INTRODUCTION
Mild cognitive impairment (MCI) is an intermediate stage between normal aging and dementia. Amnestic MCI (aMCI) is characterized by prominent memory loss and is a high-risk condition for the development of clinically probable Alzheimer’s disease (AD) [1]. A meta-analysis of 23 cohort studies has shown that the annual conversion rate from MCI or aMCI to AD was 7.5%-16.5% at clinics and 5.4%-11.5% in community samples [2]. Given the lack of effective disease-modifying drugs for AD, it is important to identify early risk factors associated with conversion to AD among patients with aMCI for further risk reduction and prevention [3].
Substantial evidence suggests that deposition of amyloid beta (Aβ), such as Aβ1-40 and Aβ1-42, and neurofibrillary tangle formation of phosphorylated tau (p-Tau) in the brain are pathological hallmarks of AD, particularly during the early phases [3]. The 2018 National Institute on Aging (NIA)-Alzheimer’s Association (AA) Research Framework defined AD based on both clinical criteria and biomarkers via cerebrospinal fluid (CSF) and neuroimaging biomarkers (e.g., positron emission tomography [PET] scans), categorized into the AT(N) scheme [4]. However, CSF collection is an invasive procedure, and brain PET is expensive. In recent years, plasma biomarkers of AD, including amyloid deposition, tau aggregates, and neurodegeneration, have been considered [5,6]. Minimally invasive and low-cost plasma biomarkers are potentially useful in clinical practice. A previous study has reported that plasma biomarker profiles could predict AD pathology and clinical progression in individuals without dementia [7].
Immunomagnetic reduction (IMR) is an ultra-high-sensitivity detection technology to assay blood AD-related protein. In IMR, magnetic nanoparticles functionalized with antibodies and well dispersed in phosphate-buffered saline solution are used as a reagent. The concentrations of detected molecules are converted to reductions in the alternative-current magnetic susceptibility of this reagent due to the association between the magnetic nanoparticles and molecules. One IMR study by our team including 26 controls, 35 amnestic MCI, and 39 AD patients showed patients group had significant higher plasma levels of Aβ1-42, total tau (t-Tau) and p-Tau 181 [8]. Another cohort study of 22 aMCI patients showed that higher plasma levels of Aβ1-42 and t-Tau are associated with greater cognitive decline [9]. Therefore, the utilization of IMR technique could reliably and accurately for early detecting AD patients in both the prodromal and dementia state.
Previous studies have reported that plasma Aβ1-42, Aβ1-40, or t-Tau are potential valuable plasma biomarkers for identifying dementia conversion among the non-dementia population.10-12 Several studies have reported Aβ1-40 and Aβ1-42 as biomarkers of conversion to dementia in MCI population [5,13]; however, some other studies did not show such association [14,15]. The levels of t-Tau, p-Tau 181, and alpha-synuclein (α-Syn) are reported to be promising biomarkers in the CSF of patients with AD [16,17] and are reported more recently in the blood [5,6], but their association with cognitive decline remains understudied. Accumulation evidence suggests that α-Syn pathology, mainly associated with synucleinopathies like dementia with Lewy bodies and Parkinson’s disease, is also involved in the pathophysiology of AD. For example, one study showed no significant difference in plasma α-Syn levels between AD patients and controls [18], but another recent study showed higher plasma α-Syn levels was found in AD patients than controls [19]. Blood α-Syn as a biomarker in patients with AD should be studies further due to several factors including technical protocols, pre-analytic processes, and particularly hemolysis [20]. Furthermore, some studies have found an association between p-Tau 217 [6], p-Tau 181 [8,21] and Aβ [5,22] with cognitive decline. For example, one 3-year cohort study of 110 amnestic MCI patients suggested that plasma p-Tau 217 (using an immunoassay on the MesoScale Discovery platform) alone had the best performance to predict AD dementia progression [6]. Another study demonstrated that plasma p-Tau 231 showed the earliest change than p-Tau 217 in association with Aβ pathology in preclinical AD patients as determined by positive Aβ PET [23]. However, others showed no such association of Aβ [6,14] tau [24], or both biomarkers [25] with cognitive decline. The inconsistency might be associated with the dementia-related biomarkers plateau in the stage of aMCI and AD, heterogeneous of AD [25], inadequate sample sizes [14], and different assay techniques used [6]. Moreover, it is still unknow whether higher baseline plasma levels of Aβ and tau protein biomarkers are associated with better identification of cognitive decline than longitudinal changes in these biomarkers in patients with aMCI.
