Mapping of genetic determinants of the sympathoneural response to stress

I. Klimes1, K. Weston4, D. Gasperíková1, P. Kovács5, R. Kvetnansky2, D. Jezová3, R. Dixon4, J. R. Thompson6, E. Seböková1 and N. J. Samani4

1 Diabetes and Nutrition Research Laboratory, Slovak Academy of Sciences, Bratislava, Slovakia
2 Stress Research Laboratory, Slovak Academy of Sciences, Bratislava, Slovakia
3 Laboratory of Pharmacological Neuroendocrinology of the Institute of Experimental Endocrinology, Slovak Academy of Sciences, Bratislava, Slovakia
4 Cardiology Group, Department of Cardiovascular Sciences, University of Leicester, United Kingdom
5 Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona
6 Department of Health Sciences, University of Leicester, United Kingdom


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Activation of the sympathoadrenal system (SAS, comprising the sympathetic nervous system and the adrenal medulla) in response to stressful stimuli is an important defense mechanism as well as a contributor to several cardiovascular diseases. There is variability in the SAS response to stress, although the extent to which this is genetically regulated is unclear. Some rodent models, including the hereditary hypertriglyceridemic (hHTg) rat, are hyperresponsive to stress. We investigated whether quantitative trait loci (QTLs) that affect sympathoadrenal response to stress could be identified. Second filial generation rats (n = 189) derived from a cross of the hHTg rat and the Brown Norway rat had plasma norepinephrine (NE) and epinephrine (Epi) levels, indices of activation of the sympathoneural and adrenal medulla components, respectively, measured in the resting state and in response to an immobilization stress. Responses were assessed early (20 min) and late (120 min) after the application of the stress. A genome scan was conducted using 153 microsatellite markers. Two QTLs (maximum peak LOD scores of 4.17 and 3.52, respectively) influencing both the early and late plasma NE response to stress were found on chromosome 10. Together, the QTLs accounted for ~20% of the total variation in both the early and late NE responses in the F2 rats. Interestingly, the QTLs had no effect on plasma Epi response to stress. These findings provide evidence for a genetic determination of the response of a specific component of the SAS response to stress. Genetically determined variation in sympathetic nervous system response to stress may contribute to cardiovascular diseases.

catecholamine; stress; genetics; quantitative trait loci


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
ACTIVATION OF THE SYMPATHOADRENAL system (SAS, comprising the sympathetic nervous system and the adrenal medulla) in response to stressful stimuli is a fundamental component of the body’s defense mechanism. However, an exaggerated response may predispose to cardiovascular diseases both by acting as an enhancing factor in the development of hypertension, atherosclerosis, and cardiac dysfunction and as a trigger of acute events, such as myocardial infarction (3). Activation of the SAS in response to stressful stimuli is marked by increases in plasma catecholamine levels, i.e., epinephrine (Epi) levels reflecting activation of the adrenal medulla and norepinephrine (NE) activation of the sympathetic nervous system. Although interindividual variability in SAS responses to stress is recognized, the determinants of the variability and in particular the role of genetic factors are poorly understood (19). Some animal models with genetic predisposition to hypertension show enhanced SAS responses to stress. Such models provide an opportunity to explore whether hyperresponsiveness of the SAS to stress has identifiable genetic determinants. The hereditary hypertriglyceridemic (hHTg) rat is such a model showing exaggerated rises in plasma levels of both NE and Epi levels on immobilization (7). Its other main characteristics are hypertriglyceridemia, hypertension, and hyperinsulinemia, reflecting several traits of the insulin resistance metabolic syndrome (8). Therefore, the aim of this study was to map major quantitative trait loci (QTLs) affecting plasma catecholamine levels in response to immobilization stress. Cosegregation analysis of plasma Epi and NE levels with genetic markers was performed on a cohort of second filial generation (F2) hybrids bred from a cross of the hHTg and Brown Norway (BN) rats.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Rat strains.
The derivation of the hHTg strain is described elsewhere (8). BN rats were purchased from Charles River Laboratories (Lyon, France). Male and female hHTg rats were reciprocally crossed with the BN rats to produce (hHTg x BN) and (BN x hHTg) F1 hybrids, which were further intercrossed to generate F2 hybrid populations. Only male F2 rats were studied. No phenotypic differences were found between the two reciprocal F2 crosses for the traits studied, and pooled results are presented. Altogether, 189 F2 hybrids were analyzed.

