Association of Subjective Cognitive Decline with Cerebrospinal Fluid Biomarkers of Alzheimer’s Disease Pathology in Cognitively Intact Older Adults: The CABLE Study

Abstract

Background:

Subjective cognitive decline (SCD) might occur at the early stages of dementia. Individuals with SCD have an increased risk of subsequent objective cognitive decline and greater rates of progression to dementia.

Objective:

We aimed to explore the associations between SCD and cerebrospinal fluid (CSF) biomarkers of Alzheimer’s disease (AD) pathology in cognitively normal individuals.

Methods:

A total of 1,099 cognitively normal elders with available data on CSF biomarkers of AD pathology (Aβ₄₂, P-tau, and T-tau) were included in our analysis. Linear regression was used to examine the associations of SCD status and SCD severity with CSF biomarkers. Additionally, a review was conducted to discuss the associations between SCD and CSF biomarkers of AD pathology.

Results:

After adjustments for covariates, SCD and SCD severity showed significant associations with CSF Aβ₄₂ (SCD: β= –0.0003, p = 0.0263; SCD severity: β= –0.0004, p = 0.0046), CSF T-tau/Aβ₄₂ ratio (SCD: β= 0.1080, p = 0.0064; SCD severity: β= 0.1129, p = 0.0009) and CSF P-tau/Aβ₄₂ ratio (SCD: β= 0.0167, p = 0.0103; SCD severity: β= 0.0193, p = 0.0006) rather than T-tau and P-tau compared with cognitively normal individuals. In the review, a total of 28 studies were finally included after reviewing 174 articles. CSF Aβ₄₂ was lower in SCD than cognitively normal (CN) individuals, but higher than those with objective cognitive decline. However, CSF tau pathology showed no difference between SCD and CN.

Conclusion:

The results indicated that pathophysiological changes in CSF Aβ pathology occurred in individuals with SCD, which provide new insights into early intervention of AD.

Keywords

Alzheimer’s disease cerebrospinal fluid biomarker subjective cognitive decline

INTRODUCTION

The global prevalence of dementia continues to increase. As the main cause of dementia, Alzheimer’s disease (AD) is a great health challenge. AD is considered to be the accumulation of neuropathological changes. Therefore, AD could be defined in vivo by biomarkers and by postmortem examination [1]. However, cerebrospinal fluid (CSF) is in direct contact with the extracellular space of the brain, and it can reflect biochemical changes in AD brain. Therefore, CSF is the optimum source of AD biomarkers. CSF biomarkers of AD pathology which can reflect the main neuropathological hallmarks include low levels of amyloid-β (Aβ) and high levels of tau (T-tau) and phosphorylated tau (P-tau) [2]. Previous studies showed that AD-related pathophysiologies begin a decade or more before the onset of objective cognitive impairment and that drug with the potential to modify the progression of AD were most effective in the early disease process. Therefore, current research is increasingly focusing on the early phase of AD [3].

After International Working Group (IWG) [4] and the National Institute of Aging and Alzheimer’s Association (NIA–AA) acknowledged a long pre-dementia stage in their new criteria for diagnosis, the term subjective cognitive decline (SCD) has received increasing attention [5 –7]. SCD is defined as individuals who experience a subjective decrease in cognitive function without evidence of objective cognitive impairment in neuropsychological testing [8], and it can indicate preclinical AD [9]. SCD participants showed a higher conversion rate and shorter conversion time to mild cognitive impairment (MCI) and dementia than cognitively intact individuals [10]. A prospective cohort study observed abnormal levels of CSF biomarkers of AD pathology in SCD participants [11]. Although CSF biomarkers of AD pathology have been extensively investigated in many studies [12], there is still a lack of research on the associations between SCD and CSF biomarkers of AD pathology. With the rapidly growing number of SCD individuals who seek medical help, investigating the association between AD-related pathology and SCD is warranted, providing new insights into early intervention for AD.

