Diagnostic performance of plasma pTau217, pTau181, Aß1-42 and Aß1-40 in the LUMIPULSE automated platform for the detection of Alzheimer disease.

BACKGROUND: Recently developed blood markers for Alzheimer's disease (AD) detection have high accuracy but usually require ultra-sensitive analytic tools not commonly available in clinical laboratories, and their performance in clinical practice is unknown. METHODS: We analyzed plasma samples from 290 consecutive participants that underwent lumbar puncture in routine clinical practice in a specialized memory clinic (66 cognitively unimpaired, 130 participants with mild cognitive impairment, and 94 with dementia). Participants were classified as amyloid positive (A +) or negative (A-) according to CSF Aß1-42/Aß1-40 ratio. Plasma pTau217, pTau181, Aß1-42 and Aß1-40 were measured in the fully-automated LUMIPULSE platform. We used linear regression to compare plasma biomarkers concentrations between A + and A- groups, evaluated Spearman's correlation between plasma and CSF and performed ROC analyses to assess their diagnostic accuracy to detect brain amyloidosis as determined by CSF Aß1-42/Aß1-40 ratio. We analyzed the concordance of pTau217 with CSF amyloidosis. RESULTS: Plasma pTau217 and pTau181 concentration were higher in A + than A- while the plasma Aß1-42/Aß1-40 ratio was lower in A + compared to A-. pTau181 and the Aß1-42/Aß1-40 ratio showed moderate correlation between plasma and CSF (Rho = 0.66 and 0.69, respectively). The areas under the ROC curve to discriminate A + from A- participants were 0.94 (95% CI 0.92-0.97) for pTau217, and 0.88 (95% CI 0.84-0.92) for both pTau181 and Aß1-42/Aß1-40. Chronic kidney disease (CKD) was related to increased plasma biomarker concentrations, but ratios were less affected. Plasma pTau217 had the highest fold change (× 3.2) and showed high predictive capability in discriminating A + from A-, having 4-7% misclassification rate. The global accuracy of plasma pTau217 using a two-threshold approach was robust in symptomatic groups, exceeding 90%. CONCLUSION: The evaluation of blood biomarkers on an automated platform exhibited high diagnostic accuracy for AD pathophysiology, and pTau217 showed excellent diagnostic accuracy to identify participants with AD in a consecutive sample representing the routine clinical practice in a specialized memory unit.

Diagnostic performance of plasma pTau 217, pTau 181, Aß 1-42 and Aß 1-40 in the LUMIPULSE automated platform for the detection of Alzheimer disease.

BACKGROUND: Recently developed blood markers for Alzheimer's disease (AD) detection have high accuracy but usually require ultra-sensitive analytic tools not commonly available in clinical laboratories, and their performance in clinical practice is unknown. METHODS: We analyzed plasma samples from 290 consecutive participants that underwent lumbar puncture in routine clinical practice in a specialized memory clinic (66 cognitively unimpaired, 130 participants with mild cognitive impairment, and 94 with dementia). Participants were classified as amyloid positive (A+) or negative (A-) according to CSF Aß1-42/Aß1-40 ratio. Plasma pTau217, pTau181, Aß1-42 and Aß1-40 were measured in the fully-automated LUMIPULSE platform. We used linear regression to compare plasma biomarkers concentrations between A + and A- groups, evaluated Spearman's correlation between plasma and CSF and performed ROC analyses to assess their diagnostic accuracy to detect brain amyloidosis as determined by CSF Aß1-42/Aß1-40 ratio. We analyzed the potential of pTau217 to predict amyloidosis in CSF. RESULTS: Plasma pTau217 and pTau181 concentration were higher in A + than A- while the plasma Aß1-42/Aß1-40 ratio was lower in A + compared to A-. pTau181 and the Aß1-42/Aß1-40 ratio showed moderate correlation between plasma and CSF (Rho = 0.66 and 0.69, respectively). The areas under the ROC curve to discriminate A + from A- participants were 0.94 (95% CI 0.92-0.97) for pTau217, and 0.88 (95% CI 0.84-0.92) for both pTau181 and Aß1-42/Aß1-40. Chronic kidney disease (CKD) was related to increased plasma biomarker concentrations, but ratios were less affected. Plasma pTau217 had the highest fold change (x4.2) and showed high predictive capability in discriminating A + from A-, having 4-7% misclassification rate. The global accuracy of plasma pTau217 using a two-threshold approach was robust in symptomatic groups, exceeding 90%. CONCLUSION: The evaluation of blood biomarkers on an automated platform exhibited high diagnostic accuracy for AD pathophysiology, and pTau217 showed excellent diagnostic accuracy to identify participants with AD in a consecutive sample representing the routine clinical practice in a specialized memory unit.

The MOPEAD project: Advancing patient engagement for the detection of "hidden" undiagnosed cases of Alzheimer's disease in the community.

In most, if not all health systems, dementia is underdiagnosed, and when diagnosis occurs, it is typically at a relatively late stage in the disease process despite mounting evidence showing that a timely diagnosis would result in numerous benefits for patients, families, and society. Moving toward earlier diagnoses in Alzheimer's disease (AD) requires a conscientious and collective effort to implement a global strategy addressing the multiple causes hindering patient engagement at different levels of society. This article describes the design of the Models of Patient Engagement for Alzheimer's Disease project, an ongoing EU-funded public-private multinational initiative that will compare four innovative patient engagement strategies across five European countries regarding their ability to identify individuals with prodromal AD and mild AD dementia, which are "hidden" in their communities and traditionally not found in the typical memory clinic setting. The strategies include an online AD citizen science platform, an open house initiative at the memory clinics, and patient engagement at primary care and diabetologist clinics.