Phenotyping.
This was carried out at 4 mo of age. Each rat was inserted with an indwelling catheter into the carotid artery for blood pressure measurement and blood sampling. Briefly, under anesthesia (ketamine hydrochloride, 70 mg/kg; and xylazine hydrochloride, 10 mg/kg), a sterile Silastic cannula 0.51 mm internal diameter (Dow Corning, Midland, MI) filled with heparin 10 IU/ml in 0.9% NaCl was placed into the right carotid artery, exteriorized through an incision in the neck, closed with a pin, and fixed to skin by a suture. Animals were allowed to recover from surgery for 2 days. On the third day after cannula implantation, 30 min of beat-to-beat direct measurement of systolic and diastolic blood pressures was carried out as described previously (9). The rats then underwent a standard immobilization stress for 2 h (10). This was achieved by taping all four limbs to metal mounts attached to an immobilization board. Blood for plasma catecholamine determinations was sampled in the resting state prior to immobilization and after 20 min and 120 min of immobilization. At each time point, 0.6 ml of blood was taken and replaced by the same volume of heparinized saline (50 IU heparin/ml of saline). In addition to the F2 rats, 10 hHTg and 10 BN rats were also studied with identical protocols. All procedures followed the principles of laboratory animal care (NIH publication No. 86-23, revised 1985) and the guidelines for the care and use of laboratory animals of the Institute of Experimental Endocrinology. The study protocol was approved by the Animal Ethics Committee of the Institute.

Plasma Epi and NE.
Plasma catecholamines were analyzed by the radioenzymatic method of Peuler and Johnson (17). Briefly, catecholamines present in 50 µl of plasma were converted into their labeled O-methylated derivatives by using S-[3H]adenosylmethionine (Amersham, UK) and lyophilized enzyme catechol-O-methyltransferase isolated from rat liver. The formed O-methylated derivatives of the catecholamines were extracted along with unlabeled carrier compounds, separated by thin-layer chromatography, eluted, and oxidized by sodium periodate, and the radioactivity of the products was measured. The detection limit of the method is 5 pg of Epi or NE per tube, and the intra-assay variations are 7.5% for Epi and 2.3% for NE.

Genetic analysis.
The selection of markers used for the study, their chromosomal distribution, and the genotyping protocols have been described in detail previously (9). Briefly, 464 rat microsatellite markers chosen from the available rat linkage maps (Wellcome Trust Centre for Human Genetics, http://www.well.ox.ac.uk; and the Whitehead Institute for Biomedical Research/MIT Rat Genome Map, http://www.broad.mit.edu/rat/public/) were analyzed for polymorphism between hHTg and BN rats. We found that 282 markers were polymorphic. There was a low incidence (7 markers, 1.5%) of residual heterozygosity in the hHTg rat. F2 rats were genotyped for 153 (54.3%) of the polymorphic markers to provide reasonable coverage for the majority of the chromosomes (9). Specific chromosomes, including chromosome 10, were enriched with additional markers (9).

Data analysis.
Normality of the quantitative traits was tested using the Anderson-Darling function on MINITAB (version 13) (Minitab, State College, PA). Because of "skewness" of the data, analysis was performed on log-transformed data. Genetic linkage maps were constructed for the markers and the location of QTLs determined using the MAPMAKER programs kindly provided by Dr. E. Lander (Whitehead Institute, Cambridge, MA) (12, 13). Cosegregation of phenotypes with alleles at marker loci was evaluated by comparing the geometric means derived from log-transformed data between different genotypes using the nonparametric Kruskal-Wallis test. To assess the significance of the linkage findings, genome-wide P values were obtained by randomly permutating the log(NE-20) measurements, reanalyzing using MAPMAKER and counting the number of maximum LOD scores that exceeded the threshold of interest. We ran 2,000 independent scans for this simulation.

Bioinformatics.
Genetic marker localization to the rat genome sequence was achieved by searching the UCSC Bioinformatics Genome Browser gateway (http://genome.ucsc.edu/) (June 2003 freeze), with the marker name. In cases where a marker alias was not found within the genome browsers, the marker database UniSTS (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=unists) was consulted to retrieve a sequence for the marker. This sequence was then used to place the marker on the rat genome sequence, by using the BLAT sequence search tool (http://genome.ucsc.edu/) (6). Identification of genes in marker-defined regions was implemented in the UCSC genome browser and the Rat Ensembl Genome Browser (http://www.ensembl.org/Rattus_norvegicus/) (version 16.2.1). The conservation of large-scale gene order between rat, human, and mouse was investigated within the Ensembl tool, SyntenyView. QTLs matching to genomic regions of interest were retrieved from the Rat Genome Database (http://rgd.mcw.edu/qtls/).


