Page 918«..10 20..917918919 920..930 940..»

Category Archives: Transhuman News

Genome Editing/Genome Engineering Market expectation surges with rising demand and changing trends by industry analysis through 2027 The Manomet…

Posted: June 6, 2021 at 7:40 pm

Global Genome Editing/Genome Engineering Market is valued approximately USD 4.4 billion in 2019 and is anticipated to grow with a healthy growth rate of more than 17.00 % over the forecast period 2020-2027.

Genome Engineering technique is used for deletion, insertion and modification of genome of a microorganism. Genome editing/genome engineering plays an integral role in modern-day biology and is widely used in the biopharmaceutical and biotechnology industry to alter the genome of microorganism to perform process such as fermentation which yield desired products. Also, this approach is majorly used for understanding DNA in cells of organism to have a better understanding of their biology, to treat infectious and autoimmune diseases. Availability of government funding and growth in the number of genomics projects are the few factors responsible for growth of the market over the forecast period of 2020-2027. For Instance: in 2017, in Canada, as per the University of Guelph, University of Genome Canada Bioinformatics and Computational Biology along with other eligible sources provide funding of $12 million for different genomics-based research projects. Similarly, according the Japan Agency for Medical Research and Development Organization, in 2017, government of Japan has introduced various initiatives such as Tohoku Medical Megabank project, Platform Program for promotion of Genome Medicine etc., these projects are inclined to provide research infrastructure.

Request for a FREE sample of this market research report@ https://www.reportocean.com/industry-verticals/sample-request?report_id=bw1334

Such government initiatives would increase the need for genome editing and genome engineering. Also, the key players of global Genome Editing/Genome Engineering market have adopted various strategies to gain competitive advantage including product launch, innovation, technological advancements, investment, funding and others. However, high equipment cost is the major factor restraining the growth of global Genome Editing/Genome Engineering market during the forecast period.

The regional analysis of global Genome Editing/Genome Engineering market is considered for the key regions such as Asia Pacific, North America, Europe, Latin America and Rest of the World. North America is the leading/significant region across the world in terms of market share as the region is one of the most significant markets for development of gene therapy in the US, the the rising prevalence of infectious diseases and cancer, increasing use of genetically modified crops, and the availability of research grants and funding. Whereas Asia-Pacific is also anticipated to exhibit highest growth rate / CAGR over the forecast period 2020-2027.

Major market player included in this report are:Thermo Fisher ScientificMerckHorizon DiscoveryGenscriptSangamo TherapeuticsLonzaEditas MedicineCrispr TherapeuticsEurofins ScientificPrecision Biosciences

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Technology:CRISPRTALENZFNANTISENSEOther technologiesBy Product and Services:Reagents and ConsumablesSoftware & systemsServicesBy Application:Cell line EngineeringGenetic EngineeringDiagnostics ApplicationsDrug discovery and developmentOthersBy End-user:Pharmaceuticals CompaniesBiotechnology CompaniesAcademic and Government research institutesBy Region:North AmericaU.S.CanadaEuropeUKGermanyFranceSpainItalyROE

Asia PacificChinaIndiaJapanAustraliaSouth KoreaRoAPACLatin AmericaBrazilMexicoRest of the World

Furthermore, years considered for the study are as follows:

Historical year 2017, 2018Base year 2019Forecast period 2020 to 2027

Send a request to Report Ocean to understand the structure of the complete report @https://www.reportocean.com/industry-verticals/sample-request?report_id=bw1334

Target Audience of the Global Genome Editing/Genome Engineering Market in Market Study:

Key Consulting Companies & AdvisorsLarge, medium-sized, and small enterprisesVenture capitalistsValue-Added Resellers (VARs)Third-party knowledge providersInvestment bankersInvestors

See the original post here:
Genome Editing/Genome Engineering Market expectation surges with rising demand and changing trends by industry analysis through 2027 The Manomet...

Posted in Genetic Engineering | Comments Off

Covid 19 coronavirus: Why the lab leak theory is still unlikely – New Zealand Herald

Posted: at 7:40 pm

The World Health Organisation maintains the coronavirus most likely arose in bats, and then spread to humans via an as-yet unidentified intermediary animal. Image / CDC

Despite the "lab leak theory" taking flight again in the US media, global scientists still point out there's little evidence to suggest the SARS-CoV-2 virus originated in a Wuhan laboratory and a large amount to suggest it came from nature. Otago University virologist Dr Jemma Geoghegan and Massey University infectious disease ecologist Professor David Hayman set out three reasons why a lab-made pandemic remains extremely unlikely.

There's a strong precedent for coronaviruses that have become "zoonotic", or jumped from animals to humans.

There have been seven that scientists are aware of including SARS-CoV and MERS-CoV and bats are thought to have been involved in most of these.

"And five of these human coronaviruses have emerged in the last 20 years," Geoghegan said.

While the source of the SARS-CoV-2 virus still hasn't been pinned down, she said that wasn't unusual.

"In fact, we don't know where most of the viruses that infect us have come from," she said.

"This is why we need to sample more viruses in nature and expand our knowledge of the diversity of viruses that exist."

Hayman added that, now that scientists were looking even harder, more cases of infections from newly-detected or "novel" coronaviruses were coming to light.

"One was identified in pneumonia patients in Malaysia where people were living in villages in close contact with domestic and wild animals."

While the pandemic found the world poorly prepared for it, scientists had been warning for years that the growing interaction between animals and nature particularly through habitat destruction had been raising the risk of a catastrophe like Covid-19.

Just like the first Sars coronavirus, the first cases of Sars-Cov-2 were associated with an animal market this time in Wuhan, China.

The World Health Organisation's report identified that live animals like ferret-badgers and rabbits were being traded in these markets.

"These animals could provide an intermediate host for the virus to jump to humans," Geoghegan said.

"It's exactly the type of place you'd expect a zoonosis event to happen."

Hayman added that some of the farmed species had complex commodity chains.

That meant the farms could well be in places where there was a greater diversity of bat viruses than in Wuhan, where the pandemic appeared to have started.

"And we have seen how SARS-CoV-2 can be maintained in farmed fur animals, such as the very large outbreaks in farmed mink in Europe, which led to substantial mink to mink transmission as well as mink-to-human transmission."

Other evidence also shows that this type of coronavirus has existed in bats for decades and the SARS-CoV-2 genome sequence happened to be 96 per cent identical to a coronavirus found in horseshoe bats.

In one of the earliest major studies into the virus, scientists analysed its genetic template for spike proteins or armatures on the outside of the virus that it used to grab and penetrate the outer walls of human and animal cells.

More specifically, they focused on two important features of the spike protein.

Those were its receptor-binding domain (RBD) - a kind of grappling hook that grips on to host cells - and what's called the cleavage site, a molecular can opener that allows the virus to crack open and enter host cells.

They found the RBD portion of the SARS-CoV-2 spike proteins had evolved to effectively target a molecular feature on the outside of human cells called ACE2 - a receptor involved in regulating blood pressure.

The SARS-CoV-2 spike protein was so effective at binding the human cells, in fact, that the scientists concluded it was the result of natural selection, and not the product of genetic engineering that some theorists have suspected.

The idea of natural evolution was given further credence by data on the virus' backbone - its overall molecular structure.

If someone were seeking to engineer a new coronavirus as a pathogen, they would have constructed it from the backbone of a virus known to cause illness.

But the scientists found that the backbone differed greatly from those of already known coronaviruses.

It turned out to mostly resemble related viruses found in bats and pangolins - scaly-skinned mammals that are prized delicacies in China.

That led scientists to suspect one of two possible scenarios.

In one scenario, the virus evolved to its current state through natural selection in an animal host and then jumped to humans.

Yet there were no documented cases of direct bat-human transmission, suggesting that an intermediate host was likely involved between bats and humans.

In this scenario, both of the distinctive features of SARS-CoV-2's spike protein - the RBD portion that binds to cells and the cleavage site that opens the virus up - would have evolved to their current state before entering humans.

In this case, the current epidemic would probably have emerged rapidly as soon as humans were infected, as the virus would have already evolved the features that made it pathogenic, or able to spread between people.

In the other proposed scenario, a non-pathogenic version of the virus jumped from an animal host into humans and then evolved to its current state within the human population.

A coronavirus from a pangolin could possibly have been transmitted to a human, either directly or through an intermediary host such as civets or ferrets.

After that, the other distinct spike protein characteristic of SARS-CoV-2 - the cleavage site - could have evolved within a human host, or possibly among a group of people, before the outbreak kicked off.

Geoghegan said the idea that the cleavage site was so unusual that it must have been engineered was "totally false".

She said that assumed an amino acid sequence within the site called PRRAR had been created in a lab.

Yet these cleavage sites had been found in other coronaviruses - even with the exact same "PRRAR" insert.

"It's a totally bonkers argument," Hayman added.

"Similarly, people really need to understand that these viruses do recombine. For example, the novel virus from Malaysia that was recently detected seems to be a recombinant of a cat and dog viruses, which were also previously not known."

The slightly more plausible alternative lab leak theory was that scientists could simply have been growing a culture of the virus, and it escaped from there.

But that would've had to assume the virus could have leaked from a secure research facility and also neglected the fact that the virus' feature of entry and infection markedly diminished in a lab culture setting.

And then, as Dr Jonathan Stoye, group leader of the Retrovirus-Host Interactions Laboratory at the UK's Francis Crick Institute, pointed out, the virus' spread around the world didn't gel with the lab-grown theory.

"The genome of SARS-CoV-2 shows more than 1000 individual differences from its closest known relative," he said.

"Given the rate of nucleotide change observed in virus spreading through the human population over the past year it seems extremely improbable, perhaps impossible, that changes spanning such an evolutionary distance could have occurred during virus growth in a lab.

"It therefore remains most likely that the immediate ancestor to SARS-CoV-2 exists in the wild and is still to be found."

Scientists aren't saying the possibility of a lab leak should be entirely ruled out on the contrary, many argue that it should be comprehensively investigated.

But more than a year after the outbreak, the weight of evidence overwhelmingly points to a natural source, while there's little to suggest the virus came from a lab.

Part of the lab leak theory is predicated on the fact that the Wuhan Institute of Virology has carried out extensive work on coronaviruses in bats.

While the institute didn't shared its lab records with a team of WHO investigators, there's as yet been no evidence that any samples of the virus were kept there before it was first reported, nor were there any viruses that could have combined to create it.

Much of the recent coverage has been fueled by a US intelligence report that stated several researchers had become sick with "symptoms consistent with both Covid-19 and common seasonal illness".

A top director at the institute has rejected this inference, reporting that all staff have tested negative for Covid-19 antibodies, and that there'd been no turnover of staff in the coronavirus team.

"Why would these scientists be working on a random secret bat virus and not have published anything on it previously?" Geoghegan said.

"Those that do gain-of-function experiments work on really well characterised viruses, and there would be really close genetic relatives of the virus published before.

"But for SARS-CoV-2, there isn't. Even the closest viruses in bats and pangolins are too divergent to be a starting point."

