Neurovascular coupling, functional connectivity, and cerebrovascular endothelial extracellular vesicles as biomarkers of mild cognitive impairment

Abstract

Introduction: Mild cognitive impairment (MCI) is a prodromal stage of dementia. Understanding the mechanistic changes from healthy aging to MCI is critical for comprehending disease progression and enabling preventative intervention.

Methods: Patients with MCI and age-matched controls (CN) were administered cognitive tasks during functional near-infrared spectroscopy (fNIRS) recording, and changes in plasma levels of extracellular vesicles (EVs) were assessed using small-particle flow cytometry.

Results: Neurovascular coupling (NVC) and functional connectivity (FC) were decreased in MCI compared to CN, prominently in the left-dorsolateral prefrontal cortex (LDLPFC). We observed an increased ratio of cerebrovascular endothelial EVs (CEEVs) to total endothelial EVs in patients with MCI compared to CN, correlating with structural MRI small vessel ischemic damage in MCI. LDLPFC NVC, CEEV ratio, and LDLPFC FC had the highest feature importance in the random Forest group classification.

Discussion: NVC, CEEVs, and FC predict MCI diagnosis, indicating their potential as markers for MCI cerebrovascular pathology.

Highlights: Neurovascular coupling (NVC) is impaired in mild cognitive impairment (MCI). Functional connectivity (FC) compensation mechanism is lost in MCI. Cerebrovascular endothelial extracellular vesicles (CEEVs) are increased in MCI. CEEV load strongly associates with cerebral small vessel ischemic lesions in MCI. NVC, CEEVs, and FC predict MCI diagnosis over demographic and comorbidity factors.

Keywords: endothelium; extracellular vesicles; functional connectivity; mild cognitive impairment; neurovascular coupling.

FIGURE 1

Clinical grading of small vessel ischemic lesions in control and participants with mild cognitive impairment (MCI). (A) Control (CN) participant (age: 68 years old, sex: female) with historical magnetic resonance imaging (MRI), recorded in 2023 shows a Fazekas scale grading of 0, indicating no small vessel ischemic damage determined by this grading classification. (B) Participant with MCI (age: 65 years old; sex: female) historical MRI, recorded in 2023, shows a Fazekas scale grading of 1, indicating moderate small vessel ischemic damage. Fazekas scale grading was assessed for deep white matter hyperintensities.

FIGURE 2

Fluid cognitive performance is diminished in participants with mild cognitive impairment (MCI), while crystalized intelligence is maintained in normal age rage. (A) Patients with MCI had a significant decrease in crystalized intelligence metric—picture vocabulary test (PIVT)—compared to control (CN), but maintained cognitive abilities in normal age, sex, race, and education range (Normative population mean = 50, SD = 10). Fluid cognition was impaired compared to age‐matched CNs in domains of inhibitory control and attention (FICA), working memory (LSMT), cognitive flexibility (DCCS), episodic memory (PSMT), and processing speed (PCPS). Fully corrected T‐score compares the test taker score to the nationally representative National Institutes of Health (NIH) toolbox sample, adjusting for age, sex, race, and educational attainment. (B) Processing speed was directly measured by oral symbol digit test and patients with MCI had decreased number of correct responses compared to age‐matched controls. (C) Fluid cognition composite scores, including performance on FICA, LSMT, DCCS, PCPS, and PSMT, indicate overall fluid cognitive deficit in MCI compared to age‐matched controls. Violin plots solid and dashed lines are presented as median and interquartile range, respectively; n = 20 participants per group. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 by two‐tailed Student's t‐test (unpaired).

FIGURE 3

Working memory performance and neurovascular coupling (NVC) is impaired in participants with mild cognitive impairment (MCI). (A) Accuracy (d’) (see formula in main text) during 2b working memory n‐back task was decreased in MCI compared to age‐matched controls (CN) and (B) reaction time was increased during the most cognitively challenging 2b task. Panels C and D show the NVC response (relative change in oxy‐hemoglobin [HbO]) during the n‐back task. To determine the NVC response to cognitively challenging tasks, the contrast: (2‐b+ 1‐b) – 0b_2 was used for CN, MCI, and (E) group comparison (MCI – CN). The black circle represents the left dorsolateral prefrontal cortex (LDLPFC), a region responsible for working memory. (C) CN group showed increased NVC (red shaded areas), and (D) MCI group showed no change to increased cognitive workload across the prefrontal cortex. (E) Group analysis of this contrast showed decreased NVC (blue‐shaded areas) in the LDLPFC and medial prefrontal cortex in MCI compared to age‐matched controls. (F) Averaged NVC responses across the entirety of the n‐back paradigm determined that MCI patients had decreased NVC responses localized to the LDLPFC and medial PFC compared to controls. (G) Regression coefficients (beta) from (F) were extracted from the LDLPFC channels and show decreased NVC in MCI compared to age‐matched controls. Violin plots (A, B) solid and dashed lines are presented as median and interquartile range and box and whiskers graph (G) is presented as median (solid line), interquartile range (IQR) and minimum and maximum. Panels C, D, E, and F t‐contrast maps were generated using Brain AnalyzIR toolbox implemented pipeline based on General Linear Model approach. For further details see main text. For Panel A: 0b_1 n = 19 CN, 20 MCI, 0b_2 n = 15 CN, 16 MCI, 1b n = 15 CN, 19 CN, 2b n = 18 CN, 19 MCI. For Panel B: 0b_1 n = 19 CN, 20 MCI, 0b_2 n = 19 CN, 20 MCI, 1b n = 19 CN, 19 MCI, 2b n = 18 CN, 19 MCI. Panels A and B, robust regression outlier removal (ROUT) method was used for extreme outlier detection (tuning constant Q = 0.1%). **p < 0.01, ****p < 0.0001 by two‐way analysis of variance (ANOVA) with Bonferroni's multiple comparisons test. For Panels C–G: n = 19 CN, 18 MCI. Panels C–F: Colors refer to t‐statistics thresholded by q < 0.05 (obtained after false discovery rate [FDR] correction) Panel G: **p < 0.01 by unpaired t‐test. 0b_1, first 0‐back; 0b_2, second 0‐back; 1b, 1‐back; 2b, 2‐back; NVC, neurovascular coupling.

