Category Archives: Human Genetics

Ultima CEO Gilad Almogy, Ph.D./courtesy of Ultima Genomics

The information stored within the confines of the human genome is some of the most important data we can use in the diagnosis of disease, prevention efforts and therapeutics. Despite the fact that the technology to conduct whole genome sequencing (WGS) has been around for decades, financial barriers have stood in the way not just for patients and doctors looking for information, but for researchers as well.

Leveraging over $600 million in funding and five years of hard work, Newark, California-based Ultima Genomics has designed a way to surmount that financial barrier lowering the cost of a human genome from the realm of $1,000 to just $100.

Ultima has achieved this through the use of its sequencing architecture which replaces the traditional flow cell, a channel that contains all of the surfaces where chemistry and imaging occur during sequencing, with a silicon wafer. The technology serves the same function but at a lower cost with larger surface area, allowing for billions of reads. The process is easier to scale, amounting in large volumes of genetic data, and avoids costly and complicated fluidics.

The company also touts novel scalable chemistry, which combines the speed, efficiency and read lengths of natural nucleotides with the accuracy and scalability of endpoint detection. Add machine learning at the genome scale that can deliver accurate results and youve got yourself a cost-effective and useful human genome ready for interpretation.

Why it Matters

The importance of cost goes beyond simply enabling access to a larger quantity of existing genomic solutions. It also enables qualitatively different experiments to be envisioned and executed, not just once, but routinely, Ultima CEO Gilad Almogy, Ph.D. said in an interview with BioSpace. This can enable scientists to ask new questions they previously couldnt answer, and it can change the way genomic information is incorporated into the broader healthcare system.

The $100 genome stands to make genomics research that was once thought of as impossible, possible. In 2020, an article celebrating the 20th anniversary of Nature Reviews Genetics discussed the future of genetics and genomics research. In the piece, Stacey Gabriel, senior director of the genomics platform at the Broad Institute, commented that the real promise of genome sequencing lies in true population-scale sequencing at the scale of tens of millions of individuals that would enable the comprehensive, unbiased study of the human genome and the variations found within it.

Genomic research has provided physicians with a wealth of knowledge about genes that can increase a persons risk of developing a certain condition, such as the BRCA2 gene which is linked to an increased risk of developing breast and ovarian cancer. However, without the ability to conduct large-scale studies, simply understanding the role that one gene or a handful of genetic mutations plays in developing disease is often not enough information to elucidate the genome's full impact. With scalable and cost-effective WGS, it will become much easier for researchers to understand the parties within our genome that contribute to the manifestation of disease, which could ultimately lead to targeted therapeutics.

Genomic Data can Inform Treatment

Gabriel stated that she believes WGS should become a part of the electronic health record. There are plenty of good reasons to collect and include genomic data as it relates to health and disease. Beyond using this data to understand the risk someone is at for a certain condition, genomic information can help direct treatment. For example, some cancer therapies specifically target genetic mutations or alterations that have occurred in the tumor microenvironment. If patients and physicians have access to more affordable genomic testing, they can use the information to choose a targeted therapy that will work best for them.

We envision a future where in nearly every interaction patients have with the healthcare system, their genomic information will be sequenced to reveal not just their inherited DNA, but also what changes in their bodies are encoded into circulating DNA, RNA, methylation and proteomics, Almogy said.

Early Application

The $100 genome is already proving its worth. Researchers from Stanford University utilized the low-cost genomic sequencing to investigate the trajectories in precancerous polyps to early colorectal adenocarcinoma. The paper, not yet peer-reviewed but published on bioRxiv, demonstrated the technologys ability to observe changes in DNA methylation that occur early in the malignant transformation process, providing clues as to what happens at a molecular level when a polyp turns cancerous. This type of research could one day translate into clinical use, where physicians could use genomic sequencing to detect DNA changes in cells that might signal the danger of an impending malignant tumor.

Low-cost genomics helps therapeutic development in a couple of fundamental ways, Almogy said. Firstly, many companies seek to understand the genomic drivers of disease by sequencing populations and looking for associations between variants and disease. This type of work inherently requires large numbers to be useful, and the $100 genome certainly enables larger studies in a wider variety of populations. Second, low-cost genomics enables large-scale experiments to reveal the function of many genes.

Ultima isnt prepared to stop at $100 though. As evidenced by its recent collaboration with Exact Sciences, the goal is to continue driving the price down. The companies entered into a long-term supply agreement in June aimed at lowering the cost of sequencing and improving patient access to genomics-based testing. As part of the alliance, Ultima and Exact will develop one or more of Exacts advanced cancer diagnostic tests that will be developed using Ultimas technology. Earlier in June, Ultima paired with Olink Holding AB to combine the latter's Explore assay with its sequencing system to enable larger-scale projects.

Were currently in early access mode, so were focused on optimizing the platform with our initial customers before making it available for broad commercial launch next year, Almogy explained. "Beyond that, we continue to develop improvements in the architecture, because for us the $100 genome is only the beginning and were committed to continuously [driving] down the cost of genomic information.

Originally posted here:
Here's how the $100 Human Genome will Change Medicine - BioSpace

This article discusses the roles nurses may play in bringing the benefits of genomic medicine to patients

Genomic medicine can improve patient care through supporting quicker diagnoses and enabling more tailored care. In England, genomic testing has already been introduced for patients with some rare conditions and cancers, and, as understanding of the genome increases, it is likely to become part of more care pathways. This article discusses the key roles nurses may play in bringing the benefits of genomics to patients as it becomes part of routine care, including in identifying patients for genomic testing, discussing testing with patients, referring to genetic counselling services or the relevant clinicians for targeted therapies, and personalising care plans. We also explain how the NHS Genomic Medicine Service Alliances will work with nurses to help bring genomics into mainstream healthcare.

Citation: Buaki-Sogo M, Percival N (2022) Genomic medicine: the role of the nursing workforce. Nursing Times [online]; 118: 8.

Authors: Maria Buaki-Sogo is lead nurse, North Thames Genomic Medicine Service Alliance; Natalie Percival was formerly chief nurse, North Thames Genomic Medicine Service Alliance, and is currently director of nursing, systems and professional development at NHS England.

Genomics is the study of all the deoxyribonucleic acid (DNA) the genome of an organism. All living organisms, whether single-celled bacteria, multicellular plants, animals or humans, have DNA, which contains the information needed for an organism to grow, survive and reproduce. DNA is arranged into genes, a sequence of nucleotides which are code for proteins that are essential for building and repairing an organism. There are also non-coding regions, which influence how these genes interact. A genome includes both the genes and the non-coding regions.

Human DNA is made from four separate chemical bases, known as A (adenine), C (cytosine), G (guanine), and T (thymine), with the whole genome made up of more than three billion DNA bases. Every humans genome is around 99.9% the same, but that 0.1% difference equates to around three million differences between one persons DNA and the next persons (Health Education England Genomics Education Programme, nd). Some of these differences in our DNA will have no impact on a persons health, but other variations may cause a genetic condition, influence our predisposition to develop certain conditions, and can even affect how we respond to some drugs.

Over the past decade, transformative advances in DNA sequencing technologies have enabled a vast expansion in human genome analysis for the purpose of diagnosing and managing human diseases. The scope of genetic testing now ranges from analysing a single gene to using multigene panels which can analyse from five to 100 genes known to be associated with the development of a condition or a collection of clinical symptoms through to whole genome sequencing, where it is possible to determine the entire human genome (International Human Genome Sequencing Consortium, 2004).

The use of this more advanced genomic testing has the potential to deliver tangible improvements for patients, including effective and quicker diagnosis of rare conditions, personalised treatment, better care for those with inherited conditions and cancer, and a clearer understanding of the underlying cause of diseases.

The role of the nursing workforce will be to offer genomic testing with confidence

In England, genomic testing, including whole genome sequencing, is now available for patients with certain rare diseases and cancers to enable better prediction, diagnosis and treatment.

In clinical practice, whole genome sequencing still requires the application of virtual panels for the analysis. As understanding of the genome and capacity in the NHS evolves, genomic testing will increasingly become part of routine care pathways for more conditions.

As a nursing community, we must be ready to adapt our current practice to reflect these innovations and ensure that our patients have access to the benefits that genomic testing can offer.

Nurses are often in an ideal position to offer support and advice to patients, whether they are living with cancer, long-term conditions or inherited genetic disorders, which need lifelong care. We work across a broad range of settings on the front line, are committed to our patients, and are typically strong and empathetic communicators, as described in the values set out in The NHS Constitution for England (Department of Health and Social Care, 2021). Nurses are vital to assisting the NHS in offering the latest advances, and it is important that we understand how genomics will affect our practice and the experiences of our patients.

Specialist nurses will work in partnership with the clinical team to offer tailored information and specific genetic testing relevant to the patients condition to inform treatment decisions. Senior nurses will also be able to support junior nurses to gradually acquire knowledge and understanding of genomic medicine to embed in their practice.

For nurses who have a lot of patient contact, gaining knowledge on the core principles of genomics may help them increase uptake of genetic screening, signpost service users to the right place to seek health advice, and could also help to address inequalities in access to genomic medicine services.

Genomic medicine is already embedded in some oncology nursing pathways. At present, genomic testing is available for inherited diseases or forms of cancer included in the National Genomic Test Directory (NHS England, 2022). Use of genomic testing could help the NHS reach its aim of diagnosing 75% of all cancers at stage 1 or 2 by 2028 (NHS England, 2019).

The North Thames Genomic Medicine Service (GMS) Alliance is working in partnership with key stakeholders to support the nursing workforce to acquire the skills and the level of knowledge to accomplish this mission effectively and efficiently. In some places, patients are driving forward conversations and we recognise the importance of patient involvement in establishing the best way to influence care pathways. Patient and public involvement is a key part of the North Thames GMS Alliances strategy, and collaborative work with patient groups is being developed.

With the right level of understanding of genomics, the support of their local trusts and the local systems, the role of the nursing workforce will be to offer genomic testing with confidence, helping to embed routine genetic testing in the NHS. This will mean:

Evidence suggests that continuity of care positively affects health outcomes and patient experience (Lautamatti et al, 2020). Nurses are often well positioned to provide this and to build strong and trusting relationships with patients and their relatives.

Consequently, we can help our patients access better care, understand the impact of inherited disease on their lives, and give them the opportunity to plan for a better quality of life. Patients and their families will have access to more precise medicine that will give clinicians the ability to offer targeted and personalised treatment, based on their unique genome (pharmacogenomics).

As genomic medicine continues to evolve and additional tests become available that can benefit patient care, nurses can also help define how these tests can be brought into practice across their specialities. We are right at the beginning of the use of genomic medicine in the NHS, and there is a real opportunity for nurses to be part of service design. We have the chance to help improve guidelines across many areas of clinical practice and be international leaders (Tonkin et al, 2018).

By embedding genomic medicine in mainstream care and providing nurses (and other practitioners such as midwives) with appropriate training on ordering genomic testing to patients, practitioners will also be able to embrace their autonomy and clinical judgement to provide genomic services to patients more effectively and efficiently.

There are, of course, ethical issues to consider when discussing the widespread use of genomic medicine in the NHS. For example, we know that some patients will not want to know their risk for future conditions or their carrier status. There is also an ongoing national discussion around whether sequencing newborn babies for rare conditions beyond the current heel-prick test should become part of practice, and how this data and consent would be managed. As nurses, it is important that we bring our knowledge and perspectives to these conversations as the genomic medicine system is being designed and embedded in the NHS (Box 1). For now, where genetic tests provide actionable results that can help us improve patient care and outcomes, nurses are vital to making these accessible for patients in an equitable way and supporting them to make informed decisions.

