Oxford researchers develop 3D printing method that shows promise for repairing brain injuries

Peer-Reviewed Publication

UNIVERSITY OF OXFORD

 

IMAGE: 

DROPLETS CONTAINING HUMAN IPSC-DERIVED NEURAL PROGENITORS WERE 3D-PRINTED TO FORM 2-LAYER CEREBRAL CORTICAL TISSUE, WHICH WAS CULTURED BEFORE IMPLANTATION INTO A MOUSE BRAIN SLICE. DNPS: DEEP-LAYER NEURAL PROGENITORS; UNPS: UPPER-LAYER NEURAL PROGENITORS. IMAGE CREDIT: YONGCHENG JIN, UNIVERSITY OF OXFORD.

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CREDIT: YONGCHENG JIN, UNIVERSITY OF OXFORD

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• Researchers have produced an engineered tissue representing a simplified cerebral cortex by 3D printing human stem cells.
• When implanted into mouse brain slices, the structures became integrated with the host tissue.
• The technique may ultimately be developed into tailored repairs to treat brain injuries.

A breakthrough technique developed by University of Oxford researchers could one day provide tailored repairs for those who suffer brain injuries. The researchers demonstrated for the first time that neural cells can be 3D printed to mimic the architecture of the cerebral cortex. The results have been published today in the journal Nature Communications.  

Brain injuries, including those caused by trauma, stroke and surgery for brain tumours, typically result in significant damage to the cerebral cortex (the outer layer of the human brain), leading to difficulties in cognition, movement and communication. For example, each year, around 70 million people globally suffer from traumatic brain injury (TBI), with 5 million of these cases being severe or fatal. Currently, there are no effective treatments for severe brain injuries, leading to serious impacts on quality of life.

Tissue regenerative therapies, especially those in which patients are given implants derived from their own stem cells, could be a promising route to treat brain injuries in the future. Up to now, however, there has been no method to ensure that implanted stem cells mimic the architecture of the brain.

In this new study, the University of Oxford researchers fabricated a two-layered brain tissue by 3D printing human neural stem cells. When implanted into mouse brain slices, the cells showed convincing structural and functional integration with the host tissue.

Lead author Dr Yongcheng Jin (Department of Chemistry, University of Oxford) said: ‘This advance marks a significant step towards the fabrication of materials with the full structure and function of natural brain tissues. The work will provide a unique opportunity to explore the workings of the human cortex and, in the long term, it will offer hope to individuals who sustain brain injuries.’

The cortical structure was made from human induced pluripotent stem cells (hiPSCs), which have the potential to produce the cell types found in most human tissues. A key advantage of using hiPSCs for tissue repair is that they can be easily derived from cells harvested from patients themselves, and therefore would not trigger an immune response.

The hiPSCs were differentiated into neural progenitor cells for two different layers of the cerebral cortex, by using specific combinations of growth factors and chemicals. The cells were then suspended in solution to generate two ‘bioinks’, which were then printed to produce a two-layered structure. In culture, the printed tissues maintained their layered cellular architecture for weeks, as indicated by the expression of layer-specific biomarkers.

When the printed tissues were implanted into mouse brain slices, they showed strong integration, as demonstrated by the projection of neural processes and the migration of neurons across the implant-host boundary. The implanted cells also showed signalling activity, which correlated with that of the host cells. This indicates that the human and mouse cells were communicating with each other, demonstrating functional as well as structural integration.

The researchers now intend to further refine the droplet printing technique to create complex multi-layered cerebral cortex tissues that more realistically mimic the human brain’s architecture. Besides their potential for repairing brain injuries, these engineered tissues might be used in drug evaluation, studies of brain development, and to improve our understanding of the basis of cognition.

The new advance builds on the team’s decade-long track record in inventing and patenting 3D printing technologies for synthetic tissues and cultured cells.

Senior author Dr Linna Zhou (Department of Chemistry, University of Oxford) said: ‘Our droplet printing technique provides a means to engineer living 3D tissues with desired architectures, which brings us closer to the creation of personalized implantation treatments for brain injury.’

Senior author Associate Professor Francis Szele (Department of Physiology, Anatomy and Genetics, University of Oxford) added: ‘The use of living brain slices creates a powerful platform for interrogating the utility of 3D printing in brain repair. It is a natural bridge between studying 3D printed cortical column development in vitro and their integration into brains in animal models of injury.’

