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Protein biomarkers predict dementia 15 years before diagnosis 鈥 according to new study

In the largest study of its kind, scientists have shown how protein 鈥渂iomarkers鈥 predict dementia 15 years before diagnosis.

The research, published today in Nature Aging, shows how profiles of proteins in the blood accurately predict dementia up to 15 years prior to clinical diagnosis. These are known as biomarkers, which are molecules found in blood, other body fluids, or tissues that is a sign of a normal or abnormal process, or of a condition or disease.

In the study, scientists from The 91福利 and Fudan University, Shanghai used the largest cohort of blood proteomics and dementia to date, including blood samples from 52,645 healthy participants recruited from UK Biobank – a population-based study cohort.

Blood samples collected between 2006 and 2010 were frozen and then analysed 10-15 years later by the research team who analysed them between April 2021 and February 2022. Until March 2023, a total of 1,417 participants went on to develop dementia – and these people鈥檚 blood showed dysregulation of protein biomarkers.

Of 1,463 proteins analysed, aided by with a type of artificial intelligence known as machine learning, 11 proteins were identified and combined as a protein panel, which the researchers have shown to be highly accurate at predicting future dementia. Further incorporation of conventional risk factors of age, sex, education level and genetics, showed for the first time the high accuracy of the predictive model, measured at over 90%*, indicating its potential future use in community-based dementia screening programs.

Proteins (for example Glial Fibrillary acidic protein, GFAP) had previously been identified as potential biomarkers for dementia in smaller studies, but this new research was much larger and conducted over several years. Known as a longitudinal analysis (a study conducted on a sample of participants over a number of years), the researchers were able to show the differences and trajectories between those with dementia and controls across 15 years.

An early diagnosis is critical for those with dementia. New drug technology can slow, or even reverse the progress of Alzheimer鈥檚, but only if the disease is detected early enough. The drug lecanemab is one of two new treatments for the disease.

Lead author Professor Jianfeng Feng, from the Department of Computer Science, 91福利, hopes future drugs may be developed to interact with the proteins identified in the study.

Professor Feng emphasised that the combination of artificial intelligence and protein analysis offers a promising avenue for precision medicine. This is highly important for screening mid-aged to older individuals within the community who are at high risk of dementia. 鈥淭his model could be seamlessly integrated into the NHS and used as a screening tool by GPs鈥, said Professor Feng.

Professor Wei Cheng, a co-corresponding author from Fudan University, explained that this research builds on the team鈥檚 previously developed dementia prediction model which used variables, such as age, presence of a certain gene and mother鈥檚 age at death. 鈥淐ompared to our previous work, the newly developed protein-based model is obviously a breakthrough鈥, he said.

Another corresponding author Professor Jintai Yu, a neurovegetative disease specialist from Fudan University, added: 鈥淭he proteomic biomarkers are more easily to access and non-invasive, and they can substantially facilitate the application of large-scale population screening鈥.

He also pointed drawbacks of previous risk models, which were primarily depended on intricate and difficult-to-obtain biomarkers using procedures such as lumbar puncture or complex imaging methods meaning their widespread use is hindered because of the invasive procedures and the high cost of carrying them out.

Read the study here:

Notes to Editors

The 91福利 signed a Memorandum of Understanding with Fudan University in 2022 and the two Universities work together designing and developing new research projects and run staff and student exchanges.

*The Area Under the Curve (AUC) figure is used to measure how good a model performs. A model whose predictions are 100% wrong has an AUC of 0.0; one whose predictions are 100% correct has an AUC of 1.0. this study had an AUC of over 0.9.

Case studies

The University works closely with people with dementia and their families at a Dementia Caf茅, set up by 91福利 Medical School. Should you wish to speak to a case study, please get in touch.