Therefore, this study aimed to investigate the baseline plasma levels and longitudinal changes in Aβ and tau protein biomarkers among four groups (aMCI converters, aMCI non-converters, AD, and controls). We hypothesized that different baseline levels and longitudinal changes in Aβ and tau protein biomarkers occur in these four groups and that the capacity to predict aMCI conversion is different for baseline levels and longitudinal changes in these protein biomarkers.
METHODS
Participants
Participants were recruited from the memory clinic of the Tri-Service General Hospital of the National Defense Medical Center, Taiwan, between September 2017 and May 2020. Individuals were eligible if they were aged ≥60 years and had negative findings on physical and neurological examinations, laboratory tests (assessment of creatinine, fasting blood sugar, free thyroxine 4, high-sensitivity thyroid-stimulating hormone, vitamin B12, and folic acid; serological tests for syphilis; and routine blood tests), and neuroimaging examinations (brain computed tomography or magnetic resonance imaging).
Individuals were excluded if they had: 1) a history of major or uncontrolled medical conditions, such as heart failure, sepsis, liver cirrhosis, renal failure, chronic obstructive pulmonary disease, poorly controlled diabetes (hemoglobin A1c>8.5), myocardial infarction, or malignancy; 2) substance abuse; 3) a history of major neurological disorders, such as stroke or Parkinson’s disease; 4) a score>9 on the short-form Geriatric Depression Scale (GDS-SF) or >3 on the modified Rankin Scale; and 5) a history of major psychiatric conditions that could impair cognition, such as major depressive disorder, bipolar disorder, or schizophrenia.
During recruitment, the participants underwent the following examinations: Mini-Mental Status Examination (MMSE), Clinical Dementia Rating (CDR), GDS-SF, verbal fluency test, Hopkins Verbal Learning Test (HVLT), forward and backward digit span, Trail Making Test (TMT), Part A, Modified Boston Naming Test (MBNT), and Hachinski Ischemia Scale (HIS). The second MMSE was conducted after the 1-year follow-up.
Participants were classified into the control, aMCI, and AD groups based on the results of HVLT, MMSE, and CDR examinations as well as recommendations from the National Institute on Aging-Alzheimer’s Association (NIA-AA) workgroups on diagnostic guidelines for AD and aMCI [26,27]. AD was diagnosed if the patients satisfied the following criteria: 1) NIA-AA criteria [27]; 2) CDR≥0.5, 3) MMSE score≤26 (middle school), MMSE score≤22 (primary school), or MMSE score≤19 (illiteracy) [28]; 4) HIS score≤3; and 5) HVLT score≤19 [29]. Unlike the MMSE, the HVLT has no ceiling effects and does not have to be adjusted for education [30]; therefore, we did not stratify HVLT cutoff by educational level. aMCI was diagnosed if the patients satisfied the following criteria: 1) NIA-AA criteria [26]; 2) CDR=0.5; 3) MMSE score>26 (middle school), MMSE score>22 (primary school), or MMSE score>19 (illiteracy); 4) HIS score≤3; and 5) HVLT score≤22 [29]. Healthy controls satisfied the following criteria: 1) no active neurological or psychiatric disorders; 2) no psychotropic drugs; 3) MMSE score> 26 (middle school), MMSE score>22 (primary school), or MMSE score>19 (illiteracy); and 4) CDR score=0. Finally, we defined aMCIs converters as individuals with aMCI who eventually progress to AD after 1-year follow-up period. aMCIs non-converters as individuals with aMCI but do not progress to AD after 1-year follow-up period.
This protocol was approved by the Institutional Review Board for the Protection of Human Subjects at the Tri-Service General Hospital (approval number TSGHIRB 1-107-05-111). All human subjects provided informed consent.
Plasma preparation
Fasting blood was collected in 9-mL K3-EDTA tubes (455036; Greiner Bio-one GmbH, Kremsmünster, Austria), which were gently inverted three times immediately following blood collection. Blood samples were then centrifuged at 2,300×g for 10 minutes (4°C) using a swing-out (bucket) rotor (5202R; Eppendorf, Hamburg, Germany). Each 0.4-mL plasma sample was transferred to a fresh 2.0-mL tube (CryzoTraq; Ziath, Cambridge, United Kingdom). All plasma samples were stored in 0.5-mL aliquots within 8 hours of blood collection at -80°C until further use.
