Background
Alzheimer’s disease (AD) is a complex, age-related neurodegenerative disorder, whose prevalence is anticipated to triple worldwide by 2050 [
1]. With the introduction of molecular biomarkers, AD progressively acquired a biological definition that optimized the traditional clinical symptom-based approach [
2]. Briefly, “A”, amyloid-beta (Aβ) plaques with amyloid precursor protein; “T”, neurofibrillary tangles of the hyperphosphorylated tau protein (p-tau); and “(N)”, neurodegeneration, taken together, define the AT(N) system, a biomarker-guided classification scheme categorizing individuals using the core pathophysiological features of the disease.
To date, for clinical routine, the quantification of biomarkers is based on the cerebrospinal fluid (CSF) concentration assessment of the 42-amino acid-long Aβ peptide (Aβ
42) and/or the ratio between Aβ
42 and the 40-amino acid-long Aβ peptide (Aβ
40), hyperphosphorylated tau (p-tau), and total tau (t-tau) proteins [
3] and/or neuroimaging techniques such as Aβ-positron emission tomography (PET) [
4], tau-PET imaging [
5], and structural magnetic resonance imaging (MRI) [
6]. However, while highly performant, such tools require expensive imaging equipment, highly trained staff, and, for lumbar puncture, invasive procedures.
To overcome these constraints, blood-based biomarkers have been developed and results are promising, especially concerning the Aβ
42/40 ratio; p-tau; neurofilament light chain (NfL), a marker of neuroaxonal injury; or glial fibrillary acidic protein (GFAP), a marker of glial activation [
7‐
9]. Initial conflicting outcomes were later explained by the unavailability of immunoassays sensitive enough or possible misclassification of clinical diagnosis [
8]. Recent advances both in mass spectrometry (MS) and immunodetection methods, together with standardization of preanalytical variables, allowed to partly overcome those limitations by improving sensitivity [
10,
11].
Eight plasma Aβ
42/40 assays were recently compared, in terms of performances, when detecting abnormal cerebral Aβ status (according to CSF Aβ
42/40 or Aβ-PET imaging) in early AD patients [
12]. Only two of them seem operable on a large scale but involve an arbitration between cost, flow, and performances: ultrasensitive single molecule array (Simoa) technology [
13] or immunoprecipitation coupled with MS (IPMS), as developed by the Washington University or Shimadzu (IPMS-Shim) [
14,
15].
A study relying on Simoa reported decreased plasma Aβ
40 and Aβ
42 concentrations and reduced Aβ
42/40 in AD patients [
16]. Such biomarkers could even discriminate mild cognitive impairment (MCI) from control individuals [
16] and were relevant predictive tools of positive amyloid-PET status [
17]. MS-based studies found similar results indicating that Aβ
42/40 was inversely proportional to brain Aβ burden [
15].
However, data are still incomplete in clinical practice and concerning the diagnostic and prognostic accuracy of Aβ plasma biomarkers to discriminate AD from MCI, individuals with subjective cognitive impairments (SCI), other neurodegenerative diseases (NDD), or other neurological disorders (OND). No comparative studies have been done between the most recent and relevant plasma biomarker dosages. In addition, it remains unclear whether plasma biomarkers have a better diagnostic usefulness based on core clinical or biological criteria (Aβ−/Aβ+, AT(N)). Eventually, the temporal changes in plasma amyloid biomarkers remained to be determined and explored using recent ultrasensitive proteomic technologies.
The main objective of our study was to determine, in a cohort of memory clinic patients with differential diagnosis and, for some of them, spread along the AD continuum, the diagnostic and prognosis relevance of the two most operable plasma amyloid biomarkers, ultrasensitive immunoassay and IPMS amyloid biomarker dosages.
Discussion
We validated, using samples obtained in a memory clinic, the diagnostic relevance of the IPMS-Shim composite score to discriminate clinical AD—in the early stages of the disease—from MCI, SCI, OND, and NDD (Fig.
3). IPMS-Shim plasma Aβ
42 measurements and Aβ
42/40 ratio were weakly but significantly correlated with CSF Aβ
42 and Aβ
42/40 results (Table S
2). In contrast, Simoa 3-PLEX did not achieve IPMS-Shim diagnostic performances and failed to correlate with the core biomarkers, at least for Aβ
42.
