1 Introduction
Worldwide, cardio- and cerebrovascular diseases are identified as leading causes of death, and are attributable to the common underlying mechanism of atherosclerosis.[1] Hypertension is one of the most important independent risk factors of atherosclerosis.[2] hypertension -related damage. Endothelial dysfunction is the initial pathophysiological step in vascular damage.[3] hypertension .[4] [5] hypertension and its growth is a good indicator of atherosclerosis progression.[6] [7] Arterial stiffness , a functional arterial wall feature described via AIx and PWV, is an early sign of atherosclerosis.[8] arterial stiffness is an independent predictor of cardiovascular events and all-cause mortality.[9]
The impact of hypertension on vascular remodeling is a well-known phenomenon, but consequential cognitive impairment has been debated in the scientific literature. The American Heart Association published a scientific statement in 2016 which stated that there were insufficient data to make evidence-based recommendations.[10] [11] [10]
Substantial evidence supports a link between hypertension and cognition .[12,13] Hypertension disrupts the structure of cerebral blood vessels, promotes atherosclerosis, and impairs vital cerebrovascular regulatory mechanisms. Hypertension has been associated with executive dysfunction, reduced mental processing speed, and, less frequently, memory deficits.[14] hypertension , little is known about the reversibility of cognitive changes in this population.[13]
The renin-angiotensin-aldosterone system (RAAS) has a central role in the pathophysiology of hypertension as well as cardio- and cerebrovascular diseases evolving from atherosclerosis.[15,16] [17,18] [19] hypertension is still under investigation. Therefore, in this 3-month follow-up study, we aimed to evaluate the influence of ACE inhibitors on early morphological and functional changes of the arterial wall and cognitive performance impairments in newly diagnosed primary hypertensive patients. We also investigated the associations between initial atherosclerotic arterial wall alterations and cognitive function parameters.
2 Methods
2.1 Patients
From January 2014 to January 2017, 59 patients with recently diagnosed primary hypertension were recruited into our baseline investigations (Fig. 1 ). No participants were on antihypertensive treatment at baseline measurements. After baseline investigations, antihypertensive monotherapy was commenced with an angiotensin-converting enzyme inhibitor (enalapril or lisinopril). Twenty-nine patients had been excluded from the study secondary to non-compliance or switching from ACE inhibitor therapy to another antihypertensive agent due to side effects or inefficacy. Hence, the final data analysis involved 30 patients (age: 43.60 ± 11.34 years; male/female ratio: 2.0, body mass index: 27.81 ± 4.04 kg/m2 ) who completed the follow-up visit at three months. No subjects were pregnant or suffered from malignancy, impaired liver or renal function, alcohol or drug dependence, infectious diseases, or symptomatic cerebro- or cardiovascular diseases as observed through medical history, general physical and neurological examination, routine laboratory tests, and cerebral computed tomography scan. There were 5 smokers among the study participants. Thirty percent of patients had higher education. The study protocol was approved by the Ethics Committee of the University of Debrecen and the study was carried out in accordance with the Declaration of Helsinki. All participants gave written informed consent.
Figure 1: Flow diagram of the study.
2.2 Laboratory assays
Venous blood samples were collected after overnight fasting. Serum ions, basic kidney functions, glucose levels, lipid profile, and complete blood count were assayed by routine automated laboratory methods. High-sensitivity C-reactive protein was assessed by turbidimetric assay on an Integra 800 analyzer (Roche Diagnostics, Mannheim, Germany). Hemoglobin A1C was measured by high-performance liquid chromatography (BioRad, Hercules, CA). Fibrinogen concentration was determined by the Clauss method.
2.3 Ambulatory blood pressure monitoring
Twenty-four-hour ambulatory blood pressure monitoring (ABPM) was performed using the ABPM-04 device (Meditech Ltd., Budapest, Hungary). Blood pressure was recorded every 15 minutes during the daytime (6 am through 10 pm ) and every 30 minutes during nighttime (10 pm through 6 am ). Based on ABPM data, mean systolic and diastolic blood pressures and systolic and diastolic hyperbaric indices for daytime and nighttime were determined.
2.4 Common carotid intima-media thickness measurement
Philips HD 11 XE ultrasound equipment with a 7.5-MHz linear transducer was used to measure common carotid intima-media thickness (IMT). Online measurements of IMT were performed in the far artery wall of the common carotid arteries, 10 mm proximal to the carotid bulb. IMT was determined as the distance between the lumen-intima interface and the upper layer of the adventitia. All measurements were performed on frozen, enlarged images at end-diastole, with the transducer in the mediolateral direction. Ten measurements of IMT were performed on both sides. The mean of the 20 IMT values in each patient was calculated.
