Tag Archive for: Neurodegenerative Disease and Dementia

Ultra-powered MRI scans show damage to brain’s ‘control centre’ is behind long-lasting Covid-19 symptoms

Patient having an MRI scan - NIHR Cambridge BRC image

Damage to the brainstem – the brain’s ‘control centre’ – is behind long-lasting physical and psychiatric effects of severe Covid-19 infection, a study suggests.

Using ultra-high-resolution scanners that can see the living brain in fine detail, researchers from the Universities of Cambridge and Oxford and supported by NIHR Cambridge and Oxford BRCs, were able to observe the damaging effects Covid-19 can have on the brain.

The study team scanned the brains of 30 people who had been admitted to hospital with severe Covid-19 early in the pandemic, before vaccines were available. The researchers found that Covid-19 infection damages the region of the brainstem associated with breathlessness, fatigue and anxiety.

The powerful MRI scanners used for the study, known as 7-Tesla or 7T scanners, can measure inflammation in the brain. Their results, published in the journal Brain, will help scientists and clinicians understand the long-term effects of Covid-19 on the brain and the rest of the body. Although the study was started before the long-term effects of Covid were recognised, it will help to better understand this condition.

The brainstem, which connects the brain to the spinal cord, is the control centre for many basic life functions and reflexes. Clusters of nerve cells in the brainstem, known as nuclei, are responsible for regulating and processing essential bodily functions such as breathing, heart rate, pain and blood pressure.

“Things happening in and around the brainstem are vital for quality of life, but it had been impossible to scan the inflammation of the brainstem nuclei in living people, because of their tiny size and difficult position.” said first author Dr Catarina Rua, from the Department of Clinical Neurosciences. “Usually, scientists only get a good look at the brainstem during post-mortem examinations.”

“The brainstem is the critical junction box between our conscious selves and what is happening in our bodies,” said Professor James Rowe, also from the Department of Clinical Neurosciences, who co-led the research. “The ability to see and understand how the brainstem changes in response to Covid-19 will help explain and treat the long term effects more effectively.”

In the early days of the Covid-19 pandemic, before effective vaccines were available, post-mortem studies of patients who had died from severe Covid-19 infections showed changes in their brainstems, including inflammation. Many of these changes were thought to result from a post-infection immune response, rather than direct virus invasion of the brain.  

“People who were very sick early in the pandemic showed long-lasting brain changes, likely caused by an immune response to the virus. But measuring that immune response is difficult in living people,” said Rowe. “Normal hospital type MRI scanners can’t see inside the brain with the kind of chemical and physical detail we need.”

“But with 7T scanners, we can now measure these details. The active immune cells interfere with the ultra-high magnetic field, so that we’re able to detect how they are behaving,” said Rua. “Cambridge was special because we were able to scan even the sickest and infectious patients, early in the pandemic.”

Many of the patients admitted to hospital early in the pandemic reported fatigue, breathlessness and chest pain as troubling long-lasting symptoms. The researchers hypothesised these symptoms were in part the result of damage to key brainstem nuclei, damage which persists long after Covid-19 infection has passed.

The researchers saw that multiple regions of the brainstem, in particular the medulla oblongata, pons and midbrain, showed abnormalities consistent with a neuroinflammatory response. The abnormalities appeared several weeks after hospital admission, and in regions of the brain responsible for controlling breathing.

“The fact that we see abnormalities in the parts of the brain associated with breathing strongly suggests that long-lasting symptoms are an effect of inflammation in the brainstem following Covid-19 infection,” said Rua. “These effects are over and above the effects of age and gender, and are more pronounced in those who had had severe Covid-19.”

In addition to the physical effects of Covid-19, the 7T scanners provided evidence of some of the psychiatric effects of the disease. The brainstem monitors breathlessness, as well as fatigue and anxiety. “Mental health is intimately connected to brain health, and patients with the most marked immune response also showed higher levels of depression and anxiety,” said Rowe. “Changes in the brainstem caused by Covid-19 infection could also lead to poor mental health outcomes, because of the tight connection between physical and mental health.”