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
hHTg rats had significantly higher basal plasma Epi and NE levels as well as conscious resting systolic and diastolic blood pressures compared with BN rats (Table 1). Both strains showed significant elevations in plasma Epi and NE levels in the early (20 min) as well as late phase (120 min) of immobilization. In absolute terms, the increase for both was greater in hHTg compared with BN rats, although the proportionate increase compared with baseline was similar for NE in the two strains and for Epi slightly greater in BN rats (Table 1).


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Table 1. Phenotypes in the parental and F2 rats

 
The distributions of plasma Epi and NE levels after 20 min and 120 min of immobilization stress in the F2 rats are shown in Table 1. There were significant correlations between basal and stress-related levels for both Epi and NE (Table 2). The correlations were stronger for NE. There were also significant correlations between both basal and stress-related levels of Epi and NE (Table 2).


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Table 2. Correlations between levels of epinephrine and norepinephrine at baseline and after 20 min and 120 min of immobilizations stress in F2 rats

 
Genetic analysis revealed two QTLs on rat chromosome 10 influencing the plasma NE response to immobilization in the F2 rats (Fig. 1). The first QTL (QTL 1) with a peak located between markers D10Wox11 and D10Mgh6 gave LOD scores of 4.17 and 3.12 for the early and late NE responses and accounted for 10.2% and 7.7%, respectively, of the early and late variation in plasma NE levels in the F2 rats. The 95% confidence interval (1 LOD score) for the QTL spanned 14.6 cM. The second QTL (QTL 2) with a peak located between markers D10Mgh23 and D10Wox20 gave LOD scores of 3.40 and 3.52 for the early and late NE responses and accounted for 9.1% and 9.6%, respectively, of the early and late variation in plasma NE levels. The 95% confidence interval for this QTL spanned 10.3 cM. The QTLs had no effect on basal NE (or Epi) level. Interestingly, despite a similar magnitude increase in Epi level after immobilization (Table 1), neither QTL had an effect on stress-related Epi level (Fig. 1). Likewise, there was no effect of the QTLs on resting blood pressure (Fig. 1).



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Fig. 1. An LOD score plot of linkage of markers on rat chromosome 10 to plasma levels of norepinephrine (NE) and epinephrine (Epi) at baseline (NE-0, Epi-0) and after 20 min (NE-20, Epi-20) and 120 min (NE-120, Epi-120) of immobilization stress. The LOD score for mean arterial pressure (MAP) is also shown. Note the two significant LOD score peaks for stress-related plasma NE levels.

 
The quantitative effects on plasma NE level at rest and after 20 and 120 min of immobilization for alleles of the most proximate markers of each QTL peak (D10Wox11 and D10Wox20) are shown in Table 3. At both loci, the hHTg allele was associated with a more exaggerated response. For the locus associated with D10Wox11 the hHTg allele appeared to be acting in a dominant manner, with levels in the heterozygous animals similar to those in animals homozygous for the hHTg allele. For the locus associated with the D10Wox20 marker, the pattern was that of a codominant effect of the two alleles (Table 3).


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Table 3. Plasma norepinephrine levels at rest and after 20 and 120 min of immobilization stress according to genotype at the most proximate markers for the two QTLs on rat chromosome 10

 
None of the markers located on other chromosomes showed a significant relationship with either resting or stress-related plasma Epi or NE levels.


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Immobilization stress is a complex multi-modal stress paradigm, which results in activation of several systems including the SAS and the hypothalamo-pituitary-adrenocortical axis (16). In this experimental study, we have used it to investigate the SAS response to stress and provide evidence that variation in the extent of the SAS response may partly reflect the direct influence of specific genetic factors. Activation of the SAS in response to stress is an important defense mechanism but also likely contributes to the pathophysiology of several cardiovascular diseases (3, 19). Our findings point to the possibility that susceptibility to the adverse cardiovascular effects of stress may be partly genetically determined due to an exaggerated activation of the SAS.

On the basis of certain assumptions, specific statistical criteria have been proposed for reporting the results of QTL mapping in experimental crosses, with a LOD score >4.3 indicating significant linkage and a LOD score >2.8 indicating suggestive linkage in an intercross with two degrees of freedom (14). On this basis, both our QTLs easily meet the criterion for suggestive linkage, with the QTL located between D10Wox11 and D10Mgh6 (QTL 1) almost satisfying that for significant linkage. Indeed, simulations using our own data (see MATERIALS AND METHODS) showed that a LOD score of 4.17, seen with the early NE response at QTL 1, gave a genome-wide significance of 0.022. In combination, the two QTLs explained approximately one-fifth of the total variation in both the early and late NE responses in the F2 rats to the immobilization stress.

