NEW STUDY. Research conducted by Dr. Nicholas Ashton, University of Gothenburg and MedTech West, has added further evidence in the possible utility of a blood test for predicting Alzheimer’s disease (AD). Using a mass spectrometry technique, the results show that a particular profile of proteins in blood was very accurate in predicting individuals with AD pathology in brain even before any clinical symptoms were present. While there is currently no effective treatment for AD, a blood test such as this could be extremely important in the effective and accurate selection of participants to aid on-going clinical trials.
Alzheimer’s disease is a public health epidemic with a large and rapidly growing burden that bears significant impact on the society. The individual suffering is great, the costs for the society are substantial, and we still lack effective treatments. Significant advances in the last decade have shown that Positron emission tomography (PET) and cerebrospinal fluid (CSF) measures of amyloid can identify individuals with preclinical Alzheimer’s disease decades before clinical onset.
Current imaging and CSF measurements are considered gold standards for diagnosis of probable AD. However, PET imaging is costly, and it is only available in relatively specialized centers. Therefore, it is unlikely to be part of routine clinical assessment of cognitive complaints before therapies being available. Neither is suitable for population-based screening for identifying high-risk individuals for early intervention before symptom onset. Thus, there is a need to develop more cost-effective and widely accessible biomarkers that can aid AD therapeutic trials in an effective recruitment process. E.g. a blood-based measure that accurately reflects AD pathology.
“Alzheimer’s disease pathology in brain begins to accumulate 15-20 years before onset of clinical symptoms of the disease”, says Nicholas Ashton. “This presents a significant problem in the search for therapeutic intervention that target these pathologies. How do we find individuals at very high risk for such trails when they are seemingly cognitively healthy?”
The article titled “A plasma protein classifier for predicting amyloid burden for preclinical Alzheimer’s disease” is based on research lead by Dr. Nicholas Ashton (University of Gothenburg) and Dr. Abdul Hye (King’s College London) and published in Science Advances on 6 February 2019, describes preliminary data on a new blood test for preclinical Alzheimer’s disease.
In this novel research, Ashton and colleagues took a different approach by developing an in-depth and unbiased screen of proteins in blood. The technique that incorporated isoelectric focusing, isobaric chemical labelling and high-resolution mass spectrometry could identify and quantify >2,500 proteins in blood. The study included 238 individuals from Australian lifestyle study (AIBL) and KARVIAH studies that were classified as amyloid-negative or amyloid-positive by PET imaging. Importantly, all individuals in the study were cognitively healthy, simulating the desired recruitment design for current AD therapeutic trials.
The results demonstrated a 12-protein model for predicting amyloid-positivity in the AIBL cohort. Importantly, this 12-protein model was independently verified in KARVIAH cohort with an accuracy of almost 90% (sensitivity = 0.78, and specificity = 0.77). Interestingly, some proteins shown to be differentially expressed in this study have already been proposed as blood markers for AD (amyloid and NFL). Given that this technique did not intend to target these key proteins, this is impartial evidence that these proteins are extremely important in preclinical Alzheimer’s disease identification. However, in combination with other peripheral proteins discovered in this study, the prediction of preclinical AD was vastly improved. Further work will need to be conducted to determine the mechanistic relationship between these novel proteins, amyloid pathogenesis and AD.
“This panel almost certainly needs to be refined, simplified, and undoubtedly validated in independent cohorts”, says Nicholas Ashton. “Furthermore, efforts need to be made to successfully translate this panel to a simpler automated platform suitable for clinical utility. However, the prediction of amyloid burden in preclinical AD using a diverse blood-based measure offers great potential in preclinical stratification for clinical trials and future diagnostic management.”
Journal: Science Advances
Title: A plasma protein classifier for predicting amyloid burden for preclinical Alzheimer’s disease
Authors: Nicholas J. Ashton, Alejo J. Nevado-Holgado, Imelda S. Barber, Steven Lynham, Veer Gupta, Pratishtha Chatterjee, Kathryn Goozee, Eugene Hone, Steve Pedrini, Kaj Blennow, Michael Schöll, Henrik Zetterberg, Kathryn A. Ellis, Ashley I. Bush, Christopher C. Rowe, Victor L. Villemagne, David Ames, Colin L. Masters, Dag Aarsland, John Powell, Simon Lovestone, Ralph Martins, Abdul Hye.
Link to article: http://advances.sciencemag.org/content/5/2/eaau7220
