and type 2. The muscle weakness associated with type 1 particularly affects muscles farthest from the center of the body, such as those of the lower legs, hands, neck, and face. Muscle weakness in type 2 primarily involves muscles close to the center of the body, such as those of the neck, shoulders, elbows, and hips. The two types of myotonic dystrophy are caused by mutations in different genes.

Many other severe neuromuscular diseases, such as Huntingtons and ALS, are also caused by similar RNA buildup, explained Yeo. There are no cures for these diseases. Yeo led the study with collaborators at Locanabio and the University of Florida.

CRISPR-Cas9 works by directing Cas9 to cut a specific target gene, allowing researchers to inactivate or replace the gene. However, the Cas9 in the RCas9 method is guided to an RNA molecule instead of DNA. In a previous study, Yeo and his team established RCas9 as a means to track RNA in living cells in a programmable manner without genetically encoded tags. In a 2017 study, in lab models and patient-derived cells, the researchers used RCas9 to eliminate 95% of the abnormal RNA linked to myotonic dystrophy type 1 and type 2, one type of ALS and Huntingtons disease.

In the current study, the method goes further, by reversing myotonic dystrophy type 1 in a mouse model of the disease. Toxic RNAs expressed from such repetitive sequences can be eliminated using CRISPR-mediated RNA targeting, yet evidence of its in vivo efficacy and durability is lacking, noted the researchers. Here, using adult and neonatal mouse models of DM1, we show that intramuscular or systemic injections of adeno-associated virus (AAV) vectors encoding nuclease-dead Cas9 and a single-guide RNA targeting CUG repeats results in the expression of the RNA-targeting Cas9 for up to three months, redistribution of the RNA-splicing protein muscleblind-like splicing regulator 1, elimination of foci of toxic RNA, reversal of splicing biomarkers and amelioration of myotonia.

The researchers packaged RCas9 in a non-infectious virus. They then gave the mice a single dose of the therapy or a placebo. RCas9 reduced the abnormal RNA repeats by more than 50%, varying a bit depending on the tissue, and the treated myotonic dystrophy mice became indistinguishable from healthy mice.

To prevent the potential of the RCas9 proteins, developing an immune reaction in the mice, the researchers tried suppressing the mices immune systems briefly during treatment. As a result, they were surprised to see that they successfully prevented immune reaction and clearance. The researchers did not see signs of muscle damage, but found an increase in the activity of genes involved in new muscle formation.

Yeo believes the findings will open a new avenue of understanding and lead the way for treating other genetic diseases. This opens up the floodgates to start testing RNA-targeting CRISPR-Cas9 as a potential approach to treat other human genetic diseasesthere are at least 20 caused by buildup of repetitive RNAs, Yeo added.

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Muscular Dystrophy Condition in Mice Reversed by RNA-Targeting Cas9 - Genetic Engineering & Biotechnology News

Precision medicine has been changing the game for the healthcare industry.

FREMONT, CA: Precision medicine, as the name suggests, is a technique to ensure the highest level of accuracy. The modern healthcare industry has been increasingly adopting the conceptualizations of precision medicine to level up their results and elevate their milestones. The pandemic that has been caused due to the outbreak of the novel COVID virus has raised the possibilities of opportunities for the healthcare researchers and technologists lately. The modern developments in precision medicine are today enabling the healthcare experts to personalize treatment by examining the genetic makeup of the patient individually.

Modern learned professionals and specialists in the healthcare industry believe that everybody is unique, and their physiological makeup is different. In the wake of making medicine personalized, precision medicine technology is offering new features and uses cases that help in crafting therapies and treatments by analyzing the genetic makeup and other unique characteristics to determine the condition of the health of an individual.

Precision medicine has proved to be beneficial in handling diseases such as cancer and other diseases that involve mutations and even infectious diseases. This technique also helps in dealing with inherited diseases as well. With the help of data, precision medicine would actually become one of the most significant aspects in not only treating the diseases according to individual vitals and characteristics but ensuring accuracy as well. Doctors and healthcare specialists believe in the fact that most of the diseases involve a range of multiple genes, and hence, a clear and complete analysis of the genetic data would be the key in the making the precision approach a success.

Data analytics and even AI and other deep learning technologies are coupled with precision medicine to help double the potential of this technique. The future of healthcare is precision medicine, and the essence and potentiality of data is the key and crucial input for the success of the precision approach. This could be the way for expert personalization of treatments as well.

See Also:Top Data Analytics Consulting/Service Companies

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How Precision Medicine Helps in Personalizing Medicine Based on the... - Healthcare Tech Outlook

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SALINAS, Calif. (KSBW) The Borofka family celebrated their son JTs second birthday by throwing him a drive-by birthday parade Sunday. JT Borofka has already achieved more obstacles than most kids his age. Suffering with Triosephosphate Isomerase Deficiency, or TPI, this rare genetic disease has been challenging to say the least.

Hes weaker, but at the moment hes stable, explained JTs mom, Tara Borofka. We still work with physical therapy. Hes got a little bit better head control. JT is extremely strong and doesnt give up. If theres a toy that is a little too far, he will reach for it even if he has to fall over.

And just like JT, his doctors in Pittsburgh arent giving up either.

The next step is to go through all the compounds they have found that could possibly be a cure, explained Jason Borofka, JTs dad.

Michael Palladino, Professor of Pharmacology and Chemical Biology at the University of Pittsburgh School of Medicine said those compounds will need to be tested.

We can test them first in a mouse model, explained Palladino. If you can show that not only did it work in JTs cell. We have JTs cells to test these drugs in, but when we put it in an animal model with his same mutations, that that animal model improves as well.

The process can take anywhere from 8 months to 3 years, but while the Borofkas wait for the cure, theyre focusing on celebrating another year with their son.

Please note: This content carries a strict local market embargo. If you share the same market as the contributor of this article, you may not use it on any platform.

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Family celebrates another year with son who has a rare genetic disease - KESQ

By UW Medicine | Newsroom

The immune system usually mounts a strong immune response to infection by SARS-CoV-2, the virus that causes COVID-19. That defensive response, however, appears to be weaker in men and people over the age of 60, a study led by researchers at the University of Washington School of Medicine in Seattle has found.

There were some early studies that suggested that there was a fairly weak antiviral response shortly after infection, but we found a very robust immune response in patients at the time of symptom onset, said lead author Nicole Lieberman. But differences in the immune response in older individuals and men may contribute to the greater severity and higher mortality we see in these groups.

Lieberman is a research scientist in the laboratory of Alex Greninger. He is an assistant professor in the department of Laboratory Medicine and Pathology at the University of Washington School of Medicine and head of the project. The results of the study appear in the open-access journal PLOS Biology. Click here for the paper.

In the study, the researchers compared samples swabbed from the noses and throats of 430 people who were infected with SARS-CoV-2 and 54 people who were not. They also worked with colleagues at Columbia University Medical Center in New York City and University of Texas Medical Branch, Galveston, Texas. These groups have developed techniques to infect cells in culture to track changes in the immune response over time.

To assess immune responses the researchers analyzed the RNA in the samples. Because the SARS-CoV-2 stores its genetic instructions in RNA, levels of viral RNA in the samples revealed the amount of virus, or viral load, an indicator of the severity of infection. In human cells. On the other hand, RNA reveals which proteins the cells are producing in response to the infection. Thats because, for the instructions for synthesizing proteins encoded in the DNA of genes to be read by the cells, the code must first be copied, into RNA. As a result, analyzing the RNA transcriptsin a sample can show which genes are being dialed up in response to the infection and which are being dialed down. This sort of analysis can reveal what sort of immune counterattack the cells are mounting against the virus.

The researchers found that the viral load in these patients was high, but also that SARS-CoV-2 triggers a strong antiviral response. This includes up-regulation of genes for a number of antiviral factors that activate the cells defenses against viral invaders. It also includes chemical signals that summon immune cells to fight the infection, such as interferons and chemokines.

The viral load with SARS-CoV-2 infection is one of the highest seen, Greninger said. But the immune response is very strong, and the higher the viral load, the stronger the response.

However, in older individuals over age 60, infection did not activate genes to summon virus-fighting cells called cytotoxic T cells and natural killer cells that are some of the bodys the most effective antiviral weapons.

The older patients activate a weaker immune response like a singer that just cant hit the high notes anymore, Greninger said.

The researchers also found that men mounted a less vigorous response compared to women. The males produced lower levels of transcripts of some anti-viral proteins, and pumped out some proteins that put a damper on the immune response.

In men were seeing an up-regulation of signals that turn off the immune system, Lieberman said. Its speculation, but it appears as though some men may throttle back their immune system too soon before mounting an effective response to infection.

This work was supported by National Institutes of Health (AI146980, AI121349, and NS091263) and the Department of Laboratory Medicine and Pathology at the UW School of Medicine.

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Why is COVID-19 more severe in men and elders? | UW... - Covington-Maple Valley Reporter

Abstract

Large-scale genomic and transcriptomic initiatives offer unprecedented insight into complex traits, but clinical translation remains limited by variant-level associations without biological context and lack of analytic resources. Our resource, PhenomeXcan, synthesizes 8.87 million variants from genome-wide association study summary statistics on 4091 traits with transcriptomic data from 49 tissues in Genotype-Tissue Expression v8 into a gene-based, queryable platform including 22,515 genes. We developed a novel Bayesian colocalization method, fast enrichment estimation aided colocalization analysis (fastENLOC), to prioritize likely causal gene-trait associations. We successfully replicate associations from the phenome-wide association studies (PheWAS) catalog Online Mendelian Inheritance in Man, and an evidence-based curated gene list. Using PhenomeXcan results, we provide examples of novel and underreported genome-to-phenome associations, complex gene-trait clusters, shared causal genes between common and rare diseases via further integration of PhenomeXcan with ClinVar, and potential therapeutic targets. PhenomeXcan (phenomexcan.org) provides broad, user-friendly access to complex data for translational researchers.

Unprecedented advances in genetic technologies over the past decade have identified over tens of thousands of variants associated with complex traits (1). Translating these variants into actionable targets for precision medicine or drug development, however, remains slow and difficult (2). Existing catalogs largely organize associations between genetic variants and complex traits at the variant level rather than by genes and often are confined to a narrow set of genes or traits (3). This has greatly limited development and application of large-scale assessments that account for spurious associations between variants and traits. As a result, only 10% of genes are under active translational research, with a strong bias toward monogenic traits (4, 5).

Complex diseases are generally polygenic, with many genes contributing to their variation. Concurrently, many genes are pleiotropic, affecting multiple independent traits (6). Phenome-wide association studies (PheWAS) aim to complement genome-wide association studies (GWAS) by studying pleiotropic effects of a genetic variant on a broad range of traits. Many PheWAS databases aggregate individual associations between a genetic variant and a trait, including GeneATLAS [778 traits from the UK Biobank (http://geneatlas.roslin.ed.ac.uk/trait/)] (7), GWAS Atlas [4155 GWAS examined over 2965 traits (https://atlas.ctglab.nl/)] (8), and PhenoScanner [more than 5000 datasets examined over 100 traits (www.phenoscanner.medschl.cam.ac.uk/)] (9). Other PheWAS databases are constructed on the basis of polygenic scores estimated from multiple variants per GWAS locus (10), latent factors underlying groups of variants (11), or variants overlapping between GWAS and PheWAS catalogs (12). By building associations directly from variants (most of which are noncoding), most PheWAS results lack mechanistic insight that can support proposals for translational experiments. Genes are primarily assigned to PheWAS results by genomic proximity to significant variants, which can be misleading (13). Some studies have attempted to improve translation of PheWAS results using gene sets and pathways (14) or networks of PheWAS variants and diseases (15, 16). However, these studies rely on the same variant-trait associations on which PheWAS are built and fall short of prioritizing likely actionable targets.