Apart from the demonstration of the two QTLs, perhaps the most interesting finding of our study is the specificity of their effect for the NE response to immobilization stress. Despite a similar variability in the Epi response to the stress in the F2 rats to that seen with NE and a significant correlation between the NE and Epi responses to stress, neither QTL affected either the early or late Epi response. Dissociation of the responses of the two components of SAS, i.e., the sympathetic nervous system (NE) and adrenal medulla (Epi), has been observed in relation to some stressors (11, 16, 20). However, with immobilization stress both NE and Epi increase substantially (10), and therefore a differential response of the two per se to this stress is not the explanation for the specificity of the QTL effect. For similar reasons, it seems unlikely that the QTLs are related to higher basal SAS activity in the hHTg rat, as both NE and Epi are raised. Furthermore, in the F2 rats no effect of the QTL was observed on basal NE level. The effect therefore seems to be specific for the stress-related rise in NE and, hence, the sympathoneural response. Whether the same QTLs affect the sympathoneural response to other forms of stress remains to be determined.

Interestingly, QTL 1 maps almost precisely to the same region that has previously been found to influence the body temperature response to immobilization stress in rats (2). Although the colocation could be incidental because of the large genomic region involved, it is possible that these two stress-related phenotypes represent the effects of the same QTL. QTL 2 maps to a region of chromosome 10 where a QTL for the tachycardia response to the air-puff startle stimulus has been mapped (4). The air-puff startle-induced response is known to be mediated via the sympathetic nervous system (1). Therefore, it is possible that the same QTL is responsible for both the stress-related rise in NE and the heart response and indeed that the latter is secondary to the NE effect. This region of chromosome 10 has also been shown in several rat crosses to influence blood pressure, especially under high salt intake (18). It is also homologous with a region on human chromosome 17q where linkage studies have suggested the presence of loci that may increase long-term longitudinal blood pressure and increase susceptibility to essential hypertension (5, 15). Although in our cross we did not find any effect of either QTL on basal blood pressure, we did not study the response of the QTLs to stress-related blood pressure. Therefore, it is possible that QTL 2 is also relevant to the blood pressure QTL that has been mapped to the same region. In any case, since the peak region of QTL 1 (between D10Wox11 and D10Mgh14) is also syntenic with a region on human chromosome 17, this chromosome is a likely site of genes that influence the sympathoneural response to stress in man.

The latest release of the rat genetic sequence identifies 523 genes in the region mapped for QTL 1 (between D10Mit4 and D10Mgh14) and 253 genes in the region mapped for QTL 2 (between D10Mgh23 and D10Wox20). There are no obvious candidate genes in either region involved in catecholamine synthesis or metabolism except for phenylethanolamine-N-methyl transferase (PNMT), which converts NE to Epi. Although impaired activity of PNMT could be hypothesized to explain the effect on NE response, one may then have expected to see reciprocal effects on the Epi response. The fact that this was not the case makes it unlikely, although it cannot be excluded at this stage. The selective effect of the QTLs on the NE stress response suggests that the genes responsible are likely to be specifically involved in NE transport or metabolism and expressed within the sympathetic nervous system. Eventual identification of the genes underlying the QTLs will require capture and narrowing of the QTL regions in congenic strains and analysis of a more limited number of putative candidate genes (18).

In summary, we report the mapping of two genomic regions on chromosome 10 in the rat that contain QTLs that specifically affect the NE response to immobilization stress. The findings indicate that individual components of the stress response may have specific genetic determinants that are identifiable. Defining the nature of these genetic determinants may have important implications for our understanding of the interindividual variation in the stress response and the role of stress in the pathogenesis of cardiovascular diseases.


    GRANTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
This work was supported by research grants of the Slovak Agency for Science (GAV 4131/1997–2000), SP 51/0280800/02808, and COST B17 and by a research grant of the Slovak Grant Agency for Technic (GAT PECO 931004) within the frame of the EURHYPGEN 1 and 2 Concerted Action of the European Union. Genotype analysis was supported by a grant from the British Heart Foundation (PG97026). R. Dixon is supported through the Wellcome Trust Functional Genomics Initiative in Cardiovascular Genetics (066780). N. J. Samani is a British Heart Foundation Professor of Cardiology.


    ACKNOWLEDGMENTS
 
We greatly appreciate the technical assistance of Alica Mitkova and Silvia Kuklova.


    FOOTNOTES
 
Article published online before print. See web site for date of publication (http://physiolgenomics.physiology.org).

Address for reprint requests and other correspondence: N. J. Samani, Cardiology Group, Dept. of Cardiovascular Sciences, Univ. of Leicester, Clinical Sciences Wing, Glenfield Hospital, Groby Road, Leicester, LE3 9QP, UK (E-mail: njs{at}le.ac.uk).

10.1152/physiolgenomics.00054.2004.


    REFERENCES
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 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 

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