Profiling of plasma biomarkers in the context of memory assessment in a tertiary memory clinic

Quantification of blood glial fibrillary acidic protein using a second-generation microfluidic assay. Validation and comparative analysis with two established assays

OBJECTIVES

Increased levels of glial fibrillary acidic protein (GFAP) in blood have been identified as a valuable biomarker for some neurological disorders, such as Alzheimer's disease and multiple sclerosis. However, most blood GFAP quantifications so far were performed using the same bead-based assay, and to date a routine clinical application is lacking.

METHODS

In this study, we validated a novel second-generation (2nd gen) Ella assay to quantify serum GFAP. Furthermore, we compared its performance with a bead-based single molecule array (Simoa) and a homemade GFAP assay in a clinical cohort of neurological diseases, including 210 patients.

RESULTS

Validation experiments resulted in an intra-assay variation of 10 %, an inter-assay of 12 %, a limit of detection of 0.9 pg/mL, a lower limit of quantification of 2.8 pg/mL, and less than 20 % variation in serum samples exposed to up to five freeze-thaw cycles, 120 h at 4 °C and room temperature. Measurement of the clinical cohort using all assays revealed the same pattern of GFAP distribution in the different diagnostic groups. Moreover, we observed a strong correlation between the 2nd gen Ella and Simoa (r=0.91 (95 % CI: 0.88-0.93), p<0.0001) and the homemade immunoassay (r=0.77 (95 % CI: 0.70-0.82), p<0.0001).

CONCLUSIONS

Our results demonstrate a high reliability, precision and reproducibility of the 2nd gen Ella assay. Although a higher assay sensitivity for Simoa was observed, the new microfluidic assay might have the potential to be used for GFAP analysis in daily clinical workups due to its robustness and ease of use.

Real-world performance of plasma p-tau181 in a heterogeneous memory clinic cohort

OBJECTIVE

In light of clinical trials and disease-modifying therapies, an early identification of patients at-risk of developing Alzheimer's disease (AD) is crucial. Blood-based biomarkers have shown promising results regarding the in vivo detection of the earliest neuropathological changes in AD. Herein, we investigated the ability of plasma p-tau181 to act as a prescreening marker for amyloid positivity in a heterogeneous memory clinic-based cohort.

METHODS

In this retrospective cross-sectional study, we included a total of 115 patients along the clinical AD continuum (mild cognitive impairment [MCI] due to AD, n = 62, probable AD dementia, n = 53). Based on their biomarker status, they were stratified into an amyloid-positive (Aβ+, n = 88) or amyloid-negative cohort (Aβ-, n = 27). Plasma and CSF p-tau181 concentrations were quantified using an ultrasensitive single-molecule array (SIMOA©). Furthermore, age- and sex-adjusted receiver operating characteristic (ROC) curves were calculated and the area under the curve (AUC) of each model was compared using DeLong's test for correlated AUC curves.

RESULTS

The median (interquartile range [IQR]) concentration of plasma p-tau181 was significantly higher in Aβ+ patients (3.6 pg/mL [2.5-4.6]), compared with Aβ- patients (1.7 pg/mL [1.2-1.9], p < 0.001). Regarding the distinction between Aβ+ and Aβ- patients and the prediction of amyloid positivity, a high diagnostic accuracy for plasma p-tau181 with an AUC of 0.89 (95% CI = 0.82-0.95) was calculated. Adding the risk factors, age and APOE4, to the model did not significantly improve its performance.

INTERPRETATION

Our findings demonstrate that plasma p-tau181 could be a noninvasive and feasible prescreening marker for amyloid positivity in a heterogeneous clinical AD cohort and therefore help in identifying those who would benefit from more invasive assessment of amyloid pathology.