Senior author Professor Zoltán Molnár (Department of Physiology, Anatomy and Genetics, University of Oxford) said: ‘Human brain development is a delicate and elaborate process with a complex choreography. It would be naïve to think that we can recreate the entire cellular progression in the laboratory. Nonetheless, our 3D printing project demonstrates substantial progress in controlling the fates and arrangements of human iPSCs to form the basic functional units of the cerebral cortex.'

Senior author Professor Hagan Bayley (Department of Chemistry, University of Oxford) said: ‘This futuristic endeavour could only have been achieved by the highly multidisciplinary interactions encouraged by Oxford's Martin School, involving both Oxford's Department of Chemistry and the Department of Physiology, Anatomy and Genetics.’

3D-printed two-layer cerebral cortical tissue visualised within a mouse brain slice. The implanted neural cells were labelled with fluorescent markers (blue and red in the image). Image credit: Yongcheng Jin, University of Oxford. 

CREDIT

Notes for editors:

The study ‘Integration of 3D-Printed Cerebral Cortical Tissue into an ex vivo Lesioned Brain Slice’ will be published in Nature Communications at 10:00 AM BST/ 05:00 AM ET Wednesday 04 October, 2023 at https://www.nature.com/articles/s41467-023-41356-w. To view a copy of the manuscript under embargo, contact Dr Caroline Wood: caroline.wood@admin.ox.ac.uk

The research was supported by a European Research Council Advanced Grant (SYNTISU) and the Oxford Martin School Programme on 3D Printing for Brain Repair. 

About the University of Oxford

Oxford University has been placed number 1 in the Times Higher Education World University Rankings for the eighth year running, and number 3 in the QS World Rankings 2024. At the heart of this success are the twin-pillars of our ground-breaking research and innovation and our distinctive educational offer.

Oxford is world-famous for research and teaching excellence and home to some of the most talented people from across the globe. Our work helps the lives of millions, solving real-world problems through a huge network of partnerships and collaborations. The breadth and interdisciplinary nature of our research alongside our personalised approach to teaching sparks imaginative and inventive insights and solutions.

Through its research commercialisation arm, Oxford University Innovation, Oxford is the highest university patent filer in the UK and is ranked first in the UK for university spinouts, having created more than 300 new companies since 1988. Over a third of these companies have been created in the past five years. The university is a catalyst for prosperity in Oxfordshire and the United Kingdom, contributing £15.7 billion to the UK economy in 2018/19, and supports more than 28,000 full time jobs.

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JOURNAL

Nature Communications

DOI

10.1038/s41467-023-41356-w 

ARTICLE TITLE

Integration of 3D-Printed Cerebral Cortical Tissue into an ex vivo Lesioned Brain Slice

 

Instant evolution: AI designs new robot from scratch in seconds

First AI capable of intelligently designing new robots that work in the real world

Peer-Reviewed Publication

NORTHWESTERN UNIVERSITY

 

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THE AI-DESIGNED ROBOT HAS THREE LEGS, REAR FINS, A FLAT FACE AND IS RIDDLED WITH HOLES — SOMETHING A HUMAN ENGINEER WOULD NEVER CONCEIVE.

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CREDIT: NORTHWESTERN UNIVERSI

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• Inventor of xenobots unveils new advance toward artificial life
• New AI algorithm compresses billions of years of evolution into seconds
• The evolved robot has three legs and rear fins, something a human engineer would never devise
• Researcher: ‘Now anyone can watch evolution in action as AI generates better and better robot bodies in real time.’

A team led by Northwestern University researchers has developed the first artificial intelligence (AI) to date that can intelligently design robots from scratch.

To test the new AI, the researchers gave the system a simple prompt: Design a robot that can walk across a flat surface. While it took nature billions of years to evolve the first walking species, the new algorithm compressed evolution to lightning speed — designing a successfully walking robot in mere seconds.

But the AI program is not just fast. It also runs on a lightweight personal computer and designs wholly novel structures from scratch. This stands in sharp contrast to other AI systems, which often require energy-hungry supercomputers and colossally large datasets. And even after crunching all that data, those systems are tethered to the constraints of human creativity — only mimicking humans’ past works without an ability to generate new ideas.

The study will be published on Oct. 3 in the Proceedings of the National Academy of Sciences.

