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. 2025 Apr 23;18:672–678. doi: 10.1016/j.ibneur.2025.04.014

The miR-133b and miR-206 serum levels as a candidate biomarker in Alzheimer's patients with dyslipidemia

Shahram Darabi a, Enam Alhagh Gorgich b, Auob Rustamzadeh a,c,⁎,1, Nafiseh Mohebi d, Hossein Mozhdehipanah e
PMCID: PMC12434688  PMID: 40959537

Abstract

Alzheimer's disease (AD) is a progressive neurodegenerative condition characterized by cognitive decline. Dyslipidemia, a risk factor for AD, may influence the expression of microRNAs (miRs) involved in AD pathogenesis. Thus, the aim of this study was to investigate the effect of dyslipidemia on the expression levels of miR-133b and miR-206 in AD patients with mild cognitive impairment. This study recruited a total of 45 subjects, who were subsequently divided into three distinct groups: the AD group (n = 15), the AD dyslipidemia group (n = 15), and the dyslipidemia group with normal cognitive status (n = 15). The Aβ42/40 serum ratio was measured using an enzyme-linked immunosorbent assay. miR expression levels were determined by RT-qPCR. Clinicopathological characteristics, including Mini-Mental State Examination (MMSE) scores, Clinical Dementia Rating (CDR), and HDL levels, were also assessed. miR-133b levels were significantly reduced in the AD dyslipidemia group compared to the other two groups (p < 0.001), while miR-206 levels were markedly elevated (p < 0.001). Spearman correlation analysis revealed that miR-133b expression levels were positively associated with the Aβ42/40 ratio (r = 0.799), MMSE scores (r = 0.578), and HDL levels (r = 0.768), while negatively associated with miR-206 levels (r = -0.461), CDR score (r = -0.539), and AD duration (r = -0.569). Conversely, miR-206 levels positively correlated with CDR and disease duration, but were inversely associated with miR-133b, MMSE, Aβ42/40, and HDL. Serum miR-133b and miR-206 levels appear to be associated with AD pathology and clinical parameters in the early stages of the disease. The studied miR expression levels could serve as reliable biomarkers in AD patients with dyslipidemia.

Keywords: Alzheimer's disease, Dyslipidemia, Biomarker, MiR-133b, MiR-206

1. Introduction

Alzheimer's disease (AD) is a complex neurodegenerative condition that develops due to a combination of genetic predispositions and environmental influences (Darabi et al., 2025). The existence of certain risk factors in middle age, including high blood pressure (Qiu et al., 2005), obesity, and hypercholesterolemia (Anstey et al., 2008, Reitz et al., 2008), has been linked to cognitive impairment later in life. Epidemiological studies have found an association between elevated plasma cholesterol levels and an increased risk of developing AD (Anstey et al., 2008, Darabi et al., 2025). A meta-analysis of 17 studies involving over 23,000 patients shows midlife hypercholesterolemia significantly increases the risk of developing Alzheimer's disease later in life (Anstey et al., 2017). It is believed that neurodegenerative processes begin 15–20 years prior the onset of clinical manifestations (Jellinger et al., 2008, Sperling et al., 2014). Early AD detection enables timely intervention; integrating accessible, cost-effective biomarkers can significantly improve clinical assessment and management (Fiandaca et al., 2014). Neuroimaging techniques such as MRI and FDG-PET can detect early AD-related changes, including medial temporal lobe atrophy, before cognitive symptoms appear. However, their clinical utility is limited by high costs and lengthy procedures, restricting widespread implementation in early diagnosis (Keller et al., 2016, Swarbrick et al., 2019, Takousis et al., 2019). MicroRNAs (miRs) offer advantages over traditional markers, as certain miRs in patient biofluids are linked to AD-related pathology (Swarbrick et al., 2019, Takousis et al., 2019). miRs regulate gene expression and influence APP processing and Aβ metabolism, key processes in the development of Alzheimer’s pathology (Cirrito et al., 2008, Kaether et al., 2006, Millan, 2017, Roher et al., 2017). Yang et al. showed that serum miR-133b levels are depleted in patients with AD and can distinguish AD patients from healthy individuals with 90.8 % sensitivity and 74.3 % specificity (Yang et al., 2019). Xie et al. analyzed serum miR-206 in 458 aMCI patients over 5 years, finding higher miR-206 levels significantly associated with progression to AD. Multivariate Cox regression confirmed miR-206 as a potential predictor of aMCI-to-AD conversion (Xie et al., 2017). Studies indicate miR-206 is linked to cognitive and memory impairments, rising before dementia onset. Its elevation is associated with blood-brain barrier (BBB) breakdown in MCI, increasing the risk of developing dementia (Kenny et al., 2019, Montagne et al., 2015). miR biomarkers show inconsistent results across studies due to differences in sample collection, miR identification, and data analysis methods. Variations in isolation techniques, contamination, measurement approaches, and sample quality affect outcomes (Jain et al., 2019, Peña-Bautista et al., 2019, Piscopo et al., 2019). Platelet miRs are more stable, with higher concentrations than in plasma or serum samples (Lee et al., 2020). Over 20 % of CSF samples from lumbar punctures (LP) are contaminated, affecting Aβ42 level assessments. Collecting CSF from elderly patients can be difficult due to spinal issues. Circulating miRs offer potential as non-invasive diagnostic biomarkers for early disease detection, progression tracking, and therapeutic evaluation (Aasebø et al., 2014). However, limited studies on their diagnostic efficiency exist, and the lack of reliable reference genes hampers research on miRs in MCI/AD patients (Peña-Bautista et al., 2019, Piscopo et al., 2019). Therefore, this study aims to evaluate how dyslipidemia influences miR-206, miR-133b expression, and amyloid levels in patients with mild AD.

