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Center for Brain Health, Department of Psychiatry, New York University School of Medicine, New York, New York 10016; and Nathan S. Kline Institute for Psychiatric Research (A.C.), Orangeburg, New York 10962
Address all correspondence and requests for reprints to: Dr. Antonio Convit, Center for Brain Health, HN-400, New York University School of Medicine, 550 First Avenue, New York, New York 10016. E-mail: antonio.convit{at}med.nyu.edu.
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Abstract |
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 Top Abstract IntroductionSubjects and MethodsResultsDiscussionReferences |
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Introduction |
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Although elevated cortisol resulting from endocrine disorders is clearly associated with increased blood pressure, the links between HPA axis dysregulation and essential hypertension are less clear. An early study reported no abnormalities among hypertensive individuals in the rate of cortisol secretion or levels of circulating cortisol (6). However, using more sensitive measures of HPA axis feedback control, later studies described subtle alterations in subjects with hypertension. For example, Reynolds et al. (7) reported that subjects with severe hypertension (systolic blood pressure, >160 mm Hg) had exaggerated cortisol responses to ACTH injection, but normal 24-h urinary cortisol levels and postdexamethasone (post-DEX) suppression. This suggests that hypertension may be associated with HPA axis alterations, particularly in the fast feedback loop.
Chronic elevations of cortisol levels, within the physiological range, are related to brain volume reductions and cognitive impairment (8). Some reports suggest that clinical syndromes involving chronic elevations of cortisol levels, such as Cushing’s disease, are also linked to brain atrophy, particularly hippocampal volume reductions (9, 10), as well as cognitive impairments in measures of memory, attention, and executive function (9, 11). In these patients, normalization of serum cortisol levels was associated with improvements in hippocampal volumes and cognitive function (12).
Interestingly, high blood pressure has also been associated with structural brain abnormalities, such as white matter hyperintensities (13) and increased global brain atrophy (14, 15). Large prospective studies have demonstrated that increased blood pressure during midlife predicted reductions in overall brain tissue volume (16, 17). Patients with hypertension also have lower levels of performance on neuropsychological tests of memory, attention, and abstract reasoning than subjects with normal blood pressure (18). There is emerging evidence that hypertension may particularly affect frontal brain function. For example, Raz et al. (19) reported specific decreases in prefrontal brain volume and executive function among hypertensive individuals. This effect was evident even in pharmacologically well controlled hypertension.
As described above, hypertension has been associated in different studies with HPA axis dysregulation, structural brain changes, and neuropsychological deficits. To our knowledge, this is the first report simultaneously assessing HPA axis function, cognition, and brain changes in hypertension, thus enabling us to assess the interrelations among these variables in middle-aged and elderly individuals. In this explorative study, we hypothesize that smaller brain volumes in hypertensive patients will be explained in part by impaired glucocorticoid feedback.
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Subjects and Methods |
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This is an exploratory study based on a sample of opportunity from a larger project. Sixty-seven subjects were consecutively evaluated in our center as part of this larger study. The subjects represent a typical research clinic population and were not drawn randomly from the general population.
Study subjects underwent medical, neurological, psychiatric, neuropsychological, and endocrine evaluations. Individuals with significant neurological, medical (apart from hypertension), or psychiatric disease were excluded. All participants were determined to be functioning in a clinically normal cognitive range, as assessed by the Global Deterioration Scale (20, 21). Because there is an extensive literature showing links among HPA axis function, depression, and changes in brain morphology and cognitive dysfunction (see Ref. 22 for a review), we also administered the Hamilton Psychiatric Rating Scale for Depression (23) to rule out depression as a contributing factor to hypertension-related brain changes. We excluded 13 of the 67 consecutively evaluated participants: 11 with known diabetes, one with an abnormal magnetic resonance imaging evaluation, and one whose blood pressure readings were not available. Thus, the final sample available for analyses was comprised of 54 nondiabetic, middle-aged and elderly men and women. Sample sizes noted as smaller than 54 reflect missing data for some of the variables involved in the analyses.
This study was approved by the institutional board of research associates of New York University School of Medicine. All study subjects gave written informed consent to participate.