“We discovered a very fast AI-driven design algorithm that bypasses the traffic jams of evolution, without falling back on the bias of human designers,” said Northwestern’s Sam Kriegman, who led the work. “We told the AI that we wanted a robot that could walk across land. Then we simply pressed a button and presto! It generated a blueprint for a robot in the blink of an eye that looks nothing like any animal that has ever walked the earth. I call this process ‘instant evolution.’”

Kriegman is an assistant professor of computer science, mechanical engineering and chemical and biological engineering at Northwestern’s McCormick School of Engineering, where he is a member of the Center for Robotics and Biosystems. David Matthews, a scientist in Kriegman’s laboratory, is the paper’s first author. Kriegman and Matthews worked closely with co-authors Andrew Spielberg and Daniela Rus (Massachusetts Institute of Technology) and Josh Bongard (University of Vermont) for several years before their breakthrough discovery. 

From xenobots to new organisms

In early 2020, Kriegman garnered widespread media attention for developing xenobots, the first living robots made entirely from biological cells. Now, Kriegman and his team view their new AI as the next advance in their quest to explore the potential of artificial life. The robot itself is unassuming — small, squishy and misshapen. And, for now, it is made of inorganic materials. But Kriegman says it represents the first step in a new era of AI-designed tools that, like animals, can act directly on the world.

“When people look at this robot, they might see a useless gadget,” Kriegman said. “I see the birth of a brand-new organism.”

Zero to walking within seconds

While the AI program can start with any prompt, Kriegman and his team began with a simple request to design a physical machine capable of walking on land. That’s where the researchers’ input ended and the AI took over.

The computer started with a block about the size of a bar of soap. It could jiggle but definitely not walk. Knowing that it had not yet achieved its goal, AI quickly iterated on the design. With each iteration, the AI assessed its design, identified flaws and whittled away at the simulated block to update its structure. Eventually, the simulated robot could bounce in place, then hop forward and then shuffle. Finally, after just nine tries, it generated a robot that could walk half its body length per second — about half the speed of an average human stride.

The entire design process — from a shapeless block with zero movement to a full-on walking robot — took just 26 seconds on a laptop.

“Now anyone can watch evolution in action as AI generates better and better robot bodies in real time,” Kriegman said. “Evolving robots previously required weeks of trial and error on a supercomputer, and of course before any animals could run, swim or fly around our world, there were billions upon billions of years of trial and error. This is because evolution has no foresight. It cannot see into the future to know if a specific mutation will be beneficial or catastrophic. We found a way to remove this blindfold, thereby compressing billions of years of evolution into an instant.”

Rediscovering legs

All on its own, AI surprisingly came up with the same solution for walking as nature: Legs. But unlike nature’s decidedly symmetrical designs, AI took a different approach. The resulting robot has three legs, fins along its back, a flat face and is riddled with holes.

“It’s interesting because we didn’t tell the AI that a robot should have legs,” Kriegman said. “It rediscovered that legs are a good way to move around on land. Legged locomotion is, in fact, the most efficient form of terrestrial movement.”

To see if the simulated robot could work in real life, Kriegman and his team used the AI-designed robot as a blueprint. First, they 3D printed a mold of the negative space around the robot’s body. Then, they filled the mold with liquid silicone rubber and let it cure for a couple hours. When the team popped the solidified silicone out of the mold, it was squishy and flexible.

Now, it was time to see if the robot’s simulated behavior — walking — was retained in the physical world. The researchers filled the rubber robot body with air, making its three legs expand. When the air deflated from the robot’s body, the legs contracted. By continually pumping air into the robot, it repeatedly expanded then contracted — causing slow but steady locomotion.

Unfamiliar design

While the evolution of legs makes sense, the holes are a curious addition. AI punched holes throughout the robot’s body in seemingly random places. Kriegman hypothesizes that porosity removes weight and adds flexibility, enabling the robot to bend its legs for walking.

“We don’t really know what these holes do, but we know that they are important,” he said. “Because when we take them away, the robot either can’t walk anymore or can’t walk as well.”

Overall, Kriegman is surprised and fascinated by the robot’s design, noting that most human-designed robots either look like humans, dogs or hockey pucks.