The researchers say the results could aid in the understanding of other conditions associated with inflammation of the brainstem, like MS and dementia. The 7T scanners could also be used to monitor the effectiveness of different treatments for brain diseases.

“This was an incredible collaboration, right at the peak of the pandemic, when testing was very difficult, and I was amazed how well the 7T scanners worked,” said Rua. “I was really impressed with how, in the heat of the moment, the collaboration between lots of different researchers came together so effectively.”

Professor Miles Parkes, director of the NIHR Cambridge BRC said: “In identifying subtle changes in the brainstem using the latest MRI scanning technology this important research helps shed light on the difficult to characterise but very real longer term consequences of COVID infection. Patients who experience these symptoms will be relieved to see progress being made in understanding them. The work was supported by the NIHR Biomedical Research Centres in Cambridge and Oxford, and shows the power of collaboration between these two centres of excellence to deliver important scientific breakthroughs”

The research was supported in part by the NIHR Cambridge Biomedical Research Centre, the NIHR Oxford Biomedical Research Centre, and the University of Oxford COVID Medical Sciences Division Rapid Response Fund.

Reference:

Catarina Rua et al. ‘7-Tesla quantitative susceptibility mapping in COVID-19: brainstem effects and outcome associations.’ Brain (2024). DOI: 10.1093/brain/awae215

Artificial intelligence outperforms clinical tests at predicting progress of Alzheimer’s disease

Graphic showing intelligence and data: Image by Gerd Altmann from Pixabay.

Cambridge scientists have developed an artificially-intelligent tool capable of predicting in four cases out of five whether people with early signs of dementia will remain stable or develop Alzheimer’s disease.

The team say this new approach could reduce the need for invasive and costly diagnostic tests while improving treatment outcomes early when interventions such as lifestyle changes or new medicines may have a chance to work best.

Dementia poses a significant global healthcare challenge, affecting over 55 million people worldwide at an estimated annual cost of $820 billion. The number of cases is expected to almost treble over the next 50 years.

The main cause of dementia is Alzheimer’s disease, which accounts for 60-80% of cases. Early detection is crucial as this is when treatments are likely to be most effective, yet early dementia diagnosis and prognosis may not be accurate without the use of invasive or expensive tests such as positron emission tomography (PET) scans or lumbar puncture, which are not available in all memory clinics. As a result, up to a third of patients may be misdiagnosed and others diagnosed too late for treatment to be effective.

A team led by scientists from the Department of Psychology at the University of Cambridge has developed a machine learning model able to predict whether and how fast an individual with mild memory and thinking problems will progress to developing Alzheimer’s disease. In research published today in eClinical Medicine, they show that it is more accurate than current clinical diagnostic tools.

To build their model, the researchers used routinely-collected, non-invasive, and low-cost patient data – cognitive tests and structural MRI scans showing grey matter atrophy – from over 400 individuals who were part of a research cohort in the USA.

They then tested the model using real-world patient data from a further 600 participants from the US cohort and – importantly – longitudinal data from 900 people from memory clinics in the UK and Singapore.

The algorithm was able to distinguish between people with stable mild cognitive impairment and those who progressed to Alzheimer’s disease within a three-year period. It was able to correctly identify individuals who went on to develop Alzheimer’s in 82% of cases and correctly identify those who didn’t in 81% of cases from cognitive tests and an MRI scan alone.

The algorithm was around three times more accurate at predicting the progression to Alzheimer’s than the current standard of care; that is, standard clinical markers (such as grey matter atrophy or cognitive scores) or clinical diagnosis. This shows that the model could significantly reduce misdiagnosis.

The model also allowed the researchers to stratify people with Alzheimer’s disease using data from each person’s first visit at the memory clinic into three groups: those whose symptoms would remain stable (around 50% of participants), those who would progress to Alzheimer’s slowly (around 35%) and those who would progress more rapidly (the remaining 15%). These predictions were validated when looking at follow-up data over 6 years. This is important as it could help identify those people at an early enough stage that they may benefit from new treatments, while also identifying those people who need close monitoring as their condition is likely to deteriorate rapidly.

