Plasma amyloid-beta (A beta) has long been investigated as a blood biomarker candidate for Cerebral Amyloid Angiopathy (CAA), however previous findings have been inconsistent which could be... Show morePlasma amyloid-beta (A beta) has long been investigated as a blood biomarker candidate for Cerebral Amyloid Angiopathy (CAA), however previous findings have been inconsistent which could be attributed to the use of less sensitive assays. This study investigates plasma A beta alterations between pre-symptomatic Dutch-type hereditary CAA (D-CAA) mutation-carriers (MC) and non-carriers (NC) using two A beta measurement platforms. Seventeen pre-symptomatic members of a D-CAA pedigree were assembled and followed up 3-4 years later (NC = 8; MC = 9). Plasma A beta 1-40 and A beta 1-42 were cross-sectionally and longitudinally analysed at baseline (T1) and follow-up (T2) and were found to be lower in MCs compared to NCs, cross-sectionally after adjusting for covariates, at both T1(A beta 1-40: p = 0.001; A beta 1-42: p = 0.0004) and T2 (A beta 1-40: p = 0.001; A beta 1-42: p = 0.016) employing the Single Molecule Array (Simoa) platform, however no significant differences were observed using the xMAP platform. Further, pairwise longitudinal analyses of plasma A beta 1-40 revealed decreased levels in MCs using data from the Simoa platform (p = 0.041) and pairwise longitudinal analyses of plasma A beta 1-42 revealed decreased levels in MCs using data from the xMAP platform (p = 0.041). Findings from the Simoa platform suggest that plasma A beta may add value to a panel of biomarkers for the diagnosis of pre-symptomatic CAA, however, further validation studies in larger sample sets are required. Show less
Chatterjee, P.; Fagan, A.M.; Xiong, C.J.; McKay, M.; Bhatnagar, A.; Wu, Y.Q.; ... ; Dominantly Inherited Alzheimer Net 2021
Objective: Investigation of pre-symptomatic CAA related blood metabolite alterations in Dutch-type hereditary CAA mutation carriers (D-CAA MCs).Methods: Plasma metabolites were measured using mass... Show moreObjective: Investigation of pre-symptomatic CAA related blood metabolite alterations in Dutch-type hereditary CAA mutation carriers (D-CAA MCs).Methods: Plasma metabolites were measured using mass-spectrometry (AbsoluteIDQ (R) p400 HR kit) and were compared between pre-symptomatic D-CAA MCs (n= 9) and non-carriers (D-CAA NCs, n= 8) from the same pedigree. Metabolites that survived correction for multiple comparisons were further compared between D-CAA MCs and additional control groups (cognitively unimpaired adults).Results: 275 metabolites were measured in the plasma, 22 of which were observed to be significantly lower in the D-CAA MCs compared to D-CAA NCs, following adjustment for potential confounding factors age, sex, and APOE epsilon 4 (p < 00.05). After adjusting for multiple comparisons, only spermidine remained significantly lower in the D-CAA MCs compared to the D-CAA NCs (p < 0.00018). Plasma spermidine was also significantly lower in D-CAA MCs compared to the cognitively unimpaired young adult and older adult groups (p < 0.01). Spermidine was also observed to correlate with CSF A beta(40) (r(s) = 0.621, p = 0.024), CSF A beta(42) (r(s) = 0.714, p = 0.006), and brain A beta load (r(s) = -0.527, p = 0.030).Conclusion: The current study provides pilot data on D-CAA linked metabolite signals, that also associated with A beta neuropathology and are involved in several biological pathways that have previously been linked to neurodegeneration and dementia. Show less
Schultz, A.P.; Kloet, R.W.; Sohrabi, H.R.; Weerd, L. van der; Rooden, S. van; Wermer, M.J.H.; ... ; Dominantly Inherited Alzheimer N 2019
It is increasingly recognized that Alzheimer’s disease (AD) exists before dementia is present and that shifts in amyloid beta occur long before clinical symptoms can be detected. Early detection of... Show moreIt is increasingly recognized that Alzheimer’s disease (AD) exists before dementia is present and that shifts in amyloid beta occur long before clinical symptoms can be detected. Early detection of these molecular changes is a key aspect for the success of interventions aimed at slowing down rates of cognitive decline. Recent evidence indicates that of the two established methods for measuring amyloid, a decrease in cerebrospinal fluid (CSF) amyloid β1−42 (Aβ1−42) may be an earlier indicator of Alzheimer’s disease risk than measures of amyloid obtained from Positron Emission Tomography (PET). However, CSF collection is highly invasive and expensive. In contrast, blood collection is routinely performed, minimally invasive and cheap. In this work, we develop a blood-based signature that can provide a cheap and minimally invasive estimation of an individual’s CSF amyloid status using a machine learning approach. We show that a Random Forest model derived from plasma analytes can accurately predict subjects as having abnormal (low) CSF Aβ1−42 levels indicative of AD risk (0.84 AUC, 0.78 sensitivity, and 0.73 specificity). Refinement of the modeling indicates that only APOEε4 carrier status and four plasma analytes (CGA, Aβ1−42, Eotaxin 3, APOE) are required to achieve a high level of accuracy. Furthermore, we show across an independent validation cohort that individuals with predicted abnormal CSF Aβ1−42 levels transitioned to an AD diagnosis over 120 months significantly faster than those with predicted normal CSF Aβ1−42 levels and that the resulting model also validates reasonably across PET Aβ1−42 status (0.78 AUC). This is the first study to show that a machine learning approach, using plasma protein levels, age and APOEε4 carrier status, is able to predict CSF Aβ1−42 status, the earliest risk indicator for AD, with high accuracy. Show less