The positive correlation between plasma IPMS-Shim Aβ
42/40 measurements and CSF values was replicated, as previously indicated [
14]. Moreover, as described by Janelidze and colleagues, we confirmed the lack of correlation between CSF and plasma using the Simoa 3-PLEX technology [
16]. It was later discovered that a substantial non-specific Aβ
3–42 signal was measured using this assay due to the region targeted by the capture antibody (amino acid 4 to 10) [
30]. Alternatively, quantification in the CSF employs the highly specific sandwich ELISA technique, potentially explaining the lack of correlation with the 3-PLEX and the modest performances of the 3-PLEX assay. Thijsenn et al. recently developed full-length antibodies against Aβ
40 and Aβ
42 that indeed revealed better sensitivity and specificity than the 3-PLEX [
30] and used for the development of a new assay (4-PLEX).
IPMS-Shim-based biomarkers revealed better diagnostic performances in all clinical categories, which could be explained by the high specificity of MS-based technologies, in general [
31], and the better performances compared with those of immunoassays [
12]. Moreover, MS minimizes the matrix effect observed in the blood [
32]. Eventually, multiple pathological conditions (inflammation, renal dysfunction…) alter or at least affect basal amyloid-β expression and might cause inter-individual variations, especially in the plasma. As shown by others, expressing Aβ
42 relative to a reference, as APP
669–711, improves its discriminative performance [
33]. Expressing Aβ
42 relative to two references, combined in a composite score, exhibit even higher performances [
15].
We were able to reveal a decrease of IPMS-Shim Aβ
42 that seemed to be specific to the AD diagnosis (Table S
5 and Fig.
5A, B). Even if these results are exploratory and should be confirmed on a larger cohort, this is the first description, to our knowledge, of such evolution of plasma Aβ
42 using ultrasensitive methods. An important change (< −0.188 over ~2 years) in plasma Aβ
42 concentrations could reveal a useful biomarker to detect AD patients as it is highly specific of the disease (Sp = 0.95). The data available in the literature indicate a drop in plasma Aβ
42 in the early phases of the disease in healthy controls transitioning to MCI [
34] or MCI to AD [
35], consistent with the decrease observed with CSF Aβ
42 [
36]. Additional studies incorporating multiple time points and using state-of-the-art technologies will be necessary to conclude on the evolution of Aβ
42 in the plasma.
Aβ
42/40 ratio was further explored since there is growing evidence emphasizing its role as a potentially better diagnostic biomarker than the absolute value of Aβ
42, at least in CSF analyses [
37]. Plasma Aβ
42/40 was reduced in AD patients relative to NDD, OND, MCI, and SCI participants (Fig.
1). We confirmed the results found by other studies that used Simoa [
16] and MS [
15,
38,
39]. Moreover, when Aβ
+, A+T+, or A+T+N+ individuals were investigated, this ratio was reduced using all strategies (Table S
3). Taken together, those results emphasize the potential role of low plasma Aβ
42/40 concentrations as a robust indicator of both AD clinical diagnosis and biologically confirmed cases.
Plasma p-tau is assumed to be another attractive blood-based candidate biomarker for AD clinical diagnosis. However, p-tau, which is stable in CSF, exhibits a very short half-life (around 10 hours) in blood [
40] and may appear later during the progression of the disease [
41]. Eventually, t-tau, considered as a biomarker of neuronal injury in the CSF but susceptible to degradation by proteases in the plasma, might be replaced, for an initial blood-based diagnostic, by NfL. NfL is a more promising biomarker, robust in the plasma, whose concentration increases with neurodegeneration, that would allow to identify patients at risk of cognitive decline and to track disease progression [
8].
Our study presents some limits. First, the number of individuals in the SCI group and with available CSF Aβ42/40 concentrations was limited. This was also the case for the longitudinal analysis; however, given the specificity in Aβ42 decrease, it appeared worth reporting. Second, a few characteristics (MMSE, education, CSF biomarkers) were not available for the OND group because it did not require the same set of procedures as the other groups in a memory clinic.
One of the strengths of our analysis is that it was conducted on a sample that reflects the population that attends memory clinics in France. None of the highly selective inclusion or exclusion criteria generally used for clinical research was used. Our sample, while heterogeneous, thus mirror the diversity of AD presentations. The most up-to-date and operable proteomic techniques were used for biomarker quantification. Our results confirm that they could be implemented for AD pre-screenings in memory clinics before further expensive or invasive tests and with diagnosis performances similar to CSF measures.
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