Integration of genomic, transcriptomic, and other regulatory and functional information offers crucial justification for therapeutic target identification efforts, such as drug development (17). Translational researchers also need access to this integrated information in a comprehensive platform that allows convenient investigation of complex relationships across multiple genes and traits.

To meet this need, we present PhenomeXcan, a massive integrated resource of gene-trait associations to facilitate and support translational hypotheses. Predicted transcriptome association methods test the mediating role of gene expression variation in complex traits and organize variant-trait associations into gene-trait associations supported by functional information (1820). These methods can describe direction of gene effects on traits, supporting how up- or down-regulation may link to clinical presentations or therapeutic effects. We trained transcriptome-wide gene expression models for 49 tissues using the latest Genotype-Tissue Expression (GTEx; v8) data (21) and tested the predicted effects of 8.87 million variants across 22,515 genes and 4091 traits using an adaptation of the PrediXcan method (18), Summary-MultiXcan (S-MultiXcan), that uses summary statistics and aggregates results across tissues (22). We then prioritized genes with likely causal contributions to traits using colocalization analysis (23). To make computation feasible given the large scale of data in this study, we developed fastENLOC (fast enrichment estimation aided colocalization analysis), a novel Bayesian hierarchical colocalization method. We showed separately that this approach of combining an association and a colocalization method performs better than each method individually at prioritizing causal genes and is comparable to baselines such as the nearest gene while incorporating greater biological context (24). We demonstrate results from integrating this tool with a deeply annotated gene-trait dataset to identify associations; this integration can be performed in any deeply annotated database of genes and traits, including molecular or biological traits rather than disease traits. PhenomeXcan is the first massive gene-based (rather than variant-based) trait association resource. Our approach not only uses state-of-the-art techniques available to biologically prioritize genes with possible contributions to traits but also presents information regarding pleiotropy and polygenicity across all human genes in an accessible way for researchers. Below, we provide several examples that showcase the translational relevance and discovery potential that PhenomeXcan offers.

We built a massive gene-to-phenome association resource that integrates GWAS results with gene expression and regulation data. We ran a version of PrediXcan (18), S-MultiXcan, designed to use summary statistics and aggregate effects across tissues (22) on publicly available GWAS. In total, we tested the predicted effects of 8.87 million variants across 22,515 genes and 4091 traits from publicly available GWAS summary statistics (see Supplementary Materials). Traits incorporate binary, categorical, or continuous data types and range from basic anthropometric measurements to clinical traits and biochemical markers. We inferred association statistics (P values and Z scores) between predicted gene-expression variation and traits using optimal prediction models trained using 49 tissues from GTEx v8 (21, 25). LD (linkage disequilibrium) contamination due to proximity between expression quantitative trait loci (eQTLs) and causal variants can produce noncausal, spurious gene-trait associations (21, 24). We therefore first performed Bayesian fine mapping using the DAP-1/fgwas algorithm in TORUS (26, 27). We then calculated the posterior probability of colocalization between GWAS loci and cis-eQTLs to prioritize possible causal genes via fastENLOC, a newly developed Bayesian hierarchical method that uses precomputed signal clusters constructed from fine mapping of eQTL and GWAS data to speed up colocalization calculations (see Supplementary Materials). The result is a matrix of 4091 traits and 22,515 genes in which each intersection contains a PrediXcan P value aggregated across 49 tissues and refined by a locus regional colocalization probability (locus RCP) (Fig. 1). While a given colocalization threshold may be arbitrary, to minimize false negatives given the conservative nature of colocalization approaches (24), we defined putative causal gene contributors as those genes with locus RCP >0.1.

Blue areas highlight methods that we performed for this project, with fastENLOC being a novel colocalization method developed in the context of PhenomeXcan development. We developed PhenomeXcan by integrating GWAS summary statistics with GTEx v8 using PrediXcan methodology and then performing fine mapping and colocalization to identify the most likely causal genes for a given trait. PhenomeXcan is a massive resource containing PrediXcan P values across 4091 traits and 22,515 genes, aggregated across 49 tissues and refined by locus RCP. SNP, single-nucleotide polymorphism; b, effect size; snpn refers to the nth SNP in the list, after SNP 1, SNP 2, ..., SNP N.

We found 72,994 significant associations (Bonferroni-corrected P value of <5.49 1010) across the entire genome/phenome space, where 22,219 (30.5%) had locus RCP >0.1 (table S1). We constructed a quantile-quantile plot of all associations, which did not show evidence of systematic inflation (fig. S1). These associations represent numerous potential targets for translational studies with biological support.

We evaluated PhenomeXcans performance using three different independent validation approaches. For the first validation, we compared significant results from PhenomeXcan to significant results from the PheWAS catalog, which combines the NHGRI-EBI (National Human Genome Research Institute - European Bioinformatics Institute) GWAS catalog (as of 4/17/2012) and Vanderbilt Universitys electronic health record to establish unique associations between 3144 variants and 1358 traits (https://phewascatalog.org/phewas) (12, 28). These gene-trait pairs, mapped to GWAS loci mostly by proximity, are likely enriched in but do not necessarily represent causal genes. We mapped traits from PhenomeXcan to those in the PheWAS catalog using the Human Phenotype Ontology (HPO) (29). After filtering for genes included in both PhenomeXcan and the PheWAS catalog, we tested 2202 gene-trait associations. At a nominal threshold (P < 0.01), 1005 PhenomeXcan gene-trait associations replicated with matched traits in the PheWAS catalog [area under the curve (AUC) = 0.62; Fig. 2A]. Considering different methods of gene assignments for each GWAS locus (PheWAS: proximity, PhenomeXcan: PrediXcan and Bayesian colocalization), we further evaluated our replication rate using random classifiers in a precision-recall (PR) curve (Fig. 2B) and found significant replicability between PhenomeXcan and PheWAS results (empirical P value of <0.01).

MultiXcan refers to the version of PrediXcan designed to take GWAS summary statistics and aggregate results across tissues (22). (A and B) Receiver operating curve (ROC) and PR curve of PrediXcan significance scores (blue) and fastENLOC (orange) to predict PheWAS catalog gene-trait associations. (C and D) ROC and PR curve of PrediXcan significance scores (blue) and fastENLOC (orange) to predict OMIM catalog gene-trait associations. AP, average precision. The predictive ability of both PrediXcan and fastENLOC demonstrate the statistical validity of PhenomeXcan associations. The maximum fastENLOC colocalization probability across tissues was used for all figures.

For the second validation, we identified a set of high-confidence gene-trait associations using the Online Mendelian Inheritance in Man (OMIM) catalog (30). We previously demonstrated that integrated analysis using PrediXcan (18) and colocalization (23) successfully predicts OMIM genes for matched traits (24). We mapped 107 traits from PhenomeXcan to those in OMIM using the HPO (29) and curated a list of 7809 gene-trait associations with support for causality. We compared gene-trait associations from this standard near GWAS loci (table S2) and found that both PrediXcan and fastENLOC in PhenomeXcan successfully predict OMIM genes (AUC = 0.64; Fig. 2C). The combination of PrediXcan and fastENLOC improves precision in this dataset (fig. S2). The limited precision seen here is expected in the setting of genes, such as those in OMIM, with large effects and rare variants (Fig. 2D). The conservative nature of colocalization analysis can lead to increased false negatives (24), which may contribute to decreased performance of fastENLOC.

For the third validation approach, we applied a medium-throughput approach to examine a disease trait with multiple functionally established gene-trait associations. The Accelerating Medicines Partnership: Type 2 Diabetes (AMP T2D) Knowledge Portal curates a list of genes with causal, strong, moderate, possible, and weak associations to type 2 diabetes based on functional data (table S3) (31). We tested the ability of both PrediXcan and fastENLOC in PhenomeXcan to successfully predict the causal, strong, and moderate genes curated by AMP T2D Knowledge Portal paired with seven UK Biobank traits: type 2 diabetes, type 2 diabetes without complications, type 2 diabetes with ophthalmic complications, type 2 diabetes with peripheral circulatory complications, Self-reported type 2 diabetes, Non-insulin dependent diabetes mellitus, and Unspecified diabetes mellitus. PhenomeXcan successfully predicted the causal gene list for type 2 diabetes (AUC = 0.67; Fig. 3, A and B).

MultiXcan refers to the version of PrediXcan designed to take GWAS summary statistics and aggregate results across tissues (22). (A and B) ROC and PR curve of PrediXcan significance scores (blue) and fastENLOC (orange) to predict significant associations between a curated gene list from the AMP T2D Knowledge Portal and type 2 diabetes traits. PrediXcan and fastENLOC, particularly PrediXcan, demonstrate predictive ability in the setting of a disease trait with 20 genes with causal, strong, and moderate evidence and present in LD blocks with GWAS signal. The maximum fastENLOC colocalization probability across tissues was used for all figures.

PhenomeXcan provides a resource for hypothesis generation using gene-trait associations, with more than 22,000 potentially causal associations (P < 5.49 1010, locus RCP > 0.1; table S1). As case studies, we discuss associations identified on the basis of trait [Morning/evening person (chronotype)] and gene (TPO).

We reviewed the 15 most significant genes associated with Morning/evening person (chronotype) (a UK Biobank trait) based on PrediXcan P values across the 49 tissues and locus RCP >0.1 (table S4). Three of 15 genes had not been previously reported in any GWAS involving UK Biobank participants related to sleep or chronotype: VIP, RP11-220I1.5, and RASL10B. Notably, a variant associated with VIP (P = 1.812 1017, locus RCP = 0.26) is discussed in a GWAS of 89,283 individuals from the 23andMe cohort who self-report as a morning person (rs9479402 near VIP, 23andMe GWAS P = 3.9 1011) (32). VIP produces vasoactive intestinal peptide, a neurotransmitter in the suprachiasmatic nucleus associated with synchronization of circadian rhythms to light cycles (33). The long noncoding RNA RP11-220I1.5 (P = 6.427 1011, locus RCP = 0.20) and the gene RASL10B (P = 1.098 1010, locus RCP = 0.15) have not been previously reported in any GWAS or functional/clinical studies associated with this trait. RASL10B produces a 23-kDa guanosine triphosphatase protein that demonstrates overexpression in the basal ganglia in GTEx (21), potentially representing a novel association. Besides VIP, three other genes in this set had clinical/functional studies associated with sleep or chronotype in PubMed: RAS4B, CLN5, and FBXL3. RAS4B (P = 1.660 1019, locus RCP = 0.63) was linked to a transcriptional network regulated by LHX1 involved in circadian control (34). CLN5 (P = 5.248 1018, locus RCP = 0.34) mutations are associated with neuronal ceroid lipofuscinosis, which can manifest with sleep-specific dysfunction (35). FBXL3 (P = 1.54 1016, locus RCP = 0.35) assists with turnover of the CRY protein through direct interaction to regulate circadian rhythms (36). Our results were also significant for the overlapping genes PER3 (P = 1.65 1017, locus RCP = 0.08) and VAMP3 (P = 7.317 1018, locus RCP = 0.63). PER3 is one of the Period genes characterized as part of the circadian clock and described in numerous functional studies, animal models, and human polymorphism association studies (37), whereas VAMP3 has little research in chronotype or sleep. VAMP3, in this instance, is likely to be a false positive in the setting of the overlapping gene structure and coregulation.

We also reviewed PhenomeXcans performance in associating chronotype traits with well-established circadian rhythm genes that have been identified through functional approaches. In mammals, the transcription factors CLOCK and BMAL1 influence the expression of the Period genes (PER1 and PER2) and the Cryptochrome genes (CRY1 and CRY2). PER3 stabilizes PER1 and PER2 (38). NPAS2 acts as a paralog to CLOCK. All genes demonstrated nominal significance (P < 0.01) with at least one chronotype trait in PhenomeXcan except CRY2 (strongest association P = 0.11) and CLOCK (strongest association P = 0.08). Except for PER1 (locus RCP = 0.24) and NPAS2 (locus RCP = 0.12), all genes showed locus RCP <0.1.

