Coronavirus treatment implicates the immune system as killer

The first paper in our series on "Coronavirus science simplified". The talented TenMei is taking cutting-edge papers on Coronavirus and boiling them down to an illustrated abstract. Today's paper is"Effective Treatment of Severe COVID-19 Patients with Tocilizumab". You can read the original here, or see the key messages simplified:

Immune cell treatment offers hope in tackling neurodegeneration

From the Cambridge Independent

 

EU grant success to harness the immune system to treat brain damage

Covered by the BusinessWeekly

Research identifies potential treatment for brain injury and inflammation

Funding awarded to Prof Adrian Liston will be used to advance the approach developed in mice to make it ready for clinical trials. Pioneering research by Prof Liston, a senior group leader at the Babraham Institute, will be developed towards being market-ready for the treatment of brain injury by funding provided by an ERC Proof of Concept grant, as announced today.

Key points:

• Immunology group leader, Prof Adrian Liston, is one of 76 top researchers to receive an ERC Proof of Concept grant, used to translate EU-sponsored research into the clinic.
• Research by Prof Liston's team and collaborators developed a method to use the immune system to prevent brain damage caused by disease and injury.
• EU funding through the European Research Council (ERC) recognises frontier research and provides support to explore the innovation potential of discoveries.
• This funding will also lead the way towards commercialisation and therapeutic application of the technology.

Research undertaken by Prof Liston and his group has shown that driving the expansion of a specific population of immune cells in the brain is effective at treating brain injury in mouse pre-clinical models. The research shows that this approach is effective at treating brain damage caused by disease, such as occurs in mouse models of multiple sclerosis, or injury, such as occurs following a head trauma or stroke.

Professor Liston, senior group leader in the Institute’s Immunology programme, said: “This is an exciting new approach to preventing neurodegenerative diseases. We have been able to come up with a completely new approach to preventing, and potentially reversing, brain damage. At the moment the treatment is proven to work in mice, with the aim to have it ready for transition to human at the end of the year. The immune system is highly conserved between mouse and human, allowing a high degree of success in translation to the clinical. This is illustrated by the immune-based therapeutics developed in mice now successfully being used in the clinic to fight immunological diseases and cancer. This new method may open up a new immune-based strategy to fight neurodegenerative disease”.

The approach harnesses the power of a type of immune cell called regulatory T cells – cells that control the immune response, suppressing the immune system from over-reacting. Increasing the number of these cells in the brain prevents and reverses the inflammatory damage that occurs to the brain during diseases such as mouse models of multiple sclerosis, traumatic brain injury or stroke. The proof-of-concept research demonstrated that just one treatment was sufficient to prevent brain degeneration and stimulate brain repair.

Image: Pre-clinical testing of neuroimmune treatment in mice receiving a brain injury. The mouse on the left was untreated, and developed neurodegeneration. The mouse on the right was treated, with protection from neurodegeneration. Background image uses immunohistology to visualise signs of active brain repair in treated mice. Image credit: Lidia Yshii (VIB, Belgium), Pascal Bielefeld (University of Amsterdam, Netherlands), Sebastian Munck (VIB, Belgium) and Axelle Kerstens (VIB, Belgium).

“It took a multi-disciplinary and international team, spanning both immunology and neuroscience, to come up with a new approach", Prof Liston said. The grant is based on EU-funded research that was performed at the VIB in Belgium and the Babraham Institute in Cambridge. "We have had a talented team pull out all the stops on this, with particular thanks to Dr Lidia Yshii, Dr Emanuela Pasciuto and Dr James Dooley. Key to the success has been collaboration - working with top neuroscientists across Europe, with Prof Matthew Holt from Belgium and Prof Carlos Fitzsimons from the Netherlands providing key insights and skills".

The research grant from the European Union will support the development of this approach over an 18 month period. The funding will allow for the validation of the treatment in pre-clinical trials and the recruitment of a commercial partner for entry into clinical trials in patients.

Professor Michael Wakelam, Institute Director, said: “It’s fantastic that the ERC have recognised the potential of this promising research. Neurodegenerative diseases increase in likelihood and severity with age, so this research very closely aligns with our mission to improve lifelong health. We’re hugely excited to take the next steps towards developing this approach and exploring the wider instances where this type of treatment may offer benefits.”

ERC Proof of Concept grants award €150,000 to researchers to explore the innovation potential of their scientific discoveries and bring the results of their frontier research closer to market.

Congratulations Dr Erika Van Nieuwenhove!

A huge round of congratulations for Dr Erika Van Nieuwenhove, who successfully defended her PhD. Erika set for gold standard for PhD defences, with an outstanding presentation and masterful question time. Erika's thesis was on inborn errors of immunity, with her PhD covering multiple new genetic mechanisms for PIDs, including mutations in ADA2 and Ikaros, plus a machine learning-driven approach to the diagnosis of JIA. The work is not yet finished either - stayed tuned for more Van Nieuwenhove papers on new genetic causes of neutropenia! A future leader in pediatric immunology and rheumatology!

PhD opportunity in the Liston lab!

Are you interested in a PhD in neuroimmunology? Want to find out how to harness the power of the immune system to cure traumatic brain injury? Check out our PhD position here. It is a rare chance to join a fantastic international team, and to learn to do high level science in a supportive and caring environment.