Hayman added that every expert in the area would have asked themselves, "what if it was that lab?"

"We ask ourselves, 'What would we see, what evidence would we need to support it?', and even, 'have we been lied to?'. We have, most of us, agonised over the possibilities.

"But right now the only way that this can be true is if there is a massive conspiracy, because while the lab pathway is a potential pathway, nothing published or reliably reported by China to date supports a lab escape at all, and there is a huge amount of data to support this being a natural event.

"This discussion would have gone away if it hadn't have happened in China. But unfortunately finding conclusive evidence of either is very unlikely."

See the article here:
Covid 19 coronavirus: Why the lab leak theory is still unlikely - New Zealand Herald

Posted in Genetic Engineering | Comments Off

Crispr-cas9 for the treatment of lung cancer | BTT – Dove Medical Press

Posted: at 7:40 pm

Markeshaw Tiruneh G/Medhin,1 Endeshaw Chekol Abebe,2 Tekeba Sisay,3 Nega Berhane,3 Tesfahun Bekele Snr,1 Tadesse Asmamaw Dejenie1

1Department of Biochemistry, School of Medicine, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia; 2Department of Biochemistry, College of Health Sciences, Debre Tabor University, Debre Tabor, Ethiopia; 3Institute of Biotechnology, College of Natural Science, University of Gondar, Gondar, Ethiopia

Correspondence: Markeshaw Tiruneh G/Medhin Tel +251922712112Email [emailprotected]

Abstract: Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated proteins are referred to as CRISPR-Cas9. Bacteria and archaea have an adaptive (acquired) immune system. As a result, developing the best single regulated RNA and Cas9 endonuclease proteins and implementing the method in clinical practice would aid in the treatment of diseases of various origins, including lung cancers. This seminar aims to provide an overview of CRISPR-Cas9 technology, as well as current and potential applications and perspectives for the method, as well as its mechanism of action in lung cancer therapy. This technology can be used to treat lung cancer in two different ways. The first approach involves creating single directed RNA and Cas9 proteins and then distributing them to cancer cells using suitable methods. Single directed RNA looks directly at the lungs mutated epidermal growth factor receptor and makes a complementary match, which is then cleaved with Cas9 protein, slowing cancer progression. The second method is to manipulate the expression of ligand-receptors on immune lymphocytic cells. For example, if the CRISPR-Cas9 system disables the expression of cancer receptors on lymphocytes, it decreases the contact between the tumor cell and its ligand-receptor, thus slowing cancer progression.

Keywords: CRISPR, Cas9, CRISPR-Cas9 technology, cancer, lung cancer, cancer treatment

The word CRISPR-Cas9 refers to Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated proteins.15 CRISPR-Cas9 system is a kind of acquired immunity possessed by most bacteria and archaea (prokaryotes) to act against their enemies (bacteriophages).4,6 It is a ribonucleic acid (RNA) guided, convenient, and versatile endonuclease platform for site-specific genome editing,1,7,8 which can play a tremendous role in the application of cancer therapy.1 The application of this technology can be used to resolve mutations and to introduce site-specific therapeutic genes in human cells so that, correcting disease-causing mutations, and alleviate disease-related symptoms. This system is also a useful tool for delineating molecular mechanisms involving hematological malignancies.4 Sequence-specific gene editing using CRISPR-Cas9 shows promise as a novel therapeutic approach for the treatment of a variety of diseases that currently lack effective treatments like cancers.3,9 To accomplish its task, it requires Cas9 DNA endonuclease protein and single guided RNA (sgRNA) that can produce precise gene matching for editing and correction techniques.2 So the system has enabled easy manipulation of genes for the scientific community by making the hybrid to the target sequence and cleaving the double-strand DNA.10

Additionally, the CRISPR-Cas9 technology is increasingly feasible to overcome drug resistance in breast cancer therapy and will become an essential tool for personalized medicine.4 It is a technological breakthrough that facilitates the ability to change nucleic acids,11 and with continued improvement in the function, the system can help to develop best treatment options to a variety of genetic disease which affects several tissues in our body.12 Gene manipulation using CRISPR-Cas9 system has revolutionized and made it easy to study the work of genes and importantly opens the new era of treatment mechanisms for different disease conditions including cancer.13 Technologies like this are a simple and efficient method of targeting the required DNA regions.14 Thus, scientists have designed two main components of the system for easy detection and alteration of gene function one component is a protein Cas9 that enzymatically cleave the desired gene and the sgRNA which scans and determines where the gene of interest will be cleaved by Cas9 protein.3,12,15 The system has been scientifically optimized and developed to regulate expression of the gene, modify and edit the desired locus and this makes the technology of choice seen by the scientific community to treat or edit disease-causing mutations more efficiently than ever before. Furthermore, its application is encouraging for more vigorous gene therapy in clinical setups.16 Based on the discovery, there are three main types of CRISPR-Cas9 system (I to III) and with three additional types (IV to VI) being identified more recently.17 They are different during the processes of immunity, adaptation, expression, and interference, each type acts in distinct mechanisms to ensure genetic manipulation. Type I employs a large complex of Cas9 proteins with distinct helicase and DNase activities, while type III employs repeat-associated mysterious proteins, which form a large Cas9 superfamily. Another classification is based on subunit effectors, with multi-subunit effector complexes being the most common. Types I, III, and IV are grouped in class 1. Those systems, on the other hand, that have a single subunit effector are categorized as class 2 comprising types II, V, and VI.17,18 Type II uses only a Single protein (Cas9) for its nuclease activity and has got more attention and adopted for genome engineering.5,17,19 Thus, the objective of this seminar is to introduce CRISPR-Cas9 technology and describe current applications and future perspectives of the system with its mechanism of action on lung cancer therapy.

The tracrRNA gene will be transcribed to tracrRNA, the crRNA gene will be transcribed to pre crRNA, and the Cas9 gene will be transcribed to Cas9 messenger RNA and converted to Cas9 protein, all of which will be post-transcribed and chopped off to form the mature CRISPR-Cas9 complex.20 Cas1 and Cas2 integrase, which are present in all CRISPR forms, catalyze spacer integration on the CRISPR array especially on the leader end of the repeat there will be a nucleophilic attack of the 3 OH of the protospacers followed by the same practice on the spacer end of the repeat.21

The CRISPR-Cas9 method has a variety of formulation methods for genome editing. The use of a plasmid-based CRISPR-Cas9 system encoding both the Cas9 protein and sgRNA from the same vector, which is necessary to avoid multiple transfections of different components of the technology, is the leading and possibly the easiest technique. The Cas9 protein and sgRNA will be expressed in the vector, which will form the sgRNA-Cas9 complex within cells to edit the target genomic sequences.3,12,15,18 The second approach involves combining Cas9 mRNA and sgRNA. The sgRNA-Cas9 complex will be formed when Cas9 mRNA is converted into Cas9 protein in cells. The third strategy is to deliver the in vitro assembled sgRNA-Cas9 complex directly to the cell.18

It is difficult to transmit nucleic acid in general, and CRISPR-Cas9 in particular, to the target tissue or cell. Physical and vector (viral or non-viral) approaches are two of the most widely used distribution strategies.11,22,23 Electroporation and microinjections are used in physical methods, while viral delivery strategies such as adeno associated virus (AAV) are widely used in vector-based methods since they are not disease-causing agents and can infect both dividing and non-dividing cells25 and lentivirus with inactivated integrase enzymes are under investigation.24

Another technique is lipofection (lipid-mediated nanoparticle transfection), which is possibly the most efficient CRISPR-Cas9 in vivo delivery method.22 This technique was further developed by26 and is currently being tested in clinical trials.13,24

The CRISPR-Cas9 system, as discussed, a little earlier, is made up of two main components that work together to accomplish its goal.19 The sgRNA contains crRNA, which scans and identifies the target DNA sequences that must be cleaved and corrected, and transactivated crRNA (tracrRNA), which recruits component two, the Cas9 protein DNA endonuclease, which can sense, identify, and establish site-specific double-strand DNA breaks (DSB).15 Because of its simplicity and convenience, the bacterial type II CRISPR-Cas9 system has been used for RNA-guided engineering nucleases.4,18 However, the proto-spacer adjacent motifs (PAM) sequences are required by the method. After recognition, two Cas9 domains cleave double-stranded DNA: the endonuclease domain named for characteristic histidine and asparagine residues (HNH) domain, which cleaves the complementary strand, and the endonuclease domain named for an E. coli protein involved in DNA repair (RuvC-like) domain, which cleaves the non-complementary strand.17 As a result, the host DNA repair machinery introduces numerous mutations such as substitutions, deletions, and insertions in the target genome, including non-homologous end joining (NHEJ) or homologous-dependent repair (HDR).1518 Another paper, CRISPR-Cas9 for Cancer Therapy: Hopes and Challenges, supports this theory by demonstrating that the sgRNA-Cas9 complex scans and anneals to the genomic target sequence with base-pairing complementarity and precisely cleaves double-stranded DNA of the target cell after identification of the protospacer adjacent motif (PAM) sequence adjacent to the target sequence. NHEJ or HDR pathways are activated as a result of double-strand breaks. NHEJ is an error-prone repair mechanism that results in indels (insertions or deletions) of random base pairs disrupting the target sequence in the absence of a homologous repair prototype with more specific repair mechanisms.23,27

Lung cancer is the major cause of death in the United States and a significant public health concern worldwide.5 In both developed and developing countries, it is a common cause of morbidity and mortality.28 According to a study conducted by the American Lung Cancer Society in 2015, lung cancer claims the lives of almost 150,000 people each year. However, surgery and radiation were used as treatment options. The treatment was later changed to selective Tyrosine kinase inhibitors (TKIs) like gefitinib and erlotinib to inhibit the tyrosine kinase activity of epidermal growth factor receptor, which has technical difficulties and nonspecific cytotoxicity (EGFR).29,30 Extracellular ligand binding, transmembrane, and intracellular tyrosine kinase domains are found in this membrane glycoprotein. When the ligand activator binds to the extracellular ligand domain, it transduces and initiates intracellular kinase activities, which cause cellular proliferation, neovascularization, invasion, and metastasis, as well as reduced apoptosis and glycolysis activation. These medications, however, have encountered drug resistance.28,29

The CRISPR-Cas9 device is the start of a new biotechnological era and a groundbreaking technology that is being used to treat lung cancer.6,29 The system works in two ways. The first is by designing sgRNA that looks for the mutated EGFR sequence, which is then accompanied by Cas9 protein. To do so, scientists created a CRISPR device that has complementary sequences with the mutated EGFR and introduced it into the patient, as mentioned earlier which has complementary sequences with the mutated EGFR and introducing this into the patient. As this complementary sequence binds to the mutated EGFR, the Cas9 protein (endonuclease) creates a double-stranded or single-stranded DNA break, depending on the type of enzyme used, followed by DNA repair mechanisms such as homologous or non-homologous DNA repair.29 If the receptor mutation is limited, there will be no contact between the ligand activator, resulting in no cell proliferation, neovascularization, or cancer metastasis, and the problem will be solved. The inhibition of EGFR by CRISPR-Cas9 increases the expression of major histocompatibility complex class I, which improves cytotoxic lymphocyte recognition and lysis of tumor cells.30,31 Off-target effects, which can induce genome instability, gene functional disturbances, and epigenetic alterations, are a challenge. Off-target effects of CRISPR-Cas9 systems, particularly when used for therapeutic purposes, should be minimized and precisely profiled. Off-target effects are separated into two categories: off-target binding and off-target cleavage. Cas9 can bind to target sequences that are partially complementary to sgRNA and inhibit target gene transcription without cleaving them.8 Off-target binding effects may thus be removed in traditional off-target identification approaches, such as using in vitro assembled sgRNA with a long-lasting association with cas9, which also has a high proportion of on-target and high efficiency for genome editing. Another technique is to use a Cas9 variant or modified Cas9 that can generate a single nick at one strand.23 So that the off-target effect is reduced.

