Alzheimer’s dementia (AD) is the most common form of dementia, making up 60 to 80% of all cases [1
], with a global prevalence of over 50 million by 2019 and an expected increase to 152 million by 2050 [2
]. Current diagnostic methods include positron emission tomography scans and changes of amyloid-β (Aβ) and tau in the cerebrospinal fluid (CSF). However, insufficient accessibility for general practitioners, invasiveness, and high cost limit the usefulness of these methods [3
]. Therefore, a reliable blood-based biomarker could be desirable. Biological pathways, such as systemic or inflammatory reactions are also implicated in AD pathogenesis, and e.g., a higher ApoE expression causes a higher systemic inflammation level, in addition to an increased vascular Aβ deposition [4
]. Breakdown of the blood–brain barrier (BBB) is thought to occur as an early event of the AD pathogenesis leading to presence of proteins associated with neurodegeneration which may be reflected in blood [6
], and the same applies for markers of potential endothelial damage in AD [7
]. However, the complex composition of blood, complicates the detection of low abundant proteins [8
Extracellular vesicles (EVs) denote a heterogeneous group of particles with a double lipid-layer membrane, which are released from cells in an evolutionary conserved manner. The two major groups of EVs are exosomes (50–150 nm) and microvesicles (100–1000 nm). During biogenesis EVs are loaded with various proteins, lipids, and miRNAs, implying that their composition potentially mirrors the physiological state of their parental cell [9
]. EVs are considered rich sources for disease biomarkers, which has related them to the term “liquid biopsies” [10
]. Studies have also shown that these entities are released by neurons, astrocytes, oligodendrocytes, and other cell types of the central nervous system (CNS) [11
], and that they are able to cross the BBB with subsequent appearance in the circulation [13
]. EVs occurring in plasma have been associated with various phenomena related to AD pathology, including synaptic dysfunction [14
], dysregulation of neuronal differentiation, proliferation, and survival [15
], complement activation [16
], and vascular complications [17
]. EVs have also been implicated in the spreading [19
] or clearing [21
] of the accumulating neurotoxic proteins Aβ and tau.
Discovery-based studies require large-scale measurements of multiple proteins based on methods like mass spectrometry, immunological methods, or combinations thereof. A variety of the mentioned methods have previously been used in studies of AD for investigating markers of disease in both plasma [23
] and EVs [13
] although often with conflicting results. Mass spectrometry is biased towards abundant proteins, making detection of low abundant proteins a challenge [27
]. A novel method, proximity extension assay (PEA), combines immunological detection with quantitative polymerase chain reaction (qPCR). By this combination, a substantial scalability, sensitivity, and specificity can be achieved [28
], where relative quantification of multiple proteins is possible. In addition, whereas many methods may require a considerable amount of sample material, PEA only requires a diminutive sample volume of as little as 1 μL [29
], to detect as many as 92 proteins simultaneously.
Therefore, the aim of this study was to investigate the levels of plasma and EV-derived proteins from patients with AD and Mild Cognitive Impairment (MCI) and to compare these with protein levels to that of healthy individuals. Our working hypothesis was that there are differences in the levels of proteins involved in neurological and inflammatory processes among healthy and disease individuals, and that these differences can be measured by the PEA technique.
Using PEA, both plasma and EVs contained a panel of protein ratios able to distinguish healthy controls from AD patients. Furthermore, PEA analysis of EVs allowed for the identification of statistically significant protein signatures, providing additional disease relevant information not found in plasma.
In this study, we used PEA to examine protein profiles in plasma and EVs that could distinguish AD patients from healthy controls. Phenotypical and structural characterisation was performed and confirmed the enrichment of EVs. Several of the measured proteins were significantly different between patients and controls, and EV samples seemed to contain more differentially expressed proteins distinguishing the groups.
NTA and TEM confirmed the presence of particles within the size range of EVs according to literature [41
]. With respect to particle concentration and size, no significant differences were found between the three groups. Other studies have found increased levels of specific subpopulations of EVs in both CSF [41
] and plasma [17
] from AD patients, but NTA measures all particles and no specific subpopulations of EVs. AD patients presented with a significantly increased protein concentration in EV pellets compared to the other groups. Furthermore, EV enrichment was confirmed using the EV markers CD9 by western blot and IEM and ALIX by western blot.
