MicroRNA expression in extracellular vesicles as a novel blood-based biomarker for Alzheimer's disease

Abstract

Introduction: Brain cell-derived small extracellular vesicles (sEVs) in blood offer unique cellular and molecular information related to the onset and progression of Alzheimer's disease (AD). We simultaneously enriched six specific sEV subtypes from the plasma and analyzed a selected panel of microRNAs (miRNAs) in older adults with/without cognitive impairment.

Methods: Total sEVs were isolated from the plasma of participants with normal cognition (CN; n = 11), mild cognitive impairment (MCI; n = 11), MCI conversion to AD dementia (MCI-AD; n = 6), and AD dementia (n = 11). Various brain cell-derived sEVs (from neurons, astrocytes, microglia, oligodendrocytes, pericytes, and endothelial cells) were enriched and analyzed for specific miRNAs.

Results: miRNAs in sEV subtypes differentially expressed in MCI, MCI-AD, and AD dementia compared to the CN group clearly distinguished dementia status, with an area under the curve (AUC) > 0.90 and correlated with the temporal cortical region thickness on magnetic resonance imaging (MRI).

Discussion: miRNA analyses in specific sEVs could serve as a novel blood-based molecular biomarker for AD.

Highlights: Multiple brain cell-derived small extracellular vesicles (sEVs) could be isolated simultaneously from blood. MicroRNA (miRNA) expression in sEVs could detect Alzheimer's disease (AD) with high specificity and sensitivity. miRNA expression in sEVs correlated with cortical region thickness on magnetic resonance imaging (MRI). Altered expression of miRNAs in sEV^CD31 and sEV^PDGFRβ suggested vascular dysfunction. miRNA expression in sEVs could predict the activation state of specific brain cell types.

Keywords: Alzheimer's disease; biomarker; brain cells; extracellular vesicles; microRNA.

FIGURE 1

Expression profiling of specific microRNAs (miRNAs) in small extracellular vesicle (sEV)^L1CAM and their correlation with cognitive impairment and temporal cortical thickness. (A) The expression of eight miRNAs was analyzed in sEV^L1CAM in subjects with normal cognition (CN; n = 11), mild cognitive impairment (MCI; n = 11), MCI-AD (Alzheimer’s disease) (n = 6), or AD (n = 11) by quantitative real-time polymerase chain reaction (PCR). Fold-change in the expression of miRNA showing detectable expression was calculated by the ΔΔCt method (as mentioned in Methods) after normalization with cel-miR-39-3p. Fold-change of all the samples is plotted by calculating 2^−ΔΔCt. ND = “not detectable.” *p < 0.05, **p < 0.005, ***p < 0.0005, ****p < 0.0001. (B–D) Receiver-operating characteristic (ROC) curves curated from logistic regression classifiers of sEV^L1CAM for overall impairment (B), MCI (C), or AD (D) outcomes using the forward selection method with alpha = 0.05. All models were adjusted for age and sex. Summary of the forward selection sEV^L1CAM miRNA shown under each ROC curve. (E) Correlation of detected miRNAs in sEV^L1CAM with the temporal cortical thickness on magnetic resonance imaging (MRI).

FIGURE 2

Expression profiling of specific microRNAs (miRNAs) in small extracellular vesicle (sEV)^GLAST and their correlation with cognitive impairment and temporal cortical thickness. (A) The expression of eight miRNAs was analyzed in sEV^GLAST in subjects with normal cognition (CN; n = 11), mild cognitive impairment (MCI; n = 11), MCI-AD (Alzheimer’s disease) (n = 6), or AD (n = 11) by quantitative real-time polymerase chain reaction (PCR). Fold-change in the expression of miRNA showing detectable expression was calculated by the ΔΔCt method after normalization with cel-miR-39-3p. Fold-change of all the samples is plotted by calculating 2^−ΔΔCt. ND = “not detectable.” *p < 0.05, **p < 0.005. (B–D) Receiver-operating characteristic (ROC) curves curated from logistic regression classifiers of sEV^GLAST for overall impairment (B), MCI (C), or AD (D) outcomes using the forward selection method with alpha = 0.05. All models were adjusted for age and sex. Summary of the forward selection sEV^GLAST miRNA shown under each ROC curve. (E) Correlation of detected miRNAs in sEV^GLAST with the temporal cortical thickness on magnetic resonance imaging (MRI).

