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Endocrinology Vol. 146, No. 3 1372-1381
Copyright © 2005 by The Endocrine Society

Correlations between Hypothalamus-Pituitary-Adrenal Axis Parameters Depend on Age and Learning Capacity

O. C. Meijer, B. Topic, P. J. Steenbergen, G. Jocham, J. P. Huston and M. S. Oitzl

Division of Medical Pharmacology (O.C.M., P.J.S., M.S.O.), LACDR and Leiden University Medical Center, 2300 RA Leiden, The Netherlands; and Institute of Physiological Psychology (B.T., G.J., J.P.H.), University of Düsseldorf, 40225 Düsseldorf, Germany

Address all correspondence and requests for reprints to: O. C. Meijer, Division of Medical Pharmacology, Leiden/Amsterdam Center for Drug Research and Leiden University Medical Center, P.O. Box 9502, 2300 RA Leiden, The Netherlands. E-mail: o.meijer{at}lacdr.leidenuniv.nl.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Glucocorticoid hormones are released after activation of the hypothalamus-pituitary-adrenal (HPA) axis and in the brain can modulate synaptic plasticity and memory formation. Clear individual differences in spatial learning and memory in the water maze allowed classification of groups of young (3 months) and aged (24 months) male Wistar rats as superior and inferior learners. We tested 1) whether measures of HPA activity are associated with cognitive functions and aging and 2) whether correlations of these measures depend on age and learning performance. Basal ACTH, but not corticosterone, was increased in aged rats, with the stress-induced ACTH response exaggerated in aged-inferior learners. Aged-superior learners had lower expression of glucocorticoid receptor and CRH mRNA in the parvocellular paraventricular nucleus of the hypothalamus compared with all other groups. Hippocampal mineralocorticoid receptor and glucocorticoid receptor mRNAs differed modestly between groups, but steroid receptor coactivator and heat-shock-protein 90 mRNAs were not different. Strikingly, correlations between HPA axis markers were dependent on grouping animals according to learning performance or age. CRH mRNA correlated with ACTH only in aged animals. Parvocellular arginine vasopressin mRNA was negatively correlated to basal corticosterone, except in aged-inferior learners. Corticosteroid receptor mRNA expression showed a number of correlations with other HPA axis regulators specifically in superior learners. In summary, the relationships between HPA axis markers differ for subgroups of animals. These distinct interdependencies may reflect adjusted set-points of the HPA axis, resulting in adaptation (or maladaptation) to the environment and, possibly, an age-independent determination of learning ability.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
CORTICOSTEROID HORMONES ARE potent modulators of neuronal function. As such, they have been implicated in a wide variety of neurobiological functions and diseases (1). Circulating concentrations of cortisol and corticosterone are regulated by the hypothalamus-pituitary-adrenal (HPA) axis, with arginine vasopressin (AVP) and CRH as the two main driving hormones from the hypothalamus (2). The central sensors of HPA axis for feedback and other activities are the two corticosteroid receptors, mineralo- and glucocorticoid receptors (MR and GR), which are expressed in the brain and in pituitary corticotrophs (3).

Hippocampal neuronal excitability (4) and hippocampus-associated learning (5, 6, 7) are two aspects of brain function that are closely linked to the activity of the HPA axis. Studies using MR- and GR-specific antagonists (1), naturally occurring variations in receptor expression (8), and transgenic animals (9, 10, 11, 12) have shown that coordinate activation of MR and GR is important for proper hippocampal function. Accordingly, learning performance depends on appropriate activation of the HPA axis in the context of learning tasks, while long-term changes in HPA axis function may interfere with cognitive function (13, 14). Vice versa, the activity of the HPA axis is modulated by hippocampal activity and hippocampal MR and GR activation.

A fundamental question in aging research is why some individuals display successful brain aging, whereas others are unsuccessful and develop cognitive decline. Evidence from animal and human studies indicates that a chronic rise in circulating glucocorticoid at old age may predict cognitive decline (14). Although aging is certainly not always associated with hypercorticism (15, 16), changes in different aspects of the HPA axis (e.g. ACTH release and corticosteroid receptor expression) are consistently found in relation to inferior cognitive performance. We hypothesized that an altered relationship between the regulators of HPA axis (re)activity might be a more appropriate indicator for cognitive decline than the circulating amounts of glucocorticoids themselves.

In a more general view, studies on strains and preselected groups of rodents indicate that there might be several distinct set-points for the various players within the HPA axis that might either contribute to the fitness of the animal in certain conditions or be maladaptive in particular circumstances (16, 17, 18). Consequently, readout parameters like corticosteroid receptor mRNA expression may have distinct meanings for the system, depending on the state of the animal. Such an effect was demonstrated recently for hippocampal plasticity in rats expressed by long-term potentiation (19) and increased choline acetyltransferase mRNA in the striatum (20), which correlated with learning performance in aged-superior (AS), but not in aged-inferior (AI) learners. The latter showed a positive correlation with striatal N-methyl-D-aspartate NR2 subunit mRNA (19). These findings imply that different subgroups may exist within the aged population and emphasize the importance of analyzing relationships between variables separately for differently performing subgroups.