Combining the Neurology and Inflammation panels for plasma and EVs separately, PLSDA determined a group of proteins in plasma and EVs, which could differentiate between the three groups. The PLSDAs provided a clear separation of the groups, with the EV samples containing the most significantly different proteins. Interestingly, when comparing controls with AD patients, five proteins; CLM-6, Contactin-5 (CNTN5), serine/threonine-protein kinase receptor R3 (SKR3), urokinase-type plasminogen activator (uPA), and TGF-α were expressed differently depending on sample material. This difference in expression could be due to the cargo selection mechanism during the biogenesis of EVs, which is currently not fully understood [10
]. As mentioned, there is an uncertainty to the clinical outcome of the MCI patients, which could also be observed in the PLSDAs, as MCI samples clustered in-between the AD and control groups. This was especially clear for the EV samples, where few MCI patients overlapped with controls and AD patients.
Our results indicated that EVs contained more proteins that were significantly different compared to that from plasma. Similar observations were made by Gidlöf et al. [43
], who compared plasma and EVs from patients with myocardial infarction to controls using PEA. EVs provided additional information that could not have been obtained with plasma alone [43
]. In our study, four neurology related proteins were significantly different in EVs after FDR correction; CD38, CLM-1, CLM-6, and Siglec-9, with these proteins being less expressed in disease groups. The proteins showed statistically significant difference between MCI patients and controls, whereas the difference was not significant between AD patients and healthy controls, even though the proteins were expressed similarly in the AD group compared to the MCI group. This could be due to a larger variation in the AD group and the limited sample size. Mice deficient in CD38 had decreased levels of Aβ, and treatment of neuronal cell cultures with CD38 inhibitors lead to decreased Aβ secretion [44
]. As we found decreased levels of CD38 in EVs for the cognitively affected, this could indicate a protective response. CLM-1 is an activating receptor participating in regulation of microglia [45
]. Absence of CLM-1 lead to increased pro-inflammatory cytokine and nitric oxide production, and demyelination [46
]. CLM-6 is an activator for monocytes [47
] and acts as an inhibitor for T cell proliferation and activation [48
]. As AD progresses, this could lead to a decreased expression of proteins with a protective function, which would agree with our findings, as we found decreased levels of these proteins for MCI and AD patients. To the author’s knowledge, no studies have reported any relation of Siglec-9 with AD. The functional murine equivalent to the human Siglec-9 is Siglec-E [49
]. Siglec-E is found expressed on microglia [49
], providing a protective effect by preventing phagocytosis of neural debris by microglia, thus reducing release of pro-inflammatory cytokines [51
]. If a similar protective function of Siglec-9 could be elucidated, it would be in agreement with our finding of a decreased expression of this protein in the disease groups. Furthermore, TGF-α and CCL11 from the Inflammation panel were significantly upregulated in plasma and EV samples, respectively, comparing AD patients with controls. A study investigating neuroinflammation found that the cytokine TGF-α produced by microglia inhibits the pathogenic activities of astrocytes and that expression of TGF-α correlated with severity in multiple sclerosis lesions [52
]. The chemokine CCL11 has been associated with ageing and neurodegeneration [53
] and proposed as a risk factor for AD [54
]. In agreement with the findings in our study, increased levels of CCL11 has been reported in CSF in vivo [54
]. Testing the diagnostic capabilities of the combined protein ratios from the PLSDA models and the FDR significant proteins proved that both sample matrices contained important information regarding biomarker candidates for comparison of healthy controls and patients with AD. Interestingly, for plasma and EVs, TGF-α and CCL11, respectively, were involved in most of the combined biomarker models. These proteins were also the only FDR corrected proteins found significant with the mentioned inclusion criteria for ROC curves.
The peripheral immune system has been shown to be implicated in AD pathology, with infiltration of immune cells, e.g., macrophages to aid microglia with phagocytosis of Aβ [55
], and cells of the immune system release EVs into the circulation [56
]. Several of the FDR significant proteins have also been associated with immune cells, some of them such as Siglec-9 with neutrophils and monocytes [57
], CLM-6 with monocytes and T cells [47
], and CLM-1 and CCL11 with eosinophils [53
]. This means that the observed expression of proteins in the current study could be due to a regulation of the peripheral immune system, as there is a cross talk between this and the CNS.