FIGURE 3

Expression profiling of specific microRNAs (miRNAs) in small extracellular vesicle (sEV)^TMEM119 and their correlation with cognitive impairment and temporal cortical thickness. (A) The expression of eight miRNAs was analyzed in sEV^TMEM119 in subjects with normal cognition (CN; n = 11), mild cognitive impairment (MCI; n = 11), MCI-AD (Alzheimer’s disease) (n = 6), or AD (n = 11) by quantitative real-time polymerase chain reaction (PCR). Fold-change in the expression of miRNA showing detectable expression was calculated by the ΔΔCt method (as mentioned in methods) after normalization with cel-miR-39-3p. Fold-change of all the samples is plotted by calculating 2^−ΔΔCt. ND = “not detectable.” *p < 0.05, **p < 0.005. (B–D) Receiver-operating characteristic (ROC) curves curated from logistic regression classifiers of sEV^TMEM119 for overall impairment (B), MCI (C), or AD (D) outcomes using the forward selection method with alpha = 0.05. All models were adjusted for age and sex. Summary of the forward selection sEV^TMEM119 miRNA shown under each ROC curve. (E) Correlation of detected miRNAs in sEV^TMEM119 with the temporal cortical thickness on magnetic resonance imaging (MRI).

FIGURE 4

Expression profiling of specific microRNAs (miRNAs) in small extracellular vesicle (sEV)^PDGFRα and their correlation with cognitive impairment and temporal cortical thickness. (A) The expression of eight miRNAs was analyzed in sEV^PDGFRα in subjects with normal cognition (CN; n = 11), mild cognitive impairment (MCI; n = 11), MCI-AD (Alzheimer’s disease) (n = 6), or AD (n = 11) by quantitative real-time polymerase chain reaction (PCR). Fold-change in the expression of miRNA showing detectable expression was calculated by the ΔΔCt method (as mentioned in methods) after normalization with cel-miR-39-3p. Fold-change of all the samples is plotted by calculating 2^−ΔΔCt. ND = “not detectable.” *p < 0.05, **p < 0.005. (B–D) Receiver-operating characteristic (ROC) curves curated from logistic regression classifiers of sEV^PDGFRα for overall impairment (B), MCI (C), or AD (D) outcomes using the forward selection method with alpha = 0.05. All models were adjusted for age and sex. Summary of the forward selection sEV^PDGFRα miRNA shown under each ROC curve except for the MCI group, where no miRNA was identified to distinguish the MCI from the CN group. (E) Correlation of detected miRNAs in sEV^PDGFRα with the temporal cortical thickness on magnetic resonance imaging (MRI).

FIGURE 5

Expression profiling of specific microRNAs (miRNAs) in small extracellular vesicle (sEV)^PDGFRβ and their correlation with cognitive impairment and temporal cortical thickness. (A) The expression of eight miRNAs was analyzed in sEV^PDGFRβ in subjects with normal cognition (CN; n = 11), mild cognitive impairment (MCI; n = 11), MCI-AD (Alzheimer’s disease) (n = 6), or AD (n = 11) by quantitative real-time polymerase chain reaction (PCR). Fold-change in the expression of miRNA showing detectable expression was calculated by the ΔΔCt method (as mentioned in methods) after normalization with cel-miR-39-3p. Fold-change of all the samples is plotted by calculating 2^−ΔΔCt. ND = “not detectable.: *p < 0.05, **p < 0.005. (B–D) Receiver-operating characteristic (ROC) curves curated from logistic regression classifiers of sEV^PDGFRβ for overall impairment (B), MCI (C), or AD (D) outcomes using forward selection technique with alpha = 0.05. All models were adjusted for age and sex. Summary of the forward selection sEV^PDGFRβ miRNA shown under each ROC curve. (E) Correlation of detected miRNAs in sEV^PDGFRβ with the temporal cortical thickness on magnetic resonance imaging (MRI).

FIGURE 6

Expression profiling of specific microRNAs (miRNAs) in small extracellular vesicle (sEV)^CD31 and their correlation with cognitive impairment and temporal cortical thickness. (A) The expression of eight miRNAs was analyzed in sEV^CD31 in subjects with normal cognition (CN; n = 11), mild cognitive impairment (MCI; n = 11), MCI-AD (Alzheimer’s disease) (n = 6), or AD (n = 11) by quantitative real-time polymerase chain reaction (PCR). Fold-change in the expression of miRNA showing detectable expression was calculated by the ΔΔCt method (as mentioned in methods) after normalization with cel-miR-39-3p. Fold-change of all the samples is plotted by calculating 2^−ΔΔCt. ND = “not detectable.” *p < 0.05, **p < 0.005, ***p < 0.0005, ****p < 0.0001. (B–D) Receiver-operating characteristic (ROC) curves curated from logistic regression classifiers of sEV^CD31 for overall impairment (B), MCI (C), or AD (D) outcomes using the forward selection technique with alpha = 0.05. All models were adjusted for age and sex. Summary of the forward selection sEV^CD31miRNA shown under each ROC curve. (E) Correlation of detected miRNAs in sEV^CD31 with the temporal cortical thickness on magnetic resonance imaging (MRI).