Longitudinal evaluation of the natural history of amyloid-β in plasma and brain

Abstract

Plasma amyloid-β peptide concentration has recently been shown to have high accuracy to predict amyloid-β plaque burden in the brain. These amyloid-β plasma markers will allow wider screening of the population and simplify and reduce screening costs for therapeutic trials in Alzheimer’s disease. The aim of this study was to determine how longitudinal changes in blood amyloid-β track with changes in brain amyloid-β. Australian Imaging, Biomarker and Lifestyle study participants with a minimum of two assessments were evaluated (111 cognitively normal, 7 mild cognitively impaired, 15 participants with Alzheimer’s disease). Amyloid-β burden in the brain was evaluated through PET and was expressed in Centiloids. Total protein amyloid-β 42/40 plasma ratios were determined using ABtest® assays. We applied our method for obtaining natural history trajectories from short term data to measures of total protein amyloid-β 42/40 plasma ratios and PET amyloid-β. The natural history trajectory of total protein amyloid-β 42/40 plasma ratios appears to approximately mirror that of PET amyloid-β, with both spanning decades. Rates of change of 7.9% and 8.8%, were observed for total protein amyloid-β 42/40 plasma ratios and PET amyloid-β, respectively. The trajectory of plasma amyloid-β preceded that of brain amyloid-β by a median value of 6 years (significant at 88% confidence interval). These findings, showing the tight association between changes in plasma and brain amyloid-β, support the use of plasma total protein amyloid-β 42/40 plasma ratios as a surrogate marker of brain amyloid-β. Also, that plasma total protein amyloid-β 42/40 plasma ratios has potential utility in monitoring trial participants, and as an outcome measure.

Blood Derived Amyloid Biomarkers for Alzheimer’s Disease Prevention

“…We found significantly lower plasma Aβ42/Aβ40 in amyloid PET-positive CU study participants with two MS based (IP-MS:WashU and IP-MALDI-TOF-MS:Shimadzu) and two IA (IA:Quanterix and IA:Roche) platforms. These results corroborate findings from other studies that have reported lower plasma Aβ42/Aβ40 in PET-positive cognitively normal older adults using MS based (11) and IA assays (6). Compared to CSF, where Aβ42/Aβ40 ratio difference between PET-positive to negative could be up to 50% (25), the differences seen with the plasma levels are quite small (7-12%).…”

“…Recent advancements in the biochemical assays of Aβ in blood-based biofluids (serum, plasma) via ultra-sensitive immunoassays (IA) and targeted massspectrometry (MS) have engendered remarkable Aβ blood tests with proven accuracy for detecting brain amyloid pathological status, as confirmed via PET or CSF (6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16); discriminating AD from cognitive normal status (15), as well as predicting cognitive decline (6,17) and clinical progression (18); alluding to high potential for clinical use. Of the variations of amyloid protein, including precursors and independent Aβ isoform types investigated, plasma Aβ42/Aβ40 ratio has been shown to reliably predict abnormal cerebral amyloid deposition in non-demented older adults, with the MS based platforms shown to provide the most robust results of AUCs reported up to 0.88 (11,19) also in a recent multicohort head-to-head comparison of multiple platforms (8).…”

Fifteen Years of the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study: Progress and Observations from 2,359 Older Adults Spanning the Spectrum from Cognitive Normality to Alzheimer’s Disease

“…We also explored levels of ApoE [90], ApoJ [91], inflammatory markers [92], and micro-RNA [93]. New A␤ immunoassays showed improved performances [94][95][96] but the combination of immunoprecipitation and mass spectrometry proved to have exceptional performance [97], equivalent to CSF assays. Notably, measurement of the natural history of plasma A␤ change, via one of the new immunoassays, suggests that the trajectory of plasma A␤ change mirrors brain A␤-amyloid accumulation as measured by PET, with a rapid phase of plasma change observable up to 6 years prior to the rapid phase of brain A␤-amyloid accumulation [96].…”

“…New A␤ immunoassays showed improved performances [94][95][96] but the combination of immunoprecipitation and mass spectrometry proved to have exceptional performance [97], equivalent to CSF assays. Notably, measurement of the natural history of plasma A␤ change, via one of the new immunoassays, suggests that the trajectory of plasma A␤ change mirrors brain A␤-amyloid accumulation as measured by PET, with a rapid phase of plasma change observable up to 6 years prior to the rapid phase of brain A␤-amyloid accumulation [96]. CSF and plasma A␤ 42 are in equilibrium, and are expected to show changes earlier than A␤-PET since the dynamic range of CSF change is greatest at the lower ranges of A␤-PET.…”

Simulating the outcome of amyloid treatments in Alzheimer’s disease from imaging and clinical data

“…Within this context, quantitative models of disease progression, Disease progression Models referred to as DPMs, have been proposed (Fonteijn et al, 2012; Jedynak et al, 2012; Nader et al, 2020; Oxtoby et al, 2017; Schiratti et al, 2015), to quantify the dynamics of the changes affecting the brain during the whole disease span. These models rely on the statistical analysis of large datasets of different data modalities, such as clinical scores, or brain imaging measures derived from MRI, Amyloid-and Fluorodeoxyglucose-PET (Bilgel et al, 2015; Burnham et al, 2020; Donohue et al, 2014; Y Iturria-Medina et al, 2016; Koval et al, 2018). In general, DPMs estimate a long-term disease evolution from the joint analysis of multivariate time-series acquired on a short-term time-scale.…”