This study examined the associations between SCD and CSF biomarkers of AD pathology in cognitively normal individuals from the Chinese Alzhei-mer’s Biomarker and LifestylE (CABLE) study.

MATERIALS AND METHODS

Participants

A total of 1,099 participants were included from the CABLE study. The CABLE study is an ongoing large-scale cohort study initiated in 2017, mainly focusing on risk factors and biomarkers for AD in the non-demented northern Chinese Han population [13]. The exclusion criteria include: 1) central nervous system infection, head trauma, multiple sclerosis, or other major neurological disorders; 2) major psychological disorders; 3) severe systemic diseases that may affect CSF or blood levels of AD biomarkers including Aβ and tau; 4) family history of genetic diseases. All participants underwent comprehensive clinical, neuropsychological, psychosocial, and psychiatric evaluations, as well as blood and CSF sample collection. Demographic information was also confirmed by the electronic medical record system, and the laboratory inspection management system. The objective cognition of participants was tested by Chinese-modified Mini-Mental State Examination (CM-MMSE) and Montreal Cognitive Assessment (MoCA), and subjective cognition was tested by a subjective cognitive decline scale (SCDS). All the cognitive diagnoses were in compliance with the NIA-AA workgroup diagnostic criteria [14, 15]. Psychological symptoms were assessed by Hamilton Rating Scale for Depression (HAMD) and Hamilton Rating Scale for Anxiety (HAMA). To exclude individuals with objective cognitive impairment, we used the various cutoff values in MMSE (≤24 for more than 6 years of education, ≤20 for 1–6 years of education, ≤17 for 0 year of education), MoCA (< 24 for more than 12 years of education, < 22 for 7–12 years of education, < 19 for < 7 years of education), HAMD (≤7), and HAMA (≤7). The design of the CABLE database was in accordance with the Helsinki Declaration and was approved by the Institutional Ethics Committee of Qingdao Municipal Hospital. Participants signed an informed consent form after being fully informed.

A total of 1,256 cognitively normal participants from CABLE had available information. Among them, 157 participants with data outside 4 standard deviations (SD) were removed. Finally, this study included 1,099 cognitively normal individuals with complete information on demographic characteristics and at least one kind of AD bio-markers.

CSF biomarkers

CSF samples were collected within 2 h after lumbar puncture at room temperature. All the samples were separated into enzyme-free EP (Eppendorf) tubes (AXYGEN; PCR-02-C) after centrifuging at 2000×g for 10 min. Samples were stored at –80°C and were subjected to a maximum of two freeze-thaw cycles. CSF biomarkers of AD pathology (Aβ₄₂, T-tau, and P-tau levels) were measured by enzyme-linked immunosorbent assays (ELISAs) using INNOTEST (Fujirebio Europe N.V.). Each sample was measured in duplicate. All the antibodies and plates were from a single lot to exclude variability between batches. Moreover, the within-batch CV was < 5% and the inter-batch CV was < 15%.

APOE gene

Status of apolipoprotein E (APOE) gene was identified by the DNA in the blood samples, which were drawn after a fasting period of at least 12 h. Samples were separated and stored in an enzyme-free EP tube at –80°C until the APOE genotyping. QIAamp ® DNA Blood Mini Kit (250) was used to extract DNA from blood samples. Two specific loci (rs7412 and rs429358) of APOE were genotyped using the SNaPshot SNP assay. Individuals with at least one copy of the APOE ɛ4 gene were considered to be carriers.

Assessment of SCD

In this study, we used two assessment methods to describe subjective cognitive function: classification of SCD status and continuous indicators of SCD severity. Information was collected through the SCDS (see Supplementary Methods), a questionnaire for SCD which was based on SCD-I recommendations [16, 17]. Participants were considered to have SCD if they answered “yes” for the question “Do you think your memory is declining compared to what it used to be?” To reflect the severity of SCD, a continuous SCD scale was used. Adopting the form of Likert Scale and combining with Top nine SCD items [18], we adapted the Subjective Memory Decline Scale [19]. The adapted scale allowed every subject to score 0–2 points for each question and the greatest total score for 6 questions in the questionnaire was 12 points. A higher total score reflected more serious SCD. Finally, individuals with cognitive decline due to other diseases or drug abuse were excluded from our study.

