DISEASE SUSCEPTIBILITY
20170240967 ยท 2017-08-24
Inventors
- Rolandus Hendrikus de Rijk (Leidschendam, NL)
- Melanie Diane Klok (Amsterdam, NL)
- Edo Ronald de Kloet (te Tienhoven, NL)
Cpc classification
G01N33/5008
PHYSICS
C12Q2600/106
CHEMISTRY; METALLURGY
C12Q1/6883
CHEMISTRY; METALLURGY
International classification
Abstract
The invention provides a method of assessing the susceptibility of a subject to, or aiding the diagnosis of, an anxiety disorder or depression, the method comprising determining whether the subject has a haplotype comprising rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951 with respective alleles +CT, C, T, C and C. The invention provides a kit of parts or solid substrate for use in assessing the susceptibility of a subject to an anxiety disorder or depression, the kit comprising or the solid substrate having attached thereto one or more nucleic acid molecules that hybridise selectively to a genomic region encompassing any two or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, and/or that hybridise selectively to a genomic region encompassing two or more polymorphic sites in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951.
Claims
1. A method of assessing the susceptibility of a subject to, or of aiding the diagnosis of, an anxiety disorder or depression, the method comprising determining whether the subject has a haplotype comprising rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951 with respective alleles +CT, C, T, C and C.
2. The method according to claim 1, wherein determining whether the subject has a haplotype comprising rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951 with respective alleles +CT, C, T, C and C, comprises genotyping any one or more single nucleotide polymorphisms (SNPs) selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, and/or one or more polymorphic sites which are in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, wherein reduced susceptibility is indicated when the allele of the one or more SNPs is respectively one or more of +CT, C, T, C and C, and/or when the allele of the one or more polymorphic sites is one that is in linkage disequilibrium with the respective one or more +CT, C, T, C and C alleles of the one or more SNPs.
3. (canceled)
4. (canceled)
5. The method according to claim 1, wherein the one or more polymorphic sites which are in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, are SNPs selected from the group consisting of rs5522, rs5525 and rs7671250, wherein reduced susceptibility is indicated when the allele of one or more of rs5522, rs5525 and rs7671250 is respectively A, C and T.
6. The method according to claim 1, wherein the one or more polymorphic sites are SNPs selected from the group consisting of rs7671250, rs5522, rs5525, rs4835519, rs2172002, rs11929719, rs11099695, rs11730626, rs2070949, rs2248038, rs9992256, rs5520, and SNP x at position 149585620 in the MR gene as numbered in
7. (canceled)
8. (canceled)
9. (canceled)
10. (canceled)
11. (canceled)
12. A method of combating an anxiety disorder or depression in a subject, the method comprising assessing the susceptibility of a subject to, or aiding the diagnosis of, an anxiety disorder or depression according to claim 1, and depending upon the outcome of the assessment treating the subject.
13. The method according to claim 12, wherein treating the subject comprises administering any one or more of an anti-depressant, an anti-convulsant, a beta-blocker, Cortisol, a Cortisol agonist, a Cortisol antagonist, an MR agonist, an MR antagonist, or an agent that modulates MR-expression to the subject.
14. The method according to claim 1, wherein the anxiety disorder is any of substance-induced anxiety disorder, generalised anxiety, panic disorder, acute stress disorder, post-traumatic stress disorder, adjustment disorder with anxious features, social phobia, obsessive-compulsive disorder or specific phobias.
15. (canceled)
16. A method of selecting an agent that modulates at least one activity of an MR in a MR gene haplotype-dependent manner, comprising: i) providing two or more MRs encodable by a respective two or more of a MR gene haplotype comprising rs2070951 and rs5522 with respective alleles G and A, or a MR gene haplotype comprising rs2070951 and rs5522 with respective alleles C and A, or a MR gene haplotype comprising rs2070951 and rs5522 with respective alleles C and G, or a MR gene haplotype comprising rs2070951 and rs5522 with respective alleles G and G; ii) providing a test agent; and iii) assessing whether the test agent modulates at least one activity of each MR in a MR gene haplotype-dependent manner.
17. (canceled)
18. (canceled)
19. The method according to claim 16, wherein the test agent is a steroid or a selective serotonin uptake inhibitor, or a tricyclic antidepressant.
20. (canceled)
21. The method according to claim 16, wherein step (iii) comprises assessing if the test agent modulates expression of a reporter polynucleotide operably linked to an MR responsive promoter.
22. (canceled)
23. (canceled)
24. (canceled)
25. The method according to claim 21, wherein expression of the reporter polynucleotide is determined by measuring the level of mRNA expressed from the reporter polynucleotide, measuring the concentration of a protein encoded by the reporter polynucleotide or measuring the activity or function of a protein encoded by the reporter polynucleotide.
26. The method according to claim 16, wherein step (iii) comprises assessing if the test agent modulates binding of the MR to a MR binding partner, or wherein step (iii) comprises assessing if the test agent modulates the effect of MR on Cortisol or ACTH levels.
27. (canceled)
28. (canceled)
29. (canceled)
30. The method according to claim 16, wherein the method is performed in vivo or ex vivo.
31. The method according to claim 30, wherein the two or more MRs in step (i) are provided in two or more respective subjects whose MR genotype is known or in two or more respective cells obtained from subjects whose MR genotype is known.
32. (canceled)
33. A method for classifying a subject according to the effectiveness of a treatment regime for an MR-related disorder, the method comprising determining whether a subject has a haplotype comprising rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951 with respective alleles CT, C, G and G, or a haplotype comprising rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951 with respective alleles +CT, C, T, C and C, or a haplotype comprising rs2070951 and rs5522 with respective alleles G and G, or a haplotype comprising rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951 with respective alleles CT, C, C, C and C, and either (i) administering a treatment regime, and assessing the effectiveness of the treatment regime, or (ii) administering an appropriate treatment regime for that haplotype, wherein the subject is one that has an MR-related disorder.
34. The method according to claim 33, wherein the MR-related disorder is anxiety disorder or depression, or a disorder associated with an anxiety disorder or depression such as any of cardiovascular disease, metabolic disorder (e.g. metabolic syndrome), Fibromyalgia, insomnia, Alzheimers disease, somatic disorder, bipolar disorder, pain, osteoporosis and immune disorder.
35. A kit of parts for use in selecting an agent that modulates at least one activity of an MR in a MR gene haplotype-dependent manner, comprising two or more MRs encoded by a respective two or more of a MR gene haplotype comprising rs2070951 and rs5522 with respective alleles G and A, or a MR gene haplotype comprising rs2070951 and rs5522 with respective alleles C and A, or a MR gene haplotype comprising rs2070951 and rs5522 with respective alleles C and G, or a MR gene haplotype comprising rs2070951 and rs5522 with respective alleles G and G, or a respective two or more polynucleotides encoding said MRs.
36. The kit of parts according to claim 35, comprising three or four MRs encoded by a respective three or four of a MR gene haplotype comprising rs2070951 and rs5522 with respective alleles G and A, or a MR gene haplotype comprising rs2070951 and rs5522 with respective alleles C and A, or a MR gene haplotype comprising rs2070951 and rs5522 with respective alleles C and G, or a MR gene haplotype comprising rs2070951 and rs5522 with respective alleles G and G, or a respective three or four polynucleotides encoding said MRs.
37. The kit of parts according to claim 35, further comprising a reporter gene operably linked to an MR responsive promoter.
38. The kit of parts according to claim 37, wherein the kit further comprises a substrate for detecting the reporter gene.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
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EXAMPLE 1: A MINERALOCORTICOID RECEPTOR HAPLOTYPE IS ASSOCIATED WITH DISPOSITIONAL OPTIMISM IN ELDERLY WOMEN BUT NOT IN MEN
Summary
[0251] The brain mineralocorticoid receptor (MR), together with the glucocorticoid receptor (GR), mediates the effects of the hormone Cortisol on behaviour and cognition. We have tested the relation between MR gene variants and dispositional optimism. Dispositional optimism is defined as having generalized expectancy of positive outcomes for the future. It is a rather stable personality trait and might confer resilience against depression.
[0252] Eight single nucleotide polymorphisms (SNPs) in the MR gene, including two functional MR SNPs, were genotyped in 450 subjects aged 65-85 of the Dutch Arnhem Elderly Study. Six known GR haplotypes, constituted of five SNPs, were taken along. Participants completed a questionnaire on their subjective levels of dispositional optimism as part of the Scale of Subjective Well-being for Older persons (SSWO). Haplotype reconstruction resulted in 3 main MR haplotypes with frequencies of 0.52, 0.36, and 0.12. MR haplotype 2 was associated with higher levels of optimism (15% increase) in women (p<0.001) but not in men (p=0.85; p=0.01 for interaction). The effect persisted after correction for several potential confounders and was estimated to explain 6% of the variance in optimism. The GR gene haplotypes had no influence on optimism scores. To conclude, our results suggest that MR haplotype 2 is associated with higher levels of dispositional optimism in women, which may establish resilience against stress and depression.
Introduction
[0253] The mineralocorticoid receptor (MR) is initially known for its function in the kidney, mediating aldosterone effects on salt status. Yet importantly, the MR is also expressed in the brain, mainly in limbic structures and frontal cortex. It has a ten-fold higher affinity for the hormone Cortisolthe main corticosteroidthan its regulatory partner, the glucocorticoid receptor (GR). Central MR is involved in basal activity of the hypothalamic-pituitary-adrenal (HPA) axis, autonomic outflow and in physiological response to a stressor (De Kloet, Vreugdenhil et al (1998); de Kloet, Van Acker et al (2000)). In humans, associations have been found between MR- and GR gene variants and HPA activity (Derijk, van Leeuwen et al (2008)). A single nucleotide polymorphism (SNP) in the MR gene, the MR-2 G/C SNP, was associated with basal Cortisol levels in elderly (Kuningas, de Rijk et al (2007)). In a study among healthy young males, another variant, the MR 1180V SNP, modulated Cortisol response after a psychosocial stressor (Trier Social Stress Test, TSST) (DeRijk, Wust et al (2006)). This same variant was also related to more feelings of depression in elderly (Kuningas, de Rijk et al (2007)). Moreover, associations between MR- and GR gene variants and stress-reactivity were found to be gender specific (Kumsta, Entringer et al (2007); Wust, Kumsta et al (2009))(Nienke PNE09 in press). These gender specific effects of MR and GR gene variants might contribute to the differences in prevalence of depression between men and women.
[0254] In addition to regulation of the HPA axis, central corticosteroid receptors are responsible for the effects of Cortisol on behaviour, learning and memory (Oitzl and de Kloet (1992); De Kloet, Vreugdenhil et al (1998)). Interestingly, based on studies with rodents the MR has been identified as a mediator of emotions and of explorative and coping behaviour (Oitzl and de Kloet (1992); Conrad, Lupien et al (1997); Rozeboom, Akil et al (2007)). Following an environmental demand the MR, but not the GR, regulates acute response selection, aimed to cope in an adaptive way. Also in humans Cortisol and its receptors are necessary for learning and memory (Lupien, Wilkinson et al (2002)). However, it is unknown whether the MR and GR modulate human coping behaviour or psychological characteristics. This would be interesting to know, as psychological traits influence coping behaviour and eventually can establish resilience or vulnerability to psychopathology (Carver and Connor-Smith 2009).
[0255] Dispositional optimism is a positive personality characteristic that seems relatively stable over time and its heritability is estimated at 25-40% (Plomin, Scheier et al (1992); Scheier, Carver et al (1994); Giltay, Kamphuis et al (2006)). The construct of dispositional optimism was introduced in 1985 by Scheier and Carver and was described as having generally positive outcome expectancies (Scheier and Carver 1985). It is associated with enhanced goal engagement and self-regulatory flexibility when encountering environmental demands or stressful situations (Scheier, Weintraub et al (1986); Carver, Pozo et al (1993); Nes and Segerstrom (2006); Geers, Weilman et al (2009)). Eventually, this can be beneficial for physiological and psychological health. Dispositional optimism is associated with less distress and predicts lower risk for depression and all-cause and cardiovascular death (Plomin, Scheier et al (1992); Scheier and Carver (1992); Carver, Pozo et al (1993); Scheier, Carver et al (1994); Vickers and Vogeltanz (2000); Giltay, Geleijnse et al (2004); Giltay, Kamphuis et al (2006); Giltay, Zitman et al (2006)). Interestingly, variability in levels of optimism and positive affect seems to relate to differences in basal Cortisol levels (Lai, Evans er al (2005); Steptoe, O'Donnell et al (2008)).
[0256] We hypothesised that the MR influences dispositional optimism, possibly modified by sex. In order to test this, we have analysed the association of eight MR gene variants, including two known functional MR SNPs, with optimism that was measured in subjects of the Arnhem elderly study cohort. Dispositional optimism was assessed with the Scale of Subjective Well-being for Older persons (SSWO), a questionnaire measuring subjective wellbeing in elderly (Tempelman (1987)). In addition, genotypes for five common GR variants were determined.
Methods
Study Population
[0257] Our study population was based on the Arnhem Elderly Study, a population-based cohort study that started in 1991-1992. The study design and population characteristics have been described previously (van den Hombergh, Schouten et al (1995)). The subjects that we included in our research were part of a random sample that was followed for 9.1 years to assess the relation between a person's level of dispositional optimism and all-cause and cardiovascular mortality (Giltay, Geleijnse et al (2004)). This sample included men and women with an age between 65 to 85 years old who were independently living in the city of Arnhem, the Netherlands. Of this random sample of 1793 individuals, 1012 subjects gave an interview, 685 subjects underwent a physical examination, and 641 subjects gave a blood sample. Of the 641 blood samples, 499 (77.8%) DNA isolates were available for genotyping, which was successful for 473 (94.8%) DNA samples. The final subset of 450 subjects (optimism scores were missing for 23 subjects) did not differ from the initial group of 1012 subjects that gave an interview on sex, education, body mass index (BMI), or total number of chronic diseases. The included subjects were, however, significantly younger (mean age 73.75.7 vs. 75.25.7, p<0.001), more often together (60.9% vs. 54.1%, p=0.03), more often had a higher socioeconomic status (SES; 64.0% vs. 55.8%, p<0.01), more often suffered from cardio-vascular disease (CVD; 24.0% vs. 14.9%, p=0.01), and were more optimistic (mean score 13.404.68 vs. 12.364.91, p=0.001). When comparing the 450 subjects with the 49 subjects for whom we did not have a complete dataset, no significant differences were found for any of the sociodemographic or health factors. This study was approved by the Medical Ethics Committee of Wageningen University (Wageningen, the Netherlands). All participants provided written informed consent.
