Synaptic proteins in neuron-derived extracellular vesicles as biomarkers for Alzheimer's disease: novel methodology and clinical proof of concept

Abstract

Aims: Blood biomarkers can improve drug development for Alzheimer's disease (AD) and its treatment. Neuron-derived extracellular vesicles (NDEVs) in plasma offer a minimally invasive platform for developing novel biomarkers that may be used to monitor the diverse pathogenic processes involved in AD. However, NDEVs comprise only a minor fraction of circulating extracellular vesicles (EVs). Most published studies have leveraged the L1 cell adhesion molecule (L1CAM) for NDEV immunocapture. We aimed to develop and optimize an alternative, highly specific immunoaffinity method to enrich blood NDEVs for biomarker development.

Methods: After screening multiple neuronal antigens, we achieved NDEV capture with high affinity and specificity using antibodies against Growth-Associated Protein (GAP) 43 and Neuroligin 3 (NLGN3). The EV identity of the captured material was confirmed by electron microscopy, western blotting, and proteomics. The specificity for neuronal origin was demonstrated by showing enrichment for neuronal markers (proteins, mRNA) and recovery of spiked neuronal EVs. We performed NDEV isolation retrospectively from plasma samples from two cohorts of early AD patients (N = 19 and N = 40) and controls (N = 20 and N = 19) and measured p181-Tau, amyloid-beta (Aβ) 42, brain-derived neurotrophic factor (BDNF), precursor brain-derived neurotrophic factor (proBDNF), glutamate receptor 2 (GluR2), postsynaptic density protein (PSD) 95, GAP43, and syntaxin-1.

Results: p181-Tau, Aβ42, and NRGN were elevated in AD samples, whereas proBDNF, GluR2, PSD95, GAP43, and Syntaxin-1 were reduced. Differences for p181-Tau, proBDNF, and GluR2 survived multiple-comparison correction and were correlated with cognitive scores. A model incorporating biomarkers correctly classified 94.7% of AD participants and 61.5% of control participants. The observed differences in NDEVs-associated biomarkers are consistent with previous findings.

Conclusion: NDEV isolation by GAP43 and NLGN3 immunocapture offers a robust novel platform for biomarker development in AD, suitable for large-scale validation.

Keywords: Alzheimer’s disease; Biomarkers; exosomes; neuron-derived exosomes.

Figure 1

NDEV isolation and characterization. The isolated NDEVs demonstrate key EV characteristics. (A) NDEVs were eluted from ExoSORT capture beads, fixed in 3% PFA, and visualized by transmission electron microscopy. Vesicular shape and size under 200 nm were observed. (B) The size distribution of eluted NDEVs was determined by nanoparticle tracking analysis. The NDEVs average diameter ± SEM was 127 ± 72 nm. (C) Western blot analysis (WES instrument) showed that NDEVs (N) contained enriched levels of typical EVs markers CD9 and FLOT1, and reduced levels of albumin, compared to unprocessed plasma (P). Mouse brain extract (B) was used as a control. Total protein loaded (ug) is shown for each lane. (D, E) Levels of albumin and ApoA1 were much lower in isolated NDEVs than in unprocessed plasma, as quantified by ELISA (R&D Systems, Cat. No. DY1455 and DY366405). The fractions of albumin and ApoA1 in NDEVs were 0.78 ± 0.2% and 4.05 ± 0.94% of the levels observed in unprocessed plasma, respectively (P < 0.0001 for both proteins). (F, G) The enrichment for neuronal material was ascertained by comparing neuron-specific proteins and RNA in plasma and NDEVs. (F) WES analysis showed that NDEVs (lanes labeled N) are enriched for neuronal markers NeuN and GluR2 compared to unprocessed plasma (lanes labeled P). Protein amounts loaded onto each lane are shown above. (G) mRNA encoding markers of EV origin from erythrocytes (hemoglobin, HBB), platelets (platelet factor 4, PF4), liver (albumin, ALB), and neurons (neurogranin, NRGN) were measured by QPCR in plasma and NDEVs. The resultant values were adjusted to the input volume. Note that there were lower levels of HBB, PF4, and ALB mRNA in NDEVs compared to plasma (1,4, 34, and 68-fold, respectively; P < 0.0001 for all comparisons). In contrast, NRGN mRNA levels were similar between NDEVs and plasma (P = 0.66).