Covariates

Demographic information included age (continuous), sex (male or female), and years of education (continuous). Data on cardiovascular risk factors and unhealthy lifestyles were also collected, including hypertension, diabetes mellitus, coronary disease, smoking status, and alcohol status. The data of all covariates were collected from the questionnaire by well-trained physicians. All the information was confirmed by electronic medical record system in Qingdao Municipal Hospital.

Statistical analysis

CSF biomarker values outside the mean±4 SD were regarded as extremes and were excluded in the analysis. Continuous variables were described as mean±SD and categorical variables were described as number (percentage). Wilcoxon test and Chi-square test were used to analyze the differences between CN and SCD groups. False discovery rate (q value) was used to adjust for multiple comparisons. Values of CSF biomarkers (Aβ₄₂, P-tau, and T-tau) did not follow a normal distribution as assessed by Shapiro-Wilk normality test (p < 0.001). Therefore, they were transformed via “car” package of R software to obtain a normal distribution. All the statistical analyses were performed on the transformed values. Linear regression analyses examined 1) crude (without adjustment), 2) demographic factors-adjusted (age, sex, years of education, and APOE ɛ4 status), 3) fully adjusted (demographic factors, cardiovascular risk factors and unhealthy lifestyles) associations among SCD (status and severity) and CSF biomarkers of AD pathology. Interaction analyses were performed in order to examine the modifying effects of age, sex, years of education, and APOE ɛ4 genotype on the associations between SCD and CSF biomarkers of AD pathology. A two-tailed p < 0.05 was considered significant. All statistical analyses were conducted using the R statistical software (version 3.6.1).

Selection criteria and search strategy for review

To determine whether SCD was associated with CSF biomarkers of AD pathology, our review considered studies including participants with different cognitive condition and the associations with CSF biomarkers of AD pathology. We did not put any limits on population. The flow diagram (Supplementary Figure 1) outlined the search and retrieval process. The exclusion criteria include: studies without healthy controls, studies without a definition for SCD, and studies without a description of associations between SCD and CSF biomarkers of AD pathology in the result.

We searched in PubMed using the strategy: “SCD”[All Fields] OR “subjective cognitive decline”[All Fields] OR “subjective cognitive impairment”[All Fields] OR “subjective memory impairment”[All Fields] OR “subjective memory decline”[All Fields] OR “cognitive complaints”[All Fields] OR “memory complaints”[All Fields] OR “cognitive concerns”[All Fields] OR “memory concerns”[All Fields]) AND (((“alzheimer disease”[MeSH Terms] OR (“alzheimer”[All Fields] AND “disease”[All Fields]) OR “alzheimer”[All Fields] OR “dementia”[All Fields]) AND ((“biological”[All Fields] AND “markers”[All Fields]) OR “biomarker”[All Fields] OR “CSF”[All Fields])) OR “cerebrospinal”[All Fields]) AND (“Abeta42”[All Fields] OR “abeta 42”[All Fields] OR “Abeta42”[All Fields] OR “abeta 42”[All Fields] OR “tau”[All Fields] till 26 April 2021. In case of omission, we hand-searched the bibliographies of relevant original studies and systematic reviews.

RESULTS

Characteristics of participants

The demographic and clinical characteristics of the whole study population are shown in Table 1. A total of 1,099 cognitively normal elders from the CABLE study were included in analysis, consisting of 655 cognitively normal (CN) participants as control and 444 SCD participants. They had a mean CM-MMSE score of 27.94±2.12. The average age of the target population was 61.85 years (±10.33); 59.96% were male. The average years of education was 9.79 (±4.29). There were 38.03%, 84.80%, and 13.47% of the participants diagnosed with hypertension, diabetes, and coronary disease, respectively. There were 30.30% and 30.03% of the participants having the habit of smoking and the habit of drinking, respectively. Significant differences were found in age, sex, as well as the frequencies of hypertension and diabetes between SCD and CN group.