Assessment of Dispositional Optimism
[0258] Optimism was assessed using the Dutch Scale of Subjective W ell-being for Older Persons (SSWO) developed by Groningen University (Groningen, the Netherlands) (Tempelman (1987)). The SS WO consists of five subscales including health, self-respect, morale, contacts, and optimism. Validity of the SSWO was previously assessed by comparing the results with objective measures of well-being (eg physical activity, mobility, use of health care, and activities of daily living) and the Hopkins Symptom Checklist (Tempelman (1987)). For each subscale an individual could indicate to what extent it conforms to a particular statement on a 3-point scale (from 0 to 2). The seven questions of the optimism subscale were: I often feel that life is full of promises, I still have positive expectations concerning my future, There are many moments of happiness in my life, I do not make any more future plans, Happy laughter often occurs, I still have many goals to strive for, and Most of the time I am in good spirits (our translations). The subscale had an adequate internal consistency (Cronbach's a: 0.76) and reliability (test-retest reliability coefficient: 0.76) (Tempelman (1987)). Questionnaires with missing data for the optimism subscale were excluded from the analyses. A mean item score for the optimism subscale was calculated and multiplied by 10, resulting in scores ranging from 0 to 20, with higher scores indicating a higher level of optimism.
Demographics, health, and blood sampling
[0259] All data on demographics and health were assessed by trained interviewers (van den Hombergh, Schouten et al (1995); Giltay, Geleijnse et al (2004)). Dichotomous variables were created for sex (0=women; 1=men), marital status (0=living together as a married or unmarried couple; 1=otherwise), education (0=otherwise; 1=higher vocational or university), presence of CVD (0=absent; 1=present), and SES (0=housewives, unskilled and skilled workers, and lower employees; 1=small-business owners, employees, and higher professions; for married or widowed women SES was defined according to that of the husband). A variable for total number of chronic diseases coded for the total number of chronic disorders and illnesses of the respondent (0, 1, 2, 3, 4, or 5 or more from a list of 24; eg chronic gastric disease, cancer, thyroid disease). Body mass index (BMI) was calculated by dividing weight in kilograms (to the nearest 0.5 kg with the subject dressed but not wearing shoes) by height in meters squared (to the nearest 0.5 cm). A single blood sample was obtained from 641 subjects. Samples were stored at 80 C. until further analysis.
Genotyping
[0260] Genomic DNA was isolated from the blood samples according to standard procedures. Genotypes were determined for the functional MR-2G/C (rs2070951) and 1180V (rs5522) SNPs. Two SNPs, the rs2070950 and rs5525, were included as additional control SNPs in case of genotyping failure for the -2 SNP or 1180V SNP respectively. Four additional SNPs, with the accession numbers rs3216799 (an insertion-deletion polymorphism of two nucleotides, CT), rs7671250, rs6814934 and rs7678048, which are located in the MR promoter region, were assessed. In addition, genotypes for several common GR variants, the Tthlll\ (rs10052957), ER22EK (rs6189), N363S (rs6195), Bcl1 (rs41423247) and 9(rs6198) SNPs, were assessed.
[0261] Genotyping was conducted using a Sequenom MassARRAY iPLEX assay (Sequenom, San Diego, Calif., USA). After a touchdown polymerase chain reaction (PCR) and a primer extension reaction to introduce mass-differences between alleles, reaction products were desalted, processed and mass differences were detected using an Autoflex (Bruker, Wormer, Netherlands) MALDI-TOF Mass Spectrometer. Genotypes were assigned real-time using MassARRAY TYPER Analyzer 3.4 software (Sequenom, San Diego, Calif., USA). As quality control, 5 to 10% of the samples were genotyped in duplicate, and positive and negative controls that were included were consistent. Samples that failed for 50% of the SNPs or more were omitted from further analysis.
Statistical Analysis
[0262] Allele frequencies for the different SNPs were tested for Hardy-Weinberg Equilibrium (HWE) using HaploView (version 4.1 for Mac OSX) (Barrett, Fry er a/(2005)). In addition, this program was used to test whether the SNPs for the MR gene were in linkage disequilibrium (LD) and to reconstruct haplotypes for the MR and GR genes. We used r.sup.2 and D.sup.l to verify respectively the magnitude of inter-marker correlations and to define haplotype bins with the Solid Spine of LD method implemented in HaploView. Individual haplotypes were reconstructed in SNPHAP (version 1.3; available online at http://www-gene.cimr.cam.ac.uk/clayton/software/; last visited on Feb. 14, 2008). For the MR, haplotypes were reconstructed based on only the -2 G/C and 1180V SNPs, which tag haplotypes 1-3 (five minor haplotypes with frequencies below 0.02 were pooled with haplotype 2 with a frequency of 0.32, resulting in a total frequency of 0.36). Samples with probabilities below 0.50 (n=1) were discarded. For the GR gene, haplotypes with a probability below 0.50 were also discarded (n=8); haplotypes with probabilities between 0.50 and 0.95 (n=10) or above 0.95 were weighted for their probabilities in the statistical analyses. Further analysis was performed in SPSS, version 16.0 for Mac OSX (SPSS Inc., Chicago, Ill., USA).
[0263] Association between dispositional optimism and sociodemographic or health factors was tested with regression analysis or an independent-samples t-test. Differences between men and women on these variables were tested using an independent-samples t-test or a.sub.X.sup.2 test. The main aim was to test the influence of MR haplotypes on the level of optimism. To verify whether any of the MR or GR SNPs was associated with optimism scores, one-way ANOVA was used. Subsequently, differences between the MR haplotypes were tested using linear regression analysis. Next, analyses were repeated for the GR haplotypes. Furthermore, confounding effects of the GR haplotypes on the results with the MR haplotypes was verified. Comparison of mean optimism scores for the different MR diplotypes was conducted with one-way ANOVA, followed by a post-hoc Gabriel test. In a second regression analysis, we adjusted for potential confounding effects of sex (when appropriate), age, educational level, marital status, and SES in multivariable model 1, or additionally for CVD and total number of chronic diseases in model 2. All regression analyses were repeated while stratifying the data for sex. Finally, as the optimism scores showed a somewhat negatively skewed distribution, scores were inversed and log-transformed (to approach a normal distribution), and tests were repeated with these log-transformed data. A two-sided p-value <0.05 was considered statistically significant. As our main interest was the one test determining the association between the MR haplotypes and optimism, no Bonferroni correction was applied.
Results
Sample Characteristics
[0264] Data sets with optimism scores, genotypes, sociodemographic and health-related variables were available for 450 individuals (Table 1; note that for SES, BMI, total number of chronic diseases, and CVD several data points were missing). Increasing age, lower educational level, living alone, and more chronic disease were significantly associated with lower dispositional optimism scores (p's<0.05). No associations with optimism were found for SES, BMI, or CVD. There were important sex differences in sociodemographic and health-related variables (Table 1), but the mean optimism scores did not differ between men and women (p=0.78). One subject reported a depressive disorder.
MR and GR Haplotype Structure and Frequencies
[0265] All allele frequencies of the MR and GR SNPs were in HWE (p>0.10). For an overview of individual SNP genotype frequencies see Table 2. Allele frequencies of the MR-2G/C and 1180V SNPs were similar as previously reported (DeRijk, Wust et al (2006); Kuningas, de Rijk et al (2007)) Nienke PNE09 in press). Reconstruction of MR haplotypes resulted in one haplotype bin containing all eight genotyped SNPs (
Associations between individual MR or GR SNPs and dispositional optimism
[0266] For the eight MR SNPs, significant associations were found between dispositional optimism and the SNPs rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, with the highest significant associations found for the promoter SNPs rs3216799 and rs7658048 (Table 2). As sex differences exist for the effects of MR and GR SNPs on HPA activity, association analysis was repeated while stratifying for gender. Significant associations between optimism scores and the MR SNPs were found only in women, but not in men. No associations were found between dispositional optimism and any of the GR SNPs, not for the total group or for women or men separately.
Associations Between MR Haplotypes and Dispositional Optimism
[0267] We also tested associations between the naturally occurring MR haplotypes and the level of dispositional optimism. The MR haplotypes were significantly associated with dispositional optimism scores; haplotype 2 was associated with higher optimism when compared to the baseline haplotype 1 (Table 3). This haplotype 2 contains the functional -2 C-allele, while it does not contain the 180 V-allele. Importantly, we found a strong MR haplotype 2-by-sex interaction effect (p=0.01). Only in women, haplotype 2 was related to higher levels of optimism, while no significant effect was found in men (Table 3 and
[0268] No association was found between dispositional optimism scores and the GR haplotypes (p=0.65 for the model for the total group), not in women (p=0.57), not in men (p=0.86;). In addition, including the GR haplotypes as confounders in the regression analysis for the MR haplotypes on optimism did not change the results. Finally, similar results were found when tests were repeated with the logarithmically transformed optimism data (data not shown).
[0269] The SSWO questionnaire actually consists of five subscales, namely health, self-respect, morale, contacts, and optimism. Association between the three MR haplotypes and these additional subscales was verified. Interestingly, also only in women haplotype 2 was associated with higher levels of self-respect, p<0.01; and the total SSWO score, p<0.001; a statistical trend was found for higher morale, p=0.06 and better health p=0.07.
TABLE-US-00001 TABLE 1 Sociodemographic and health factor measures according to sex in 450 elderly subjects Variable Total n Total Women Men p-value* Gender 450 450 215 (47.8%) 235 (52.2%) Age 450 73.7 5.7 74.2 5.9 73.2 5.5 0.06 Education level Highschool or 450 91 (20.2%) 26 (12.1%) 65 (27.7%) <.001 University Otherwise 359 (79.8%) 189 (87.9%) 170 (72.3%) Marital status Living 450 274 (60.9%) 80 (37.2%) 194 (82.6%) <.001 together ((un)married couple) Otherwise 176 (39.1%) 135 (62.8%) 41 (17.4%) Socioeconomic Low 444 160 (36.0%) 88 (41.7%) 72 (30.9%) 0.02 status High 284 (64.0%) 123 (58.3%) 161 (69.1%) BMI 448 25.8 3.9 26.3 4.5 25.4 3.1 0.01 Total number of 0 446 90 (20.2%) 32 (15.0%) 58 (25.0%) 0.02 chronic diseases 1 122 (27.4%) 54 (25.2%) 68 (29.3%) 2 100 (22.4%) 51 (23.8%) 49 (21.1%) 3 67 (15.0%) 39 (18.2%) 28 (12.1%) 4 30 (6.7%) 14 (6.6%) 16 (6.9%) 5 or more 37 (8.3%) 24 (11.2%) 13 (5.6%) Cardiovascular Absent 446 339 (76.0%) 171 (79.9%) 168 (72.4%) 0.06 disease Present 107 (24.0%) 43 (20.1%) 64 (27.6%) Dispositional 450 13.40 4.68 13.46 4.69 13.34 4.68 0.78 optimism Data are mean SD or n (%). *An independent-samples t-test or .sup.2 test was used to examine p-values for sex differences.
TABLE-US-00002 TABLE 2 Dispositional optimism scores according to genotypes for the different MR and GR SNPs in 450 elderly subjects Total Women Men (n = 450) (n = 215) (n = 235 Optimism Test Optimism Test Optimism Test n (mean statistic.sup.# n (mean statistic.sup.# n (mean statistic.sup.# Genotypo (frequency) SD) p-value (frequency) SD) p-value (frequency) SD) p-value MR SNP rs3216799 / 195 12.70 F(1, 413) = 84 12.38 F(1, 196) = 111 12.95 F(1, 214) = n = 416 (0.47) (4.81) 7.66 (0.42) (4.59) 12.22 (0.51) (4.97) 0.52 /+CT 173 13.88 p = .01 97 13.58 p = .001 76 14.27 p = .47 (0.42) (4.36) (0.49) (4.61) (0.35) (4.02) +CT/+CT 48 14.35 18 16.75 30 12.50 (0.11) (5.15) (0.09) (4.27) (0.14) (5.16) rs7671250 TT 334 13.49 F(1, 446) = 153 13.58 F(1, 211) = 181 13.43 F(1, 232) = n = 449 (0.74) (4.61) 0.50 (0.72) (4.69) 0.46 (0.77) (4.55) 0.19 TC 110 13.12 p = .44 58 13.23 p = .50 52 12.99 p = .66 (0.25) (4.90) (0.27) (4.76) (0.22) (5.09) CC 5 12.86 3 11.50 2 14.29 (0.01) (5.71) (0.01) (5.41) (0.01) (8.08) rs66814934 GG 125 12.91 F(1, 443) = 51 12.47 F(1, 212) = 74 13.22 F(1, 228) = n = 446 (0.28) (4.53) 4.61 (0.24) (4.27) 8.65 (0.32) (4.71) 0.05 CC 211 13.33 p = .03 107 13.10 p < .01 104 13.57 p = .82 (0.47) (4.74) (0.50) (4.87) (0.45) (4.62) CC 110 14.23 57 15.04 53 13.37 (0.25) (4.52) (0.26) (4.37) (0.23) (4.76) rs7658048 CC 207 12.82 F(1, 442) = 89 12.42 F(1, 209) = 118 13.11 F(1. 230) = n = 445 (0.47) (4.80) 6.28 (0.42) (4.57) 14.92 (0.51) (4.96) 0.00 CT 187 13.67 p = .01 101 13.55 p < .001 84 13.81 p = .95 (0.42) (4.42) (0.49) (4.69) (0.36) (4.08) TT 51 14.43 20 17.14 31 12.67 (0.11) (4.99) (0.09) (3.37) (0.13) (5.12) rs2070950 GG 123 12.93 F(1, 442) = 51 12.47 F(1, 210) = 72 13.25 F(1, 229) = n = 445 (0.28) (4.56) 4.66 (0.24) (4.27) 3.16 (0.31) (4.76) 0.02 GC 212 13.20 p = .03 105 13.02 p < .01 107 13.38 p = .88 (0.47) (4.77) (0.49) (4.88) (0.46) (4.68) CC 110 14.27 57 15.11 53 13.37 (0.25) (4.63) (0.27) (4.39) (0.23) (4.76) rs2070951 GG 123 12.81 F(1, 441) = 50 12.34 F(1, 210) = 73 13.13 F(1, 228) = (2 G/C) (0.28) (4.50) 5.70 (0.24) (4.22) 10.05 (0.32) (4.68) 0.12 n = 444 GC 210 13.29 p = .02 105 13.02 p < .01 105 13.56 p = .73 (0.47) (4.74) (0.49) (4.88) (0.45) (4.60) CC 111 14.27 58 15.10 53 13.37 (0.25) (4.61) (0.27) (4.36) (0.23) (4.76) rs5522 AA 331 13.56 F(1, 433) = 156 13.57 F(1, 206) = 175 13.54 F(1, 224) = (I180V) (0.76) (4.60) 1.21 (0.74) (4.72) 1.31 (0.77) (4.51) 0.19 n = 436 AG 101 12.94 p = .27 52 13.02 p = .25 49 12.86 p = .67 (0.23) (4.92) (0.25) (4.65) (0.22) (5.23) GG 4 13.21 1 5.71 3 15.71 (0.01) (7.13) (0.01) (0.01) (6.23) ra5525 CC 343 13.51 F(1, 446) = 160 13.61 F(1, 211) = 183 13.43 F(1, 232) = n = 449 (0.76) (4.58) 0.85 (0.75) (4.68) 1.08 (0.78) (4.51) 0.08 CT 101 12.97 p = .36 52 13.08 p = .30 49 12.86 p = .78 (0.23) (4.95) (0.24) (4.72) (0.21) (5.23) TT 5 13.43 2 10.00 3 15.71 (0.01) (6.19) (0.01) (6.06) (0.01) (6.23) GR SNP rs10052957 CC 218 13.22 F(1, 441) = 104 13.30 F(1, 209) = 114 13.14 F(1, 229) = (TthIIII) (0.49) (4.57) 0.46 (0.49) (4.58) 0.23 (0.49) (4.59) 0.23 n = 444 CT 175 13.61 p = .50 83 13.56 p = .63 92 13.65 p = .64 (0.39) (4.89) (0.39) (4.84) (0.40) (4.96) TT 51 13.50 25 13.71 26 13.30 (0.12) (4.54) (0.12) (4.98) (0.11) (4.16) rs6189 GG 421 13.41 F(1, 447) = 198 13.41 F(1, 213) = 223 13.41 F(1, 232) = (ER22/23EK) (0.93] (4.64) 0.13 (0.92) (4.70) 0.36 (0.95) (4.60) 1.17 n = 450 GA 27 13.44 p = .72 17 14.12 p = .55 10 12.29 p = .28 (0.06) (5.29) (0.08) (4.65) (0.04) (6.32) AA 2 10.71 0 2 10.71 (0.01) (7.07) (0.01) (7.07) rs6195 AA 418 13.46 F(1, 444) = 202 13.57 F(1, 212) = 216 13.35 F(1, 230) = (N363S) (0.94) (4.67) 1.75 (0.94) (4.70) 2.37 (0.93) (4.65) 0.16 n = 446 AG 28 12.24 p = .19 12 11.43 p = .13 16 12.86 p = .69 (0.06) (5.02) (0.06) (4.39) (0.07) (5.50) GG 0 0 0 rs41423247 CC 169 13.52 F(1, 437) = 78 13.52 F(1, 208) = 91 13.53 F(1, 226) (Bc11) (0.38) (4.48) 0.23 (0.37) (4.46) 0.48 (0.40) (4.52) 0.00 n = 440 CG 215 13.38 p = .63 105 13.74 p = .49 110 13.04 p = .99 (0.49 (4.87) (0.50) (4.83) (0.48) (4.91) GG 56 13.19 28 12.45 28 13.93 (0.13) (4.74) (0.13) (4.70) (0.12) (4.76) rs6198 AA 303 13.17 F(1, 436) = 144 13.08 F(1, 208) = 159 13.26 F(1, 225) = (9) (0.69) (4.57) 1.34 (0.68) (4.58) 2.03 (0.70) (4.58) 0.07 n = 439 AG 120 14.06 p = .25 61 14.48 p = .16 59 13.70 p = .79 (0.27) (4.76) (0.29) (4.73) (0.26) (4.80) GG 16 12.96 6 12.86 10 12.86 (0.04) (4.33) (0.03) (3.94) (0.04) (4.76) Data are presented for the total group, as well as for women and men separately. .sup.#One-way ANOVA F-values for linear trend (and their accompanying degrees of freedom) were used to examine p-values for association.
