Association of plasma BDNF and MMP-9 levels with mild cognitive impairment: a matched case-control study

Abstract

The prevalence of Alzheimer’s disease (AD) is on the rise globally, and everyone who develops AD eventually experiences mild cognitive impairment (MCI) first. Timely intervention at an early stage of the disease may mitigate disease progression. Recent studies indicate that BDNF and MMP-9 play a significant role in the pathogenesis of AD. Therefore, this study aims to ascertain whether there are differences in plasma BDNF and MMP-9 levels between individuals with mild cognitive impairment due to AD and those with normal cognition, and to analyze the factors influencing mild cognitive impairment.This case-control study included 102 individuals with mild cognitive impairment and 102 controls, matched by age and sex. Participants completed a series of questionnaires, neuropsychological assessments, and clinical examinations. Plasma concentrations of BDNF and MMP-9 of the participants were quantified using ELISA. Subsequently, the factors influencing MCI were analyzed using univariate and multivariate logistic regression. The differences in plasma BDNF levels, MOCA total scores, and scores in various cognitive domains (including visuospatial and executive abilities, abstract thinking, attention, language, naming, and delayed memory) between the MCI and the control groups showed statistically significant (p < 0.05). Logistic regression analysis revealed that plasma BDNF levels and years of formal education were significantly negatively associated with MCI. This study indicates that plasma BDNF and years of formal education are protective factors influencing cognitive function.

Introduction

Alzheimer’s disease (AD), the leading cause of dementia, is a prevalent, incurable neurodegenerative disorder characterized by progressive declines in memory, language, and thinking¹. As of 2020, approximately 35 million people worldwide are affected by Alzheimer’s disease, with that figure expected to rise to 152 million by 2050². Studies have indicated that although the rate of progression varies among individuals, the life expectancy with a diagnosis of AD is three to nine years. As the disease develops, people lose physical function and, eventually, their lives^3,4. There are three phases of AD: preclinical AD, mild cognitive impairment (MCI) due to Alzheimer’s disease, and dementia due to AD^1,5,6. MCI, a state that exists between normal cognition and early dementia^7,8, is used to describe a collection of individuals who have some cognitive impairment but its severity is insufficient to meet the criteria for dementia⁹. Everyone who develops AD eventually experiences MCI first¹. A cross-sectional research found that 60–100% of people with MCI develop AD within 5–10 years¹⁰, and early intervention at this time has the potential to mitigate disease progression^11–13.

The diagnosis of MCI typically involves a combination of cognitive tests and a comprehensive clinical assessment, primarily based on the established gold standard, Petersen’s criteria. In 2024, the Alzheimer’s Association (AA) propose that the following can be diagnostic of AD: amyloid PET; CSF Aβ 42/40, CSF p-tau 181/Aβ 42, CSF t-tau/Aβ 42; or plasma p-tau 217. These biomarkers and their integrated model also function as an effective tool for early screening of MCI due to AD^5,9,13, with plasma p-tau217 being a particularly promising measure for early diagnosis¹⁴. However, previous studies indicate that p-tau217 isn’t the end of the search for biomarkers, more blood biomarkers are needed to monitor disease progression and to assess the brain’s response to treatments targeting different aspects of the disease. For example, some proteins can indicate the speed of cognitive decline^15,16. Previous studies found that cognitive impairment in AD is attributable to neurodegeneration¹⁷. Meanwhile, several research groups have shown some non-Aβ and non-tau markers as candidates for neurodegeneration, with brain-derived neurotrophic factor (BDNF) as one example¹⁸.