Box 1. Embedding genomics services in the NHS

We believe that nurses are a key element in the implementation of routine genetic testing in the NHS, but for nurses to assist with better use of genomics in mainstream healthcare they will need financial aid for training and support to acquire the appropriate skills and knowledge. Existing workforce pressures, a historical lack of secure funding on education and training, as well as inequalities in health, are all barriers that need to be acknowledged and addressed.

There is some support already being put in place for the nursing community through the establishment of seven regional GMS Alliances established in England in January 2021. One of the main purposes of the GMS Alliances is to provide training and education opportunities, which will help health professionals, including nurses, to increase their knowledge of genomics and keep up to date with how this may affect their clinical practice. There are also several training and education resources provided by Health Education England at national and regional levels, including continuing professional development programmes supported by the educational teams within each GMS Alliance (Health Education England Genomics Education Programme, nd).

At a service development level, nurses are also being consulted on how genomic medicine can work within their organisations (see Box 2 for an example of how this is used in practice). The GMS Alliances are working with healthcare organisations and nurses to improve current frameworks and pathways of care, tackling inequalities in accessing genomic testing, and promoting patient-centred care via the increased presence of patient and public involvement groups.

Box 2. Lynch syndrome: an example of genomic medicine in current practice

There is a need for further training opportunities to help prepare the nursing workforce for the future, and for ongoing consultation to ensure genomics is implemented in the right way. Powerful and influential nursing leadership is required in the UK to embed the genomics framework into nursing education pathways at all levels of practice and make sure the impact of genomics on the nursing workforce is understood and considered in decision making. This is to ensure that nurses can develop the core competencies and confidence in their understanding of genomic medicine required to meet the service users needs.

GMS Alliances are working with nurses, patients and the public to build trust in genomics and to support the multiprofessional workforce to use genomics safely and effectively. By embedding genomics into the mainstream health service, our aim is to deliver improvements for patients, including better and quicker diagnosis of rare conditions, personalised treatment, and care for those with inherited conditions and cancer, as well as building a better understanding of the underlying cause of many diseases. To achieve this, nurses need support to develop genomics literacy and begin to use genetic testing within their care pathways.

Bowel Cancer UK (2018) Testing for Lynch syndrome what you need to know. bowelcanceruk.org.uk, 9 April (accessed 23 June 2022).

Department of Health and Social Care (2021) The NHS Constitution for England. gov.uk , 1 January (accessed 23 June 2022).

Health Education England Genomics Education Programme (nd) What is genomics? genomicseducation.hee.nhs.uk (accessed 27 June 2022).

Hegde M et al (2014) ACMG technical standards and guidelines for genetic testing for inherited colorectal cancer (Lynch syndrome, familial adenomatous polyposis, and MYH-associated polyposis). Genetics in Medicine; 16: 1, 101-116.

International Human Genome Sequencing Consortium (2004) Finishing the euchromatic sequence of the human genome. Nature; 431, 931-945.

Lautamatti E et al (2020) Continuity of care is associated with satisfaction with local are services. BMC Family Practice; 21: 1, 181.

Li X et al (2021) Recent advances in Lynch syndrome. Experimental Haematology and Oncology; 10: 37.

NHS England (2022) National Genomic Test Directory. england.nhs.uk (accesssed 5 July 2022).

NHS England (2019) The NHS Long Term Plan. NHSE.

St Marks Hospital (2019) Lynch Syndrome: Information for Patients. North West Thames Regional Genetics Service.

Tonkin ET et al (2018) The first competency-based framework in genetics/genomics specifically for midwifery education and practice. Nursing Education in Practice; 33: 133-140.

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Genomic medicine: the role of the nursing workforce - Nursing Times

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AbbViehas ended its collaboration deal withAlectorto develop one of two potential Alzheimer's Disease drugs.

The antibody drug in question, AL-003, was designed to target the receptor CD33, a checkpoint receptor found in the brain's immune cells. AbbVie signed a co-development and option agreement with Alector in October 2017. The goal was to tap into the latter's unique approach to utilizing the immune system to fight neurodegeneration. For that deal, Alector received $205 million upfront, with the potential to gain as much as $20 million.

In afilingwith the Securities and Exchange Commission, the decision to terminate came after the two firms jointly conducted a review of their next steps for the drug. On June 30, AbbVie gave written notice that it was no longer interested in pursuing AL-003.

The document does not provide any details on why AbbVie is discontinuing. That company has also yet to make an official statement regarding the matter.

Alector's sharesdropped7 cents to close at $11.49 per share shortly after the SEC filing was made public.

However, the relationship isn't totally severed between the pair as they are still working to develop AL002, which is focused on targeting triggering receptors expressed on myeloid cells 2 (TREM2) also for Alzheimer's Disease. Interest in AL002 is based on positive results from the INVOKE-2 Phase II clinical trial, which looked into the safety and efficacy of the drug in slowing disease progression in people living with Alzheimer's.

AL002 is an investigational, humanized monoclonal antibody whose role in potentially treating Alzheimer's was first identified in large-scale genome-wide association studies. Researchers found that reducing TREM2's functionality may contribute to AD progression and other types of dementia. By increasing TREM2 in the brain, there may be a way to target multiple pathologies linked to the disorder instead of just focusing on one pathology type.

"Loss of TREM2 activity has been shown through human genetics to be one of the notable risk factors for developing Alzheimer's disease. AL002 is a first-in-class TREM2 targeting antibody in Phase 2 clinical development for [the disorder]," Robert Paul, M.D., Ph.D., chief medical officer of Alectorsaidin an earlier statement.

In the same press release, Michael Gold, M.D., vice president of development neurosciences at AbbVie, added, "Alzheimer's is a devastating disease that robs a person of their identity, and a family of their loved one. We are hopeful that AL002 may one day be a treatment option for the millions of people diagnosed with this disease."

See more here:
AbbVie Half Breaks Up with Alector on Alzheimer's - BioSpace

New York, July 04, 2022 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Human Identification Market Forecast to 2028 - COVID-19 Impact and Global Analysis By Product and Services, Technology, Application, and End User" - https://www.reportlinker.com/p06289913/?utm_source=GNW

However, high cost of instruments used for genomic studies are expected to hamper the growth of the human identification market.Human Identification is a branch of science that deals with the analysis of genetic materials, helping identify an individual based on genetics. Human identification has various applications in forensics, paternity test, and others.Government entities worldwide have strengthened their support for the field of human identification due to its potential, demand, and varied applications in various industries.Many forensic science disciplines, including DNA analysis, are undergoing a transformation in the US and the world.

New approaches are being created, validated, and implemented to help criminal investigations. Investigators face challenges regarding the validity and accuracy of older and current methods.Forensic DNA analysis can help reunite families, particularly in cases where children separate from their parents at an early age.The Forensic Project, funded by the Bureau of Democracy of the US Department of State, intends to increase the use of this evaluation technique to assist families separated during riots and violent incidents.

The Center for Human Identification (CHI) at the University of North Texas Health Science Center at Fort Worth is a world-renowned hub for forensic DNA testing as it receives funding from the state of Texas and various federal government agencies.The Forensic Unit helps the Texas Department of Public Safety (DPS) reduce the backlog of sexual assaults.In addition, the Forensic Unit gets federal funds from the National Institute of Justice (NIJ) of the US Department of Justice (DOJ) to handle cases in Texas.

These grants allow the unit to provide free DNA testing services (autosomal and Y chromosome STR typing) to many law enforcement agencies in North Texas counties. Thus, increasing government support and initiatives for forensics programs are driving the human identification market.Moreover, many forensic research projects focus on developing novel analytical instruments, assessment techniques for trace amounts of evidence, and proteomic analysis techniques with unique sampling procedures, allowing hair-, skin-, and bone-based identification.Several portable equipment types have been manufactured for extensive analysis in the on-site field.

Portable forensic instruments prove to be useful in transporting unstable, perishable, or hazardous compounds to the laboratory, which are further expected to propel the market during the forecast period.Additionally, scientists sequence a DNA sample and provide investigators information on the probable characteristics of suspects, such as hair, eye, and skin color, to identify them.Age and biological background can also be predicted using newer approaches.

The personnel can also use biosensors to analyze the minute traces of bodily fluids found in fingerprints to identify the suspect. Data detected using such samples include age, medications, gender, and lifestyle.Furthermore, a smartphone-based sensor has been developed to evaluate a saliva sample through immunochromatography; the tests can also be run away from a lab.Geolocating a suspect or victim using stable isotopes of water is another advanced technique in forensic sciences.

Scientists can determine the samples origin by isolating the isotopes in a water sample found on a suspect or victim. Thus, advancements based on modern technologies and smart sampling methods are generating new trends in the market.The global human identification market is analyzed on the basis of products and services, technology, application, and end user.Based on products and services, the market is segmented into consumables, instruments, services, and software.

Further, the consumables segment is classified into electrophoresis kits and reagents, DNA amplification kits and reagents, DNA quantification kits and reagents, DNA extraction kits and reagents, and rapid DNA analysis kits and reagents.The consumables lasers segment led the market in 2021.

It is anticipated to register the highest CAGR during the forecast period.Based on technology, capillary electrophoresis, polymerase chain reaction, nucleic acid purification and extraction, automated liquid handling, microarrays, next-generation sequencing, and rapid DNA analysis.The capillary electrophoresis segment held the largest market share in 2021.

However, the next-generation sequencing segment is anticipated to register the highest CAGR during the forecast period.Based on application, the market is segmented into forensic applications, paternity identification, and other applications.The forensic applications segment held the largest market share in 2021.

It is also expected to register the highest CAGR during the forecast period.Based on end user, the market is segmented into forensic laboratories, research and academic centers, and government institutes.The forensic laboratories segment held the largest market share in 2021.

It is also anticipated to register the highest CAGR during the forecast period.COVID-19 Impact Analysis: Human Identification MarketThe COVID-19 pandemic in the regions had a mixed impact on the growth of the human identification market.Various companies have shut down their productions, hence are unable to manufacture to meet the rising demand.

The COVID19 pandemic has significantly negatively impacted the global economies.Health services are highly prioritized globally to serve patients affected by COVID-19.

The routine health care services have remained suspended. Market players operating in the human identification market were focused on developing and producing COVD-19 testing kits, which reduced the productive utilization of human identification products.Due to the pandemic, many governments-imposed lockdowns to prevent the spread of the virus, which resulted in a significant reduction in crime rates.Additionally, the lack of proper standard operating procedures for criminal investigation during the pandemic has significantly reduced the demand for human identification products.

On the other hand, the shortage of definitive therapy offers significant opportunities for the genome editing-related market as the US FDA has recently approved the use of plasma therapy for critically ill COVID 19 patients. Furthermore, the active involvement of the governments and the associated market players in exploring opportunities for genome editing-related products and services is expected to drive such developments in the human identification market over the next few years.National Institute of Justice (NIJ), Institute Genetics Nantes Atlantique (IGNA), Forensic Capability Network, International Centre for Theoretical Physics (ICTP), and International Atomic Energy Agency (IAEA) are among the primary and secondary sources referred to while preparing the report on the human identification market.Read the full report: https://www.reportlinker.com/p06289913/?utm_source=GNW

About ReportlinkerReportLinker is an award-winning market research solution. Reportlinker finds and organizes the latest industry data so you get all the market research you need - instantly, in one place.

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The human identification market size is projected to reach - GlobeNewswire

Scientists believe that global wheat production could be doubled by accessing into the crop's "untapped genetic potential".