In the present study, we examined the HPA axis of young and aged rats that had previously been classified as inferior and superior learners in the water maze. Our hypothesis was that cognitive performance and age-related cognitive decline are associated with changed HPA axis activity, defined by altered relationships between commonly measured components of the axis. To this aim we calculated correlations between expression data of MR, GR, AVP, and CRH in the brain and basal and stress-induced ACTH and corticosterone concentrations in blood plasma in young and aged, inferior and superior learners.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Animals
Male Wistar rats obtained from the animal breeding facilities of the Heinrich-Heine-University of Düsseldorf (TVA Düsseldorf, Germany) aged either 3 months (n = 20, 306.3 ± 2.2 g) or 24 months (n = 34, 581.3 ± 9.2 g) at the beginning of the experiment were maintained under standard laboratory conditions with food and water ad libitum under a reversed 12-h light, 12-h dark cycle (lights off between 0700 and 1900 h). Experiments were performed during the rats’ active period between 0900 and 1600 h; carried out in accordance with the German Law on the Protection of Animals, approved by the State Authority (Bezirksregierung Düsseldorf, Germany).

Experimental design
Within 3 months, rats were subjected to 1) an open field and a water maze training followed by a series of other behavioral tests (elevated plus maze, motor coordination, light-dark tasks, inhibitory avoidance, and tail flick test) followed 2 wk after the last behavioral task by the 2) collection of blood samples to assess basal resting and restraint-induced activity of the HPA axis, and, finally, 3 wk later, 3) decapitation to measure the expression of mRNA related to the glucocorticoid system with in situ hybridization. At the time of decapitation, rats were 6 and 27 months of age, respectively.

Here we focus on central and peripheral markers of the activity of the HPA axis of young and aged rats classified according to their performance in the water maze as rats with superior and inferior learning abilities (see below).

Morris water maze
The maze consisted of a black, circular tank filled with water (185 cm diameter, 40-cm-high side wall, 30 cm deep, 20–21 C (19). Rats were tested in the submerged platform version of the task for seven consecutive days, three trials per day, except for the first day, which consisted of four trials. If the rat did not reach the platform within 90 sec, it was set on it. The intertrial interval was 60 min. Per trial, time and distance to reach the platform, as well as the duration of thigmotaxis, were recorded and analyzed by the EthoVison system (Noldus Technology, Wageningen, The Netherlands).

For classification of performance, the mean time and distance to the platform over all trials was calculated per rat. Because time and distance to platform correlated highly on most trials (r > 0.9), only the time to the platform was used for classification. Aged animals with latencies larger than 4 SD from the mean performance of young animals were classified as AI. Aged animals with performance in the range of less than 2 SD from the young group were defined as AS. The AI and AS groups, respectively, comprised 27% of the aged sample group distribution tails. For classification of young rats in inferior and superior learners, 27% of the rats were selected with, respectively, the lowest and highest water maze latencies: young-inferior (YI) and young-superior (YS). In the present study, we used six rats per group (i.e. 27% of the number of young rats (5.4) completed to n = 6 and a random selection of six animals from the aged groups); mean ± SEM time/distance for YS was 17.4 ± 2.4/3.6 ± 0.5; YI, 31.9 ± 1.8/7.0 ± 0.4; AS, 33.6 ± 3.1/8.4 ± 1.1; and AI, 70.5 ± 2.8/18.9 ± 1.6. Mean and individual values for time to the platform are presented in Fig. 1Go. According to this classification scheme, water maze performance of YI and AS learners was comparable.



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  		FIG. 1. Water maze performance of rats classified as superior (YS, AS) and inferior (YI, AI) learners, expressed as mean time to platform over 22 trials per rat. Horizontal lines indicate the group mean.

 
Blood sampling and hormone measurement
Blood samples were collected by tail incision (21). Briefly, the rat was placed in a towel onto a table and gently held by hand. A small incision was made approximately 2 cm from the tip of the tail. Approximately 300 µl blood was collected in microcuvettes (EDTA coated; Sarstedt, Nümbrecht, Germany) within 90 sec after opening of the animal’s cage. Five blood samples were taken from each rat. Basal resting concentrations of corticosterone and ACTH were measured in blood samples taken directly before restraint stress. For restraint, the rat was fixed in a plastic tube for 10 min. Just before releasing the animal from the restrainer, a blood sample was taken (t = 10 min) and the rat was returned to its home cage. At 60, 120, and 180 min after the onset of restraint, additional samples were collected. Between periods of sampling, the rats were returned to their home cages. Blood samples were kept on ice and centrifuged (3000 rpm for 10 min at 4 C), and the plasma was directly pipetted into polystyrene tubes and stored at –20 C.

Experiments were performed between 0900 and 1300 h. Because the rats were kept in a reversed day/night cycle, basal resting concentrations of hormones (collected between 0900 and 1000 h) were expected to be elevated.

Corticosterone was measured with a [125I]corticosterone RIA for rats and mice (ICN Pharmaceuticals Inc., NY) with a detection limit of 8.5 ng/ml, and inter- and intraassay coefficients of variations were both 7%.