The second, and equally significant, strategy for using this biotechnological method to treat lung cancer is to search for immune cells like lymphocytes. T cells are immune cells that are extracted from the blood of patients engaged in a clinical trial for lung cancer treatment in China, and then CRISPR-Cas9 is used to knock out a gene in the cells that encodes a protein called PD-1. The edited gene cells would then be propagated in the lab before being injected back into the patients bloodstream.6,25 Scientists took blood from the patient and extracted lymphocytes, which were then treated with a CRISPR-Cas9 gene-editing system containing a sgRNA sequence with a pattern identical to lymphocytes programmable death 1 protein (PD 1). When the system detects its target sequence, cas9 would sever the DNA, which is then repaired by cell repair mechanisms. When the expression of the PD 1 gene is blocked or disabled, cancerous cells lack the receptor on immune lymphocytes.6,25 As a result, if lymphocytes do not express the PD 1 receptor well, there will be less contact between the cancerous ligand and receptor, causing the T cell receptor to identify the problematic cell and perform its function. Naturally, these manipulated lymphocytes were screened for viability and lympho-proliferation to rule out new mutations, and only those cells that passed the test were returned to the patient.6,25 Furthermore, knocking out the PD-1 protein on immune cells is necessary for caspase activation, which is needed for programmed cell death and enhanced apoptosis in cancerous cells.31 It also concludes that PD-1-deficient cells have potent antitumor activity of cytotoxic lymphocytes. The hyperactivity of the manipulated T cells is one of the technologys drawbacks for use in this way6 and obtaining a safe and efficient delivery method, as well as some side effects Patients with advanced NSCLC with positive PD-1 expression were assigned to a Phase I clinical trial to assess the safety of CRISPR-Cas9-mediated knockout of PD-1 gene therapy in patients with metastatic non-small cell lung cancer. Nine patients were enrolled, and eight patients received PD-1 deficient T cell therapy, and the patients were manifested with PD-1 deficient T cell therapy.25 Patients undergoing PD-1 deficient T cell therapy, on the other hand, appeared to be healthy, and researchers recommended that broader studies be conducted to determine the most appropriate dosage and immune response.

In cancer biology, the CRISPR-Cas9 device has a bright future ahead of it,9, because it is a technology that is adaptable, simple, convenient and efficient.32,33 The method introduces a novel approach to cancer treatment by allowing for modifications to the genome of target cells, which was previously difficult to achieve.3436 the technologys versatility, effectiveness, and flexibility would make it the best form of cancer care in the future.4,37,38 It will affect cancer biology as a whole in the future,34 and if researchers have devised well-organized strategies and instruments for delivering the technology to the target cell or tissue, as well as effective methods and instructions for controlling and eliminating the technologys off-target effects.

The CRISPR-Cas9 device is a recent biotechnological breakthrough and scientific achievement. This technology has created a new treatment option for diseases of various origins, such as cancer and infectious disease. To solve the problem, the best sgRNA must be designed using a CRISPR tool (http://crispr.mit.edu) and its associated endonuclease cas9 protein against the target sequence. However, ethical concerns, the need for the best delivery strategies, and the risk of off-target effects are only a few of the problems that must be addressed. Since the technology is still in its infancy, researchers must devise simple methods and mechanisms to track and test its protection and efficacy. For a simple comparison, the benefits of this technology are simple, fast, relatively effective, relatively precise, and versatile, while the drawbacks are distribution is difficult, ethical problems are highly conservative, some off-target effects, and some adverse effects.

ATP, Adenosine triphosphate; CRISPR, Clustered regularly interspaced short palindromic repeat; CRISPR-Cas, Clustered regularly interspaced short palindromic repeat-associated; CrRNA, Clustered regularly interspaced short palindromic repeat ribonucleic acid; DNA, Deoxyribonucleic acid; DSB, Double-stranded break; EGFR, epidermal growth factor receptor; HDR, Homologous directed repair; mRNA, Messenger ribonucleic acid; NHEJ, Non-homologous end-joining; PD 1, Programmable death protein 1; RNA, Ribonucleic acid; SgRNA, Single guided ribonucleic acid; TracrRNA, Trans activating clustered regularly short palindromic repeat ribonucleic acid; TKIs, Tyrosine kinase inhibitors.

All authors made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; took part in drafting the article or revising it critically for important intellectual content; agreed to submit to the current journal; gave final approval of the version to be published; and agree to be accountable for all aspects of the work.

There is no funding to report.

The authors declare that they have no conflicts of interest for this work.

1. Liu T, Shen JK, Li Z, Choy E, Hornicek FJ, Duan Z. Development and potential applications of CRISPR-Cas9 genome editing technology in sarcoma. Cancer Lett. 2016;373(1):109118. doi:10.1016/j.canlet.2016.01.030

2. Yin H, Song CQ, Dorkin JR, et al. Therapeutic genome editing by combined viral and non-viral delivery of CRISPR system components in vivo. Nat Biotechnol. 2016;34(3):328333. doi:10.1038/nbt.3471

3. Zhen S, Li X. Oncogenic human papillomavirus: application of CRISPR/Cas9 therapeutic strategies for cervical cancer. Cell Physiol Biochem. 2017;44(6):24552466. doi:10.1159/000486168

4. Chen Y, Zhang Y. Application of the CRISPR/Cas9 system to drug resistance in breast cancer. Adv Sci. 2018;5(6):1700964. doi:10.1002/advs.201700964

5. Shen Q, Li J, Mai J, et al. Sensitizing non-small cell lung cancer to BCL-xL-targeted apoptosis. Cell Death Dis. 2018;9(10):13. doi:10.1038/s41419-018-1040-9

6. Castillo A. Gene editing for the treatment of lung cancer (CRISPR-Cas9). Colomb Med. 2016;47(4):178180. doi:10.25100/cm.v47i4.2856

7. Platt RJ, Chen S, Zhou Y, et al. CRISPR-Cas9 knockin mice for genome editing and cancer modeling. Cell. 2014;159(2):440455. doi:10.1016/j.cell.2014.09.014

8. Wen WS, Yuan ZM, Ma SJ, Xu J, Yuan DT. CRISPRCas9 systems: versatile cancer modeling platforms and promising therapeutic strategies. Int J Cancer. 2016;138(6):13281336. doi:10.1002/ijc.29626

9. Bhattacharjee R, Purkayastha KD, Adapa D, Choudhury A. CRISPR/Cas9 genome editing system in the diagnosis and treatment of cancer. J RNAi Gene Silencing. 2017;13:585591.

10. Gwiazda KS, Grier AE, Sahni J, et al. High-efficiency CRISPR/Cas9-mediated gene editing in primary human T-cells using mutant adenoviral E4orf6/E1b55k helper proteins. Mol Ther. 2016;24(9):15701580. doi:10.1038/mt.2016.105

11. Wang T, Wei JJ, Sabatini DM, Lander ES. Genetic screens in human cells using the CRISPR-Cas9 system. Science. 2014;343(6166):8084. doi:10.1126/science.1246981

12. Ran FA, Cong L, Yan WX, et al. In vivo genome editing using Staphylococcus aureus Cas9. Nature. 2015;520(7546):186191. doi:10.1038/nature14299

13. Gori JL, Hsu PD, Maeder ML, Shen S, Welstead GG, Bumcrot D. Delivery and specificity of CRISPR/Cas9 genome editing technologies for human gene therapy. Hum Gene Ther. 2015;26(7):443451. doi:10.1089/hum.2015.074

14. Shinmyo Y, Tanaka S, Tsunoda S, Hosomichi K, Tajima A, Kawasaki H. CRISPR/Cas9-mediated gene knockout in the mouse brain using in utero electroporation. Sci Rep. 2016;6(1):13. doi:10.1038/srep20611

15. Ratan ZA, Son YJ, Haidere MF, et al. CRISPR-Cas9: a promising genetic engineering approach in cancer research. Ther Adv Med Oncol. 2018;10:1758834018755089. doi:10.1177/1758834018755089

16. Jamal M, Ullah A, Ahsan M, et al. Treating genetic disorders using state-of-the-art technology. Curr Issues Mol Biol. 2017;26:3346. doi:10.21775/cimb.026.033

17. Kim EJ, Kang KH, Ju JH. CRISPR-Cas9: a promising tool for gene editing on induced pluripotent stem cells. Korean J Intern Med. 2017;32(1):42. doi:10.3904/kjim.2016.198

18. Liu C, Zhang L, Liu H, Cheng K. Delivery strategies of the CRISPR-Cas9 gene-editing system for therapeutic applications. J Control Release. 2017;266:1726. doi:10.1016/j.jconrel.2017.09.012

19. Snchez-Rivera FJ, Jacks T. Applications of the CRISPRCas9 system in cancer biology. Nat Rev Cancer. 2015;15(7):387393. doi:10.1038/nrc3950

20. Lino CA, Harper JC, Carney JP, Timlin JA. Delivering CRISPR: a review of the challenges and approaches. Drug Deliv. 2018;25(1):12341257. doi:10.1080/10717544.2018.1474964

21. McGinn J, Marraffini LA. Molecular mechanisms of CRISPRCas spacer acquisition. Nat Rev Microbiol. 2019;17(1):712. doi:10.1038/s41579-018-0071-7

22. Finn JD, Smith AR, Patel MC, et al. A single administration of CRISPR/Cas9 lipid nanoparticles achieves robust and persistent in vivo genome editing. Cell Rep. 2018;22(9):22272235. doi:10.1016/j.celrep.2018.02.014

23. Martinez-Lage M, Puig-Serra P, Menendez P, Torres-Ruiz R, Rodriguez-Perales S. CRISPR/Cas9 for cancer therapy: hopes and challenges. Biomedicines. 2018;6(4):105. doi:10.3390/biomedicines6040105

24. Kolli N, Lu M, Maiti P, Rossignol J, Dunbar GL. Application of the gene-editing tool, CRISPR-Cas9, for treating neurodegenerative diseases. Neurochem Int. 2018;112:187196. doi:10.1016/j.neuint.2017.07.007