PhenomeXcan, to our knowledge, is one of the first hypothesis-generating tools to provide unbiased links between a trait and associated genes for the researchers evaluation. In conjunction with rich knowledge obtained from functional studies, PhenomeXcan can be used to generate or support subsequent translational efforts.

We next evaluate PhenomeXcan as a platform to study novel and underreported gene-trait associations. Thyroid peroxidase (TPO) encodes a membrane-bound glycoprotein that plays a crucial role in thyroid gland function (39). The strongest associations in PhenomeXcan support the known role of TPO in thyroid hormone production: Self-reported hypothyroidism or myxedema (P = 1.40 1014, locus RCP = 0.99) and Treatment with levothyroxine (P = 1.54 1010, locus RCP = 0.99). Hypothyroidism has been clinically linked to increased respiratory symptoms. Although the mechanism for this is not well understood (40), our results suggest that these could be explained by common genetic factors; Treatment with salmeterol (a medication used to treat lung disease such as asthma or chronic obstructive pulmonary disease) showed moderate associations with TPO in PhenomeXcan (P = 7.45 105, locus RCP < 0.1). TPO is also contained in the National Institutes of Health (NIH) Biosystems Pathways for the development of pulmonary dendritic cells (41). Time to complete round (drawing as a measure of cognitive function) showed another moderate association in PhenomeXcan (P = 1.19 104, locus RCP < 0.1). Thyroid function has been clinically linked to time to draw a clock as a form of cognitive measurement (42). Other trait associations identified in PhenomeXcan with TPO include Single major depression episode (P = 2.48 104, locus RCP < 0.1) and Treatment with doxazosin (a medication used in the United Kingdom for hypertension) (P = 8.80 104, locus RCP < 0.1), both of which have demonstrated clinical association with thyroid abnormalities (43, 44). When reviewing thyroid dysfunction traits in PhenomeXcan, TPO is among the 35 most significantly associated genes, with the others primarily involved in immune regulation or the hypothalamic-pituitary-thyroid axis. To our knowledge, depression and doxazosin use have not been deeply investigated with TPO previously, highlighting how PhenomeXcan may be useful in expanding gene-trait association studies and functional studies through consideration of independent traits associated with a given gene.

PhenomeXcan allows more complex investigation of associated genes and traits beyond individual queries. As an example, to study genes associated with white blood cell count, we can cluster related genes and traits. Starting from the trait Lymphocyte percentage, the top associated genes include PSMD3, CD69, KLF2, CXCL2, CREB5, CXCL3, ZFP36L2, JAZF1, NCOR1, and TET2. These genes represent pathways associated with chemokine and interleukin signaling as well as peptide ligand binding but are not specific to one particular pathway or genomic location (45). We can assess these genes associations with white blood cell traits (neutrophil count/percentage, lymphocyte count/percentage, eosinophil count/percentage, and monocyte and basophil percentages) and infer some understanding of their causal mechanism. PSMD3, for instance, demonstrates stronger associations with neutrophil and lymphocyte traits (mean P < 1 1030, mean locus RCP = 0.50), whereas ZFP36L2 demonstrates consistent associations across white blood cell, platelets, and red blood cell traits (mean P < 1.54 1024, mean locus RCP = 0.36) (Fig. 4). Disruption of ZFP36L2 results in defective hematopoiesis in mice (46), whereas PSMD3 has been identified in GWAS related to white blood cell count and inflammatory states (47). Clusters of associated genes and traits can support more robust translational hypotheses through similarities in associations and generate more nuanced experimental designs through differences between associations.

Z scores are derived from PrediXcan P values, with the ceiling of association (dark blue) 7. In this heatmap, we demonstrate the associations between the genes PSMD3, CD69, KLF2, CXCL2, CREB5, CXCL3, ZFP36L2, JAZF1, NCOR1, and TET2 and the white blood cell traits neutrophil count and neutrophil percentage, lymphocyte count and lymphocyte percentage, eosinophil count and eosinophil percentage, monocyte percentage and basophil percentage. Platelet count and mean corpuscular volume (for red blood cells) serve as alternate blood traits. ZFP36L2 has consistent associations across platelets and red blood cells relative to other genes. Accordingly, functional studies demonstrate that ZFP36L2 plays a role in hematopoiesis, whereas studies support the other genes involvement in inflammation-related pathways or diseases. These types of clusters can support hypotheses and experimental designs regarding the mechanisms through which genes contribute to traits.

PhenomeXcan can also be integrated with any gene-trait databases to study pleiotropically linked traits and shared associated genes. We integrated PhenomeXcan with ClinVar, a publicly available archive of rare human diseases and associated genes (including OMIM) and one of the most widely used gene-trait databases in the clinical setting (48). We examined the associations between the 4091 GWAS-derived traits in PhenomeXcan and 5094 ClinVar diseases by (i) calculating PrediXcan Z scores for every gene-trait association in PhenomeXcan and (ii) for each PhenomeXcan/ClinVar trait pair, we computed the average squared PrediXcan Z score considering the genes reported in the ClinVar trait (see Materials and Methods). We then created a matrix of PhenomeXcan traits by ClinVar traits with mean squared Z scores (Fig. 5, A and B), where peaks represent shared genes. We defined significant associations between traits as those with Z score >6; this represents the equivalent of a Bonferroni-adjusted P value of 0.05 based on our map of the distribution of Z scores (fig. S3).

(A) Schematic depicting the development of PhenomeXcan ClinVar. For each PhenomeXcan/ClinVar trait pair, we computed the average squared PrediXcan Z score considering the genes reported in the ClinVar trait. (B) Heatmap visualizing the overall structure of associations in PhenomeXcan ClinVar. Darker blue represents stronger association. Again, complex clusters of intertrait associations can be identified to link common traits and rare diseases. Queries for traits or genes of interest can be submitted through a web application at phenomexcan.org. (C) Heatmap demonstrating an example linked traits in PhenomeXcan (rows) and ClinVar (columns) using the association between Parkinsons disease and red blood cell traits. We see the strongest associations between mean corpuscular volume, mean reticulocyte volume, and mean spherical red cell volume and Parkinson disease 15. In ClinVar, each variant of Parkinsons disease linked to a different gene is listed under a different number, making it expected that associations to other forms of Parkinsons disease are not as strong.

As an example, we found links between the ClinVar trait Parkinson disease 15 and the following traits: mean corpuscular volume, mean reticulocyte volume, and mean spherical red cell volume (Fig. 5C). The gene linked to Parkinson disease 15 in ClinVar is FBXO7. The mean Z score across eight red blood cell traits was 21.14; the mean locus RCP was 0.84 with P values all <1 1030. FBXO7 plays a role in the ubiquitin system; its entry in ClinVar is associated with an autosomal recessive, juvenile-onset form of Parkinsons disease (49). Three GWAS [the HaemGen consortium, eMERGE (Electronic Medical Records and Genomics), and van der Harst et al.] link FBXO7 with red blood cell attributes including mean corpuscular volume and mean cell hemoglobin (5052). At least one mouse model describes defective erythropoiesis and red blood cell changes due to induced mutations in FBXO7 (53). Through PhenomeXcan, we found a pleiotropic relationship between Parkinsons disease and red blood cell traits mediated through FBXO7 that has not been studied in humans. The nearest adjacent genes, SYN3 and BPIFC, are unlikely to be separately affecting red blood cells; they have no published association to red blood cells and demonstrate mean locus RCPs with red blood cell traits in PhenomeXcan of 0.55 and 0, respectively. Validating this finding, one mouse model specifically studies the pleiotropy of FBXO7 on both parkinsonism and red blood cell traits (54). This case study demonstrates how this powerful variation on PhenomeXcan can substantially improve translational hypothesis generation by supporting genetic links between associated rare diseases and common traits across research platforms.

PhenomeXcan offers direct translational applicability, providing genomic evidence to support therapeutic targets and associated side effects. As an example, PCSK9 is a genetically supported, clinically validated target for cardiac prevention through inhibition of its binding to the low-density lipoprotein (LDL) receptor and reduction of blood LDL cholesterol levels (55). We can study the cluster of genes and traits produced by PCSK9 in PhenomeXcan for relevant information about this target. Most of the traits with strongest associations to PCSK9 relate to diagnosis and treatment of elevated cholesterol or atherosclerosis, including familial heart disease. Because inherited PCSK9 variation is associated with increased likelihood of type 2 diabetes, there was concern that PCSK9 therapies could elevate risk to type 2 diabetes. The inhibiting drugs therefore required large substudies from clinical trials to confirm no association with worse diabetes (56, 57). While not at genome-wide significance, PCSK9 has a negative association with type 1 diabetes in PhenomeXcan (P = 8.2 104, locus RCP < 0.1), consistent with the clinical concern that down-regulation of the gene could lead to increased diabetes risk. We recognize that type 1 and type 2 diabetes have different clinical etiologies. For the purpose of drug development, though, assessing PCSK9 in PhenomeXcan produces both its primary target (blood cholesterol levels as related to atherosclerosis) and, through independently identified traits, potential adverse effects via diabetes. The most commonly represented genes associated with the strongest traits for PCSK9 include APOE, LDLR, APOB, PSRC1, CELSR2, SORT1, ABCG8, ABCG5, and HMGCOR. Unsurprisingly, all of these genes have all been implicated in genetic susceptibility to hypercholesterolemia (some, such as SORT1, may be the primary causative gene in their pathway) (58). Examining potential targets in PhenomeXcan could not only help anticipate side effects via independent traits but also identify related gene networks or alternative targets with therapeutic relevance.

Here, we introduce PhenomeXcan, an innovative, powerful resource that makes comprehensive gene-trait associations easily accessible for hypothesis generation. Using PrediXcan allows us to derive gene-based associations with traits in context by integrating GWAS summary statistics with transcriptome-wide predicted expression and regulatory or functional information. We previously demonstrated that integrated analysis using PrediXcan and colocalization improves precision and power for target gene identification (24). To build PhenomeXcan, we also develop a novel, rapid colocalization method, fastENLOC, that could handle data at this scale (4091 traits 22,515 genes 49 tissues) (see Materials and Methods). PhenomeXcan implements the best practices derived from applying GTEx v8 (21, 59) to biologically prioritize genes with possible causal contribution to a given trait.

PhenomeXcans flexible structure and adaptability allow translational researchers to easily explore clinically relevant questions. The resource can be queried by gene or trait and allows identification of novel and underrepresented associations. It offers exploration of polygenicity and pleiotropy dimensions by allowing for queries across multiple genes and traits. It can also be integrated with other gene-trait datasets to explore linked traits and report common associated genes. We offer ClinVar as an example, but any deeply annotated database of genes and traits, including molecular or biological traits, may be integrated in this manner. Other possible translational uses of PhenomeXcan include biomarker exploration, identification of clinically relevant disease modifiers, and polygenic score building (using genes associated with queried traits), as well as novel directions for basic science collaborations and clinical study of linked traits (using traits associated with queried genes).