By using modern techniques such as speed breeding and gene editing, the international team behind the new research say that it would be possible to cultivate new varieties of wheat tailored to each region that they're grown in.

Depending on their genes, different varieties of wheat capture water, sunlight and nutrients in different ways. The scientists propose that with an optimal genome wheat crops would be able to deliver a higher yield of grain per acre.

Read more: Billions of pounds of Ukrainian wheat cannot be exported amid food crisis in developing countries

The study, led by the UK's Rothamsted Research, used existing data on how different genes contribute to individual plant traits "such as size, shape, metabolism and growth".

They ran millions of simulations to effectively design the perfect wheat plants suited to their local environments. Comparing these to locally adapted cultivars, they found in all cases that current wheat varieties were underperforming for grain yield.

Read more: Ukraine war - 'Humanitarian disasters' if wheat exports are stopped, says OECD

Dr Mikhail Semenov, one of the study's leads, said: "Current wheat cultivars are, on average, only at the half-way point with respect to the yields they could produce given the mismatches between their genetics and local wheat growing conditions.

"Global wheat production could be doubled by the genetic improvement of local wheat cultivars - without increasing global wheat area," he added.

Fellow study lead Dr Nimai Senapati said that improving this "genetic yield gap" would both help feed the world's growing population and reduce the pressure to convert wild habitats to farmland.

Humans have farmed wheat for millennia and the impact on our species has been enormous - agriculture is often described as the first revolutionary step in human civilisation as it led to settlements and evolved social structures.

Today wheat is the most widely grown crop in the world and second only to rice in terms of human consumption, with global harvests in the region of 750 million tons.

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The new study published in the journal Nature Food looks at 53 wheat growing regions across 33 countries, covering all of the global wheat growing environments.

The team first calculated the potential yield from 28 commonly grown wheat varieties at each of these sites, assuming the best cultivation conditions were in place for each one.

The harvests this delivered varied enormously, with less than four tons per hectare in Australia and Kazakhstan, with 14 tons per hectare in New Zealand.

But these were improved by replacing the local cultivars with the idealised varieties of wheat favouring particular traits, such as "tolerance and response to drought and heat stresses, the size and orientation of the light-capturing upper leaves, and the timing of key life cycle events".

According to the study, by optimising these key traits, the global average genetic yield gap could be closed by 51% - meaning global wheat production could be doubled.

"Not unsurprisingly, the countries with the lowest current yields could gain the most from closing their genetic yield gaps," said Dr Senapati.

"That said, even improvements in those countries with a medium genetic yield gap of 40 to 50%, but with a large proportion of global wheat harvest area - such as the leading producers India, Russia, China, USA, Canada, and Pakistan - would have a substantial effect on global wheat production due to the larger wheat cultivation areas involved."

According to the researchers, before this study it was not known how large the genetic yield gaps were at a country and global level.

They say this concept of a genetic yield gap contrasts with the existing and more traditional view of a yield gap which compares harvests to how they could have performed under optimal management "as a result of factors such as pest or diseases, lack of nutrients, or sowing or harvesting at the wrong time".

"Our analysis suggests that such genetic yield gaps due to sub-optimal genetic adaptation could, in relative terms, be as large as the traditional yield gap due to imperfect crop and soil management," said Dr Semenov.

"Wheat was first domesticated about 11,000 years ago, but despite this and not to mention the sequencing of its entire genome in 2018 the crop is still some way from being at its 'genetic best'," he added.

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Global wheat production can be doubled to feed millions and save land, say scientists - Sky News

HUNTSVILLE, Ala. (WHNT) Its an honor only 100 people get every year, a spot on TIMEs most influential people list. This year, a scientist from Huntsville earned that honor because of her work on the Human Genome Project.

Karen Miga is a Buckhorn High School graduate. She told News 19 that her teachers and experiences throughout high school in the Rocket City shaped her into the researcher and scientist she is today.

After high school, Karen got her Bachelors of Science degree at The University of Tennessee before heading to Cleveland, Ohio and getting a Masters Degree in Genetics at Case Western University. Afterward, she headed to Duke University and obtained her Ph.D. in Evolutionary Genetics.

Now, Karen is an Assistant Professor at The University of California, Santa Cruz teaching Biomolecular Engineering. But, TIME is recognizing Karen for her work on the Human Genome Project.

The human genome was first mapped in 2001, but according to scientists, it was not entirely accurate nor complete. So, Karen helped lead a team of international scientists, known as the Telomere-to-Telomere Consortium, or T2T, to complete the first gapless sequence of the human genome.

I started my career when the human genome was first announced and it was clear to me at the time there were large and persistent gaps that the rest world, except for some in the scientific community, were largely ignoring, Karen told News 19.

So, before she became a co-founder of the T2T consortium she was already building a career studying the human genome sequence gaps. Through her studies, she knew there was a lot more to explore.

When I finally reached a point where I knew technology could close some of these regions, thats when I was able to team up with Adam Phillipe who is the other co-founder and is involved with the computational putting together really difficult parts of the genome, Karen explained. So, its this balanced expertise of knowing about these sequences, studying them, then the computational process.

Karen credits a lot of her excitement for science with growing up in the Rocket City. Huntsville has always been this champion for research, she told News 19. Theres always been a tremendous amount of PhDs and folks who are rocket scientists around and there is an appreciation for science.

Karen joins many influential names on the list including President Biden, Ketanji Brown Jackson who was confirmed to fill retiring Justice Stephen Breyers seat, and singer Adele, among many others. She told News 19 TIMEs willingness to diversify who they consider influential is imperative for the science industry.

I think theyve been consistently putting science on the same platform with these important milestones met politically, as well as artists and folks who are making a difference with law in our legal system and Supreme Court Justices, Karen explained.

She also believes the COVID-19 pandemic opened peoples eyes to the importance of science. Weve all seen with the pandemic how important science is and what it means to have a vaccine and the health risks, Karen shared. Science is so important to every aspect of our life but we dont get a lot of exposure to the scientists themselves.

She hopes the upcoming elementary and high school students in the Rocket City take advantage of the research and opportunities around them.

Most of us who are getting these awards started with a single step forward, with a question we were passionate about, building that type of momentum over time, itll pay off, and its never easy and never a direct path but the process of getting there is really an enriching thing, Karen said.

Karens words to those with big dreams, Goals can sometimes seem daunting when you are young, but with continuous hard work, you can change the world.

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Huntsville native among TIMEs 100 most influential people - WHNT News 19

SAN FRANCISCO, June 28, 2022 /PRNewswire/ -- Human Reproduction journal has published the ground-breaking results of an international clinical study, where a novel AI algorithm called Life Whisperer Genetics was developed by AI healthcare company Presegen to assess the genetic integrity of embryos using only images. The assessment is non-invasive, low-cost, and provides results instantly. This is in stark contrast with PGT-A, the standard method used in IVF today, which requires an invasive and potentially risky biopsy to remove a portion of the embryo, followed by an expensive and time-consuming genetic testing procedure.

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The study was conducted with IVF clinics globally, including Ovation Fertility (USA), IVF-Life (Europe), Alpha IVF & Women's Specialists (SE Asia), and Wings IVF (India). Results showed that the AI algorithm could identify whether an embryo was genetically normal, or 'euploid'. Identification of euploid embryos can result in improved clinical outcomes, such as a better chance at pregnancy success.

Presagen's Chief Medical Science Officer Dr Sonya Diakiw explained "Because this assessment is based on images alone, it is not as accurate as PGT-A itself, which involves actual DNA sequencing. But we are finding that PGT-A results themselves can be variable, as they depend on the embryo sample being tested. PGT-A only tests 5 cells from a total of around 200, so it is not always representative of the entire embryo. Life Whisperer Genetics is a whole-embryo assessment of genetic integrity that does not require any invasive procedures, which can be used to prioritize embryos for use in IVF procedures."

The technology was evaluated prospectively on patients in Europe in collaboration with the IVF-Life Group. Dr Jon Aizpurua from IVF-Life said "Life Whisperer Genetics can be used for patients as a pre-screen, to ensure we only genetically test embryos that are likely to be normal, saving patients time and money. For patients who are not comfortable with invasive genetic tests, or in countries like Germany where invasive genetic tests are not permitted, Life Whisperer Genetics is a viable alternative to help select embryos that are most likely to be euploid."

Story continues

Prospective studies were also performed in collaboration with Alpha IVF & Women's Specialists in Malaysia. Chief Embryologist Adelle Yun Xin Lim said "Computer vision with AI may revolutionise IVF treatment and this new technique is another milestone of AI in IVF. The technique will help doctors and embryologists around the world to predict the chromosome status of embryos in a rapid and non-invasive manner enabling the prioritization of embryos that are likely to be euploid for transfer or for further confirmatory PGT testing, leading to a faster time to pregnancy and reducing the cost of the treatment."

Ovation Fertility's VP of Scientific Advancement, Dr Matthew (Tex) VerMilyea said "This new product is very exciting. In some ways it is like a 'Rapid Antigen Test (RAT)' for embryo assessment, providing a non-invasive, instantaneous evaluation of genetic integrity, which will have massive potential for the US market when it receives FDA approval."

Life Whisperer Genetics is already available for IVF clinics and their patients in over 40 countries globally. It can be used in combination with Life Whisperer Viability, which assesses if an embryo is likely to lead to a pregnancy. International clinical studies have shown that Life Whisperer Viability can perform better than embryologists' current manual embryo assessment methods. Together, Life Whisperer Viability and Life Whisperer Genetics provide a comprehensive assessment of embryo quality.

Paper Title

Development of an artificial intelligence model for predicting the likelihood of human embryo euploidy based on blastocyst images from multiple imaging systems during IVF

https://academic.oup.com/humrep/advance-article/doi/10.1093/humrep/deac131/6604228

Authors

S. M. Diakiw1, J. M. M. Hall1,2,3, M. D. VerMilyea4,5, J. Amin6, J. Aizpurua7, L. Giardini7, Y. G. Briones7, A. Y. X. Lim8, M. A. Dakka1, T. V. Nguyen1, D. Perugini1, M. Perugini1,9

Life Whisperer Diagnostics (a subsidiary of Presagen), San Francisco, CA, USA, and Adelaide, SA, Australia

Australian Research Council Centre of Excellence for Nanoscale BioPhotonics, The University of Adelaide, Adelaide, SA, Australia

School of Physical Sciences, Faculty of Sciences, The University of Adelaide, Adelaide, SA, Australia

Ovation Fertility, Nashville, Tennessee, USA

Texas Fertility Center, Austin, Texas, USA

Wings IVF Women's Hospital, Ahmedabad, Gujarat, India

IVF-Spain, Alicante, Spain

Alpha IVF & Women's Specialists, Petaling Jaya, Selangor, Malaysia

Adelaide Medical School, Faculty of Health Sciences, The University of Adelaide, Adelaide, SA, Australia

Paper Abstract

STUDY QUESTION

Can an artificial intelligence (AI) model predict human embryo ploidy status using static images captured by optical light microscopy?

SUMMARY ANSWER

Results demonstrated predictive accuracy for embryo euploidy, and showed a significant correlation between AI score and euploidy rate, based on assessment of images of blastocysts at Day 5 after IVF.

