Brain Amyloid-β Deposition and Blood Biomarkers in Patients with Clinically Diagnosed Alzheimer’s Disease

Abstract

Brain amyloid-β (Aβ) deposition is a hallmark to define Alzheimer’s disease (AD). We investigated the positive rate of brain amyloid deposition assessed with ¹¹C-Pittsburgh compound (PiB)-PET and blood Aβ levels in a cohort of probable AD patients who were diagnosed according to the 1984 NINCDS-ADRDA criteria. Eighty-four subjects with a clinical diagnosis of probable AD dementia, amnestic mild cognitive impairment (MCI), and cognitively normal (CN) status were subjected to PiB-PET and ¹⁸F-fluorodeoxyglucose (FDG)-PET scans. Plasma biomarkers of Aβ₄₂, Aβ₄₀, and T-tau were measured using single molecule array technology. The positive rate of PiB-PET, the associations between PiB-PET status and FDG-PET, plasma biomarkers, and clinical manifestations were analyzed. PiB-PET was positive in 77.36% of probable AD patients, 31.80% of MCI patients, and 0 of NC. Plasma Aβ₄₂/Aβ₄₀ ratio was associated with PiB-PET, the ROC curve analysis revealing an AUC of 0.77 (95% CI: 0.66–0.87), with a sensitivity of 82% and specificity of 64%. Some clinical manifestations were associated with PiB-PET imaging. Our findings indicate that only three-fourths of patients diagnosed with probable AD fit the pathological criteria, suggesting that we should be cautious regarding the accuracy of AD diagnosis when no biomarker evidence is available in our clinical practice.

Keywords

Alzheimer’s disease amyloid-beta amyloid PET blood biomarkers diagnosis mild cognitive impairment probable AD dementia tau

INTRODUCTION

Alzheimer’s disease (AD) is the most common type of aging-related dementia, which brings a heavy burden to patients and society [1, 2]. AD is pathologically characterized by extracellular senile plaques containing amyloid-β (Aβ) and intraneuronal neurofibrillary tangles composed of hyperphosphorylated tau protein, as well as other neurodegenerative changes such as synaptic loss and neuronal death in the brain [3].

Senile plaques are a hallmark to define the diagnosis of AD, which once depended on postmortem biopsy [4]. Due to the unavailability of brain biopsy, for a long period the diagnosis of AD has been based on the National Institute of Neurological and Communicative Diseases and Stroke/AD and Related Disorders Association (NINCDS-ADRDA) criteria, which was proposed in 1984 and required the assessment of disease history, symptoms, and exclusion of other possible causes of cognitive impairment [5]. In recent years, biomarkers were incorporated into the new diagnostic criteria to provide pathological evidence and thus improve the accuracy of AD diagnosis [6 –8]. These biomarkers are grouped into Aβ deposition, pathologic tau, and neurodegeneration [AT(N)], which reflect various aspects of AD pathogeneses [9]. Among these biomarkers, brain Aβ deposition, illustrated by amyloid PET scan, is essential for making a definite AD diagnosis [10, 11].

However, as biomarker tests like amyloid PET are not available in most hospitals at this stage, AD diagnosis still primarily relies on the NINCDS-ADRDA criteria in routine clinical practice. Therefore, it is essential to know the accuracy of AD diagnosis in clinic. Besides, a report of the Amyloid Imaging Task Force (AIT), the Society of Nuclear Medicine and Molecular Imaging (SNMMI), and the Alzheimer’s Association (AA) proposes that amyloid imaging is inappropriate when patients meet the core clinical diagnosis criteria of AD at typical age of onset [12]. In this regard, we also need to verify the necessity of amyloid PET examination for probable AD in clinical practice.

To answer these questions, the present study investigated the positive rate of amyloid deposition assessed with ¹¹C-Pittsburgh compound (PiB)-PET in a clinical cohort of probable AD subjects, and we further explore the associations between amyloid PET and other potential biomarkers including ¹⁸F-fluorodeoxyglucose (FDG)-PET, evidence of neurodegeneration [13], and blood Aβ₄₂, Aβ₄₀, total tau (T-tau), and clinical manifestations.