FIGURE 4

Functional connectivity (FC) is decreased in participants with mild cognitive impairment (MCI) during a working memory task. Individual global (i.e., referring to all functional near‐infrared spectroscopy (fNIRS) channels across the frontal cortex) network metrics show no change in number of normalized connections (i.e., node degree) in participants with MCI compared to age‐matched controls (CN) during each task (A) and all tasks averaged (B). Normalized left dorsolateral prefrontal cortex (LDLPFC) ‐averaged local node degree showed decreased number of connections in participants with MCI compared to CN irrespective of task (C) and all tasks averaged (D). Correlation matrices (E‐L) determine the strength of surrogate‐thresholded Pearson‐correlation (p < 0.05) coefficient values between each channel. Matrix connection values are inverse Fisher‐z transformed (i.e., atanh(z(r))) to obtain a normally distributed sample then averaged across the duration of each n‐back task (72 s). These data show increased connection strength (dark red) in and between areas of the LDLPFC in CN (E‐H) compared to participants with MCI (I‐L). Global connection strength, a global network metric representing the average number of connections adjusted relative to the maximum connection strength showed no change between MCI and CN (M) and n‐back task‐averaged connection strength (N). Following similar analytical measures as global connection strength (see main text for details), LDLPFC significant strength of connection to the rest of the cortex determined decreased LDLPFC connection strength irrespective of task (O), and a trend of decreased connection strength when all n‐back tasks were averaged in patients with MCI compared to CN (P). For Panels A, C, M, O: 0b_1 n = 20 CN, 20 MCI, 0b_2 n = 20 MCI, 1b n = 20 CN, 19 MCI, 2b n = 19 CN, 19 MCI following ROUT method; *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 by 2‐way ANOVA with Bonferroni's multiple comparisons test. For Panel C 0b_2 n = 18 CN and Panels A, M, O n = 20 CN following the ROUT method. For Panel B, D, N, P: n = 19 CN, 18 MCI; *p < 0.05, **p < 0.01 by Mann–Whitney unpaired t‐test.

FIGURE 5

Participants with mild cognitive impairment (MCI) have increased cerebrovascular endothelial extracellular vesicles (CEEVs). Representative image of age‐matched control (CN) (A) and MCI (B) CEEV load. The ratios of cerebrovascular to other vascular vesicles were assessed by dividing the number of endothelial‐ and MAL‐positive vesicles by the number of all vesicles of endothelial origin (EEV) (endothelial+/MAL+ divided by endothelial+/MAL+ + endothelial+/MAL‐) and expressed as percentage (C). Panel C shows a significant increase in CEEV% in MCI compared to CN. Panel D shows a significant increase in CEEV concentration (events/μL) in MCI compared to CN. Panel E shows distribution of CEEVs to patients Fazekas scale grading. CEEV% had a significant correlation to increased WMH load. *p < 0.05, **p < 0.01 by Mann–Whitney unpaired t‐test. Panel E rho and p values were obtained by nonparametric Spearman correlation.

FIGURE 6

Neurovascular coupling (NVC), cerebrovascular endothelial extracellular vesicles (CEEVs), and functional connectivity (FC) are the most informative features in mild cognitive impairment (MCI) classification. We determined an optimal classification model using random Forest integrated with leave‐one‐out cross‐validation (LOOCV). Feature importance scores were assigned to variables, highlighting the model's predictive capability. Variables selected for analyses were neurovascular measures (NVC and FC metrics), CEEVs, and data either known to contribute to progression from aging to MCI, and/or data that had a trend toward a differential distribution between groups. The top three features were left dorsolateral prefrontal cortex (LDLPFC) NVC, CEEV ratio, and task‐averaged LDLPFC connection strength ( ^w ) with importance values of 0.4052, 0.3091 and 0.0926, respectively. These features were selected for the final model and following 100 runs with different test‐train splits, the chosen model showed a mean predictive accuracy of 68.00%, SD 16.00%. Individual model evaluation, highlighting its validity, achieved a precision of 88.57%, recall of 85.71% and an F1 score of 85.08%. ^w $\overline{D_{LDP}}$, weighted task‐averaged LDLPFC node degree; $\overline{D}$, task‐averaged global node degree; ^w $\overline{D}$, weighted task‐averaged global node degree.

FIGURE 7

Summary of pathologic progression from aging to mild cognitive impairment (MCI). In older age, neurovascular coupling (NVC) is impaired and there is an increase in global functional connectivity (FC) that acts as a memory/cognitive compensation mechanism. We show in MCI, NVC is further decreased, and the FC compensatory response is lost, which classifies MCI with high precision and validity. Cerebrovascular endothelial extracellular vesicles (CEEVs) were elevated in MCI patients compared to controls and significantly correlated with MCI patient small vessel ischemic damage, cognition and FC, and was the second most important feature in MCI classification, potentially implicating CEEVs in the pathogenesis of MCI.