MAIN RESULTS AND THE ROLE OF CHANCE

Overall accuracy for prediction of euploidy on a blind test dataset was 65.3%, with a sensitivity of 74.6%. When the blind test dataset was cleansed of poor quality and mislabeled images, overall accuracy increased to 77.4%. This performance may be relevant to clinical situations where confounding factors, such as variability in PGT-A testing, have been accounted for. There was a significant positive correlation between AI score and the proportion of euploid embryos, with very high scoring embryos (9.0-10.0) twice as likely to be euploid than the lowest scoring embryos (0.0-2.4). When using the genetics AI model to rank embryos in a cohort, the probability of the top-ranked embryo being euploid was 82.4%, which was 26.4% more effective than using random ranking, and ~13-19% more effective that using the Gardner score. The probability increased to 97.0% when considering the likelihood of one of the top two ranked embryos being euploid, and the probability of both top two ranked embryos being euploid was 66.4%. Additional analyses showed that the AI model generalized well to different patient demographics and could also be used for evaluation of Day 6 embryos and for images taken using multiple time-lapse systems. Results suggested that the AI model could potentially be used to differentiate mosaic embryos based on the level of mosaicism.

WIDER IMPLICATIONS OF THE FINDINGS

These findings collectively support the use of this genetics AI model for evaluation of embryo ploidy status in a clinical setting. Results can be used to aid in prioritizing and enriching for embryos that are likely to be euploid for multiple clinical purposes, including selection for transfer in the absence of alternative genetic testing methods, selection for cryopreservation for future use, or selection for further confirmatory PGT-A testing, as required.

About Presagen and Life Whisperer

Presagen is an AI healthcare company that is changing the way clinics, patients, and medical data from around the world are connected through AI. Its platform, The Social Network for Healthcare, connects clinics and patients globally, and enables collaboration and data sharing to create scalable AI healthcare products that are affordable and accessible for all. The decentralized network democratizes the creation of AI products, promotes collaboration through incentives, and protects data privacy and ownership. With a focus on improving Women's Health outcomes globally, Presagen's first product, Life Whisperer, is being used by IVF clinics globally to improve pregnancy outcomes for couples struggling with fertility. With a vision of creating the largest network of clinics, patients, and medical data from around the world, Presagen is driving the future of AI Enhanced Healthcare.

About Ovation Fertility

Ovation Fertility is a national network of reproductive endocrinologists and scientific thought leaders focused on reducing the cost of having a family through more efficient and effective fertility care. Ovation's IVF and genetics laboratories, along with affiliated physician practices, work collaboratively to raise the bar for IVF treatment, with state-of-the-art, evidence-based fertility services that give hopeful parents the best chance for a successful pregnancy. Physicians partner with Ovation to offer their patients advanced preconception carrier screening; preimplantation genetic testing; donor egg and surrogacy services; and secure storage for their frozen eggs, embryos and sperm. Ovation also helps IVF labs across America improve their quality and performance with expert off-site lab direction and consultation. Learn more about Ovation's vision of a world without infertility at http://www.OvationFertility.com.

About IVF-Life

IVF-Life is a group of fertility clinics specialized in complex cases. Centres located inSpain and the UK have the latest advances in Reproductive Medicine and outstanding professionals in this field. The constant innovation and a firm commitment to technology keep IVF-Life at the forefront in the assisted reproduction field treating patients from all over the world with ahigh degree of success. IVF-Life perform a comprehensive range of treatments and diagnostic tests with the aim to provide effective solutions to a wide variety of fertility problems.

About Alpha IVF & Women's Specialists

Alpha IVF group comprises IVF centres in Kuala Lumpur, Penang and Singapore. Alpha IVF is a world-class fertility treatment provider bringing the most advanced fertility technologies and excellent success rates in achieving the goal of having a baby. Alpha IVF consists of a team of highly qualified and skilled doctors, scientists and nurses that deliver international standards of patient care. As the name Alpha suggests, the team have pioneered numerous innovative fertility treatments. Alpha IVF offers its patients access to a network of fertility experts and facilities fully equipped with a full range of cutting-edge laboratories, innovative technologies such as Artificial Intelligence, Next Generation Sequencing (NGS), 100% post-warm survival rate for embryo cryopreservation, time-lapse embryo monitoring, PIEZO-ICSI, sperm separation technologies and many others. Continuous R&D have led Alpha IVF to achieve numerous world firsts and innovative fertility treatment protocols both regionally and globally.

About Wings

Wings IVF comprises a chain of leading fertility clinics across India, with more than 12,000 live births through IVF. Wings hospitals are state of art specialty hospitals & clinics providing all infertility treatments and IVF. They provide top quality, comprehensive, holistic care to women of India at a reasonable cost. An interdisciplinary team of expert and caring professionals is committed to meeting the physical as well as emotional and spiritual needs for each woman and her family. The Wings Hospitals have been designed and furnished to provide a high level of fertility care with comfort and privacy.

SOURCE Presagen

See the rest here:
New hope for IVF patients as global study published in Human Reproduction shows AI can effectively assess genetic integrity of embryos - Yahoo Finance

Gordon Research Conference (GRC) Systems Aging 2022. Row 1: Vera Gorbunova, Cavin Ward-Caviness, ... [+] Samuel Beck, Sruthi Sivakumar, Vittorio Sebastiano, Steve Horvath, Vadim Gladyshev, Morgan Levine, Daniel Promislow, Brianah McCoy, Richard Miller; Row 2: Morten Scheibye-Knudsen, Diljeet Gill, Andrei Seluanov, Yuancheng Lu, Cynthia Kenyon, Nicholas Schork, Kristen Fortney, Sara Jovanovska, Steve Cummings, Vyacheslav Labunskyy, Kathrin Kajderowicz, Jane Chuprin, Nathan Price, Emma Teeling, Ruogu Fang, Martin Borch Jensen; Row 3: Ake Lu, Alex Chen, Naisha Shah, Sara Hagg, Oliver Hahn, Joris Deelen, Riccardo Marioni, Raghav Sehgal, Nick Schaum, Alex Zhavoronkov, Brian Chen, James Clement, Ryan Smith, Joo Pedro de Magalhes, Alexander Suvorov, Elinor Karlsson, Inigo Martincorena; Row 4: Ellen Quarles, Bradley English, Grace Edmonds, Iosif Gershteyn, Lillian Zhu, Laura Feiner, Brian Kennedy, Laura Goetz, Luay Boulahouache, Anahita Mojiri, Elisa Morales, Daniel Nachun, Hanna Barlit, Andrey Parkhitko, Daniel Richard, Hang Ma, Jeffrey Yunes; Row 5: Aqil Rashid, Patrick Griffin, Maximilian Unfried, Zhengping Hu, Sanjeev Goel, Nikola Markov, Priscila Chiavellini, Margaux Quiniou, Wayne Mitchell, Alex Trapp, Juan Vazquez, Thomas Stoeger, Ivan Morgunov, Dylan Suvlu, Daniel Vera, Peter Niimi, Jennifer Gamble, Michael Antonov; Row 6: Qi Yan, Elizabeth Gaskell, Kaiyang Cheng, Suzanne Martos, Jose Luis Ricon, Csaba Kerepesi, Kristen McGreevy, Arkadi Mazin, Gabrielle Gilmer, Zachary Hettinger, Grant Belgard, Benjamin Salzer, Koby Baranes, Enrique Ramos, Denis Tsygankov, Hamilton Oh, Benjamin Anderson, Michael Basson, Bryan Cox; Row 7: Ada Nguyen, Michael Petr, Nadia Sutton, Grace Phelps, Michael Florea, Gary Churchill, Manuel Serrano, Kenneth Raj, Peter Kharchenko, Mlanie Mangier, Brian Okundaye, Glen Pridham, Spring (Bahareh) Behrouz, Julio Leon Incio, Farzaneh Nasirian, Tomoko Kasahara, Xinna Li, Jesse Poganik, Changqi Zhu; Row 8: Andrei Tarkhov, Yuri Deigin, Nimrod Rappoport, Sun Hee Yim, Anastasia Shindyapina, Benjamin Barr, Mahdi Moqri, Kejun Ying, Bohan Zhang, Mia Petljak, Kay Linker, Marc Kirschner, Leon Peshkin, Robert Palovics, Steven Shuken, Gregory Johnson, Jacob Kimmel, Bruce Ksander, Manish Chamoli, jinlong lu, Larissa Smulders, Mathew Vadas, Andrea Cipriano, Peter Douglas, Weronika Prusisz, Sergiy Libert, James Welsh

Important Disclaimer: the conference does not allow any photography of posters and talks. Hence, all photos in the article were taken during the extracurricular and team building activities.

One of the best ways for young scientists to get inspired and advance their scientific carriers is to interact with the faculty, research management of major funding bodies, editors of major journals, and industry leaders who may later serve as their mentors. Now that coronavirus lockdowns are winding down, hopes are up and people are beginning to ditch virtual meetings for in-person interactions; it has led to a surge in events and conferences around the globe. This has allowed the scientists to finally meet in-person to share ideas and have open discussions. Of course, some of the conferences like the largest aging research and drug discovery conference, the annual ARDD forum, was held in Europe (Copenhagen) in 2020 and 2021 and may be even larger in 2022, but in the US scientists in aging research were starving for high-quality in person meetings. Since our AI-discovered dual-purpose novel target implicated in aging and fibrosis entered Phase I human clinical trials, I started to get invited to many AI, chemistry, biology, and aging research meetings. But at most of these meetings if you present unpublished data, it will be rapidly photographed and disseminated in the industry. So when I was invited to the Gordon Research Conference by two celebrity chairs, Harvard/MGB professor Vadim Gladyshev, and the father of methylation aging clocks (possible Nobel prize), UCLA professor and one of the top scientists at the newly-formed longevity startup, Altos Labs, Steve Horvath, I got very excited.

Conference Chair Professor Vadim Gladyshev

GRC is a platform where you can openly present unpublished research, get feedback and valuable advice, find collaborators, and be certain that no one will take pictures, or disclose confidential information. Also, the meeting was held in a super distant ski resort 1.5 hour drive from the nearest airport, and the academic and industry heavyweights could not leave that easily if you commit, you commit. So without disclosing anything confidential, I will try to provide you with a glimpse into this amazing meeting designed to promote open interaction between the scientists presenting unpublished data, and culminate with a word-for-word copy of the interview with the chairs who did such a great job organizing the event.

Screenshot of the GRC conference program

The Gordon Research Conferences is a non-profit organization that hosts international scientific conferences and seminars to bring a global network of scientists together to discuss the latest pre-publication research in their field. The conference topics cover frontier research in areas like analytical chemistry, aging, artificial intelligence, astrophysics, bioengineering, and neuroscience, among many other areas of science. The conferences have been held since 1931, and have expanded to nearly 200 conferences per year. In 2022, GRC has planned over 395 events a great way for like-minded people to gather, share ideas, and have a fun time. As part of its no publication policy, each member of a GRC conference or seminar agrees that any information presented at an event is a private communication from the individual making the contribution and is presented in a way that it is not for public use. This makes the GRC one of the most thought after conferences in the world and certainly one of the most strict when it comes to disclosing unpublished data externally. Since each conference is limited to 150-200 attendees; scientists must apply to the conference and be selected by the conference chair to attend the meeting. However, for those who are really interested in not missing out, the conference topics covered are regularly published in the journal Science.

Last day of the GRC conference - review of the results

One of the events hosted by the GRC this year was the conference called Systemic Processes, Omics Approaches, and Biomarkers in Aging. It was the inaugural Systems Aging Gordon Research Conference. Held in Newry, Maine, this event is not easy to get to. Many of the scientists on the East Coast of the US needed to spend half a day or more just to get there. There is a reason for this. Often, conferences that are organized in large metropolitan areas with easy access do not have the same level of pressure cooking and interactive networking just because many senior scientists tend to be distracted and often leave prematurely. But when they are put together in a remote location, it is not easy to leave and they have no choice but to interact with each other, share knowledge, and come up with new ideas and collaborations.