“When humans design robots, we tend to design them to look like familiar objects,” Kriegman said. “But AI can create new possibilities and new paths forward that humans have never even considered. It could help us think and dream differently. And this might help us solve some of the most difficult problems we face.”

Potential future applications

Although the AI’s first robot can do little more than shuffle forward, Kriegman imagines a world of possibilities for tools designed by the same program. Someday, similar robots might be able to navigate the rubble of a collapsed building, following thermal and vibrational signatures to search for trapped people and animals, or they might traverse sewer systems to diagnose problems, unclog pipes and repair damage. The AI also might be able to design nano-robots that enter the human body and steer through the blood stream to unclog arteries, diagnose illnesses or kill cancer cells.

“The only thing standing in our way of these new tools and therapies is that we have no idea how to design them,” Kriegman said. “Lucky for us, AI has ideas of its own.”

The study, “Efficient automatic design of robots,” was supported by Schmidt Futures (grant number G-22-64506, the Intelligence Advanced Research Projects Activity (grant number 2019-19020100001, the Defense Advanced Research Projects Agency (grant number HR001-18-2-0022) and the National Science Foundation (grant number 2020247).

Several AI-designed robots in the laboratory.

Lead researcher Sam Kriegman holds an AI-designed robot in his hand.

An open robot shows its interior "air muscles" (on the left). Pumping air into the muscles enables it to walk.

Lead researcher Sam Kriegman shows one of the AI-designed robots.

Watch the AI-designed robot wa [VIDEO] |

JOURNAL

Proceedings of the National Academy of Sciences

METHOD OF RESEARCH

Experimental study

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Efficient automatic design of robots

ARTICLE PUBLICATION DATE

3-Oct-2023

 

Can public financing for political campaigns affect voter participation?

Peer-Reviewed Publication

WILEY

Policies that provide public financing for political campaigns have gained popularity in the United States. One example is the Democracy Vouchers program that was implemented in Seattle, Washington in 2017 to potentially reduce candidates' reliance on large donations. Research published in Contemporary Economic Policy studied the effects of this program on voter registration and turnout.

In Seattle’s Democracy Vouchers program, every registered voter in the city receives $100 worth of publicly funded vouchers to donate to candidates for municipal office, and candidates who accept vouchers agree to limits on non‐voucher contributions.

By analyzing data on voter registration, voter turnout, and campaign donations from 2009 to 2021 in King County, where Seattle is located, Sarah Papich, a PhD candidate in economics at the University of California Santa Barbara, estimated that the Democracy Vouchers program increased voter turnout by 4.9 percentage points. This finding suggests that public financing programs can increase political participation.

The analysis also revealed a shift in the composition of political contributions, with campaigns becoming more reliant on small contributions after the Democracy Vouchers program was implemented. For city council candidates, dollars from small contributions under $100 increased by 156% whereas dollars from large contributions over $250 decreased by 93%.

“Low voter turnout and the disproportionate influence of big donors are two significant problems in our democracy,” said Papich. “These findings provide encouraging evidence that public financing for political campaigns can help address both problems.”

URL upon publication: https://onlinelibrary.wiley.com/doi/10.1111/coep.12625

 

Additional Information
NOTE: The information contained in this release is protected by copyright. Please include journal attribution in all coverage. For more information or to obtain a PDF of any study, please contact: Sara Henning-Stout, newsroom@wiley.com.

About the Journal
First published in 1982, Contemporary Economic Policy publishes scholarly research and analysis on important policy issues facing society. The journal provides insight into the complexity of policy decisions and communicates evidence-based solutions in a form accessible to economists and policy makers. Contemporary Economic Policy provides a forum for debate by enhancing our understanding of key issues and methods used for policy analysis.

About Wiley
Wiley is a knowledge company and a global leader in research, publishing, and knowledge solutions. Dedicated to the creation and application of knowledge, Wiley serves the world’s researchers, learners, innovators, and leaders, helping them achieve their goals and solve the world's most important challenges. For more than two centuries, Wiley has been delivering on its timeless mission to unlock human potential. Visit us at Wiley.com. Follow us on Facebook, Twitter, LinkedIn and Instagram.

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JOURNAL

Contemporary Economic Policy

DOI

10.1111/coep.12625 

ARTICLE TITLE

Do Democracy Vouchers Help Democracy?