BDNF is a neurotrophic signaling molecule that promotes neuronal growth, synaptic plasticity, and synapse maturation during development^7,19. It is widely expressed in the brain, can cross the blood-brain barrier, and is thus detectable in the blood. BDNF regulates cognition and memory by promoting neurogenesis and synaptic growth, enhancing neurotransmission across synapses, and modulating synaptic plasticity. Recent studies indicate that BDNF plays a significant role in the pathogenesis of AD^20,21. Significantly decreased peripheral brain-derived neurotrophic factor (BDNF), which occurs at the early stage of AD, can result in the degeneration and progressive atrophy of specific neuronal populations in the brain. This process is associated with the severity of cognitive dysfunction, indicating that diminished BDNF levels may be a contributing factor to neuronal dysfunction during the development of AD. BDNF may serve as a potential target for AD intervention to slow down the progression of neurodegeneration¹⁷. However, previous studies on plasma BDNF levels in AD and MCI patients have conflicting results^2,11. It is therefore essential to gain a deeper understanding of the role of BDNF in differentiating MCI due to AD from normal cognitive decline²⁰. Besides, risk factors for cognitive impairment, such as age, lifestyle, and physical conditions, associated with plasma BDNF levels as the disease progresses are still unknown¹⁷. Matrix metalloproteinase-9 (MMP-9) is an enzyme crucial for synaptic plasticity, learning and memory, and brain development²². MMP-9 has multiple physiological functions, including tissue remodeling, cell migration, cellular differentiation, and axon regeneration²³. MMP-9 is involved in the conversion of pro-brain-derived neurotrophic factor (proBDNF) to mature BDNF (mBDNF)^24,25. Notably, the balance of pro-BDNF and mBDNF is important for cell survival and synaptic plasticity. Studies have reported higher plasma MMP-9 levels in mild cognitive impairment (MCI) and Alzheimer’s disease (AD)²⁶, meaning MMP-9 may be potentially associated with the pathology of neurodegeneration.

The study aimed to investigate potential variances in plasma BDNF and MMP-9 levels between individuals with mild cognitive impairment and those with normal cognitive function. In addition, it endeavored to examine the correlations between BDNF and MMP-9 and to identify the factors influencing the prevalence of MCI. If patients with AD can be identified in the MCI stage or potentially pre-symptomatic stage through biomarker testing, rational clinical interventions—such as lifestyle modifications, including adherence to regular exercise, a Mediterranean diet and engagement in meaningful mental stimulation and intellectual activities—can be implemented before significant cognitive impairment develops^3,13.

Materials and methods

Sample size calculation

This case-control study matched participants in a 1:1 ratio based on sex and age (with a matching tolerance of 0 and ± 5 years)⁴. As indicated in the existing literature, the estimated prevalence of mild cognitive impairment (MCI) is 20.20%²⁷. The test efficacy was set at 0.80, with an alpha of 0.05, by the methodology outlined, which resulted in a minimum sample size of n = 63.

Participants and Inclusion/exclusion criteria

The case and control group for this study were recruited from patients who visited the Department of Neurology and the Department of Cardiology at the hospital between December 2023 and June 2024. All participants received a standard diagnostic workup including comprehensive neuropsychological examination, neurological evaluations, and magnetic resonance imaging (MRI), with two clinicians assisting in the clinical diagnosis. To be included in the case group, participants were required to meet the following criteria: (1) Age ≥ 50 years; (2) Fulfillment of the diagnostic criteria for MCI due to AD (based on Petersen’s criteria²⁸ and NIA-AA 2011 criteria⁵: (i) Memory complaint at least 3 months; (ii) MOCA scale scores between 15 and 23; (iii) Not demented; (iv) Normal activities of daily living, as indicated by a Clinical Dementia Rating (CDR) score of ≤ 0.5, Activity of Daily Living Scale (ADL) scores ≤ 16, and Modified Hachinski ischemia scale scores ≤ 4 points; ) (3) Voluntarily participated in and agreed to complete this program actively. To be included in the control group (CG), individuals were required to meet the following criteria: (1) Age differences ≤ five years from the matched cases; (2) Normal activities of daily living; (3) MoCA scores ≥ 24 and normal general cognitive function; (4) No family history of dementia. The ethics committees of Shihezi People’s Hospital approved the study. All participants were informed about the aims and methods of the study and provided their written informed consent.

Exclusion criteria

The exclusion criteria were as follows: (1) a diagnosis of dementia; (2) People with cognitive impairment attributable to other well-defined etiologies, for instance, stroke, epilepsy, Parkinson’s disease, vascular dementia, traumatic brain injury, or severe brain vascular burden (Fazekas > 2 on MRI); (3) People with severe psychiatric disorders or profound visual and auditory impairments that significantly hinder normal communication⁴.