MATERIALS AND METHODS

Study subjects

Consecutive subjects with cognitive impairment admitted to the memory clinic of Daping Hospital from January 2015 to August 2018 were enrolled into the present study. Eligible subjects were required 1) to have been diagnosed with AD or mild cognitive impairment (MCI); 2) to have undergone Pittsburgh compound B (PiB)-PET, illustrating brain Aβ deposition and FDG-PET scans, illustrating neurodegeneration status; and 3) to be willing to participate in the study. Seventy-five patients who met the enrolling standards were finally included in the present study. In addition, nine cognitively normal (CN) subjects with PET scans were also enrolled into the present study. This study was approved by the Institutional Review Board of Daping Hospital, and all subjects and their caregivers provided informed consent.

Clinical assessments

All subjects underwent clinical assessments including medical history, physical examination, laboratory tests, APOE genotyping, and neuropsychological tests. Demographic characteristics including age, sex, and education levels were recorded. ApoE genotypes (rs429358 and rs7412) were determined by the polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) method as described in our previous study [14]. Mini-Mental State Examination (MMSE) [15] and Montreal Cognitive Assessment (MoCA) [16] were initially administered to screen and assess the overall cognitive. The subjects who were abnormal in MMSE or MoCA assessments were further administered with a battery of neuropsychological tests including: Clinical Dementia Rating (CDR) [17], administered for denoting the presence or absence of dementia and its severity; Activities of Daily Living Scale (ADL) [18] and Pfeiffer Outpatient Disability Questionnaire (POD) [19], administered for assessing ability of social activities; and Hachinski Ischemic Score (HIS) [20], administered to exclude significant vascular disease.

Neuroimaging

All subjects were subjected to brain magnetic resonance imaging (MRI) or computed tomography (CT). Structural MRI brain scans were based on a 1.5-T imaging systems with a standardized protocol that included T1-weighted images of sagittal, coronal and transverse section. CT was taken as substitute when the patients cannot stand the process of MRI scan. Images were visually rated by two experienced radiologists who were blind to all clinical information, and the final ratings for brain atrophy were decided by consensus. The brain atrophy was judged referring to the following standard [21]: 1) the size of the sulcus, cisterns and ventricles are wider compared with the normal peers, the width of the sulcus is more than 5 mm; 2) the frontal angle, occipital angle and temporal horn of the ventricle become round and obtuse; 3) the hippocampus is smaller than that of the normal peers.

Classification of cognitive and behavior impairment symptoms

The cognitive or behavioral impairment symptoms were classified as follows [6]: 1) Impaired ability to acquire and remember new information. Symptoms include: forgetting events, repetitive questions or conversations, misplacing personal belongings, getting lost on a familiar route. 2) Impaired reasoning and handling of complex tasks, poor judgment (executive dysfunction). Symptoms include: poor understanding of risks, poor decision-making ability, inability to manage finances, inability to plan sequential or complex activities. 3) Impaired visuospatial abilities. Symptoms include: inability to recognize faces or common objects, difficulty in finding objects in direct view, inability to operate simple implements, or orient clothing to the body. 4) Impaired language functions (speaking, reading, writing). Symptoms include: difficulty thinking of common words while speaking; spelling, speech, and writing errors. 5) Changes in personality, behavior, or comportment. Symptoms include: uncharacteristic mood fluctuations such as agitation, impaired motivation, initiative, social withdrawal, apathy, decreased interest in many activities, compulsive or obsessive behaviors, loss of empathy, socially unacceptable behaviors. 6) Hallucinations in different sensory modalities like auditory and/or visual hallucinations.

Diagnosis of AD dementia and MCI

Dementia was diagnosed based on the criteria from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV). Clinical diagnosis of AD dementia was made by experienced neurologists according to NINCDS-ADRDA criteria [5], including 1) insidious onset of symptoms; 2) a clear-cut history of worsening of cognition; and 3) prominent cognitive deficits in at least one of the following categories: amnestic presentation, language presentation, visuospatial presentation or executive presentation. Those who had 1) a history of head trauma or brain lesions; 2) a substantial concomitant cerebrovascular disease; 3) core features of dementia with Lewy bodies other than dementia itself; 4) prominent features of behavioral variant frontotemporal dementia; and 5) evidence for another concurrent comorbidity or use of medication that could have a substantial effect on cognition were excluded.