2. Patients and methods

2.1. Study design and subjects

In total, 45 AD patients who were referred to the neurology and geriatric center of Booali Sina Hospital (Qazvin), Rasoul Akram Hospital, and Jam`s Memory Clinic, Tehran, Iran between October 2022 and February 2024 were recruited in the current study. All participants underwent the mini-mental state examination (MMSE). Patients also provided a blood sample to assess their lipid profiles, including triglyceride (TG), low-density lipoprotein (LDL), total cholesterol (TC), and high-density lipoprotein (HDL), in order to determine whether or not dyslipidemia was present.

The following is the list of requirements for inclusion: 1-Diagnosis of mild sporadic AD using the neuropsychological clinical questionnaire, which includes the MoCA and MMSE with a combined score of 19–24, and the neurologist's diagnosis; 2-Evidence supporting the diagnosis of secondary dyslipidemia from biochemical testing and a demographic survey; and 3-Verification of routine MRI imaging due to hippocampal atrophy and cerebral ventricle enlargement. The study's exclusion criteria included not having brain tumors, active epilepsy, diabetes, uncontrolled hypertension, brain surgery, heart failure, severe renal failure, thyroid diseases, alcoholism, or usage of opioid medications.

2.2. Blood sampling and measuring lipid profile

Eight milliliters of each patient's venous blood were drawn both before and after the pharmaceutical intervention (Charkhat Gorgich et al., 2024), and the blood was then placed in tubes containing clot-activating gel (VacuLab® SSGT model, Liuyang SANLI Medical Technology Development Co., China). The tubes were centrifuged for eight minutes at 4000 rpm after that. Before being moved to the −80 °C freezer, they were briefly isolated in a microtube in a clean room and under the hood. An autoanalyzer (model Pictus 700, Diatron Company) was used to assess the levels of HDL, TG and TC, and LDL using lipid kits (Delta Darman Part Co., Tehran, Iran) based on enzymatic principles.

2.3. Measurement of Aβ1–42/Aβ1–40 peptide serum level

An enzyme-linked immunosorbent assay (ELISA) kit consisting of a double biotin antibody sandwich type was utilized in the investigation to test Aβ1–42 and Aβ1–40 quantitatively (Human Aβ1–42 and Aβ1–40 peptide ELISA Kit- ZellBio GmbH, Hamburg, Germany). The Aβ1–42 protein is added to wells that have already been coated with the Aβ1–42 monoclonal antibody as part of the experiment. When biotin-labeled Aβ1–42 antibodies were added, a streptavidin-HRP combination was produced, leading to the creation of an immunological complex. Following incubation and washing, the unbound enzymes were eliminated. Following the addition of substrates A and B, the solution first colored blue before becoming yellow due to the acid's impact. At a wavelength of 450 nm, the absorbance (OD) of every well was measured. The point-by-point calculation approach was used to create the standard curve based on the concentration of the standards and the accompanying OD values. This kit's sensitivity for measuring the serum level of the Aβ1–42 peptide was 1 ng/L. According to the appropriate kit, these procedures were likewise followed for the Aβ1–40 peptide.