2.5 Brachial artery flow-mediated dilatation measurement
Brachial artery flow-mediated dilatation (FMD) assessment was performed using the HP Sonos 5500 ultrasound with 10-MHz linear assay transducer. A B-mode longitudinal section was obtained from the brachial artery above the antecubital fossa. A forearm cuff was inflated to supra-systolic pressures for 5 minutes to induce arterial occlusion. Upon cuff release, the induced reactive hyperemia promotes an increase in shear stress-mediated NO release and subsequent vasodilation. FMD is expressed as the percent increase in arterial diameter following cuff release with the arterial diameter at baseline as reference.
2.6 Assessment of arterial stiffness
Measurements were carried out using a TensioClinic arteriograph (TensioMed Ltd., Hungary). Arterial stiffness was assessed by determining the augmentation index (AIx) and pulse wave velocity (PWV). The method is based on the phenomenon of myocardial contractions generating pulse waves in the aorta. The pulse wave travels to the arm (first wave), where the cuff is located, then back to the aorta. The first wave is reflected at the bifurcation of the aortic wall; therefore, a second, reflected wave appears as a late systolic peak. The cuff detects both pulse waves. AIx is calculated from the amplitudes of the first and second wave and represents the pressure difference between the late systolic peak and the early systolic peak divided by the pulse pressure. PWV is the ratio of the jugular fossa–symphysis distance and the reflection time at 35-mmHg suprasystolic pressure on the brachial artery.
2.7 Neuropsychological assessment
All patients underwent a comprehensive 1.5-hour long neuropsychological examination carried out and evaluated by trained psychologists. The test battery was composed specifically for the determination of the main neurocognitive functions as listed by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM -5 ): reaction time, attention, executive function, learning, memory, and perceptual-motor skills. The battery included the most sensitive tests to reveal minor cognitive function deviations, which are not necessarily evident during everyday activity. The categorization shown in Table 3 was used to assign each test of the battery to 1 of 3 neuropsychological domains of importance in hypertension -related cognitive impairment.
Table 3: Neuropsychological tests and questionnaires (n = 30).
Because anxiety and depression assessment is a basic requirement in neurocognitive examination, the subjects filled out the State-Trait Anxiety Inventory and the Beck Depression Inventory; this enabled us to also examine if higher levels of these variables have a negative influence on performance.
2.8 Statistical analysis
Statistical analysis was performed using Stata version 15 (StataCorp LLC, College Station, TX). P < .05 was regarded as statistically significant. Baseline and follow-up levels of variables were described using standard statistics and compared using paired t tests if normality assumptions were satisfied, or Wilcoxon matched-pairs signed-ranks tests otherwise. Location and variability parameters mentioned in the body text are given as mean ± standard deviation or median (interquartile range).
Overall scores for each neuropsychological domain were derived by direction-correcting each variable in the domain (i.e., multiplying by negative 1 if necessary, so that greater values represent better performance), standardizing them, and taking their average.
2.9 Correlation estimates were based on Pearson's correlation coefficient
Associations between clinical data and neuropsychological outcomes were evaluated using linear regression. The outcome variable was additive change from baseline to follow-up in the neuropsychological parameter. Explanatory variables included baseline value and additive change in the clinical variable (key explanatory variables), an interaction term between them, age, sex, and baseline of the neuropsychological parameter. Model-predicted outcomes were plotted as a function of the key explanatory variables to assess which combination of the latter was predictive of significant changes in the outcome. Statistical proof for the relevance of the clinical parameter was interpreted through the joint P value associated with the key variable pair (general indication of relevance) as well as through the P value associated with the interaction term (indicating an interplay between baseline and change, i.e., a positive change from a low baseline has a different effect than one from an already high baseline, and likewise for negative changes).
3 Results
3.1 Laboratory and ABPM data
The laboratory characteristics of study participants at baseline and after 3 months of ACE inhibitor therapy are summarized in Table 1 . There were no significant differences at 3-month follow-up compared to baseline in traditional vascular risk parameters, renal function, or complete blood count. ABPM data are demonstrated in Table 2 . ABPM revealed a significant decrease in systolic and diastolic blood pressures and in systolic hyperbaric index for both active (daytime) and passive (nighttime) evaluations. However, no significant differences were detected between baseline and follow up in daytime or nighttime diastolic hyperbaric index.
Table 1: Laboratory parameters of study participants.