The clinical diagnosis of MCI was made by experienced neurologists according to the established Petersen criteria [22], including 1) subjective complaints of memory deficits by patient or informant; 2) objective evidence of impairment in one or more cognitive domains, typically including memory; 3) preservation of independence in functional abilities; 4) absence of dementia (CDR≤0.5). Subjects with comorbid depressive disorder were excluded. MMSE and MoCA were the screening tests for cognitive impairment. The cut-off score of MMSE was related to education level (illiterate ≤19, primary school ≤22, and high school ≤26) [23]. MoCA had a cut-off score ≤25, ≤24, and ≤23, respectively, for individuals at 60–79 years old, 80–89 years old, and ≥90 years old [24]. CDR was used to rate severity of cognitive impairment. Those who had no memory complaints and performed within normal range in the MMSE and MoCA tests were grouped as cognitively normal.

PET acquisition and analysis

All subjects were asked to fast for at least 6 h but had free access to water prior to PET scan. PET scans were performed with a Siemens Biograph 64 PET/CT machine (Siemens, Munich, Germany) in three-dimensional mode. PiB-PET and FDG-PET scans were performed according to standardized research protocols [25, 26] at separate sessions. Specifically, a dynamic 90 min emission scan was administered with an intravenous injection of ¹¹C-PiB after 10 min of transmission scan. And an intravenous injection of ¹⁸F-FDG was administered with a 10 min transmission scan followed by a 15 min emission scan. Standardized images were extracted within the regulated interval time after injection. All scans were performed in a dimly lit and quiet room with subjects in a resting state.

The visual ratings were assigned by two experienced radiologists with specific training in the interpretation of PET, who were blind to all clinical information, and the final ratings were decided by consensus. PiB-PET scans were rated as either PiB-PET+ (binding in at least one cortical brain region such as frontal, temporal, parietal, or occipital) or PiB-PET–(no binding or binding predominantly in white matter) [27]. FDG-PET scans were rated as consistent with AD (named FDG-PET+ in our study) when decreased FDG uptake primarily involved the temporoparietal cortex, posterior cingulate/precuneus, or occipital cortex [23, 28]. Representative scans are shown in Fig. 1.

Fig.1

Representative patients clinically diagnosed with AD dementia. Patient 1, female, 65 years old, gradual decline of cognition for two years, MRI suggested brain atrophy, PiB-PET positive, FDG-PET positive. Patient 2, female, 70 years old, gradual decline of cognition for two years, MRI suggested brain atrophy, PiB–PET negative, FDG–PET negative. PiB, ¹¹C-Pittsburgh compound B; FDG, ¹⁸F-fluorodeoxyglucose; SUV, standard uptake value.

Measurements of plasma Aβ and tau

Fast blood was collected between 07 : 00 a.m. and 09 : 00 a.m. to avoid interference from any possible circadian rhythm effects. The blood samples were centrifuged within an hour of collection and EDTA plasma was aliquoted in 0.5 ml polypropylene tubes and stored at –80°C until used. Plasma levels of Aβ₄₂, Aβ₄₀, and T-tau were measured simultaneously using the commercially available single molecule array (SIMOA) Human Neurology 3-Plex A assay kit (Quanterix, Lexington, MA) on-board of the automated SIMOA HD-1 analyzer (Quanterix, Lexington, MA), according to the manufacturer’s instructions [29].