Definition of hypertension
Blood pressure (BP) was measured twice during one of the visits to our facility. The first reading was performed at 0830 h, 30 min after the subjects arrived. A second reading was obtained at 1345 h. Subjects were classified as having hypertension when they met hypertension criteria according to the Third Report of the National Cholesterol Education Program Expert Panel (systolic BP 
130 mm Hg and/or diastolic BP 85 mm Hg on both readings; n = 16) (24). In addition, individuals, who at the time of the evaluation were being treated for hypertension with medication (n = 11) were also included in the hypertension group regardless of their blood pressure readings. Of the 54 subjects included, 27 were considered to have normal blood pressure, and 27 met this definition of hypertension.
The criteria and cutoff values that are used to define hypertension have been recently revised downward based on outcome studies (24, 25). Studies using the new criteria, such as ours, may include subjects in the hypertension group who would have previously been included in the control group. This may clarify findings by providing a more clinically homogeneous control group for comparison.
HPA measures
We assessed nocturnal (12-h) urinary free cortisol excretion as a measure of baseline cortisol secretion. On a different day, separated by a minimum of 1 wk from the urine collection night, HPA axis feedback inhibition was evaluated using the combined DEX/CRH challenge test. In this study we carried out the simplified DEX/CRH test (26).
Twelve-hour nighttime (2000–0800 h) urinary free cortisol measurement. This measure provides a global index of the total amount of cortisol produced when the subject is not physically active and therefore is more reflective of basal secretion. The 12-h nighttime sample has been shown to correlate fairly well with 24-h urine samples (27).
DEX/CRH challenge test. This in vivo challenge provides an evaluation of HPA axis feedback inhibition. Subjects took 1.5 mg DEX, orally, at 2300 h the night before they came into the laboratory for the CRH test. On the day of the test, subjects arrived at the laboratory by 1300 h and were provided with a standardized lunch. After lunch, an iv catheter was placed in the forearm and was kept patent with a heparin lock. The subject was asked to sit quietly (but was not allowed to sleep) in a lazy chair in a quiet room. The subject was allowed to read. No blood samples were drawn for at least 1 h after placement of the iv catheter to allow sufficient time for cortisol levels to return to baseline after the stress of the catheter insertion. Two independent baseline blood samples were drawn at 1452 and 1455 h to measure DEX, cortisol, and ACTH levels. At 1500 h, 100 µg CRH were given iv. Subsequently blood samples for cortisol and ACTH determinations were drawn at 1530, 1545, 1600, and 1615 h. Six milliliters of blood were collected into two chilled 3-cc EDTA tubes at each time point. Blood was kept on ice and immediately spun down in a refrigerated centrifuge (4 C). Plasma was separated into aliquots and frozen at –80 C. We used the average post-DEX baseline cortisol and ACTH levels and the area under the cortisol and ACTH curves after CRH treatment as our variables of interest.
Hormone assays
Total blood plasma cortisol was measured with a commercial enzyme immunoassay (IBL, Hamburg, Germany) with a sensitivity of 0.1 µg/dl. ACTH was measured with an RIA (Nichols Institute, Bad Nauheim, Germany) with a sensitivity of 2 pg/ml. Free urinary cortisol was measured with an RIA that uses a double-antibody (Diagnostics Product Corp., Los Angeles, CA). All assays had inter- and intraassay coefficients of variance less than 12%.
Magnetic resonance imaging
Rating of white matter hyperintensities (WMH).
We obtained complete brain coverage using a transverse fast fluid-attenuated inversion recovery (FLAIR) to rule out primary neurological disease and to quantify white matter disease due to hypertension. The fast FLAIR sequence parameters were: time to repetition (TR), 9000 msec; time to echo (TE), 110 msec; time to inversion (TI), 2500 msec; acquisition matrix, 154 x 256; field of view (FOV), 160 x 210; 20 slices; slice thickness, 5 mm; no gaps; number of excitations, 1; acquisition time, 2 min, 15 sec. The first 14 cases evaluated (before having FLAIR as part of our standard protocol) had T2-weighted fast spin echo images (parameters: TR, 7000 msec; TE, 98 msec; acquisition matrix, 256 x 256; FOV, 200 x 200 mm; number of excitations, 1; acquisition time, 3 min, 44 sec). These cases were evenly distributed between the hypertensive and normotensive groups (eight in the normotensive group and six in the hypertensive group; 
2 = 0.39; P = 0.53). WMH ratings were performed on the T2-weighted images for this subgroup.