Figure 2

Efficiency and precision of NDEV isolation. (A) NDEV isolation was performed on unprocessed plasma samples (Round 1, N = 4, aliquoted from the same plasma pool). After the first round of ExoSORT, supernatants were retained and subjected to an additional round of capture with fresh ExoSORT beads (Rounds 2 and 3, see Supplementary Figure 3). NRGN mRNA was measured by TaqMan QPCR. Ct values are shown. (B) Tau-rich EVs generated by iPSC-derived neurons were spiked into plasma aliquots. The recovery of spiked NDEVs in three consecutive rounds of ExoSORT was measured as above, and residual NDEV amounts after each round were estimated. Fold change differences between initial plasma pools (Round 1) and the two consecutive rounds are shown (Rounds 2 and 3). The signals in Rounds 2 and 3 were 8.7 ± 5.5% and 0.02 ± 0.01% in Round 1, respectively. (C) EVs isolated from a culture of human iPSC-differentiated cortical neurons were spiked into 300 ml plasma aliquots in 4 different concentrations based on known amounts of Tau. EV recovery was calculated by the following formula: Tau recovery after ExoSORT remained uniform for a range of spiked-in EV-associated Tau amounts and was much higher than with IgG control (P = 0.026, two-way ANOVA). (D) Identical EV amounts from a culture of human iPSC-differentiated cortical neurons were spiked into plasma samples from 11 healthy individuals and six dementia patients. The variability of recovery was < 13% for all samples, with no difference between groups (P = 0.6). (E-G) Five different ExoSORT procedures were performed on different days, using aliquots derived from the same two plasma samples (QC1 and QC2, respectively). The levels of p181-Tau, total-tau, and Aβ42 were measured in the same assay (Luminex-based Milliplex), yielding variability estimates of 20.3%, 22.7%, and 14.9% for p181-Tau, Tau, and Aβ42, respectively. (H) ExoSORT was performed in triplicate technical replicates by two operators on plasma from 4 distinct donors, and the results were compared using Tau levels as an output. We note similar variations between donors and similar levels determined by different operators for each donor (P = 0.83).

Figure 3

p181-Tau and Aβ42 in NDEVs in three cohorts. The levels of p181-Tau, total Tau, and Aβ42 were measured in three cohorts of early-stage AD patients and control donors. (A, B) NDEVs-associated p181-Tau and Aβ42 were measured by a Milliplex assay in the BioIVT cohort (N = 10 per group, P = 0.007 and P < 0.0001, respectively). (C, D) Different aliquots of the same 20 plasma samples from the BioIVT cohort were analyzed again at a later date to assess the correlation between the two measurements (R² = 0.93, P < 0.01 and R² = 0.55, P < 0.002, respectively). (E, F) p181-Tau measurements were conducted in NDEVs derived from NIA samples (20 early AD and 19 controls, P < 0.0001) and PMED samples (30 early AD and 9 controls, P = 0.02). (G, H) NDEVs-associated Aβ42 was measured by Luminex in the NIA and PMED cohorts, and significant differences were detected between the disease and control groups (P = 0.01 and P = 0.001, respectively).

Figure 4

NDEVs and their source plasma samples were used to measure BDNF and proBDNF in early AD and control donors. (A) Measurements in the BioIVT cohort showed high enrichment of proBDNF levels in NDEVs (P < 0.001) compared to unprocessed plasma. Moreover, we observed lower levels of NDEVs-associated proBDNF in early AD compared to control individuals (P = 0.002), while no difference was observed in unprocessed plasma. (B) BDNF was 2.6-fold lower in NDEVs than in plasma (P < 0.01) and did not vary between AD and controls. (C) ProBDNF measurements in two independently stored aliquots from 20 samples showed a moderately strong correlation (R² =0.7, P < 0.0001). (D, E) NDEVs-associated proBDNF was measured in two additional cohorts from NIA and PMED; the decrease in NDEVs-associated proBDNF in early AD compared to control individuals was reproduced in the NIA cohort (P = 0.001), while the PMED cohort generated a similar trend that did not reach statistical significance (P = 0.09), potentially due to an insufficient number of control samples.

Figure 5

The levels of five synaptic proteins, NRGN, GAP43, PSD95, Syntaxin-1, and GluR2, were measured in three independent cohorts. (A-I) NDEVs-associated NRGN, GAP43, PSD95, Syntaxin-1, and GluR2 were measured in the NIA cohort (20 AD and 19 controls; NRGN: P = 0.025, GAP43: P < 0.001, PSD95: P = 002, Syntaxin-1: P = 0.011, and GluR2: P < 0.001). (B-J) The same proteins were measured in the combined BioIVT/PMED cohort (40 AD and 19 controls total), NRGN: P = 0.087, GAP43: P = 0.063, PSD95: P = 0.2, Syntaxin-1: P = 0.03 and GluR2: P < 0.001). (K) ROC analysis was conducted for all three cohorts combined. Each line corresponds to a different NDEV biomarker; higher values indicate AD/MCI, and lower values indicate CN Control status.