In situ hybridization
Rats were killed by overdose of CO2 and decapitated; the brain was removed from the skull and rinsed in ice-cold Ringer’s solution; and one hemisphere was immediately frozen in isopentane for in situ hybridization.

Tissue preparation and in situ hybridization procedures are described in detail elsewhere (22, 23). Briefly, 14-µm brain sections were cut on a cryostat (Reichert-Jung Frigocut 2800) and processed to measure the expression of MR and GR mRNA; steroid receptor coactivators (SRC1a, -1e, and -2) and heat-shock-protein 90 (hsp90) mRNA in the hippocampus and cortex; and GR, CRH, and AVP mRNA in the paraventricular nucleus (PVN) of the hypothalamus.

Sections were fixed with paraformaldehyde and prehybridized. For MR, GR, AVP, and CRH mRNA expression, riboprobes were used. For GR, we used a 500-bp fragment (exon 2, coding for the N terminus of the receptor; courtesy of Dr. M. Bohn) of the original full-length GR clone (courtesy of Dr. K. Yamamoto). The MR probe was generated from a 500-bp fragment coding for rat MR exon two in pGEM4 (courtesy of Dr. J. Arriza). AVP probe was generated from a 205-bp-long cDNA coding for exon C of the rat AVP gene in pGEM2 (courtesy of Dr. P. Burbach). The plasmid with an hsp90 insert was a kind gift of Dr. C. Wikstrom. For the CRH probe, we used a full-length rat cDNA in pGEM-T (courtesy of Dr. G. Dent). For coactivators, we used end-labeled oligonucleotide probes (23).

Linearized plasmids were transcribed with the appropriate RNA polymerase in the presence of 35S-labeled UTP to get antisense and (negative control) sense probes. Per slide, 100 µl of hybridization mix, containing 50% formamide, 10% dextran sulfate, 10 mM dithiothreitol, 1x Denhardt’s, 3x standard saline citrate (SSC), tRNA, and single-strand DNA, and 2 x 106 cpm of the labeled probe were used to hybridize overnight at 55 C. After hybridization, sections were washed in 2x SSC at room temperature and incubated with RNase A in 0.1 M Tris (pH 8.0) for 15 min at 37 C. Subsequently, different wash protocols were used for each probe, each with increasing stringency up to 0.1x SSC at 65 C. For oligonucleotide probes, we used a modified protocol, described elsewhere (23). After dehydration in an ethanol series, slides were put in a cassette and a Biomax-MR film (Kodak) was exposed for periods ranging from 17 h (AVP) to 2 wk (MR/GR/SRCs). Sections containing the PVN were dipped in photographic emulsion (Kodak) for high-resolution analysis.

Individual densities of mRNAs were calculated for each rat as the average from at least three tissue sections.

Analysis of the autoradiograms was done on an automated imaging system (AnalySIS, SIS, Germany). Films were digitized, and OD of the relevant areas was measured. These were corrected for film and tissue background. Parvocellular GR mRNA was determined from film using films from adjacent sections that were hybridized for CRH as a mask. Parvocellular AVP and CRH were measured from dipped sections using Scion Image (Scion Corp., Frederick, MD). Here also, the parvocellular division was defined by CRH-expressing neurons in the adjacent section. The total AVP signal, number of cells, and the expression per cell was measured under dark-field microscopy. From the combined AVP and CRH analysis, the percentage of CRH-positive cells that coexpress AVP was calculated per rat.

Statistics
Because we worked with extreme groups from two populations and did not assume normal distribution of our data, we used nonparametric tests for group comparisons: the Kruskal Wallis test followed by the Mann-Whitney U test. Significance was accepted at P < 0.05. The development of a systematic approach to uncover group-specific correlates, i.e. the sliding window correlation procedure, pointed to the possibility that, for a whole range of aged rats, there might exist several subgroups for which correlations can differ in direction (positive vs. negative) and strength or be absent altogether (24). Because we hypothesized that the relationship between selected HPA axis markers may differ as a function of age or learning capacity, we performed Spearman rank-order correlations separately for the aged and young rats as well as for the superior and inferior learners. If a statistically promising correlation was present for a group (i.e. young, aged, superior, or inferior), we also tested whether the correlation could be attributed to one of the corresponding subgroups (e.g. YI, YS, etc.). Although for the Spearman correlations scattergrams depicting the rank for each individual would be appropriate, for purposes of clarity we decided to show the raw data.

To minimize the problem of multiple tests that is inherent to the number of parameters we measured, we considered only specific relationships that follow from well-defined hypotheses on HPA axis variables. For example, we did not correlate central markers with stress-induced corticosterone, because we considered ACTH release as the best direct measure for HPA axis output. The specific hypotheses are indicated in Results. P values are interpreted as a measure of effect (25) and given in the text or tables and figures. Statistical analysis was performed using SPSS.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Group differences
ACTH and corticosterone.
Basal ACTH was different between groups (H = 14.2; P = 0.003; Fig. 2AGo) because of elevation in aged rats compared with young (P < 0.05). All groups responded with increased ACTH to restraint, again with significant differences between groups (H = 11.9; P = 0.008). AI learners showed an exaggerated response of ACTH at 10 min after onset of restraint compared with all other groups (P < 0.05). No significant changes related to performance were observed at other time points. Plasma corticosterone did not differ between the four groups at any time point. Basal levels (near the circadian peak) were approximately 10 µg/dl. Restraint led to a significant elevation of circulating plasma corticosterone at 10 and 60 min after restraint (Fig. 2BGo).