2.4. Serum miR-206 and miR-133b expression assessment by RT-qPCR

Serum samples from patients were used to isolate total RNA via the guanidinium thiocyanate-phenol-chloroform technique (triazole-LS solution). Using a specific kit, cDNA synthesis was carried out, and a nanodrop was used to quantify the concentration of total RNA. To screen and quantify miR profiles, we employed a stem-loop RT-qPCR technique (Chen et al., 2005). Each RT-qPCR reaction was subjected to the following temperature cycles: hold temperature = 15 min; 40 cycles with 3 steps; 95ᵒ for 30 s; 60ᵒ for 30 s; and 72ᵒ for 30 s, with a melting temperature ranging from 55 to 95ᵒ. The Corbett Rotor-Gene 6000 (Corbett Research, Mortlake, Australia, version 1.7.87) was used to read the genes. After confirming that a particular product was produced, CTs were extracted using the Rotor-Gene software, and the relative expression method was used to quantify the outcomes. The 2^-ΔΔCT method was used to measure the relative expression of miRs, and U6 was used as an internal reference gene for normalization (Charkhat Gorgich et al., 2022, Shi et al., 2020). The sequence of primers was as follows:

miR-206 Stem:

5′-CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAGCCACACAC-3′

miR-206 Forward:

5′-ACACTCCAGCTGGGTGGAATGTAAGGAAGT-3

miR-133b Stem:

GTGCAGGGTCCGAGGTCAGAGCCACCTGGGCAATTTTTTTTTTTAGCTGG

miR-133b Forward:

5’-UUUGGUCCCCUUCAACCAGCUA-3

U6-snRNA; RT:

5’GTCGTACTCAACGTGGTTAGGGTCCGAGGTATAGGTTCCCACGTGGAGGACGACGAATATG-3’

U6-snRNA; F:

5’-GGATGACGCAAATTCGTGAAGC-3

Universal Reverse:

CCA GTG CAG GGT CCG AGG TA

To amplify the target fragment, the forward and reverse primers travel in opposite directions after attaching a stem-specific primer specifically made for miRs to their 3′ end (L. H. Yang et al., 2014). SYBR green's fluorescence intensity was used to screen for proliferation rate.

2.5. Statistical analysis

To evaluate the normality of the distribution for all variables in the dataset, the Kolmogorov-Smirnov test was employed. The data were reported as mean ± standard deviation (SD). The Kruskal-Wallis test or ANOVA test, followed by a post-hoc Dunn's test, was used to compare the mean changes of serum factors among the three groups. The SPSS and GraphPad Prism 8 software were applied for data analysis and drawing graphs, respectively. The significance level was set as p less than 0.05.

3. Results

3.1. Demographic and clinicopathological characteristics of subjects

In the current study, 45 participants were recruited; 15 AD patients without dyslipidemia (AD group), 15 AD patients with dyslipidemia (AD dyslipidemia group), and 15 dyslipidemia individuals with normal cognitive status (CogNormal dyslipidemia). The mean age of the participants in the AD group was 74.80 ± 5.088, the AD dyslipidemia group was 74.60 ± 4.718, and the CogNormal dyslipidemia group was 73.87 ± 3.701 years. More details about participants' characteristics are represented in Table 1. The age and gender of the participants did not show statistically significant differences between the study groups (p > 0.05). The MMSE score in both AD groups was significantly lower than the CogNormal dyslipidemia individuals (p < 0.0001), while there was no such significant difference between the two AD groups (p = 0.932) (see Table 1). In addition, the CDR in both AD groups was significantly higher compared to the CogNormal dyslipidemia group. In the CogNormal dyslipidemia and AD dyslipidemia groups, TC and TG was significantly higher than AD groups, while LDL levels in AD patients was lower compared the CogNormal dyslipidemia individuals and AD dyslipidemia patients. On the other hand, HDL level in AD patients with dyslipidemia was significantly lower than other studied groups (Table 1).

Table 1.

Demographic and clinicopathological characteristics of the study groups.

