The potential clinical value of plasma biomarkers in Alzheimer's disease

Blennow, Kaj; Galasko, Douglas; Perneczky, Robert; Quevenco, Frances‐Catherine; van der Flier, Wiesje M.; Akinwonmi, Akin; Carboni, Margherita; Jethwa, Alexander; Suridjan, Ivonne; Zetterberg, Henrik

doi:10.1002/alz.13455

Cited by 13 publications

(5 citation statements)

References 61 publications

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“…Our study presents a data-driven approach that is aimed at achieving diagnosis in the most efficient manner without compromising diagnostic performance. In addition such approach may streamline clinical decision-making pipelines with blood-based biomarkers in the future by limiting the number of patients that require confirmatory testing [ 48 ]. However, detecting underlying (AD) pathology marks only the beginning.…”

Section: Discussionmentioning

confidence: 99%

Computerized decision support is an effective approach to select memory clinic patients for amyloid-PET

Rhodius-Meester,

van Maurik,

Collij

et al. 2024

PLoS ONE

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Background The use of amyloid-PET in dementia workup is upcoming. At the same time, amyloid-PET is costly and limitedly available. While the appropriate use criteria (AUC) aim for optimal use of amyloid-PET, their limited sensitivity hinders the translation to clinical practice. Therefore, there is a need for tools that guide selection of patients for whom amyloid-PET has the most clinical utility. We aimed to develop a computerized decision support approach to select patients for amyloid-PET. Methods We included 286 subjects (135 controls, 108 Alzheimer’s disease dementia, 33 frontotemporal lobe dementia, and 10 vascular dementia) from the Amsterdam Dementia Cohort, with available neuropsychology, APOE, MRI and [18F]florbetaben amyloid-PET. In our computerized decision support approach, using supervised machine learning based on the DSI classifier, we first classified the subjects using only neuropsychology, APOE, and quantified MRI. Then, for subjects with uncertain classification (probability of correct class (PCC) < 0.75) we enriched classification by adding (hypothetical) amyloid positive (AD-like) and negative (normal) PET visual read results and assessed whether the diagnosis became more certain in at least one scenario (PPC≥0.75). If this was the case, the actual visual read result was used in the final classification. We compared the proportion of PET scans and patients diagnosed with sufficient certainty in the computerized approach with three scenarios: 1) without amyloid-PET, 2) amyloid-PET according to the AUC, and 3) amyloid-PET for all patients. Results The computerized approach advised PET in n = 60(21%) patients, leading to a diagnosis with sufficient certainty in n = 188(66%) patients. This approach was more efficient than the other three scenarios: 1) without amyloid-PET, diagnostic classification was obtained in n = 155(54%), 2) applying the AUC resulted in amyloid-PET in n = 113(40%) and diagnostic classification in n = 156(55%), and 3) performing amyloid-PET in all resulted in diagnostic classification in n = 154(54%). Conclusion Our computerized data-driven approach selected 21% of memory clinic patients for amyloid-PET, without compromising diagnostic performance. Our work contributes to a cost-effective implementation and could support clinicians in making a balanced decision in ordering additional amyloid PET during the dementia workup.

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Section: Discussionmentioning

confidence: 99%

Computerized decision support is an effective approach to select memory clinic patients for amyloid-PET

Rhodius-Meester,

van Maurik,

Collij

et al. 2024

PLoS ONE

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“…During the laboratory session, participants had an indwelling cannula sited for collection of regular blood samples at three-hourly intervals (including overnight) for 24 h to assess time of day variation in biomarkers. The samples were processed and were analysed for levels of melatonin, as a gold-standard marker of the circadian clock, as well as biomarkers of dementia e.g., neurofilament light (NfL), phosphorylated tau (p-tau), amyloid-beta (AB40 and AB42; e.g., [ 65 , 66 , 67 ]). In addition, participants collected urine for 24 h in four-hourly intervals (eight hours overnight) for measurement of aMT6s.…”

Section: Methodsmentioning

confidence: 99%

A Protocol for Evaluating Digital Technology for Monitoring Sleep and Circadian Rhythms in Older People and People Living with Dementia in the Community

della Monica,

Ravindran,

Atzori

et al. 2024

Clocks & Sleep

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Sleep and circadian rhythm disturbance are predictors of poor physical and mental health, including dementia. Long-term digital technology-enabled monitoring of sleep and circadian rhythms in the community has great potential for early diagnosis, monitoring of disease progression, and assessing the effectiveness of interventions. Before novel digital technology-based monitoring can be implemented at scale, its performance and acceptability need to be evaluated and compared to gold-standard methodology in relevant populations. Here, we describe our protocol for the evaluation of novel sleep and circadian technology which we have applied in cognitively intact older adults and are currently using in people living with dementia (PLWD). In this protocol, we test a range of technologies simultaneously at home (7–14 days) and subsequently in a clinical research facility in which gold standard methodology for assessing sleep and circadian physiology is implemented. We emphasize the importance of assessing both nocturnal and diurnal sleep (naps), valid markers of circadian physiology, and that evaluation of technology is best achieved in protocols in which sleep is mildly disturbed and in populations that are relevant to the intended use-case. We provide details on the design, implementation, challenges, and advantages of this protocol, along with examples of datasets.