ARTICLE PUBLICATION DATE

4-Oct-2023

 

Intervention for caregivers helps prevent elder mistreatment

Peer-Reviewed Publication

WILEY

An educational and social support intervention for caregivers reduced elder mistreatment of older adults with chronic illness, including dementia. That’s the result of a recent double-blind, randomized controlled trial published in the Journal of the American Geriatrics Society.

Elder mistreatment is defined as “an intentional act or failure to act by a caregiver or another person in a relationship involving an expectation of trust that causes or creates a risk of harm to an older adult.” Through the Comprehensive Older Adult and Caregiver Help (COACH) intervention tested in this trial, coaches met with caregivers weekly for up to 12 sessions to listen to their concerns and guide them through a personally tailored behavioral and educational intervention. Participants were provided with caregiving tools and coping strategies and were also educated about mistreatment so they could be vigilant against abusive behaviors by themselves and others. Eighty caregivers were randomized to the COACH intervention or a control group.

Treatment group caregivers reported less mistreatment against their care recipient, which dropped from 22.5% at baseline to 0% following the completion of the 3-month intervention. In the control group, reported rates did not change significantly.

“COACH was created to benefit older adults who rely on a caregiver and are particularly vulnerable to harm. It now stands out as the first intervention that has been shown to prevent elder mistreatment,” said corresponding author Zach Gassoumis, PhD, of the University of Southern California. “Our study provides initial evidence that COACH may be immensely successful, and a potential lifeline for the millions of older adults who experience abusive behavior each year.”

URL upon publication: https://onlinelibrary.wiley.com/doi/10.1111/jgs.18597

 

Additional Information
NOTE: The information contained in this release is protected by copyright. Please include journal attribution in all coverage. For more information or to obtain a PDF of any study, please contact: Sara Henning-Stout, newsroom@wiley.com.

About the Journal
Journal of the American Geriatrics Society is the go-to journal for clinical aging research. We provide a diverse, interprofessional community of healthcare professionals with the latest insights on geriatrics education, clinical practice, and public policy—all supporting the high-quality, person-centered care essential to our well-being as we age.

About Wiley
Wiley is a knowledge company and a global leader in research, publishing, and knowledge solutions. Dedicated to the creation and application of knowledge, Wiley serves the world’s researchers, learners, innovators, and leaders, helping them achieve their goals and solve the world's most important challenges. For more than two centuries, Wiley has been delivering on its timeless mission to unlock human potential. Visit us at Wiley.com. Follow us on Facebook, Twitter, LinkedIn and Instagram.

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JOURNAL

Journal of the American Geriatrics Society

DOI

10.1111/jgs.18597 

ARTICLE TITLE

Comprehensive Older Adult and Caregiver Help (COACH): A person-centered caregiver intervention prevents elder mistreatment

ARTICLE PUBLICATION DATE

4-Oct-2023

 

Is universal screening for type 1 diabetes around the corner?

Reports and Proceedings

DIABETOLOGIA

The the latest data on  universal screening for type 1 diabetes (T1D) is reveiwed in a session at this year’s Annual Meeting of the European Association for the Study of Diabetes (EASD) in Hamburg, Germany (2-6 October). The talk will be given by Dr Emily K. Sims, Associate Professor of Pediatrics, Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA.

Research by various groups has established that individuals with multiple islet autoantibodies (biomarkers showing that the body is attacking and killing its own insulin producing beta cells in the pancreas) have a near 100% risk of developing T1D over their lifetime (Ziegler et al. JAMA. 2013 Jun 19;309(23):2473-9). Multiple groups including Ezio Bonifacio and colleagues from the TEDDY Consortium (Diabetes Care 2021) and Ghalwash and colleagues from Type 1 Diabetes Intelligence Study Group (The Lancet Diabetes & Endocrinology 2022) have shown that screening for islet auto-antibodies  at two ages – 2 and at 5-7 years - would predict most cases of type 1 diabetes that would develop by age 15 years.

Dr Sims will highlight that, although screening programs have previously most often focused on people with family members with T1D (who can have up to 15 times increased risk of developing T1D), most people who develop T1D (85-90%) have no family history of the condition. “Our knowledge of type 1 diabetes has now evolved from thinking it is a disease that suddenly develops, to knowing that it is something that gradually develops, after the appearance of multiple islet-autoantibodies. By screening children and adults to identify individuals with early, presymptomatic stages of disease, we can more accurately predict when they will first need insulin and prevent life-threatening DKA episodes that otherwise frequently occur at diagnosis,” she explains. “Natural history studies have shown us that once someone has reached the threshold of multiple islet autoantibodies, progression occurs similarly in relatives and those with no family history.”