We note some caveats. Diseases with variability not related to changes in gene expression (e.g., epigenetic regulation or traits with important environmental contributions) are not expected to be captured well by this method. With just expression levels, this resource is a starting point, and additional molecular traits, such as microRNA levels, protein levels, and alternative splicing structures, are a priority for us to incorporate as data become available in sufficiently large sample sizes. Our model also better captures common overall genetic contributors rather than genes identified from rare variants. We do note that our validation standards tend to favor larger-effect genes with monogenic etiology, while the PhenomeXcan association method itself is less biased. Regulatory pleiotropy is widespread across the genome (21). In our chronotype example, VAMP3 and PER3 demonstrate regulatory pleiotropy. VAMP3, from our findings associated with chronotype, is likely to be a false positive because of coregulation of both genes by causal variants. With that degree of proximity, large-scale tools are not able to well distinguish causal genes, exemplifying the need for additional functional data to determine the causality of the gene (21). We discuss this finding to acknowledge how PhenomeXcan encounters this phenomenon and show the benefit of performing these associations across all human genes. We offer colocalization as a possible means of prioritizing causal variants, but significance of association, colocalization, and coregulatory sites must be taken into account in our results. Work from large-scale statistical genetics tools, such as PhenomeXcan, and Mendelian genetics and functional studies must then be combined to best understand the breadth of genetic contributors to complex traits. We have favored a locus RCP threshold of 0.1 to limit false negatives related to colocalization. Poor RCP (locus RCP ~ 0) may reflect a lack of sufficient evidence with available data, particularly for understudied genes, rather than true lack of causality. We therefore reported traits in this paper that had a locus RCP <0.1 but had functional support for potential association. Similarly, the genome-wide threshold of significance is conservative, and we discuss associations with functional support even with less significant P values. GWAS summary statistics used in this project were for participants and patients of European ancestry. Improving the applicability of this type of work to global populations remains of paramount importance throughout genetic medicine, and we will continue to integrate more GWAS summary statistics from broader consortia.

Resources that translate biologically relevant genomic and transcriptomic information into gene-trait associations are already critical for hypothesis generation and clinically relevant research (60). We offer PhenomeXcan, an integrated mapping for the function of every human gene, as a publicly available resource to advance the investigation of complex human diseases by improving the accessibility of relevant links between the entire genome and the phenome.

S-MultiXcan is a method in the PrediXcan family (18) that associates genes and traits by testing the mediating role of gene expression variation in complex traits but (i) requires only GWAS summary statistics and (ii) uses multivariate regression to combine expression information across tissues (22). First, linear prediction models of genotype in the vicinity of the gene to expression are trained in reference transcriptome datasets such as the GTEx project (21). Second, predicted expression based on actual genetic variation is correlated to the trait of interest to produce a gene-level association result for each tissue. In S-MultiXcan, the predicted expression is a multivariate regression of expression across multiple tissues. To avoid collinearity issues and numerical instability, the model decomposes the predicted expression matrix into principal components and keeps only the eigenvectors of non-negligible variance. We considered a principal components analysis regularization threshold of 30 to be a conservative choice. This approach improves detection of associations relative to use of one tissue type alone and offers a reduced false-negative rate relative to a Bonferroni correction. We used optimal prediction models based on the number and proportion of colocalized gene-level associations (24). These models select features based on fine mapping (25) and weights using eQTL effect sizes smoothed across tissues using mashr (59). The result of this approach is a genome-wide gene-trait association list for a given trait and GWAS summary statistic set.

Bayesian fine mapping was performed using TORUS (27). We estimated probabilities of colocalization between GWAS and cis-eQTL signals using Bayesian RCP, as described in the ENLOC (enrichment estimation aided colocalization analysis) methodology (23). For this particular study, given the large scale of the data, we developed a novel implementation, entitled fastENLOC. fastENLOC was applied for all trait-tissue pairs, and the maximum colocalization probability across all tissues was used, thus obtaining a single RCP value for each gene-trait pair. This aggregation of RCP values across tissues allowed us to combine results from fastENLOC and S-MultiXcan.

We evaluated the accuracy of gene-trait associations in PhenomeXcan by using two different gene-trait association datasets (PheWAS catalog and OMIM) as well as genes linked with functional evidence with type 2 diabetes (T2D) according to the AMP T2D. We then derived the receiver operating characteristic curve (ROC) and PR curves for PrediXcan and fastENLOC independently and a combination of both.

We mapped traits from PhenomeXcan to those in either PheWAS catalog (28) or OMIM (30) by using the HPO (29) and the GWAS catalog as intermediates. For traits in the PheWAS catalog, we tested 2202 gene-trait associations that could be mapped in both PhenomeXcan and the PheWAS catalog, from a total 19,119 gene-traits associations consisting of all genes present in an LD block with GWAS signal. For the OMIM traits, we developed a standard (table S2) of 7809 high-confidence gene-trait associations that could be used to measure the performance of PhenomeXcan, of which 125 presented in the LD block of GWAS signal so those were included in the analysis. This standard, as described in our recent work (24), was obtained from a curated set of trait-gene pairs from the OMIM database by mapping traits in PhenomeXcan to those in OMIM. Briefly, traits in PhenomeXcan were mapped to the closest phecode using the GWAS catalogtophecode map proposed in (28). As disease description in OMIM has been mapped to the HPO (29), we created a map from phecodes to terms in HPO, which allowed us to link our GWAS traits to OMIM disease description by using phecodes and HPO terms as intermediate steps. For each gene-trait pair considered causal in this standard, we determined whether PhenomeXcan identified that association as significant on the basis of the resulting P value. The OMIM-based standard is publicly available through R package (https://github.com/hakyimlab/silver-standard-performance).

For T2D, we obtained a list of predicted effector transcripts identified by AMP T2D and used 76 genes categorized as causal, strong, or moderate as our gold standard for evaluation (table S3). As we did for OMIM and PheWAS catalogs, 20 of these causal genes could be mapped in PhenomeXcan, from a total of 5036 genes present in an LD block with GWAS signal. We used seven traits highly related to T2D: International Classification of Diseases 10 codes E11 and E14, Self-reported type 2 diabetes (data-field 20002 in UK Biobank with code 1223), and four phenotypes manually curated by the FinnGen Consortium (type 2 diabetes without complications, type 2 diabetes with ophthalmic complications, type 2 diabetes, and type 2 diabetes with peripheral circulatory complications); then, we took the maximum Z score obtained (for MultiXcan) and the maximum RCP (for fastENLOC) across the seven T2D traits for each gene evaluated. The results are shown in Fig. 3 and fig. S2. Notice that multiple testing is not an issue, since for the performance curves, we are not using a significance threshold, but all levels are assessed in terms of the false-positive and true-positive rates.

PhenomeXcan results for case studies were included on the basis of their P values and locus RCP. We defined putative causal gene contributors as those genes with P values less than 5.49 1010 and locus RCP >0.1. Given these conservative measures, however, we did discuss associations that were less significant or had a lower locus RCP with functional evidence. We used the NHGRI-EBI GWAS catalog (21 October 2019) to identify GWAS results both using the UK Biobank (given the predominance of this dataset in PhenomeXcan) and other datasets. We performed systematic literature searches on PubMed using the gene name alone, with the specific trait category and trait name to identify functional studies relevant to a trait of interest.

We examined links between 4091 PhenomeXcan traits and 5094 ClinVar traits and associated genes. ClinVar traits were excluded if they did not have known associated genes in PhenomeXcan. To compare a PhenomeXcan trait t and a ClinVar trait d, we calculated the mean squared Z scoreavg(t,d2)=1ki=1kZt,i2where k is the number of genes reported in ClinVar for trait d and Z is the Z score of gene i obtained with S-MultiXcan for trait t. We then created a matrix of PhenomeXcan traits by ClinVar traits with mean squared Z scores. We defined significant associations between traits as those with Z score >6; this represents the equivalent of a Bonferroni-adjusted P value of 0.05 based on our map of the distribution of Z scores (fig. S3).

See the rest here:
PhenomeXcan: Mapping the genome to the phenome through the transcriptome - Science Advances

We seek a new postdoc who will work within the Center of Public Health Sciences, Faculty of Medicine, University of Iceland, on the ERC funded project StressGene led by Prof Unnur Valdimarsdttir.

The main goal of the StressGene program is to study health sequels after significant life stressors or trauma and uncover sequence variants associated with stress-related psychiatric disorders and somatic conditions (e.g. cardiovascular disease) following such adversities. This research is conducted in collaboration between an extended network of researchers at (but not limited to) the University of Iceland, deCODE Genetics, and Karolinska Institutet in Sweden. The postdoc will work in close collaboration with senior colleagues at these institutions and leverage population-based register and biobank resources with the overarching goal of understanding how genes and environment act and interact to modify risk of ill health after significant life stressors or trauma. Prof Valdimarsdttirs team has long-standing experience in using Nordic health and population registers as well as longitudinal cohort studies (e.g. the SAGA cohort, Swedish Tsunami Cohort, and COVID-19 National Resilience Cohort) in research of mental disorders, especially stress-related disorders and unravelling their associations to various somatic conditions.This project builds on recent findings and prospective work aims at identifying common molecular mechanisms to stress-related disorders and various somatic diseases.

Your mission

We seek an outstanding and innovative postdoc to join our team for one year with a possible extension to two years. We are data-rich, and need a professional-level data scientist, with a solid background in biostatistics or genetic epidemiology, to maximize our understanding of the data we have. This individual should be passionately committed to furthering knowledge of psychiatric disorders and somatic conditions associated with trauma in order to improve the lives of these vulnerable populations. The successful applicant will join our

team and conduct research on the genomics of psychiatric disorders and somatic conditions associated with trauma leveraging multi-omic approaches and approaches used for complex register data.

Your profile

PhD degree in medical science such as epidemiology, biostatistics, computer science, statistics, genetics, etc. is required. Applicants who have not completed a doctorate at the end of the application period may also apply, provided that all requirements for a completed degree are met before the (intended) date of employment. This must be substantiated by the applicants main supervisor, director or equivalent. Those with PhDs in other areas but who have advanced/relevant data science skills will also be considered.

Experience in professional analysis of multiple types of modern genomic datasets, including GWAS, exome sequencing, or register-based studies are a plus.

Skills in programming (e.g., R, Python, SQL, Unix/Linux), use of standard software packages (e.g., PLINK, GATK), flexibly manipulating large datasets, bioinformatic integration, and pathway analysis.

Knowledge of complex trait genomics.

Good skills in teamwork in scientific work as well as independent, organized and solution-oriented work methods.

Excellent oral and written communication skills in English are required, along with experience with scientific writing.

What do we offer?

We are a friendly, creative, international and inspiring environment full of expertise and curiosity.

The University of Iceland is a progressive educational and scientific institution in the heart of Reykjavk, the capital of Iceland. A modern, diversified and rapidly developing institution, it is by far the largest teaching and research institution in Iceland ranked in the top 300 in clinical medicine and public health on the Times Higher Education Ranking for the past 5 years. Located in the deCODE Genetics Building, Sturlugata 8 Reykjavik, Center of Public Health Sciences (CPHS) is the Universitys research institution in population sciences and organizes interdisciplinary academic graduate programs in public health sciences, including in epidemiology and biostatistics. CPHS includes five professors, two associated professors and 5 research fellows on a post-doctoral level, 2-3 research administrators and 12 doctoral students.CPHS research activity is funded by multiple national and international grants including the ERC consolidator-grant (awarded to Prof. Valdimarsdttir): The genetics of morbidity and survival in response to significant life stressors (StressGene).

Please check out our latest cohort initiatives:

THE SAGA COHORT

ABOUT

Application

Please apply through the University of Iceland website, vacancies

Deadline for application is 21st of September 2020 and the starting date is according to an agreement.

An employment application must contain the following documents in English or Icelandic:

i. A complete resum, including date of the thesis defense, title of the thesis, previous academic

positions, academic title, current position, academic distinctions, and committee work

ii. Certified copy of diplomas

iii.Letter of recommendation

iv. A statement in which the interest in the project is described and discusses what the applicant can contribute to it.

Applicants will be asked to describe past examples of having developed structured approaches to solving unanticipated and complex problems.

Salary is according to official agreement between collective wage and salary agreement between the Minister of Finance and the relevant union.

All applications will be answered and applicants will be notified of the employment decision when a decision has been made. Applications will be valid for six months from the end of the application deadline.

Further information

For further information, please contact Unnur Anna Valdimarsdttir (unnurav@hi.is) or Dra R. lafsdttir (dro@hi.is).

Appointments to positions at the University of Iceland are made in consideration of the Equal Rights Policy of the University of Iceland.