Table 1

Characteristic of participants

Variable	CN (n = 655)	SCD (n = 444)	Total (n = 1,099)	p	q
Age (y)	60.50±10.32	63.85±10.03	61.85±10.33	< 0.01	< 0.01
Sex (male)	414 (63.21%)	245 (55.18%)	659 (59.96%)	0.01	0.03
Education (y)	9.86±4.30	9.68±4.29	9.79±4.29	0.63	0.64
APOE ɛ4 carrier	92 (14.05%)	69 (15.54%)	161 (14.65%)	0.55	0.59
CM-MMSE score	28.03±2.09	27.82±2.16	27.94±2.12	0.05	0.09
SCD severity scale	0.11±0.49	2.20±2.05	1.21±1.85	< 0.01	< 0.01
Hypertension (yes)	229 (34.96%)	189 (42.57%)	418 (38.03%)	0.01	0.03
Diabetes mellitus (yes)	571 (87.18%)	361 (81.31%)	932 (84.80%)	< 0.01	0.01
Coronary disease (yes)	80 (12.21%)	68 (15.32%)	148 (13.47%)	0.17	0.21
Smoking (yes)	205 (31.30%)	128 (28.83%)	333 (30.30%)	0.39	0.45
Alcohol (yes)	209 (31.91%)	121 (27.25%)	330 (30.03%)	0.11	0.15
CSF biomarkers (pg/mL)
Aβ₄₂	192.53±104.79	181.84±98.02	188.21±102.20	0.03	0.07
P-tau	36.48±8.90	37.67±9.66	36.96±9.23	0.10	0.14
T-tau	166.67±69.66	180.15±87.23	172.12±77.49	0.05	0.09

Continuous variables are presented as mean±SD and categorical variables as number (percentage). CN, cognitive normal; SCD, subjective cognitive decline; CM-MMSE, Chinese-modified Mini-Mental State Examination; APOE ɛ4, apolipoprotein E ɛ4; CSF, cerebrospinal fluid; Aβ, amyloid- β; P-tau, phosphorylated-tau; T-tau, total-tau. Differences between two groups were analyzed by Chi-square tests for categorical variables and Wilcoxon tests for numerical variables. q, significance after false discovery rate (FDR) correction.

Associations between SCD and CSF biomarkers of AD pathology

The associations between SCD and CSF biomarkers of AD pathology are shown in Fig. 1 and Supplementary Table 1. Compared to individuals without SCD, individuals with SCD were found to be associated with lower Aβ₄₂ (β=-0.0003, p = 0.0320) as well as higher levels of T-tau (β= 0.0003, p = 0.0242), T-tau/Aβ₄₂ ratio (β= 0.1597, p = 0.0001) and P-tau/Aβ₄₂ ratio (β= 0.0221, p = 0.0006) in crude model. After adjusting for demographic factors, significant associations were found of SCD with lower Aβ₄₂ (β= –0.0004, p = 0.0219), greater T-tau/Aβ₄₂ ratio (β= 0.1081, p = 0.0065) and greater P-tau/Aβ₄₂ ratio (β= 0.0170, p = 0.0086). And these associations remained significant even after adjustment for all the covariates (CSF Aβ₄₂: β= –0.0003, p = 0.0263; CSF T-tau/Aβ₄₂ ratio: β= 0.1080, p = 0.0064 and CSF P-tau/Aβ₄₂ ratio: β= 0.0167, p = 0.0103).