Importantly, those 50% of people who have symptoms such as memory loss but remain stable, would be better directed to a different clinical pathway as their symptoms may be due to other causes rather than dementia, such as anxiety or depression.

Senior author Professor Zoe Kourtzi from the Department of Psychology at the University of Cambridge said: “We’ve created a tool which, despite using only data from cognitive tests and MRI scans, is much more sensitive than current approaches at predicting whether someone will progress from mild symptoms to Alzheimer’s – and if so, whether this progress will be fast or slow.

“This has the potential to significantly improve patient wellbeing, showing us which people need closest care, while removing the anxiety for those patients we predict will remain stable. At a time of intense pressure on healthcare resources, this will also help remove the need for unnecessary invasive and costly diagnostic tests.”

While the researchers tested the algorithm on data from a research cohort, it was validated using independent data that included almost 900 individuals who attended memory clinics in the UK and Singapore. In the UK, patients were recruited through the Quantiative MRI in NHS Memory Clinics Study (QMIN-MC) led by study co-author Dr Timothy Rittman at Cambridge University Hospitals NHS Trust and Cambridgeshire and Peterborough NHS Foundation Trusts (CPFT).

The researchers say this shows it should be applicable in a real-world patient, clinical setting.

Dr Ben Underwood, Honorary Consultant Psychiatrist at CPFT, assistant professor at the Department of Psychiatry, University of Cambridge and NIHR Cambridge BRC researcher, said: “Memory problems are common as we get older. In clinic I see how uncertainty about whether these might be the first signs of dementia can cause a lot of worry for people and their families, as well as being frustrating for doctors who would much prefer to give definitive answers. The fact that we might be able to reduce this uncertainty with information we already have is exciting and is likely to become even more important as new treatments emerge.”

Professor Kourtzi said: “AI models are only as good as the data they are trained on. To make sure ours has the potential to be adopted in a healthcare setting, we trained and tested it on routinely-collected data not just from research cohorts, but from patients in actual memory clinics. This shows it will be generalisable to a real-world setting.”

The team now hope to extend their model to other forms of dementia, such as vascular dementia and frontotemporal dementia, and using different types of data, such as markers from blood tests.

Professor Kourtzi added: “If we’re going to tackle the growing health challenge presented by dementia, we will need better tools for identifying and intervening at the earliest possible stage. Our vision is to scale up our AI tool to help clinicians assign the right person at the right time to the right diagnostic and treatment pathway. Our tool can help match the right patients to clinical trials, accelerating new drug discovery for disease modifying treatments.”

The study was funded by Wellcome, the Royal Society, Alzheimer’s Research UK, the Alzheimer’s Drug Discovery Foundation Diagnostics Accelerator, the Alan Turing Institute, and the National Institute for Health and Care Research Cambridge Biomedical Research Centre.

Paper:

Lee, LY & Vaghari, D et al. Robust and interpretable AI-guided marker for early dementia prediction in real-world clinical settings. eClinMed; 12 July 2024; DOI: 10.1016/j.eclinm.2024.102725

Study estimates number of patients for potential new Alzheimer’s disease treatments


Clinical researchers at Cambridgeshire and Peterborough NHS Foundation Trust and South London and Maudsley NHS Foundation Trust have collaborated to model how many patients might receive new treatments for Alzheimer’s disease currently under review.

Using data on eligible patients from both Trusts and scaling up, the team estimate that a maximum of 30,000 people using dementia services around the country would be suitable for these potential treatments and that NHS providers could provide them on a small scale if approved.

This partnership study was supported by the National Institute for Health and Care Research (NIHR) Cambridge and Maudsley Biomedical Research Centres. Their paper has been shared with research and clinical communities in The British Journal of Psychiatry First View while the drugs are being reviewed for regulatory approval in the UK.

