Biosensor for the Detection of Alzheimer’s Disease

Alzheimer’s affects an estimated 6.5 million Americans over the age of 65, with 73% of those aged 75 and older. This means that around 1 in 9 people over the age of 65 live with the devastating neurodegenerative disease.1

Biosensor for the Detection of Alzheimer’s Disease.

Image Credit: Atthapon Raksthaput/Shutterstock.com

Detecting Alzheimer’s early on provides patient’s with an improved chance of responding to treatments and also offers the benefit of being eligible for new trials and studies that may advance the research and benefit others suffering from the disease.

Researchers at Simon Fraser University (SFU) have been developing an innovative, new biosensor for the screening and early detection of Alzheimer’s and other diseases. Published in the journal Nature Communications, the team that forms part of SFU’s Nanodevice Fabrication Group describes how their biosensor is able to detect a particular cytokine, which is a specific kind of protein, commonly known as Tumour Necrosis Factor alpha (TNF alpha).

Detecting TNF Alpha

Increased cytokine levels in the body can be an indicator of an underlying health condition, so being able to identify TNF alpha effectively could prove to be a helpful measurement tool for assessing an individual’s health. Moreover, studies have shown that “cytokine storms,” which are an inflammatory reaction to COVID-19, can be effectively treated with cytokine inhibitors and thus improve the chances of survival.

Current testing methods, such as mass spectrometry and enzyme-linked immunosorbent assay (ELISA) for detecting certain biomarkers, like cytokines, require invasive techniques to draw samples. These samples then often need to be sent to a laboratory for testing, which increases the time to results. However, the biosensor the SFU team has designed could offer rapid results without the need for costly invasive procedures.

Our goal is to develop a sensor that’s less invasive, less expensive and simpler to use than existing methods…These sensors are also small and have potential to be placed in doctor’s offices to help diagnose different diseases, including Alzheimer’s disease.

Michael Adachi, Engineering Science Assistant Professor

Biosensing Technology

Biosensors are categorized as analytical devices that are constructed by placing a receptor known as a biorecognition element on a transducer, which is then able to transform the interactions between the biorecognition element and the specified target into a signal that can be measured. In other words, it is a device used for the detection of a biochemical substance by combining a physicochemical detector with a biological component.

The SFU biosensor is described as having extreme sensitivity as it has the capacity to detect TNF alpha in concentrations in blood as low as 10 fM, which is much lower than levels found in samples of healthy blood, which is around 200-300 fM.

SFU’s two-electrode diode biosensor has already demonstrated proof-of-concept by effectively detecting varying levels of TNF alpha down to 10 fM in preparations of synthesized samples. The next step is to move the testing toward the detection of proteins in blood and perhaps other bodily fluids.

The other objective is to use the same device but a different receptor to detect proteins that are more specific to Alzheimer’s disease.

Hamidreza Ghanbari, Engineering Science Ph.D. Student, SFU

Therefore, through further testing, the team hopes to advance the capabilities of the technology and make it more effective for practical use outside the laboratory setting. The biosensor has demonstrated promising results for the rapid detection of TNF alpha with a simple two-electrode design, potentially opening the door to user-friendly point-of-care testing in the near future.

The Nanodevice Fabrication Group team has recently filed provision patents for the technology at SFU’s Technology Licensing Office (TLO).

References and Further Reading

Alzheimer's disease facts and figures (2023) Alzheimer's Disease and Dementia. Available at: https://www.alz.org/alzheimers-dementia/facts-figures#:~:text=The%20number%20of%20Americans%20living,are%20age%2075%20or%20older.

Shaw, M. (2023) SFU scientists developing early alzheimer's disease detection sensor, SFU News - Simon Fraser University. Available at: https://www.sfu.ca/sfunews/stories/2023/01/sfu-scientists-developing-early-alzheimer-s-disease-detection-se.html.

De Silva, T. et al. (2022) “Ultrasensitive rapid cytokine sensors based on asymmetric geometry two-dimensional MOS2 diodes,” Nature Communications, 13(1). Available at: https://doi.org/10.1038/s41467-022-35278-2.

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

David J. Cross

Written by

David J. Cross

David is an academic researcher and interdisciplinary artist. David's current research explores how science and technology, particularly the internet and artificial intelligence, can be put into practice to influence a new shift towards utopianism and the reemergent theory of the commons.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Cross, David. (2023, January 19). Biosensor for the Detection of Alzheimer’s Disease. AZoSensors. Retrieved on November 21, 2024 from https://www.azosensors.com/news.aspx?newsID=15331.

  • MLA

    Cross, David. "Biosensor for the Detection of Alzheimer’s Disease". AZoSensors. 21 November 2024. <https://www.azosensors.com/news.aspx?newsID=15331>.

  • Chicago

    Cross, David. "Biosensor for the Detection of Alzheimer’s Disease". AZoSensors. https://www.azosensors.com/news.aspx?newsID=15331. (accessed November 21, 2024).

  • Harvard

    Cross, David. 2023. Biosensor for the Detection of Alzheimer’s Disease. AZoSensors, viewed 21 November 2024, https://www.azosensors.com/news.aspx?newsID=15331.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this news story?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.