Assessment of plasma Aβ and tau levels
IMR, an ultra-sensitive analytical assay, can reliably detect ultra-low concentrations of Aβ and tau biomarkers, including Aβ 1-40 (Aβ1-40), Aβ1-42, t-Tau, p-Tau 181, and α-Syn [31]. The levels of plasma Aβ1-40, Aβ1-42, t-Tau, p-Tau 181, and α-Syn were assessed using IMR kits (MF-AB0-0060, MF-AB2-0060, MF-TAU-0060, MF-PT1-0060, and MF-ASC-0060; MagQu Co., New Taipei City, Taiwan). For each assay, 40 µL (Aβ1-40, t-Tau, p-Tau 181, and α-Syn) or 60 µL (Aβ1-42) of plasma was mixed with 80 µL or 60 µL of reagent, respectively. Each reported biomarker concentration is the average of two duplicate measurements. An IMR analyzer (XacPro-S; MagQu Co., New Taipei City, Taiwan) was used for all assays. The measured biomarker concentrations ranged from 0.17 to 1,000 pg/mL for Aβ1-40, 0.77 to 30,000 pg/mL for Aβ1-42, 0.026 to 3,000 pg/mL for tTau, 0.0196 to 1,000 pg/mL for p-Tau181, and 0.0014 to 1,020 pg/mL for α-Syn. Intra- or inter-assay coefficients of variation using IMR ranged from 7% to 10% and from 10% to 15% for high- and low-concentration quality control samples of Aβ1-40, Aβ1-42, t-Tau, p-Tau 181, or α-Syn, respectively. Two batches of reagents were used for each biomarker, and the quality of each batch of reagents was controlled by monitoring the particle size, particle concentration, and bioactivity. The variation in the reagent properties between batches was lower than 10%.
Apolipoprotein E genotyping
To obtain genetic information from samples collected from Taiwanese Han Chinese patients, the Taiwan Biobank (TWB) designed the TWB genotype array based on the Affymetrix Axiom genotyping platform. The TWB genotype array enables high-quality genotyping. Two single-nucleotide polymorphisms (SNPs; rs429358 and rs7412) defining apolipoprotein E (ApoE) isoforms were genotyped using the TWB array.
Statistical analyses
Group differences (aMCI vs. control and AD vs. control) in categorical variables were examined using Fisher’s exact test and those in continuous variables were examined using independent samples t-test or analysis of variance (ANOVA). Tukey’s honest significant difference test was used for posthoc ANOVA. The values of the IMR data were logarithmically transformed. The temporal ordering (controls, aMCI, and AD) of the cognitive tests and plasma biomarkers was examined using p trend analysis. The association between plasma biomarkers and MMSE scores in the aMCI and AD groups was assessed using partial correlation network analysis with adjustments for sex, age, education level, and follow-up duration. Within-group intercorrelations of plasma biomarkers were assessed using Pearson correlation. Receiver operating characteristic (ROC) curve analysis was performed to examine the predictive ability of AD conversion. The 95% confidence interval (CI) for the area under the ROC curve (AUC) was calculated using DeLong’s test. All tests were two-tailed and p<0.05 was considered statistically significant. No adjustment for multiple testing (multiplicity) was performed. Data analyses were conducted using SPSS version 25 (IBM Corp., Armonk, NY, USA).
RESULTS
Baseline demographics data
A total of 67 participants were included (control group=20, aMCI group=37, and AD group=10). Patients in the AD group were older than those in the control group (75.2±10.3 years vs. 66.0±6.7 years, p=0.006). Regarding the cognitive tests, patients in the AD (22.0±3.3) and aMCI (26.2±2.2) groups had poorer MMSE scores than those in the control group (29.4±0.5). Patients in the AD group had poorer HVLT (14.3±4.3), backward digit span (3.9±1.7), and verbal fluency test scores (7.3±3.2) than those in the control group (HVLT, 21.4±6.1; backward, 7.0±2.7; verbal fluency, 13.6±2.8). Patients in the aMCI group had poorer backward digit span (5.3±2.0) and MBNT (13.8±1.3) scores and better TMT part A (66.2±29.1) scores than those in the control group (backward, 7.0±2.7; MBNT, 14.6±0.6; TMT, 42.7±21.0). In terms of Aβ and tau biomarkers, the aMCI group had higher Aβ1-42 (16.9±1.1 pg/mL), t-Tau (24.2±5.7 pg/mL), and p-Tau 181 (3.9±0.8 pg/mL) levels than the control group (Aβ1-42, 16.1±0.8; t-Tau, 21.2± 2.5; p-Tau 181, 3.4±0.5, all in pg/mL). The ApoE allele status of the study groups is presented in Table 1. We did not find statistical significance for the baseline levels of biomarkers between AD and aMCI for Aβ1-40 (t=-0.130, p=0.897), Aβ1-42 (t=-0.541, p=0.591), t-Tau (t=-1.178, p=0.245), p-Tau 181 (t=-1.073, p=0.289), and α-Syn (t=-0.344, p=0.733).