25. Lu Y. PD-1 knockout engineered T cells for metastatic non-small cell lung cancer. ClinicalTrials.gov. 2019. doi:10.1016/j.compcom.2006.05.002

26. Doudna JA. The promise and challenge of therapeutic genome editing. Nature. 2020;578(7794):229236. doi:10.1038/s41586-020-1978-5

27. Pandey VK, Tripathi A, Bhushan R, Ali A, Dubey PK, Therapy G. Application of CRISPR/Cas9 genome editing in genetic disorders: a systematic review up to date. J Genet Syndr Gene Ther. 2017;8(2). doi:10.4172/2157-7412.1000321

28. Jiang C, Lin X, Zhao Z. Applications of CRISPR/Cas9 technology in the treatment of lung cancer. Trends Mol Med. 2019;25(11):10391049. doi:10.1016/j.molmed.2019.07.007

29. Tang H, Shrager JB. CRISPR/Casmediated genome editing to treat EGFRmutant lung cancer: a personalized molecular surgical therapy. EMBO Mol Med. 2016;8(2):8385. doi:10.15252/emmm.201506006

30. Lizotte PH, Hong RL, Luster TA, et al. A high-throughput immune-oncology screen identifies EGFR inhibitors as potent enhancers of antigen-specific cytotoxic T-lymphocyte tumor cell killing. Cancer Immunol Res. 2018;6(12):15111523. doi:10.1158/2326-6066.CIR-18-0193

31. Zhao Z, Shi L, Zhang W, et al. CRISPR knock out of programmed cell death protein 1 enhances the anti-tumor activity of cytotoxic T lymphocytes. Oncotarget. 2018;9(4):5208. doi:10.18632/oncotarget.23730

32. Zhang B. CRISPR/Cas gene therapy. J Cell Physiol. 2021;236(4):24592481.

33. Lu Y, Xue J, Deng T, et al. Safety and feasibility of CRISPR-edited T cells in patients with refractory non-small-cell lung cancer. Nat Med. 2020;26(5):732740. doi:10.1038/s41591-020-0840-5

34. Li H, Yang Y, Hong W, Huang M, Wu M, Zhao X. Applications of genome editing technology in the targeted therapy of human diseases: mechanisms, advances, and prospects. Signal Transduct Target Ther. 2020;5(1):123.

35. Xu M, Weng Q, Ji J. Applications and advances of CRISPR/Cas9 in an animal cancer model. Brief Funct Genomics. 2020;19(3):235241. doi:10.1093/bfgp/elaa002

36. Ma CC, Wang ZL, Xu T, He ZY, Wei YQ. The approved gene therapy drugs worldwide: from 1998 to 2019. Biotechnol Adv. 2020;40:107502. doi:10.1016/j.biotechadv.2019.107502

37. Hanna RE, Doench JG. Design and analysis of CRISPRCas experiments. Nat Biotechnol. 2020;38(7):813823. doi:10.1038/s41587-020-0490-7

38. Hong W, Huang M, Wei Y, Wei X. A new and promising application of gene editing: CRISPR-controlled smart materials for tissue engineering, bioelectronics, and diagnostics. Sci China Life Sci. 2019;62(11):15471549. doi:10.1007/s11427-019-1576-0

Read more from the original source:
Crispr-cas9 for the treatment of lung cancer | BTT - Dove Medical Press

Posted in Genetic Engineering | Comments Off

Human Genetics | Cincinnati Children’s

Posted: June 4, 2021 at 4:14 pm

Mission: The Division of Human Genetics at Cincinnati Childrens leverages genomic technology to provide world-class clinical care, train the next generation of caregivers and researchers, and develop new therapies for our patients and others like them around the world.

We work at the forefront of genomic medicine and research to diagnosis even the rarest diseases and provide outstanding care, as well as discover and implement therapies to improve the health of all children. As a leader in pediatric health, our approach is to integrate a culture of genomics through institution-wide collaboration in both research and clinical initiatives that cross every subspecialty at Cincinnati Childrens.

One focus of our division is the Genetics of Time. This allows us to concentrate on fetal development, premature birth, circadian rhythms related to sleep or taking medication, and mitochondrial disorders. These areas impact the clinical care we provide, as well as areas of research.

The Division of Human Genetics features three key areas:

In our clinics, we use a precision-medicine approach so that our geneticists, genetic counselors, advanced practice and registered nurses diagnose, manage and treat genetic diseases in children and adults taking into account individual variations and responses to treatment.

In addition, we provide comprehensive services through our Genetics and Genomics Diagnostic Laboratory, whichoffers leading-edge technology for biochemical, cytogenetic and molecular genetic testing for a variety of disorders.

The world of genomics is evolving rapidly and our investigators are at the front line of basic science discovery, as well as translational and clinical trial research. Our investigators ultimate goal is to bring genomics into medical care through discovery of better diagnoses, therapeutics and disease prevention. To do this, we use innovative methods to discover new genes and genetic mutations, diagnose and treat rare diseases, and gain deeper understanding of basic biological events, such as preterm birth or craniofacial development. Learn more about some of our key programs.

The Division of Human Genetics is a leader in genetics education. Cincinnati Childrens offers a genetics specialty residency and a genetics fellowship training program. And the Genetic Counseling Graduate Program is one of the oldest and largest such programs in the United States.

We also welcome graduate students and postdocs from other areas such as Molecular and Developmental Biology, Biomedical Informatics and Immunology who are interested in learning more about genetics and genomics.

In addition, we have a Grassroots Genomics Speaker Series a series of videos explaining genomics and how it is used in pediatric medicine and our Genomic Discovery & Translational Series of talks from outside speakers.

To learn more about genomics in the news, as well as about published research from our faculty, follow us on Twitter @CincyKidsGenomX.

Read the original here:
Human Genetics | Cincinnati Children's

Posted in Human Genetics | Comments Off

UMaine researchers: Culture drives human evolution more than genetics – UMaine News – University of Maine – University of Maine

Posted: at 4:14 pm

In a new study, University of Maine researchers found that culture helps humans adapt to their environment and overcome challenges better and faster than genetics.

After conducting an extensive review of the literature and evidence of long-term human evolution, scientists Tim Waring and Zach Wood concluded that humans are experiencing a special evolutionary transition in which the importance of culture, such as learned knowledge, practices and skills, is surpassing the value of genes as the primary driver of human evolution.

Culture is an under-appreciated factor in human evolution, Waring says. Like genes, culture helps people adjust to their environment and meet the challenges of survival and reproduction. Culture, however, does so more effectively than genes because the transfer of knowledge is faster and more flexible than the inheritance of genes, according to Waring and Wood.

Culture is a stronger mechanism of adaptation for a couple of reasons, Waring says. Its faster: gene transfer occurs only once a generation, while cultural practices can be rapidly learned and frequently updated. Culture is also more flexible than genes: gene transfer is rigid and limited to the genetic information of two parents, while cultural transmission is based on flexible human learning and effectively unlimited with the ability to make use of information from peers and experts far beyond parents. As a result, cultural evolution is a stronger type of adaptation than old genetics.

Waring, an associate professor of social-ecological systems modeling, and Wood, a postdoctoral research associate with the School of Biology and Ecology, have just published their findings in a literature review in the Proceedings of the Royal Society B, the flagship biological research journal of The Royal Society in London.

This research explains why humans are such a unique species. We evolve both genetically and culturally over time, but we are slowly becoming ever more cultural and ever less genetic, Waring says.

Culture has influenced how humans survive and evolve for millenia. According to Waring and Wood, the combination of both culture and genes has fueled several key adaptations in humans such as reduced aggression, cooperative inclinations, collaborative abilities and the capacity for social learning. Increasingly, the researchers suggest, human adaptations are steered by culture, and require genes to accommodate.

Waring and Wood say culture is also special in one important way: it is strongly group-oriented. Factors like conformity, social identity and shared norms and institutions factors that have no genetic equivalent make cultural evolution very group-oriented, according to researchers. Therefore, competition between culturally organized groups propels adaptations such as new cooperative norms and social systems that help groups survive better together.

According to researchers, culturally organized groups appear to solve adaptive problems more readily than individuals, through the compounding value of social learning and cultural transmission in groups. Cultural adaptations may also occur faster in larger groups than in small ones.

With groups primarily driving culture and culture now fueling human evolution more than genetics, Waring and Wood found that evolution itself has become more group-oriented.

In the very long term, we suggest that humans are evolving from individual genetic organisms to cultural groups which function as superorganisms, similar to ant colonies and beehives, Waring says. The society as organism metaphor is not so metaphorical after all. This insight can help society better understand how individuals can fit into a well-organized and mutually beneficial system. Take the coronavirus pandemic, for example. An effective national epidemic response program is truly a national immune system, and we can therefore learn directly from how immune systems work to improve our COVID response.

Waring is a member of the Cultural Evolution Society, an international research network that studies the evolution of culture in all species. He applies cultural evolution to the study of sustainability in social-ecological systems and cooperation in organizational evolution.

Wood works in the UMaine Evolutionary Applications Laboratory managed by Michael Kinnison, a professor of evolutionary applications. His research focuses on eco-evolutionary dynamics, particularly rapid evolution during trophic cascades.

Contact: Marcus Wolf, 207.581.3721; marcus.wolf@maine.edu

Go here to read the rest:
UMaine researchers: Culture drives human evolution more than genetics - UMaine News - University of Maine - University of Maine

Posted in Human Genetics | Comments Off

Primordial Genetics Grants Arcturus Therapeutics Exclusive License of an RNA Polymerase for Human and Animal Therapeutics – PRNewswire

Posted: at 4:14 pm

SAN DIEGO, June 2, 2021 /PRNewswire/ -- Primordial Genetics ("Primordial"), a synthetic biology company developing enzymatic production systems for nucleic acids, today announced granting Arcturus Therapeutics Holdings Inc.("Arcturus",Nasdaq: ARCT), a clinical-stage messenger RNA (mRNA) medicines company, an exclusive license of an enzyme for an RNA polymerase (RNApol). The enzyme was discovered by Primordial to meet the challenge of manufacturing high-quality, long RNAs for therapeutic applications.

mRNA based medicines represent a promising new approach to drug and vaccine development. Primordial owns proprietary technology relating to RNA manufacturing, specifically its collection of RNA polymerase genes, promoters, and proteins that may be used to synthesize RNA. Primordial is focused on developing improved RNApols for higher efficiency and lower cost manufacturing of mRNAs used in therapeutics and vaccines.

"We look forward to the meaningful achievements Arcturus can make with this licensed Primordial Genetics RNA polymerase, from clinical trials to a marketable RNA product that can be used in pharmaceuticals to improve or save lives," said Helge Zieler, PhD, founder and President of Primordial Genetics. "We are thrilled for this Primordial and Arcturus collaboration that meets the core of our mission to connect innovation with social needs via new, biologically-based alternatives to traditional therapeutics.