TABLE-US-00003 TABLE 3 Effects of MR haplotypes 1 to 3 on mean dispositional optimism scores in 450 elderly subjects MR haplotype MR haplotype MR haplotype 1 2 3 Total (n = 450) .sup.a Crude ref. B = 0.90 (0.33); B = 0.08 (0.50); p = .01 p = .88 Mode 1 ref. B = 0.81 (0.33); B = 0.26 (0.49); p = .01 p = .60 Mode 2 ref. B = 0.72 (0.32); B = 0.13 (0.49); p = .03 p = .79 Women (n = 215) .sup.b Crude ref. B = 1.82 (0.48); B = 0.04 (0.69); p < .001 p = .95 Mode 1 ref. B = 1.70 (0.48); B = 0.31 (0.70); p < .001 p = .66 Mode 2 ref. B = 1.67 (0.47); B = 0.21 (0.69); p < .001 p = .76 Men (n = 235) .sup.c Crude ref. B = 0.14 (0.45); B = 0.13 (0.70); p = .75 p = .85 Mode 1 ref. B = 0.08 (0.44); B = 0.13 (0.69); p = .87 p = .86 Mode 2 ref. B = 0.09 (0.44); B = 0.67 (0.68); p = .85 p = .92
[0270] Effects on mean dispositional optimism scores were compared between the three most frequent MR haplotypes, crude or adjusted for potential confounders, model 1 and 2. Model 1: adjusted for sex (when appropriate), age, education level, marital status, and SES. Model 2: data additionally adjusted for CVD and total number of chronic diseases. Linear regression analysis was used to yield B-coefficients and p-values. B-coefficients can be interpreted as the mean difference (SEM) in dispositional optimism score per haplotype allele when compared to the reference haplotype 1.
[0271] .sup.aTotal: R.sup.2=0.02; mode 1: R.sup.2=0.06 for step 1, R.sup.2=0.02 for step 2; mode 2: R.sup.2=0.06 for step 1, R.sup.2=0.03 for step 2, R.sup.2=0.01 for step 3. .sup.bWomen: R.sup.2=0.07; mode 1: R.sup.2=0.06 for step 1, R.sup.2=0.06 for step 2, mode 2: R=0.06 for step 1, R.sup.2=0.03 for step 2, R.sup.2=0.06 for step 3. Wen: R.sup.2<0.01, mode 1: R.sup.2=0.07 for step 1, R.sup.2<0.01 for step 2, mode 2: R.sup.2=0.06 for step 1, R.sup.2=0.04 for step 2, R.sup.2<0.01 for step 3.
Discussion
[0272] We found that the MR haplotype 2, which consists of the C-allele of the functional -2 G/C SNP and extends into the promoter region, was highly significant associated with higher levels of dispositional optimism in elderly women but not in men. This was independent of several potential confounders. Importantly, we were also able to show that haplotype 2 was associated with optimism in a dose dependent manner, with women having a 2/2 diplotype reporting even higher optimism scores than women with only one haplotype 2 allele. No effect was found for the GR haplotypes. This is the first report on a MR gene variant that is associated with a positive psychological trait in humans.
[0273] MR haplotype 2 contains the functional -2 G/C SNP. The C-allele of this SNP increases MR expression and MR-driven gene transcription in vitro [Nienke PNE09 in press] In addition, the -2 C-allele has been shown to associate with lower basal Cortisol levels in elderly (Kuningas, de Rijk et al (2007)). Together with our results, this finding seems to fit with a study showing that higher levels of optimism associate with lower basal Cortisol levels (Lai, Evans et al (2005)). It would be interesting to know whether the differences in optimism scores we found were also associated with variances in Cortisol levels. Unfortunately, no Cortisol data were assessed in the Arnhem elderly study. Furthermore, our results are also in line with a report showing that the MR 180 V-allele, or haplotype 3, associated with more depressive symptoms in a Dutch elderly cohort, the Leiden 85+cohort (Kuningas, de Rijk et al (2007)). In our study this haplotype 3 (although carried by only 2 subjects) was associated with the lowest scores for optimism.
[0274] Only in women, MR haplotype 2 associated with higher levels of dispositional optimism. Sex differences have previously been reported for HPA responses to stress but also for personality traits (Kudielka and Kirschbaum (2005); Schmitt, Realo et al (2008)). A gene-by-sex interaction could contribute to this and indeed has been found for HPA axis functioning and personality (Lang, Hellweg et al (2008); Wust, Kumsta et al (2009)). Additionally, also in rodents sex-specific effects of genes are found, for example for the MR and its influence on behavioural stress response (Rozeboom, Akil et al (2007)). One of the possible explanations for this gene-by-sex interaction of the MR may be its interaction with sex steroids. Estrogens and progesterone modulate protein and mRNA expression of corticosteroid receptors (Castren, Patchev et al (1995); Turner (1997)). In addition, progesterone can also bind to the human MR (Quinkler, Meyer et al (2002)). However, all women were 65+ of age, which means they probably all have low levels of estradiol due to menopause. Still, when conducting certain cognitive tests, only in elderly women variability in endogenous estradiol levels has been reported to relate to differences in performance (Wolf and Kirschbaum (2002)).
[0275] No relation was found between the GR gene variants and optimism. Rodent studies have shown that both the MR and GR modulate anxiety- and depressive like behaviours, including learned helplessness (Urani, Chourbaji et al (2005); Rozeboom, Akil et al (2007)). Moreover, both the MR and GR are involved in behaviour and cognition. However, it seems that it is mainly the MR that is mediating choice of behavioural strategy, flexibility and reactivity (Oitzl and de Kloet (1992); Berger, Wolfer et al (2006); Brinks, van der Mark et al (2007)). When, for example after a training session rats are treated with a MR antagonist, they show an altered search-escape strategy in the Morris water maze. Blocking the GR had no such effect (Oitzl and de Kloet (1992)). To our knowledge there is only one study that reported an effect of MR blockage on cognitive flexibility in humans (Otte, Moritz et al (2007)). The importance of the GR for cognitive functioning during elevated levels of Cortisol is generally accepted, but additional studies are warranted to elucidate the specific roles of the MR and GR in cognitive flexibility, coping behaviour and psychological traits.
[0276] To the best of our knowledge, this is the first study reporting on a gene variant that was associated with variability in the positive psychological trait dispositional optimism. Evidence is accumulating for optimism having influence on goal engagement and coping behaviour, indirectly enhancing a multitude of health outcomes, (Scheier, Weintraub et al (1986); Plomin, Scheier et al (1992); Scheier and Carver (1992); Carver, Pozo et al (1993); Scheier, Carver et al (1994); Vickers and Vogeltanz (2000); Giltay, Geleijnse et al (2004); Giltay, Kamphuis et al (2006); Giltay, Zitman et al (2006); Nes and Segerstrom (2006); Geers, Wellman et al (2009)). Hopelessness, on the other hand, has been reported to increase risk for disease and mortality and is positively associated to stress-related disorders like depression (Everson, Goldberg et al (1996); Joiner, Steer et al (2001)). Optimists seem more resilient against everyday challenges. People with high levels of optimism are better in tolerating stressful conditions and choose a coping strategy that is appropriate for the situation. For example, in a study following women that were diagnosed with breast cancer, the more optimistic women were able to accept their situation and used positive retraining and also humour to deal with it, leading to less distress (Carver, Pozo et al (1993)). Optimists are cognitively more flexible, seek and perceive more social support, and more often turn to religion or exercise (Scheier and Carver (1992); Carver, Pozo et al (1993); Scheier, Carver et al (1994); Southwick, Vythilingam et al (2005)). Moreover, optimists cope better may be in part because they perceive information from their environment differently. Optimists are able to ignore negative stimuli better when it is not relevant and have more attention to positive stimuli (Isaacowitz (2005)). The identification of genes and biological mechanisms underlying traits that confer resilience against stress could provide important information for pharmaco- and cognitive therapy in patients with anxiety- and depressive disorders. The mechanism by which glucocorticoids and the MR affect optimism remains unclear. It has been postulated that people who are able to remain optimistic during challenging situations have a neurobiologicai system for reward and motivation that is hyperactive or resistant to change (Southwick, Vythilingam et al (2005)). Multiple studies have reported that glucocorticoids act on the brain reward system. An example is the effect of glucocorticoids on the motivation to take drugs, that is known to be mediated at least by the GR (Ambroggi, Turiault et al (2009)). Whether the MR is implicated in reward mechanisms needs further investigation.
[0277] We found an association between a MR gene variant and variability in optimism among elderly subjects. Multiple studies have reported on changes in emotional and cognitive functioning among older adults. Levels of optimism and positive effect but also cognitive functioning slowly decrease, while the prevalence of depressive symptoms and depressive disorder increases (de Beurs, Comijs et al (2005); Giltay, Zitman et al (2006); Kuningas, de Rijk et al (2007)). Malfunctioning of the HPA axis might be one of the underlying mechanisms. Expression of corticosteroid receptors in the brain changes during development, throughout adulthood and during aging (van Eekelen, Rots et al (1992); Schmidt, Enthoven et al (2003); Dalm, Enthoven et al (2005)). For example, expression of MR in the hippocampus is decreased in old rats. It is possible that MR gene variants play a modulating role, resulting in more or less decrease in MR expression, eventually leading to better or worse psychological functioning. As mentioned before, the -2 C-allele results in more expression of MR and a higher gene transactivation in vitro. Moreover, haplotype 2 also consists of two SNPs located in the promoter region for which the highest significant associations were found with optimism. It is very well possible that these SNPs have an additional and may be even stronger effect on MR expression. Therefore, these promoter SNPs need to be tested for their effect on promoter activity.
[0278] To conclude, we found that the MR haplotype 2, including the functional -2 C-allele but not the 180 V-allele, was associated with higher levels of dispositional optimism in Dutch elderly females in a dose dependent manner. The results indicate that the MR modulates not only neuroendocrine- and autonomic response to a stressor but can also affect a positive psychological trait, which may determine resilience against stress and depression.
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Chourbaji, et al (2005) Mutant mouse models of depression: candidate genes and current mouse lines. Neurosci Biobehav Rev 29(4-5): 805-28. [0320] van den Hombergh, C. E., E. G. Schouten, et al (1995) Physical activities of noninstitutionalized Dutch elderly and characteristics of inactive elderly. Med Sci Sports Exerc 27(3): 334-9. [0321] van Eekelen, J. A., N. Y. Rots, et al (1992) The effect of aging on stress responsiveness and central corticosteroid receptors in the brown Norway rat. Neurobiol Aging 13(1): 159-70. [0322] Vickers, K. S. and N. D. Vogeltanz (2000) Dispositional optimism as a predictor of depressive symptoms over time Person. Individ. Diff 28: 259-272. [0323] Wolf, O. T. and C. Kirschbaum (2002) Endogenous estradiol and testosterone levels are associated with cognitive performance in older women and men. Horm Behav 41(3): 259-66. [0324] Wust, S., R. Kumsta, et al (2009) Sex-specific association between the 5-HTT gene-linked polymorphic region and basal Cortisol secretion. Psychoneuroendocrinology.
EXAMPLE 2: HUMAN MINERALOCORTICOID RECEPTOR GENE VARIANTS MODULATE COGNITIVE VULNERABILITY FOR DEPRESSION
[0325] The mineralocorticoid receptor (MR) plays a central role in the regulation of hypothalamic-pituitary-adrenal (HPA) axis activity. Animal studies indicate that the MR mediates effects of Cortisol on emotions and coping behaviour. We hypothesise that human MR-gene variants influence cognition and emotions. We have identified a MR haplotype (frequency 0.36) to relate to higher dispositional optimisim in elderly women, not in men (see Example 1).
[0326] In the present study 154 students (46 M/108 F; 23.95 yrs) completed a questionnaire that measures cognitive vulnerability to depression and that includes subscales for hopelessness, rumination and aggression (LEIDS-Rsee Appendix; Van der Does, Behav Res & Therap 40:105-120, 2002); Leiden Index of Depression Sensitivity-Revised). Neuroticism was also measured (NEO-PI) as well as symptoms of depression (HADS-D). MR SNPs and haplotypes were assessed, resulting in three haplotypes with frequencies of 0.50; 0.35; 0.13.