Lead author and CPFT Academic Clinical Fellow Dr Axel Laurell said: “‘Last year the first drugs which can slow down the progression of Alzheimer’s disease by targeting brain amyloid were identified as lecanemab and donanemab. This year they are being considered for approval to use in the UK. We wanted to answer a crucial question to help the NHS plan and prepare, by predicting the largest number of people that might receive these drugs if approved based on eligibility criteria from the clinical trials.”

The study team used anonymised research patient databases from Cambridgeshire and Peterborough and South London and Maudsley NHS Foundation Trusts and examined the records of 82,386 people referred to their services. Applying the eligibility criteria to receive these new types of drugs (monoclonal antibodies) for Alzheimer’s, such as diagnosis, stage of disease, other health conditions, brain imaging data and cognitive test results, they predict that 906 people every year could receive these treatments in their services. This model scales up to indicate around 30,000 people using dementia services nationally might use them. 

Dr Ben Underwood, honorary consultant psychiatrist, Research and Development Director at CPFT and study lead said: “Our work, based on real NHS data, suggests that some of the drugs currently being appraised would only be appropriate for a minority of the people we see in clinic. This gives some idea of the potential scale of the challenge of delivering these new treatments in the NHS if they were approved for use. It is important that we continue to research alternatives that can benefit the majority of people living with Alzheimer’s disease. At CPFT, we work to test and bring the latest proven treatments to our patients as a research active Trust, when their safety and clinical efficacy has been assessed and approved for the NHS.”

Dr Ash Venkataraman, NIHR Academic Clinical Lecturer at the Institute of Psychiatry, Psychology and Neuroscience (IoPPN) King’s College London, Speciality Registrar in Old Age Psychiatry at South London and Maudsley NHS Foundation Trust and joint lead author said: “There is understandably a lot of anticipation around the potential of these new Alzheimer’s drugs, but they are both expensive and resource intensive as they require regular infusions and brain scans to check suitability and monitor side effects. As such, it is important to have an accurate estimate of how many people may be suitable for these medications to inform service provision. Our study is the first to do this at a detailed level using diverse patient data across two NHS Trusts.”

The NHS is a world leader in rolling out innovative treatments, including personalised cancer and life-saving gene therapies, and has established a dedicated programme team to prepare the NHS for the potential arrival of new Alzheimer’s treatments. They must first be approved by the Medicines and Healthcare products Regulatory Agency (MHRA) and meet National Institute for Health and Care Excellence (NICE) standards for patient safety, clinical and cost effectiveness.

NIHR’s BRCs are collaborations between world-leading universities and NHS organisations that bring together academics and clinicians to translate lab-based scientific breakthroughs into potential new treatments, diagnostics and medical technologies.

Lab-grown ‘small blood vessels’ point to potential treatment for major cause of stroke and vascular dementia

Cambridge scientists have grown small blood vessel-like models in the lab and used them to show how damage to the scaffolding that support these vessels can cause them to leak, leading to conditions such as vascular dementia and stroke.

The study, published today in Stem Cell Reports, also identifies a drug target to ‘plug’ these leaks and prevent so-called small vessel disease in the brain.

Cerebral small vessel disease (SVD) is a leading cause of age-related cognitive decline and contributes to almost half (45%) of dementia cases worldwide. It is also responsible for one in five (20%) of ischemic strokes, the most common type of stroke, where a blood clot prevents the flow of blood and oxygen to the brain.

The majority of cases of SVD are associated with conditions such as hypertension and type 2 diabetes, and tend to affect people in their middle age. However, there are some rare, inherited forms of the disease that can strike people at a younger age, often in their mid-thirties. Both the inherited and ‘spontaneous’ forms of the disease share similar characteristics.

Scientists at the Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, used cells taken from skin biopsies of patients with one of these rare forms of SVD, which caused by a mutation in a gene called COL4.

By reprogramming the skin cells, they were able to create induced pluripotent stem cells – cells that have the capacity to develop into almost any type of cell within the body. The team then used these stem cells to generate cells of the brain blood vessels and create a model of the disease that mimics the defect seen in patients’ brain vessels.