Questionnaire survey

The questionnaire utilized in this study encompasses the following elements: (1) Basic Information: gender, age, height, weight, marital status, education level, occupational status, place of residence, and others. (2) Lifestyle factors: smoking, alcohol consumption, dietary habits, physical activity, sleep patterns, intellectual activities, and other health-related behaviors. (3) Chronic disease information: diseases and family history of diseases, including hypertension, diabetes, coronary heart disease (CHD), hyperlipidemia, anemia, cerebral infarction, cerebral hemorrhage, traumatic brain injury, intracranial infections, CO poisoning, epilepsy, Parkinson’s disease, psychiatric disorders, and abnormal thyroid function, as well as history of medication use^4,13,29. (4) Subjective cognition: cognitive impairment, memory issues, language challenges, organizational skills, and attention problems. Participants were asked to report their disease status and duration themselves.

Cognitive assessments

Assessment of cognitive function

The Montreal Cognitive Assessment Beijing Version (MoCA-BJ) scale is a validated cognitive screening test with a total score of 30, which can differentiate between normal cognition, MCI, mild and moderate AD in Chinese older adults with varying levels of education³⁰. The MoCA-BJ was administered on the day of admission to evaluate the patients’ seven cognitive domains, including visuospatial and executive abilities (5 points), attention (6 points), naming (3 points), abstract thinking (2 points), language (3 points), delayed memory (5 points), orientation (6 points), with transient memory being not scored. The final scores were augmented by one point if the participants had completed ≤ 12 years of formal education. Scores ≥ 24 indicate normal cognition, and 15–23 indicate mild cognitive impairment^31,32.

Assessment of dementia symptoms

The Clinical Dementia Rating Scale (CDR) scale was employed to evaluate the presence and severity of dementia in the subjects under investigation. The assessment encompassed six domains, including memory, judgment, problem-solving abilities, orientation, social functioning, and other pertinent domains. A comprehensive rating was made based on the scores of each dimension after communication with the patients, who were determined to be cognitively normal (0 point), suspected of having dementia (0.5 points), exhibiting mild dementia (1 point), moderate dementia (2 points), and severe dementia (3 points)^32,33.

Assessment of daily living capacity

The Activity of Daily Living Scale (ADL) scale was used to determine the disability of older adults, consisting of 14 items: dressing, bathing, eating, using the bathroom, controlling urination, and so on. Points from 1 to 4 are assigned for each item, with one point indicating normal ability, and the total score ranges from 14 to 56. Scores ≤ 16 reflect complete normalcy, while ≥ 22 indicate severe impairment³⁴.

Assessment of depressive symptoms

The Geriatric Depression Scale consists of 30 questions. A response of “yes” earns 1 point, while a response of “no” receives no score, resulting in a maximum score of 30. A score of 0–10 indicates no depression or anxiety symptoms, 11–20 indicates mild depression and 21–30 indicates moderate depression.

Biochemical testing

Within 36 h of the patient’s admission to the hospital, 5 ml of fasting venous blood was collected in the early morning and placed into an EDTA anticoagulation blood collection tube. The tube was then kept at room temperature for two hours and subsequently centrifuged at low temperature (4℃, 3000 r/min, 10 min)⁴. The supernatant was transferred into clean EP tubes and stored at -80℃. The levels of BDNF and MMP-9 were quantified using an enzyme-linked immunosorbent assay (ELISA), with the procedure conducted by the provided instructions. The BDNF and MMP-9 kits were procured from Shanghai Jianglai Biotechnology Company.

Statistical analysis

The statistical analysis was conducted using SPSS v.25.0. Continuous normally distributed data were presented as mean ± standard deviation (SD) and compared with independent samples Student’s t-test. Non-normally distributed data were expressed as median (P25, P75) and compared with Mann-Whitney U test. For discrete variables number of patients and percentages are given, and compared using the χ² or Fisher exact test. Linear regression models were used to test for an interaction between plasma BDNF and MMP-9 levels. Univariate and multivariate logistic regression were used to analyze the factors influencing the development of MCI. A p-value ≤ 0.05 was considered significant.