White matter abnormalities once evident on T2 or FLAIR are unlikely to revert to normal; therefore, for those 14 subjects with white matter ratings based on the T2 images, we confirmed the ratings using FLAIR images that were acquired 12–24 months later as part of their participation in the parent longitudinal study. The inspection of the later FLAIR images did not change our T2 ratings for those 14 subjects.
We carried out a semiquantitative assessment of WMH using the modified Fazekas scale (28). This scale assigns scores ranging from 0–3 for two areas: periventricular (0 = absence; 1 = caps or pencil-thin lining; 2 = smooth halo around the lateral ventricles, 3 = irregular periventricular) and deep white matter (0 = absence, 1 = punctuate foci; 2 = minimal confluence of foci; 3 = large confluent areas).
Volumetric measurements. For the brain measurements, a thin slice, three-dimensional, sagittal T1-weighted, spoiled gradient recalled (SPGR) sequence was used. The SPGR sequence parameters were: TR, 35 msec; TE, 9 msec; flip angle 60 degree and 1 signal average; 120 slices; 1.2 mm slice thickness with no gap, acquisition matrix, 256 x 128; FOV, 250 x 250 mm; acquisition time, 9 min. The SPRG study provided data to create reformatted (coronal, axial, sagittal, and oblique) images and adequate T1-weighted contrast for the accurate determination of the regional volumes. Using our locally developed Multimodal Image Data Analysis System software, regions of interest were drawn on coronal images created as reformats from the sagittal SPRG images. We outlined individual temporal and frontal lobe structures using our published parcellation methods (29, 30), briefly outlined below. The volume of structures was calculated by multiplying the cross-sectional area by the slice thickness and summing across slices. We measured brain regions known to play a role in different cognitive function domains: hippocampus, superior temporal gyrus, and prefrontal region. We also obtained measures of global brain atrophy and frontal atrophy (see below).
Hippocampus. Hippocampal volume was measured using standardized boundaries. The hippocampal volumes so derived were validated at postmortem and are similar to those reported by other investigators (31, 32). Our image analysis software, Multimodal Image Data Analysis System, allows the simultaneous display of orthogonal views; distinguishing the boundaries of the hippocampus and the amygdala is greatly simplified with simultaneous access to the sagittal and axial data (33). We achieved high levels of agreement between two raters (intra class correlation coefficient = 0.94; n = 16) using this method.
Superior temporal gyrus. The superior temporal gyrus has as a medial border a line joining a reference point in the middle of the temporal horn to the most medial and inferior extension of the Sylvian fissure (29). The superior margin of the gyrus is the Sylvian fissure. The inferior border is the superior temporal sulcus.
Prefrontal region. The frontal lobe, which extends from the anterior pole to the precentral sulcus, can be divided into several major regions (30): the motor cortex and supplementary motor region, the prefrontal region, and the frontal pole. The prefrontal region is bound anteriorly by the cingulate sulcus and posteriorly by the anterior margin of the supplementary motor cortex. We differentiate the prefrontal cortex from the supplementary motor region geometrically, using as a boundary the coronal plane that bisects the distance between the cingulate sulcus and the precentral sulcus in two equal parts. By applying a thresholding procedure to the cerebrospinal fluid (CSF) portion of this frontal intracranial volume, we estimated the degree of frontal atrophy. Our frontal lobe parcellation method has a high level of reproducibility (30).
Cerebral vault size. To adjust for individual differences in head size and to obtain a measure of overall (global) atrophy, we obtained an intracranial vault volume (ICV). We used every fifth sagittal image (midpoints every 3.3 mm) to trace the outline of the supratentorial compartment by following the margins of the dura and tentorium. This estimate of premorbid brain size (before the atrophy associated with aging) is used to account for the variability in overall brain size, which may, in turn, impact on the size of the brain structures of interest. We used a thresholding procedure to estimate the CSF portion of this ICV, which was then used as a measure of global atrophy.