Statistics

Differences between groups were assessed by the two-sample independent t-test, the Mann-Whitney U test, the Chi-squared test, Fisher’s exact test or analysis of variance (ANOVA) according to the characteristics of the data. The data were expressed as the mean±standard deviation (SD) for numerical variables or as the count (%) for categorical variables. The positive rate of PiB-PET and FDG-PET were calculated within different subgroups. We examined the association between plasma biomarkers and amyloid PET using two-sample independent t-test or Mann-Whitney U tests for univariate analysis and using logistic regression models adjusted for age, sex, and APOE genotype status for multivariate analysis. Confidence intervals (CIs) at the 95% level were calculated for the odds ratios (ORs). ROC curves analyses were carried out to evaluate the capacity of biomarkers in discriminating subjects with positive and negative amyloid PET imaging. Optimum cut-off values for each biomarker were defined using the highest Youden’s index (sensitivity+specificity–1).

All hypothesis testing was two-sided, and statistical significance was defined as p < 0.05. All statistical computations were performed using SPSS version 19.0 (SPSS Inc., Chicago, IL, USA), and all figures were created using a graphics package (GraphPad Prism, version 6).

RESULTS

Characteristics of the study subjects

The present study included 53 patients with AD, 22 patients with MCI, and 9 CN individuals (Table 1). There was no significant difference in age, sex, education level, APOE genotype status, plasma Aβ₄₀ and T-tau among the three groups. Plasma Aβ₄₂ in AD subjects was lower than MCI subjects (p < 0.05). The positive percentages of clinical manifestations, including executive dysfunction, impaired language functions, hallucination, impaired visuospatial abilities, brain atrophy, and changes in personality, behavior, or comportment, were significantly higher in AD group than those in MCI and CN subjects (p < 0.05). MMSE, MoCA, CDR, ADL, and POD scores significantly differed between AD and MCI subjects (p < 0.05), as well as between AD and CN subjects (Supplementary Table 1).

Table 1

Demographic and clinical characteristics of study subjects (n = 84)

Clinical diagnosis	AD dementia	MCI	CN
Sample size	53	22	9
Age, y, mean±SD	68.39±9.65	64.60±9.37	61.78±10.52
M/F (% female)	24/29 (57.71)	13/9 (40.91)	4/5 (55.56)
Years of education, mean±SD	10.20±4.20	10.76±4.47	12.50±4.95
APOEɛ4 carriers (%)	50	35.29	37.50
Executive dysfunctions (%)	61.90^§	0	0
Impaired language functions (%)	7.14^§	0	0
Changes in personality, behavior, or comportment (%)	73.81^§	23.53^*	0
Hallucination (%)	9.52^§	0	0
Impaired visuospatial abilities (%)	42.86^§	0	0
Brain atrophy (%)	84^§	57.89^*	22.22
Plasma Aβ₄₂, mean±SD (pg/mL)	8.51±4.35δ	12.90±5.97	8.78±1.85
Plasma Aβ₄₀, mean±SD (pg/mL)	205.77±108.61	261.89±115.52	219.37±19.42
Plasma T-tau, mean±SD (pg/mL)	5.47±2.69	6.68±4.03	4.62±0.50

^§AD dementia > MCI, CN: p < 0.05. ^δAD dementia < MCI: p < 0.05. ^*MCI > CN: p < 0.05. Differences between groups were assessed using ANOVA (age, years of education, plasma Aβ₄₂, plasma Aβ₄₀, plasma T-tau), or Chi-squared tests (sex, clinical manifestations, APOE genotype status). AD, Alzheimer’s disease; MCI, mild cognitive impairment; CN, cognitively normal; M, male; F, female.

PiB-PET and FDG-PET in the study subjects

77.36% of clinically diagnosed AD patients were PiB-PET+, and 81.13% were FDG-PET+ (Fig. 2). In the MCI group, the proportions decreased to 31.8% among PiB-PET+ subjects and 22.7% among FDG-PET+ subjects. In the CN group, the proportions were zero among PiB-PET+ subjects and 22.2% among FDG-PET+ subjects. The concordance between PiB-PET and FDG-PET assessments was 92.86%. These results suggested that 22.64% of probable AD patients diagnosed according to NINCDS-ADRDA criteria were amyloid imaging negative and were actually not AD.

Fig.2

The percentage of PET+ and PET–subjects within each diagnostic subgroup. A) Percentage for PiB–PET assessment. B) Percentage for FDG–PET assessment. ADD, Alzheimer’s disease dementia; MCI, mild cognitive impairment; CN cognitively normal; PiB, ¹¹C-Pittsburgh compound B; FDG, ¹⁸F-fluorodeoxyglucose.