[0327] Significant associations were found only in females between the haplotype with a frequency 0.35 and lower scores for hopelessness, aggression, risk aversion, neuroticism (p<0.05), and in particular for rumination (p=0.001), persisting after adjustment for age and emotional abuse during childhood. Excluding currently depressed participants (n=14) strengthened the results. Moreover, this haplotype significantly associated with less symptoms of depression (p<0.05). The results fit with our study showing an association between this haplotype and higher dispositional optimism (Example 1), also only in women. Together the data indicate that MR-gene variants modulate cognitive vulnerability for depression.
[0328] In the present study 154 Dutch students (46 M/108 F; 23.95 yrs) completed a questionnaire that was prepared to assess cognitive vulnerability to depression, the LEIDS-R (Leiden Index of Depression Sensitivity-Revised). This questionnaire measures cognitive reactivity to sad mood (Van der Does, A. J. W., 2002). The subjects have to read the instructions and indicate to what extend they agree with in total 34 statements. The scale includes 6 subscales, namely hopelessness/suicidality, acceptance/coping, aggression, control/perfectionism, risk aversion, and rumination. In addition, neuroticism was measured (NEO-PI) as well as symptoms of depression and anxiety (HADS-D and HADS-A). All students were genotyped for the MR SNPs-2G/C (rs2070951) and 1180V (rs5522) and haplotypes were reconstructed.
[0329]
APPENDIX
[0330] LEIDS-R Questionnaire
[0331] Instructions
[0332] Below are a number of statements that may apply to you to a lesser or greater extent.
[0333] Almost every statement concerns your thoughts about a certain matter at times when you feel down or when you are in a low mood. This does not mean a seriously depressed mood or true depression. Your task is to indicate the extent to which the statements apply to you when you feel somewhat sad.
[0334] Try to imagine the following situation when filling out this questionnaire.
[0335] It is certainly not a good day, but you don't feel truly down or depressed.
[0336] Perhaps your mood is an early sign of something worse to come, but things might also improve in the next day or two.
[0337] On a scale ranging from 0 to 10 (0=not at all sad; 10=extremely sad; 6 and above=a truly depressed mood), you would choose a 3 or 4 to describe your mood.
[0338] The scale looks like this:
[0339] The soak?, looks like thin
##STR00001##
[0340] Please try to imagine yourself in the above situation, for instance by thinking back to the last time you felt somewhat sad (score 3 or 4). [0341] {Now take some time to imagine such a situation.}
[0342] To what extent are you able to imagine such a situation? [0343] well [0344] somewhat [0345] not at all
[0346] Now proceed to the next question (even if you find it difficult to imagine yourself in such a situation).
TABLE-US-00004 This applies to me . . .: (please circle) not moder- very at all a bit ately strongly strongly 1. I can only think positive when I am in a good 0 1 2 3 4 mood. 2. When in a low mood, I take fewer risks. 0 1 2 3 4 3. When I feel sad, I spend more time thinking 0 1 2 3 4 about what my moods reveal about me as a person. 4. When in a sad mood, I am more creative than 0 1 2 3 4 usual. 5. When I feel down, I more often feel hopeless 0 1 2 3 4 about everything. 6. When I feel down, I am more busy trying to 0 1 2 3 4 keep images and thoughts at bay. 7. In a sad mood. I do more things that I will later 0 1 2 3 4 regret. 8. When I feel sad, I go out and do more 0 1 2 3 4 pleasurable activities. 9. When I feel sad, I feel as if I care less if I lived 0 1 2 3 4 or died. 10. When I feel sad, I am more helpful. 0 1 2 3 4 11. When I feel sad, I am less inclined to express 0 1 2 3 4 disagreement with someone else. 12. When I feel somewhat depressed, I think I can 0 1 2 3 4 permit myself fewer mistakes. 13. When I feel down, I more often feel 0 1 2 3 4 overwhelmed by things. 14. When in a low mood, I am more inclined to 0 1 2 3 4 avoid difficulties or conflicts. 15. When I feel down, I have a better intuitive 0 1 2 3 4 feeling for what people really mean. 16. When in a sad mood, I become more bothered 0 1 2 3 4 by perfectionism. 17. When I feel sad, I more often think that I can 0 1 2 3 4 make no one happy. 18. When I feel bad, I feel more like breaking things. 0 1 2 3 4 19. I work harder when I feel down. 0 1 2 3 4 20. When I feel sad, I feel less able to cope with 0 1 2 3 4 everyday tasks and interests. 21. In a sad mood, I am bothered more by 0 1 2 3 4 aggressive thoughts. 22. When I feel down, I more easily become cynical 0 1 2 3 4 (blunt) or sarcastic. 23. When I feel down. I feel more like escaping 0 1 2 3 4 everything. 24. When in a sad mood, I feel more like myself. 0 1 2 3 4 25. When I feel down, I more often neglect things. 0 1 2 3 4 26. When I feel sad, I do more risky things. 0 1 2 3 4 27. When I am sad, I have more problems 0 1 2 3 4 concentrating. 28. When in a low mood, I am nicer than usual. 0 1 2 3 4 29. When I feel down, I lose my temper more easily. 0 1 2 3 4 30, When I feel sad. I feel more that people would 0 1 2 3 4 be better off if I were dead. 31. When I feel down, I am more inclined to want to 0 1 2 3 4 keep everything under control. 32. When I feel sad, I spend more time thinking 0 1 2 3 4 about the possible causes of my moods. 33. When in a sad mood, I more often think about 0 1 2 3 4 how my life could have been different. 34. When I feel sad, more thoughts of dying or 0 1 2 3 4 harming myself go through my mind. not a bit moder- strongly very at all ately strongly
[0347] Statistical Analysis of LEIDS-R Questionnaire Results
[0348] COMPUTE HOP=MEAN.4(leids5,leids9,leids17,leids30,leids34)*5.
[0349] COMPUTE ACC=MEAN.4(leids4,leids10,leids15,leids24,leids28)*5.
[0350] COMPUTE AGG=MEAN.5(leids7,leids18,leids21,leids22,leids26,leids29)*6.
[0351] COMPUTE CON=MN.5(leids3,leids8,leids12,leids16,leids19,leids31)*6.
[0352] COMPUTE RAV=MEAN.5(leids1, leids2,leids6,leids11,leids14,leids23)*6.
[0353] COMPUTE RUM=MEAN.5(leids13,leids20,leids25,leids27,leids32,leids33)*6.
[0354] EXECUTE.
[0355] COMPUTE LEIDSR=HOP+ACC+AGG+CON+RAV+RUM EXECUTE.
[0356] In this syntax, subscales are computed with the MEAN function and multiplied by the number of items.
[0357] Of course, this is the same as summing the itemsif there are no missing values.
[0358] This syntax allows one missing item per subscale (the missing value is replaced with the average item score for that particular subscale).
[0359] Labels:
[0360] HOP=hopelessness/suicidality
[0361] ACC=acceptance/coping
[0362] AGG=aggression
[0363] CON=control/perfectionism
[0364] HAV=risk aversion
[0365] RUM=rumination
EXAMPLE 3: HUMAN MINERALOCORTICOID RECEPTOR (MR) GENE HAPLOTYPES MODULATE MR EXPRESSION AND TRANSACTIVATION: IMPLICATION FOR THE STRESS RESPONSE
SUMMARY
[0366] Stress causes activation of the hypothalamic-pituitary-adrenal (HPA) axis, resulting in secretion of corticosteroids which facilitate behavioural adaptation. These effects exerted by corticosteroids are mediated by two brain corticosteroid receptor types, the mineralocorticoid (MR) receptor, with a high affinity already occupied under basal conditions and the glucocorticoid receptor (GR), with a low affinity only activated during stress.
[0367] Here, we studied MR gene haplotypes constituted by the two single nucleotide polymorphisms MR-2G/C (rs2070951) and MRI180V (rs5522). In vitro the haplotypes showed differences in cortisol-induced gene transcription and protein expression, while the structural variant MRU 80V did not affect ligand binding.
[0368] Moreover, in a well characterized cohort of 166 school teachers these haplotypes have been associated with perceived chronic stress (Trier Inventory for the Assessment of Chronic Stress, TICS) and, in a subgroup of 47 subjects, with ACTH, Cortisol and heart rate responses to acute psychosocial stress (Trier Social Stress Test, TSST). MR haplotypes were significantly associated with the TICS scales excessive demands at work and social overload. Subjects homozygous for haplotype MR-2 C/MRI180, which in vitro showed highest expression and transactivational activity, displayed the highest salivary Cortisol (p<0.01), plasma Cortisol (p<0.03), plasma ACTH (p<0.01) and heartrate (p<0.01) responses.
[0369] It is concluded that the investigated MR haplotypes modulate cortisol-induced gene transcription in vitro. Moreover, these haplotypes may contribute to individual differences in perceived chronic stress as well as neuroendocrine and cardiovascular stress responses.
Introduction
[0370] Cortisol has profound effects in the brain, underlying behavioural adaptation to stress and feedback regulation of the hypothalamic-pituitary-adrenal (HPA) axis. These actions exerted by Cortisol are mediated by a high affinity brain corticosteroid receptor, the mineralocorticoid receptor (MR) and a lower affinity glucocorticoid receptor (GR). The GR is widely expressed while the MR predominantly occurs in limbic brain areas including the hippocampus. Animal studies have shown that MR occupation is maintained at basal pulsatile Cortisol levels, while the GR becomes only activated with rising Cortisol levels in response to stress and at the peaks of the corticosterone pulses (Conway-Campbell et al., 2007; Lightman et al., 2008; Sarabdjitsingh et al., 2009). The MR and GR operate as transcription factors in the regulation of gene transcription, but recently these receptors were also found to mediate fast membrane-mediated actions (Di et al., 2003; Karst et al., 2005). Through the MR Cortisol regulates basal HPA pulsatility (Atkinson et al., 2008) and the threshold or onset of the HPA axis response to stress (Arvat et al., 2001; Dodt et al., 1993; Ratka et al., 1989; Wellhoener et al., 2004), while the GR facilitates the suppression of stress-induced HPA activation and promotes adaptation.
[0371] Two functional single nucleotide polymorphisms (SNPs) in the MR have been previously identified, namely MR-2G/C (rs2070951) located 2 nucleotides before the translation startsite and MRU 80V (rs5522), a SNP resulting in an amino acid change in the N-terminal domain of the protein. Both SNPs affect transactivation in vitro (DeRijk et al., 2006; van Leeuwen et al., 2010). MR-2G/C is located outside the coding region of the MR but inside the Kozac translation regulatory sequence, and is expected to influence brain function via changes in MR protein expression. The structural variant MRU 80V was previously found to be associated with HPA axis and autonomic nervous system reactivity (DeRijk et al., 2006). This effect exerted by MRU 80V may occur through differences in ligand binding, translocation to the nucleus, dimerization or recruitment of coactivators. Furthermore, these two SNPs in the MR are in linkage disequilibrium. (DeRijk et al., 2008). The in vitro and in vivo effects of these haplotypes are currently not known.
[0372] The main objective of the current study was to measure transactivation, ligand binding and protein expression of MRU 80V, MR-2G/C and the resulting haplotypes. In addition, we sought to evaluate the association between these haplotypes and valid (endo)phenotypes for psychobiological stress regulation in a cohort that is independent of the samples that have previously been studied by our group (DeRijk et al., 2006; van Leeuwen et al., 2010). Therefore, we performed a genetic association analysis in a cohort of school teachers that has been characterized with the Trier Inventory for the Assessment of Chronic Stress (TICS) and the Trier Social Stress Test (TSST).
Materials and Methods
Functional Characterization In Vitro
Construction of the hMR Plasmids
[0373] The expression plasmid containing human MR was obtained from Dr. R. Evans (gene expression laboratory and HHMI, The Salk Institute for Biological Studies, La Jolla, Ca) and is described elsewhere (Arriza et al., 1987).
[0374] MR-2G/C (rs2070951) and MRU 80V (rs5522) sites were mutated from G to C and from A to G, respectively using primers 5-GGCCGAGGCAGCGATGGAGACCAAAG-3 (SEQ ID No: 10) and 5-CGCTGCCTCGGCCCTTTGGTCTCCAT-3 (SEQ ID No: 11) and primers 5-GGCGTCATGCGCGCCGTTGTTAAAAGCCCCTAT-3 (SEQ ID No: 12) and 5-ATAGGGCTTTTAACAACGGCGCGCATGACGCC-3 (SEQ ID No: 13) and the Quick Change Site Directed Mutagenesis kit (Stratagene, La Jolla, Calif.), according to the manufacturer's protocol. After mutagenesis the hMR insert of the plasmid was sequenced to assure absence of other mutations.
Transactivation Assay
[0375] Cos-1 cells (African green monkey kidney cells) were cultured in DMEM high glucose supplemented with 10% FCS (Gibco, Paisley, UK). Cells were seeded in 24-well plates (Greiner Bio-One, Alphen a/d Rijn, The Netherlands) at 310.sup.4 cells/well in DMEM supplemented with charcoal-stripped serum. The cells were transfected the next day using SuperFect (Qiagen, Venlo, The Netherlands). hMR plasmids and the reporter pasmid TAT3-Luc (tyrosine amino transferase triple hormone response element) were used at 100 ng/well. The control plasmid pCMV-R (Promega, Leiden, The Netherlands) coding for Renilla luciferase controlled by cytomegalovirus (CMV) promoter was used (10 ng/well). One day after transfection, the cells were treated with Cortisol (Sigma-Aldrich, Zwijndrecht, the Netherlands) in concentrations ranging from 0 to 10.sup.8 M. After 24 h of incubation the cells were harvested in passive lyses buffer (Promega) and firefly and Renilla luciferase activity was determined using a dual label reporter assay (Promega) and a luminometer (CENTRO XS3 LB960, Berthold, Bad Wildbad, Germany). Three separate experiments were performed and all three experiments were performed in triplicate.
Western Blot
[0376] For western blot Cos-1 cells were seeded in 6-well plates (Greiner Bio-One, Alphen a/d Rijn, The Netherlands) at 210.sup.5 cells/well in DMEM supplemented with charcoal-stripped serum. The cells were transfected the next day using Trans-it Cos transfection reagent (Mims, Madison, USA). Plasmids containing one of the hMR variants or no hMR (control) were used at 2 g/well. Cells were harvested 48 hours after transfection. The primary antibody MR 1D5 (a generous gift by Gomez-Sanchez, Division of endocrinology, University of Mississippi, Jackson, Miss.) was diluted 1:1000 in 0.5% milk powder in Tris buffered saline and Tween 20 (TBST) and incubated for 1 h at room temperature (RT). The secondary antibody goat anti-mouse IgG HRP was used in 1:5000 dilutions in TBST with 0.5% milk for 1 h at RT. Tubulin was used as a control for the amount of cells and the monoclonal anti -Tubulin was used at a 1:1000 dilution (T6557; Sigma-Aldrich, Zwijndrecht, the Netherlands). The ECL detection system (GE healthcare, Diegem, Belgium) was used for detection. The differences in intensity of the MR bands were quantified with Image J (ImageJ, U. S. National Institutes of Health, Bethesda, Md., USA, http://rsb.info.nih.gov/ij/). Three separate experiments were performed.