Knowing who is likely to develop T1D will help prevent cases of diabetic ketoacidosis (DKA) that occurs when the body doesn't have enough insulin to allow blood sugar into the cells for use as energy. Instead, the liver breaks down fat for fuel, producing acids called ketones; the build-up of these ketones to dangerous levels causes DKA. These episodes can be dangerous and even fatal, causing a number of uncomfortable symptoms. The symptoms of DKA can be the first sign of T1D in people who haven’t yet been diagnosed.

Various research programs are going on worldwide to establish the best ways of implementing universal screening, including programmes in Germany, the USA, Israel, the UK, and Australia, and a new program (Edent1fi) has just been funded that is going to include multiple new countries in Europe, including the UK, Germany, Poland, Portugal, Italy and the Czech Republic.  “These are all research programs. The next steps before universal screening for type 1 diabetes becomes general policy will require guidelines for monitoring and endorsement of screening and monitoring guidelines by applicable societies,” explains Dr Sims. This will also be helped by broader access to disease modifying therapies to impact progression and the need to start insulin injections.

She explains that these research programmes are in many cases working with primary care doctors to obtain blood testing for autoantibodies - while some of them work through newborn screening (genetic testing performed on infant blood spots followed by antibody screening in individuals at higher genetic risk).
 

Dr Sims says: “The costs of screening, optimal ways to scale it up, and how to connect it with access to disease modifying therapies, such as the monoclonal anti-CD3 antibody that was recently FDA-approved in the US for delay of Stage 3 T1D in individuals meeting criteria for Stage 2 disease (multiple islet autoantibodies and changes in blood sugar), are all still to be worked out. Other important considerations moving forward include reaching traditionally understudied populations and more tailored approaches for individual patients.”

As the question of when we could see universal screening for T1D rolled, Dr Sims concludes: “ I think we will start to see increasing society endorsement of screening and monitoring guidelines over the next five years and that as this occurs, countries will start incorporating screening into routine care for young children at the general practitioner’s office – for example, when children are called for routine childhood vaccinations.” Screening for adults, who can also develop T1D, is less well studied. Although optimal approaches have yet to be clearly elucidated, this population will also likely benefit from identification of early stage disease and the advantages of education, monitoring, and access to therapy.

“Given that we know that individuals without a family history are the most likely to present with new T1D and that once they reach criteria for early stage disease, they are at similar risk to individuals with a family history, universal screening the of general population is key to ultimately allow the most individuals to benefit from access to education, monitoring, and disease modifying therapies.

Dr Sims will also take part in the embargoed press conference taking place at 1200H Noon CEST Hamburg time on Tues 3 Oct, in the Vienna Hall.

To join by zoom, use this link

https://us06web.zoom.us/j/86523053998?pwd=0CxM4PetJCn8K6CbnavJVbp3uIZ3aa.1

For press conference slide presentation, click here

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ARTICLE PUBLICATION DATE

3-Oct-2023

COI STATEMENT

Dr Emily Sims, Associate Professor of Pediatrics, Center for Diabetes and Metabolic Disease, Indiana University School of Medicine, Indianapolis, IN, USA. Please e-mail to arrange interview. E) eksims@iu.edu Alternative contact in the EASD Press Room: Tony Kirby T) + 44 7834 385827 E) tony@tonykirby.com This press release is based on session S27 to take place in the Barcelona Hall at the European Association for the Study of Diabetes (EASD) Annual Meeting in Hamburg at 0900H AM CEST on Wednesday 4 October. The presenter is happy to answer any questions. Dr Sims will also take part in the embargoed press conference taking place at 1200H Noon CEST Hamburg time on Tues 3 Oct, in the Vienna Hall. To join by zoom, use this link https://us06web.zoom.us/j/86523053998?pwd=0CxM4PetJCn8K6CbnavJVbp3uIZ3aa.1

 For press conference slide presentation, click here

Metabolic signature can help predict which smokers will develop type 2 diabetes

UK Biobank analysis of over 93,000 adults finds that smoking increases the risk of type 2 diabetes in part through its effects on the metabolism

Reports and Proceedings

DIABETOLOGIA

New research being presented at this year’s Annual Meeting of The European Association for the Study of Diabetes (EASD), Hamburg (2-6 Oct) finds that cigarette smoking increases the risk of developing type 2 diabetes in part by affecting a variety of metabolites—small chemicals produced in the processes of metabolism—that circulate in the bloodstream.