About Primordial Genetics

Primordial Genetics is a synthetic biology company founded in 2013 and based in San Diego, California. The company is the world leader in constructive biology; a revolutionary new way of practicing biotechnology that creates novel genes from genomic building blocks to accelerate the evolution of highly efficient enzymes and microbes. Primordial's product focus is to develop efficient production processes for DNA and RNA manufacturing to enable biologically-based alternatives to traditional therapeutics, nutritional products, agriculture and fuels. For more information, visit: http://www.primordialgenetics.com

SOURCE Primordial Genetics

http://www.primordialgenetics.com

More:
Primordial Genetics Grants Arcturus Therapeutics Exclusive License of an RNA Polymerase for Human and Animal Therapeutics - PRNewswire

Posted in Human Genetics | Comments Off

D. Wade Walke, Ph.D. Joins 23andMe as Vice President of Investor Relations – PRNewswire

Posted: at 4:14 pm

SUNNYVALE, Calif., June 2, 2021 /PRNewswire/ -- 23andMe Inc., a leading consumer genetics and research company, today announced that D. Wade Walke, Ph.D. will join the company as Vice President of Investor Relations. Earlier this year, 23andMe entered into a definitive merger agreement with VG Acquisition Corp. (NYSE: VGAC), a special purpose acquisition company sponsored by Virgin Group, to become a publicly-traded company. Walke will be responsible for demonstrating 23andMe's vision and long-term value with its shareholders and the financial community as the company transitions to the public markets.

"With his extensive background developing and implementing strategic investor relations programs within the biotech space, we are confident that Wade is the ideal fit to help build and shape 23andMe's future IR program," said Steve Schoch, Chief Financial Officer of 23andMe. "Studying genetics early in his career, Wade brings a deep scientific background and he will undoubtedly help the investment community appreciate the significant value-building opportunity that lies ahead in both 23andMe's consumer and biotechnology segments. He also brings a strong network of relationships with buy-side and sell-side healthcare analysts and institutional investors."

"I am excited to join 23andMe at this unique time of transition. I have been following the company closely for many years now, and it is evident to me that the team at 23andMe has worked diligently to create innovative, impactful and actionable insights for its entire customer base," said Dr. Walke. "In particular, I've been impressed with the recent work 23andMe has done to build a personalized health and wellness experience that brings so much value to the individual customer. I am very much looking forward to working closely with Anne, Steve, the entire team and, most importantly, our global shareholder base as 23andMe begins its next phase of growth."

Prior to joining 23andMe, Walke spent nine years at Ionis Pharmaceuticals, a leading company in RNA-targeted drug discovery and development, where he most recently served as Vice President of Investor Relations. During his time there, he was ranked as one of the top IR professionals three years in a row (2017 - 2019) by Institutional Investor magazine's "All-American Executive Team" (Biotechnology) rankings.

Prior to joining Ionis Pharmaceuticals, Walke also spent 14 years at Lexicon Pharmaceuticals, where he began as a Scientist and worked his way up to Associate Director of Bioinformatics in the Department of Functional Genomics. From there, he pivoted to lead Communications and Investor Relations for the company, where he oversaw the implementation of a targeted program of IR activities. Walke holds a Bachelor of Science degree from Brigham Young University and a Ph.D. and Master of Science degree from the University of Michigan.

About 23andMe23andMe, Inc., headquartered in Sunnyvale, CA, is a leading consumer genetics and research company. Founded in 2006, the company's mission is to help people access, understand, and benefit from the human genome. 23andMe has pioneered direct access to genetic information as the only company with multiple FDA authorizations for genetic health risk reports. The company has created the world's largest crowdsourced platform for genetic research, with 80 percent of its customers electing to participate. The 23andMe research platform has generated more than 180 publications on the genetic underpinnings of a wide range of diseases, conditions and traits. The platform also powers the 23andMe Therapeutics group, currently pursuing drug discovery programs rooted in human genetics across a spectrum of disease areas, including oncology, respiratory, and cardiovascular diseases, in addition to other therapeutic areas. More information is available at http://www.23andMe.com.

Forward-Looking StatementsThis communication contains certain "forward-looking statements" including statements regarding the Company's ability to timely prepare and file the Quarterly Report. The words "anticipate," "believe," "continue," "could," "estimate," "expect," "intends," "may," "might," "plan," "possible," "potential," "predict," "project," "should," "would," and similar expressions may identify forward-looking statements, but the absence of these words does not mean that a statement is not forward-looking. The forward-looking statements contained herein are based on the Company's current expectations and beliefs concerning future developments and their potential effects, but there can be no assurance that these will be as anticipated. These forward-looking statements involve a number of risks, uncertainties (some of which are beyond the control of the Company), or other assumptions that may cause actual results or performance to be materially different from those expressed or implied by these forward-looking statements. These factors include, among others: the inability to complete the proposed business combination with VGAC (the "Business Combination"), including due to the failure to receive required security holder approvals, or the failure of other closing conditions. Except as required by law, the Company does not undertake any obligation to update or revise any forward-looking statements whether as a result of new information, future events, or otherwise.

Additional InformationVGAC has filed with the Securities and Exchange Commission (the "SEC") a Registration Statement on Form S-4, as amended (the "Form S-4"), which included the definitive proxy statement of VGAC, a prospectus, and 23andMe's consent solicitation statement. The Form S-4 was declared effective on May 14, 2021. The definitive proxy statement/prospectus and other proxy materials were mailed to VGAC's shareholders of record as of the close of business on May 5, 2021. Shareholders of VGAC and other interested persons are advised to read the Form S-4, the definitive proxy statement/prospectus included in the Form S-4, and documents incorporated by reference therein filed in connection with the proposed Business Combination because these documents contain important information about VGAC, 23andMe, and the Business Combination. Shareholders will also be able to obtain copies of the Form S-4 and the proxy statement/prospectus, without charge, by directing a request to: VG Acquisition Corp. 65 Bleecker Street, 6th Floor, New York NY 10012. These documents and VGAC's annual and other reports filed with the SEC can also be obtained, without charge, at the SEC's internet site (https://www.sec.gov).

The date of VGAC's extraordinary general meeting of shareholders to vote on the proposed Business Combination has been set for June 10, 2021. VGAC's shareholders of record as of the close of business on May 5, 2021 are entitled to vote on matters that come before the extraordinary general meeting, including the proposed Business Combination. The Business Combination, if approved by VGAC's shareholders, is expected to close as soon as practicable following the extraordinary general meeting.

This communication does not constitute an offer to sell or the solicitation of an offer to buy any securities, or a solicitation of any vote or approval, nor shall there be any sale of securities in any jurisdiction in which such offer, solicitation, or sale would be unlawful prior to registration or qualification under the securities laws of any such jurisdiction.

Participants in the SolicitationVGAC, 23andMe, and their respective directors, executive officers, other members of management, and employees may be deemed to be participants in the solicitation of proxies from VGAC's shareholders in connection with the Business Combination. Information regarding the names and interests in the proposed Business Combination of VGAC's directors and officers is contained in VGAC's filings with the SEC. Additional information regarding the interests of such potential participants in the solicitation process is included in the Form S-4 (and the definitive proxy statement/prospectus) and other relevant documents filed with the SEC.

SOURCE 23andMe Inc.

http://www.23andMe.com

Posted in Human Genetics | Comments Off

A bug in the system the difficulties of linking the microbiome to cancer aetiology – Cancer Research UK

Posted: at 4:14 pm

Variations in the human gut microbiome have been linked to cancer an exciting prospect for cancer prevention, but teasing apart causation from correlation is no easy task says Dr Kaitlin Wade

Cancer remains one of the leading causes of death worldwide as well as one of the greatest economical burdens on health care systems. And yet, evidence indicates that over 40% of all cancers are likely explained by preventable causes.

One of the main challenges is identifying so-called modifiable risk factors for cancer aspects of our environment that we can change to reduce the incidence of disease. One very promising avenue of research has been the gut microbiome. There is growing evidence from human and predominantly mouse models supporting the relationship between the human gut microbiome and cancer aetiology.

Human studies have largely been observational, and investigations have so far been unable to offer convincing causal evidence

We know the gut microbiome can have a substantial impact on host metabolism, inflammation, and immune response to external infections, so there are many plausible biological mechanisms by which it could influence cancer development and progression. However, findings have been inconsistent, or even contradictory, and very few hypotheses have been reliably supported with data from multiple model organisms.

Human studies have largely been observational, and investigations have so far been unable to offer convincing causal evidence. This isnt helped by several important limitations in the design of studies and analyses of data linking the gut microbiome and cancer aetiology. Common causes of gut microbiome variation and cancer (confounding), the ability for cancer to influence the gut microbiome (reverse causation) and various biases can distort results. This, of course, affects our ability to find out what variation in the human gut microbiome, if any, may cause cancer. Distinguishing correlation from causation therefore requires very precise data analysis.

The gut microbiome is a complex system of microorganisms aiding digestion, providing protection against pathogens and creating essential metabolites. Variation in the gut microbiome has been linked to many common cancers.

Taking colorectal cancer (CRC) as an example, there is compelling in vivo and in vitro evidence that modifying gut microbiota may reduce the incidence of the disease. Alongside this, epidemiological studies suggest a lower microbiota diversity in people with CRC. There is also research showing lower levels of some bacteria, such as Bifidobacterium and Roseburia, as well as higher levels of others, such as Fusobacterium and Porphyromonas, in those with CRC.

Despite a lack of causal evidence, there is still a growing market for commercial products targeting the microbiome

Despite a lack of causal evidence, there is still a growing market for commercial products targeting the microbiome several companies now offer sequencing of faecal samples and prescribe personalised nutritional information. There is controversy around this given the uncertainty of the likely impact, which is not helped by a lack of consistency between observational studies and large-scale randomised controlled trials. Something which is clearly a barrier when trying to harness the gut microbiome to tackle disease. What this does highlight though, is the public demand for such information which could suggest an untapped opportunity to make important population-based health interventions. Therefore, we need alternative approaches to interrogate causality and tease apart the links between the gut microbiome and cancer aetiology.

One way of improving causal inference has been the integration of human genetic variation within population health sciences. With the growth in genome-wide association studies (GWASs), we now know thousands of genetic variants across the genome that influence almost every aspect of human physiology and even elements of behaviour.

We need alternative approaches to interrogate causality and tease apart the links between the gut microbiome and cancer aetiology

Within the last few years, GWAS has been used to understand the relationships between human genetic variation and the gut microbiome. These studies have provided evidence for the contributions of human genetics on features of the gut microbiome such as diversity, abundance and enterotype. While this is not in itself causal evidence, knowledge of the relationships between human genetic variation and various characteristics has provided an opportunity to tease out causality from observational epidemiological associations.

Established in the early 2000s and applied mainly to understand the links between modifiable risk factors and cardiometabolic diseases, Mendelian randomisation (MR) is a method that enables the interrogation of causality.