Ligand Binding Assay
[0377] Cos-1 cells were seeded in 20 cm plates (Greiner Bio-One, Alphen a/d Rijn, The Netherlands) at 210.sup.6 cells/plate in DMEM supplemented with 5% charcoal-stripped serum. Cells were transfected the next day using Minis Transit-COS reagent according to the manufacturer's protocol (Sopachem, Ochten, The Netherlands) and hMR plasmids were used at 30 g/plate. After 24 hours medium was replaced with serum free DMEM and after another 24 hours cells were pelleted. All further steps are carried out at 0 C. Cells were resuspended in 3.5 ml buffer (5 mM Tris-HCl (pH 7.4), 1 mM EDTA, 1 mM B-Mercaptoethanol, 10 mM Na-Molybdate, 5% glycerol) per plate and 315 seconds homogenised using an electric homogenizer (Pro200, Pro scientific, Oxford, Conn., USA). The homogenate was centrifuged (100.000g, 2 C.) to obtain cytosol.
[0378] 200 l cytosol was incubated with [.sup.3H]Cortisol (70 Ci/mmol, Amersham, Buckinghamshire, UK) to asses total binding or [.sup.3H]Cortisol and a 500 fold excess of dexamethasone (Sigma-Aldrich, Zwijndrecht, the Netherlands) to asses non-specific binding. [.sup.3H]Cortisol was used at 0.5 nM, 1 nM, 1.5 nM, 2.5 nM, 3.5 nM, 5 nM. After vortexing and 3 hours incubation on ice bound and free [.sup.3H]Cortisol fractions were separated by Sephadex LH-20 as described previously (de Kloet et al., 1975). Fractions containing the receptor bound radioligand were collected, vortexed with 3 ml Ultima Gold scintillation fluid (Perkin Elmer, Waltham, Mass., USA) and radioactivity was measured in a liquid scintillation analyzer (1900CA Packard, Perkin Elmer). Three separate experiments were performed and all three experiments were performed in triplicate.
Statistical Analysis
[0379] The in vitro experiments were analyzed using GraphPad prism 4 (GraphPad software Inc, San Diego, Calif.). In the transactivation assays firefly/renilla luciferase ratios were normalized against the highest signal and background expression was subtracted. MR protein expression measured by western blot was normalized against -Tubulin. The differences between the four hMR variants were analyzed with one and two-way
[0380] ANOVAs with Bonferroni posttests. In the radioligand binding assay one-binding-site curve fitting was used to determine the dissociation constant (Kd) and maximal binding (Bmax). The specific MR Cortisol binding was obtained by subtracting the non-specific binding from the total binding. The difference in Kd and Bmax between MRU 80 and MR180V was tested with a t-test. In vitro results are shown as the meanSD.
Genetic Association Study
Recruitment
[0381] We approached teachers of all major school types in the region of Trier (Germany) and Luxembourg by means of personal visits in local schools and by newspaper announcements. Teachers were entered into the study if they reported to be free of psychiatric disorders, diabetes, pregnancy, and corticosteroid or psychotropic medication. Written informed consent was obtained from all participants and the protocol was approved by the ethics committee of the University of Trier and the Rheinland-Pfalz State Medical Association.
DNA Extraction and Genotyping
[0382] DNA was extracted from 10 ml peripheral venous blood following a standard method (Miller et al., 1988). Subjects were genotyped for the MR-2G/C and MRI180V SNPs by both matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS), using the Sequenom MassARRAYtm methodology (Sequenom Inc., San Diego, Calif., USA) and by TaqMan pre-designed SNP genotyping assays, assay ID C12007869_20 and C1594392_10, respectively, in combination with TaqMan universal PGR master mix (Applied Biosystems, Nieuwekerk a/d IJssel, The Netherlands). Reaction components and amplification parameters were based on the manufacturer's instructions. Genotyping the samples with two different genotyping methods decreases method specific genotyping errors.
Assessment of Perceived Chronic Stress
[0383] Perceived chronic stress was measured using the short version of the Trier Inventory for the Assessment of Chronic Stress (TICS-S) (Schulz and Schlotz, 1999). The TICS covers nine dimensions of chronic stress, namely work overload, social overload, excessive demands at work, lack of social recognition, work discontent, social tension, performance pressure, social isolation and chronic worrying. For each item, the frequency of the experience in the last year had to be indicated on a 5-point rating scale, ranging from never to very often.
Psychosocial Stress Protocol
[0384] The Trier Social Stress Test (TSST) consists of a three minutes preparation phase followed by a five minutes free speech phase (job interview) and a five minutes mental arithmetic task in front of a panel and a camera (for a detailed description of this protocol see (Kudielka et al., 2007b; Kudielka et al., 2007a). Test sessions were only run in the afternoon, starting between 15 h and 16 h. Participants were instructed to refrain from physical exercise, a heavy lunch and alcoholic beverages on test days. Premenopausal women not taking oral contraceptives were invited during the luteal phase of the menstrual cycle. The menstrual phase was estimated on the basis of the first day of last menses and the subject's usual cycle length. Only women with a regular cycle between 28 and 35 days were included and the luteal phase was defined as the last 14 days of the cycle. In the laboratory, at first an intravenous catheter was inserted in the antecubital vein of the dominant arm for later blood draws and subjects were instrumented with heart rate monitors. Heart rate was measured at 5 second intervals using a transmitter belt with a wrist receiver (Polar Sport Tester; Polar Electro, Buttelborn, Germany). After a rest period of 40 min following canula insertion and 10 min before the start of the stressor, subjects were asked to stand up. After TSST exposure subjects remained in an upright position for another 10 minutes.
Blood and Saliva Sampling
[0385] Blood samples for the assessment of ACTH and total plasma Cortisol were collected in EDTA containing monovettes (Sarstedt, Numbrecht, Germany) 1 min before as well as 1, 10, 20, 30 and 90 min after cessation of the TSST. In parallel, subjects obtained native saliva in 2 ml reaction tubes (Sarstedt, Numbrecht, Germany) for later assessment of salivary Cortisol. Additional saliva samples were obtained at 45 and 60 min after cessation of the TSST.
Biochemical Analysis
[0386] Salivary Cortisol was measured by an in-house DELFIA (intra- and inter-assay variation 11.5%). Blood samples were instantaneously stored on ice and centrifuged at 4 C. for 15 min at 2000 g and pipetted into aliquots. Aliquots for the analysis of plasma Cortisol as well as saliva samples were stored at 20 C. and aliquots for the analysis of ACTH were stored at 80 C. until assayed. ACTH and total plasma Cortisol were measured by ELISA assays (plasma Cortisol: IBL Hamburg, Germany, intra- and inter-assay variation6.9%; ACTH: Biomerica Newport Beach, USA, intra- and inter-assay variation6.0%).
Statistical Analysis
[0387] Haploview (Barrett et al., 2005) was used to calculate Hardy Weinberg equilibrium (HWE) and linkage disequilibrium among the two MR SNPs (estimated with D and r.sup.2). Haplotypes were estimated and assigned to each individual using SNPHAP (http://www-gene.cimr.cam.ac.uk/clayton/software/). In order to analyze the association between haplotypes and perceived chronic stress levels, we used the haplotype trend regression (HTR) approach as outlined by Zaykin et al (2002). Assuming additive effects of the haplotypes on the trait, the HTR approach tests for the contribution of individual haplotypes rather than haplotype pairs. We applied a permutational approach to obtain empirical p-values utilizing the HTR function of the R-package gap, version 1.0-17 (R 2.7.2; http://www.R-project.org) with 10.000 simulations. HTR procedures provide a global p-value as well as p-values indicating the association between the trait and each haplotype. A two-stage strategy was applied to test for possible associations between haplotypes and neuroendocrine as well as autonomic TSST responses. First, the HTR approach was used as global significance test. Therefore, area under the response curve (AUC) measures were computed for salivary Cortisol, plasma Cortisol, ACTH and heart rate responses and entered into the HTR models. Secondly, post hoc tests were performed to further inspect the detected effects. To use the full information of the repeated measures design this was done with general linear models (GLMs) to assess the repeated measures effect time, the between-subjects effect haplotype as well as the interaction time x haplotype. In order to control for possible influences of gender, sex was included as additional predictor. Effect sizes were calculated for significant results by partial eta squared (.sup.2). Greenhouse-Geisser corrections were applied where appropriate, and only adjusted results are reported. GLM procedures were performed using the PASW statistical software package (Version 18.0). Unless otherwise stated, results are expressed as meanstandard error of the mean (S.E.M.). While Cortisol, ACTH and heart rate values were log-transformed before statistical analyses to yield unskewed outcome variables, figures show untransformed means in order to provide a more naturalistic impression of endocrine levels.
Results
Functional Characterization In Vitro
[0388] All four MR haplotypes were tested in vitro. According to the observed frequency in the population (DeRijk et al., 2008) the haplotypes are referred to as Hap 1 (GA), constituted by MR-2 G and MRI180V A, Hap 2 (CA), constituted by MR-2 C and MRI180V A, Hap 3 (CG), constituted by MR-2 C and MRU 80V G and the in vivo rarely observed Hap 4 (GG), constituted by MR-2 G and MRU 80V G.
Transactivation Assay
[0389] The four different MR haplotypes showed differential cortisol-induced luciferase transcription from a triple tyrosine amino transferase (TAT-3) promotor (F.sub.3.26=42.7; p<0.0001; .sup.2=0.06;
Western Blot
[0390] The MR haplotypes influenced MR protein expression in transfected COS-1 cells (F.sub.34=7.07; p=0.03; .sup.2=0.80,
Ligand Binding
[0391] Cortisol binding to the MR (Kd and Bmax) was not influenced by MRU 80V. The Kds of MRI180 and MR180V were not significantly different, being 0.860.20 and 0.930.16 nM, respectively. There was also no significant difference in Bmax, showing values of 6539499 and 7112371 binding sites/cell for the MRI180 and MR180V, respectively. As there was no significant difference between the three separate experiments, data of the three experiments were pooled for analysis.
Genetic Association Study
Genotypes and Haplotypes
[0392] The two employed genotyping methods yielded identical results. The distribution of both SNPs, MRU 80V and MR-2G/C, did not deviate significantly from Hardy Weinberg equilibrium (HWE). The estimated linkage between MRU 80V and MR-2G/C was D=1 (conf bounds 0.63-1) and r.sup.2=0.093. As expected, in this sample Hap 1 (GA) showed with 48.8% the highest frequency followed by Hap 2 (CA) with a frequency of 41.9% and Hap 3 (CG) with a frequency of 9.3%. Consistent with previous studies Hap 4 (GG) was not observed in this cohort (see
Final Sample
[0393] The sample for the present analysis consisted of 166 healthy subjects (55 males and 111 females). Participants were between 23 to 63 years of age (mean age: 45.589.8) and had a mean body mass index (BMI) of 25.94.7. Fifteen of the subjects reported to be smokers. Questionnaire data from 163 to 166 participants (due to a different number of missing values across scales) could be analyzed.
Perceived Chronic Stress
[0394] HTR models revealed associations between the MR haplotype structure and perceived chronic stress assessed with the TICS in respect to four subscales, namely social overload, excessive demands at work, social tension, and social isolation (Table 4). While global p-values were significant for social overload (F=3.21, p=0.042) and excessive demands at work (F=3.65, p=0.029), a trend was detected for social tension (F=2.39, p=0.095) and social isolation (F=2.63, p=0.076). Inspection of haplotype specific p-values for these four scales revealed that carriers of Hap 3 (CG) reported significantly more chronic stress in terms of excessive demands at work (F=7.27; p=0.008) and social overload (F=4.17; p=0.045) than non-carriers. Furthermore, individuals with two copies of Hap 1 (GA) reported more chronic stress in terms of social isolation (F=4.93; p=0.029) and social tension (F=4.80; p=0.032) than individuals with one copy or zero copies of Hap 1. The respective social isolation effect for Hap 2 (CA) was also significant (F=4.95; p=0.027), while the respective social tension effect (F=3.44; p=0.071) as well as the social overload effect (F=3.75; p=0.056) showed a trend, with individuals with zero copies having higher scores than individuals with one or two copies of Hap 2.
TABLE-US-00005 TABLE 4 Association between subscales of the Trier Inventory for the assessment of chronic stress and MR haplotypes. Table shows asymptotic F- and empirical p-values; *p < .05, .sup.+p < .10. Haptotype MR 0 Copies 1 Copy 2 Copies Global Test Specific Test Haplotypes Mean (Std) p [F] p [F] Work Overload n.s. GA 2.22 (0.91) 2.29 (0.81) 2.41 (0.98) CA 2.48 (0.94) 2.21 (0.82) 2.19 (0.80) CG 2.26 (0.88) 2.51 (0.88) Social Overload .042 [3.21]* GA 1.93 (0.91) 1.91 (0.04) 2.10 (0.87) n.s. CA 2.18 (0.96) 1.84 (0.85) 1.85 (0.90) .056 [3.75].sup.+ CG 1.90 (0.88) 2.28 (0.91) .045 [4.17]* Excessive .029 [3.65].sup.+ Demands at Work GA 1.35 (0.77) 1.19 (0.79) 1.29 (0.80) n.s. CA 1.37 (0.86) 1.16 (0.75) 1.25 (0.73) n.s. CG 1.19 (0.01) 1.62 (0.79) .008 (7.27)* Lack of Social n.s. Recognition GA 1.60 (0.99) 1.63 (1.03) 1.64 (1.10) CA 1.73 (1.12) 1.66 (1.02) 1.61 (0.95) CG 1.71 (1.02) 1.50 (1.13) Work Discontent n.s. GA 0.95 (0.00) 0.99 (0.77) 1.12 (0.76) CA 1.06 (0.72) 1.04 (0.86) 0.87 (0.82) CG 1.01 (0.80) 1.00 (0.83) Social Tension .095 [2.39].sup.+ GA 1.13 (0.72) 1.17 (0.72) 1.45 (0.78) .032 [4.80]* CA 1.44 (0.77) 1.10 (0.72) 1.21 (0.70) .071 [3.44]* CG 1.26 (0.74) 1.16 (0.79) n.s. Performance n.s. Pressure GA 1.84 (0.70) 1.79 (0.74) 1.89 (0.70) CA 1.91 (0.77) 1.77 (0.68) 1.83 (0.70) CG 1.82 (0 69) 1.91 (0.84) Social Isolation .076 [2.63]* GA 1.28 (0.86) 1.71 (0.95) 1.73 (1.10) .029 [4.93]* CA 1.73 (1.03) 1.64 (0.95) 1.25 (0.87) .027 [4.95]* CG 1.59 (0.99) 1.69 (0.88) n.s. Chronic Worrying n.s. GA 1.89 (1.02) 1.68 (0.84) 1.78 (1.09) CA 1.80 (1.04) 1.74 (0.95) 1.75 (0.83) CG 1.70 (0-02) 2.04 (1.15)
ACTH, Cortisol and Heart Rate Responses to Acute Psychosocial Stress
[0395] A subsample of 54 participants (20 males and 34 females) underwent the stress protocol. Because of the well-known intervening effects of oral contraceptive or sex steroid intake (Kirschbaum et al., 1999; Kudielka et al., 1999) as well as smoking (Rohleder and Kirschbaum, 2006) on acute HPA axis stress responses, we excluded three women taking oral contraceptives or receiving hormonal replacement therapy and two smokers from all further analyses. Two further subjects had missing data in the endocrine measures while six subjects had missing heart rate data due to technical problems. Thus, we included 47 subjects in the final analysis of endocrine and 41 subjects in the analysis of heart rate responses.