The influence of these metabolic changes on diabetes risk appears to be amplified in individuals with genetic susceptibility to type 2 diabetes or insulin resistance.

The analysis of over 93,000 UK Biobank participants also identified a metabolic signature of 131 metabolic traits that can help predict which smokers are more likely to develop type 2 diabetes.

“Our metabolism is constantly changing depending on what we ingest or are exposed to”, says lead author Yuxia Wei from the Karolinska Institutet in Sweden. “Our study is the first to develop a metabolic signature for smoking based on comprehensive metabolomic profiles, and provides new insights into how smoking influences certain metabolites to increase the risk of type 2 diabetes. The findings underscore the importance of refraining from or quitting smoking to prevent diabetes, particularly for individuals with genetic risk factors for diabetes who seem to be more vulnerable to these changes.”

Previous observational evidence suggests that smokers are 20-60% more likely to develop type 2 diabetes, but the underlying mechanisms are unclear.

To address this knowledge gap, researchers used nuclear magnetic resonance spectroscopy (NMR) to analyse hundreds of metabolites in blood samples from 93,722 never, former, and current smokers (aged 37-73 years) without diabetes at the start of the study (2006-10) from the UK biobank—which holds genetic, health, and medical information from approximately half a million British volunteers. Metabolomics data were collected again in 2012-13.

During an average (median) follow-up of 13 years, 1,869 new cases of diabetes were identified.

The observational analysis and causal relationship analysis identified 131 metabolites affected by smoking, including glycoprotein acetyls (an inflammatory biomarker), fatty acids, and lipids, which collectively indicated whether an individual would go on to develop type 2 diabetes.

Compared with people who never smoked, current smoking increased the risk of type 2 diabetes by 73%; and 38% of this excess risk was mediated through the smoking-related metabolic signature (44% in men and 30% in women), after accounting for traditional diabetes risk factors such as age, sex, education level, ethnicity, BMI, physical activity, diet, and family history of diabetes.

For free fatty acids, smoking seemed to lead to higher levels of unhealthy saturated and monosaturated fatty acids, and lower percentages of healthy polyunsaturated ones such as DHA, omega-6 fatty acids, and omega-3 fatty acids (mainly found in seafood). Smoking was also positively associated with metabolites including different lipids in very-low-density lipoproteins (VLDL), triglycerides, and LDL cholesterol (also called ‘bad’ cholesterol), and lower levels of all forms of HDL cholesterol (often know as good cholesterol).

Importantly, the findings indicate that most of the smoking-related metabolic changes are reversible after quitting smoking.

The analysis also found that a high level of the metabolic signature was associated with a 61% higher risk of developing type 2 diabetes compared to a low level.

Genetic susceptibility also made a difference. Individuals with both a high level of the metabolic signature and a high genetic susceptibility to type 2 diabetes were three times as likely to develop the condition as those with low levels of the signature and genetic susceptibility.

The interaction between genetic susceptibility and the metabolic signature enhances their overall impact on type 2 diabetes. As the Wei explains: “The excess risk of developing type 2 diabetes in people with both a high genetic susceptibility and a high level of the signature surpasses what we would expect by simply adding the excess risk in people with only a high genetic susceptibility and the excess risk in people with only a high level of the signature. Our findings suggest that it is even more important for people with high genetic susceptibility to avoid smoking than the general population.”

The researchers further tested and verified the metabolic signature in blood samples from 3,626 participants in the TwinGene Study, a cohort nested in the Swedish Twin Register. They noted that the ability for the metabolic signature to determine risk of type 2 diabetes was highly reproducible despite the fact that individuals living in the UK and Sweden have different dietary habits, lifestyles, and environmental exposures.

“The reproducibility of the findings in the Swedish population indicate the robustness of the approach”, says Wei. “Nevertheless, more than half of the smoking-diabetes link was not explained by the metabolic signature, suggesting that other pathophysiological consequences of smoking play a role in diabetes development. These mechanisms may include the adverse effects of smoking on pancreatic tissue and beta cell function.”