Results

General demographic characteristics

Figure 1 shows the flowchart of the study participants. Table 1 summarizes the demographic characteristics of the study participants. Following the matching process, mean age = 59.19 years, SD = 6.26 (MCI group, n = 102); mean age = 58.42 years, SD = 6.15 (control group, n = 102). There was a relatively balanced sex of 57 males (55.9%) and 45 females (44.1%) in both MCI and control group. Analysis of variance between groups revealed that years of formal education differed significantly (p = 0.015) between the MCI group (9.16 ± 3.00) and the control group (10.30 ± 3.05). No statistically significant differences were observed for age, gender, BMI, marital status, family history of AD, smoking, drinking, depression, hypertension, diabetes, CHD, hyperlipidemia, insomnia, or exercise frequency between the MCI and control group (p > 0.05).

Fig. 1.

Flowchart of study participants. A total of 234 patients with cognitive impairment were recruited for this study. According to the established inclusion and exclusion criteria, 13 patients were identified as having severe cognitive impairment, and 57 patients were excluded due to the presence of stroke, cerebral hemorrhage, a history of cerebrovascular infarction, Parkinson’s disease, or other comorbidities. Furthermore, five patients were excluded due to visual or hearing impairment, 17 patients did not complete all cognitive tests due to low education levels, and eight patients were excluded due to non-adherence. Ultimately, 102 patients with MCI were included in the case group. The case and control groups were matched 1:1 based on gender and age among the neurological and cardiological inpatients during the same period.

Table 1.

Demographic characteristics of study participants.

Demographic characteristics		Mean ± SD or n (%)		Z	p-values
		MCI	Control
Age (in years)		59.19 ± 6.26	58.42 ± 6.15	-0.819	0.413
Sex	Man	57(55.9)	57(55.9)	˂0.001	1.000
	Woman	45(44.1)	45(44.1)
Years of formal education		9.16 ± 3.00	10.30 ± 3.05	-2.430	0.015*
BMI (kg/m2),		26.28 ± 3.58	26.10 ± 4.03	-0.856	0.392
Marriage	Married	95(93.1)	95(93.1)	5.467	0.243
	Othera	7(6.9)	7(6.9)
AD	Yes	8(7.8)	5(4.9)	0.739	0.390
	No	94(92.2)	97(95.1)
Smoke	Yes	33(32.4)	40(39.2)	1.045	0.307
	Never	69(64.2)	62(60.8)
Drink	Yes	29(28.4)	38(37.3)	1.800	0.180
	Never	73(71.6)	64(62.7)
Depression	no	94(92.2)	90(88.2)	0.976	0.614
	Mild	7(6.9)	11(10.8)
	Moderately severe	1(1.0)	1(1.0)
Hypertension	Yes	57(55.9)	47(46.1)	1.962	0.161
	No	45(44.1)	55(53.9)
Diabetes	Yes	24(23.5)	16(15.7)	1.990	0.158
	No	78(76.5)	86(84.3)
CHD	Yes	24(23.5)	14(13.7)	3.234	0.072
	No	78(76.5)	88(86.3)
Hyperlipidemia	Yes	24(23.5)	26(25.5)	0.106	0.745
	No	78(76.5)	76(74.5)
Insomnia	Yes	69(67.6)	63(61.8)	0.773	0.379
	No	33(32.4)	39(38.2)
Exercise frequency	seldom	5(4.9)	14(13.7)	7.487	0.058
	once a week	2(2.0)	4(3.9)
	Multiple times a week	20(19.6)	11(10.8)
	Everyday	54(52.9)	59(57.8)

MCI mild cognitive impairment, n Number, SD Standard deviation, BMI body mass index, BDNF Brain-derived neurotrophic factor, MMP-9 Matrix metalloproteinase-9, CHD Coronary heart disease.

^aOther, which includes individuals who are divorced, widowed, remarried, or have never been married. *indicates p < 0.05, **indicates p < 0.01, and ***indicates p < 0.001.