Correlation network between biomarkers and annual change in MMSE
We examined the correlation between the plasma levels of dementia-related protein biomarkers and the annual change in MMSE scores between patients with aMCI and AD, after adjustment for sex, age, education level, and follow-up duration. A larger annual change in the MMSE score correlated with a larger elevation in the plasma levels of p-Tau 181 (r=-0.431, p=0.004) and t-Tau (r=-0.330, p=0.030) (Figure 1). Higher baseline plasma levels of p-Tau 181 (r=0.373, p=0.014) and t-Tau (r=0.332, p=0.030) correlated with smaller annual changes in the MMSE score. Plasma levels of Aβ1-40, Aβ1-42, and α-Syn were not significantly correlated with annual changes in the MMSE score (Supplementary Table 1).
Group differences in baseline, follow-up, and change in levels of p-Tau 181
The four groups differed in their baseline plasma levels of p-Tau 181 (F=7.415, p<0.001) (Figure 2A). The post-hoc analysis showed that the aMCI non-converter group had significantly higher levels of p-Tau 181 than the aMCI converter (mean difference, 0.88; 95% CI, 0.28-1.48; adjusted p=0.002) and control groups (0.69; 95% CI, 0.21-1.17; adjusted p=0.002). Patients in the AD group showed no significant difference in p-Tau 181 levels compared with those in the control, aMCI non-converter, and aMCI converter groups.
The four groups also differed in terms of annual changes in the plasma levels of p-Tau 181 (F=6.634, p<0.001) (Figure 2B). The annual change levels of p-Tau 181 were significantly lower in the aMCI non-converter group than in the aMCI converter (-1.07; 95% CI, -1.78 to -0.35; adjusted p=0.001) and control groups (-0.59; 95% CI, -1.16 to -0.03; adjusted p=0.037), whereas the annual change levels of p-Tau 181 were significantly higher in the aMCI converter group than in the AD group (1.03; 95% CI, 0.17 to 1.89; adjusted p=0.013). For the follow-up plasma levels of p-Tau 181, patients with AD plus aMCI converters showed no significant difference in p-Tau 181 levels compared with that noted in patients in the non-converter and control groups (Figure 2C).
Correlation of baseline dementia-related proteins among aMCI converters versus non-converters
The intercorrelation of dementia-related proteins (Aβ1-40, Aβ1-42, t-Tau, p-Tau 181, and α-Syn) was different between the aMCI converter and non-converter groups. In the aMCI non-converter group, Aβ1-42 was positively correlated with p-Tau 181 (r=0.40) and t-Tau (r=0.60), and p-Tau 181 was positively correlated with t-Tau (r=0.63). However, in the aMCI converter group, a significant negative correlation was observed only between Aβ1-40 and p-Tau 181 (r=-0.66) (Figure 3).
Discriminatory capacity of plasma annual change levels of biomarkers in predicting AD conversion
The annual rate of AD conversion was 27%. The ROC curve was analyzed to estimate the predictive potential and accuracy of AD conversion in aMCI patients using the plasma annual change levels of p-Tau 181 and t-Tau during the follow-up period. We found higher accuracy in discriminating aMCI converters and aMCI non-converters obtained for annual plasma change levels of p-Tau 181 than t-Tau (AUC, 0.867 vs. 0.722) (Figure 4).