Head size correction. Several methods have been used to adjust for individual differences in head size, including the computation of ratios or the use of regression to obtain residualized volumes. A recent review (34) shows that ratios can lead to spurious correlations. Thus, we residualized all brain volumes to head size (ICV) by means of regression analyses and then used the residualized volumes in the subsequent statistical analyses. Similarly, the measure of global atrophy, the CSF volume within the intracranial vault, was residualized to head size. The prefrontal atrophy measure was obtained by residualizing prefrontal CSF to prefrontal intracranial volume. For ease of reference and to make our results comparable with those of other published studies, we also report raw values for all the brain measures in Results.
Neuropsychological and functional measures
To describe the functional and overall cognitive status of the participating subjects, the Global Deterioration Scale (GDS) (20, 21) and the Shipley Institute of Living Scale (35) were used. The Shipley provides an estimate of intelligence quotient (IQ). To allow comparison to other studies, the Mini Mental State Exam (36) was also used.
The neuropsychological battery was comprised of tests to measure attention (Digit Symbol Substitution Test) (37), perceptual speed (38), working memory (Digit Span Backward, taken from the Wechsler Memory Scale revised) (39), declarative memory (Paragraph Recall Immediate and Delayed, taken from the Wechsler Memory Scale revised) (39), and two measures of executive function [the word-color interference score from the Stroop (40) and the number of excessive moves in the computerized version of the Tower of London (41)].
Data analysis
HPA parameters were not normally distributed (all indices of skewness >1.0). Therefore, in the analyses we used log-transformed measures for all cortisol and ACTH measures. Group differences between hypertensive and nonhypertensive subjects in background variables such as age, body mass index (BMI), and depressive symptoms (Hamilton scale) were examined using independent-sample t tests. Distribution differences in gender and GDS (a measure of overall functioning) were tested using 2 tests.
Group differences (hypertension vs. control) in ratings of WMH were tested using 2 tests. We examined group differences (hypertension vs. control) in residualized brain volume measures (see methods above), log-transformed HPA axis markers, and cognitive tests using univariate General Linear Models.
Because age, gender, and BMI are likely to influence the brain, HPA axis function, and/or cognition, we statistically controlled for these variables by including them as covariates in the General Linear Models. Association between HPA axis function and brain measures were tested using partial correlation coefficients, also controlling for age, gender, and BMI.
All analyses were performed using SPSS statistical software (version 12.0, SPSS, Inc., Chicago, IL). A value of P < 0.05 was considered statistically significant, whereas a value of P 
0.10 was interpreted as a statistical trend. Data are presented as the mean ± SD.
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Results |
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The sample was comprised of 27 hypertensive and 27 normotensive participants. The normotensive group had a mean systolic BP (averaged across the two measurements) of 116.7 ± 9.5 mm Hg and a mean diastolic BP of 71.6 ± 5.5 mm Hg. Untreated patients with hypertension had average systolic BP of 138.7 ± 9.6 mm Hg and diastolic BP of 79.4 ± 8.8 mm Hg. This difference was statistically significant (t = 7.3; P < 0.001 and t = 3.6; P = 0.001 for systolic and diastolic BPs, respectively). The treated hypertensive patients (n = 11) had a mean systolic BP of 123.4 ± 13.2 and a mean diastolic BP of 72.5 ± 7.3 mm Hg.
Descriptive statistics of the two groups are shown in Table 1
. The groups did not differ in IQ (Shipley IQ), global measures of cognition (Mini Mental State Exam), or depression scores (Hamilton Depression Scale; see Table 1). GDS scores were also not significantly different (hypertensives: GDS 1, n = 10; GDS 2, n = 14; GDS 3, n = 3; controls: GDS 1, n = 10; GDS 2, n = 17; GDS 3, n = 0; 2 = 3.3; P = 0.19). The two groups also did not differ on other variables often associated with hypertension, such as fasting glucose and high density lipoprotein cholesterol or triglyceride levels.