The level and impact of scientific conferences is often evaluated by the number and quality of the sponsors. And the GRC conference on Aging sported a number of high-profile sponsors including GRC itself, Carl Storm International Diversity Fellowship Program, National Institute on Aging, IOMICS Intelligent Analytics, Zymo Research, Kinexum, Insilico Medicine, Illumina, Aging journal, Impetus Grants, Infinita Life Science and VitaDAO.

Evening campfire get-together at the GRC

With Vadim Gladyshev serving as chairman and Steve Horvath as vice-chairman, the conference set the stage for the field, paving the way for the development of interventions to delay and reverse aging. Vadim is a professor of medicine at Harvard Medical School and director of Redox Medicine at Brigham and Womens Hospital, while Steve is a professor of human genetics and biostatistics at the University of California - Los Angeles, and a senior scientist at Altos Labs. Both are world-renowned researchers, and spoke and led the discussions at the conference.

The "Copenhagen Longevity Mafia" scientists from Scheibye-Knudsen lab arriving to the Portland ... [+] airport and excited to go to GRC. Newry, the actual location of the event is 1.5 hour bus ride away from the Portland airport to ensure that the scientists stay together.

The conference was attended by a number of prominent researchers from renowned institutions; such as Cynthia Kenyon of Calico Labs, who discussed about interventions that slow aging, Morten Scheibye-Knudsen of the University of Copenhagen, who talked about modulating DNA repair for healthy aging, and Emma Teeling of the University College Dublin, who spoke about the genetic basis of exceptional longevity of bats. Of course, there were many other luminaries and industry leaders. I spoke on the applications of deep aging clocks in clinical practice and described how we used AI and aging clocks to identify a dual-purpose aging and disease protein target that is now in Phase I clinical trials.

The conference included archery lessons. I spiced it up a little by adding individual target names: ... [+] TORC1, PHD2, and SIRT6 as a pun.

The fifth-day event was divided by various discussion topics so each day was highlighted by a new subject matter, sometimes two subject matters.

Day one was about Delaying Age, and was led by Steve Horvath as the discussion leader. On this day, Cynthia Kenyon, Richard Miller of the University of Michigan and Inigo Martincorena of the Sanger Institute presented. Richard and Inigo presented on drugs and mutations that slow aging in mice, and somatic mutations and clonal expansions in aging, respectively.

Day two was all about Epigenetic Reprogramming and Rejuvenation. It was led by Joe Betts-LaCroix of Retro Biosciences. Manuel Serrano of IRB Barcelona started the day with a talk on understanding and manipulating in vivo reprogramming and its effects on aging. He was followed by Vittorio Sebastiano of Stanford University, who spoke about transient reprogramming for multifaceted reversal of aging. Jacob Kimmel of NewLimit Research followed Vittorio with a talk on reprogramming strategies to restore youthful gene expression. Then came Morgan Levine of Yale University, who discussed DNA methylation landscapes in aging and reprogramming. She was followed by Yuancheng Lu of Whitehead Institute and Diljeet Gill of Altos Labs Cambridge Institute, who discussed reprogramming to recover youthful epigenetic information and restore vision, and multi-omics rejuvenation of human cells by maturation phase transient reprogramming, respectively. The second subject matter of the day was Genomics of Aging and was led by Emma Teeling as the discussion leader. Nicholas Schork of TGen discussed integrated approaches to characterizing the polygenic basis of longevity. Edward Boyden of MIT followed with a talk on technologies for mapping and controlling aging-related processes. Next came Martin Borch Jensen of Gordian Biotechnology with a talk on using pooled in vivo perturbation screens to understand how aging mechanisms manifest across tissues and cell types. He was followed by Joris Deelen of Max Planck, who discussed identification and functional characterization of genetic variants linked to human longevity.

The first discussion topic for the next day was Epigenetic Biomarkers, with Kristen Fortney of Bioage leading the discussions. First to the podium was Nick Schaum of Astera Institute, whose discussion topic was rejuvenome: toward a functional and multiomics understanding of aging and rejuvenation. Samuel Beck of MDI came after Nick and shared his thoughts on misexpression of genes lacking CpG islands. He was followed by Riccardo Marioni of University of Edinburgh and Ake Lu of San Diego Institute of Science, who discussed about epigenetic clocks and universal DNA methylating age, respectively. The day continued with Sara Hagg of Karolinska Institutet and Patrick Griffin of Harvard Medical School all speaking about aging research. The second subject of discussion of the day was Clinical and Molecular Biomarkers, and the discussions were led by Meng Wang of Baylor College. Cavin Ward-Caviness of the US EPA started the day with a discussion on air pollution and accelerated aging. He was followed by Morten, who was followed by Brian Kennedy of the NUS Singapore. The day ended with Paola Sebastiani of Tufts, who discussed molecular signatures of aging and extreme old age.

Day 4 Artificial Intelligence and Machine Learning

Artificial Intelligence and Machine Learning was the first subject matter for the next day, which was moderated by Marc Kirschner of Harvard. Sergiy Libert of Calico started the day with a talk on construction and analysis of the physiology clock for human aging. I took to the podium next and discussed applications of deep aging clocks in clinical practice and drug discovery. I was followed by Kristen Fortney of Bioage and Albert-laszlo Barabasi of Northeastern University, who discussed data-informed drug discovery for aging and the dark matter of nutrition, respectively. Other speakers included Peter Kharchenko of Harvard Medical School, Ruogu Fang of University of Florida, and Nathan Price of Thorne Health Tech. Following a short break, the day continued with Aging as a Systemic Process led by Steve Cummings. Meng Wang of Baylor College, Danica Chen of University of California, Amandine Chaix of University of Utah, Gary Churchill of The Jackson Laboratory, Xin Jin of Scripps Research, and Subhash Kulkarni of Johns Hopkins presented their views on aging and longevity.

Kristen Fortney, PhD, CEO of BioAge in the middle surrounded by the chairs of the 9th ARDD. Dr. ... [+] Fortney's BioAge has three Phase II programs in the pipeline and she will be presenting at ARDD in Copenhagen.

In my humble opinion, Kristen Fortneys BioAge presentation and some of the posters were probably the most important reveals at the conference. She has a Phase II clinical readout coming up in the matter of weeks. If this readout is successful, it will help boost our industry.

The first agenda for the last day was Comparative Genomics of Aging led by Andrei Seluanov of University of Rochester. Speakers included Vera Gorbunova of University of Rochester, Emma Teeling, Joao Pedro de Magalhase of University of Birmingham, Elinor Karlsson of UMass Chan Medical School, Leon Peshkin of the Harvard Systems Biology Department , Mia Petljak of Broad Institute, Vyacheslav Labunskyy of Boston University School of Medicine, Steve Cummings of San Fransisco Coordinating Center and Alex Colville of Stanford. The second agenda of the day was Fundamental Bases of Aging, led by Cynthia Kenyon. Kenneth Raj of Altos Labs presented first, and was followed by Daniel Promislow of University of Washington, Sruthi Sivakumar of University of Pittsburgh, Oliver Hahn of Stanford, and Margaux Quiniou of Brain Research Institute. The last speaker of the entire event was Peter Douglas of University of Texas Southwestern Medical Center, who d intracellular lipid surveillance in aging.

Over the course of the five-day event, presentations covered many topics, like delaying aging, aging clocks, longevity intervention, and so much more. Many organizations like MIT, Stanford and Yale were represented. It was truly a great opportunity to network with peers.

With this successful conference on aging, the GRC has now plans the second Systems Aging meeting in 2024.

Dr. Steve Horvath of UCLA and Altos Labs (left) and Dr. Vadim Gladyshev of Harvard MGH (right), the ... [+] two chairs of the Gordon Research Conference on aging

Alex Zhavoronkov: The GRC conference brought together some of the most advanced groups from all over the world. I understand that most of the research presented is unpublished, but just talking about the general trends, can you describe a few truly "hot" areas that are likely to impact the field for the years to come?

Professor Vadim Gladyshev:

Alex Zhavoronkov: If you were to highlight just five breakthrough talks, what would these be?

Professor Vadim Gladyshev: Talks from Ken Raj, Manuel Serrano, Ake Lu, Nathan Price, and Kristen Fortney particularly come to mind, but there were many other excellent talks too. There was also an outstanding set of posters, probably on average the strongest I have ever seen.

Alex Zhavoronkov: How close are we to seeing the first longevity therapeutics in humans and what needs to happen to get the pharma companies to invest heavily into this field?

Professor Vadim Gladyshev: We are probably 5-10 years away from it, as clinical trials are needed to unequivocally demonstrate the longevity effects of some interventions. For companies to heavily invest into the space, we need at least one intervention that significantly extends healthspan and lifespan without serious side effects.

Alex Zhavoronkov: I noticed that compared to several other GRCs I attended a few years back, there was surprisingly high number of industry speakers. Altos, Bioage, our company, VitaDAO, and several others (I will provide the list). Do you see that the industry started producing valuable scientific research output?

Professor Vadim Gladyshev: This is a characteristic feature of the field now. About a quarter of attendees at the Systems Aging GRC were from industry, and some of the best talks were delivered by scientists working at companies. In a way, some companies such as Altos, Calico, Bioage, Insilico Medicine, Retro, blur the distinction between academia and industry, as they support research that is published and presented at meetings. It may be a common goal or the nature of the field, but this is definitely an exciting time to be in this area.

Alex Zhavoronkov: Are there any groups and biotechnology companies that the pharmaceutical companies should evaluate closer for partnerships or learning the best practices?

If pharma is serious about expanding into this space, it should partner with the best academic science. This is the only way for major advances. Aging research appears simple to newcomers, and there is almost no barrier to join this field and begin contributing. However, aging is in fact incredibly complex. Moreover, there is currently no consensus on the most basic features of aging. So, it is easy to slip into doing research that is appealing, but which could lead to nowhere.

Alex Zhavoronkov: Aging clocks seem to be dominating the field right now. What are the most interesting findings in this field that you can highlight from the conference?

Professor Vadim Gladyshev: Aging clocks have started a revolution in the field. At the conference, we learned of various new types of clocks, both molecular and physiological, that could apply to cells, tissues, organisms and even species and that can be trained for various manifestations of aging.

Alex Zhavoronkov: I was very impressed by the social networking component of the conference. It is truly wonderful to see so many giants in the field in person. What was the most popular extracurricular activity that everyone enjoyed the most?

Professor Vadim Gladyshev: It seems that what attendees enjoyed most is the unmatched intellectual power of the group. I could see people discussing science well after midnight, every day. And they did it during various activities too: in the pool and sauna, while hiking and doing archery, at a bar and at a fire pit.

One of the highlights of GRC are the poster sessions. This is where the many young scientists can learn from the others, interact with veteran academics and industry leaders, and receive valuable feedback and collaboration proposals. Again, due to the nature of the conference, I will not talk about the unpublished data, and cover the posters, but one thing is clear - the field of aging research is rapidly advancing with the many new wonderful scientists joining the field, many new companies starting their journeys and many venture capitalists who are getting more and more sophisticated in this highly promising field.

Winners of the poster awards with the conference chairs

In the case that you have made it this far, I would like to encourage you to learn more about this exciting field and register for the next GRC in 2024. In the meantime, there are many resources that can help people from other industries as well as physicians, computer scientists, and venture capitalists get into the field of aging research. One of the best ways to get into the field is to take free introductory courses and attend industry conferences. The next large interdisciplinary conference on aging research will transpire in Europe, and is organized by the University of Copenhagen.