Table 2: Ambulatory blood pressure monitoring data.
3.2 Arterial wall morphology and functional characteristics
No significant decrease in the IMT value was observed after 3 months of ACEI therapy (0.55 ± 0.10 mm at baseline vs 0.54 ± 0.08 mm at follow-up, P = .125). There was no significant increase in the FMD value after 3-month ACE inhibition (7.52 ± 2.21% at baseline vs 8.12 ± 2.60% at follow-up, P = .393). Arterial stiffness parameters also did not differ significantly between baseline and 3-month follow-up (AIx: –17.47 ± 34.44% vs –23.09 ± 34.32%, P = .078; PWV: 9.3 ± 2.40 m/s vs 9.0 ± 2.04 m/s, P = .141).
3.3 Neuropsychological tests and questionnaires
The neuropsychological test results are given in Table 3 . After three months of ACEI therapy, significant improvement was revealed in executive function (–0.038 (0.936) vs 0.233 (0.447); P = .001); study patients had a significantly better performance in visual fluency (5-Point Test, 96.27 (11.76) vs 98.68 (5.26); P = .009) and inhibition skills (Stroop Test Victoria Version, 2.0 (0.533) vs 1.78 (0.444); P = .010). Complex attention and immediate memory overall scores did not show a significant improvement from baseline to follow up. The study participants reached significantly lower scores on the tests evaluating anxiety (Spielberger State Anxiety Inventory, P = .016) and depression (Beck Depression Inventory, P = .031) at follow-up compared to baseline.
We analyzed the relationships between the morphological and functional characteristics of the arterial wall and the parameters of cognitive functions by Pearson correlation analysis. Significant negative correlations were identified between IMT and complex attention (r = –0.482, P = .008 at baseline; r = –0.598, P = .0008 at follow-up), executive function (r = –0.420, P = .006 at baseline; r = –0.617, P = .0005 at follow-up) and immediate memory (r = –0.420, P = .026 at follow-up) overall scores. AIx had significant and negative correlations with complex attention (r = –0.410, P = .027 at baseline; r = –0.568, P = .001 at follow-up), executive function (r = –0.441, P = .017 at baseline; r = –0.374, P = .046 at follow-up), and immediate memory (r = –0.507, P = .005 at follow-up) overall scores. Significant and negative univariate correlation of PWV with complex attention overall score at follow up (r = –0.490, P = .007) was found, but a positive association of PWV with state anxiety score at follow-up (r = 0.397, P = .035) was detected.
FMD was correlated significantly and negatively with Spielberger Trait Anxiety score at baseline (r = –0.606, P = .001).
In evaluating the associations between ABPM data and neurocognitive performance overall test scores, systolic blood pressure correlated significantly and negatively with immediate memory overall score at baseline (r = –0.409, P = .034). Furthermore, the systolic hyperbaric index had significant and negative relationships with immediate memory overall score (r = –0.436, P = .023) and executive function overall score (r = –0.475, P = .012) at baseline.
Analyzing the associations of anxiety and depression levels with overall test scores, state anxiety showed significant and negative correlations with immediate memory at baseline (r = –0.413, P = .023) and executive function at follow up (r = –0.398, P = .030).
The improvement in executive function overall score were associated with baseline thrombocyte count and change in thrombocyte count (joint effect P = .006 and interaction P = .023) presented in Figure 2 (A), with baseline hematocrit values and change in hematocrit values (joint effect P = .023, interaction P = .012) presented in Figure 2 (B), and also with baseline red blood cell count and change in red blood cell count (joint effect P = .024, interaction P = .005) presented in Figure 2 (C).
Figure 2: Executive function overall score changes from baseline to follow-up as a function of changes in, and baseline levels of, thrombocyte count (A), hematocrit (B), and red blood cell count (C). Marker labels indicate P value of model-predicted change at that location. HTC = hematocrit, NS = not significant, RBC = red blood cell, THR = thrombocyte.
4 Discussion
Since many of the more advanced vascular lesions in hypertension are not completely reversible, the importance of prevention, early treatment, and more effective blood pressure control is clearly demonstrated.[20,21] hypertension -induced early vascular alterations and consequential changed cognitive functions remained unanswered in critical aspects. By reducing the harmful effects of angiotensin II, RAAS blockade with an ACE inhibitor might provide a rational approach to reverse early hypertension -induced vascular damage and cognitive alterations.[3,22] hypertension -induced initial vascular and cognitive changes.