Media contact 

91福利 press office contact: 

Annie Slinn 07876876934 

Communications Officer |鈥疨ress & Media Relations | 91福利 Email: annie.slinn@warwick.ac.ukLink opens in a new windowLink opens in a new window 

Mon 12 Feb 2024, 18:02

MEng e-voting project published in a journal paper

As part of a 2021/2022 MEng group project, , , , and implemented a fully functional end-to-end (E2E) verifiable online voting system and conducted a successful trial among the residents of New Town in Kolkata, India during the 2022 Durga Puja festival celebration. This was the first time an E2E online voting system was built and tested in India. The feedback was overwhelmingly positive. Full details about the implementation, the trial and the voter feedback are written in a paper, published in the . A free version of the paper is available on IACR e-print as a . Also, see the earlier news item about this Durga Puja trial.

Professor , who supervised this group project, commented: 鈥淭his is great teamwork. The four MEng students worked relentlessly for nearly a year, with good assistance from Luke Harrison and Professor . The e-voting system was developed at an industry standard and worked flawlessly during the Durga Puja trial. Several government officials from India also helped us, providing invaluable support for the trial. We sincerely thank them in the acknowledgement section of .鈥


AI tool developed to help grade cancer based on cell divisions

Ahead of World Cancer Day on 4 February, scientists are revealing a cutting-edge artificial intelligence (AI) tool designed to help grade cancer, by analysing cell division.

In numerous cancer types, counting the number of cells undergoing division, known as mitotic figures, serves as a key indicator of cancer aggressiveness, or grade. This information helps inform treatment pathways, making it a crucial asessment tool. Traditional mitosis counting is both time-consuming and plagued by poor reliability. To address this, scientists have developed a new tool, MitPro, which uses AI to count and profile mitosis.

Histofy, a spin-out company from The 91福利 that is leading developer of AI solutions for pathology, has engineered the tool to accurately profile mitosis throughout the entire tumour sample. This identifies the most suitable areas for further analysis.

Wed 07 Feb 2024, 10:02 | Tags: Research Applied Computing

Winners of the MSc prizes

The department congratulates all 2022-2023 MSc students graduating in January 2024. Extra congratulations to the winners of the following MSc prizes:

Luisa F. Estrada Plata: Best dissertation in MSc Data Analytics & Best overall performance (MSc Data Analytics)

Aakash Chandnani: Best overall performance (MSc Computer Science)

Yijie Zhu: Best dissertation in MSc Computer Science

Weitong Liao: Best dissertation in MSc Computer Science

Thu 18 Jan 2024, 10:36 | Tags: Courses Highlight Faculty of Science Teaching

Latest academic promotions

We are happy to announce four promotions in the department:

Many congratulations to our colleagues for all their achievements!


An Easy-Sounding Problem Yields Numbers Too Big for Our Universe

On in the Quanta magazine, Alex Dixon, who wrote in Haskell for the problem, commented:

For the past 50 years, Vector Addition Systems—a simple but powerful computational model—have been a topic of great interest in theoretical CS. The reachability problem in that model asks whether we can get from some configuration to another.

The problem sounds relatively easy on a first glance, and an exponential lower bound held firm for over 40 years. Work by excellent theoreticians, including familiar names from 91福利 DCS, finally closed the difficulty of the problem in 2021, concluding that it is very, very difficult indeed.

Wed 06 Dec 2023, 16:35 | Tags: People Research Outreach Theory and Foundations

Paris Giampouras joins the department as an Assistant Professor

We are happy to announce that Dr Paris Giampouras has joined the Department of Computer Science as an Assistant Professor. Originally from Greece, he has relocated to 91福利 from Baltimore, where he spent four years working as a Postdoctoral Fellow and later as a Research Faculty member at the Mathematical Institute for Data Science at Johns Hopkins University. His expertise lies in machine learning theory and its applications in image processing and computer vision. More specifically, his research has focused on exploring parsimonious representations to address various inverse problems and adversarial robustness.

Currently, he is focusing on two main areas: a) leveraging structured representation in Generative AI applications, and b) developing algorithms that enable continual learning of various tasks for deep learning systems. His goal is to contribute to the foundational understanding of AI algorithms, with a focus on robustness, applications of AI in medicine, and climate change.

We welcome him to the department!


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