GRC Chairs, Dr. Vadim Gladyshev and Dr. Steve Horvath, with ARDD Chairs, Morten Scheibye-Knudsen, ... [+] MD, PhD, and Alex Zhavoronkov, PhD in the "Come to ARDD in Copenhagen" pose

If you enjoyed reading about the GRC conference, which is very difficult to get in, please consider attending the 9th Aging Research and Drug Discovery conference in Copenhagen, running from 29th of August to 2nd of September either virtually or in-person. Both GRC chairs will be presenting and many of the scientists who presented at the GRC will be at the ARDD. The ARDD will also bring together many venture capitalists, pharmaceutical companies, and startups in longevity biotechnology.

Read more here:
A Week At The Most Secretive Conference On Aging - Forbes

Summary

Host genetics and the gut microbiome can both influence metabolic phenotypes. However, whether host genetic variation shapes the gut microbiome and interacts with it to affect host phenotype is unclear. Here, we compared microbiotas across > 1,000 fecal samples obtained from the TwinsUK population, including 416 twin-pairs. We identified many microbial taxa whose abundances were influenced by host genetics. The most heritable taxon, the family Christensenellaceae, formed a cooccurrence network with other heritable Bacteria and with methanogenic Archaea. Furthermore, Christensenellaceae and its partners were enriched in individuals with low body mass index (BMI). An obese-associated microbiome was amended with Christensenella minuta, a cultured member of the Christensenellaceae, and transplanted to germfree mice. C. minuta amendment reduced weight gain and altered the microbiome of recipient mice. Our findings indicate that host genetics influence the composition of the human gut microbiome and can do so in ways that impact host metabolism.

The human gut microbiome has been linked to metabolic disease and obesity (Karlsson et al., 2013; Le Chatelier et al., 2013; Ley et al., 2005; Qin et al., 2012; Turnbaugh et al., 2009). Variation in host genetics can also underlie susceptibility to metabolic disease (Frayling et al., 2007; Frazer et al., 2009; Herbert et al., 2006; Yang et al., 2012). Despite these shared effects, the relationship between host genetic variation and the diversity of gut microbiomes is largely unknown.

The gut microbiome is environmentally acquired from birth (Costello et al., 2012; Walter and Ley, 2011), therefore it may function as an environmental factor that interacts with host genetics to shape phenotype, as well as a genetically determined attribute that is shaped by, and interacts with, the host (Bevins and Salzman, 2011; Spor et al., 2011; Tims et al., 2011). Because the microbiome can be modified for therapeutic applications (Borody and Khoruts, 2012; Hamilton et al., 2013; Khoruts et al., 2010; van Nood et al., 2013), it constitutes an attractive target for manipulation. Once the interactions between host genetics and the microbiome are understood, its manipulation could be optimized for a given host genome to reduce disease risk.

Although gut microbiomes can differ markedly in diversity across adults (Consortium, 2012; Qin et al., 2010), family members are often observed to have more similar microbiotas than unrelated individuals (Lee et al., 2011; Tims et al., 2013; Turnbaugh et al., 2009; Yatsunenko et al., 2012). Familial similarities are usually attributed to shared environmental influences, such as dietary preference, a powerful shaper of microbiome composition (Cotillard et al., 2013; David et al., 2013; Wu et al., 2011). Yet related individuals share a larger degree of genetic identity, raising the possibility that shared genetic composition underlies familial microbiome similarities.

Support for a host genetic effect on the microbiome comes mostly from studies taking a targeted approach. For instance, the concordance rate for carriage of the methanogen Methanobrevibacter smithii is higher for monozygotic (MZ) than dizygotic (DZ) twin pairs (Hansen et al., 2011), and studies comparing microbiotas between human subjects differing at specific genetic loci have shown gene-microbiota interactions (Frank et al., 2011; Khachatryan et al., 2008; Rausch et al., 2011; Rehman et al., 2011; Wacklin et al., 2011). A more general approach to this question has linked genetic loci with abundances of gut bacteria in mice (Benson et al., 2010; McKnite et al., 2012), but in humans, a general approach (e.g., using twins) has failed to reveal significant genotype effects on microbiome diversity (Turnbaugh et al., 2009; Yatsunenko et al., 2012). Thus, heritable components of the human gut microbiome remain to be identified using an unbiased approach.

Here, we assessed the heritability of the gut microbiome with a well-powered twin study. Comparisons between MZ and DZ twin pairs allowed us to assess the impact of genotype and early shared environment on their gut microbiota. Our study addressed the following questions: Which specific taxa within the gut microbiome are heritable, and to what extent? Which predicted metagenomic functions are heritable? How do heritable microbes relate to host BMI? Finally, we use fecal transplants into germfree mice to assess the phenotype effects of the most heritable taxon.

We obtained 1,081 fecal samples from 977 individuals: 171 MZ and 245 DZ twin pairs, 2 from twin pairs with unknown zygosity, and 143 samples from just one twin within a twinship (i.e., unrelated). In addition, we collected longitudinal samples from 98 of these individuals (see Supplemental Information). Most subjects were female, ranging in age from 23 to 86 years (average age: 60.6 0.3 years). The average BMI of the subjects was 26.25 ( 0.16) with the following distribution: 433 subjects had a low to normal BMI (<25), 322 had an overweight BMI (25-30), 183 were obese (>30) and 39 individuals in which the current BMI status was unknown. We generated 78,938,079 quality-filtered sequences that mapped to the Bacteria and Archaea in the Greengenes database (average sequences per sample: 73,023 889).

We sorted sequences into 9,646 operational taxonomic units (OTUs, 97% ID). Of these OTUs, 768 were present in at least 50% of the samples. Taxonomic classification revealed a fairly typical Western diversity profile: the dominant bacterial phyla were Firmicutes (53.9% of total sequences), Bacteroidetes (35.3%), Proteobacteria (4.5%), with Verrucomicrobia, Actinobacteria, and Tenericutes each comprising 2% of the sequences, and a tail of rare bacterial phyla that together accounted for the remaining 1% of the sequences.

The most widely shared methanogen was M. smithii (64% of people, using nonrarefied data), followed by vadinCA11, a member of the Thermoplasmata with no cultured representatives (~6%), Methanospheara stadtmanae (~4%), and Methanomassiliicoccus (~4%, a member of the Thermoplasmata). Forty-six of the 61 samples in which we detected vadinCA11 also contained M. smithii, indicating that the two most dominant archaeal taxa are not mutually exclusive. Faith's PD was positively correlated with the relative abundance of the family Methanobacteriaceae (rho = 0.42 rarefied, 0.37 for transformed counts, P < 1 x 1011), which corroborates previous reports of higher richness associating with methanogens.

We observed that microbiotas were more similar overall within individuals (resampled) than between unrelated individuals (P < 0.001 for weighted and unweighted UniFrac and Bray-Curtis using a Student's t-test with 1,000 Monte Carlo simulations; Table S1A), and were also more similar within twin pairs compared to unrelated individuals (P < 0.009 for weighted and unweighted UniFrac and Bray-Curtis; , S1 and Table S1). MZ twin pairs had more similar microbiotas than DZ twins for the unweighted UniFrac metric (P = 0.032), but not the weighted UniFrac and Bray-Curtis metrics (, S1). As greater similarities for MZ versus DZ twin pairs are seen in unweighted UniFrac but not abundance-based metrics, MZ similarities are driven by shared community membership rather than structure.

A, C-F: Box plots of beta-diversity distances between microbial communities obtained when comparing individuals within twinships for monozygotic (MZ) twin pairs and dizygotic (DZ) twin pairs, and between unrelated individuals (UN). A: the whole microbiome; C: the bacterial family Ruminococcaceae; D-E: the bacterial family Lachnospiraceae; F: the family Bacteroidaceae. The specific distance metric used in each analysis is indicated on the axes. *P<0.05, **P<0.01, ***P<0.001 for Student's t-tests with 1,000 Monte Carlo simulations. B: The average relative abundances in the whole dataset for the top six most prevalent bacterial families (unrarefied data, see Methods). Relates to Figure S1 and Table S1.

We next constrained the distance metric analyses to the three most dominant bacterial families: the Lachnospiraceae and Ruminococcaceae (Firmicutes) and Bacteroidaceae (). We observed greater similarities for MZ compared to DZ twins using the unweighted UniFrac metric within the Ruminococcaceae family (). Within the Lachnospiraceae family, significantly greater similarity for MZ compared to DZ twins emerged using the weighted UniFrac and Bray-Curtis metrics (). In contrast, when restricted to the Bacteroidaceae family, we found that MZ and DZ twins had similar pair-wise diversity using all three metrics (, S1B and S1E).

We next asked if the abundances of specific taxa were generally more highly correlated within MZ twin pairs compared to DZ twin pairs. For each twin pair we generated intraclass correlation coefficients (ICCs) for the relative abundances of OTUs. Mean ICCs were significantly greater for MZ compared to DZ twin pairs (Wilcoxon signed rank test on ICCs at the OTU level, P = 6 x 1004; ). Since many OTUs are closely phylogenetically related, their abundances may not be independent, which may inflate levels of significance. To account for this effect, we maintained the structure of the phylogenetic tree but permuted the MZ and DZ labels in 10,000 tests to generate randomized ICCs. As an independent validation, we also applied these analyses to two previously published datasets generated originating in a population of twins from Missouri, USA: Turnbaugh (Turnbaugh et al., 2009), which described 54 twin pairs ranging from 21-32 years of age, and Yatsunenko (Yatsunenko et al., 2012), which included 63 twin pairs with an age range of 13-30 years of age. Mean ICCs of OTU abundances were significantly greater for MZ compared to DZ twin pairs in both of these datasets (significance by permutation: P < 0.001 and 0.047 respectively; Figure S2), corroborating our observations.

At left is a phylogeny of taxa in the TwinsUK study (Greengenes tree pruned to include only OTUs shared by 50% of the TwinsUK participants) and at right are corresponding twin-pair intra class correlation coefficients (ICCs). ICCs were calculated for each OTU and the difference in correlation coefficients for MZ twin pairs versus DZ twin pairs. Bars pointing to the right indicate that the difference is positive (i.e., MZ ICCs > DZ ICCs) and bars pointing to the left indicate negative differences (DZ ICCs > MZ ICCs). The scale bar associated with the phylogeny shows substitutions/site. Relates to Figure S2.

We estimated heritability using the twin-based ACE model, which partitions the total variance into three component sources: genetic effects (A), common environment (C), and unique environment (E) (Eaves et al., 1978). The largest proportion of variance in abundances of OTUs could be attributed to the twins unique environments (i.e., E > A; Table S2). However, for the majority of OTUs (63%), the proportion of variance attributed to genetic effects was greater than the proportion of variance attributed to common environment (A > C; Table S2).

From the ACE model we calculated 95% confidence intervals for the heritability estimates, and determined the significance of the heritability values using a permutation method to generate nominal P values (Table S2). We found a high correlation between the tail probability for inclusion of zero in the confidence interval of heritability and the P values obtained from the permutation tests (rho = 0.872, P < 1015), indicating substantial consistency across these tests. Although heritability studies traditionally report confidence intervals and nominal P values only, we also generated FDR-corrected P values (Table S2).

We also applied the ACE model to the abundances of sequences mapping to each node in the phylogeny. Across the three studies, the nodes of the phylogeny with the strongest heritabilities lie within the Ruminococcaceae and Lachnospiraceae families, and the Bacteroidetes are mostly environmentally determined ( and S3). Subsets of the Archaea are also heritable in the TwinsUK and the Yatsunenko studies (the Turnbaugh study did not include data for Archaea).