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Postdoctoral Researcher in Psychiatric- and Genetic Epidemiology, - Nature.com

PLEASANTON, Calif., Sept. 15, 2020 (GLOBE NEWSWIRE) -- 10x Genomics (Nasdaq: TXG) today announced it has begun shipping its Chromium Single Cell Multiome ATAC + Gene Expression solution to customers, marking the first commercial release of a product capable of simultaneously profiling the epigenome and transcriptome from the same single cell. This multi-omic approach provides customers with the ability to link a cells epigenetic program to its transcriptional output, enabling a better understanding of cell functionality and bypassing the need to infer relationships through computer simulations.

This is one of our most ambitious undertakings at the company, said Ben Hindson, co-founder and Chief Scientific Officer of 10x Genomics. By introducing the first solution that captures ATAC and gene expression simultaneously, researchers can gain even more clarity by combining two already powerful methods to profile biological systems at single cell resolution simultaneously for the first time.

The new solution builds on an array of new products launched by the company this year for both its Chromium platform for single cell analysis as well as its Visium platform for spatial genomics. Early customers already working with Chromium Single Cell Multiome ATAC + Gene Expression include Stanford University School of Medicine, Icahn School of Medicine at Mt. Sinai and Spains Centro Nacional de Anlisis Genmico.

My lab is interested in understanding why some immune cell types fail to fight the cancer, said Dr. Ansuman Satpathy, Assistant Professor of Pathology, Stanford University School of Medicine. We plan to use 10x Genomics' new assay to understand the epigenetic and transcriptional regulation of immune cell dysfunction directly in patient samples, and to use this information to precisely engineer more effective immunotherapies in the future.

Until now, we have relied on computational prediction to match a cell's epigenome to a single-cell gene expression profile, said Dr. Holger Heyn, leader of the single cell genomics team at Spains Centro Nacional de Anlisis Genmico that is working on delineating the dynamics underlying B-cell differentiation and activation. 10x Genomics new multiome assay will allow us to directly measure what before could only be predicted, and offers a new gold standard that will confirm how accurate these predictions had been.

"With this new technology, we can better understand the mechanisms affected by the non-coding risk genetic variation across a wide range of neuropsychiatric diseases, including Alzheimers, Parkinsons, Schizophrenia, bipolar disorder and major depression, along with different severity of neuropathology and clinical symptomatology," added Dr. Panagiotis Roussos, Associate Professor of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai.

By using Chromium Single Cell Multiome ATAC + Gene Expression, researchers can:

Chromium Single Cell Multiome ATAC + Gene Expression is shipping to customers. To learn more, visit https://www.10xgenomics.com/products/single-cell-multiome-atac-plus-gene-expression.

About 10x Genomics10x Genomics is a life science technology company building products to interrogate, understand and master biology to advance human health. The companys integrated solutions include instruments, consumables and software for analyzing biological systems at a resolution and scale that matches the complexity of biology. 10x Genomics products have been adopted by researchers around the world including 97 of the top 100 global research institutions and 19 of the top 20 global pharmaceutical companies, and have been cited in over 1,500 research papers on discoveries ranging from oncology to immunology and neuroscience. The companys patent portfolio comprises more than 775 issued patents and patent applications.

Forward Looking StatementsThis press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995 as contained in Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. Forward-looking statements generally can be identified by the use of forward-looking terminology such as may, will, should, expect, plan, anticipate, could, intend, target, project contemplate, believe, estimate, predict, potential or continue or the negatives of these terms or variations of them or similar terminology. These forward-looking statements include statements regarding 10x Genomics, Inc.s partnership activities, which involve risks and uncertainties that could cause 10x Genomics, Inc.s actual results to differ materially from the anticipated results and expectations expressed in these forward-looking statements. These statements are based on managements current expectations, forecasts, beliefs, assumptions and information currently available to management, and actual outcomes and results could differ materially from these statements due to a number of factors. These and additional risks and uncertainties that could affect 10x Genomics, Inc.s financial and operating results and cause actual results to differ materially from those indicated by the forward-looking statements made in this press release include those discussed under the captions "Risk Factors" and "Management's Discussion and Analysis of Financial Condition and Results of Operations" and elsewhere in the documents 10x Genomics, Inc. files with the Securities and Exchange Commission from time to time. The forward-looking statements in this press release are based on information available to 10x Genomics, Inc. as of the date hereof, and 10x Genomics, Inc. disclaims any obligation to update any forward-looking statements provided to reflect any change in its expectations or any change in events, conditions, or circumstances on which any such statement is based, except as required by law. These forward-looking statements should not be relied upon as representing 10x Genomics, Inc.s views as of any date subsequent to the date of this press release.

Disclosure Information10x Genomics uses filings with the Securities and Exchange Commission, its website (www.10xgenomics.com), press releases, public conference calls, public webcasts and its social media accounts as means of disclosing material non-public information and for complying with its disclosure obligations under Regulation FD.

ContactsMedia:media@10xgenomics.comInvestors:investors@10xgenomics.com

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10x Genomics First to Market With Product to Simultaneously Capture Epigenome and Transcriptome - GlobeNewswire

DENVER, Sept. 15, 2020 (GLOBE NEWSWIRE) -- Mydecine Innovations Group Inc. (CSE:MYCO) (OTC:MYCOF) (FSE:0NFA) ("Mydecine" or the "Company"), today announced the Company has formed a special committee to evaluate a number of options to increase shareholders value.

Topics that the special committee will discuss include, but limited to, a potential spin out of certain company assets. Currently, the company owns and operates a number of growing US assets in the THC-cannabis and hemp-CBD space, along with distribution, that are being evaluated and assessed as potential spin out options with respect to the Mydecine's non-fungi related assets. Current shareholders would receive automatic shares of the SpinCo.

We are constantly looking at ways to increase our shareholder value. Our company has grown at an incredible rate and is quickly establishing itself as a leader in the functional mushroom and psychedelic medicine space, said Mydecine Chief Executive Officer, Joshua Bartch. With that said, the company has a number of highly valuable assets that could potentially create larger shareholder value if they were spun out into a more focused stand-alone vehicle. We are currently evaluating a number of potential options and partners to accomplish this goal."

Further information will be provided as this opportunity develops.

About Mydecine Innovations Group Inc.Mydecine Innovations Group is a publicly traded life sciences parent company dedicated to the development and production of adaptive pathway medicine, natural health products and digital health solutions stemming from fungi. Mydecines experienced cross functional teams have the dynamic capabilities to oversee all areas of medicine development including synthesis, genetic research, import/export, delivery system development, clinical trial execution, through to product commercialization and distribution. By leveraging strategic partnerships with scientific, medical, military, and clinical organizations, Mydecine is positioned at the forefront of psychedelic medicine naturally derived from fungi, therapeutic solutions, and fungtional mushroom vitality products. Our portfolio of unified companies, including Mydecine Health Sciences, Mindleap Health, and NeuroPharm focus on providing innovative and effective options that can provide millions of people with a healthier quality of life.

For further information about Mydecine Innovations Group Inc., please visit the Companys profile on SEDAR at http://www.sedar.comor visit the Companys website at http://www.mydecine.com.

On behalf of the Board of Directors:Joshua Bartch, Chief Executive Officercontact@mydecineinc.com

Corp Communication:Charles Lee, Investor Relationscorp@mydecineinc.com+1 (250) 488-6728

Public Relations:Cynthia Salarizadeh, PRpr@mydecineinc.com

The Canadian Securities Exchange has neither approved nor disapproved the contents of this news release and accepts no responsibility for the adequacy or accuracy hereof. This news release contains forward-looking statements, which relate to future events or future performance and reflect managements current expectations and assumptions. Such forward-looking statements reflect managements current beliefs and are based on assumptions made by and information currently available to the Company. Readers are cautioned that these forward-looking statements are neither promises nor guarantees, and are subject to risks and uncertainties that may cause future results to differ materially from those expected including, without limitation, the availability and continuity of financing, the ability of the Company to adequately protect and enforce its intellectual property, the Company's ability to bring its products to commercial production, continued growth of the global adaptive pathway medicine, natural health products and digital health industries, and the risks presented by the highly regulated and competitive market concerning the development, production, sale and use of the Company's products. Although the Company has attempted to identify important factors that could cause actual results to differ materially from those contained in forward-looking information, there may be other factors that cause results not to be as anticipated, estimated or intended. There can be no assurance that such information will prove to be accurate, as actual results and future events could differ materially from those anticipated in such information. These forward-looking statements are made as of the date hereof and the Company does not assume any obligation to update or revise them to reflect new events or circumstances save as required under applicable securities legislation. This news release does not constitute an offer to sell securities and the Company is not soliciting an offer to buy securities in any jurisdiction in which such offer, solicitation or sale would be unlawful prior to registration or qualification under the securities laws of such jurisdiction. This news release does not constitute an offer of securities for sale in the United States. These securities have not and will not be registered under United States Securities Act of 1933, as amended, or any state securities laws and may not be offered or sold in the United States or to a U.S. Person unless so registered, or an exemption from registration is relied upon.

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Mydecine Innovations Group, Inc. to Create Special Committee for the Spin Out of US Related Assets - GlobeNewswire

Research coming out of the University of Pennsylvania School of Medicine last month demonstrated how artificial intelligence (AI) can be utilized to fight against opioid abuse. It focused on a chatbot which sent reminders to patients who underwent surgery to fix major bone fractures.

The research was published in the Journal of Medical Internet Research.

Christopher Anthony, MD, is the studys lead author and the associate director of Hip Preservation at Penn Medicine. He is also an assistant professor of Orthopaedic Surgery.

We showed that opioid medication utilization could be decreased by more than a third in an at-risk patient population by delivering psychotherapy via a chatbot, he said. While it must be tested with future investigations, we believe our findings are likely transferable to other patient populations.

Opioids are an effective treatment for pain following a severe injury, such as a broken arm or leg, but the large prescription of the drugs can lead to addiction and dependence for many users. This is what has caused the major opioid epidemic throughout the United States.

The team of researchers believe that a patient-centered approach with the use of the AI chatbot can help reduce the number of opioids taken after such surgerys, which can be a tool used against the epidemic.

Those researchers also included Edward Octavio Rojas, MD, who is a resident in Orthopaedic Surgery at the University of Iowa Hospitals & Clinics. The co-authors included: Valerie Keffala, PhD; Natalie Ann Glass, PhD; Benjamin J. Miller, MD; Mathew Hogue, MD; Michael Wiley, MD; Matthew Karam, MD; John Lawrence Marsh, MD, and Apurva Shah, MD.

The research involved 76 patients who visited a Level 1 Trauma Center at the University of Iowa Hospitals & Clinics. They were there to receive treatment for fractures that required surgery, and those patients were separated into two groups. Both groups received the same prescription for opioids to treat pain, but only one of the groups received daily text messages from the automated chatbot.

The group that received text messages could expect two per day for a period of two weeks following their procedure. The automated chatbot relied on artificial intelligence to send the messages, which went out the day after surgery. The text messages were constructed in a way to help patients focus on coping better with the medication.

The text messages, which were created by a pain psychologist specialized in pain and commitment therapy (ACT), did not directly go against the use of the medication, but they attempted to help the patients think of something other than taking a pill.

The text messages could be broken down into six core principles, : Values, Acceptance, Present Moment Awareness, Self-As-Context, Committed Action, and Diffusion.

One message under the Acceptance principle was: feelings of pain and feelings about your experience of pain are normal after surgery. Acknowledge and accept these feelings as part of the recovery process. Remember how you feel now is temporary and your healing process will continue. Call to mind pleasant feelings or thoughts you experienced today.

The results showed that the patients who did not receive the automated messages took, on average, 41 opioid pills following the surgeries, while the group who did receive the messages averaged 26. The 37 percent difference was impressive, and those who received messages also reported less overall pain two weeks after the surgery.

The automated messages were not personalized for each individual, which demonstrates success without over-personalization.

A realistic goal for this type of work is to decrease opioid utilization to as few tablets as possible, with the ultimate goal to eliminate the need for opioid medication in the setting of fracture care, Anthony said.

