The accuracy and robustness of plasma biomarker models for amyloid PET positivity

Abstract

Background Plasma biomarkers for Alzheimer’s disease (AD) have broad potential as screening tools in primary care and disease-modifying trials. Detecting elevated amyloid-β (Aβ) pathology to support trial recruitment or initiating Aβ-targeting treatments would be of critical value. In this study, we aimed to examine the robustness of plasma biomarkers to detect elevated Aβ pathology at different stages of the AD continuum. Beyond determining the best biomarker—or biomarker combination—for detecting this outcome, we also simulated increases in inter-assay coefficient of variability (CV) to account for external factors not considered by intra-assay variability. With this, we aimed to determine whether plasma biomarkers would maintain their accuracy if applied in a setting which anticipates higher variability (i.e., clinical routine). Methods We included 118 participants (cognitively unimpaired [CU, n = 50], cognitively impaired [CI, n = 68]) from the ADNI study with a full plasma biomarker profile (Aβ42/40, GFAP, p-tau181, NfL) and matched amyloid imaging. Initially, we investigated how simulated CV variations impacted single-biomarker discriminative performance of amyloid status. Then, we evaluated the predictive performance of models containing different biomarker combinations, based both on original and simulated measurements. Plasma Aβ42/40 was represented by both immunoprecipitation mass spectrometry (IP-MS) and single molecule array (Simoa) methods in separate analyses. Model selection was based on a decision tree which incorporated Akaike information criterion value, likelihood ratio tests between the best-fitting models and, finally, and Schwartz’s Bayesian information criterion. Results Increasing variation greatly impacted the performance of plasma Aβ42/40 in discriminating Aβ status. In contrast, the performance of plasma GFAP and p-tau181 remained stable with variations >20%. When biomarker models were compared, the models “AG” (Aβ42/40 + GFAP; AUC = 86.5), “A” (Aβ42/40; AUC = 82.3), and “AGP” (Aβ42/40 + GFAP + p-tau181; AUC = 93.5) were superior in determining Aβ burden in all participants, within-CU, and within-CI groups, respectively. In the robustness analyses, when repeating model selection based on simulated measurements, models including IP-MS Aβ42/40 were also most often selected. Simoa Aβ42/40 did not contribute to any selected model when used as an immunoanalytical alternative to IP-MS Aβ42/40. Conclusions Plasma Aβ42/40, as quantified by IP-MS, shows high performance in determining Aβ positivity at all stages of the AD continuum, with GFAP and p-tau181 further contributing at CI stage. However, between-assay variations greatly impacted the performance of Aβ42/40 but not that of GFAP and p-tau181. Therefore, when dealing with between-assay CVs that exceed 5%, plasma GFAP and p-tau181 should be considered for a more robust determination of Aβ burden in CU and CI participants, respectively.

Blood phospho-tau in Alzheimer disease: analysis, interpretation, and clinical utility

“…Plasma Aβ1-42:Aβ1-40 ratio measured with IP-MS is another high-performing blood biomarker for Aβ pathology 139,140 . However, in re-analysis of previously-published datasets this marker showed small changes (10%) between PET Aβ-positive individuals and Aβ-negative individuals (compared with 37.7% for CSF Aβ1-42:Aβ1-40 ratio in the same set of participants who had paired CSF and plasma samples available) as also demonstrated before in several independent studies [139][140][141][142] . This small change in plasma Aβ1-42:Aβ1-40 ratios between Aβ-PET-positive and Aβ-PET-negative individuals (representing approximately a quarter of the fold change seen for CSF) leads to large overlaps that are susceptible to minor analytical variations, as demonstrated recently 141 .…”

“…However, in re-analysis of previously-published datasets this marker showed small changes (10%) between PET Aβ-positive individuals and Aβ-negative individuals (compared with 37.7% for CSF Aβ1-42:Aβ1-40 ratio in the same set of participants who had paired CSF and plasma samples available) as also demonstrated before in several independent studies [139][140][141][142] . This small change in plasma Aβ1-42:Aβ1-40 ratios between Aβ-PET-positive and Aβ-PET-negative individuals (representing approximately a quarter of the fold change seen for CSF) leads to large overlaps that are susceptible to minor analytical variations, as demonstrated recently 141 . Conversely, the fold changes of CSF and plasma p-tau231 between PET Aβ-positive and Aβ-negative individuals were more comparable (166% for CSF p-tau231 versus 85.6% for plasma p-tau231, meaning that the fold change in CSF is only reduced by half in plasma).…”

“…Conversely, the fold changes of CSF and plasma p-tau231 between PET Aβ-positive and Aβ-negative individuals were more comparable (166% for CSF p-tau231 versus 85.6% for plasma p-tau231, meaning that the fold change in CSF is only reduced by half in plasma). This limits the susceptibility of plasma p-tau231 to small technical variations 141 . Box 4 illustrates robustness of Aβ1-42:Aβ1-40 ratio and p-tau measured in CSF versus plasma to predict Aβ-PET positivity.…”

The Alzheimer's Association Appropriate Use Recommendations for Blood Biomarkers in Alzheimer’s Disease

“…4,15 The likely explanation is that the Aβ pathology-related reduction in plasma Aβ42/Aβ40 occurs on top of peripherally present Aβ, because Aβ produced in extracerebral tissues are conceivably not affected by brain Aβ pathology. Consequently, plasma Aβ42/Aβ40 is a less robust brain Aβ pathology biomarker than CSF Aβ42/Aβ40 for biological reasons 16. It is challenging to standardize and maintain stability of this type of test over time in clinical laboratory practice with the rigor needed to reliably detect the small difference between Aβ-positive and -negative individuals.…”

Discernment of cerebral amyloid and cognitive status using ultrasensitive blood biomarkers collected with a non-traditional anticoagulant

“…We did not have access to plasma GFAP for the cognitively impaired group, and thus were unable to examine the predictive capacity of plasma GFAP for discriminating diagnosis. Other work has found Simoa-measured plasma GFAP alone to be the best predictor for amyloid status in their sample overall, as well for within the unimpaired group alone (total sample, AUC = 0.775; unimpaired alone, AUC = 0.728) 43 . However, for the impaired group in this study, a combination of plasma GFAP and pTau-181 best predicted amyloid status (AUC = 0.871).…”