Variables CogNormal dyslipidemia group (n = 15) AD dyslipidemia group (n = 15) AD group (n = 15) p-value
Age (years) 73.87 ± 3.701 74.60 ± 4.718 74.80 ± 5.088 0.955
Gender (M:F) 7:8 7:8 10:5 0.448
AD duration (years) - 5.60 ± 1.639 4.93 ± 1.792 0.475
MMSE 27.60 ± 1.404 20.07 ± 0.961 20.13 ± 1.060 < 0.001
CDR 0.066 ± 0.175 1.000 ± 0.462 1.066 ± 0.416 < 0.001
BMI 27.660 ± 1.586 27.073 ± 1.890 25.220 ± 1.697 0.002
TC 266.800 ± 21.183 271.666 ± 23.331 146.866 ± 14.396 < 0.001
TG 246.933 ± 33.274 235.866 ± 38.435 124.933 ± 13.624 < 0.001
HDL 51.733 ± 2.520 33.933 ± 3.239 46.726 ± 5.031 < 0.001
LDL 144.800 ± 11.564 133.213 ± 14.252 85.513 ± 9.087 < 0.001
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3.2. The Aβ42/40 serum levels

In the present study, the Aβ42/40 serum levels was assessed using ELISA. Our findings showed a significant difference between Aβ42/40 levels in studied groups (p < 0.05). The Aβ42/40 level in the AD dyslipidemia group (0.334 ± 0.445) was significantly lower compared to the CogNormal dyslipidemia (1.007 ± 0.113) and AD (0.543 ± 0.043) groups (p < 0.001 (Fig. 1).

Fig. 1.

Fig. 1

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Evaluation of serum Aβ42/40 levels in study groups. Data are presented as mean ± SD. The differences between the groups were examined using Kruskal-Wallis test, followed by a post-hoc Dunn's test (***p < 0.001). (AD dyslipidemia compare to AD and CogNormal dyslipidemia).

3.3. Serum miRs expression levels

The miR-133b and miR-206 expression levels were estimated by RT‑qPCR. As shown in Fig. 2, the serum miR-133b expression levels were significantly lower in AD dyslipidemia patients compared to the AD patients and the CogNormal dyslipidemia individuals (p < 0.001). On the other hand, the serum miR-206 expression levels in the AD dyslipidemia group were significantly higher than the AD and the CogNormal dyslipidemia groups (p < 0.001).

Fig. 2.

Fig. 2

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The miRs expression levels analysis by qRT-PCR in study groups. The relative expression of miR-133b (A) and miR-206 levels. U6-snRNA gene expression was used for normalization and was quantified using the 2-ΔΔct method. Data are expressed as mean ± SD. The significant difference was analyzed by Kruskal-Wallis test, followed by a post-hoc Dunn's test (*p < 0.05, ***p < 0.001; AD dyslipidemia compare to AD and CogNormal dyslipidemia).

3.4. Association between the miRs levels and clinicopathological parameters

The correlation between the miRs levels and clinicopathological parameters was seek by Spearman's correlation coefficient. The result showed that the miR-133b expression levels was positively associated to MMSE score (r = 0.578, p < 0.001), Aβ42/40 serum level (r = 0.799, p < 0.001), and HDL (r = 0.768, p < 0.001), while negatively correlated with disease duration (r = -0.569, p = 0.000), CDR (r = -0.539, p < 0.001), and miR-206 expression levels (r = -0.461, p = 0.001) (Table 2).

Table 2.

Association between the miRs and clinical/paraclinical parameters in AD patients with dyslipidemia.

Markers/parameters AD duration MMSE score Aβ42/40 CDR HDL miR-206 miR-133b
miR−133b r = −0.569
p < 0.001		 r = 0.578
p < 0.001		 r = 0.799
p < 0.001		 r = −0.539
p < 0.001		 r = 0.768
p < 0.001		 r = −0.461
p = 0.001		 -
miR−206 r = 0.377
p = 0.011		 r = −0.417
p = 0.004		 r = −0.542
p < 0.001		 r = 0.436
p = 0.003		 r = −0.519
p < 0.001		 - r = −0.799
p = 0.001
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Furthermore, we found that miR-206 serum levels expression positively correlated with AD duration (r = 0.377, p = 0.011) and CDR (r = 0.436, p = 0.003), while negatively correlated with MMSE score (r = -0.417, p = 0.004), HDL (r = -0.519, p < 0.001), Aβ42/40 serum level (r = -0.542, p < 0.001), and miR-133b (r = -0.799, p = 0.001) (Table 2).