The study received funding by a grant from the Orthopaedic Trauma Association.

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AI Used To Identify Gene Activation Sequences and Find Disease-Causing Genes - Unite.AI

MEDIA ADVISORY

FOR IMMEDIATE RELEASE: Nature Communications: Published Monday, September 14, 2020

Newswise Corresponding Author:Yasmin Hurd, PhD, Director of The Addiction Institute of Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, and other coauthors.

Bottom Line:Herion-addicted individuals have alterations in the expression a gene called FYN - a gene known to regulate the production of Tau, a protein that is highly elevated and implicated in neurocognitive disorders like Alzheimers disease. The study emphasizes that opioid use can affect the brain in a way that might increase vulnerability of neural systems that trigger neurodegeneration later in life; however, since these changes are epigenetic (alterations in gene function that are influenced by environmental factors and not alterations of the DNA itself), they are reversible and medications that have already been developed to target FYN for neurodegenerative disorders may be studied as a novel treatment for opioid addiction.

Results:Interestingly, findings were consistent across human, animal and cell models. Through post-mortem analysis of the brains of human heroin users, the team found that, specifically in neurons, the most significantly impaired epigenetic region is related to a gene called FYN. Essentially, heroin opened up the DNA at the FYN gene, which encodes a protein called tyrosine kinase FYN, that is strongly linked to synaptic plasticity and which directly results in production of Tau. Too much Tau in the brain is associated with neurodegenerative diseases. They observed that expression and activity of tyrosine kinase FYN was also induced in rats trained to self-administer heroin and also in primary striatal neurons treated with chronic morphine in vitro. Additionally, they demonstrated that inhibition of the FYN kinase (either via pharmacological means or through genetic manipulation) reduces heroin-seeking and heroin-taking behaviors.

Why the Research Is Interesting:The findings will increase awareness about the potential impact of heroin to alter neural systems related to neurodegenerative disorders. The findings also identify FYN inhibitors as a novel therapeutic treatment for heroin use disorders.

Who: Human brains from a cohort of subjects who succumbed to heroin overdose and normal controls, translational animal model of rats trained to self-administer heroin, and primary striatal neurons treated with chronic morphine in vitro.

When: Adult animals were exposed to heroin and their brains studied.

What:They performed unbiased, cell-type-specific, genome-wide profiling of chromatin accessibility, providing insights into epigenetic regulation directly in the brains of heroin-addicted individuals. To assess the causal relationship between heroin use and FYN pathology, they studied the brains of rats trained to self-administer heroin and they hit primary striatal neurons with chronic morphine in petri dishes to examine the effect at the individual cellular level.

Study Conclusions:By scanning the entire genome of heroin users to identify whether disturbances in how genes are turned on or off exist, Mount Sinai researchers found that heroin opened up the DNA at the FYN gene. The FYN gene is known to regulate the production of Tau, a protein implicated in neurodegenerative disorder like Alzheimers disease, meaning that heroin may put users at an increased risk of neurodegenerative disease later in life. Importantly, these novel findings suggest that FYN inhibitors (which have already been developed and are being assessed for use in Alzheimers disease) may be promising therapeutic tools for heroin-use disorder.

Paper Title: Chromatin accessibility mapping of the striatum identifies tyrosine kinase FYN as a therapeutic target for heroin use disorder

Said Mount Sinai's Dr. Yasmin Hurd of the research: Drug overdoses due to opioid abuse remain at epidemic levels and continue to rise precipitously during the current pandemic, with novel treatments desperately needed. Direct molecular insights into the heroin-addicted human brain are critical to guide future therapies. Our new study findings clearly open up new lines of treatment opportunities for opioid use disorder, which could benefit and potentially save the lives of so many.

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People with Heroin Addiction Have Unique Molecular Alterations to The Brain That Resemble Brain Disturbances Seen in Neurodegenerative Disorders Like...

Image credit: NASA

Duke researchers team up with NASA to explore gene-environment interactions in astronauts

By Alexis Kessenich

Astronauts on long-duration spaceflights (LDSF) face a number of risks to their health some more obvious that others like during dynamic events such as launch and landing. But there are also lesser-known dangers, such as spaceflight-associated neuro-ocular syndrome (SANS), a spectrum of physiologic and pathologic neuro-ophthalmic changes that include swelling of the optic disc, nerve damage and vision impairment.

An astronauts susceptibility of developing SANS remains largely unknown, but a team of researchers in the Center for Applied Genomics and Precision Medicine (CAGPM) is on a mission to discover what causes the predisposition.

The Nutritional Biochemistry Laboratory at NASAs Johnson Space Center, led byScott M. Smith, completed preliminary studies and found metabolomics and geneticdifferencesin astronauts who developed SANS. This ledto a broader evaluation of genetics, so the team at CAGPM engaged to help.

Rachel MyersandRicardo Henaowill lead the studys data science efforts.

Were exploring over 80 genes associated with these metabolic pathways and around 500 different genetic variants within those genes, says Rachel Myers, lead analyst for the study. Our team will test each to see if one or groups of these variants are associated with SANS.

The study is comprised of three different cohorts: one pre- and post-spaceflight cohort and two cohorts mimicking SANS and spaceflight environments on Earth.

For the first cohort, data, such as eye measurements, were collected from astronauts before and after an LDSF. For the second cohort, data will be collected from patients at the Mayo Clinic with polycystic ovary syndrome, which shares some characteristics with SANS. The third cohort is a 30-day head-down tilt bedrest study, which mimics spaceflight environments and has been shown to inflict similar ocular changes.

Because the sample size is so small, and the number of astronauts available to participate is limited, the team will look at ways to combine different variants together and test association with the phenotypes provided by NASAs preliminary study to see if they can find what causes the predisposition.

No one has ever looked at the genetic aspect of SANS before. Its going to be really interesting to explore non-traditional approaches for genetic associations, adds Myers.

At the end of the study, the team hopes to have both an understanding of what the genetic landscape of SANS is and a sense of what approaches are going to work for further investigation.

With a small cohort, we run the risk of finding something thats completely random, says Myers, so well do additional validation after our initial findings before making recommendations.

Ultimately, were exploring gene-environment interactions, addsGeoff Ginsburg, principal investigator on the study. The astronauts exposures in space from ionizing radiation and microgravity to extreme social isolation presents an exciting scientific opportunity to understand how this intense and hostile environment interacts with our genomes.

Myers says after the study the team also hopes to have a new pipeline in the Center for processing sequencing data to get genetic variants, which will help with future studies.

A solution for these astronauts is hopefully on the horizon. But, for now, the project is one small leap for CAGPM, one giant leap for genetic research!

Association of Genetics and B Vitamin Status With the Magnitude of Optic Disc Edema During 30-Day Strict Head-Down Tilt Bed RestAstronaut ophthalmic syndromeGenotype, Bvitamin status, and androgens affect spaceflightinduced ophthalmic changesSpaceflight-related ocular changes:the potential role of genetics, and the potential ofB vitaminsas a countermeasure

Originally posted here:
Houston, We Have an Eye Problem - Duke Today

The tooth is a biological organ and consists of multiple tissues including the cementum, dentin, enamel, and pulp. Dental caries, Periodontal disease, and tooth fracture are the three main factor for tooth loss. Tooth Regeneration is the specialty concerned with the treatment of dental diseases such as a cavity, periodontal disease and fracture of the tooth. Dental caries is also known as tooth decay is the main oral health problems in most of the industrialized countries. Facial trauma also the major cause of tooth loss. Tooth loss leads to people mentally and physically disturb and it also affect the self-confidence and quality of life. Tooth regeneration is the process of individual tissue and the whole tooth development. Basically, it is the process of restoring the loss of natural teeth. Tooth regeneration is stem cell-based regenerative medical procedure which is used in stem cell biology sector and tissue engineering. There are two approaches used in the build of new whole teeth, in vivo implantation of tooth germ cells which were previously generated from stem cells and grow in vitro cells and another organotypic culture is an appropriate technique for the generation of teeth. The process of tooth regeneration imitates the natural tooth development using stem cells. In another way instead of whole teeth regeneration, Different part of the teeth regenerates such as Enamel regeneration, Dentin regeneration, Pulp regeneration, and periodontal regeneration.

Globally increasing incidence and prevalence of dental problems such as a cavity, periodontal disease, and tooth fracture are the major factors driving the growth of the Tooth Regenerations market. Innovative new techniques in Tooth regeneration such as cell homing, cell transplantation is expected to increase the acceptance of Tooth Regenerations. Tooth regeneration not only regrowth the entire tooth but also the restoration of individual components of the tooth such as dentin, cementum, enamel and dental pulp and these individual regeneration process is anticipate the boost the market growth of tooth regeneration market. Dental implantation also increases the growth of tooth regeneration market. People are very keen interested in the tooth regeneration and they are also giving more importance to the aesthetic aspects of dental products, which is expected to increase the Tooth Regenerations and dental market over the forecast period. The increasing demand for a customized Tooth Regeneration with the specifications and other dental decorative installations is the key factor anticipated to propel the demand for Tooth Regenerations worldwide.

To remain ahead of your competitors, request for a sample here@

https://www.persistencemarketresearch.com/samples/26263

The Global Tooth Regenerations market is segmented on the basis of application, Demographics, technique and by End user

Based on the Application type Tooth Regenerations market is segmented as:

Based on the Demographic Tooth Regenerations market is segmented as:

Based on the Technique, Tooth Regenerations market is segmented as:

Based on the end user Tooth Regenerations market is segmented as:

According to WHO, approx.30% the geriatric population is affected by the complete loss of teeth. Rapidly increasing Dental cavities and periodontal diseases are the major drivers in the Tooth Regenerations market. The global Tooth Regenerations market by application is expected to be dominated the market of Tooth Regenerations, out of which Enamel segment is expected to generate maximum revenue share over the forecast period. By end user, Tooth Regenerations market is expected to be dominated by dental clinics and hospitals. The manufacturers in the concerned market are focusing on manufacturing advanced products for better patient compliance and make the procedure easier. The market of tooth regeneration is anticipated to boost by stem cell regeneration technology

To receive extensive list of important regions, Request Methodology here @

https://www.persistencemarketresearch.com/methodology/26263

The global Tooth Regenerations market is expected to be dominated by North America due to higher adoption and significant geriatrics population which also increase the demand for dental service for Dental caries and Periodontal disease. Europe is expected to be the second most lucrative Tooth Regenerations market due to rising funds for research for the growing patient population. Asia-Pacific is expected to be the fastest growing Tooth Regenerations market due to rapidly increasing incidence of dental surgery, general prosthetic fixation. Latin America and Middle East & Africa are expected to be the least lucrative market due to Low awareness regarding the use of Tooth Regenerations technology and comparatively less developed healthcare infrastructure in major regions.

Examples of some of the market participants in the global Tooth Regenerations market identified are DENTSPLY Implant, Unilever, Datum Dental, Institut Straumann AG, Keystone Dental, Inc., Zimmer Biomet, Wright Medical Group N.V., Integra LifeSciences, CryoLife, Inc, BioMimetic Therapeutics, Inc, Cook Group and among others.

The report is a compilation of first-hand information, qualitative and quantitative assessment by industry analysts, inputs from industry experts and industry participants across the value chain. The report provides in-depth analysis of parent market trends, macro-economic indicators and governing factors along with market attractiveness as per segments. The report also maps the qualitative impact of various market factors on market segments and geographies.

You Can Request for TOC Here @https://www.persistencemarketresearch.com/toc/26263

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Life Sciences & Transformational HealthLandscape

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Persistence Market Research (PMR) is a third-platform research firm. Our research model is a unique collaboration of data analytics andmarket research methodologyto help businesses achieve optimal performance.

To support companies in overcoming complex business challenges, we follow a multi-disciplinary approach. At PMR, we unite various data streams from multi-dimensional sources. By deploying real-time data collection, big data, and customer experience analytics, we deliver business intelligence for organizations of all sizes.