Associations between plasma biomarkers and amyloid PET

We found that PiB-PET+subjects had lower value of Aβ₄₂/Aβ₄₀ ratio than PiB-PET–subjects (0.0425±0.0203 versus 0.0566±0.0231 pg/ml, p < 0.001). After adjustment for age, sex, and APOE ɛ4 status, the association between Aβ₄₂/Aβ₄₀ ratio and PiB-PET remained significant (OR = 0.78, 95% CI: 0.60–1.00) (Table 2).

Table 2

Associations between blood biomarkers and PiB-PET imaging

Biomarkers	PET+ (n = 48, mean±SD)	PET–(n = 36, mean±SD)	p value (univariate)	p value (multivariate)	OR (95% CI)
Aβ₄₂	9.01±4.87	10.91±5.44	0.12	0.15	0.92 (0.82–1.03)
Aβ₄₀	221.76±109.53	219.14±116.15	0.92	0.99	1.00 (0.99–1.00)
T-tau	5.38±2.54	6.48±3.87	0.13	0.18	0.88 (0.73–1.06)
Aβ₄₂/Aβ₄₀	0.0425±0.0203	0.0566±0.0231	<0.001	0.05	0.78 (0.60–1.00)
Aβ₄₂/T-tau	1.75±0.73	2.07±1.09	0.12	0.20	0.65 (0.34–1.26)

p value (univariate), two-sample independent t-test or Mann–Whitney U test; p value (multivariate), logistic regression analysis adjusted by age, sex and APOE genotype status. PiB, ¹¹C-Pittsburgh compound; CI, confidence interval.

Plasma Aβ₄₂/Aβ₄₀ ratio was used to compute ROC curve for PiB-PET status (Fig. 3), and we found an AUC of 0.77 (95% CI: 0.66–0.87). The Youden’s cut-off was 0.0477, with a sensitivity of 82% and specificity of 64%. We further found that plasma Aβ₄₂/Aβ₄₀ ratio could discriminate PiB-PET+ and PiB-PET–probable AD patients, with a sensitivity of 81.81% and specificity of 50%.

Fig.3

ROC curves of plasma Aβ₄₂/Aβ₄₀ ratio for discriminating PiB-PET+ and PiB-PET– subjects. ROC, receiver operating characteristic; AUC, area under the curve.

Associations between clinical manifestations and amyloid PET

Except for the common memory decline symptom, clinical manifestations of AD usually vary. We further analyzed the correlations of amyloid PET with these manifestations (Table 3). Hallucination presentation and impaired language functions were highly associated with PiB-PET positivity respectively with a specificity of 100% and 90.91%. Brain atrophy and changes in personality, behavior or comportment were two important symbols with high sensitivity for PiB-PET result (92.11% and 77.42%, respectively).

Table 3

Associations between clinical manifestations and PiB-PET assessments

	PiB-PET positive, n (%)		Diagnosis accuracy, %
	Symptom positive	Symptom negative	Sensitivity	Specificity
Executive dysfunctions	20 (76.92)	11 (68.75)	64.52	45.45
Impaired language functions	2 (66.67)	29 (74.36)	6.45	90.91
Changes in personality, behavior, or comportment	24 (77.42)	7 (63.64)	77.42	36.36
Hallucination	4 (100)	27 (71.05)	12.90	100.00
Impaired visuospatial abilities	13 (72.22)	18 (75)	41.94	54.55
Brain atrophy	35 (83.33)	3 (37.5)	92.11	41.67
APOEɛ4 positive	19 (86.36)	15 (68.18)	55.88	70

Taking the clinical manifestation as a predictor for PiB-PET positivity, their diagnosis accuracy for PiB-PET status was expressed by sensitivity and specificity. The information of clinical manifestations was missing for 11 subjects.

DISCUSSION

In present study, the probable AD diagnosed according to the 1984 NINCDS-ADRDA criteria had an approximate positive rate of 80% for amyloid PET. Plasma Aβ₄₂/Aβ₄₀ ratio and some clinical manifestations were associated with amyloid PET status.