Despite the important findings, the researchers note several limitations of the study, including that smoking status and metabolite levels may have changed during follow-up, which may have influenced the results; and that the study was conducted in people mainly of European origin, so the findings may not be generalisable to other populations.

This work was supported by the Swedish Research Council, FORTE, the Novo Nordisk Foundation, and the China Scholarship Council.

This press release is based on poster presentation 322 at the annual meeting of the European Association for the Study of Diabetes (EASD). The material has been peer reviewed by the congress selection committee. There is no full paper at this stage, but the research has been submitted to a medical journal for publication. The authors are happy to answer any questions.

 

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ARTICLE PUBLICATION DATE

3-Oct-2023

COI STATEMENT

This work was supported by the Swedish Research Council, FORTE, the Novo Nordisk Foundation, and the China Scholarship Council.

 

PARMESAN: An AI-based predictive tool to find new treatments for genetic disorders

Peer-Reviewed Publication

TEXAS CHILDREN'S HOSPITAL

To discover new treatments for genetic disorders, scientists need a thorough knowledge of prior literature to determine the best gene/protein targets and the most promising drugs to test. However, biomedical literature is growing at an explosive rate and often contains conflicting information, making it increasingly time-consuming for researchers to conduct a complete and thorough review.  

To address this challenge, Cole Deisseroth, a graduate student enrolled in the M.D./Ph.D. program and mentored by Drs. Huda Zoghbi and Zhandong Liu at the Jan and Duncan Neurological Research Institute (Duncan NRI) at Texas Children’s Hospital and Baylor College of Medicine, led a study to generate a natural language processing (NLP) tool called PARsing ModifiErS via Article aNnotations (PARMESAN). This new tool can search for up-to-date information, assemble it into a central knowledge base, and even predict likely drugs that could correct specific protein imbalances. A description of the tool and its capabilities was published recently in the American Journal of Human Genetics.

“PARMESAN offers a wonderful opportunity for scientists to speed up the pace of their research and thus, accelerate drug discovery and development,” Howard Hughes Medical Institute investigator, Dr. Huda Zoghbi, who is also the founding director of Duncan NRI and distinguished service professor at Baylor College, added.

This artificial intelligence (AI)-powered tool scans through public biomedical literature databases (PubMed and PubMed Central), to identify and rank descriptions of gene-gene and drug-gene regulatory relationships. However, what stands out about PARMESAN in particular is its ability to leverage curated information to predict undiscovered relationships.

“The unique feature of PARMESAN is that it not only identifies existing gene-gene or drug-gene interactions based on the available literature but also predicts putative novel drug-gene relationships by assigning an evidence-based score to each prediction,” Dr. Zhandong Liu, Chief of Computation Sciences at Texas Children’s Hospital and associate professor at Baylor College of Medicine, noted.

PARMESAN’s AI algorithms analyze studies that describe the contributions of various players involved in a multistep genetic pathway. Then it assigns a weighted numerical score to each reported interaction. Interactions that are consistently and frequently reported in the literature receive higher scores, whereas interactions that are either weakly supported or appear to be contradicted between different studies are assigned lower scores.

PARMESAN currently provides predictions for more than 18,000 target genes, and benchmarking studies have suggested that the highest-scoring predictions are over 95% accurate.

"By pinpointing the most promising gene and drug interactions, this tool will allow researchers to identify the most promising drugs at a faster rate and with greater accuracy," Cole Deisseroth, said.

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Others involved in the study were Won-Seok Lee, Jiyoen Kim, Hyun-Hwan Jeong, Ryan S. Dhindsa, and Julia Wang. They were affiliated with one or more of the following institutions: Baylor College of Medicine, the Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital, the University of Pennsylvania, and Howard Hughes Medical Institute. The study was supported by the National Institutes of Health (NIH), the Medical Scientist Training Program of Baylor College of Medicine, the Robert and Janice McNair Foundation M.D./Ph.D. Student Scholar Program, Howard Hughes Medical Institute International Student Research Fellowship, the BrightFocus Foundation, the JPB Foundation, the CHDI Foundation, the Huffington Foundation, and the Ting Tsung and Wei Fong Chao Foundation.

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JOURNAL

American Journal of Human Genetics