MR utilises human germline genetic variation usually single nucleotide polymorphisms to help investigate whether the gut microbiome changes the risk of cancer or whether cancer changes the gut microbiome. Genetic variation cant be influenced by the gut microbiome or disease. Therefore, if people who are genetically predisposed to having a higher abundance of certain bacteria within their gut also have a lower risk of cancer, this would strongly suggest a causal and protective role of those bacteria in cancer aetiology.

With the recent growth in GWASs focusing on the gut microbiome, there have been a handful of studies applying MR to assess the impacts of gut microbiome variation on several cardiometabolic, inflammatory and auto-immune diseases. As yet however, there are no studies that focus on the appropriate application of these methodologies to cancer something I aim to change as part of my Cancer Research UK fellowship. I plan to use human genetic information to shed light on the relationship between the gut microbiome and cancer aetiology.

Knowledge of the relationships between human genetic variation and various characteristics has provided an opportunity to tease out causality from observational epidemiological associations

Using MR should largely avoid the limitations of observational epidemiological studies however, the specifics of the way the method is applied is very important and is something that can be hard to get right. Clearly, I want to ensure my results give a reliable indication of causality. So, first order of business for this study will be to apply a more robust way to tease apart correlation from causation. To be able to do this, there are a number of caveats to the current use of MR in the field that need to be considered carefully.

These caveats centre around the core assumptions of the MR framework. First, that human genetic variation must be associated with the gut microbiome. Second, that there must be no confounding that is to say common causes of the gut microbiome and cancer and, third, there must be no relationship between microbiome-related genetic variation and cancer independent of the gut microbiome. However, the current applications of MR to try and understand the role of the gut microbiome on health outcomes rarely consider these caveats carefully enough.

The appropriate application of MR to interrogate causality of the gut microbiome in cancer has begun to show promise. However, early work has also highlighted the importance of inter-disciplinary collaboration between population health, genetic and basic sciences. We really do need a triangulation of evidence to unpick causation from correlation. Any research conducted within one discipline cannot provide concrete evidence to support or challenge the role of the gut microbiome in cancer aetiology.

I am hopeful with this Fellowship, and the support from my team of experts in microbiology, basic sciences and population health sciences, we can take a new and important step towards refining the current applications of complex integrative methodologies in cancer research. And it is this which will in turn allow more accurate evaluation of potential treatments or protective factors for cancer prevention.

About the author

Dr Kaitlin Wade is a lecturer in epidemiology and Co-Director of the MSc in Epidemiology in the MRC Integrative Epidemiology Unit based at the University of Bristol. She was awarded a Cancer Research UK Population Research Postdoctoral Fellowship in 2020.

AcknowledgementsThe research conducted as part of my CRUK Population Research Postdoctoral Fellowship will be supported by the following collaborators: Nicholas Timpson, Caroline Relton, Jeroen Raes, Trevor Lawley, Lindsay Hall and Marc Gunter. Additional thanks to Chloe Russell, who supplied the image for this piece.

Human Genetics Market is Thriving Worldwide with Top Growing Companies QIAGEN, Agilent Technologies, Thermo Fisher Scientific The Almanian – The…

Posted: at 4:14 pm

LOS ANGELES, United States: QY Research offers an overarching research and analysis-based study on, Global Human Genetics Market Report, History and Forecast 2016-2027, Breakdown Data by Companies, Key Regions, Types and Application. This report offers an insightful take on the drivers and restraints present in the market. Human Genetics data reports also provide a 5 year pre-historic and forecast for the sector and include data on socio-economic data of global. Key stakeholders can consider statistics, tables & figures mentioned in this report for strategic planning which lead to success of the organization. It sheds light on strategic production, revenue, and consumption trends for players to improve sales and growth in the global Human Genetics Market. Here, it focuses on the recent developments, sales, market value, production, gross margin, and other significant factors of the business of the major players operating in the global Human Genetics Market. Players can use the accurate market facts and figures and statistical studies provided in the report to understand the current and future growth of the global Human Genetics market.

This report includes assessment of various drivers, government policies, technological innovations, upcoming technologies, opportunities, market risks, restrains, market barriers, challenges, trends, competitive landscape, and segments which gives an exact picture of the growth of the global Human Genetics market.

Competitive Landscape

Competitor analysis is one of the best sections of the report that compares the progress of leading players based on crucial parameters, including market share, new developments, global reach, local competition, price, and production. From the nature of competition to future changes in the vendor landscape, the report provides in-depth analysis of the competition in the global Human Genetics market.

Key questions answered in the report:

Table of Contents

1 Market Overview of Human Genetics1.1 Human Genetics Market Overview1.1.1 Human Genetics Product Scope1.1.2 Human Genetics Market Status and Outlook1.2 Global Human Genetics Market Size Overview by Region 2016 VS 2021VS 20271.3 Global Human Genetics Market Size by Region (2016-2027)1.4 Global Human Genetics Historic Market Size by Region (2016-2021)1.5 Global Human Genetics Market Size Forecast by Region (2022-2027)1.6 Key Regions, Human Genetics Market Size (2016-2027)1.6.1 North America Human Genetics Market Size (2016-2027)1.6.2 Europe Human Genetics Market Size (2016-2027)1.6.3 Asia-Pacific Human Genetics Market Size (2016-2027)1.6.4 Latin America Human Genetics Market Size (2016-2027)1.6.5 Middle East & Africa Human Genetics Market Size (2016-2027) 2 Human Genetics Market Overview by Type2.1 Global Human Genetics Market Size by Type: 2016 VS 2021 VS 20272.2 Global Human Genetics Historic Market Size by Type (2016-2021)2.3 Global Human Genetics Forecasted Market Size by Type (2022-2027)2.4 Cytogenetics2.5 Prenatal Genetics2.6 Molecular Genetics2.7 Symptom Genetics 3 Human Genetics Market Overview by Application3.1 Global Human Genetics Market Size by Application: 2016 VS 2021 VS 20273.2 Global Human Genetics Historic Market Size by Application (2016-2021)3.3 Global Human Genetics Forecasted Market Size by Application (2022-2027)3.4 Research Center3.5 Hospital3.6 Forensic Laboratories 4 Human Genetics Competition Analysis by Players4.1 Global Human Genetics Market Size by Players (2016-2021)4.2 Global Top Players by Company Type (Tier 1, Tier 2 and Tier 3) & (based on the Revenue in Human Genetics as of 2020)4.3 Date of Key Players Enter into Human Genetics Market4.4 Global Top Players Human Genetics Headquarters and Area Served4.5 Key Players Human Genetics Product Solution and Service4.6 Competitive Status4.6.1 Human Genetics Market Concentration Rate4.6.2 Mergers & Acquisitions, Expansion Plans 5 Company (Top Players) Profiles and Key Data5.1 QIAGEN5.1.1 QIAGEN Profile5.1.2 QIAGEN Main Business5.1.3 QIAGEN Human Genetics Products, Services and Solutions5.1.4 QIAGEN Human Genetics Revenue (US$ Million) & (2016-2021)5.1.5 QIAGEN Recent Developments5.2 Agilent Technologies5.2.1 Agilent Technologies Profile5.2.2 Agilent Technologies Main Business5.2.3 Agilent Technologies Human Genetics Products, Services and Solutions5.2.4 Agilent Technologies Human Genetics Revenue (US$ Million) & (2016-2021)5.2.5 Agilent Technologies Recent Developments5.3 Thermo Fisher Scientific5.5.1 Thermo Fisher Scientific Profile5.3.2 Thermo Fisher Scientific Main Business5.3.3 Thermo Fisher Scientific Human Genetics Products, Services and Solutions5.3.4 Thermo Fisher Scientific Human Genetics Revenue (US$ Million) & (2016-2021)5.3.5 Illumina Recent Developments5.4 Illumina5.4.1 Illumina Profile5.4.2 Illumina Main Business5.4.3 Illumina Human Genetics Products, Services and Solutions5.4.4 Illumina Human Genetics Revenue (US$ Million) & (2016-2021)5.4.5 Illumina Recent Developments5.5 Promega5.5.1 Promega Profile5.5.2 Promega Main Business5.5.3 Promega Human Genetics Products, Services and Solutions5.5.4 Promega Human Genetics Revenue (US$ Million) & (2016-2021)5.5.5 Promega Recent Developments5.6 LabCorp5.6.1 LabCorp Profile5.6.2 LabCorp Main Business5.6.3 LabCorp Human Genetics Products, Services and Solutions5.6.4 LabCorp Human Genetics Revenue (US$ Million) & (2016-2021)5.6.5 LabCorp Recent Developments5.7 GE5.7.1 GE Profile5.7.2 GE Main Business5.7.3 GE Human Genetics Products, Services and Solutions5.7.4 GE Human Genetics Revenue (US$ Million) & (2016-2021)5.7.5 GE Recent Developments 6 North America6.1 North America Human Genetics Market Size by Country (2016-2027)6.2 United States6.3 Canada 7 Europe7.1 Europe Human Genetics Market Size by Country (2016-2027)7.2 Germany7.3 France7.4 U.K.7.5 Italy7.6 Russia7.7 Nordic7.8 Rest of Europe 8 Asia-Pacific8.1 Asia-Pacific Human Genetics Market Size by Region (2016-2027)8.2 China8.3 Japan8.4 South Korea8.5 Southeast Asia8.6 India8.7 Australia8.8 Rest of Asia-Pacific 9 Latin America9.1 Latin America Human Genetics Market Size by Country (2016-2027)9.2 Mexico9.3 Brazil9.4 Rest of Latin America 10 Middle East & Africa10.1 Middle East & Africa Human Genetics Market Size by Country (2016-2027)10.2 Turkey10.3 Saudi Arabia10.4 UAE10.5 Rest of Middle East & Africa 11 Human Genetics Market Dynamics11.1 Human Genetics Industry Trends11.2 Human Genetics Market Drivers11.3 Human Genetics Market Challenges11.4 Human Genetics Market Restraints 12 Research Finding /Conclusion 13 Methodology and Data Source13.1 Methodology/Research Approach13.1.1 Research Programs/Design13.1.2 Market Size Estimation13.1.3 Market Breakdown and Data Triangulation13.2 Data Source13.2.1 Secondary Sources13.2.2 Primary Sources13.3 Disclaimer13.4 Author List

About Us:

QYResearch always pursuits high product quality with the belief that quality is the soul of business. Through years of effort and supports from huge number of customer supports, QYResearch consulting group has accumulated creative design methods on many high-quality markets investigation and research team with rich experience. Today, QYResearch has become the brand of quality assurance in consulting industry.

The rest is here:
Human Genetics Market is Thriving Worldwide with Top Growing Companies QIAGEN, Agilent Technologies, Thermo Fisher Scientific The Almanian - The...