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  		FIG. 2. Plasma ACTH (A) and corticosterone (B) concentrations (mean + SEM) of rats before (basal) and at several time points after restraint (AS, YS, YI, and AI learners). *, P < 0.05 vs. young; $, P < 0.05 vs. all other groups.

 
PVN mRNA expression.
CRH mRNA expression in the PVN was significantly different between groups (H = 10.8; P = 0.012), and significantly lower in the AS learners only (~35%; Table 1Go; P < 0.05). Measures of other ACTH secretagogues did not differ significantly between the groups, such as AVP mRNA in the parvocellular neurons (Table 1Go) and the percentage of CRH-positive parvocellular neurons that expressed AVP (not shown). GR mRNA in the parvocellular division of the PVN was significantly different between the groups (H = 11.6; P = 0.009) because of lower expression in the AS group (~30%; Table 1Go; P < 0.05). To exclude the possibility that the observed changes were the consequence of the multiple behavioral tests that the animals were subjected to, we also determined GR and CRH mRNA in young and aged naive rats. Both transcripts were lower in aged compared with young rats, similarly to the animals that had been behaviorally characterized; OD for CRH in young was 93 ± 3 and in aged was 73 ± 8; P = 0.01; and for GR in young was 143 ± 3 and in aged was 72 ± 8; P = 0.03.


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  		TABLE 1. Expression of AVP, CRH, GR, and MR mRNAs in rats grouped according to performance and age (YS, AS, YI, and AI), age only (young and aged), and performance independent of age (superior and inferior)

 
Hippocampal and cortical MR and GR mRNA expression.
Modest differences were apparent when the rats were compared according to their performance. MR mRNA was significantly lower in dentate gyrus (DG), CA3, CA2, and cortex of inferior learners compared with superior learners (Table 1Go; P < 0.05). GR mRNA was decreased in the DG of aged compared with young rats (Table 1Go; P < 0.05). Differences in hippocampal mRNAs were in the 10% range.

Comparing the four groups revealed no significant differences for either receptor in the hippocampus. Surprising was the MR mRNA signal in the isocortex. Very little MR mRNA signal is present when compared with the hippocampus principal cell layers, but the signal was significantly different between the groups (H = 10.4; P = 0.016) because of lower expression in both age groups of inferior learners compared with the AS rats (Table 1Go; P < 0.05). The expression of SRC1e, -1a, and -2 and hsp90 was comparable between groups and, thus, not affected by age or performance (data not shown).

Correlations
The differences in mean values for HPA axis markers in the four groups of animals suggested a number of correlations. First, CRH and GR mRNA expression in the PVN showed parallel changes in AS learners. Second, only aged rats differed significantly in both ACTH response to stress and parvocellular CRH mRNA expression. Thus, we hypothesized that ACTH secretagogue expression might be an indicator for HPA axis activity, selectively in aged animals. We extended this hypothesis and tested correlations between HPA axis markers that might occur specifically in animals of the same age or performance group, even in the absence of group differences in average levels of those markers.

We analyzed the data for all animals as well as per group, i.e. as a function of aging and learning performance. In these correlations we considered ACTH rather than corticosterone as the determining variable for the output of the PVN. Basal corticosterone concentrations were considered as input (i.e. feedback or feedforward signal) to the brain, presenting possible determinants for mRNA regulation.

AVP/CRH mRNA vs. ACTH.
We tested the hypothesis that mRNA of the two ACTH secretagogues, CRH and AVP in the parvocellular PVN (2), were correlated to basal and stress-induced ACTH concentrations. As independent variables we used CRH OD, CRH mRNA as measured by grains per cell, AVP mRNA as grains per cell, and the percentage of AVP-positive plus CRH mRNA-expressing cells. As dependent variables we included basal ACTH and ACTH at 10 min of restraint stress.

When all animals were considered, no prominent correlations were found for basal ACTH as a function of the AVP and CRH mRNA measures. However, when the animals were split by age, a positive correlation for CRH mRNA and basal ACTH was much more prominent in aged than in young rats (Fig. 3Go). The correlations for CRH cells were similar for two different measures, i.e. for the percentage of CRH-positive cells that coexpressed AVP mRNA (aged, r = 0.56 and P = 0.07; young, r = 0.02 and P = 0.95; Fig. 3AGo), and for CRH mRNA levels (aged, r = 0.53 and P = 0.1; young, r = –0.14 and P = 0.64). The AS learners showed a very prominent correlation between CRH mRNA and basal ACTH levels (r = 1 and P = 0.017; Fig. 3BGo). The relationship between CRH mRNA expression and basal ACTH for the AI learners seemed to be similar, but shifted to the right (r = 0.66 and P = 0.15; Fig. 3BGo).