Comparison of assessment indexes between the two groups

As illustrated in Table 2, the differences in plasma BDNF levels, MoCA total scores, visuospatial and executive ability scores, naming scores, attention scores, language scores, abstract thinking scores, and delayed memory scores were statistically significant between the two groups (p < 0.05). Conversely, the differences in plasma MMP-9 levels and orienteering scores were not statistically significant (p > 0.05). Notably, plasma BDNF levels were significantly lower in the MCI group (10.86 ± 1.39 pg/ml) compared to the control group (11.34 ± 1.19 pg/ml, p < 0.05).

Table 2.

Biomarker levels and cognitive assessment (MoCA) scores for each group.

index	MCI	Control	Z	p-values
Log BDNF	10.86 ± 1.39	11.34 ± 1.19	0.193	0.010*
Log MMP-9	5.43 ± 1.15	5.52 ± 1.06	-0.588	0.556
Moca	19.53 ± 2.39	25.23 ± 1.10	-12.335	˂0.001***
Visuospatial	2.75 ± 1.48	4.24 ± 0.77	-7.646	˂0.001***
Naming	2.75 ± 0.50	2.98 ± 0.14	-4.344	˂0.001***
Attention	4.27 ± 1.42	5.53 ± 0.77	-6.839	˂0.001***
Language	2.37 ± 0.73	2.83 ± 0.45	-5.578	˂0.001***
Abstraction	0.65 ± 0.75	1.33 ± 0.68	-6.180	˂0.001***
Delayed recall	0.95 ± 1.08	2.37 ± 1.35	-7.220	˂0.001***
Orientation	5.80 ± 0.63	5.91 ± 0.29	-0.960	0.337

*indicates p < 0.05, **indicates p < 0.01, and ***indicates p < 0.001.

Association between plasma BDNF and MMP-9 levels

To ascertain whether a potential correlation exists between the two biomarkers, plasma BDNF and MMP-9 were analyzed in the present study. Linear regression results showed BDNF levels were positively associated with MMP-9 levels, with a higher level of plasma MMP-9 significantly associated with a higher level of plasma BDNF (β[95% CI] = 0.454[0.403–0.705], p < 0.001). The association remained statistically significant after including age, gender, years of education, BMI, and other additional covariates (β[95% CI] = 0.466[0.415–0.725], p < 0.001).

Univariate logistic regression analysis

The results of the univariate logistic regression analysis revealed that BDNF (OR[95%CI] = 0.754[0.608,0.936], p = 0.010) and years of formal education (OR[95%CI] = 0.866[0.787,0.953], p = 0.003) were both significantly associated with cognitive impairment in middle-aged and older adults (p < 0.05). The analysis showed that both BDNF levels, years of formal education were significantly negatively associated with MCI.

Multivariate logistic regression analysis

Multivariate logistic regression analysis was performed with whether MCI occurred as the dependent variable, and the factors with statistically significant differences in univariate analysis as the independent variables. The assignment of values to the independent variables is illustrated in Table 3. As depicted in Table 4, plasma BDNF levels (OR[95% CI] = 0.703[0.558,0.884], p = 0.003) and years of formal education (OR[95% CI] = 0.844[0.764–0.931], p < 0.001) were identified as protective factors for MCI. After adjusting for age, gender, and other relevant covariates, both BDNF levels and years of education remained significantly negatively associated with MCI.

Table 3.

Methods for assigning independent variables in multivariate logistic regression analysis.

Variable	Assignment method
Sex	Male = 1, female = 0
Marital history	Married = 1, Divorced = 2, Widowed = 3, Remarried = 4, Unmarried = 5
Family history of AD	Yes = 1, No = 0
History of smoking	Yes = 1, No = 0
History of alcohol	Yes = 1, No = 0
Hypertension	YES = 1, NO = 0

Table 4.

Multivariate logistic regression of factors influencing cognitive impairment.

Models	Independent variable	Beta	Standard error	p-values	OR	95%CI
1	Log BDNF	-0.353	0.117	0.003**	0.703	0.558–0.884
	Years of formal education	-0.170	0.050	0.001***	0.844	0.764–0.931
2	Log BDNF	-0.338	0.118	0.004**	0.713	0.566–0.898
	Years of formal education	-0.177	0.051	0.001***	0.838	0.758–0.926
3	Log BDNF	-0.379	0.136	0.005**	0.685	0.525–0.893
	Years of formal education	-0.194	0.055	0.001***	0.824	0.740–0.917

95% CI, 95% confidence interval; ^*indicates p < 0.05, ^**indicates p < 0.01, and ^***indicates p < 0.001.

