So I’ll begin with a brief introduction. It is well known that Alzheimer’s disease contributes to an immense social and financial burden on the society. It is estimated that by the year 2050, approximately 150 million individuals worldwide will be suffering from AD. And the key pathological features of AD are extracellular amyloid plaques and intracellular neurofibrillary tangles. Aging is one of the key risk factors...
So I’ll begin with a brief introduction. It is well known that Alzheimer’s disease contributes to an immense social and financial burden on the society. It is estimated that by the year 2050, approximately 150 million individuals worldwide will be suffering from AD. And the key pathological features of AD are extracellular amyloid plaques and intracellular neurofibrillary tangles. Aging is one of the key risk factors. And with age, multiple co-pathologies are observed in AD patients. These co-pathologies include cerebral amyloid angiopathy, Lewy body dementia, TDP-43 pathology, etc. Therefore, it is crucial to detect these co-pathologies so that we can monitor disease progression and response to the therapeutic interventions such as FDA-approved lecanemab and donanemab, etc. However, there is a lack of in vivo biomarkers to detect such co-pathologies. So the objective of this study was to identify novel blood-based biomarkers for AD co-pathology so as to accurately detect and assess the severity for tailoring treatment plans while reducing the risk of adverse effects. We have utilized neuropathogen-confirmed 306 cases from the Banner Brain and Body Donation Program which have post-mortem AD, TDP43, Lewy body, and CA scores available. And we were fortunate that the antemortem plasma samples were obtained within the five years of death. So we had access to the plasma samples as well as the scores of the diseases, the pathological scores. And then we employed nucleic acid-linked immunosandwich assay or NULISA from the LMR platform, their CNS panel for an exploratory biomarker quantification in plasma of patients. We evaluated the differential protein expression, the NPQ NULISA protein quantification, expression between groups using a linear model adjusted for age, sex, APOE status. Based on analysis, P-tau217 shows a strong association with Alzheimer’s disease pathology, corroborating the existing data and highlighting the utility of NULISAseq for biomarker discovery. As we all know, you must be knowing that P-tau217 has been approved for the Lumipulse platform, and it is one of the key pathological biomarkers for tracking the progression of Alzheimer’s disease. Further, in TDP43 pathology, phospho-TDP43 and the related ratios were normally elevated in TDP43-positive cases. For tracking or monitoring pathology, an artificial neural network model trained on the full NULISAseq panel accurately predicted the Lewy body pathology, demonstrating the power of multi-protein signatures to quantify pathological burden. For cerebral amyloid angiopathy, we have done several analyses, the logistic regression and the ROC curve analysis, and we found that a refined multi-analyte model, including age, sex, AD status, APOE4 status and five panel markers from the NULISAseq panel which are CRP, IL4, CCL11, NfL, and PD-L1, they had an area under the curve of 0.90 which was very encouraging and to identify the presence of CA at post-mortem, which was replicated in an independent validation cohort from the University of California, Irvine campus. So our findings show that plasma biomarkers combination that may act as surrogate indicators of these above-mentioned pathologies, such as TDP-43, alpha-synuclein, CA, but it still warrants further investigation and validation.
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