Our client success stories feature a range of clients from Fortune 500 companies to fast-growing startups. PMRs collaborative environment is committed to building industry-specific solutions by transforming data from multiple streams into a strategic asset.

Contact us:

Naved BegPersistence Market ResearchAddress 305 Broadway, 7th Floor, New York City,NY 10007 United StatesU.S. Ph. +1-646-568-7751USA-Canada Toll-free +1 800-961-0353Salessales@persistencemarketresearch.comWebsitehttps://www.persistencemarketresearch.com

See the original post here:
Increase in Frequency of Product Innovations to Drive the Tooth Regenerations Market from 2018 to 2026 - Lake Shore Gazette

The tooth is a biological organ and consists of multiple tissues including the cementum, dentin, enamel, and pulp. Dental caries, Periodontal disease, and tooth fracture are the three main factor for tooth loss. Tooth Regeneration is the specialty concerned with the treatment of dental diseases such as a cavity, periodontal disease and fracture of the tooth. Dental caries is also known as tooth decay is the main oral health problems in most of the industrialized countries. Facial trauma also the major cause of tooth loss. Tooth loss leads to people mentally and physically disturb and it also affect the self-confidence and quality of life. Tooth regeneration is the process of individual tissue and the whole tooth development. Basically, it is the process of restoring the loss of natural teeth. Tooth regeneration is stem cell-based regenerative medical procedure which is used in stem cell biology sector and tissue engineering. There are two approaches used in the build of new whole teeth, in vivo implantation of tooth germ cells which were previously generated from stem cells and grow in vitro cells and another organotypic culture is an appropriate technique for the generation of teeth. The process of tooth regeneration imitates the natural tooth development using stem cells. In another way instead of whole teeth regeneration, Different part of the teeth regenerates such as Enamel regeneration, Dentin regeneration, Pulp regeneration, and periodontal regeneration.

Globally increasing incidence and prevalence of dental problems such as a cavity, periodontal disease, and tooth fracture are the major factors driving the growth of the Tooth Regenerations market. Innovative new techniques in Tooth regeneration such as cell homing, cell transplantation is expected to increase the acceptance of Tooth Regenerations. Tooth regeneration not only regrowth the entire tooth but also the restoration of individual components of the tooth such as dentin, cementum, enamel and dental pulp and these individual regeneration process is anticipate the boost the market growth of tooth regeneration market. Dental implantation also increases the growth of tooth regeneration market. People are very keen interested in the tooth regeneration and they are also giving more importance to the aesthetic aspects of dental products, which is expected to increase the Tooth Regenerations and dental market over the forecast period. The increasing demand for a customized Tooth Regeneration with the specifications and other dental decorative installations is the key factor anticipated to propel the demand for Tooth Regenerations worldwide.

To remain ahead of your competitors, request for a sample here@

https://www.persistencemarketresearch.com/samples/26263

The Global Tooth Regenerations market is segmented on the basis of application, Demographics, technique and by End user

Based on the Application type Tooth Regenerations market is segmented as:

Based on the Demographic Tooth Regenerations market is segmented as:

Based on the Technique, Tooth Regenerations market is segmented as:

Based on the end user Tooth Regenerations market is segmented as:

According to WHO, approx.30% the geriatric population is affected by the complete loss of teeth. Rapidly increasing Dental cavities and periodontal diseases are the major drivers in the Tooth Regenerations market. The global Tooth Regenerations market by application is expected to be dominated the market of Tooth Regenerations, out of which Enamel segment is expected to generate maximum revenue share over the forecast period. By end user, Tooth Regenerations market is expected to be dominated by dental clinics and hospitals. The manufacturers in the concerned market are focusing on manufacturing advanced products for better patient compliance and make the procedure easier. The market of tooth regeneration is anticipated to boost by stem cell regeneration technology

To receive extensive list of important regions, Request Methodology here @

https://www.persistencemarketresearch.com/methodology/26263

The global Tooth Regenerations market is expected to be dominated by North America due to higher adoption and significant geriatrics population which also increase the demand for dental service for Dental caries and Periodontal disease. Europe is expected to be the second most lucrative Tooth Regenerations market due to rising funds for research for the growing patient population. Asia-Pacific is expected to be the fastest growing Tooth Regenerations market due to rapidly increasing incidence of dental surgery, general prosthetic fixation. Latin America and Middle East & Africa are expected to be the least lucrative market due to Low awareness regarding the use of Tooth Regenerations technology and comparatively less developed healthcare infrastructure in major regions.

Examples of some of the market participants in the global Tooth Regenerations market identified are DENTSPLY Implant, Unilever, Datum Dental, Institut Straumann AG, Keystone Dental, Inc., Zimmer Biomet, Wright Medical Group N.V., Integra LifeSciences, CryoLife, Inc, BioMimetic Therapeutics, Inc, Cook Group and among others.

The report is a compilation of first-hand information, qualitative and quantitative assessment by industry analysts, inputs from industry experts and industry participants across the value chain. The report provides in-depth analysis of parent market trends, macro-economic indicators and governing factors along with market attractiveness as per segments. The report also maps the qualitative impact of various market factors on market segments and geographies.

You Can Request for TOC Here @https://www.persistencemarketresearch.com/toc/26263

Explore Extensive Coverage of PMR`s

Life Sciences & Transformational HealthLandscape

About us:

Persistence Market Research (PMR) is a third-platform research firm. Our research model is a unique collaboration of data analytics andmarket research methodologyto help businesses achieve optimal performance.

To support companies in overcoming complex business challenges, we follow a multi-disciplinary approach. At PMR, we unite various data streams from multi-dimensional sources. By deploying real-time data collection, big data, and customer experience analytics, we deliver business intelligence for organizations of all sizes.

Our client success stories feature a range of clients from Fortune 500 companies to fast-growing startups. PMRs collaborative environment is committed to building industry-specific solutions by transforming data from multiple streams into a strategic asset.

Contact us:

Naved BegPersistence Market ResearchAddress 305 Broadway, 7th Floor, New York City,NY 10007 United StatesU.S. Ph. +1-646-568-7751USA-Canada Toll-free +1 800-961-0353Salessales@persistencemarketresearch.comWebsitehttps://www.persistencemarketresearch.com

Link:
Incremental Sales to Drive the Tooth Regenerations Market from 2018 to 2026 - Lake Shore Gazette

More than 1 million Americans are diagnosed with a chronic brain disorder each year, yet effective treatments for most complex brain disorders are inadequate or even nonexistent.

A major new research effort at the McGovern Institute for Brain Research at MIT aims to change how we treat brain disorders by developing innovative molecular tools that precisely target dysfunctional genetic, molecular, and circuit pathways.

The K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics in Neuroscience was established at MIT through a $28 million gift from philanthropist Lisa Yang and MIT alumnus Hock Tan 75. Yang is a former investment banker who has devoted much of her time to advocacy for individuals with disabilities and autism spectrum disorders. Tan is president and CEO of Broadcom, a global technology infrastructure company.This latest gift brings Yang and Tans total philanthropy to MIT to more than $72 million.

In the best MIT spirit, Lisa and Hock have always focused their generosity on insights that lead to real impact," says MIT President L. Rafael Reif. Scientifically, we stand at a moment when the tools and insights to make progress against major brain disorders are finally within reach. By accelerating the development of promising treatments, the new center opens the door to a hopeful new future for all those who suffer from these disorders and those who love them. I am deeply grateful to Lisa and Hock for making MIT the home of this pivotal research.

Engineering with precision

Research at the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics in Neuroscience will initially focus on three major lines of investigation: genetic engineering using CRISPR tools, delivery of genetic and molecular cargo across the blood-brain barrier, and the translation of basic research into the clinical setting. The center will serve as a hub for researchers with backgrounds ranging from biological engineering and genetics to computer science and medicine.

Developing the next generation of molecular therapeutics demands collaboration among researchers with diverse backgrounds, says Robert Desimone, McGovern Institute director and the Doris and Don Berkey Professor of Neuroscience at MIT. I am confident that the multidisciplinary expertise convened by this center will revolutionize how we improve our health and fight disease in the coming decade. Although our initial focus will be on the brain and its relationship to the body, many of the new therapies could have other health applications.

There are an estimated 19,000 to 22,000 genes in the human genome and a third of those genes are active in the brain the highest proportion of genes expressed in any part of the body. Variations in genetic code have been linked to many complex brain disorders, including depression, Parkinsons, and autism. Emerging genetic technologies, such as the CRISPR gene editing platform pioneered by McGovern Investigator Feng Zhang, hold great potential in both targeting and fixing these errant genes. But the safe and effective delivery of this genetic cargo to the brain remains a challenge.

Researchers within the new Yang-Tan Center will improve and fine-tune CRISPR gene therapies and develop innovative ways of delivering gene therapy cargo into the brain and other organs. In addition, the center will leverage newly developed single-cell analysis technologies that are revealing cellular targets for modulating brain functions with unprecedented precision, opening the door for noninvasive neuromodulation as well as the development of medicines. The center will also focus on developing novel engineering approaches to delivering small molecules and proteins from the bloodstream into the brain. Desimone will direct the center and some of the initial research initiatives will be led by associate professor of materials science and engineering Polina Anikeeva; Ed Boyden, the Y. Eva Tan Professor in Neurotechnology at MIT; Guoping Feng, the James W. (1963) and Patricia T. Poitras Professor of Brain and Cognitive Sciences at MIT; and Feng Zhang, James and Patricia Poitras Professor of Neuroscience at MIT.

Building a research hub

My goal in creating this center is to cement the Cambridge and Boston region as the global epicenter of next-generation therapeutics research. The novel ideas I have seen undertaken at MITs McGovern Institute and Broad Institute of MIT and Harvard leave no doubt in my mind that major therapeutic breakthroughs for mental illness, neurodegenerative disease, autism, and epilepsy are just around the corner, says Yang.

Center funding will also be earmarked to create the Y. Eva Tan Fellows program, named for Tan and Yangs daughter Eva, which will support fellowships for young neuroscientists and engineers eager to design revolutionary treatments for human diseases.

We want to build a strong pipeline for tomorrows scientists and neuroengineers, explains Hock Tan. We depend on the next generation of bright young minds to help improve the lives of people suffering from chronic illnesses, and I can think of no better place to provide the very best education and training than MIT.

The molecular therapeutics center is the second research center established by Yang and Tan at MIT. In 2017, they launched the Hock E. Tan and K. Lisa Yang Center for Autism Research, and, two years later, they created a sister center at Harvard Medical School, with the unique strengths of each institution converging toward a shared goal: understanding the basic biology of autism and how genetic and environmental influences converge to give rise to the condition, then translating those insights into novel treatment approaches.

All tools developed at the molecular therapeutics center will be shared globally with academic and clinical researchers with the goal of bringing one or more novel molecular tools to human clinical trials by 2025.

We are hopeful that our centers, located in the heart of the Cambridge-Boston biotech ecosystem, will spur further innovation and fuel critical new insights to our understanding of health and disease, says Yang.

See more here:
New molecular therapeutics center established at MIT's McGovern Institute - MIT News

What, he wonders, if the highly educated harden into a hereditary aristocracy? And what if this occurs under a flag of fairness, during a time when B.A.s and higher degrees are ever more closely tied to income and prestige? Lets set aside the case of rich parents who bribe corrupt officials or donate huge sums to get their child into a good college. Lets focus instead, Sandel writes, on the inequity that creeps in without breaking any rules. At Princeton and Yale, for example, more students come from families in the top 1 percent of income than from the bottom 60 percent. Two-thirds of students in all the Ivy League schools come from families in the top 20 percent. This is very largely because of the head start woven into upper-income life itself: engaging dinner conversation, better schools, private tutors, foreign travel.