Dr Alessandra Granata from the Department of Clinical Neurosciences at Cambridge, who led the study, said: “Despite the number of people affected worldwide by small vessel disease, we have little in the way of treatments because we don’t fully understand what damages the blood vessels and causes the disease. Most of what we know about the underlying causes tends to come from animal studies, but they are limited in what they can tell us.

“That’s why we turned to stem cells to generate cells of the brain blood vessels and create a disease model ‘in a dish’ that mimics what we see in patients.”

Our blood vessels are built around a type of scaffolding known as an extracellular matrix, a net-like structure that lines and supports the small blood vessels in the brain. The COL4 gene is important for the health of this matrix.

In their disease model, the team found that the extracellular matrix is disrupted, particularly at its so-called ‘tight junctions’, which ‘zip’ cells together. This leads to the small blood vessels becoming leaky – a key characteristic seen in SVD, where blood leaks out of the vessels and into the brain.

The researchers identified a class of molecules called metalloproteinases (MMPs) that play a key role in this damage. Ordinarily, MMPs are important for maintaining the extracellular matrix, but if too many of them are produced, they can damage the structure – similar to the how in The Sorcerer’s Apprentice, a single broom can help mop the floor, but too many wreak havoc.

When the team treated the blood vessels with drugs that inhibit MMPs – an antibiotic and anti-cancer drug – they found that these reversed the damage and stopped the leakage.

Dr Granata added: “These particular drugs come with potentially significant side effects so wouldn’t in themselves be viable to treat small vessel disease. But they show that in theory, targeting MMPs could stop the disease. Our model could be scaled up relatively easily to test the viability of future potential drugs.”

Professor Martin Bennett NIHR Cambridge BRC theme lead for Cardiovascular and Respiratory said: “Cerebral small vessel disease (SVD) is both the commonest cause of vascular dementia and a major cause of stroke, and a major focus of experimental studies in the Cambridge Cardiorespiratory BRC theme. This study provides an important model to identify the mechanisms underlying some genetic forms of SVD, and potential targets and drugs to prevent cerebral SVD.”

The study was funded by the Stroke Association, British Heart Foundation and Alzheimer’s Society, with support from the NIHR Cambridge Biomedical Research Centre and the European Union’s Horizon 2020 Programme.

Paper Reference

Al-Thani, M, Goodwin-Trotman, M. A novel human 1 iPSC model of COL4A1/A2 small vessel disease unveils a key pathogenic role of matrix metalloproteinases. Stem Cell Reports; 16 Nov 2023; DOI: https://doi.org/10.1016/j.stemcr.2023.10.014

Researchers awarded prestigious Academy of Medical Sciences Fellowships

Four NIHR Cambridge BRC researchers have been elected to the Academy of Medical Sciences Fellowship.

Theme Leads Professors James Rowe and Serena Nik-Zainal, together with researchers Professors Charlotte Coles and Emanuele Di Angelantonio, received the awards in recognition of their outstanding biomedical and health research which has translated into benefits for patients and wider society.

James B. Rowe, Prof - Dementia
Neurodegenerative Disease and Dementias Theme Lead Professor James Rowe
Professor Serena Nik Zainal
Genomic Medicine Theme Lead Professor Serena Nik Zainal
Prof Charlotte Coles
Professor Charlotte Coles
Prof Emanuele Di Angelantonio
Prof Emanuele Di Angelantonio

Academy of Medical Sciences President Professor Dame Anne Johnson said: “These new Fellows are pioneering biomedical research and driving life-saving improvements in healthcare. It’s a pleasure to recognise and celebrate their exceptional talent by welcoming them to the Fellowship.”

  • This year Fellows were chosen from 353 candidates, and a shortlist of 126 candidates for peer review. To find out more about the Fellowship visit the Academy of Medical Sciences website.

Dementia signs detected as early as nine years ahead of diagnosis

Cambridge scientists have shown that it is possible to spot signs of brain impairment in patients as early as nine years before they receive a diagnosis for one of a number of dementia-related diseases.