4. Discussion

Alzheimer's disease (AD) is an intricate neurodegenerative disease marked by progressive cognitive and memory impairments in humans which mostly affects the aged population. Exploring new approaches for early diagnosis and treatment of AD is crucial due to the lack of a known cure and limited early diagnostic biomarkers for AD at present (Mohammadi et al., 2024).

In this scenario, miRs are a class of small non‑coding RNAs molecules which numerous studies have shown that dysregulation of miRs plays a crucial role in the development of various human diseases such as AD (Tian et al., 2019; Wang et al., 2023). Certain miRs have been suggested to play a role in the synaptic plasticity, development, and differentiation of neurons. Moreover, dysregulation of miRs could be associated with various pathological condition in the CNS diseases including AD (Maniati et al., 2019). Hong et al. findings suggest that miR-125b, miR-191–5p, miR-9, and miR-28–3p have the potential to serve as biomarkers for AD, and their expression levels were confirmed in SH‑SY5Y cell line and animal model of AD (Hong et al., 2017). Another study by Kumar et al. showed an upregulation of miR-455–3p in AD patients as compared to the levels observed in healthy controls. Their findings demonstrateed that miR-455–3p may have a potential impact on the development of AD (Kumar et al., 2017).

However, to date, the discovery of the role of miRs as a biomarker in AD and their importance in the pathogenesis of this disease, the relationship between specific miRs serum levels and metabolic disorders such as dyslipidemia in Alzheimer's patients has not been fully elucidated. Dyslipidemia, a condition characterized by abnormal lipid profiles, is often comorbid with AD and can exacerbate its symptoms. Additionally, the levels of total Aβ42/40 ratio, key biomarkers of AD, have been linked to the disease progression.

In recent years, there has been considerable interest in the association between serum miR-133b levels and AD patients with dyslipidemia. Regarding the association between miR-133b and Aβ levels, research suggests that miR-133b may play a role in regulating Aβ levels. Yang et al. found that in the AD group, the miR-133b serum levels of were significantly lower than control group. Their findings also stated that overexpression of miR-133b effectively mitigated the suppression of cell viability and the promotion of cell apoptosis induced by Aβ25–35 in a cellular model of AD. This implies that miR-133b could play a neuroprotective effect in AD by modulating Aβ levels (Yang et al., 2019). In our research, the serum miR-133b level in AD dyslipidemia patients was significantly lower compared to both AD and CogNormal dyslipidemia groups. Yang et al.’s cohort (Yang et al., 2019) did not stratify AD patients by dyslipidemia status. Given that 50–60 % of AD patients have comorbid dyslipidemia, their cohort likely included mixed subpopulations. Our focused comparison reveals that dyslipidemia exacerbates miR-133b depletion specifically in AD, suggesting metabolic comorbidity modulates miR expression beyond AD pathology alone. This aligns with evidence that dyslipidemia alters circulating miR profiles by influencing lipoprotein-mediated miR transport (Wiedrick et al., 2019). Additionally, in their study analyzed AD patients without specifying disease stage, whereas our cohort focused on early-stage AD with MCI. miR-133b exhibits stage-dependent fluctuations, as shown by Xie et al. (2017), where its levels inversely correlated with Aβ42/40 ratios during MCI-to-AD progression. Early dyslipidemia-driven miR-133b suppression may accelerate pathogenic cascades (e.g., FAIM dysregulation (Coccia et al., 2020), creating divergent expression trajectories compared to later-stage AD. These factors collectively suggest that dyslipidemia acts as an effect modifier, accentuating miR-133b depletion in early AD. Stratifying AD cohorts by metabolic comorbidities is critical for resolving biomarker inconsistencies.

Furthermore, has been shown that the Aβ42/40 ratio provide greater diagnostic accuracy than Aβ42 alone in differentiating AD dementia from other clinical phenotypes (Constantinides et al., 2023). The relationship between the Aβ42/40 ratio and cognitive and functional decline in individuals with mild cognitive impairment (MCI) has been identified. As reported by Delaby et al. lower Aβ42/40 ratios have been associated with poorer cognitive performance and an increased likelihood of developing dementia compared to individuals with higher ratios (Delaby et al., 2022), which was consistent with the results of the current study in AD dyslipidemia patients. Furthermore, our findings revealed a positive association between serum level of miR-113b and Aβ42/40 ratio. In this context, the lower serum miR-133b levels in AD patients with dyslipidemia may contribute to the exacerbation of lipid abnormalities, which in turn can accelerate neurodegeneration and increase Aβ levels.