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2 = 2.7; P = 0.10). Consequently, age, gender, and BMI were considered potential confounds (because they may be associated with changes in brain volumes, HPA axis activity, and/or cognition) and were statistically controlled for in all subsequent analyses. Hypertension and HPA axis
No significant differences were found in 12-h urinary free cortisol levels. There were no significant group differences in the circulating DEX levels measured just before CRH administration (t = 1.5; P = 0.14) and attained after the administration of 1.5 mg DEX at 2300 h the previous night. Furthermore, there were no group differences in cortisol or ACTH levels after overnight DEX treatment (before CRH injection). However, patients with hypertension had significantly elevated area under the cortisol curve (cortisol AUC) after CRH injection (after controlling for age, gender, and BMI; F = 6.8; P = 0.01; see Table 2).
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Patients with hypertension had smaller prefrontal volumes (intracranial vault residualized; see Materials and Methods) compared with normotensive subjects (P = 0.03) when the two groups were contrasted in univariate, two-tailed analyses. However, this difference showed only a statistical trend after controlling for age, gender, and BMI (F = 3.0; P = 0.09). The association with hypertension was specific to the prefrontal tissue volume; P values for other brain regions were larger than 0.10 (hippocampus: F = 0.1; P = 0.74; superior temporal gyrus: F = 1.9; P = 0.17; global atrophy: F = 2.2; P = 0.14; frontal atrophy: F = 2.3; P = 0.14) (see Table 3).
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2 tests showed no significant differences for periventricular WMH (2 = 1.0; P = 0.31) or deep WMH (2 = 0.1; P = 0.78) ratings between subjects with hypertension and controls. Interrelations of HPA axis markers with brain volumes
As shown in Table 4, only cortisol AUC significantly correlated with brain measures (partial correlations controlling for age, gender, and BMI). Significant positive correlations were observed with frontal and global atrophy measures, and a negative trend was observed with prefrontal volume.
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Group comparisons revealed statistically significantly lower scores in one of two tests of executive function (Tower of London: F = 5.4; P = 0.03) in hypertensive patients after controlling for age, gender, and BMI. No indications for group differences were found for measures of attention or working and declarative memory.
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Discussion |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Based on animal studies and experimental data in humans, elevations in cortisol levels have been proposed to contribute to hypertension (1). Using the combined DEX/CRH suppression test (cortisol AUC after CRH injection), we found that the hypertensive group had subtle impairments of fast feedback regulation of the HPA axis. However, markers of basal cortisol secretion (12-h overnight urine collection) and slow feedback (i.e. cortisol and ACTH levels after overnight low dose DEX treatment) were not significantly different between the two groups. This finding is in agreement with reports of high rates of hypertension among individuals with intermittent cortisol hypersecretion, as seen in glucocorticoid resistance syndrome and subclinical Cushing’s syndrome (4, 5). Our data confirm the findings of a recent study (7) that reported impaired fast feedback regulation of cortisol production after ACTH challenge in hypertensive individuals. In line with our results, this study did not find significant differences in basal urinary cortisol levels or cortisol plasma levels after DEX administration.
We found hypertension to be related to lower scores in one of two measures of executive function; the Tower of London was significantly lower, whereas the Stroop was not. In addition, measures of memory and attention were not different between groups. These findings, indicating possible frontal lobe dysfunction in hypertension, are in line with previous research in humans (19) and experimental evidence from animal studies (42). With that being said, cognitive reductions among our hypertensive patients were subtle, perhaps due to the fact that we assessed both treated and untreated patients. Our sample was not large enough to allow us to stratify by treatment. However, previous studies have reported that even pharmacologically well controlled hypertension interferes with cognitive function (19).
Despite the lack of an increased presence of white matter lesions among hypertensives, we found reduced brain volumes in this sample of middle-aged participants with relatively mild disease. Our study confirms and expands the study by Raz et al. (19); neither study found a significant reduction in temporal lobe regions, such as hippocampus and superior temporal gyrus, associated with hypertension. It is also in line with a recent report by Wiseman et al. (43), in which they describe increased global atrophy, but no association of blood pressure and hippocampal volumes in a community sample aged 70 yr or older with more severe hypertension (systolic BP, 160–179 mm Hg; or diastolic BP, 90–99 mm Hg). Our data suggest an association between hypertension and smaller prefrontal volume; even with our conservative statistical approach (two-sided testing and statistically controlling for age, gender, and BMI), we still had a trend.