A: OTU Heritability (A from ACE model) estimates mapped onto a microbial phylogeny and displayed using a rainbow gradient from blue (A = 0) to red (A 0.4). This phylogenetic tree was obtained from the Greengenes database and pruned to include only nodes for which at least 50% of the TwinsUK participants were represented. B: The significance for the heritability values shown in A was determined using a permutation test (n=1,000) and are shown on the same phylogeny as in panel A. P values range from 0 (red) to >0.1 (blue). Relates to Figure S3 and Table S2.

We characterized the longitudinal stability of each OTU by calculating the ICCs of the OTU abundance across repeat samples, which consisted of two samples collected from the same individual at different times. By permuting these repeat sample ICCs, we found that heritable OTUs (A > 0.2) were more stable (ICC > 0.6) than expected by chance (Figure S3E; P < 0.001, P value was determined as the fraction of permutations that had greater than or equal to the observed number of OTUs that are both heritable and stable).

We used PICRUSt (Langille et al., 2013) to produce predicted metagenomes from the 16S rRNA gene sequence data and applied the ACE model to estimate the heritability of predicted abundances of conserved orthologous groups (COGs). This analysis revealed 6 functions with heritabilities A > 0.2 and nominal P values < 0.05 (P values are generated by permutation testing; Supplementary Methods; Table S2). Correcting for multiple comparisons, one category, secondary metabolites biosynthesis, transport and catabolism (Q), passed a stringent FDR (A = 0.32, 95% CI = 0.16-0.44). We also tested alpha diversity for heritability and found that it was not heritable.

The most heritable taxon overall was the family Christensenellaceae (A = 0.39, 95% confidence interval 0.21-0.49, P = 0.001, and Table S2; this taxon passes a stringent FDR) of the order Clostridiales. Christensenellaceae was also highly heritable in the Yatsunenko dataset (A = 0.62, 95% confidence interval 0.38-0.77; and Table S2). We repeated this analysis for the taxa abundances with the effect of BMI regressed out, and results were highly correlated (Pearson correlation = 0.95, P < 11015).

Scatter plots comparing the abundances of Christensenellaceae in the gut microbiota of MZ and DZ co-twins. Christensenellaceae abundances were transformed and adjusted to control for technical and other covariates (Residuals are plotted, see Supplemental Methods) and the data are separated by zygosity (MZ or DZ twins). A: TwinsUK dataset. B: Yatsunenko dataset.

We observe a module of co-occurring heritable families, and the hub (node connected to most other nodes) of this module is the family Christensenellaceae ( and S4A). The heritable module includes the families Methanobacteriaceae (Archaea) and Dehalobacteriaceae (Firmicutes) and the orders SHA-98 (Firmicutes), RF39 (Tenericutes) and ML615J-28 (Tenericutes). The Christensenellaceae-network is anti-correlated with the Bacteroidaceae and Bifidobacteriaceae families. We validated these results by applying this method to the family-level taxonomic abundances in the Yatsunenko dataset (as this one is most technically similar to the TwinsUK dataset), where we also found the same Christensenellaceae-centered module of heritable families anti-correlated to the Bacteroidaceae/Bifidobacteriaceae module (Figure S4B).

A and B show the same network built from SparCC correlation coefficients between sequence abundances collapsed at the family level. The nodes represent families and the edges represent the correlation coefficients between families. Edges are colored blue for a positive correlation and grey for a negative correlation, and the weight of the edge reflects the strength of the correlation. Nodes are positioned using an edge-weighted force directed layout. In panel A, the nodes are colored by the heritability of the family, and in panel B, the nodes are colored by the significance of the association families and a normal vs. obese BMI. Family names are either indicated on the panel, or nodes are given a letter code. Phylum Actinobacteria: (a) Actinomycetaceae, (b) Coriobacteriaceae; Phylum Bacteroidetes: (c) Barnesiellaceae, (d) Odoribacteraceae, (e) Paraprevotellaceae, (f) Porphyromonadaceae, (g) Prevotellaceae, (h) Rikenellaceae; Phylum Firmicutes: (i) Carnobacteriaceae, (j) Clostridiaceae, (k) Erysipelotrichaceae, (l) Eubacteriaceae, (m) Lachnospiraceae, (n) Lactobacillaceae, (o) Mogibacteriaceae, (p) Peptococcaceae, (q) Peptostreptococcaceae, (r) Ruminococcaceae, (s) Streptococcaceae, (t) Tissierellaceae, (u) Turicibacteraceae, (v) Unclassified Clostridiales, (w) Veillonellaceae; Phylum Proteobacteria: (x) Alcaligenaceae, (y) Enterobacteriaceae, (z) Oxalobacteraceae, (aa) Pasteurellaceae, (ab) Unclassified RF32; Phylum Verrucomicrobia: (ac) Verrucomicrobiaceae. Relates to Figure S4.

The family Christensenellaceae was significantly enriched in subjects with a lean BMI (< 25) compared to those with an obese BMI (> 30; Benjamini-Hochberg corrected P value < 0.05 from t-test on transformed counts; Table S2). Other members of the Christensenellaceae consortium were also enriched in lean-BMI subjects: the Dehalobacteriaceae, SHA-98, RF39, and the Methanobacteriaceae (). Overall, a majority (n=35) of the OTUs with highest heritability scores (A > 0.2, nominal P < 0.05) were enriched in the lean subjects. A subset of OTUs classified as Oscillospira were enriched in lean subjects, and M. smithii, though not significantly heritable, was positively associated with a lean BMI.

Because the names Christensenella and Christensenellaceae were only recently assigned to the bacterial phylogeny, we assessed the abundances of sequences assigned to these taxa in previously published studies. This analysis revealed that members of the Christensenellaceae were enriched in fecal samples of healthy versus pediatric and young adult IBD patients (P < 0.05) (Papa et al., 2012). Christensenellaceae were at greater abundance in lean-BMI compared to obese-BMI twins in the Turnbaugh dataset but the difference was not quite significant (time-point 2 samples, P = 0.07). In a case study of the development of an infant's gut microbiome (Koenig et al., 2011), Christensenellaceae was present at 8.6% in the mother's stool at the time of birth, and at 20% in the infant's meconium. We also noted that Christensenellaceae is enriched in omnivorous compared to herbivorous and carnivorous mammals (Muegge et al., 2011). However, we did not find a relationship between Christensenellaceae and diet information in human studies (Wu et al., 2011; Martinez et al., 2010; Koren et al., 2012).

Methanogens co-occurred with Christensenellaceae in this study and have been linked to low BMI in previous studies. Because of this previous association with a low-BMI, we wanted to ensure that methanogens were present in the Christensenellaceae consortium in an initial experiment exploring its effect on weight phenotypes. Therefore, we selected 21 donors for fecal transfer to germfree mice based on BMI status (low or high) and presence or absence of the methanogen-Christensenellaceae consortium. Donors fell into one of four categories: lean with detectable methanogens (L+), lean without methanogens (L-), obese with methanogens (O+), or obese without methanogens (O-). The abundance of Christensenellaceae positively correlated with the abundance of methanogens in donor stool (rho=0.72, P=0.0002), indicating that methanogen abundance was a good proxy for the methanogen-Christensenellaceae consortium.

A 16S rRNA analysis of the fecal microbiomes before and after transfer to germfree mice showed that although members of the Christensenellaceae were present throughout the experiment in recipient mice (), M. smithii was undetectable in the mouse fecal or cecal samples (the first sampling was at 20hrs post-inoculation). At 20 hrs post-inoculation, the microbiota had shifted dramatically in diversity from the inoculation, but by Day 5 had shifted back partially and remained fairly stable through Day 21 (, S5A, and S5B). Abundances of Christensenella were correlated with PC3 (abundances rarefied at 55,000 sequences per sample vs. unweighted UniFrac; Spearman rho = 0.59, P < 2.2 x 1016), and PC3 captured the differences between the 4 donor groups (). We observed a trend for Christensenella abundances as highest in the L+ group and lowest in the O- group (), which mirrored the weight differences between those groups: the percent change in body weights of the recipient mice was significantly lower in the L+ group compared to the O- group (Day 12, P < 0.05, t-test; ). Cecal levels of propionate and butyrate were significantly elevated in mice receiving methanogen-positive compared to methanogen-negative microbiomes controlling for the effect of donor BMI (two-way ANOVA, P < 0.05 for both SCFAs, Figures S5C-E). Stool energy content was significantly higher for the methanogen-positive microbiomes at Day 12, when the percent changes in weight were greatest (two-way ANOVA, P = 0.004, no effect of BMI or interaction; Figure S5F). In a replicated experiment, using 21 new donors, the same weight differences were observed (a significantly lower mean weight gain for the L+ compared to the O- mouse recipients at Day 10 post-inoculation; one-way t-test, P = 0.047; Figure S5G).

A: Median relative abundances for OTUs classified as the genus Christensenella in the four donor treatment groups over time in the recipient mouse microbiotas. B: Principal coordinates analysis of unweighted UniFrac distances for (i) the inoculum prior to transplantation, (ii) fecal samples at 4 time points, and (iii) cecal samples at Day 21 post-transplant; see panel legend for color key. The amount of variance described by the first two PCs is shown on the axes. C: Richness (Faith's PD) for the microbiomes of the transplant mice plotted against time (days post inoculation, with Day 0 = inoculation day). D: The mean values S.E.M. for PC3 derived for the same analysis as shown in panel B are plotted against time (Day 0 = inoculation day) for the four treatment groups. The amount of variance explained by PC3 is in parentheses. E: Percent weight change since inoculation for germfree mouse recipients of 21 donor stools that were obtained from lean or obese donors with or without detectable M. smithii, which was used as a marker for the Christensenellaceae consortium. Means for each treatment group are plotted S. E. M. F: Box plots for percent weight changes for the 4 groups at Day 12 post-transplant, when maximal weight differences were observed. Letters next to boxes indicate significant differences if letters are different (p < 0.05). For all panels, Dark blue = L+, lean donor with methanogens; Light blue = L-, lean donor lacking methanogens; Dark orange = O+, obese donor with methanogens; Light orange = O-, obese donor without methanogens. We repeated this experiment with a set of 21 new mice and unique human donors and recovered the same effect. Relates to Figure S5.

Based on the observation that Christensenella levels in the previous experiment were similar to the weight gain patterns, we performed experiments in which a donor stool lacking detectable Christensenella was amended with C. minuta and weight gain of recipient mice was monitored. One obese human donor was selected from the 21 donors from the first transplant experiment based on its lack of detectable OTUs assigned to the genus Christensenella. At Day 21 post-gavage, mice receiving the C. minuta treatment weighed significantly less than those that received unamended stool (nested ANOVA, P < 0.05, ). Adiposity was significantly lower for mice receiving the C. minuta treatment (nested ANOVA, P = 9.4 x 105, ). Energy content for stool collected at Day 21 was not different between treatments (data not shown).

A: Box plot of percent weight change for germfree mouse recipients of a single donor stool only (lacking detectable Christensenella in unrarefied 16S rRNA data) or the donor stool amended with live C. minuta. B: Box plots showing percent body fat for mice in each group at Day 21 N = 12 mice per treatment. C, D: Principal coordinates analysis of unweighted UniFrac distances for (i) the inoculum prior to transplantation, (ii) fecal samples at 5 time points post-transplant; see panel legend for color key. The amount of variance described by the first two PCs is shown on the axes. The same data projection is shown in panels C and D; sample symbols are colored by time point (C) and by treatment (D). E: Relationship between PCs from the PCoA analysis and levels of Oscillospira at Day 21 (rho = 0.71, P = P < 0.001). Symbols are colored by treatment. Relates to Figure S6.