DISCUSSION
This study examined the baseline plasma levels and longitudinal changes in Aβ and tau protein biomarkers among the aMCI converter, aMCI non-converter, AD, and control groups. The main findings were as follows: 1) annual change in the MMSE score was correlated with plasma levels of tau biomarkers, while no correlation was found for plasma Aβ1-40, Aβ1-42, and α-Syn levels; 2) the aMCI non-converter group had higher baseline plasma levels of p-Tau 181, and the aMCI converter group had larger annual change levels of plasma levels of p-Tau 181; 3) among patients in the aMCI non-converter group, p-Tau 181 was positively correlated with t-Tau and Aβ1-42, and t-Tau was positively correlated with Aβ1-42. However, p-Tau 181 was negatively correlated with Aβ1-40 among patients in the aMCI converter group; and 4) annual change in plasma levels of p-Tau 181 showed the best capacity to discriminate between aMCI converters and non-converters.
Blood-based biomarkers provide an alternative method of lowering costs and are less invasive to the community for identifying and monitoring cognitive function. In the present study, plasma tau biomarkers, instead of amyloid, were associated with annual changes in the MMSE scores. Notably, the present study showed rapid elevation of t-Tau and p-Tau 181 levels predicted subsequent cognitive decline. This is consistent with previous study, showing a longitudinal increase of plasma p-Tau 181 was associated with faster worsening cognitive function [32]. However, patients with aMCI and AD with lower baseline p-Tau 181 and t-Tau were more likely to have cognitive decline during the follow-up period. The results were inconsistent with previous studies [33-35]. For example, one Korean cohort study of 49 MCI and 113 cognitively unimpaired patients showed that higher baseline p-Tau 181 levels predicted cognitive conversion in 3-year follow-up period [34]. Another study of 458 cognitively healthy and MCI participants showed plasma t-Tau was associated with significant decline in cognitive function [36]. The inconsistency might be due to different ethnic population, various plasma assay techniques used, or disease stage. To be specific, three studies reported higher p-Tau 181 linked to greater cognitive decline are different from ours with regard to ethnic (from Sweden [33,35] or South Korea [34]), plasma assay techniques (Sioma [34,35] or Meso Scale Discovery platform [33]), or disease stage (preclinical AD, MCI, and AD dementia [33]; cognitive unimpaired, MCI, and AD dementia [35]; cognitive unimpaired and MCI [34]). All these potential factors contributing to the inconsistencies between the present and previous studies. The levels of p-Tau 181 may detect AD-type changes and reflect AD symptoms, which are linked to the tau pathology [33]. In the Aβ-positive cognitive unimpaired population, a positive baseline plasma p-Tau 181 shows a higher likelihood in developing dementia after the follow-up period [21]. In addition, plasma p-Tau 181 is a strong indicator of both CSF tau levels and tau PET-positivity [33]. Another PET imaging study of participants with MCI and AD found that tau PET is more sensitive than Aβ PET in association with cortical thickness and detection of early cognitive change [37]. Therefore, the present study provides significant additional evidence for the use of plasma tau, particularly p-Tau 181, as a non-invasive diagnostic and prognostic tool for aMCI and AD, which may be of great benefit in clinical trial recruitment.
Another finding of the present study was that aMCI converters showed significantly lower plasma levels of p-Tau 181 but higher annual changes in plasma levels of p-Tau 181 than aMCI non-converters. The plasma levels of p-Tau 181 predicted progression to AD among participants with aMCI during the follow-up period, which was consistent with the findings of previous studies from Western countries [33,38,39]. For example, a 4-year follow-up study of 573 patients with MCI showed plasma p-Tau 181 in combination with neurofilament best predicted clinical progression to AD [38]. Inclusion of p-Tau 181 may reflect that p-Tau 181 detects AD-type changes as tau and neurodegeneration markers continue to increase during the symptomatic stages of the disease [33]. On the other hand, plasma Aβ1-42 may have added value at the preclinical stage of the diseases with the presence of pathological accumulation [39]. Prior evidence suggests that racial differences influence the levels of t-Tau and p-Tau 181 in the CSF of both patients with MCI and AD [40]. The APOE ε4 allele influences tau pathogenesis and tau-mediated neurodegeneration independently of Aβ pathology [41]. In tau PET studies, widespread tau progression with age throughout the brain was detected in cognitively unimpaired individuals, and elevated tau levels were more commonly found when amyloid accumulation was present [42]. African Americans with the APOE ε4 allele are prone to having lower levels of t-Tau and p-Tau in the CSF. Although individuals of Asian ethnicity have a lower APOE ε4 frequency than their Western counterparts, the present study found that plasma p-Tau 181 levels could be a possible candidate biomarker for conversion to AD among aMCI individuals.