Model 1: Independent variables: Log BDNF, dependent variable: MCI prevalence status, covariate: years of education.

Model 2: Added age and gender as covariates.

Model 3: Added BMI, marital history, smoking history, drinking history, family history of AD, and exercise frequency as covariates.

Discussion

Patients with mild cognitive impairment (MCI) typically exhibit subjective cognitive decline, particularly in their capacity to learn new knowledge or recall stored information, while their objective cognition, daily living, and social functioning are relatively well established¹³. This stage may precede the development of dementia by 10 to 20 years³⁵. Compared to age-matched individuals in the general population, patients with MCI due to AD are at a higher risk of progressing to dementia. Given the potential association of BDNF and MMP-9 with the pathogenesis of AD, as well as their crucial role in synaptic plasticity and cognition, this study aims to assess the possible differences in plasma BDNF and MMP-9 concentrations between individuals with MCI due to AD and those with normal cognition and to explore the influencing factors of MCI.

This study analyzed 102 pairs of case-control samples matched according to age and gender and examined the associations of plasma BDNF and MMP-9 levels with cognitive ability and disease status of individuals with MCI. BDNF is the most widely distributed neurotrophic factor in the central nervous system. It mediates neuronal differentiation, proliferation, and survival; regulates synaptic function; promotes brain plasticity; and modulates long-term potentiation, learning, and memory formation in the hippocampus³⁶. The study revealed that plasma BDNF levels were markedly lower in individuals with MCI compared to the control group. The results remained valid even after adding age, gender, BMI, and other covariates, indicating that individuals with higher plasma BDNF levels have a lower probability of developing mild cognitive impairment. The current state of research often presents inconsistent and contradictory evidence on the levels of peripheral BDNF in MCI. A meta-analysis demonstrated that plasma BDNF levels were markedly diminished in patients with MCI relative to control group subjects, consistent with the results of this study¹¹. In contrast, one study found that compared to HC, upon controlling for covariates, they found significantly higher plasma BDNF in MCI versus controls, regardless of whether they were assessing total or MCI sub-types². The main source of heterogeneity observed in previous peripheral BDNF studies is clinical factors. Among the critical clinical factors is the high heterogeneity in older adults with MCI, many of whom have psychiatric comorbidities. Prior research has demonstrated alterations in BDNF blood levels that may result from genetic and environmental influences. For instance, BDNF has been associated with a range of psychiatric disorders, including bipolar disorder, major depression, anxiety disorders, and other psychiatric disorders associated with exposure to stressful conditions^36,37. The present study’s homogeneous subject population, devoid of depression, effectively circumvents the aforementioned heterogeneity. A statistical comparison between the MCI group (n = 94, 92.2%) and the control group (n = 90, 88.2%) yielded no significant difference (Z = 0.976, p = 0.614). The current findings suggest that both long-term and acute aerobic exercise increase serum and plasma BDNF levels in patients with cognitive impairment^38–40. In addition, intermittent fasting (IF) was reported to upregulate BDNF and enhance cognitive performance in animal models⁴¹. A combination of cognitive training, physical exercise, and intermittent fasting is anticipated to yield superior effects on BDNF than either of these strategies alone⁴².

Comparison of differences between the groups revealed that compared to the control group (10.30 ± 3.05), the case group (9.16 ± 3.00) had a significantly lower level of education (Z = -2.430, p = 0.015). Logistic regression analysis indicated that plasma BDNF levels and years of formal education were protective factors affecting patients’ cognitive function, with both showing a significant negative correlation. The results of this study are consistent with previous studies that have shown that a lower education level is significantly associated with a higher prevalence of MCI². This suggests that plasma BDNF levels and years of education could serve as potential targets for intervention to prevent or delay the progression of MCI.