Abnormal endothelial function, arterial stiffness , and carotid media thickening have been implicated in the pathophysiology of essential hypertension .[4,6,8] arterial stiffness parameters (AIx, PWV) with arteriograph.
Miyamoto et al found that ACE inhibitor and angiotensin II receptor blocker (ARB) antihypertensive treatment can improve FMD-assessed endothelial dysfunction better than other drug types.[23] [24] [25]
On the other hand, in the study by Ohta et al, carotid IMT increased progressively in spite of well-controlled home blood pressure values.[26] [27] [28]
All classes of antihypertensive drugs might potentially decrease arterial stiffness passively via the reduction of the distending pressure.[29,30] arterial stiffness , and RAAS blockade in patients with hypertension has more pronounced effects on arterial stiffness than other antihypertensive drugs.[31,32] arterial stiffness measured by PWV or AIx, and concluded that ACEI have modest beneficial effects in reducing arterial stiffness , and this effect is at least partly independent of blood pressure changes.[33] arterial stiffness parameters.
Chronic arterial hypertension is a major contributor to cognitive impairment.[34] hypertension on cognitive function in midlife and late-life. Executive function and processing speed seem to be the cognitive domains most affected, but memory can also be impaired.[13] hypertension , several key questions remain to be answered regarding the impact of antihypertensive treatment on cognitive change in this population.[13] [35] [36,37] [38] [28] cognition or reducing cognitive decline,[39–41] [13]
The association between hypertension and anxiety is well-recognized.[42] [38] hypertension reached significantly lower anxiety levels in the previous investigation of our research team after 1 year of antihypertensive therapy, and in this study after three months of ACE inhibitor treatment. Previous data are contradictory regarding the relationship between hypertension and depression. Scalco et al reported earlier that hypertension was associated with depression.[43] hypertension would be a risk factor for depression.[44] [45] [46–49] hypertension .
Carotid intima-media thickness and arterial stiffness may serve as risk markers for vascular cognitive impairments.[34] arterial stiffness with cognitive function.[34,50,51] hypertension .
As less evidence is available on the relationship between blood cell count and cognitive function,[52–54]
A limitation of our study is the potential selection bias that might exist due to the fact that the Department of Neurology was recruiting untreated hypertensive patients for this study. In most cases, hypertension is diagnosed in primary care in Hungary; this study, however, involved patients referred to us by primary care on suspicion of hypertension , which was to be confirmed by our team through a diagnostic workup (ambulatory BP monitoring etc). Self-selection of patients included in the study is also possible since more than half of eligible patients were lost during the follow-up period. This results in a relatively small size of the study sample, which limits the statistical power of our investigation; however, the significant improvement in cognitive alteration caused by early hypertension -related vascular lesions underlines the positive impact of ACE inhibition on vascular deteriorations and consequential cognitive impairments. Furthermore, the measurements of morphological and functional characteristics of the arterial wall and the assessments of cognitive function parameters were performed after a short period of ACE inhibitor treatment. We, therefore, cannot provide information about what duration of ACE inhibition is required for significant improvement to arterial wall alterations.
5 Conclusion
In conclusion, timely and effective antihypertensive therapy with ACE inhibitors for as short a period as 3 months was observed to produce significant improvements in cognitive performance compromised by early hypertension -related vascular damage. Our study suggests that ACE inhibitors might serve as a potential agent for the reversal of cognitive alterations induced by initial vascular damage associated with early-stage hypertension . As to longer-term treatment, further prospective data are essential to determine the duration of ACE inhibition required for significant improvement in early hypertension -related vascular damage.
Acknowledgments
The authors owe special thanks to our colleague Ildikó Borók József Ferencné for conducting medical diagnostic measurements and sonography.
Author contributions
Conceptualization: Mónika Andrejkovics, László Csiba.
Data curation: Enikő Csikai, Bernadett Balajthy-Hidegh.
Formal analysis: Katalin Réka Czuriga-Kovács, László Csiba.
Funding acquisition: László Csiba.
Investigation: Enikő Csikai, Bernadett Balajthy-Hidegh, Gergely Hofgárt, Ágnes Diószegi, Róbert Rostás.
Methodology: Mónika Andrejkovics, László Kardos.
Project administration: Enikő Csikai, Bernadett Balajthy-Hidegh.
Resources: László Csiba.
Supervision: Mónika Andrejkovics, László Csiba.
Validation: László Kardos.
Visualization: László Kardos.
Writing – original draft: Enikő Csikai, László Kardos, Éva Csongrádi.
Writing – review & editing: Katalin Réka Czuriga-Kovács, László Csiba.
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