Moving Beyond Depression: Mood Symptoms Across the Spectrum Relate to Tau Pathology in Older Women at Risk for Alzheimer's Disease

We examined how symptoms across the mood spectrum relate to Alzheimer's disease (AD) biomarkers in older women at high risk for AD. Participants included 25 women aged 65+ with mild cognitive deficits and elevated AD genetic risk. The Profile of Mood States Questionnaire measured mood symptoms and a total mood disturbance (TMD) score. Tau burden in the meta-temporal region of interest was measured using MK-6240 Tau positron emission tomography (PET) imaging. A subset (n = 12) also had p-Tau181, and Aß40/42 levels measured in plasma. Higher TMD scores related to higher tau PET standardized uptake value ratio (SUVR). Greater negative mood symptoms correlated with higher tau PET SUVR, while greater vigor correlated with lower SUVR. Similar results were seen with plasma p-Tau181 levels, but not with Aβ40/42 levels. In conclusion, positive and negative mood symptoms related to tau pathology in older women at high risk for AD, highlighting a role of mental well-being in AD risk.

Towards early diagnosis of Alzheimer's disease: advances in immune-related blood biomarkers and computational approaches

Alzheimer's disease has an increasing prevalence in the population world-wide, yet current diagnostic methods based on recommended biomarkers are only available in specialized clinics. Due to these circumstances, Alzheimer's disease is usually diagnosed late, which contrasts with the currently available treatment options that are only effective for patients at an early stage. Blood-based biomarkers could fill in the gap of easily accessible and low-cost methods for early diagnosis of the disease. In particular, immune-based blood-biomarkers might be a promising option, given the recently discovered cross-talk of immune cells of the central nervous system with those in the peripheral immune system. Here, we give a background on recent advances in research on brain-immune system cross-talk in Alzheimer's disease and review machine learning approaches, which can combine multiple biomarkers with further information (e.g. age, sex, APOE genotype) into predictive models supporting an earlier diagnosis. In addition, mechanistic modeling approaches, such as agent-based modeling open the possibility to model and analyze cell dynamics over time. This review aims to provide an overview of the current state of immune-system related blood-based biomarkers and their potential for the early diagnosis of Alzheimer's disease.

Tracking reactive astrogliosis in autosomal dominant and sporadic Alzheimer's disease with multi-modal PET and plasma GFAP

BACKGROUND

Plasma assays for the detection of Alzheimer's disease neuropathological changes are receiving ever increasing interest. The concentration of plasma glial fibrillary acidic protein (GFAP) has been suggested as a potential marker of astrocytes or recently, amyloid-β burden, although this hypothesis remains unproven. We compared plasma GFAP levels with the astrocyte tracer 11C-Deuterium-L-Deprenyl (11C-DED) in a multi-modal PET design in participants with sporadic and Autosomal Dominant Alzheimer's disease.

METHODS

Twenty-four individuals from families with known Autosomal Dominant Alzheimer's Disease mutations (mutation carriers = 10; non-carriers = 14) and fifteen patients with sporadic Alzheimer's disease were included. The individuals underwent PET imaging with 11C-DED, 11C-PIB and 18F-FDG, as markers of reactive astrogliosis, amyloid-β deposition, and glucose metabolism, respectively, and plasma sampling for measuring GFAP concentrations. Twenty-one participants from the Autosomal Dominant Alzheimer's Disease group underwent follow-up plasma sampling and ten of these participants underwent follow-up PET imaging.

RESULTS

In mutation carriers, plasma GFAP levels and 11C-PIB binding increased, while 11C-DED binding and 18F-FDG uptake significantly decreased across the estimated years to symptom onset. Cross-sectionally, plasma GFAP demonstrated a negative correlation with 11C-DED binding in both mutation carriers and patients with sporadic disease. Plasma GFAP indicated cross-sectionally a significant positive correlation with 11C-PIB binding and a significant negative correlation with 18F-FDG in the whole sample. The longitudinal levels of 11C-DED binding showed a significant negative correlation with longitudinal plasma GFAP concentrations over the follow-up interval.

CONCLUSIONS

Plasma GFAP concentration and astrocyte 11C-DED brain binding levels followed divergent trajectories and may reflect different underlying processes. The strong negative association between plasma GFAP and 11C-DED binding in Autosomal Dominant and sporadic Alzheimer's disease brains may indicate that if both are markers of reactive astrogliosis, they may detect different states or subtypes of astrogliosis. Increased 11C-DED brain binding seems to be an earlier phenomenon in Alzheimer's disease progression than increased plasma GFAP concentration.