As for the associations between SCD severity and CSF biomarkers, all the biomarkers were associated with the severity of SCD in the crude model (Supplementary Table 1). After adjusting for demographic factors, only lower Aβ₄₂ levels (β= –0.0004, p = 0.0056), higher T-tau/Aβ₄₂ ratio (β= 0.1118, p = 0.0011) and higher P-tau/Aβ₄₂ ratio (β= 0.0190, p = 0.0006) were associated with the severity of SCD. And these associations remained significant even after adjustment for all the covariates (CSF Aβ₄₂: β= –0.0004, p = 0.0046), CSF T-tau/Aβ₄₂ ratio: β= 0.1129, p = 0.0009) and CSF P-tau/Aβ₄₂ ratio: β= 0.0193, p = 0.0006)).

Interaction analysis suggested that the associations were not affected by age, sex, years of education, and APOE ɛ4 status (Supplementary Table 2).

Fig. 1

Associations of SCD with CSF biomarkers of AD pathology. The results of linear regression models (A). SCD participants had lower level of Aβ₄₂ (B), higher T-tau/Aβ₄₂ ratio (C) and higher P-tau/Aβ₄₂ ratio (D) compared with those without SCD. CN, cognitive normal; SCD, subjective cognitive decline; CSF, cerebrospinal fluid; Aβ, amyloid-β; P-tau, phosphorylated-tau; T-tau, total-tau. M1, Crude model; M2, Demographic factors-adjusted model; M3, Fully adjusted model. Demographic factors include age, sex, years of education, and APOE ɛ4 status. The fully adjusted model includes demographic factors, cardiovascular risk factors (hypertension, diabetes mellitus and coronary disease), and unhealthy lifestyles (smoking and alcohol status). ^*p < 0.05.

Results of review

The flow diagrams of the study selection process were shown in Supplementary Figure 1. The search included 174 studies from PubMed. A total of 72 studies were considered to be potentially eligible after reviewing titles and abstracts. And 47 studies were excluded after reviewing full texts. Adding two studies from previous systematic reviews, a total of 28 studies were finally included (Supplementary Table 3).

Most of the studies were conducted in European countries (82.14%) (except five in America and one in South Korea). The study population size ranged from 28 to 993, and the cognitive status of participants ranged from normal to AD. There were 11 studies (39.29%) with a sample size of more than 100. There were ten longitudinal studies (35.71%) with the longest follow-up of five years.

Eighteen studies (64.29%) showing CSF Aβ₄₂ was associated with SCD, and three studies (10.71%) found no relationship between CSF Aβ₄₂ and SCD. As for CSF tau pathology, eight studies (28.57%) found no difference between SCD and CN groups. However, 11 studies (39.29%) showed individuals with SCD had lower CSF tau than those with MCI.

DISCUSSION

This study examined the associations between SCD and CSF biomarkers of AD pathology in 1099 cognitively intact older adults. SCD was found associated with CSF Aβ-related biomarkers (lower Aβ₄₂, higher T-tau/Aβ₄₂ ratio and higher P-tau/Aβ₄₂ ratio). However, no relationship was found between SCD and tau pathology (neither T-tau alone nor P-tau alone). These findings were consistent with that of a previous cohort study showing that SCD was associated with Aβ₄₂ levels but not with tau levels among cognitively normal participants [18 –22].

Our study showed that Aβ₄₂ was lower in SCD group than that in CN group, indicating abnormal metabolism of Aβ in SCD. We further found that SCD was positively associated with Aβ pathology. Although CSF biomarkers of AD pathology tended to be more normal in SCD compared with AD or MCI [22 –30], a study found that in participants with SCD, a lower but still normal CSF Aβ₄₂ level was associated with faster cognitive decline after a median follow-up of 2.3 years [31]. Individuals with SCD showed amyloid deposition in the brain, but these pathological changes were not sufficient enough to affect objective cognition. To predict the clinical progression of SCD [32] and improve the diagnostic accuracy of AD [33], we combined Aβ and tau to explore the relationships between SCD and their ratios, showing SCD was associated with greater T-tau/Aβ₄₂ ratio and greater P-tau/Aβ₄₂ ratio. All the above results indicated that individuals with SCD had Aβ pathological changes.