A successful candidate will be:

• passionate about science and the project
• experienced at failure, with a track-record in the resilience needed to pick yourself up and try again
• willing to be wrong, willing to learn, willing to improve
• driven to make a difference, discover new biology or move a promising therapeutic to the next stage
• creative and imaginative
• detail-orientated and reliable

The successful candidate does not need:

• experience at immunology or neuroscience. You are here to learn, not start as an expert!
• technical experience in X, Y or Z - as above
• a perfect CV. I'm interested in seeing that you know how to succeed in the face of adversity

 If you are submitting an application, consider a co-application to a Cambridge College, such as Peterhouse.

Golden Pipette won by Dr Wenson Karunakaran

Congratulations to Dr Wenson Karunakaran! 

It was tough competition for the sixth Golden Pipette at the Cambridge-Leuven joint lab retreat. The final prize had to go to Dr Karunakaran for his work on brain CD4 T cells.

Many neuroscientists assume there are no CD4 T cells inside the healthy brain, but there are in fact around 5000 per gram of brain tissue. How do we know? Wenson imaged and counted them, one by one. 

That is what it takes to win the Golden Pipette.

Immune profiling ‘will be a revolution in medicine’

A revolution in medicine is coming.

It could aid the diagnosis of diseases, guide the way patients are treated and inform the discovery of new therapies.

Immune profiling seeks to explain how our body’s own defences are affected by and are responding to disease.

At the Babraham Institute, Professor Adrian Liston is working on the translation of this technique from the laboratory to the clinic.

“The immune profile is much more powerful than genomic data, but it’s much easier to get genomic data,” he tells the Cambridge Independent. “You can take blood, send it overnight and get it sequenced off-site. We are not at that stage with immune system data.

“But the more we know about different diseases, the more we realise there are inflammatory, or immune-mediated, components.

“It can be a revolution in medicine. Once the infrastructure is set up and hospitals are doing the analysis routinely, we will see an explosion in utility. Right now, it’s a research tool only.”

Read the full article at the Cambridge Independent

Dokter Algoritme

Algoritmen kunnen inzichten bereiken waar een mens moeilijk toe komt. Computeralgoritmen kunnen almaar beter moeilijke diagnosen stellen, soms zelfs beter dan artsen. Immunologe Erika Van Nieuwenhove van de Leuvense tak aan het Vlaams Instituut voor Biotechnologie (VIB) en haar collega’s melden in Annals of the Rheumatic Diseases dat ze een zelflerend algoritme hebben ontwikkeld dat met bijna 90 procent zekerheid artritis bij kinderen kan vaststellen, louter op basis van een bloedtest.

Het gaat om de vaakst voorkomende vorm van reuma bij kinderen, maar omdat de ernst en de evolutie van de symptomen sterk kunnen variëren, is een diagnose stellen niet altijd gemakkelijk. Het algoritme evalueert alleen de samenstelling van het immuunsysteem van de patiënten. Het zal nuttig zijn om te bepalen welke behandeling aangewezen is.

Knack - 24 Apr. 2019 - Page 86

Using machine learning to diagnose disease

Profiling the immune system in paediatric arthritis patients offers hope for improved diagnosis and treatment

A team of scientists from VIB and KU Leuven has developed a machine learning algorithm that identifies children with juvenile arthritis with almost 90% accuracy from a simple blood test. The new findings, published this week in Annals of the Rheumatic Diseases, pave the way for the use of machine learning to improve diagnosis and to predict which juvenile arthritis patients may respond best to different treatment options. The work was led by Professor Adrian Liston, a group leader at the Babraham Institute in Cambridge, UK and at VIB and KU Leuven in Leuven, Belgium.

Juvenile idiopathic arthritis is the most common rheumatic disease in children, but it presents in many different severities and forms. This diversity makes clinical assessment and patient classification difficult.

A team of researchers at Belgian research organisations VIB, KU Leuven and UZ Leuven undertook a detailed biological characterisation of the immune system of hundreds of children with and without juvenile arthritis to help the diagnosis or treatment decisions for this disease.

“Essentially, we took blood samples from more than 100 children, two thirds of whom had childhood arthritis,” explains Erika Van Nieuwenhove (VIB-KU Leuven), and first author of the study. “We analysed their immune system at a greater level of detail than was ever done before for this disease, and simply using this data we then used machine learning to see if we could tell which children had arthritis.”

The results were quite remarkable: the algorithm was about 90% accurate at identifying the children with the disease. “Using only information on the immune system, and no clinical data at all, we could design a machine learning algorithm that was about 90% accurate at spotting which kids had arthritis,” says Professor Adrian Liston (Babraham Institute, Cambridge, UK and VIB-KU Leuven). “This result is a proof-of-principle demonstration that immune phenotyping combined with machine learning holds huge potential to diagnose disease. Similar approaches could be applied to improve patient selection for treatments and clinical trials.”

The researchers are hopeful about the impact of this research in improving patient outcomes. “The tool needs further validation but otherwise there are no scientific barriers to this approach being quickly translated to the clinic,” comments Professor Carine Wouters (UZ Leuven), who was the clinical lead for this study. “Down the line, we could use this kind of detailed classification information—and machine learning analysis—to identify which patients will respond best to specific treatment options.”

EMBO Young Investigator meeting

Great meeting with great people

Punting on the Cam

Visiting the original lab books of Rosalind Franklin