[0396] Despite the small size of this subsample MR haplotypes were significantly associated with neuroendocrine and autonomic TSST responses in a rather consistent way. Regarding the global test HTR procedures revealed significant associations between the investigated MR haplotype structure and the area under the curve measures for salivary Cortisol responses (F=6.80; p=0.005), plasma Cortisol responses (F=3.34; p=0.046), and ACTH responses (F=4.03; p=0.029). The respective effect for heart rate responses showed a trend towards statistical significance (F=2.37; p=0.109).
[0397] To use the full information of the repeated measures design, post hoc inspection of associations of specific haplotypes was done with general linear models. For Hap 2 (CA), significant main effects haplotype were observed for ACTH (F.sub.2.41=6.69, p=0.003, .sup.2=0.25), plasma cortisol (F.sub.2.41=5.12, p=0.010, .sup.2=0.20), salivary cortisol (F.sub.2.41=12.11, p=0.000, .sup.2=0.37) as well as heart rate (F.sub.2.35=4.51, p=0.018, .sup.2=0.21). Across all measures, individuals with two copies of Hap 2 showed a stronger response to the stressor than individuals with one copy or zero copies. In addition, significant time x haplotype interactions were found for ACTH (F.sub.3.76, 76.39=4.58, p=0.003, .sup.2=0.18) and salivary cortisol (F.sub.6.89, 141.17=2.57, p=0.017, .sup.2=0.11), while the respective interactions for plasma cortisol and heart rate were not significant (all p>0.14). Mean responses are shown in
[0398] A similar picture emerges for Hap 1 (GA), which is not surprising given that Hap 1 and Hap 2 are largely complimentary. Here, those individuals with zero copies of Hap 1 showed significantly elevated ACTH (main effect F.sub.2.41=7.73, p=0.001, .sup.2=0.27), salivary cortisol (main effect F.sub.2.41=6.67, p=0.003, .sup.2=0.25) and heart rate (main effect F.sub.2 35=4.96, p=0.013, .sup.2=0.22) levels. The effect for plasma Cortisol levels just missed the level of significance (main effect F.sub.2.41=2.90, p=0.066). A significant time x haplotype emerged for ACTH (F.sub.3.61, 74.05=4.68, p=0.003, .sup.2=0.19) and a trend was observed for salivary cortisol (F.sub.3.26, 128.26=1, 91, p=0.072), while the respective interactions for plasma cortisol and heart rate were not significant (all p>0.19,
Discussion
[0399] Here we described neuroendocrine and behavioral consequences of two common functional polymorphisms in the human MR, MRU 80V and MR-2G/C, both in vitro and in vivo. The haplotypes of the two SNPs showed differences in cortisol-induced transcription of the reporter gene. From protein analysis of the haplotypes it can be concluded that MR-2G/C changes protein expression while MRI180V did not have this effect. Furthermore, MRI180V did not affect ligand binding. Our data suggest that the haplotypes are associated with stress-induced HPA axis and autonomic responses following a psychosocial stress test. Moreover, the haplotypes might be associated with several aspects of perceived chronic stress.
[0400] Transactivation assays have been performed with the two MR SNPs individually (DeRijk et al., 2006; van Leeuwen et al., 2010). However, the combinations of the two SNPs, as occur in vivo as part of the observed haplotypes, have not been tested so far. Both haplotypes containing MR-2 C had a higher activity as compared to the two haplotypes containing MR-2 G. Moreover, statistical analysis did not reveal an interaction effect between the -2G/C and the MRI180V.
[0401] MRI180V produces an amino acid change in the N-terminal domain, which is involved in recruiting co-regulators that selectively modulate transcriptional activity of the MR. As shown in the current study, this effect was not mediated by differences in Cortisol binding characteristics, since no differences in maximal binding capacity (Bmax) or dissociation constants (Kd) were observed between MRU 80 and MR180V. This suggests that other factors such as differences in translocation to the nucleus, dimerization of the MR or binding of co-regulators might be responsible for the observed differences in transactivation.
[0402] In contrast to the MRI180V, the MR-2 G/C is not changing the primary structure of the receptor and is therefore less likely to have an effect on MR protein characteristics. In this study we showed that both haplotypes containing MR-2 C had a higher MR protein expression as compared to the two haplotypes containing MR-2 G while the MRI180V did not influence the protein expression. This finding explains the higher transactivational capacity of the two haplotypes containing MR-2 C, as occurring in haplotypes 2 and 3. In a supplementary part of the present study we investigated the association between these MR gene variants and subjectively perceived chronic stress and neuroendocrine as well as autonomic responses to acute experimental psychosocial stress. We selected a small but well characterized sample of healthy school teachers, since the teaching profession has been repeatedly described as a potentially stressful occupation (Guglielmi and Tatrow, 1998), which is reflected in high rates of early retirement among German school teachers (Weber, 2004). This cohort is independent of the samples in which the previously reported associations between MR gene polymorphisms and HPA axis regulation have been observed (DeRijk et al., 2006; van Leeuwen et al., 2010). This cohort has a rather modest sample size and this holds in particular for the subsample that was exposed to the TSST. However, given this limitation, the observed associations between MR gene haplotypes and biological stress responses have been remarkably consistent across the different indices.
[0403] Individuals carrying two copies of haplotype 2 (CA) showed higher salivary cortisol, plasma cortisol, ACTH as well as heart rate responses to acute psychosocial stress, compared to individuals with only one or zero copies of this haplotype. Despite the small sample, the global effect for salivary Cortisol responses did survive bonferroni correction for multiple comparisons (corrected for four HTR procedures) and some of the GLM p-values are remarkably small. The distinct mean ACTH and Cortisol response differences shown in
[0404] As a consequence of the sample size it was not possible to compute a separate analysis for males and females. We did, however, control for sex effects statistically, we did only include females who did not take oral contraceptives and premenopausal females were tested in the luteal phase of the menstrual cycle.
[0405] The association between MR gene haplotypes and perceived chronic stress could be investigated in a larger, but still modest sample of 166 subjects. Without correction for multiple testing haplotype 3 (CG) carriage was significantly related to higher levels of excessive demands at work and social overload. Haplotype 1 (GA) was significantly related to higher social isolation and social tension scores. Consistently, haplotype 2 (CA) was also significantly related to social isolation scores andon a trend levelto the subscales social overload and social tension.
[0406] Combining the neuroendocrine and perceived chronic stress data, haplotype 2 appears to be associated with higher neuroendocrine stress-responses and better stress handling. A previous study showed that the MR-2 C variant associates with lower basal non-stress levels of Cortisol in an elderly population (Kuningas et al., 2007). This suggests that a more reactive HPA axis with lower basal levels is beneficial for coping with stressors, as has been proposed (de Kloet et al., 2007). Moreover, the in vitro data show that haplotype 2 increases MR-expression, again adding to the notion that higher MR-expression is beneficial. This is further substantiated by animal research showing that increased MR-expression in the forebrain of mice results in less anxiety-like behavior (Rozeboom et al., 2007). With respect to the HPA axis response, the MR is involved in tonic inhibition of Cortisol/corticosterone levels. Furthermore, during the ageing process, a loss of MR-expression in the brain is observed which coincides with less sensitivity towards ACTH in the Brown Norway rat (Van Eekelen et al., 1992). Also in MR forebrain knock out mice, less adaptation of the HPA axis response to stress is observed (Brinks et al., 2009). This indicates that higher MR-expression in the brain leads to a more dynamic HPA axis response with lower basal non-stress levels.
[0407] The precise mechanism how the putative increased MR-expression leads to a more reactive HPA axis responses and resilient behavior to stressors is unknown. MR-expression is essential for neuronal protection and stability of neuronal circuits (de Kloet et al., 2007; Lai et al., 2009). The recent discovery of a MR located in the membrane, in addition to the nuclear MR, has further implications (Karst et al., 2005). This low affinity membrane version of the MR becomes activated during stress-levels of Cortisol and increases excitatory glutaminergic transmission while decreasing post-synaptic after-hyperpolarization (Joels et al., 2008). This rapid excitatory MR-mediated effect may very well underlie the non-genomic actions exerted by Cortisol on neuroendocrine, emotional and cognitive processes (Brinks et al., 2009). Therefore, it will be a challenge for future research to dissociate during a psychosocial stressor the genomic and non-genomic effects mediated by the MR on processing of stressful information resulting in HPA axis reactivity and behavior. The MR haplotypes identified in this study may be very helpful in this respect.
[0408] In conclusion, in vitro assays demonstrate large differences in transactivation between the haplotypes. The molecular mechanism of these differences is only partly elucidated. In vivo, individuals with two copies of MR haplotype 2 (CA) had the most dynamic response to an acute psychosocial stressor, both the HPA axis and autonomic responses were higher in these individuals. Furthermore, our data suggest involvement of MR gene variants in perceived chronic stress, in which the haplotype 2 may be beneficial for coping with stressors. All together, it is concluded that these MR haplotypes may contribute to individual differences in the neuroendocrine response during coping with psychological stress.
REFERENCES FOR EXAMPLE 3
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A., Dykes, D. D., Polesky, H. F., 1988. A Simple Salting Out Procedure for Extracting Dna from Human Nucleated Cells. Nucleic Acids Research 16, 1215-1215. [0435] Ratka, A., Sutanto, W., Bloemers, M., de Kloet, E. R., 1989. On the role of brain mineralocorticoid (type I) and glucocorticoid (type II) receptors in neuroendocrine regulation. Neuroendocrinology 50, 117-123. [0436] Rohleder, N., Kirschbaum, C, 2006. The hypothalamic-pituitary-adrenal (HPA) axis in habitual smokers. Int. J. Psychophysiol. 59, 236-243. [0437] Rozeboom, A. M., Akil, H., Seasholtz, A. F., 2007. Mineralocorticoid receptor overexpression in forebrain decreases anxiety-like behavior and alters the stress response in mice. Proc. Natl. Acad. Sci. USA 104, 4688-4693. [0438] Sarabdjitsingh, R. A., Meijer, O. C., Schaaf, M. J., de Kloet, E. R., 2009. Subregion-specific differences in translocation patterns of mineralocorticoid and glucocorticoid receptors in rat hippocampus. Brain Res. 1249, 43-53. [0439] Schulz, P., Schlotz, W., 1999. The Trier Inventory for the Assessment of Chronic Stress (TICS): Scale construction, statistical testing, and validation of the scale work overload. Diagnostica 45, 8-19. [0440] Van Eekelen, J. A., Rots, N. Y., Sutanto, W., de Kloet, E. R., 1992. The effect of aging on stress responsiveness and central corticosteroid receptors in the brown Norway rat. Neurobiol.Aging 13, 159-170. [0441] van Leeuwen, N., Kumsta, R., Entringer, S., de Kloet, E. R., Zitman, F. G., DeRijk, R. H., Wiist, S., 2010. Functional mineralocorticoid receptor (MR) gene variation influences the Cortisol awakening response after dexamethasone. Psychoneuroendocrinology 35, 339-349. [0442] Weber, A., 2004. Krankheitsbedingte Fruhpensionierungen von Lehrkraften, Early retirement of teachers as a result of health problems. Psychosomatische Erkrankungen bei Lehrerinnen and Lehrem Hillert and E. Schmitz, Editors, 22-38. [0443] Wellhoener, P., Born, J., Fehm, H. L, Dodt, C, 2004. Elevated resting and exercise-induced Cortisol levels after mineralocorticoid receptor blockade with canrenoate in healthy humans. J. Clin. Endocrinol. Metab 89, 5048-5052. [0444] Zaykin, D. V., Westfall, P. H., Young, S. S., Karnoub, M. A., Wagner, M. J., Ehm, M. G., 2002. Testing association of statistically inferred haplotypes with discrete and continuous traits in samples of unrelated individuals. Hum.Hered. 53, 79-91.
EXAMPLE 4: COMMON FUNCTIONAL MINERALOCORTICOID RECEPTOR POLYMORPHISMS MODULATE THE CORTISOL AWAKENING RESPONSE: INTERACTION WITH SSRIS
Summary
Background:
[0445] Cortisol controls the activity of the hypothalamic-pituitary-adrenal (HPA) axis during stress and during the circadian cycle through central mineralocorticoid (MR) and glucocorticoid receptors (GR). Changes in MR and GR functioning, therefore, may affect HPA axis activity. In this study we examined the effect of common functional MR gene variants on the Cortisol awakening response (CAR), which is often disturbed in stress-related disorders like depression.
[0446] Methods: Common functional MR single nucleotide polymorphisms (SNPs; MR-2G/C and 1180V) and haplotypes were tested for association with variability in the CAR in a large cohort (Netherlands Study of Depression and Anxiety, NESDA) of patients diagnosed with a lifetime major depressive disorder (MDD). Saliva cortisol measurements and genotypes could be obtained from a total of 1026 individuals, including 324 males and 702 females.
[0447] Results: The MR-2C/C genotype was associated with an attenuated CAR increase in women (p=0.03) but not in men (p=0.18; p=0.01 for SNP-by-sex interaction). The MR 1180V SNP had no significant effect on the CAR. Additional analysis revealed that effect of the -2G/C SNP on the CAR was due to an interaction with frequent use of selective serotonin reuptake inhibitors (SSRIs). Only in subjects using SSRIs (men and women) a prolonged CAR was observed in -2G/G carriers, while the CAR was completely flattened in women with the -2 C/C genotype (p<0.05). The results were independent of multiple potential confounders and had an effect size of r=0.14-0.27.
Conclusions:
[0448] This study shows that the MR-2G/C SNP modulated the CAR only in the MDD patients using SSRIs, with a clear allele-dose effect only in women. This suggests that effect of SSRIs on Cortisol regulation depends in part on MR genotype with possible implications for future treatment selection.
Introduction
[0449] Optimal regulation of cortisol levels by the hypothalamic-pituitary-adrenal (HPA) axis is crucial for physical and psychological responsiveness to everyday challenges and health (De Kloet et al., 1998). Hence, disturbances in activity of the HPA axis may develop into various disorders, including major depressive disorder (MDD) (Nestler et al., 2002), while normalization of HPA axis parameters preceding clinical relief is often observed (Barden et al., 1995; Zobel et al., 2004). These changes in HPA axis activity depend on the feedback action of Cortisol, which is mediated by two brain corticosteroid receptors, i.e. the high affinity mineralocorticoid receptor (MR) and the low affinity glucocorticoid receptor (GR).