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  		FIG. 3. Parvocellular expression of the ACTH secretagogues CRH and AVP mRNA and basal ACTH. Relationship between the percentage of coexpression of CRH and AVP mRNA (percent coexpressing parvocellular neurons) and ACTH (A) and CRH mRNA and ACTH (B). Note that the effect was particularly present in AS learners. P and r values shown in the boxes are from Spearman tests.

 
ACTH levels at 10 min of restraint stress in superior learners tended to correlate negatively with CRH mRNA expression (r = –0.57; P = 0.07), in contrast to inferior learners (r = 0.13; P = 0.67).

GR mRNA in PVN.
GR mRNA expression in the parvocellular PVN may be expected to reflect negative feedback actions of glucocorticoids via GR protein. We used GR mRNA expression in the PVN as the determining independent variable to test correlations with CRH and AVP mRNA (26) and basal and stress-induced ACTH (27).

GR mRNA was negatively correlated with basal ACTH (r = –0.48; P = 0.04). Further analysis revealed that this relationship held specifically for superior learners (r = –0.69; P = 0.027) but not inferior learners (r = –0.12; P = 0.77; Fig. 4AGo). No correlation was found when the animals were analyzed per age category.



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  		FIG. 4. Parvocellular GR mRNA, CRH mRNA, and ACTH. Relationship between GR mRNA in the parvocellular PVN is independent of age and negatively correlated with basal ACTH (A) and positively with CRH mRNA (B), specifically in superior learners (open symbols, dashed line). P and r values shown in the boxes are from Spearman tests.

 
CRH mRNA expression was positively correlated with GR mRNA in the PVN, as expected from the parallel differences in mean values between the groups for CRH mRNA OD (r = 0.52; P = 0.03). The correlation between GR and CRH mRNA in PVN was prominent for superior learners (r = 0.67; P = 0.047 for CRH mRNA OD) but not inferior learners (r = –0.13, P = 0.73; Fig. 4BGo). No correlations were observed between GR mRNA and AVP mRNA expression (not shown).

Hippocampal MR mRNA.
Activation of hippocampal MR and GR protein can lead to modulation of the HPA axis activity (28, 29, 30). We therefore correlated MR and GR mRNA expression with basal and stress-induced ACTH and with CRH and AVP mRNA expression in PVN. MR mRNA in the DG was negatively correlated with ACTH at 10 min of restraint stress (r = –0.56; P = 0.004; Fig. 5AGo). This correlation could not be attributed to a particular subgroup of rats, because r and P values were similar for groups split by age or performance.



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  		FIG. 5. Correlates of MR mRNA with parameters in PVN and blood plasma. A, MR mRNA in the DG of the hippocampus is negatively correlated with ACTH at 10 min of restraint stress in all groups. B, MR mRNA in DG of the hippocampus and CRH mRNA expression in the PVN of the hypothalamus were positively correlated in superior learners only. (S; open symbols, dashed line). P and r values shown in the boxes are from Spearman tests.

 
Correlation of MR mRNA in the DG to CRH mRNA in the PVN was apparent for superior learners but not for inferior learners. This difference was clear for CRH mRNA expressed as OD (superior, r = 0.69 and P = 0.05; inferior, r = –0.21 and P = 0.48) and expressed as grains per cell (superior, r = 0.63 and P = 0.05; inferior, r = –0.01 and P = 0.98; Fig. 5BGo).

Hippocampal GR mRNA.
GR mRNA in CA1 and DG were negatively correlated with ACTH at 10 min of restraint in superior learners but not inferior learners (for CA1: superior, r = –0.76 and P = 0.015; inferior, r = –0.08 and P = 0.80; Fig. 6AGo; for DG: superior, r = –0.65 and P = 0.04; inferior, r = 0.06 and P = 0.95). GR mRNA in DG showed positive correlation with parvocellular CRH mRNA OD (for all animals, r = 0.59 and P < 0.01; Fig. 6BGo). This correlation could not be attributed to a particular subgroup of rats, as r and P values were similar for groups split by age or performance.



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  		FIG. 6. GR mRNA in the hippocampus, ACTH and CRH mRNA in the PVN of the hypothalamus. A, In superior rats, GR mRNA in the CA1 area was negatively correlated with ACTH at 10 min of restraint stress. B, GR mRNA in the DG was positively correlated with CRH mRNA. P and r values shown in the boxes are from Spearman tests.

 
Corticosterone vs. CRH/AVP/GR/MR mRNA.
Basal resting concentrations of corticosterone were considered as input into the brain, i.e. as potential regulators of gene expression. mRNA expression of CRH and AVP in the PVN (26, 31), as well as that of MR and GR (32), are potentially corticosteroid regulated. No significant correlations were found between basal corticosterone and CRH, MR, or GR mRNA. Parvocellular AVP mRNA expression showed a prominent negative correlation with basal corticosterone in young but not aged rats (young, r = –0.75 and P = 0.026; aged, r = +0.3 and P = 0.78). The correlation was strongest (P = value) if AI learners were excluded from the analysis (r = –0.72; P = 0.006; Fig. 7Go). AVP mRNA expression was not correlated to any other parameter.