In research published in Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, the team analysed data from the UK Biobank and found impairment in several areas, such as problem solving and number recall, across a range of conditions.

The findings raise the possibility that in the future, at-risk patients could be screened to help select those who would benefit from interventions to reduce their risk of developing one of the conditions, or to help identify patients suitable for recruitment to clinical trials for new treatments.

There are currently very few effective treatments for dementia or other neurodegenerative diseases such as Parkinson’s disease. In part, this is because these conditions are often only diagnosed once symptoms appear, whereas the underlying neurodegeneration may have begun years – even decades – earlier. This means that by the time patients take part in clinical trials, it may already be too late in the disease process to alter its course.

Until now, it has been unclear whether it might be possible to detect changes in brain function before the onset of symptoms. To help answer this question, researchers at the University of Cambridge and Cambridge University Hospitals NHS Foundation Trust turned to UK Biobank, a biomedical database and research resource containing anonymised genetic, lifestyle and health information from half a million UK participants aged 40-69.

As well as collecting information on participants’ health and disease diagnoses, UK Biobank collected data from a battery of tests including problem solving, memory, reaction times and grip strength, as well as data on weight loss and gain and on the number of falls. This allowed them to look back to see whether any signs were present at baseline – that is, when measurements were first collected from participants (between five and nine years prior to diagnosis).

People who went on to develop Alzheimer’s disease scored more poorly compared to healthy individuals when it came to problem solving tasks, reaction times, remembering lists of numbers, prospective memory (our ability to remember to do something later on) and pair matching. This was also the case for people who developed a rarer form of dementia known as frontotemporal dementia.

People who went on to develop Alzheimer’s were more likely than healthy adults to have had a fall in the previous 12 months. Those patients who went on to develop a rare neurological condition known as progressive supranuclear palsy (PSP), which affects balance, were more than twice as likely as healthy individuals to have had a fall.

For every condition studied – including Parkinson’s disease and dementia with Lewy bodies – patients reported poorer overall health at baseline.

First author Nol Swaddiwudhipong, a junior doctor at the University of Cambridge, said: “When we looked back at patients’ histories, it became clear that they were showing some cognitive impairment several years before their symptoms became obvious enough to prompt a diagnosis. The impairments were often subtle, but across a number of aspects of cognition.

“This is a step towards us being able to screen people who are at greatest risk – for example, people over 50 or those who have high blood pressure or do not do enough exercise – and intervene at an earlier stage to help them reduce their risk.”

Senior author Dr Tim Rittman from the Department of Clinical Neurosciences at the University of Cambridge added: “People should not be unduly worried if, for example, they are not good at recalling numbers. Even some healthy individuals will naturally score better or worse than their peers. But we would encourage anyone who has any concerns or notices that their memory or recall is getting worse to speak to their GP.”

Dr Rittman said the findings could also help identify people who can participate in clinical trials for potential new treatments. “The problem with clinical trials is that by necessity they often recruit patients with a diagnosis, but we know that by this point they are already some way down the road and their condition cannot be stopped. If we can find these individuals early enough, we’ll have a better chance of seeing if the drugs are effective.”

The research was funded by the Medical Research Council with support from the NIHR Cambridge Biomedical Research Centre.

Paper Reference

Swaddiwudhipong, N, et al. Pre-Diagnostic Cognitive and Functional Impairment in Multiple Sporadic Neurodegenerative Diseases. Alzheimer’s & Dementia; 13 Oct 2022; DOI: 10.1002/alz.12802


Scientists identify the cause of Alzheimer’s progression in the brain

Cambridge researchers have used human data to measure the speed of different processes that lead to Alzheimer’s disease and found that it develops in a very different way than previously thought. The results could help researchers to develop new treatments.

An international research team, led by the University of Cambridge and supported by the NIHR Cambridge BRC, found that Alzheimer’s disease starts in multiple, different regions of the brain, rather than from a single point which then spreads elsewhere. How quickly the disease kills cells in these regions determines how quickly the disease progresses overall.