[0450] Due to its low affinity the GR only becomes activated when cortisol levels are high, as occurs during stress and at the peaks of the ultradian rhythm during the circadian cycle (de Kloet and Sarabdjitsingh, 2008). Through the GR, stress-induced cortisol levels are suppressed. The MR has a high affinity for cortisol and therefore remains already highly occupied throughout the day under non-stress, basal conditions. During the day the MR exerts a tonic inhibition on circulating cortisol levels (De Kloet et al., 1998). Administration of a MR antagonist to both animals and humans increases diurnal plasma corticosteroid levels by enhancing the amplitude of the corticosteroid pulses (Heuser et al., 2000; Atkinson et al., 2008). In addition, the MR potentiates the initial neuroendocrine stress reaction. In response to stress the MR and GR mediate in complementary fashion the action of cortisol from the initial stress reaction to the management of later adaptive phases. Recently, besides a cytoplasmic high affinity MR also a low affinity membrane MR was identified, however, the specific roles of these distinctly localized receptors in HPA axis activity still has to be assessed (Joels et al., 2008). What the specific roles of the MR and GR are in regulating the circadian peak is still unclear. Because of its high affinity it is likely that the MR is implicated. Moreover, the question remains whether cortisol levels at the circadian peak are high enough to actually bind to the GR. The present study focuses on the MR.
[0451] By examining the effect of common functional MR gene variants, we showed that MR genetic variability confers inter-individual differences in neuroendocrine regulation under both basal non-stress conditions and after stress (DeRijk et al., 2006; Kuningas et al., 2007; van Leeuwen et al., 2009). For the MR gene, two functional SNPs (MR 1180V and -2G/C) have been described so far, both affecting MR expression and/or gene transactivation in cell lines. The V-allele of the MR 1180V SNP results in a higher Cortisol response to the Trier Social Stress Test (TSST) (DeRijk et al., 2006), which was accompanied by an increased heart rate response. In a different study, the C-allele of the MR-2G/C SNP was found to be associated with lower plasma Cortisol levels in the morning among healthy elderly (Kuningas et al., 2007). These data indicate that both basal non-stress and stress-induced HPA regulation may vary in part due to differences in MR activity. As yet, it is still unclear to what extent the MR (and GR) influences the Cortisol awakening response (CAR). In a recent study, both known MR SNPs were found to affect the CAR in healthy individuals, although effects were only significant after dexamethasone treatment and were sex dependent (van Leeuwen et al., 2009).
[0452] The CAR consists of a distinct rise in Cortisol levels directly after awakening, which reaches peak levels at 30 min and returns to baseline levels 60 min after awakening (Pruessner et al., 1997; Wust et al., 2000b; Wilhelm et al., 2007). The CAR is considered as a response to awakening, superimposed on the ultradian rhythm during the circadian cycle (Kuehner et al., 2007). Because of its intra-individual stability, the CAR is thought of as a trait measure for HPA axis activity (Pruessner et al., 1997; Wust et al., 2000a) and appears to be influenced in part by genetic factors (Wust et al., 2000a). Sociodemographic, lifestyle and sleep factors, chronic stress and daily hassles all may modulate the CAR (Pruessner et al., 1997; Wust et al., 2000a; Wust et al., 2000b; Buchanan et al., 2004; Hellhammer et al., 2007; Fries et al., 2009; Vreeburg et al., 2009b).
[0453] Major depressive disorder (MDD) is in many cases associated with hyperactivity of the HPA axis (Nestler et al., 2002), including an enhanced CAR often found in both remitted and current depressed patients (Vreeburg et al., 2009a). Normalization of HPA axis reactivity often occurs after treatment with antidepressants (Barden et al., 995; Zobel et al., 2004), while antidepressants themselves were found in animal studies and cell lines to increase the expression of both the MR and/or GR (Seckl and Fink, 1992; Holsboer and Barden, 1996; Bjartmar et al., 2000). Moreover, MR antagonists diminish, while MR agonists enhance the efficacy of a tricyclic antidepressant (TCA) or a selective serotonin reuptake inhibitor (SSRI) respectively (Holsboer, 1999; Otte et al., 2009). Collectively, these data imply an important role for the efficiency of MR signaling in changing HPA axis activity, pathogenesis and with consequences for treatment.
[0454] Here we tested the hypothesis that genetic variants of the MR gene relate to variability in the CAR in lifetime MDD patients. To address this hypothesis, the MR-2G/C and 1180V SNPs were examined for association with the 1-hour Cortisol awakening response in a large cohort of patients with a lifetime diagnosis of MDD (remitted and current). Subsequently, data were stratified for sex to assess sex-dependent effects. Finally, possible interaction effects with MR were tested for stressful life events and frequent use of SSRIs.
Materials and Methods
Study Population
[0455] Data were used from the Netherlands Study of Depression and Anxiety (NESDA), an eight-year longitudinal cohort study on the causes and course of depressive and anxiety disorders in people aged 18-65 years. For the NESDA study, a total of 2981 respondents were recruited from the general population and from primary care and specialized mental health care practices, including 2329 patients with a lifetime depressive and/or anxiety disorder and 652 subjects without a any (lifetime or current) depressive and/or anxiety disorder. Among those subjects a primary clinical diagnosis of psychotic disorder, obsessive-compulsive disorder, bipolar disorder, or severe addiction disorder, and not being fluent in Dutch was excluded. All participants provided written informed consent before inclusion. For details on the NESDA study see (Penninx et al., 2008).
[0456] In the present study patients were selected when they had a lifetime MDD diagnosis (n=1925), as assessed with the DSM-IV Composite International Diagnostic Interview (CIDI) version 2.1. Patients were excluded when they indicated not to be from western European ancestry (n=109), when taking corticosteroids (n=15) or when pregnant or breastfeeding (n=11). Of this subset of 1790 MDD patients, genotypes were available for 1572 individuals, which were assessed earlier as part of a large genome wide association (GWA) study for MDD, the GAIN-MDD study (Sullivan et al., 2009). Saliva Cortisol data were available for 1091 of the 1572 genotyped MDD patients. When comparing this group of 1091 respondents with the subjects for which no genotypes or saliva data were available (n=699), they did not differ in sex. However, they were slightly older (43.612.4 vs. 39.612.2; p<0.001), were more educated (12.23.2 yrs vs. 11.63.2 yrs; p<0.001) and were more often currently depressed (54.3% vs. 45.7%; p<0.01). Finally, an additional group of 65 individuals was excluded because less than 2 valid CAR measurement points were available, leaving a final group of 1026 respondents. Of this final group of 1026 lifetime MDD patients, 555 (54.1%) had a current depression (depression diagnosis in the past 6 months) and 715 (69.7%) had a comorbid lifetime anxiety disorder. The present study combines remitted and current depressed patients as the previous analysis by Vreeburg et al. (Vreeburg et al., 2009a) showed that the CAR was similarly heightened in both groups when compared to the controls.
Sociodemoaraphic. Sampling and Health Factors
[0457] Covariates
[0458] Multiple sociodemographic, sampling and health factors that were previously taken along as (possible) determinants of salivary Cortisol were considered as potential covariates in the present study (Vreeburg et al., 2009a). These include: sex (1=men; 2=women), age (in years), education (years of attained education), time of awakening on sampling day, working on sampling day (0=not working; 1=working), sampling on a weekday vs. weekend day (0=weekend day; 1=weekday), season (0=dark months, that is October through February; 1=months with more daylight, that is March through September), average sleep duration during the last 4 weeks (0=more than 6 h sleep a night; 1=6 h of sleep or less a night), smoking status (0=no current smoker; 1=current smoker) and physical activity (which was assessed using the International Physical Activity Questionnaire and expressed as activity per 1000 MET-minutes, a metabolic equivalent of the number of calories spent per minute, per week).
[0459] Potential Moderators of Genetic Association
[0460] Based on literature, potential interaction effects with the MR gene were tested for sex (Carey et al., 1995; Turner, 1997; Kumsta et al., 2007; van Leeuwen et al., 2009), SSRIs (0=no frequent SSRI use; 1=frequent SSRI use; for at least 1 month) (Seckl and Fink, 1992; Bjartmar et al., 2000; Otte et al., 2009) and stress (Gesing et al., 2001; Bet et al., 2009), i.e. childhood trauma before age 16 (index score on the Netherlands Mental Health Survey and Incidence Study childhood trauma interview (de Graaf et al., 2004) assessing the frequency of emotional neglect, psychological neglect, physical abuse and sexual abuse experienced before the age of 16 years; median split, 0=no or infrequent trauma; 1=frequent trauma) and number of life events in the past year (including illness or death of family member among others; median split, 0=no life events; 1=1+life events). Multiple studies suggest an interaction between the MR gene and SSRIs or TCAs (Seckl and Fink, 1992; Holsboer and Barden, 1996; Holsboer, 1999; Bjartmar et al., 2000; Otte et al., 2009). Due to the low number of cases using TCAs (n=35) or other antidepressants that may modulate MR activity, an interaction effect with the MR could not be tested. Because of potential differential mechanisms we did not initially choose to test for an interaction effect between the MR and all antidepressants (benzodiazepines not included) combined.
Salivary Cortisol Measurements
[0461] At the baseline interview, the patients were instructed to collect saliva samples using salivettes (Sarstedt AG and Co, Ndmbrecht, Germany) at home and on a regular (preferably working) day shortly after the interview. This is a minimally intrusive method to assess the free and active form of Cortisol that has previously been shown to be a reliable measure of free Cortisol in the blood (Kirschbaum and Hellhammer, 1994). Patients were instructed not to eat, drink, smoke or brush their teeth within the 15 min before sampling. The CAR was measured at 4 time points: at awakening (T1) and at 30 (T2), 45 (T3) and 60 (T4) minutes after awakening. Participants were instructed to store the salivettes in their refrigerator until returning them by mail. For details on Cortisol measurements, see (Vreeburg et al., 2009a). In short, Cortisol analysis was performed by competitive electrochemiluminescence immunoassay (E170; Roche, Basel, Switzerland). The functional detection limit was 0.07 g/dL or 2 nMol/L and the intra-assay and inter-assay variability coefficients were below 10%.
Cortisol Awakening Response (CAR)
[0462] For genetic association analyses with the course of the CAR, at least 2 valid CAR measurement points had to be available, that is when collected within a margin of 5 min before or after the protocol time and when values were not more than 2 standard deviations (SDs) from the mean. With linear mixed model (LMM) analyses missing values could be interpolated, which was conducted for 24 subjects with 2 CAR measurement points, and 96 subjects with 3 CAR measurement points. For the remaining 906 subjects all 4 data points were available. Besides studying the course of the CAR with LMM analysis, also the area under the curve (AUC) with respect to the increase (AUCi) and with respect to the ground (AUCg) were used, calculated according to the formula's by (Pruessner et al., 2003). The AUCg is a measure for the total Cortisol secretion during the first hour after awakening, while the AUCi is a measure for Cortisol increase with respect to awakening (TO) and therefore is a measure of the dynamics of the CAR (Clow et al., 2004). For association analyses with the AUC subjects were included when all 4 1-hour awakening Cortisol samples were available (n=906).
Genotyping
[0463] Genotyping of the patients was performed as part of a large GWA study, the GAIN-MDD study (Sullivan et al., 2009). Details on blood sampling and data collection can be found elsewhere (Boomsma et al., 2008). Individual genotyping was conducted by using the Perlegen GWAS platform (Mountain View, Calif., USA). The SNPs that were present on these arrays were selected to tag common variation in the HapMap European and Asian populations. For the MR gene the two common and functional MR-2G/C (rs2070951_GC) and 1180V (rs5522_AG) SNPs were present. Based on DNA sequencing and haplotype reconstruction by our group it is known that, in the Dutch population, these two SNPs tag the three most common haplotypes located in exon 2 and extending into the promoter region (see Example 1).
Statistical Analyses
[0464] Allele frequencies for the different SNPs were tested for Hardy-Weinberg Equilibrium (HWE) using HaploView (version 4.1 for Mac OSX; available online at http://www.broadinstitute.org/mpg/haploview; (Barrett et al., 2005). In addition, HaploView was used to assess inter-marker linkage disequilibrium (LD) scores (expressed as D and r.sup.2) between the MR SNPs and to reconstruct haplotypes. Individual haplotypes were reconstructed with SNPHAP (version 1.3; available online at http://www-gene.cimr.cam.ac.uk/clayton/software/snphap.txt). Further analysis was performed in SPSS, version 16.0 for Mac OSX (SPSS Inc., Chicago, Ill., USA).
[0465] Differences between men and women for the various characteristics were verified using an independent-samples t-test, a Mann-Whitney test or a .sup.2-test. Before testing for sex differences, a square root transformation was used to reach a normal distribution for awakening time and physical activity. The 4 morning Cortisol measures were positively skewed and therefore log-transformed data were used in Linear Mixed Models (LMM) analysis, for the AUCg and AUCi non-transformed values could be used. For the data shown in
[0466] First, associations between the single MR SNPs and AUCg or AUCi as outcome variables were tested with AN(C)OVA. Linear regression analysis was used to analyze associations between MR haplotypes and the AUCg or AUCi. Putative covariates were entered first, followed by adding the haplotypes in the second step. Random coefficient analysis of the 4 morning Cortisol values was conducted with the help of LMM analysis. This method can interpolate missing values and it keeps the correlation between repeated data into account (Gueorguieva and Krystal, 2004). The model included a random intercept, taking into account different intercepts for the different subjects, the SNPs or haplotypes, time points (T1, T2, T3 or T4) and all covariates were entered In the model as fixed factors. To examine whether the different genetic variants affected the course of Cortisol levels after awakening we added a variant-by-time interaction term. Second, because of clear sex-dependent effects of MR (and GR) gene variants in earlier studies, interaction effects between the SNPs and sex were verified and association analysis was repeated in both sex strata (Kumsta et al., 2007; van Leeuwen et al., 2009). Third, an interaction effect was tested for the MR SNPs with SSRIs or stress, i.e. childhood trauma or recent life events. Due to low frequencies, no interaction effect could be tested for use of TCAs (n=35). A two-sided p-value below 0.05 was considered statistically significant. For significant findings effect sizes are given as r=(t.sup.2/t.sup.2+df). Our main interest was to determine the association between the MR-2G/C SNP and the CAR. Because of multiple testing a Bonferroni correction was applied where appropriate.
Results
Population Characteristics
[0467] Characteristics of the 1026 subjects are presented in Table 5. The mean age of this subpopulation was 43.5 years (SD=12.3, range 18-65) and 68.4% was female. Of the 1026 subjects 72.3% showed an increase in Cortisol level in the first hour after awakening. The two sexes differed significantly in age, education level, smoking behaviour, sleep duration, current depression diagnosis and Cortisol level at T2 and T4. No significant differences in demographics were found depending on the MR SNP genotypes or haplotypes.