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  		FIG. 7. Expression of AVP mRNA (grains per cell) in the parvocellular PVN of the hypothalamus and basal corticosterone in blood plasma. For the negative correlation of AVP mRNA with basal corticosterone, AI learners were excluded. AI rats showed a positive correlation of AVP mRNA and basal corticosterone, suggesting impaired glucocorticoids sensitivity in these rats. Note that basal corticosterone was measured during the active period of the rats. P and r values shown in the boxes are from Spearman tests.

 
Correlates between HPA axis parameters depend on age and learning performance.
Overall, we detected a number of correlations, which mostly were much stronger in one subgroup of animals than in the other. Correlations between measures of CRH mRNA and ACTH were quite weak and restricted to aged animals. The negative correlation between parvocellular AVP mRNA and basal corticosterone was much more prominent in young than in aged rats and particularly disturbed in AI rats. Correlations between corticosteroid receptor mRNAs and other HPA axis parameters held true for all animals (MR mRNA and basal ACTH, GR mRNA in DG, and CRH mRNA expression in PVN) or were apparent in superior learners only (GR mRNA in DG vs. ACTH response, MR mRNA in DG vs. CRH mRNA, and parvocellular GR mRNA vs. ACTH and CRH mRNA).


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
We have characterized several elements of the HPA axis of young and aged rats that had been classified as inferior and superior learners. Age-associated changes consisted of elevated basal ACTH levels in the aged rats and a restraint stress-induced ACTH increase specifically in AI learners. No signs of hypercorticism were noted in the aged rats. Aging was accompanied by a modest decrease in GR mRNA expression in the DG of the hippocampus. At the level of the parvocellular PVN, CRH and GR mRNA were decreased predominantly in AS learners. Thus, our data support studies linking an overactive HPA axis, cognition, and aging in some aspects but not in others.

The most prominent age effect was the elevated basal and increased stress-induced ACTH in the aged group. This indication for a disinhibited HPA axis is supported by the emerging positive correlations between basal ACTH and two different measures of the activity of CRH-expressing cells in the PVN in aged rats (Fig. 3Go). At the same time, the exaggerated ACTH response to stress of AI rats was associated with the possible lack of negative control of corticosterone on parvocellular AVP mRNA expression (Fig. 7Go). The adrenal gland apparently compensated for the increased ACTH output of the pituitary. We saw no evidence for increased exposure to corticosterone in either age group; basal peak and stress-induced steroid levels were similar in all groups, and corticosterone concentrations were not correlated to cognitive performance. Because we did not measure basal trough or complete circadian corticosterone levels we cannot exclude subtle differences between (aged) superior and inferior learners. Other links between cognitive performance and corticosteroid signaling may exist, such as strain-dependent differences in HPA axis regulation (16, 33), lifetime exposure to corticosterone, or (chronic) differences in corticosteroid sensitivity (5, 13, 27, 34), which might influence learning capacity. However, our data do not suggest a general direct involvement of hypercorticism in age-associated cognitive deficits

Strikingly, the clearest changes in brain mRNA levels occurred in the AS learners compared with the AI learners. The challenging implication of this finding is that changes in HPA axis regulation described in elderly subjects (as present in the PVN of our groups of testing-naive rats) can represent adaptive processes that counteract cognitive decline, rather than be markers for pathological processes. Plasticity in HPA axis regulation might be crucial for cognitively successful aging.

Correlation analysis
We determined correlations between a selected but still substantial number of parameters related to the HPA axis. We emphasize that with such multiple correlations, the occurrence of type I error increases. Small group sizes hardly bear Bonferroni correction, e.g. the perfect correlation observed for CRH mRNA and basal ACTH levels in AS learners only leads to P = 0.017. Therefore we urge caution in interpretation of the results. The P values were not interpreted in terms of significance but simply as measures of effect (25). Although not suited for rejecting null hypotheses, the resulting measures can serve as indices and a basis for generation of hypotheses and confirmatory experimentation. In addition, small group sizes also have a high risk of type II errors. Also in this respect, P values are interpreted as a measure of effect.

The correlations between HPA axis markers revealed that the relationships of these markers may be group specific. An important implication is that the proper interpretation of mRNA measurement is dependent on the particular animal. There were several hypotheses concerning the regulation of the HPA axis underlying our analyses. Before discussing the correlative evidence of HPA axis regulation in more detail, it seems appropriate to address some additional general precautions.

Correlation analyses such as we have used here are generally driven by presumed causal relationships. Although significant correlations might reflect such relationships, common factors that influence the correlated variables have to be considered. For example, the animals of the present data set had been subjected to rigorous behavioral testing between determination of their learning performance in the water maze task, the restraint stress test, and killing. However, the similar differences in CRH and GR mRNA in the PVN that were observed in testing-naive rats argues for an age-dependent effect per se.