Posted in Human Genetics | Comments Off

Body mass index and osteoarthritis risk | IJGM – Dove Medical Press

Posted: at 4:14 pm

Introduction

Osteoarthritis, a common disease of the musculoskeletal system, is an important cause of pain and disability in the elderly.1 Although joint replacement is effective for treating end-stage osteoarthritis, problems such as poor joint function recovery and limited lifetime of artificial joint hinder further improvement in prognosis. Therefore, the management of the disease is shifting to the prevention and early treatment of osteoarthritis.1,2 Overweight and obesity have been identified as risk factors of the occurrence and progression of osteoarthritis,35 and relief of symptoms was observed in patients with osteoarthritis who had undergone diet and exercise therapy.5,6 However, a causal effect of overweight or obesity on osteoarthritis cannot be convincingly established with evidence from observational studies, in which there is a lack of randomization of exposure factors and therefore confounding and reverse causality cannot be ruled out in the observed association. Traditional randomized clinical controlled trials are suitable from the viewpoint of methodology, but are not practicable due to ethical concern.

Mendelian randomization (MR) is a method that used genetic variations as instrumental variables of exposure factors to infer the causal relationship between exposure factors and outcomes. Because genetic variations follow the law of Mendelian and are randomly distributed in the population, the influence of confounding factors are largely controlled.7 With the popularity of genome-wide association study (GWAS) studies and GWAS meta-analysis, MR becomes an efficient and practicable method to investigate causal effect.8 The two-sample MR is a method to estimate the causal effect of an exposure on an outcome using only summary statistics from GWAS, in which genetic variation-exposure factor association data and genetic variation-disease outcome association data from two independent samples with similar distribution characteristics were used. In the study, we used the two-sample MR method based on GWAS data to analyze whether there is a causal effect of body mass index (BMI) on the risk of osteoarthritis.

Publicly accessible data for genetic variants associated with BMI were obtained from the Genetic Investigation of ANthropometric Traits (GIANT) Consortium.9 The detail of studies and datasets was presented in Table 1. The consortium included 3,339,224 participants and the number of included single nucleotide polymorphism (SNP) was 2,555,511. To minimize the impact caused by linkage disequilibrium (LD), we set the threshold of statistical significance as P <5108; LD r2 <0.1 to identify the SNPs associated with BMI. In total, there were 79 SNPs included in this study (rs1000940, rs10132280, rs1016287, rs10182181, rs10733682, rs10840100, rs11030104, rs11057405, rs11165643, rs11672660, rs1167827, rs11727676, rs12286929, rs12429545, rs12448257, rs12940622, rs12986742, rs13021737, rs13078960, rs13107325, rs13130484, rs13191362, rs13201877, rs13329567, rs1421085, rs1441264, rs1460676, rs14810, rs1516725, rs1528435, rs16851483, rs17001654, rs17066856, rs17094222, rs17203016, rs17381664, rs17724992, rs1928295, rs2033529, rs2060604, rs2112347, rs2176598, rs2183825, rs2365389, rs2820292, rs2836754, rs2890652, rs3736485, rs3800229, rs3817334, rs3849570, rs3888190, rs4740619, rs4889606, rs543874, rs6091540, rs6457796, rs6477694, rs6567160, rs657452, rs6713510, rs6804842, rs7138803, rs7144011, rs7531118, rs7550711, rs7599312, rs7715256, rs7899106, rs7903146, rs879620, rs891389, rs9304665, rs9374842, rs943005, rs9540493, rs9579083, rs977747, and rs9926784). The variation in the included SNPs was 2.7%. The F value was 5,529, which was larger than 10 and suggested the strength of the instrumental variable was not weak.10 As a result, all these SNPs were included into the study.

Table 1 Details of Studies and Datasets Used in the Study

The GWAS summary data for osteoarthritis were obtained from MRC Integrative Epidemiology Unit (MRC-IEU) consortium, which was published in 2018 and available through the UK Biobank.11 The sample size was 462,933, with 38,472 cases and 424,461 participants in the control group. The number of SNP included in the study was 9,851,867. All the above SNPs associated with BMI were found in MRC-IEU consortium.

After data from the GWAS study or GWAS meta-analysis associated with BMI or osteoarthritis were obtained via MR-Base platform,12 MR analysis was further carried out using the package TwoSampleMR of the R program (version 3.4.2). Three statistical methods including inverse-variance weighted (IVW) method, weighted median estimator, and MR-Egger regression were used to investigate the causal relationship between BMI and osteoarthritis.1215 The IVW method is the method to assess the causal relationship by the meta-analysis of every Wald ratio for the included SNPs.12,13 Significantly, there is a premise for the IVW method that all the included SNPs must be valid variables. Unlike the IVW method, the MR-Egger regression can still function when all the SNPs are invalid.15 The slope of MR-Egger indicates the effect of BMI on osteoarthritis when the intercept term is zero or without statistical significance.12,15 The weighted median estimator was intermediate and the valid variables must be no less than 50%.14 The result of the weighted median estimator was the median when the effect estimations of each single SNP are sorted in the order of weight values. The estimation of the causal relationship between BMI and osteoarthritis was expressed as odds ratio (OR) and its 95% confidence interval (CI). A P value less than 0.05 indicates that the difference is statistically significant.

The method of leave-one-out method was utilized to investigate the sensitivity of the results. Similar to the meta-analysis, we removed the single SNP one by one and calculated the effect of the remaining SNPs by the IVW method.16 In this way, we examined the effect of individual SNP on the causal inference.

The details of each SNP were presented in Table 2, including the chromosome location, genes, effect allele (EA), and effect allele frequency (EAF). Estimations of the associations of each SNP with BMI and osteoarthritis including beta value, standard error (SE) and P value were also presented in Table 2. Among them, 17 SNPs, namely rs13107325 ( 0.0096; SE 0.0011; P<0.001), rs6457796 ( 0.0025; SE 0.0006; P<0.001), rs3736485 ( 0.0017; SE 0.0006; P<0.001), rs2836754 ( 0.0016; SE 0.0006; P 0.01), rs2820292 ( 0.0014; SE 0.0006; P 0.02), rs6477694 ( 0.0012; SE 0.0006; P 0.04), rs11030104 ( 0.0029; SE 0.0007; P <0.001), rs3849570 ( 0.0012; SE 0.0006; P 0.04), rs16851483 ( 0.0029; SE 0.0012; P 0.01), rs891389 ( 0.0012; SE 0.0006; P 0.05), rs1516725 ( 0.0023; SE 0.0008; P 0.01), rs10182181 ( 0.0013; SE 0.0006; P 0.02), rs13021737 ( 0.0026; SE 0.0008; P <0.001), rs7138803 ( 0.0013; SE 0.0006; P 0.03), rs7531118 ( 0.0012; SE 0.0006; P 0.04), rs6567160 ( 0.0017; SE 0.0007; P 0.01), and rs1421085 ( 0.0013; SE 0.0006; P 0.03), were significantly associated with both BMI and osteoarthritis.

As presented in Table 3, result of the IVW method suggested that there was a positive association between BMI with higher genetic predictability for the risk of osteoarthritis (OR 1.028, 95% CI 1.0211.036). The weighted median estimator and MR-Egger method showed consistent results (the weighted median estimator: OR 1.028, 95% CI 1.0191.037; MR-Egger Method: OR 1.028, 95% CI 1.0091.046). These results could also be observed in the forest plot (Figure 1) and the scatter diagram (Figure 2).

Table 3 Causal Associations Between Genetically Determined BMI and Osteoarthritis

Figure 1 Forest plot of single nucleotide polymorphisms (SNPs) associated with body mass index (BMI) and the risk of osteoarthritis. Black points represent the log odds ratio (OR) for osteoarthritis per standard deviation (SD) increase in BMI, which is produced by using each SNP selected as a separate instrument (rs1000940, rs10132280, rs1016287, rs10182181, rs10733682, rs10840100, rs11030104, rs11057405, rs11165643, rs11672660, rs1167827, rs11727676, rs12286929, rs12429545, rs12448257, rs12940622, rs12986742, rs13021737, rs13078960, rs13107325, rs13130484, rs13191362, rs13201877, rs13329567, rs1421085, rs1441264, rs1460676, rs14810, rs1516725, rs1528435, rs16851483, rs17001654, rs17066856, rs17094222, rs17203016, rs17381664, rs17724992, rs1928295, rs2033529, rs2060604, rs2112347, rs2176598, rs2183825, rs2365389, rs2820292, rs2836754, rs2890652, rs3736485, rs3800229, rs3817334, rs3849570, rs3888190, rs4740619, rs4889606, rs543874, rs6091540, rs6457796, rs6477694, rs6567160, rs657452, rs6713510, rs6804842, rs7138803, rs7144011, rs7531118, rs7550711, rs7599312, rs7715256, rs7899106, rs7903146, rs879620, rs891389, rs9304665, rs9374842, rs943005, rs9540493, rs9579083, rs977747, and rs9926784). Red points show the combined causal estimate using all SNPs together as a single instrument, using the three different methods (the inversevariance weighted (IVW) method, weighted median estimator, and MREgger). Horizontal line segments denote 95% confidence intervals of the estimate.

Figure 2 Scatter plot of SNPs associated with BMI and the risk of osteoarthritis. The plot presents the effect sizes of the SNP-BMI association (x-axis, SD units) and the SNP-osteoarthritis association (y-axis, log (OR)) with 95% confidence intervals. The regression slopes of the lines correspond to causal estimates using the three Mendelian randomization (MR) methods (the IVW method, weighted median estimator, and MREgger).

There was no evidence that the result was affected by genetic pleiotropy (MR-Egger regression intercept=1.3105, SE=0.00025, P=0.959). From the result of the Leave-one-out method, there was no single SNP playing a decisive role in the causal inference (Figure 3).

Figure 3 Leave-one-out of SNPs associated with BMI and their risk of osteoarthritis. Each black point represents result of the IVW MR method applied to estimate the causal effect of BMI on osteoarthritis excluding particular SNP (rs1000940, rs10132280, rs1016287, rs10182181, rs10733682, rs10840100, rs11030104, rs11057405, rs11165643, rs11672660, rs1167827, rs11727676, rs12286929, rs12429545, rs12448257, rs12940622, rs12986742, rs13021737, rs13078960, rs13107325, rs13130484, rs13191362, rs13201877, rs13329567, rs1421085, rs1441264, rs1460676, rs14810, rs1516725, rs1528435, rs16851483, rs17001654, rs17066856, rs17094222, rs17203016, rs17381664, rs17724992, rs1928295, rs2033529, rs2060604, rs2112347, rs2176598, rs2183825, rs2365389, rs2820292, rs2836754, rs2890652, rs3736485, rs3800229, rs3817334, rs3849570, rs3888190, rs4740619, rs4889606, rs543874, rs6091540, rs6457796, rs6477694, rs6567160, rs657452, rs6713510, rs6804842, rs7138803, rs7144011, rs7531118, rs7550711, rs7599312, rs7715256, rs7899106, rs7903146, rs879620, rs891389, rs9304665, rs9374842, rs943005, rs9540493, rs9579083, rs977747, and rs9926784) from the analysis. Each red point depicts the IVW estimate using all SNPs. No single SNP is strongly driving the overall effect of BMI on osteoarthritis in this leave-one-out sensitivity analysis.