As indicated in the literature, these FDR significant proteins are involved in immunological processes and correlations showed that most of the expressions of these proteins were positively associated to each other, possibly indicating a functional association or response in regards to disease pathology. However, none of these proteins correlated with measured CRP levels. Neither, the two inflammatory proteins CCL11 and TGF-α correlated with CRP levels. This may indicate that their functions are not related to a systemic immunological reaction.
Whelan and colleagues have previously examined plasma from AD and MCI patients compared to controls using PEA [59
]. They examined plasma and CSF also using the Neurology and Inflammation panels. Similar findings were observed, including changes in the protein’s junction adhesion molecule B (JAM-B), uPA, CD200, and CD38. JAM-B was significantly different in plasma and CSF comparing AD patients and healthy controls, and significantly different in plasma comparing MCI patients and healthy controls. We did not detect any differences in plasma; however, EVs depicted a similar difference of JAM-B, as that seen in the study by Whelan et al. [59
], where JAM-B was found downregulated in cognitively affected. JAM-B is a tight junction protein expressed by brain endothelial cells forming the BBB [60
], and its dysregulation could be ascribed to the disruption of the BBB [61
]. JAM-B has also been associated with lymphocyte transendothelial migration [62
] and vascular inflammation [63
]. Similar observations could be observed for uPA, CD200, and CD38, hence strengthening our observations on differences between the three groups with downregulation of these proteins in disease groups. uPA has been shown to be important for recovery of axons after injury [64
] together with ezrin (EZR) [65
] which also was downregulated in our study, as well as inhibition of Aβ neurotoxicity [66
]. The expression of uPA has been shown to be increased in cells stimulated by Aβ which through binding to uPA receptor (uPAR) and activation of plasminogen to plasmin can degrade Aβ [66
]. The lower levels of uPA in plasma and EVs are not contradictory to this, but may indicate that uPA is bound to uPAR and plasminogen in the brain [68
]. CD200 is thought to be involved in enhanced amyloid phagocytosis [69
PEA has also previously been used to investigate EVs derived from neurons using the Neurology panel [70
]. Proteins highly expressed in neuron-derived EVs were also of relevance in our study. These proteins included CLEC1B, CLM-6, epithelial discoidin domain-containing receptor 1 (DDR1), EZR, SKR3, tumour necrosis factor receptor superfamily member 21 (TNFRSF21), and PLXNB3 downregulated in AD, as well as interleukin 12 (IL12) and SPARC-related modular calcium-binding protein 2 (SMOC2) upregulated in AD. Another study reported of decreased levels of hepatocyte growth factor (HGF) in neuron-derived EVs from AD patients [15
], which is in contrast to our findings showing increased levels of HGF in plasma from AD patients compared to controls. However, HGF have been shown to be increased in CSF of AD patients, possibly as a response to white matter damage [71
], and it might be a similar response we observed in our plasma samples.
Our study heralds some limitations. At first, relatively low numbers of participants were included. However, we were able to observe a clear differentiation of AD patients from controls using the protein profiles from the PLSDA. Secondly, only larger EVs from the 20,000 × g enrichment was analysed by PEA, and therefore the information from smaller EVs have not been investigated. Thirdly, since PEA utilized panels of specifically selected proteins, other possibly relevant proteins were not measured. Fourthly, PEA only measured relative concentrations and no absolute levels of proteins making a direct comparison with other studies difficult. Due to this output of relative abundances, the PEA method is suitable as a screening device for discovery studies, however, absolute quantification using other methods would be needed for further validation studies. Fifthly, although all patients were clinically verified for MCI or AD, not all were examined for clinical markers such as CSF Aβ and tau, which could have been correlated to our proposed protein biomarkers. Sixthly, the controls were slightly younger than the patients were, since it was not possible to recruit older individuals, but this difference is probably only of minor importance.
Thus, the present results imply significant indications regarding the analysis of plasma- and EV- related proteins as putative biomarkers in AD, but our findings warrant further investigations using a larger independent cohort of cases and controls. It would also be of interest to include other types of dementia and more severe cases of AD to investigate if these proteins are specific to AD and if they follow disease progression.