The group-specific differences in correlations appear to be representative for the impact of aging, as well as for learning performance. It is important to realize that for our correlation analysis we have grouped inferior or superior learners from both ages. The absolute learning performance of (subdivisions of) young and old animals differs considerably, with a much larger variation in the old animals (Fig. 1Go). Our analysis of correlations that are specific for inferior or superior learners rests on the explicit assumption that there are common factors in both age groups that relate to learning capacity. We tentatively interpret the fact that a number of correlations between HPA axis parameters are found specifically for superior learners as supportive for this notion. Thus, we speculate that these characteristics may be a stable trait and that YI learners may be predestined to become AI learners. However, this would be proven only by a large longitudinal study in which the learning performances are checked at different ages.

With respect to the influence of the HPA axis on learning, it merits attention that although the water maze performance of YI and AS learners is comparable, the regulation of their HPA axis is very different. This again emphasizes that many different circuits and transmitter systems are involved in water maze performance, which may differ dramatically between any of our groups, and that these differences give rise to the contexts in which HPA axis activity may have a modulating role. It may be the lack of functionality in homeostatic control of the HPA axis (1) that is related to impaired cognitive performance, as indicated by the lack of correlates between corticosteroid receptor measures and HPA axis output in the inferior learners.

ACTH and corticosterone
It is generally accepted that ACTH and corticosterone levels are correlated, particularly after a stressor, because the first is the secretagogue for the second. The fact that such a relationship was not found emphasizes individual differences in adrenal sensitivity (16, 18, 35).

Expression of hypothalamic PVN mRNAs
The mRNA level of the ACTH secretagogues AVP and CRH might be related to ACTH output of the pituitary. The lack of strong correlations may not be surprising, given the many processes between mRNA synthesis/turnover and the response of the corticotrophs to stimulation. Translation, processing of the peptide products, transport to the median eminence, stimulation of secretion, and the actual stimulus-secretion coupling, as well as a similar chain of events in the corticotrophs, all provide potential (or proven) points of regulation. In this light, it is striking that we observed in aged animals a trend for a positive correlation between measures of parvocellular gene expression and basal ACTH, which was highly prominent for AS learners and completely absent in young rats. This relationship was found for two measures of parvocellular activity, CRH mRNA and the percentage of AVP-coexpressing CRH-positive cells. Although these two measures are not completely independent, the identical relationships found with basal ACTH levels in the two groups of aged animals is important given the relatively small number of animals in the individual AI and AS groups. We speculate that in the aged animals, a number of checks in the pathway from CRH expression to ACTH release are no longer functioning. The right shift observed in AI rats compared with AS rats apparently points to a lower efficiency of parts of the regulatory system, such as translational processes or pituitary CRH receptor-1 sensitivity.

Parvocellular GR mRNA expression might be indicative for GR protein levels and function, which can regulate AVP and CRH expression in PVN on the one hand and peptide secretion on the other hand (26, 31, 36, 37, 38). The negative correlation between GR mRNA in the PVN and basal ACTH was exclusive for superior learners. This is consistent with a tonic negative feedback on the secretion from the PVN neurons, which would be related to PVN GR mRNA expression in these animals.

CRH and AVP mRNA in PVN might be directly down-regulated via activation of GR. The promoters of the CRH gene [at least in humans, with relevant sequences conserved in rodents (37)] and the AVP gene (39) can be a direct target for negative regulation via GR. Supporting this hypothesis are the findings that newborn GR knockout mice show strongly increased CRH mRNA (36), and increased stress induction of CRH and AVP have been shown in relation to decreased GR mRNA in PVN (40). However, most recent evidence suggests that corticosterone effects on parvocellular CRH expression may take place outside of the PVN (41). The positive correlation between CRH mRNA and GR mRNA that was particularly observed in superior learners is suggestive of a common transcriptional regulation of the genes.

An alternative hypothesis would be that transrepression of this gene (CRH) occurs only at stress levels of corticosterone [or exposure to dexamethasone (31)]. Thus, the positive correlation found in our study reflects the positive transcriptional regulation that may also occur at this gene (42). In any case, GR mRNA levels appear to be no indicator for negative feedback on secretagogue gene expression under basal conditions.

We did observe a strong correlation between basal corticosterone concentrations in the blood and parvocellular AVP mRNA expression in three groups of animals. This supports the notion that particularly AVP mRNA is very sensitive to corticosterone negative feedback (26, 38). It is the concentration of circulating corticosterone rather than the amount of receptors or coactivators that constitutes the rate-limiting factor in this transrepression process. The clear difference between AI rats and the other groups does suggest that there is a degree of glucocorticoid feedback disturbance in the AI rats.

The dissociations of the correlates between GR mRNA and ACTH, GR mRNA and CRH/AVP mRNA expression, as well as basal corticosterone and AVP mRNA emphasize that glucocorticoids do not just feed back negatively at the PVN as a whole but that synthesis of ACTH secretagogues and stimulation of ACTH release itself are different domains with distinct sensitivity to glucocorticoids. A similar multilevel mechanism of control by glucocorticoids seems to take place in pituitary corticotrophs (43).