The implications of this association are multifaceted. Firstly, lower level of miR-133b in AD dyslipidemia patients might worsen lipid abnormalities, thereby hastening neurodegeneration. Secondly, the measurement of serum levels of miR-133b may applied as a reliable fluid-based biomarker for identifying patients at high risk of developing dyslipidemia and AD. This could enable early intervention strategies aimed at preventing or slowing disease progression. This could facilitate early intervention efforts to prevent or decelerate disease advancement. Moreover, the dysregulation of miR-133b by dyslipidemia in AD highlights the intricate interaction between lipid metabolism and neurodegenerative disorders. It seems that comprehension of this interplay is essential for the development of successful treatment approaches that address both lipid metabolism and neuroprotection.

Our results regarding the assciation between serum levels of miR-206 in studied groups showed that miR-206 levels in AD dyslipidemia patients were significantly higher than in AD patients and CogNormal dyslipidemia individuals. The results also revealed a negative correlation between the serum levels of miR-206 and the Aβ42/40 ratio.

In this context, several studies have investigated the relationship between miR-206 and AD. Tang et al. stated that expression levels of miR-206 were significantly elevated in the brains and blood of AD patients than healthy individuals. They also found that this higher level of miR-206 was associated with lower levels of brain-derived neurotrophic factor (BDNF), a protein essential for neuronal integrity (Tang et al., 2017). Another study revealed that miR-206 levels are notably higher in the blood samples of AD patients in comparison to age-matched healthy controls. The elevation in miR-206 expression has been observed in both the blood of individuals with MCI and in the temporal cortex of human brains affected by AD (Coccia et al., 2020). Kenny et al. included 458 patients diagnosed with amnestic MCI revealed that higher levels of miR-206 in the blood were significantly associated with the development of AD over a 5-year period (Kenny et al., 2019), which all these studies were consistence with our findings about serum miR-206 levels in patients with AD. This reveals that miR-206 could applied as a potential promising biomarker for dyslipidemia AD patients’ early diagnosis and monitoring.

The interplay between Aβ42/40 levels and peripheral lipid profiles in AD pathogenesis is increasingly recognized. In our study, lower Aβ42/40 ratios were significantly associated with higher total cholesterol and triglyceride levels, and lower HDL concentrations in AD patients with dyslipidemia. Dyslipidemia may exacerbate amyloid pathology by impairing Aβ clearance mechanisms, promoting its deposition in the brain (Darabi et al., 2025, Roher et al., 2017). Elevated LDL and triglyceride levels have been shown to disrupt BBB integrity, facilitating the accumulation of neurotoxic Aβ species (Montagne et al., 2015). Conversely, HDL is thought to promote Aβ efflux from the brain and protect against amyloid aggregation (Cheng et al., 2020). Prior studies have reported that a reduced Aβ42/40 ratio in plasma and CSF is a hallmark of AD progression and correlates with cognitive decline (Delaby et al., 2022). Our findings support the hypothesis that lipid metabolism abnormalities significantly influence peripheral Aβ dynamics and may contribute to early neurodegenerative changes. Therefore, managing dyslipidemia may have cardiovascular benefits and potential neuroprotective effects in slowing AD progression. Future research should explore whether therapeutic modulation of lipid levels can directly alter Aβ metabolism and improve clinical outcomes in patients at risk for AD.

Aβ42/40 ratio are a hallmark of AD pathology. Aβ42/40 elevated levels are associated to high risk of cognitive impaiment and dementia. Recent studies have demonstrated that miR-206 levels are linked to Aβ42/40 ratio in patients with AD. Xing et al. reported that miR-206 levels were positively correlated with Aβ42/40 levels in the brains of AD patients (Xing et al., 2016), which was in contrast with the findings of the present investigate. Regarding this contradiction, it can be stated that based on available evidence the precise ways in which miR-206 impacts AD pathology are not fully clarified, but it is believed to influence BDNF expression. Increased levels of miR-206 may result in reduced BDNF production, potentially worsening AD symptoms. Furthermore, miR-206 has been demonstrated to control cholesterol metabolism, which is disrupted in AD, and this disruption may play a role in the buildup of Aβ, a key feature of AD pathology. (Amakiri et al., 2019; Assis et al., 2024). On the other hand, has been shown that elevated level of miR-206 has been associated with elevated levels of pro-inflammatory cytokines, including tumor necrosis factor-alpha (TNFα) and interleukin-1 beta (IL-1β). This implies that miR-206 level may play a role in the inflammatory response in AD (Xing et al., 2016). Therefore, targeting this pathway can be more underscored as an AD-therapeutic strategy in the future.