However, we could not detect any statistically significant association of SCD with tau pathology (neither T-tau alone nor P-tau alone) in the present study. Consistent with the above findings, a previous multicenter cohort study, Neurodegenerative Diseases (DZNE)-Longitudinal Cognitive Impairment and Dementia Study (DELCODE), found that there were no differences in Tau or P-tau concentrations between SCD and CN groups [20] and that quantitative SCD scores were not associated with total Tau or P-tau [21]. Liguori et al. included patients affected by SCD, MCI, mild AD, and moderate-to-severe AD in a study along with CN subjects as controls and found that CSF T-tau and P-tau levels did not differ between SCD and CN groups [22].

Our analysis showed that SCD was related to CSF Aβ pathology but not tau pathology, which was consistent with the result of our review. The level of CSF Aβ₄₂ in SCD group was lower than CN group and higher than those with objective cognitive decline. CSF tau level in SCD group showed no significant difference compared with CN but was lower than that in individuals with objective cognitive decline. In pathological process of AD, low CSF Aβ₄₂ is a marker of Aβ deposition in the brain and can occur more than 10 years before the appearance of objective cognitive symptoms. Aβ is thought to be the trigger, or even the driver of the disease process [34]. Tau pathology, a downstream event of Aβ deposition in amyloid hypothesis [35], often occurs in the middle and late stages of the disease and is closely related to objective cognitive decline.

In the review, three studies showed that no significant relationship was found between CSF Aβ₄₂ and SCD [36 –38], which was inconsistent with our result. But sample size of these three studies were less than 100 (28, 43 and 84 respectively). What’s more, two studies of them were conducted in America. Our study was conducted in Chinese Han population; most of the studies included in review were conducted in Europe countries. Therefore, the heterogeneity of population should be taken into account. At the same time, different studies have different objectives and available methods and measures. Lack of standard assessment tools and thresholds or cutoffs to distinguish SCD effectively seems to be disadvantages for promotion of consistency across sites, while the variability of SCD operationalization continues to increase scientific understanding of SCD [15]. Our review found that most of the current studies on the association between SCD and CSF biomarker of AD pathology are cross-sectional studies. In the future, cross-sectional with large sample size and longitudinal studies are needed to provide more convincing and high-quality evidence for the association between SCD and CSF biomarker of AD pathology.

Our study explored the associations between SCD and CSF biomarkers of AD pathology in a large population. To enhance the reliability, two items (the status of SCD and the severity of SCD) were used, and similar positive results were obtained on their associations with CSF biomarkers of AD pathology. However, some limitations exist in our study. Firstly, this was a cross-sectional study which could not elucidate the associations between CSF biomarkers and cognitive changes and how the disease evolved. Secondly, our study was conducted in Han Chinese population. The findings should be replicated in other racial or ethnic groups in the future.

In conclusion, our study explored the associations between SCD and CSF biomarkers of AD pathology. We found SCD was associated with CSF Aβ-related biomarkers (lower Aβ₄₂, higher T-tau/Aβ₄₂ ratio and higher P-tau/Aβ₄₂ ratio) but not with tau pathology (neither T-tau alone nor P-tau alone) compared with CN. The results indicate that pathophysiological changes have already occurred in SCD, but the changes are still minor to affect objective cognition as assessed by questionnaires. Changes in CSF biomarkers of AD pathology began earlier than expected, which provided new clues to early identification of subjects in the preclinical stage of AD.

Footnotes

ACKNOWLEDGMENTS

The authors thank all participants of the present study as well as all members of staff of the CABLE study for their role in data collection. This study was supported by grants from the National Natural Science Foundation of China (91849126), the National Key R&D Program of China (2018YFC1314700), Shanghai Municipal Science and Technology Major Project (No.2018SHZDZX01), ZJLab, Shanghai Center for Brain Science and Brain-Inspired Technology, Tianqiao and Chrissy Chen Institute, and the State Key Laboratory of Neurobiology and Frontiers Center for Brain Science of Ministry of Education, Fudan University.

Authors’ disclosures available online ().

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

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