Hippocampal MR/GR mRNAs
We have used MR and GR mRNA as potential measures for HPA axis control by the respective proteins. Evidence from other rat strains suggests that in particular hippocampal GR mRNA may not be a particularly good indicator of receptor function, because age-associated changes affected translocation and DNA binding of the GR (44). Although we have measured hsp90 mRNA expression, and did not see any differences between groups, it is possible that existing correlations with hippocampal GR function (rather than mRNA) were missed.

The MR is extensively occupied by corticosterone even at basal conditions (45, 46). If mRNA levels are indicative of protein levels, then correlations of MR mRNA with functional parameters may be expected to be stronger than for GR, where ligand concentration plays an important additional role. Indeed, we found that hippocampal MR mRNA was correlated negatively with stress-induced ACTH in all groups. Although early reports on the role of MR in the HPA axis showed that blockade of MR protein disinhibits the HPA axis under basal conditions rather than stress-induced activation (28), more recent studies have pointed to a role of MR in suppression of stress-induced ACTH in animals previously exposed to stressors (29, 47). Such a role for the MR is supported by the present inverse relationship of MR mRNA and ACTH response observed in animals that had been exposed to a host of previous stressors during the behavioral testing.

Also, GR mRNAs show negative correlations with the ACTH response after stress, albeit solely in superior learners. On the one hand, this is consistent with the widely held view that both MR and GR are involved in steroid feedback; on the other hand, it is at odds with the MR/GR balance hypothesis. The latter is based on opposite MR- and GR-mediated effects on hippocampal neuronal excitability (4) as well as on studies that have shown that the GR antagonists RU38486 infused into the hippocampus inhibited whereas the MR antagonist RU28318 facilitated stress-induced HPA axis activation (30). An alternative interpretation of the negative correlation of GR mRNA and ACTH is that there is a parallel regulation of hippocampal GR and HPA axis responsiveness to novelty specifically for superior learners. Serotonin might be a potential regulator because serotonergic activity not only stimulates hippocampal GR expression (48, 49) but also has been shown to normalize the increased ACTH response to novelty in a group of aged (male) rats relative to young animals (50).

Hippocampal MR mRNA was positively correlated with CRH mRNA expression in the PVN in superior learners. Although there is a well established control of the hippocampus over PVN activity (51), the observed correlation may in fact be indicative of a reversed influence, because CRH can rapidly up-regulate MR expression (52).

Group-specific correlations
Earlier, measures of hippocampal and striatal synaptic plasticity (long-term potentiation) and learning performance in a water maze (19) were found to be correlated specifically in AS learners vs. AI learners. Some of the correlations with MR and GR mRNAs were established in grouped superior learners of both ages. From the lack of correlation between corticosteroid receptors and other HPA axis parameters in inferior learners it could be concluded that in superior learners corticosteroid receptor mRNAs are causally linked to the downstream effects we measured; in inferior learners the chain of events may be interrupted, for example as a consequence of impaired steroid receptor signaling. Such a form of impaired steroid signaling could be indicative of a concomitant lack of the appropriate corticosteroid regulation of hippocampal activity that is needed for optimal cognitive performance (13). Of the many candidates for an altered corticosteroid signaling, the expression of hsp90, SRC-1a, SRC-1e, and SRC-2 mRNA revealed no group differences. Therefore, the factor underlying the lack or presence of correlates between MR and GR mRNA and the other HPA axis markers is as yet unknown.

Taken together, our data suggest that the relationship between corticosteroid receptor mRNA expression and other HPA axis markers depends on the subpopulation of subjects within a given strain of rats. Here we emphasize that age and learning capacity form conditions that are associated with specific differences in the relationships between expression of receptors and ACTH secretagogues and the actual levels of ACTH and corticosteroid hormones. With respect to learning capacity, we speculate that this may be a setting that is established early in life, whereas the age-dependent differences can be interpreted as a resetting. These differential adaptations of the HPA axis might prove to be more or less successful, depending on the context. We finally expect that the study of these relationships in selected groups of animals will lead to increased understanding of interactive properties of regulators and rate-limiting factors of the HPA axis as a homeostatic control system.


   Acknowledgments
 
We thank Marc Fluttert for his technical assistance.


   Footnotes
 
This work was supported by Netherlands Organization of Scientific Research (NWO)-Aspasia 015.01.076 (to M.S.O.) and North American Alliance for Research on Schizophrenia and Depression and NWO-Vidi 016.036.381 (to O.C.M.).

First Published Online November 24, 2004

Abbreviations: AI, Aged-inferior; AS, aged-superior; AVP, arginine vasopressin; DG, dentate gyrus; GR, glucocorticoid receptor; HPA, hypothalamus-pituitary-adrenal; hsp90, heat-shock-protein 90; MR, mineralocorticoid receptor; PVN, paraventricular nucleus; SRC, steroid receptor coactivator; SSC, standard saline citrate; YI, young-inferior; YS, young-superior.

Received March 31, 2004.

Accepted for publication November 16, 2004.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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