Analysis of the microbial community by 16S rRNA gene sequencing showed an impact on the overall community diversity that persisted over time (). After an initial acclimation (20 h), the communities within recipient mice began to separate by treatment regardless of the effects of time and co-caging ( and S6). At 5 days post-inoculation, the relative abundance of C. minuta was similar to that observed in the previous transplant experiment and persisted throughout the duration of the study. We identified two genera that discriminated the two treatments at Day 21: Oscillospira and a genus within the Rikenellaceae were enriched in the C. minuta treatment (misclassification error rate of 0.06). Oscillospira abundances were significantly correlated with PC2 in the unweighted UniFrac analysis of the communities (rho = 0.71, P = 0.0009; ), which is the PC that separates the C. minuta-amended and unamended microbiotas.

Our results represent the first strong evidence that the abundances of specific members of the gut microbiota are influenced in part by the genetic makeup of the host. Earlier studies using fingerprinting approaches also reported host genetic effects (Stewart et al., 2005; Zoetendal et al., 2001), but without sequence data it is not possible to know if the taxa shown here to be heritable were also driving those patterns. The Turnbaugh et al. and Yatsunenko et al. studies, which are quite similar in experimental approach, reported a lack of host genetic effect on the gut microbiome, most likely because both studies were underpowered. Nevertheless, re-analysis of the data from both studies validated our observation that the abundances of taxa are more highly correlated within MZ than DZ twin pairs. Thus, host genetic interactions with specific taxa are likely widespread across human populations, with profound implications for human biology.

The most highly heritable taxon in our dataset was the family Christensenellaceae, which was also the hub of a co-occurrence network that includes other taxa with high heritability. A notable component of this network was the archaeal family Methanobacteriaceae. Similarly, Hansen et al. had previously identified members of the Christensenellaceae (reported as relatives of Catabacter) as co-occurring with M. smithii (Hansen et al., 2010). These co-occurrence patterns could derive from different scenarios: for instance, multiple taxa may be heritable and co-occur while each taxon is affected by host genetics independently, or alternatively one (or a few) taxa may be heritable and other taxa correlate with host genetics due to their co-occurrence with these key heritable taxa. Further experimental research will be required to elucidate if the co-occurring heritable taxa interact in syntrophic partnerships or simply respond similarly to host-influenced environmental cues in the gut.

Our results suggest that environmental factors mostly shape the Bacteroidetes community, since most were not heritable. These results are consistent with those of a recent study of Finnish MZ twins, in which levels of Bacteroides spp. were more similar between twins when their diets were similar (Simoes et al., 2013). Members of the Bacteroidetes have been shown to respond to diet interventions (Wu et al., 2011; David et al. 2013)

Importantly, the family Christensenellaceae is heritable in the Yatsunenko dataset and its network is also present. This validation did not involve a directed search using the taxa identified in this study but was made by applying the ACE model independently. In the TwinsUK as well as the Missouri twins datasets, the majority of OTUs with the highest heritability estimates fell within the Ruminococcaceae and Lachnospiraceae families. The Missouri and TwinsUK studies differed somewhat in the levels and structure of heritability, which may relate to study size (Kuczynski et al., 2010), participant age (Claesson et al., 2011), population (Yatsunenko et al., 2012), and/or diet (Wu et al., 2011), all of which have been shown to affect microbiome structure.

The high heritability of the Christensenellaceae raises questions about the nature of interactions between the host and members of this family, but to date there is little published work with which to infer their roles. Christensenella minuta is Gram-negative, non-spore forming, non-motile, and produces SCFAs (Morotomi et al., 2012). A review of publicly available data suggests it is present from birth and associates with a healthy state but not with diet. Thus, although diet is a heritable trait in the same population (Menni et al., 2013; Teucher et al., 2007), it does not appear to be driving the heritability of the Christensenellaceae. Obesity is also strongly heritable in the TwinsUK population, raising the question of whether the heritabilities we saw for gut microbes were driven by BMI. To test this, we reran the heritability calculations using residuals after regressing out the effect of BMI and found that results of the two analyses were highly correlated. This suggests that the effect of host genetics on Christensenellaceae abundance is independent of an effect of BMI.

Our transplantation experiments showed a moderating effect of methanogen-presence in the human donor on weight gain of recipient mice, although strikingly, M. smithii did not persist in mice. In contrast, Christensenellaceae levels in mice mirrored their weight gain. Transfer to germfree mice of microbiomes from obese and lean donors generally results in greater adiposity gains for obese compared to lean donors (Ridaura et al., 2013; Turnbaugh et al., 2008; Vijay-Kumar et al., 2010). These studies have not reported the methanogen or Christensenellaceae status of the donors, so whether these microbes affect the host phenotype is unknown. M. smithii has been associated with a lean phenotype in multiple studies (Million et al., 2013; Million et al., 2012; Schwiertz et al., 2010; Armougom et al., 2009; Le Chatelier, 2013), raising the possibility that methanogens are key components of the consortium for regulating host phenotype. The results of our methanogen-Christensenellaceae transfer revealed that although methanogens may be a marker for a low BMI in humans, they are not required to promote a lean phenotype in the germfree mouse experimental model. This result suggests that methanogens may be functionally replaced by another consortium member in the mouse, while the Christensenellaceae are not.

The results of the C. minuta spike-in experiments supported the hypothesis that members of the Christensenellaceae promote a lean host phenotype. Addition of C. minuta also remodeled the diversity of the community. Intriguingly, Oscillospira, which includes heritable OTUs in the TwinsUK dataset and is associated with a lean BMI, was enriched in the C. minuta-amended microbiomes. How C. minuta reshapes the community remains to be explored. The relatively low levels of C. minuta and its profound effects on the community and the host may indicate that it is a keystone taxon. Together these findings indicate that the Christensenellaceae are highly heritable bacteria that can directly contribute to the host phenotype with which they associate.

Fecal samples were obtained from adult twin pair participants of the TwinsUK registry (Moayyeri, 2013). Most participants were women (only 20 men were included). Twins collected fecal samples at home, and the samples were refrigerated for up to 2 days prior to their annual clinical visit at King's College London, at which pointed they were stored at 80C until processing.

We amplified 16S rRNA genes (V4) from bulk DNA by PCR prior to sequencing on the Illumina MiSeq 2x250bp platform at Cornell Biotechnology Resource Center Genomics Facility. We performed quality filtering and analysis of the 16S rRNA gene sequence data with QIIME 1.7.0 (Caporaso et al., 2010).

PICRUSt v1.0.0 was used to predict abundances of COGs from the OTU abundances rarefied at 10,000 sequences per sample.

Heritability estimates were calculated on the OTU abundances, taxon bins, nodes throughout the bacterial phylogenetic tree, -diversity, and PICRUSt-predicted COGs using the structural equation modeling software OpenMx (Boker et al., 2011).

Stool samples from the Twins UK cohort were selected as described in the main text and inoculated into 6-week old germ-free Swiss Webster mice via oral gavage, with one recipient mouse per fecal donor. Mice were single-housed. For the Christensenella minuta addition, three experiments were conducted: In the first experiment, one treatment group received only donor stool inoculum, whereas the other received donor stool amended with 1 108C. minuta cells;for the second experiment, a heat-killed C. minuta control was added; in the third experiment, the heat-killed control was compared to live C. minuta only (no vehicle-only control). Mice were housed 4 per cage, with 3 cages per treatment. In all experiments, mice were provided with autoclaved food and water ad libitum and maintained on a 12-hr light/dark cycle. Body weight and chow consumption were monitored and fecal pellets were collected weekly. At sacrifice, adiposity was analyzed using DEXA. Body, mesenteric adipose tissue, and gonadal fat pad tissue weights were collected at this time. Gross energy content of mouse stool samples was measured by bomb calorimetry using an IKA C2000 calorimeter (Dairy One, Ithaca, NY). Wet cecal contents were weighed and resuspended in 2% (v/v) formic acid by vortexing and measured using a gas chromatograph (HP series 6890) with flame ionization detection.

Values are expressed as the mean SEM unless otherwise indicated. Full methods are described in the Supplemental Information

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Author Contributions: R.E.L. and A.G.C. supervised the study, and J.T.B. and T.D.S. helped design study and provided comments and discussion. J.T.B. and T.D.S. oversaw collection of samples; J.K.G., R.E.L., O.K., J.L.S., A.C.P, J.L.W. oversaw microbial data generation; J.K.G. performed the analysis with contributions from R.E.L, R.B., A.G.C., J.L.W., O.K., A.C.P, M.B., W.V.T. and R.K; J.K.G. and J.L.W. performed microbiota transfer experiments; J.K.G., J. L.W and R.E.L. prepared the manuscript, with comments from A.G.C, T.D.S, J.T.B, R.B., and R.K.

Author Information: The 16S rRNA gene sequences have been deposited in the European Nucleotide Archive (ENA), European Bioinformatics Institute, with accession numbers ERP006339 and ERP006342.

SUPPLEMENTAL INFORMATION

Supplemental Information includes Extended Experimental Procedures and data and can be found with this article online.

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Human genetics shape the gut microbiome - PMC

June 12, 2022

A conference abstract presented at the European Society of Human Genetics Conference looks at the use of retinal vascular complexityto predict risk of myocardial infarction.

Professor Sir Nilesh Samani, Medical Director at the British Heart Foundation, said:

The earlier and more accurately we can predict someones risk of heart attacks, the better the opportunities for prevention. This study suggests that information from retinal scans can improve such prediction. However, more research is needed to show that this improvement in prediction is robust. Work will also be required to understand the feasibility of this approach and determine how best to incorporate these scans into routine clinical practice.

Dr James Ware, Cardiologist, Reader in Genomic Medicine at Imperial College London and MRC Investigator, MRC London Institute of Medical Sciences, said:

The abstract is very concise and does not contain much methodological detail (as is often the case for a conference abstract). This doesnt mean that there is any problem with the work, but I am not able to judge whether the study is robust from this short summary, and it has not been peer reviewed, so I would await more detail before forming an opinion on the robustness of the findings.

There was a paper that looks very similar earlier this year in Nature Machine Intelligence (https://www.nature.com/articles/s42256-021-00427-7) also using imaging of retinal vessels to predict myocardial infarction (MI). There isnt enough info in the abstract to make clear to me if this approach is importantly different or better.

And there is other prior work predicting coronary artery disease (though not specifically MI) https://www.thelancet.com/journals/landig/article/PIIS2589-7500(21)00043-1/fulltext, also using the UK biobank.

It is well recognised that the retina provides a unique opportunity to directly visualise vessels and assess vascular health. Approaches like this that use computer vision and/or machine learning to detect subtle vascular features predictive of future heart health appear promising.

This study also included genetic information in the prediction model which would not normally be available at the time of a routine eye exam. It will be interesting to see whether the model identifies people at risk of MI without knowing their polygenic risk score, as this would be simpler to implement in practice. Genetic risk scores also promise to be very powerful tools for early identification of at-risk individuals, and indeed genetic risk can be assessed from birth.

The studies also highlight the enormous value of the UK Biobank which is a hugely powerful research resource, and represents a fantastic investment in science in the UK, with far reaching benefits.

The press release is based off an abstract Decreased retinal vascular complexity is an early biomarker of myocardial infarction supported by a shared genetic control being presented at the European Society of Human Genetics Conference and was under embargo until 23:01 UK time Sunday 12 June.

Declared interests

Dr James Ware: I dont have any disclosures that are relevant.!

No others received.

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expert reaction to a conference abstract on retinal screening predicting risk of myocardial infarction - Science Media Centre