Matrix metalloproteinase-9 (MMP-9) is a member of the zinc-dependent group of extracellular endopeptidases and is expressed in the brain through neurons and glial cells. MMP-9 cleaves substrates such as extracellular components, cell surface receptors, and neurotrophic factor precursors such as proBDNF. MMP-9 is involved in extracellular matrix breakdown and BBB remodeling, contributes to the infiltration of peripheral immune cells into the central nervous system, activates resident immune cells such as microglia, and regulates synaptic plasticity, learning, and memory processes²³. The findings of this study indicated that there was no statistically significant difference in plasma MMP-9 levels between the case and control groups. However, no consensus had been reached regarding peripheral MMP-9 levels in MCI. One study demonstrated that the expression of MMP-9 is increased in Alzheimer’s disease (AD)³. In contrast, another study found that plasma MMP-9 levels were decreased in patients with cognitive impairment⁴. This may be attributed to the high coefficient of variation observed in plasma MMP-9 levels. However, the present study revealed a significant positive correlation between plasma BDNF levels and MMP-9 (β[95% CI] = 7.251[0.403, 0.705], p < 0.001). This indicates that as plasma MMP-9 levels increase, there is a corresponding increase in BDNF levels. Prior research has illustrated that the secretory autophagy-mediated elevation of cellular MMP-9 levels can lead to an increase in the extracellular mBDNF/proBDNF ratio, facilitating the efficient cleavage of proBDNF and the accumulation of mBDNF³⁷.

In this study, the case and control groups were matched 1:1 based on age and gender, controlling for the influence of age and gender factors on the results, which could reduce selection bias and enhance comparability between the two groups. Significant differences in plasma BDNF levels between the case and control groups were confirmed, and both groups underwent the same rigorous assessments for MCI and neuropsychological evaluation, providing a reliable diagnosis. However, several limitations remain. First, the participants in the case group of this study were clinically diagnosed with MCI without the positivity of biomarkers by means of PET or CSF testing, which are mandatory for diagnosing MCT duo to AD based on latest version of AD diagnostic criteria. Despite our research revealing a potential association between BDNF and clinically diagnosed MCI, further studies are warranted to confirm our findings based on the latest AD diagnostic criteria. Second, the current study design limits the ability to understand the relationship between changes in BDNF trajectories and the progression of AD. Gaining clarity on this relationship could provide deeper insights into the role of BDNF in the pathogenesis of AD. Future studies are needed to explore this important topic. Finally, the sample size of this study was relatively modest. Further validation studies ought to involve larger sample sizes.

Conclusions

In summary, plasma BDNF levels and years of formal education are protective factors influencing cognitive function, with a significant negative correlation for both. These findings suggest BDNF and education could be potential targets of intervention to prevent or delay the progression of MCI.

Abbreviations

AD

Alzheimer’s disease

MCI

Mild cognitive impairment

BDNF

Brain-derived neurotrophic factor

proBDNF

pro-brain-derived neurotrophic factor

mBDNF

mature BDNF

MMP-9

Matrix metalloproteinase-9

Aβ

Amyloid-beta

PET

Positron emission tomography

CSF

Cerebrospinal fluid

MoCA-BJ

Montreal cognitive assessment Beijing version

ADL

Activity of daily living scale

CHD

Coronary heart disease

CDR

Clinical dementia rating scale

ELISA

Enzyme-linked immunosorbent assay

SD

Standard deviation

BMI

Body mass index

EDTA

Ethylenediaminetetraacetic acid

Author contributions

TYZ and HLS contributed equally to this work. Conception and design of the study: HLS, TYZ, JLL, and RLM; Drafting of the original manuscript: TYZ; Revising the manuscript: TYZ, HLS and RLM; Acquisition and analysis of data: TYZ, JLL, HLS, and RLM. All authors read and approved the final manuscript.

Funding

This work was supported by the Science and Technology Program of Shihezi City (2023SF06). The funding sources had no role in the design and conduct of the study; and preparation, review, or approval of the manuscript.

Data availability

The data that support the findings of this study are not publicly available due to reasons of sensitivity. The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The study was approved by the ethics committees of Shihezi People’s Hospital under the Declaration of Helsinki (KJ-2023-06). All participants included in the study were informed about the aims and methods of the study and provided their written informed consent.

Competing interests

The authors declare no competing interests.