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“…Screening CSF tests for Aβ42, Aβ40, and p-tau 181 were analyzed using Lumipulse (Fujirebio assay). Plasma Aβ42 and Aβ40 used the Euroimmun ELISA assay, and p-tau 181 was analyzed using a Simoa assay [38]. The screening CSF assays were required for enrollment and were therefore conducted in batches over several months during the screening period.…”

Section: Fluid Biomarker Analysesmentioning

confidence: 99%

Effects of Oral ALZ-801/Valiltramiprosate on Plasma Biomarkers, Brain Hippocampal Volume, and Cognition: Results of 2-Year Single-Arm, Open-Label, Phase 2 Trial in APOE4 Carriers with Early Alzheimer’s Disease

Hey,

Abushakra,

Blennow

et al. 2024

Drugs

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Introduction ALZ-801/valiltramiprosate is a small-molecule oral inhibitor of beta amyloid (Aβ) aggregation and oligomer formation being studied in a phase 2 trial in APOE4 carriers with early Alzheimer’s disease (AD) to evaluate treatment effects on fluid and imaging biomarkers and cognitive assessments. Methods The single-arm, open-label phase 2 trial was designed to evaluate the effects of the ALZ-801 265 mg tablet taken twice daily (after 2 weeks once daily) on plasma fluid AD biomarkers, hippocampal volume (HV), and cognition over 104 weeks in APOE4 carriers. The study enrolled subjects aged 50–80 years, with early AD [Mini-Mental State Examination (MMSE) ≥ 22, Clinical Dementia Rating-Global (CDR-G) 0.5 or 1], apolipoprotein E4 (APOE4) genotypes including APOE4/4 and APOE3/4 genotypes, and positive cerebrospinal fluid (CSF) AD biomarkers or prior amyloid scans. The primary outcome was plasma p-tau 181 , HV evaluated by magnetic resonance imaging (MRI) was the key secondary outcome, and plasma Aβ42 and Aβ40 were the secondary biomarker outcomes. The cognitive outcomes were the Rey Auditory Verbal Learning Test and the Digit Symbol Substitution Test. Safety and tolerability evaluations included treatment-emergent adverse events and amyloid-related imaging abnormalities (ARIA). The study was designed and powered to detect 15% reduction from baseline in plasma p-tau 181 at the 104-week endpoint. A sample size of 80 subjects provided adequate power to detect this difference at a significance level of 0.05 using a two-sided paired t -test. Results The enrolled population of 84 subjects (31 homozygotes and 53 heterozygotes) was 52% females, mean age 69 years, MMSE 25.7 [70% mild cognitive impairment (MCI), 30% mild AD] with 55% on cholinesterase inhibitors. Plasma p-tau 181 reduction from baseline was significant (31%, p = 0.045) at 104 weeks and all prior visits; HV atrophy was significantly reduced ( p = 0.0014) compared with matched external controls from an observational Early AD study. Memory scores showed minimal decline from baseline over 104 weeks and correlated significantly with decreased HV atrophy (Spearman’s 0.44, p = 0.002). Common adverse events were COVID infection and mild nausea, and no drug-related serious adverse events were reported. Of 14 early terminations, 6 were due to nonserious treatment-emergent adverse events and 1 death due to COVID. There was no vasogenic brain edema observed on MRI over 104 weeks. Conclusions The effect of ALZ-801 on reducing plasma p-tau 181 over 2 years demonstrates target engagement and supports its anti-Aβ oligomer action that leads to a robust decrease in amyloid-induced brain neurodegeneration. The significant correlation between reduced HV atrop...

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The potential clinical value of plasma biomarkers in Alzheimer's disease

Cited by 13 publications

References 61 publications

Computerized decision support is an effective approach to select memory clinic patients for amyloid-PET

Computerized decision support is an effective approach to select memory clinic patients for amyloid-PET

A Protocol for Evaluating Digital Technology for Monitoring Sleep and Circadian Rhythms in Older People and People Living with Dementia in the Community

Effects of Oral ALZ-801/Valiltramiprosate on Plasma Biomarkers, Brain Hippocampal Volume, and Cognition: Results of 2-Year Single-Arm, Open-Label, Phase 2 Trial in APOE4 Carriers with Early Alzheimer’s Disease

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