In the past, limited by expense and availability, the clinical utility of amyloid PET in medical practice required careful definition, which was thought unnecessary for patients with typical AD symptoms [12, 30]. However, based on our present study, the amyloid-positive rate of patients with typical AD symptoms was merely 77.36%, which was consistent with previous studies that the prevalence of amyloid positivity ranging from 65 % to 91.2% [31 –35]. Our low concordance rate between clinical diagnosis and amyloid PET assessment suggests that the diagnosis according to the symptoms had a low accuracy in distinguishing AD from numerous other dementia related diseases, such as frontotemporal dementia, dementia with Lewy bodies, and depressive disorder [36, 37]. These conditions differ greatly in prognosis and therapeutic interventions. Moreover, a polycentric research concluded that proper diagnosis was unavailable to many dementia patients, owing to a lack of memory clinics and dementia clinicians [38]. With the assistance of tools like PET technique, more accurate diagnosis can be achieved. Therefore, it is necessary to use amyloid PET to achieve an accurate AD diagnosis, and the intervention strategies for patients will be more specific and hopeful to generate positive outcomes.

Identification of blood-based biomarkers is critical for the early diagnosis and screening of AD patients. A recent study has reported that plasma Aβ₄₂/Aβ₄₀ ratio can serve as a pre-screener for AD pathological changes [39]. Another study also proposed a set of plasma biomarkers, comprising the APP669–711/Aβ₄₂ and Aβ_40/42 ratios and their composites, can predict AD amyloid burden with high sensitivity and specificity [40]. Consistently, plasma Aβ₄₂/Aβ₄₀ ratio was associated with PiB-PET in present study, suggesting that plasma Aβ₄₂/Aβ₄₀ ratio is a potential biomarker to reflect brain amyloid burden.

Exploring the relationship between clinical manifestations and amyloid PET status also attaches great importance. It can be helpful to improve the diagnosis accuracy. In our study, AD patients with hallucination presentation were totally PiB-PET positive. Impaired language functions, brain atrophy, and changes in personality, behavior, or comportment are also associated with PiB-PET assessment. Useful hints for making an accurate AD diagnosis in clinical practice can be provided when no PET assessment is available.

MCI is heterogeneous in terms of clinical appearance, etiology, and prognosis [41]. Concordance between clinical MCI diagnosis and amyloid PET assessments was low in our study, implying the heterozygous pathogenesis of these patients. The previous studies showed a significant proportion of MCI patients do not progress to AD and a subgroup even reverts to normal cognition [42, 43]. In our study, 31.80% of MCI patients were PiB-PET positive, suggesting that biomarker assessment is necessary for making an accurate diagnosis at the prodromal stage of AD.

Our study has several strengths. First, this is the first research exploring the amyloid positivity of AD patients in a Chinese population. Second, data on the relationships between plasma Aβ₄₂, Aβ₄₀, T-tau, and amyloid pathology were limited, our research provided an evidence to illustrate this problem. The study also has several limitations. First, the sample size of our cohort is small, especially CN subjects, replication of our findings in a larger cohort would help to validate our findings. Besides, as clinical AD trials of potentially disease-modifying therapy toward asymptomatic stage individuals may be more promising [44], a larger sample is needed to explore the positive percent of amyloid deposition in CN individuals in the future. Second, our ratings for PET were restricted to visual assessments, which were less accurate than quantitative readouts, deviation and considerable overlap can hardly avoid; a quantitative readout in the future would give us more detailed and accurate information about the association of amyloid PET with disease biomarkers and manifestations.

In summary, our findings indicate that only three-fourths of patients diagnosed with probable AD in our routine clinical practice fit the pathological criteria, suggesting that we should be cautious in diagnosing AD when no biomarker evidence is available.

Footnotes

ACKNOWLEDGMENTS

This study was supported by the Chinese Ministry of Science and Technology (grant no.2016YFC1306401).

Authors’ disclosures available online ().

The supplementary material is available in the electronic version of this article: .

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