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Blood protein predictors of brain amyloid for enrichment in clinical trials?

ABSTRACT: BACKGROUND:Measures of neocortical amyloid burden (NAB) identify individuals who are at substantially greater risk of developing Alzheimer's disease (AD). Blood-based biomarkers predicting NAB would have great utility for the enrichment of AD clinical trials, including large-scale prevention trials. METHODS:Nontargeted proteomic discovery was applied to 78 subjects from the Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing with a range of NAB values. Technical and independent replications were performed by immunoassay. RESULTS:Seventeen discovery candidates were selected for technical replication. ?2-Macroglobulin, fibrinogen ?-chain (FGG), and complement factor H-related protein 1 were confirmed to be associated with NAB. In an independent cohort, FGG plasma levels combined with age predicted NAB had a sensitivity of 59% and specificity of 78%. CONCLUSION:A single blood protein, FGG, combined with age, was shown to relate to NAB and therefore could have potential for enrichment of clinical trial populations.

SUBMITTER: Ashton NJ

PROVIDER: S-EPMC4876903 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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Blood protein predictors of brain amyloid for enrichment in clinical trials?

Ashton Nicholas J NJ Ashton Nicholas J NJ Kiddle Steven J SJ Graf John J Ward Malcolm M Baird Alison L AL Hye Abdul A Westwood Sarah S Wong Karyuan Vivian KV Dobson Richard J RJ Rabinovici Gil D GD Miller Bruce L BL Rosen Howard J HJ Torres Andrew A Zhang Zhanpan Z Thurfjell Lennart L Covin Antonia A Hehir Cristina Tan CT Baker David D Bazenet Chantal C Lovestone Simon S

Alzheimer's & dementia (Amsterdam, Netherlands) 20150329 1

<h4>Background</h4>Measures of neocortical amyloid burden (NAB) identify individuals who are at substantially greater risk of developing Alzheimer's disease (AD). Blood-based biomarkers predicting NAB would have great utility for the enrichment of AD clinical trials, including large-scale prevention trials.<h4>Methods</h4>Nontargeted proteomic discovery was applied to 78 subjects from the Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing with a range of NAB values. Technical ...[more]

PMID: 27239491

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Project description:In the era of precision medicine, drugs are increasingly developed to target subgroups of patients with certain biomarkers. In large all-comer trials using a biomarker stratified design, the cost of treating and following patients for clinical outcomes may be prohibitive. With a fixed number of randomized patients, the efficiency of testing certain treatments parameters, including the treatment effect among biomarker-positive patients and the interaction between treatment and biomarker, can be improved by increasing the proportion of biomarker positives on study, especially when the prevalence rate of biomarker positives is low in the underlying patient population. When the cost of assessing the true biomarker is prohibitive, one can further improve the study efficiency by oversampling biomarker positives with a cheaper auxiliary variable or a surrogate biomarker that correlates with the true biomarker. To improve efficiency and reduce cost, we can adopt an enrichment strategy for both scenarios by concentrating on testing and treating patient subgroups that contain more information about specific treatment parameters of primary interest to the investigators. In the first scenario, an enriched biomarker stratified design enriches the cohort of randomized patients by directly oversampling the relevant patients with the true biomarker, while in the second scenario, an auxiliary-variable-enriched biomarker stratified design enriches the randomized cohort based on an inexpensive auxiliary variable, thereby avoiding testing the true biomarker on all screened patients and reducing treatment waiting time. For both designs, we discuss how to choose the optimal enrichment proportion when testing a single hypothesis or two hypotheses simultaneously. At a requisite power, we compare the two new designs with the BSD design in terms of the number of randomized patients and the cost of trial under scenarios mimicking real biomarker stratified trials. The new designs are illustrated with hypothetical examples for designing biomarker-driven cancer trials.

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Blood protein predictors of brain amyloid for enrichment in clinical trials?

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Blood protein predictors of brain amyloid for enrichment in clinical trials?

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