The levels of Aβ and tau are the two main histopathological signatures of AD, and their association is bidirectional [43]. A previous study reported that decreased CSF levels of Aβ1-42 were associated with increased CSF levels of t-Tau in patients with AD [43]. Regarding plasma levels of dementia-related proteins, the present study showed a significantly positive correlation between both t-Tau and p-Tau 181 and Aβ1-42 concentrations in aMCI non-converters but not in aMCI converters. These results were consistent with those of our previous studies [44], showing that the AD spectrum (including aMCI) is a dual proteinopathy consisting of both Aβ and p-Tau 181. Indeed, only the plasma levels of p-Tau 181 were associated with clinical severity in AD spectrum groups, but not the plasma levels of Aβ [44]. In a brain magnetic resonance imaging study of 740 patients with aMCI, those with a more profound cortical atrophy pattern were more likely to progress to AD [45]. The levels of Aβ decrease with disease progression, whereas the levels of p-Tau 181 increase later than those of the Aβ, suggesting that the levels of p-Tau 181 might be a potential marker for brain AD pathology and disease progression [46]. The reduction in the plasma levels of Aβ1-42 with greater severity among aMCI converters might partially explain the null correlation between p-Tau 181 and Aβ1-42.
To the best of our knowledge, we report the first IMR study using plasma level of p-Tau 181 as a potential biomarker to predict AD conversion in patients with aMCI. The present study showed the annual conversion rate was 27%, which is higher than previous studies conducted at a memory clinic in Taiwan [47]. Another meta-analysis study showed a pooled conversion rate to AD from MCI using Petersen criteria was 23.8% [48]. More strict definition to diagnosis MCI in the present study might explain the relatively higher conversion rate. Our follow-up data showed that the annual change in plasma levels of p-Tau 181 was better than the annual change in plasma levels of t-Tau for predicting AD conversion. For t-Tau, a previous IMR study reported that the AUC of t-Tau in predicting AD conversion was 0.8, which was similar to our results (AUC: 0.722) [9]. For cognitive trajectories, the present study confirmed previous IMR study, showing p-Tau 181 was associated cognitive decline in the follow-up period. However, the evidence of plasma t-Tau level on cognitive change yielded inconistent results. For example, prior studies have shown that t-Tau levels was not associated with annual changes in global cognitive function [11], but other showed association [9] including ours. The conflicting results likely due to, at least in part, to confounding clinical (e.g., age, comorbidities) and methodological factors. In the present study, we also found a higher discriminatory ability of p-Tau 181 than of t-Tau, with an AUC of 0.867. The levels of t-Tau can be assessed in numerous peripheral organs, such as the colon and liver, in both AD and non-AD patients [49]. A study with a 3-year follow-up (110 patients with aMCI) found that p-Tau 217 had the best performance for differentiating progression to AD from other plasma dementia-related proteins [6]. The present study examined p-Tau 181, which might be relatively under-performed than p-Tau 217 in differentiating patients with AD from those with frontotemporal dementia [50]. Importantly, evidence has shown that both p-Tau 181 and p-Tau 217 have excellent diagnostic performance in distinguishing AD from cognitively healthy controls [50].
This study has several limitations. First, the relatively modest sample size may have provided inadequate statistical power to detect the association between other dementia-related proteins and conversion to AD. Further large-scale follow-up studies are warranted to validate our findings. Second, the participants were recruited from a memory clinic; therefore, the findings of the present study cannot be generalized to other community-dwelling elderly people. Third, the performance of different blood assays such as immunoaffinity purification mass spectrometry, Simoa, or multimer-detection systems, could have induced different results. Furthermore, the present study did not examine other p-Tau variants, such as 191, 217, 231, etc. Future study using other blood assay and investigate other p-Tau variants was warranted. Fourth, the present study recruited clinical diagnosis of AD patients without standard diagnostic modalities such as amyloid PET scan or CSF biomarker, which could be considered as another limitation of the study.
In conclusion, we found that a larger elevation in annual change in plasma levels of t-Tau and p-Tau 181 was associated with better identification of cognitive decline than higher baseline levels of these protein biomarkers in patients with aMCI and AD. Furthermore, the annual change in plasma levels of p-Tau 181 provided the best discriminatory ability for predicting AD conversion in patients with aMCI. These findings suggest that plasma p-Tau 181 levels can be used to assess the severity of cognitive impairment and monitor cognitive decline in patients with aMCI and AD. Our findings need to be replicated in future large-scale longitudinal studies.
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