Osteoarthritis is a chronic joint inflammatory disease with joint swelling, pain and dysfunction as the main clinical manifestations, which seriously affects the quality of life of patients and increases the economic burden of the family and society.2 In recent years, with the gradual intensification of the aging trend in the population, the prevalence rate of osteoarthritis is also increasing year by year.1,2 Age, sex, joint injury and obesity are important risk factors for osteoarthritis, among which overweight and obesity are easier to control and prevent than other risk factors. However, due to the influence of confounding factors, it is difficult for classical epidemiological studies to explain the causal sequence of exposure factors and disease results. The purpose of this study is to explore the relationship between BMI and the risk of osteoarthritis through a two-sample Mendelian randomized study based on GWAS. The result indicated that the causal relationship between BMI with the increased risk of osteoarthritis.

In this study, we explored the relationship between BMI and the risk of osteoarthritis through a two-sample MR study based on GWAS. 79 SNPs significantly related to BMI were selected as tool variables. When using the IVW method, weighted median estimator, and MR-Egger MR method with data from the GWAS study of osteoarthritis, it was found that there was a causal relationship between high BMI and the increased risk of osteoarthritis. The main implication of our findings is that it supports weight control as a intervention for the prevention and management of osteoarthritis.

Overweight and obesity are modifiable and easier to manage than other risk factors of osteoarthritis (such as age, sex, and joint injury), and therefore it becomes a promising target for management of osteoarthritis if overweight and obesity do casually increase the risk of the occurrence and/or progress of osteoarthritis. The association between overweight and osteoarthritis has been reported in several studies. Raud et al17 found that there was a dose-response relation between BMI and the knee of osteoarthritis. A Spanish research demonstrated that the osteoarthritis risk both in hip and knee was increased in being overweight.18 However, due to the potential influence of confounding factors and reverse causality, it is difficult for conventional observational studies to establish the causal relationship between BMI and osteoarthritis, while the MR method is a promising tool for such an investigation, since it uses genetic variations as instrumental variables of exposure factors to infer the causal relationship between exposure factors and outcomes. There were a few available studies that used the MR method to investigate the relationship between BMI and osteoarthritis.19,20 Hindy et al19 used methods including independent sample traditional and multivariate MR, and two sample traditional and multivariate MR methods to explore the causal relationship between BMI and osteoarthritis. Their results showed that there was a causal relationship between high BMI and low LDL and osteoarthritis. However, the study population they investigated was mainly from Malm Diet and Cancer Study, which contained 4,226 cases and 23,456 controls in 1991 to 1996. Instead, we used the GWAS data released in 2018, with 38,472 cases and 424,461 controls. The updated data and increased sample sizes increased the strengths of our study, which had more practical significance and statistical power to confirm the investigated causal relationship. FunckBrentano et al20 also found a causal relationship between high BMI and knee arthritis and hip arthritis through MR method, but not with hand arthritis. The conclusion of our study was similar to these two studies, but in addition to the use of updated data and a larger sample size, the methods we used for investigation were more rigorous since a sensitivity analysis using the method of leave-one-out was conducted and consistent results were observed.

The etiology of the causal effect of BMI on osteoarthritis is not completely clear. Some studies have suggested that individuals with high BMI might be with increased joint load and therefore it accelerates the aging of the articular surface, leading to the occurrence and aggravation of osteoarthritis.21 In addition, obesity can induce the development of inflammation by increasing the intermediates produced by lipid metabolism, leading to osteoarthritis.22 However, more researches are need for further study.

Our study had some strengths. First, the MR method was used in the study, and therefore confounding factors and reverse causality were well controlled, at least to a great extent. Second, the study was based on data from published GWAS researches and GWAS meta-analyses, with a large sample size and genetic variations. However, the study also had some limitations. First, genetic polymorphisms are difficult to validate, and even if we used the MR-Egger method, misclassification in genetic polymorphisms cannot be completely ruled out. Second, the GWAS dataset of BMI used in this study was based on a mixed population, while the population from which the data of osteoarthritis was derived was European. This might lead to the bias from population stratification, and it remains unknown whether the result can be directly applied to other populations, which warrants further investigations. Third, there might be over-identification in the two-sample MR study, which may overestimate the association between SNP and exposure.23

This study indicated that high BMI might be causally associated with increased risk of osteoarthritis, which supports the importance of weight control for the prevention and treatment of osteoarthritis. Further researches are needed to explore the underlying mechanisms of this causal relationship.

This article does not contain any studies with human participants or animals performed by any of the authors.

The authors declare that they have no competing interests.

1. Geyer M, Schnfeld C. Novel insights into the pathogenesis of osteoarthritis. Curr Rheumatol Rev. 2018;14(2):98107. doi:10.2174/1573397113666170807122312

2. Glyn-Jones S, Palmer AJR, Agricola R, et al. Osteoarthritis. Lancet. 2015;386(9991):376387. doi:10.1016/S0140-6736(14)60802-3

3. Blagojevic M, Jinks C, Jeffery A, et al. Risk factors for onset of osteoarthritis of the knee in older adults: a systematic review and meta-analysis. Osteoarthritis Cartilage. 2010;18(1):2433. doi:10.1016/j.joca.2009.08.010

4. Butterworth PA, Landorf KB, Smith SE, et al. The association between body mass index and musculoskeletal foot disorders: a systematic review. Obes Rev. 2012;13(7):630642. doi:10.1111/j.1467-789X.2012.00996.x

5. Kolasinski SL, Neogi T, Hochberg MC, et al. 2019 American College of Rheumatology/Arthritis Foundation guideline for the management of osteoarthritis of the hand, hip, and knee. Arthritis Rheumatol. 2020;72(2):220233. doi:10.1002/acr.24131

6. Messier SP, Mihalko SL, Legault C, et al. Effects of intensive diet and exercise on knee joint loads, inflammation, and clinical outcomes among overweight and obese adults with knee osteoarthritis: the IDEA randomized clinical trial. JAMA. 2013;310(12):12631273. doi:10.1001/jama.2013.277669

7. Ference BA, Ray KK, Catapano AL, et al. Mendelian randomization study of ACLY and cardiovascular disease. N Engl J Med. 2019;380(11):10331042. doi:10.1056/NEJMoa1806747

8. Li MJ, Liu Z, Wang P, et al. GWASdb v2: an update database for human genetic variants identified by genome-wide association studies. Nucleic Acids Res. 2016;44(D1):D869D876. doi:10.1093/nar/gkv1317

9. Locke AE, Kahali B, Berndt SI, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518(7538):197206. doi:10.1038/nature14177

10. Burgess S, Thompson SG; CRP CHD Genetics Collaboration. Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol. 2011;40(3):755764. doi:10.1093/ije/dyr036

11. Elsworth BL, Lyon MS, Alexander T, et al. The MRC IEU OpenGWAS data infrastructure. bioRxiv. 2020.

12. Hemani G, Zheng J, Elsworth B, et al. The MR-Base platform supports systematic causal inference across the human phenome. Elife. 2018;7:e34408. doi:10.7554/eLife.34408

13. Bowden J, Del Greco MF, Minelli C, et al. A framework for the investigation of pleiotropy in twosample summary data Mendelian randomization. Stat Med. 2017;36(11):17831802. doi:10.1002/sim.7221

14. Bowden J, Davey smith G, Haycock PC, et al. Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator. Genet Epidemiol. 2016;40(4):304314. doi:10.1002/gepi.21965

15. Hartwig FP, Davey Smith G, Bowden J. Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption. Int J Epidemiol. 2017;46(6):19851998. doi:10.1093/ije/dyx102

16. Mikshowsky AA, Gianola D, Weigel KA. Assessing genomic prediction accuracy for Holstein sires using bootstrap aggregation sampling and leave-one-out cross validation. J Dairy Sci. 2017;100(1):453464. doi:10.3168/jds.2016-11496

17. Raud B, Gay C, Guiguet-Auclair C, et al. Level of obesity is directly associated with the clinical and functional consequences of knee osteoarthritis. Sci Rep. 2020;10(1):17. doi:10.1038/s41598-020-60587-1

18. Reyes C, Leyland KM, Peat G, et al. Association between overweight and obesity and risk of clinically diagnosed knee, hip, and hand osteoarthritis: a populationbased cohort study. Arthritis Rheumatol. 2016;68(8):18691875. doi:10.1002/art.39707

19. Hindy G, kesson KE, Melander O, et al. Cardiometabolic polygenic risk scores and osteoarthritis outcomes: a Mendelian randomization study using data from the Malm Diet and Cancer Study and the UK Biobank. Arthritis Rheumatol. 2019;71(6):925934. doi:10.1002/art.40812

20. FunckBrentano T, Nethander M, MovrareSkrtic S, et al. Causal factors for knee, hip, and hand osteoarthritis: a Mendelian randomization study in the UK biobank. Arthritis Rheumatol. 2019;71(10):16341641. doi:10.1002/art.40928

21. Ibounig T, Simons T, Launonen A, et al. Glenohumeral osteoarthritis: an overview of etiology and diagnostics. Scand J Surg. 2020:1457496920935018. doi:10.1177/1457496920935018

22. Francisco V, Prez T, Pino J, et al. Biomechanics, obesity, and osteoarthritis. The role of adipokines: when the levee breaks. J Orthop Res. 2018;36(2):594604. doi:10.1002/jor.23788

23. Bowden J, Dudbridge F. Unbiased estimation of odds ratios: combining genomewide association scans with replication studies. Genetic Epidemiol. 2009;33(5):406418. doi:10.1002/gepi.20394

See original here:
Body mass index and osteoarthritis risk | IJGM - Dove Medical Press

Posted in Human Genetics | Comments Off

Page 918«..10 20..917918919 920..930 940..»

Category Archives: Transhuman News

Genome Editing/Genome Engineering Market expectation surges with rising demand and changing trends by industry analysis through 2027 The Manomet…

Covid 19 coronavirus: Why the lab leak theory is still unlikely – New Zealand Herald

Crispr-cas9 for the treatment of lung cancer | BTT – Dove Medical Press

Human Genetics | Cincinnati Children’s

UMaine researchers: Culture drives human evolution more than genetics – UMaine News – University of Maine – University of Maine

Primordial Genetics Grants Arcturus Therapeutics Exclusive License of an RNA Polymerase for Human and Animal Therapeutics – PRNewswire

D. Wade Walke, Ph.D. Joins 23andMe as Vice President of Investor Relations – PRNewswire

A bug in the system the difficulties of linking the microbiome to cancer aetiology – Cancer Research UK

Human Genetics Market is Thriving Worldwide with Top Growing Companies QIAGEN, Agilent Technologies, Thermo Fisher Scientific The Almanian – The…

Body mass index and osteoarthritis risk | IJGM – Dove Medical Press

The Prometheus League

Breaking News and Updates

Prometheism

Forbidden Fruit

The Evolutionary Perspective

Transtopia Menu

Library Updates

Library Books

Future Euvolution

Lucid Dreams from Childhood

Genetic Revolution

Speciation + Self-Directed Evolution