Our findings demonstrate that dyslipidemia significantly modulates the expression of key circulating biomarkers associated with AD pathology. We observed a significant reduction in the serum Aβ42/40 ratio in AD patients with dyslipidemia compared to AD patients without dyslipidemia and cognitively normal individuals with dyslipidemia. This result aligns with previous findings suggesting that lipid dyshomeostasis exacerbates amyloidogenic processes. Lipid rafts, cholesterol-enriched membrane microdomains, play critical roles in the production and aggregation of Aβ peptides. Alterations in the composition of lipid rafts due to dyslipidemia can enhance Aβ accumulation (Cerasuolo et al., 2024). Furthermore, systemic lipid metabolism disturbances, as highlighted by Yin et al., have been implicated in promoting amyloidogenesis and neuroinflammation, two hallmarks of AD pathology (Yin, 2023).

Our analysis showed significantly decreased miR-133b and elevated miR-206 levels in AD patients with dyslipidemia, supporting growing evidence of non-coding RNAs in AD pathogenesis. Importantly, miR-133b may regulate synaptic integrity by targeting Neuronal Pentraxin 2 (NPTX2), a key synaptic protein involved in cognitive function (Han et al., 2024). Lower levels of miR-133b may thus contribute to the observed cognitive decline in AD patients, possibly through impaired synaptic function. Conversely, elevated levels of miR-206, which negatively regulate brain-derived neurotrophic factor (BDNF), were observed in the AD dyslipidemia group. BDNF is essential for synaptic plasticity and cognitive resilience. Previous studies have shown that miR-206 upregulation can impair BDNF expression, exacerbate neuroinflammation, and worsen cognitive outcomes (Wang et al., 2024). Our data, demonstrating a strong inverse correlation between miR-206 levels and cognitive performance (MMSE scores), further support the detrimental role of miR-206 overexpression in AD, particularly in the context of dyslipidemia.

Our results are also supported by the evidence from Neth et al., who demonstrated that dietary interventions such as a modified Mediterranean ketogenic diet (MMKD) can reverse the plasma lipidomic profile associated with AD (Neth et al., 2025). Given the substantial impact of dyslipidemia on miR-133b and miR-206 expression, targeting lipid metabolism therapeutically could also normalize miRNA expression patterns and potentially slow cognitive decline. Furthermore, the importance of identifying novel biomarkers, particularly non-coding RNAs, is emphasized by the Common Alzheimer's Disease Research Ontology (CADRO) system (Leisgang Osse et al., 2025, Zhang et al., 2021), which highlights gaps in biomarker discovery, especially those linked to metabolic dysfunctions. Our study provides evidence that serum miR-133b and miR-206 levels may serve as promising non-invasive biomarkers for identifying AD patients at higher risk due to dyslipidemia.

Regarding the association between miR-133b and miR-206 levels and MMSE our results showed a significant positive association among miR-133b and MMSE score, while we found a negative association among miR-206 and MMSE score in AD patients (Arevalo-Rodriguez et al., 2015).

The MMSE is widely used in clinical settings to screen for cognitive decline and provides an overall assessment. The MMSE score is significantly valuable in diagnosing mild cognitive decline that could progress to AD. Yang et al. with consistance with our findings reported a posituive association of miR-133b serum levels with the MMSE scores. Their results proved that lower miR-133b levels associated to the severity of cognitive decline in AD patients. They also claimed that levels of miR‑133b can applied as a reliable fluid-based biomarker for distinguishing between patients with AD and those who are healthy individulas (Yang et al., 2019). A longitudinal cohort study found that there was a strong association among elevated levels of miR-206 and deteriorating cognitive function, as assessed through MMSE scores. Increased miR-206 was observed in individuals with MCI at least 2 years before they developed dementia. Elevated miR-206 levels were linked to the cognitive decline progression and the onset of dementia in MCI cases, and were associated with declining MMSE scores over time (Kenny et al., 2019). These findings paralleled the increase in miR-206 observed in the study by Kenny et al. (2019) and Xie et al. (2017).

In brief, according to available findings decreased seruom expression level of miR-133b and increased serum expression level of miR-206 are associated with the severity of cognitive decline in patients with AD, particularly in AD patients with dyslipidemia, as measured by MMSE scores.