The researchers used post-mortem brain samples from Alzheimer’s patients, as well as brain PET scans from living patients with a range of cognitive impairment, from mild impairment through to those with late-stage Alzheimer’s disease. The researchers used the samples and scans to track how a protein called tau (one of two key proteins thought to cause the condition) formed into clumps called ‘aggregates’.

In Alzheimer’s disease, tau and another protein called amyloid-beta, build up into tangles and plaques (clumps) – aggregates – causing brain cells to die and the brain to shrink. This results in memory loss, personality changes and difficulty carrying out daily tasks. For many years, the processes within the brain which result in Alzheimer’s disease have been described using terms like ‘cascade’ and ‘chain reaction’. It is a difficult disease to study, since it develops over decades, and a definitive diagnosis can only be given following examination of samples of brain tissue after death.

However, by combining five different datasets and applying them to the same mathematical model, the researchers observed that the speed at which aggregates multiply in individual regions of the brain determines the progression of Alzheimer’s disease, rather than aggregates spreading from one region to another.

“The thinking had been that Alzheimer’s develops in a way that’s similar to many cancers: the aggregates form in one region and then spread through the brain,” said Dr Georg Meisl from Cambridge’s Yusuf Hamied Department of Chemistry, the paper’s first author. “But instead, we found that when Alzheimer’s starts there are already aggregates in multiple regions of the brain, and so trying to stop the spread between regions will do little to slow the disease.”

The results, reported in the journal Science Advances, open up new ways of understanding the progress of Alzheimer’s and other neurodegenerative diseases, and new ways that future treatments might be developed.

This is the first time that human data has been used to understand the development of Alzheimer’s disease over time. It was made possible in part by approaches developed in Cambridge over the last decade, which allowed the modelling of protein aggregation and spread in the brain, as well as advances in PET scanning and improvements in the sensitivity of other brain measurements.

“This research shows the value of working with human data instead of imperfect animal models,” said co-senior author Professor Tuomas Knowles, also from the Department of Chemistry. “It’s exciting to see the progress in this field – fifteen years ago, the basic molecular mechanisms were determined for simple systems in a test tube by us and others; but now we’re able to study this process at the molecular level in real patients, which is an important step to one day developing treatments.”

The researchers found that tau aggregates multiply slower than expected – taking up to five years. “Neurons are surprisingly good at stopping aggregates from forming, but we need to find ways to make them even better if we’re going to develop an effective treatment,” said co-senior author Professor Sir David Klenerman, from the UK Dementia Research Institute at the University of Cambridge. “It’s fascinating how biology has evolved to stop the aggregation of proteins.

“The work allows us to determine the rate limiting molecular step in the development and spread of tau aggregate through the brain and hence should be targeted for an effective therapy for Alzheimer’s disease. In future it also might allow the effectiveness of a potential treatment to be measured by analysing the changes in PET signal over time using the model we have developed,” Professor Sir David Klenerman added.

The researchers say their research could be used to help the development of treatments for Alzheimer’s disease, which affects an estimated 44 million people worldwide, by targeting the most important processes that occur when humans develop the disease. It could also be applied to other neurodegenerative diseases, such as Parkinson’s disease.  

“The key discovery is that stopping the replication of aggregates rather than their propagation is going to be more effective at the stages of the disease that we studied,” said Knowles.

The researchers are now planning to look earlier in the development of the disease, and extend the studies to other diseases such as Frontal temporal dementia, traumatic brain injury and progressive supranuclear palsy where tau aggregates are also formed during disease.

The study is a collaboration between researchers at the UK Dementia Research Institute, the University of Cambridge and Harvard Medical School. Funding is acknowledged from Sidney Sussex College Cambridge, the European Research Council, the Royal Society, JPB Foundation, the Rainwater Foundation, the NIH, and the NIHR Cambridge Biomedical Research Centre, which supports the Cambridge Brain Bank.

To read the full paper:

Georg Meisl et al.
In vivo rate-determining steps of tau seed accumulation in Alzheimer’s disease.’ Science Advances (2021).
DOI: 10.1126/sciadv.abh1448

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