It is interesting to note that in our sample the cortisol AUC showed the strongest associations with prefrontal atrophy, global atrophy, and prefrontal region volumes. To our knowledge, this is the first empirical evidence suggesting that subtle alterations in glucocorticoid feedback may account for some of the effects of hypertension on brain volume. This should be confirmed in larger, better controlled samples.
It is unclear whether the subtle alterations in the HPA axis feedback that we report to be associated with hypertension in our cross-sectional study are the cause or the effect of the prefrontal volume reductions. However, there are several possible explanations for our results.
First, impaired glucocorticoid feedback may account for the effects of hypertension on brain structure and function. Chronic elevations of cortisol levels, within the physiological range, are related to brain volume reductions and cognitive impairments (8). Mechanisms proposed to explain brain volume losses by excess glucocorticoids include neurotoxicity, decreased brain-derived growth factors, decreased neurogenesis, and loss of plasticity (44).
Second, atrophy of frontal regions may cause impaired HPA axis feedback. Animal studies suggest that prefrontal regions play an important role in HPA axis regulation, including control of the fast feedback loop (see Ref. 45 for review). In line with this hypothesis, a recent human study showed increased morning levels of cortisol in patients with lesions in the frontal cortex (46).
Third, vascular and glucocorticoid mechanisms may contribute, additively or synergistically, to the development of frontal brain atrophy in hypertension. It has long been hypothesized that increased glucocorticoid levels may potentiate ischemic injury to neurons (47). Lending support for this premise, several animal studies have shown that administration of glucocorticoids (48) or exposure to chronic stress (49) can exacerbate focal cerebral ischemia in adult animals (50). Thus, impaired HPA axis feedback may facilitate hypertension-induced neuronal damage and brain atrophy.
Raz et al. (19) have hypothesized that due to the relatively limited vascular reserve of prefrontal white matter, the frontal region may be more vulnerable to the decreased cerebral blood flow that occurs with hypertension. It is interesting to note that in hypertension, topical application of corticosteriods leads to increased peripheral vasoconstriction compared with normotensive controls (51). Although it is not known whether this phenomenon is also present in cerebral blood vessels, it is possible that subtle glucocorticoid feedback impairments may further exacerbate the vasoconstriction present in hypertension and potentiate the damaging effect of hypertension on frontal regions.
Lastly, it cannot be entirely ruled out that some of our findings are due to the lack of adjustment for multiple comparisons. Generally, adjustments for multiple comparisons in large bodies of data are recommended to avoid spurious results. However, the consistent and biologically plausible directions of effects of hypertension with increased cortisol, decreased frontal brain volumes, and lower scores of executive function in our data suggest that the effects are probably reflecting some biological signal and are not due to chance. If they were due to chance, one would expect a more random pattern of associations.
Future research should also examine these different models in samples of carefully matched controls and hypertensive patients. Such studies should include in vivo measures of cerebral vascular capacity (perfusion imaging). Examining the relative impact of hypertension on gray vs. white matter as well as white matter integrity, as measured by diffusion-weighted imaging, could provide additional insight into the mechanisms of action.
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Acknowledgments |
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Footnotes |
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First Published Online March 22, 2005
Abbreviations: AUC, Area under the curve; BMI, body mass index; BP, blood pressure; CSF, cerebrospinal fluid; DEX, dexamethasone; FLAIR, fast fluid-attenuated inversion recovery; FOV, field of view; GDS, Global Deterioration Scale; HPA, hypothalamo-pituitary-adrenal; ICV, intracranial vault volume; IQ, intelligence quotient; SPGR, spoiled gradient recalled; TE, time to echo; TI, time to inversion; TR, time to repetition; WMH, white matter hyperintensity.
Received November 4, 2004.
Accepted March 15, 2005.
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