Sandel is not about guilt-tripping anxious parents of front-row kids; theyre suffering too, he says. But the credentialed have come to imagine themselves as smarter, wiser, more tolerant and therefore more deserving of recognition and respect than the noncredentialed. One reason for this, he suggests, lies in our American rhetoric of rising. Both rich and poor parents tell their kids, if you try hard enough, you can achieve your goals. For the upper strata, things may work out, but for the downwardly mobile blue collar and poor, theres a Catch-22. If they fail to reach their goals which a torpid economy almost guarantees they blame themselves. If only I could have gotten that degree, they say. Even the poorly educated, Sandel notes, look down on the poorly educated.

Donald Trump has reached out to this group with open arms I love the poorly educated. He has harvested their demoralization, their grief and their shame, most certainly if they are white. But, Sandel notes, two-thirds of all American adults lack four-year degrees. And in the wake of automation, in real wages, the white man without a B.A. earns less now than he did in 1979. The dignity of his labor has steeply declined. And since 1965, high-school-educated men in the very prime of life 25 to 54 have been slipping out of the labor force, from 98 percent in 1965 to 85 percent in 2015. Of all Americans whose highest degree is a high school diploma, in 2017 only 68 percent worked. And with rising deaths of despair, many are giving up on life itself. So you who are highly educated, Sandel concludes, should understand that youre contributing to a resentment fueling the toxic politics you deplore. Respect the vast diversity of talents and contributions others make to this nation. Empathize with the undeserved shame of the less educated. Eat a little humble pie.

But we are left with an important issue Sandel does not address: the targeting by the right wing of colleges themselves. This isnt new: Running parallel to the rise of the meritocracy in America has been a suspicion of the egghead who cant skin a rabbit, build a house or change a tire. As the historian Richard Hofstadter observed in Anti-Intellectualism in American Life, and Tocqueville before him, many Americans have valued not simply the cultivated intelligence of heroes in a culture of merit but also the creative genius of the common man in a culture of survival.

Today this has taken a shockingly partisan turn. For the first time in recent history, the less education you have, the more you lean right and distrust higher education itself. In a 2019 Pew survey, 59 percent of Republicans (and Republican-leaning independents) agree that colleges have a negative effect on the way things are going in the country these days, whereas only 18 percent of Democrats (and those leaning left) agree.

Continue reading here:
Whats Wrong With the Meritocracy - The New York Times

A joint report by several NGOs caused a stir on September 7th by claiming that [gene editing] was now detectable by means of a laboratory test. This refutes the claim of genetic engineering proponents that plants produced using [gene editing] are indistinguishable from conventionally grown plants.

Among others, Greenpeace . funded a study conducted by researchers from Iowa who said they have developed a detection method that can be used to identify point mutations.

The Federal Office for Consumer Protection and Food Safety (BVL), as the licensing authority, took a closer look at this study. The BVL came to a significantly different conclusion than the anti-genetic engineering NGOs.

The herbicide tolerance trait in Cibus oilseed rape [used in the study] was the result of a point mutation. The BVL made it clear: These mutations can have very different origins: New breeding methods, such as genome editing, as well as classic breeding methods and random biological processes are all possible sources of such genetic changes.

According to the information available, the BVL comes to the conclusion that the point mutation considered in the article did not result from genome editing processes, the agency said.

In a more detailed analysis . the BVL stated that the named detection method is suitable for identifying this specific point mutation, but not whether it actually came about in one of the rapeseed lines through genome editing, BVL added in its statement.

This story was published in German and has been translated and edited for clarity.

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Can gene-edited crops be 'detected'? Claims by Greenpeace and anti-biotech activists dismissed by safety officials, scientists - Genetic Literacy...

A former Idaho State University medical laboratory science student. | Courtesy Idaho State University

POCATELLO Medical laboratory scientists play an important role in helping keep the health care system running, but they dont often get credit for what they do because they work behind the scenes.

Idaho State Universitys Medical Laboratory Science Program Director Rachel Hulse explained that medical lab scientists are sometimes referred to as the doctors doctor. This is because they assist primary care providers in disease diagnosis.

Between 70% and 80% of all medical decisions that primary health care providers make are based on scientists lab findings.

Every tube of blood thats drawn, every body tissue, every urine or other kind of body fluid that might come out of the body, were the ones who are running the tests and the analyses on those to try to figure out whats going on, Hulse said.

Hulse says 100% of ISU graduates in the program are employed in the field or in a closely related field immediately after earning their degree.

ISUs medical laboratory science program is the only accredited program in the state of Idaho that offers both a bachelors and a masters degree, according to Hulse.

We actually have a huge workforce shortage, similar to what you hear about in nursing, Hulse explained. The number of graduates (nationally) cant fill the number of jobs that we have, and thats exacerbated now, by COVID, because theres an increased need for testing capacity.

It can be difficult for doctors to differentiate between a cold, flu or COVID-19 without doing laboratory diagnostic testing, she said. But even if the pandemic wasnt happening right now, testing is something that never goes away because people get sick and some have chronic health issues.

Before the onset of the pandemic, the profession was projected to grow between 10% and 16% within the next decade.

That is way above the national average for job growth, she said.

An article published on Genetic Engineering and Biotechnology News also noted that the job outlook for medical lab scientists over the next few years is growing much faster than average.

Courtesy Idaho State University

While the occupation is something Hulse doesnt believe is recognized enough, especially for being a massively critical part of the healthcare team, she feels COVID-19 has exposed the profession a little more, and the virus has helped students realize how essential and fulfilling the job is.

I think its so important to recognize the other pieces of the healthcare team that are so critical, not only in healthcare in general but in a pandemic setting, Hulse added. Its important to have an understanding of what those teams are and the options that (students) have.

The ISU medical laboratory science program can be taken online. Students in Alaska, rural parts of Idaho and other areas of the country have participated in the program.

The application for the program will open in October and is due at the end of February. Students who are admitted will start the program at the beginning of the following fall semester.

More information on the program can be found here.

Former students in Idaho State Universitys medical laboratory science program. | Courtesy Idaho State University

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The growing demand for medical lab scientists and the 'important role' they play during COVID-19 - East Idaho News

Conspiracy theories about COVID-19 have been spreading since the early days of the outbreak. But how do we know whether a biological entity is artificially made or has occurred naturally? Marc Baiget Francesch explores the capabilities of current scientific approaches in terms of virus engineering and how this applies to the present pandemic.

OVER THE LAST few months, numerous theories relating to the origin of the novel coronavirus SARS-CoV-2 have invaded the internet. Sometimes, these theories can give rise to more interesting discussions than what is originally intended by the authors. For example, the theory that the new coronavirus has been purposely made as a biological weapon would mean that SARS-CoV-2 is a synthetic organism, which simultaneously implies that scientists can create synthetic viruses. How much truth is there in that implication? How far can current technologies go in terms of artificial microorganisms design? To answer these questions, we first need to understand the current state of synthetic biology as a field and acknowledge its limitations.

While making a new virus from scratch is not technically impossible, it would require a level of knowledge that is implausible to imagine in any scientific institution at present

Synthetic biology greatly relies on predictive models and computer simulated structures. Computer programmes use the information collected by years of research in molecular biology, which is stored in huge libraries of microorganisms, molecules and domains, to explore their potential when modified or combined in silico that is, on a computer. The idea of these programmes is to form combinations that, presumably, do not exist in nature in order to analyse potential structures for multiple uses. However, despite in silico models providing valuable information and saving time and money on in vitro experimentation, they are far from perfect.

Professor JA Davies, from the University of Edinburgh, published a paper in the open access journal Life that analysed the current flaws of the engineering approach in synthetic biology. While he recognises that this approach, based on the design-build-test dogma, is interesting and that relying on standard pre-existing parts simplifies the overall design of synthetic structures, it lacks biological understanding.1

In biology, every component from a microorganism has a metabolic cost, ie, the more components you add to a cell, the less energy the cell can direct to each part. Therefore, the fewer parts used for a function, the better. In genetic engineering this is a crucial consideration, since adding new genes normally supposes that pre-existing genes are deleted in order for the organism to be viable. In addition, the interactions between two different pre-existing parts might affect its original function. Hence, as Professor Davies argues, using a novel part, designed for a specific function, might prove easier than trying to reproduce the same function with two pre-existing ones. Ultimately, evolution is based on constant changes of previous structures induced by a huge number of factors and not on the combination of unchanging structures. So, while synthetic biology can cover a lot of unexplored possibilities, it is still far from being an almighty tool or competing with natural evolution.

This brings us to the next question: how capable are current scientific approaches in terms of virus engineering? Researchers can recreate an existing virus from scratch, and this is what many research teams have been attempting since the coronavirus started to spread in order to understand the virus better.2 However, creating a new one is another story. It is possible to create new viruses from original ones; though, there are some restrictions. As aforementioned, synthetic biology relies on the use of pre-existing parts, which means we would need to use different parts of existing viruses and assemble them in order to produce a new virus. Dr Robert F Garry, a microbiologist specialising in virology, commented in Business Insider that there is no consensus on what exactly makes a virus pathogenic.3 Therefore, while making a new virus from scratch is not technically impossible, it would require a level of knowledge that is implausible to imagine in any scientific institution at present. Nevertheless, our current knowledge of molecular science allows us to identify potentially man-made structures or microorganisms.4 This is possible because they are based on pre-existent parts; an engineered virus would have identifiable segments of DNA that belong to other viruses whose sequences are stored in libraries. This means that we should be able to identify if a new virus was artificially designed or is a product of natural evolution.

To study the case of the novel coronavirus, we need to have access to its genetic sequence. This has been a major advancement in epidemiology, as for previous pandemics researchers had to wait from months to years in order to study the microorganism responsible for the outbreak, whereas the structure of SARS-CoV-2 was available within weeks. By analysing its genetic structure, scientists have realised that the backbone of the virus is, indeed, a new one.5 However, this does not mean that the virus was not artificially made; we just know that the backbone was not copied from another virus.

What about prompting an existent virus to mutate? It could be that biotechnologists induced mutations to a known virus in order to produce a novel one, like what we see in nature. However, when scientists evaluated the structure of SARS-CoV-2 and compared it to other viral structures, the closest relative they found was SARS-CoV RaTG13, which showed a 96 percent similarity to the novel coronavirus.6 Although 96 percent may seem a lot, considering the size of SARS-CoV-2, which is close to 30,000 nucleotides long, this four percent difference is quite significant around 1,200 nucleotides.7

Studying evolution and natural processes is key for synthetic biology to expand and become an even more powerful tool

Nevertheless, there may still be some resistance to debunking certain theories. One might argue that, while using known parts of similar viruses, targeted mutations could have been applied to give the virus the ability to attach to human cells which is essentially what makes this virus able to infect humans. One of the most curious facts about the coronavirus is that the receptor binding domain the part that makes SARS-CoV-2 able to attach to human cells was simulated in silico once the sequence of the virus was made available. This sequence showed poor efficiency on the simulations, meaning that nature has found a mechanism that we had not been able to predict.3 If we put together all the facts and reflect on the fact that 75 percent of the new emerging diseases are from zoonotic origin, it appears the theories around SARS-CoV-2 being a man-made virus are quite unrealistic, to say the least.8

Something I have found interesting since the search of the origin of the SARS-CoV-2 started, is that we have confirmed that synthetic biology still has a long way to go. We still need to understand a lot about nature to get a bigger picture of how things work and to grasp all the possibilities that molecular biology has to offer. Studying the evolution of viruses not only benefits the epidemiologists, but also the synthetic biologists, who gain insights into how molecular interactions work. This newfound knowledge can be used to improve current models and propose frameworks for the creation of new molecules. Therefore, one can conclude that studying evolution and natural processes is key for synthetic biology to expand and become an even more powerful tool.

Marc Baiget Francesch is an MSc in Pharmaceutical Engineering and currently works as an Assistant Editor for the International Journal of Molecular Sciences. He also writes articles and innovation grants as a freelancer.

Excerpt from:
The limits of synthetic biology through the origins of SARS-CoV-2 - Drug Target Review