These results firstly reveal the role of these miRs in the pathology of AD in the early stages with mild cognitive impairment. Additionally, they provided insight into how abnormal lipid profiles contribute to the dysregulation of miR-133b and miR-206 levels in patients with mild cognitive impairment. Lastly, it seems that these miRs can be applied in clinical settings as a useful biomarkers in early diagnosis, disease trending and monitoring in AD patients.

Peripheral blood mononuclear cells (PBMCs) play a significant role in pathology, particularly concerning lipid metabolism and Aβ dynamics. Studies have shown that PBMCs from AD patients exhibit increased accumulation of neutral lipids and higher expression of acyl-coenzyme A: cholesterol acyltransferase-1 (ACAT-1), an enzyme responsible for cholesterol esterification. This accumulation correlates with decreased plasma high-density lipoprotein cholesterol (HDL-C) levels and cognitive decline, suggesting that PBMC lipid profiles may serve as early indicators of AD and systemic lipid dysfunction (Pani et al., 2009)

Furthermore, PBMCs can influence Aβ42 dynamics. When exposed to Aβ42 aggregates, PBMCs adopt a pro-inflammatory phenotype, releasing cytokines such as tumor necrosis factor-alpha (TNF-α) and interleukins that may exacerbate neuronal damage and disturb Aβ metabolism and clearance (Kot et al., 2024). This highlights a potential mechanism whereby PBMCs not only reflect systemic inflammation but actively contribute to amyloid pathology in the central nervous system.

This study has several limitations. The small sample size and cross-sectional design limit generalizability and preclude causal inferences. Potential confounding factors such as inflammation, oxidative stress, and medication use were not assessed. Additionally, only serum samples were analyzed, without comparison to cerebrospinal fluid (CSF) or brain tissue. The use of U6-snRNA for normalization, despite known stability concerns, may affect data accuracy. Furthermore, the study population was geographically restricted. Future research should involve larger, longitudinal, and multi-center studies to validate these findings.

5. Conclusion

Given that the association between serum miR-133b and miR-206 levels and Aβ42/40 ratio in dyslipidemia AD patients underscores the crucial role of lipid metabolism in neurodegenerative processes. It seems that the measurement of serum expression of miR-133b and miR-206 may applied as a valuable fluid-based biomarker for patients with AD and mild cognitive impairment in clinical settings. In conclusion, the available evidence suggests that both serum expression miR-133b and miR-206 levels involved in the onset and progression of AD, with miR-133b having a neuroprotective function and miR-206 being linked to neuroinflammation. In addition, our findings suggest that dyslipidemia significantly alters the serum levels of key miRNAs associated with AD pathology, thereby exacerbating disease progression. miR-133b may have a protective role by supporting synaptic integrity, while miR-206 may promote neurodegeneration by suppressing BDNF expression. Further research are highly recommended to fully elucidate the mechanisms by which miR-133b and miR-206 contributes to AD pathology and to explore their potential as a theranostic target.

CRediT authorship contribution statement

Rustamzadeh Auob: Writing – review & editing, Writing – original draft, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Gorgich Enam Alhagh: Writing – review & editing, Writing – original draft, Visualization, Validation, Software, Resources, Methodology, Investigation, Formal analysis. Darabi Shahram: Writing – review & editing, Writing – original draft, Visualization, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Mozhdehipanah Hossein: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Methodology, Investigation, Formal analysis. Mohebi Nafiseh: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Methodology, Investigation.

Ethics statement

This study was approved by the ethics committee of Qazvin University of Medical Sciences (IR.QUMS.REC.1400.494). All individuals who took part in the study provided written consent after being informed about the details of the research.

Author contributions

ARu and ShD conceived and designed research. EAG, NM, HMP prepared material and kits, conducted experiments, patients assesment, and wrote the first draft and manuscript preparation. ShD, EAG, ARu, and NM contributed to collecting data, analytical tools, and data interpretation. All authors read and approved the final manuscript.

Funding

This study was financially funded by Qazvin University of Medical Sciences (Grant No.: 400000605).

Declaration of Competing Interest

The authors declare no competing financial or non-financial interests directly or indirectly related to the work submitted for publication.

Acknowledgements

The authors thank the Deputy of Research at Qazvin University of Medical Sciences for financial and administrative support.

Data availability

Data will be made available on request.

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