Genotype and Haplotype Frequencies
[0468] Allele frequencies of the MR SNPs were in HWE, as assessed using HaploView. Frequencies for the MR-2G/C and 1180V genotypes and haplotypes (Table 5) and the inter-marker LD scores (D=1.0; r.sup.2=0.14) were similar as previously described (Derijk, 2009; van Leeuwen et al., 2009). Concordant with previous results, three main haplotypes were found; haplotype 1 consisting of the -2 G-allele and the 180 1-allele (or A nucleotide; hap 1 freq.=0.50); haplotype 2 consisting of the -2 C-allele and the 180 1-allele (hap 2 freq.=0.38) and haplotype 3 consisting of the -2 C-allele and the 180 V-allele (or G nucleotide, hap 3 freq.=0.12). Notably, there were no individuals carrying a haplotype consisting of the G-allele of the -2G/C SNP combined with the V-allele (or G nucleotide) of the 1180V SNP, in accordance with our previous observations this combination is very rare.
Associations Between MR Gene Variants and the CAR
[0469] Of the variables listed in Table 5 age, smoking, time of awakening, working on day of sampling and frequent TCA use were significant determinants of the CAR in the total group or in the women or men separately. Without or with adjustment for these covariates (except for TCAs, due to the small number; n=35) no effect was found for the -2G/C and 1180V SNPs on the CAR in the total group.
[0470] However, a significant interaction effect was found for the -2G/C SNP with sex on the AUCi (p=0.01) and a trend was found for an interaction effect on the AUCg (p=0.08). Therefore, for further analysis data were stratified for sex. The course of the CAR over time (
[0471] As a third step, interaction was verified with frequent use of SSRIs. No significant three-way (-2G/C-x-sex-x-SSRI) interaction effect was found (p=0.49 for AUCg; p=0.06 for AUCi). However, the effect found for the -2G/C SNP on the CAR in women was found to be due to an interaction with SSRI use (p=0.07 for the AUCg and p=0.05 for the AUCi). No significant interaction effect was found in men (p>0.3) or in the total group (men and women; p>0.10). Interestingly, subsequent stratification of the data for the use of SSRIs (
[0472] Additional correction for remitted vs. current depression did not change the results. LMM analysis in only the 906 subjects with all 4 CAR data point available gave similar (bit stronger) results. In addition, results did not change after excluding the subjects taking TCAs (n=35; of the subjects using SSRIs, n=227, only 2 were also taking TCAs). An interaction effect between the MR SNP and the use/no use of all antidepressants combined was verified but was not significant. No interaction effect was found between the MR-2G/C SNP and childhood trauma or recent life events. Finally, as earlier studies indicate that sex hormones can effect MR (and GR) mRNA and protein expression and protein binding (Carey et al., 1995; Turner, 1997), a possible interaction was verified between the -2G/C SNP and the use of oral contraceptives (OC) or menstrual phase, however, no significant interaction was observed.
TABLE-US-00006 TABLE 5 Sample characteristics of the total group and comparisons between men and women. Total Men Women Variable Total group n = 324 n = 702 Demographic n n = 1026 (31.6%) (68.4%) p-value Age, mean (SD), y 1026 43.5 (12.3) 45.3 (11.2) 42.6 (12.8) .001 Education level, mean (SD), y 1026 12.2 (3.2) 11.9 (3.1) 12.4 (3.2) .02 Health Smoking, % 1026 36.7 41.0 34.8 .05 Physical activity, mean (SD) 1026 3.7 (3.1) 3.7 (3.2) 3.7 (3.0) .79 Sampling factor Time of awakening, mean (SD) 1026 07:31 07:30 07:31 .71 (1 h, 13 min) (1 h, 12 min) (1 h, 13 min) Working on day of sampling, % 1026 57.5 59.9 56.4 .30 Sampling on a weekday, % 1026 91.5 89.2 92.6 .07 Sampling in month with more daylight, % 1026 58.0 58.3 57.8 .86 6 h of sleep, % 1026 29.5 34.0 27.5 .04 Frequent antidepressant use TCA, % 1026 3.4 3.4 3.4 .96 SSRI, % 1026 22.1 23.5 21.5 .49 Other, % 1026 7.8 9.3 7.1 .24 Benzodiazepines, % 1026 8.6 9.9 8.0 .31 Trauma Childhood trauma index score, regularly, % 1022 48.5 45.5 49.9 .19 Life events in past year, 1 or more events, % 1026 39.1 35.5 40.7 .11 Depression Current, % 1026 54.1 59.6 51.6 .02 Comorbid anxiety disorder, % 1026 69.7 67.6 70.7 .33 Cortisol CAR, mean (SD), nMol/L T1, at awakening 1014 17.0 (6.8) 17.8 (7.5) 16.7 (6.4) .07 T2, 30 min after awakening 1005 21.4 (9.3) 22.6 (10.9) 20.9 (6.5) .03 T3, 45 min after awakening 1000 20.2 (9.8) 20.7 (11.5) 20.1 (9.0) .86 T4, 60 min after awakening 1011 18.0 (9.7) 16.9 (8.1) 18.5 (10.3) .03 AUCg, mean (SD), n/Mol/L/h 906 19.6 (7.1) 20.2 (7.7) 19.3 (6.8) .10 AUCi, mean (SD), n/Mol/L/h 906 2.5 (6.3) 2.2 (7.0) 2.6 (5.9) .31 MR variants rs2070951 (2) GG/CG/CC, freq. 1026 .23/.54/.23 .21/.54/.25 .24/.54/.22 .30 rs5522 (I180V) AA/GA/GG, freq. 1026 .78/.20/.02 .75/.23/.02 .79/.19/.02 .30 MR hap 1 G-A, freq. 1026 .50 .48 .52 MR hap 2 C-A, freq. 1026 .38 .39 .37 .23 MR hap 3 C-G, freq. 1026 .12 .14 .11 Abbreviations: SD = standard deviation; MET = metabolic energy turnover; TCA = tricyclic antidepressant; SSRI = serotonin transporter reuptake inhibitor; CAR = Cortisol awakening response; AUCg = area under the morning curve with respect to the ground (= (((T1 + T2)/2)*0.5) + (((T2 + T3)/2)*0.25) + (((T3 + T4)/2)*0.25)); AUCi = area under the morning curve with respect to the increase = (((T1 + T2)/2)*0.5) + (((T2 + T3)/2)*0.25) + (((T3 + T4)/2)*0.25)) (T1*(0.5 + 0.25 + 0.25)) (Pruessner et al., 2003).
TABLE-US-00007 TABLE 6 Unadjusted and adjusted area under the curve cortisol values according to MR SNPs and haplotypes, F-statistics, standardized regression coefficients () and p-values. rs2070951 rs5522 MR haplotype 1-3 GG GC CC AA AG/GG Constant Hap 2 Hap 3 Women AUCg, mean 19.4 19.4 19.0 19.5 16.4 19.5 19.5 18.5 (n = 624) (SD) (8.5) (6.8) (7.2) (0.9) (6.3) (0.5) (0.4) (0.6) Unadjusted F (1, 621) = 0.33; p = .56 F (1, 622) = 2.77; p = .10 ref. B = 0.00 (0.43); p = 1.0 B = 0.99 (0.83); p = .12 Adjusted F (2, 617) = 0.34; p = .71 F (1, 618) = 2.29; p = .13 ref. B = 0.10 (0.42); p = .80 B = 0.94 (0.81); p = .13 Adjusted, F (2, 489) = 0.07; p = .93 F (1, 490) = 2.13; p = .15 ref. B = 0.45 (0.48); p = .35 B = 0.73 (0.68); p = .29 no SSRI use Adjusted, F (2, 121) = 3.55; p = .03 F (1, 122) = 0.04; p = .84 ref. B = 2.27 (0.83); p < .01 B = 1.33 (1.37); p = .33 SSRI users Men AUCg, mean 22.0 19.2 20.6 20.5 19.3 20.9 20.4 19.6 (n = 282) (SD) (9.1) (7.0) (7.8) (7.9) (7.3) (0.8) (0.7) (1.0) Unadjusted F (1, 279) = 0.99; p = .32 F (1, 280) = 1.34; p = .25 ref. B = 0.44 (0.72); p = .54 B = 1.30 (1.01); p = .20 Adjusted F (2, 275) = 2.86; p = .05 F (1, 376) = 0.84; p = .36 ref. B = 0.09 (0.71); p = .89 B = 0.89 (1.00); p = .38 Adjusted, F (2, 214) = 0.99; p = .37 F (1, 215) = 0.79; p = .38 ref. B = 0.11 (0.81); p = .89 B = 1.03 (1.17); p = .38 no SSRI use Adjusted, F (2, 54) = 4.35; p = .02 F (1, 55) = 0.13; p = .73 ref. B = 1.18 (1.51); p = .44 B = 1.24 (2.04); p = .64 SSRI users Women AUCi, mean 3.1 2.9 1.5 2.8 1.9 3.4 2.7 2.3 (n = 624) (SD) (6.0) (5.6) (6.4) (8.0) (5.4) (0.4) (0.4) (0.6) Unadjusted F (1, 621) = 4.88; p = .03 F (1, 622) = 2.18; p = .14 ref. B = 0.70 (0.35); p = .06 B = 1.03 (0.55); p = .06 Adjusted F (2, 617) = 3.60; p = .03 F (1, 618) = 1.94; p = .16 ref. B = 0.77 (0.37); p = .04 B = 1.03 (0.54); p = .06 Adjusted, F (2, 489) = 0.86; p = .42 F (1, 490) = 2.23; p = .14 ref. B = 0.35 (0.42); p = .41 B = 0.91 (0.59); p = .13 no SSRI use Adjusted, F (2, 121) = 6.31; p < .01 F (1, 122) = 0.00; p = 1.0 ref. B = 2.63 (0.79); p = .001 B = 1.27 (1.31); p = .34 SSRI users Men AUCi, mean 2.8 1.5 3.1 2.3 1.8 2.0 2.2 2.0 (n = 282) (SD) (8.9) (5.5) (7.8) (7.2) (6.3) (0.8) (0.7) (0.9) Unadjusted F (1, 279) = 0.11; p = .74 F (1, 280) = 0.31; p = .53 ref. B = 0.28 (0.65); p = .67 B = 0.02 (0.92); p = .99 Adjusted F (2, 275) = 1.74; p = .18 F (1, 276) = 0.90; p = .77 ref. B = 0.39 (0.65); p = .55 B = 0.26 (0.93); p = .78 Adjusted, F (2, 214) = 0.76; p = .47 F (1, 215) = 0.02; p = .89 ref. B = 0.21 (0.74); p = .77 B = 0.25 (1.08); p = .82 no SSRI use Adjusted, F (2, 54) = 1.92; p = .16 F (1, 55) = 1.03; p = .31 ref. B = 2.89 (1.52); p = .06 B = 0.63 (2.08); p = .76 SSRI users Adjusted = adjusted for age, smoking, awakening time, working on day of sampling and lifetime diagnosis of major depressive disorder. Abbreviations: AUCg = area under the morning curve with respect to the ground; AUCi = area under the morning curve with respect to the increase; SD = standard deviation; SSRI = serotonin transporter reuptake inhibitor
Discussion
[0473] This study shows that the MR-2G/C SNP modulates the CAR in lifetime MDD patients depending on the use of SSRIs; a clear effect of the MR-2G/C SNP was found specifically in subjects (men and women) frequently using SSRIs. No effect of the MR SNPs on the CAR was found in subjects not using SSRIs. The results, therefore, suggest that MR gene variants can have substantial effects on HPA axis activity while interacting with other factors like use of SSRIs.
[0474] The current results are partly in line with a first report revealing that the MR-2 C-allele significantly associated with slightly lower morning cortisol levels among an elderly cohort consisting for 66% of women (Kuningas et al., 2007). Of note is that these results were based on a single morning blood sample for which no effect of time of awakening was taken into account. Earlier studies showed that cortisol levels measured at multiple time points in the morning are more reliable (Pruessner et al., 1997). The present results are also partly in line with a more recent study by our group. Among a group of healthy subjects (n=218) (van Leeuwen et al., 2009) showed that the CAR was lower in subjects with the MR-2C/C genotype. However, this association was not significant and was found only in men (n=93) and not in women (n=125; genotype-by-sex effect p=0.20). Together the results indicate that the MR-2 C-allele is related to a decrease in cortisol levels under specific conditions.
[0475] Since the MR is involved in tonic inhibition of basal corticosteroid levels, an increased expression of the MR protein is expected to result in lower cortisol levels. In accordance with this hypothesis and the above mentioned results, in cell lines the -2 C-allele results in increased expression of the MR protein, resulting in a higher capacity to activate target genes (van Leeuwen et al., 2009); N. van Leeuwen et al., unpublished observations). The -2G/C variant interferes with expression of the MR protein potentially at the translational level. Notably, MR expression is highly dynamic. Following exercise or an acute single psychological stressor, but also during ageing changes in MR expression can be observed, at least in the latter two conditions associated with changes in HPA axis reactivity (van Eekelen et al., 1991; Gesing et al., 2001; Chang et al., 2008). Based on the present and previous association studies (DeRijk et al., 2006; van Leeuwen et al., 2009) we hypothesize that only under challenging conditions (like stress or medication) the MR gene variants may affect HPA axis activity. Here, a clear effect of the MR-2G/C SNP was found only in the lifetime MDD patients frequently using SSRIs. Among those subjects, carriers of the MR-2 C-allele showed an attenuated CAR, with a clear allele-dose effect only in women. On the other hand, carriers (men and women) of the -2G/G genotype showed an extended CAR, with elevated Cortisol levels even 60 min after awakening. In the previous study by (van Leeuwen et al., 2009) also a more distinct effect of the -2G/C SNP on the CAR was detected following pre-treatment with dexamethasone and in a sex-dependent manner. Finally, a significant effect of MR gene variants on ACTH, Cortisol and heartbeat could be observed under psychosocial stress conditions (DeRijk et al., 2006) N. van Leeuwen et al., unpublished observations).
[0476] Importantly, the two functional MR SNPs described here are linked to multiple SNPs located in the MR gene promoter region. These promoter SNPs result in turn in differences in transcriptional activity, leading to differential mRNA and protein regulation (M. D. Klok et al., unpublished observations). Together the SNPs result in 3 major haplotypes (which are tagged by the -2G/C and 1180V SNPs) with distinct genetic sequences, which can modulate MR expression and HPA activity in a context-dependent manner. Most likely, these SNPs located in the promoter region modulate effects of other factors like corticosteroids, sex steroids or antidepressants leading to gene-variant specific changes in MR regulation. Proof for possible interactions between the MR gene and sex steroids has been demonstrated for both estrogens and progesterone, which modulate mRNA and/or protein expression and binding of corticosteroid receptors (Carey et al., 1995; Turner, 1997). This could provide an explanation for the gender-dependent effects of the MR on the CAR.
[0477] Multiple indications for an interaction between MR signaling and the serotonin system exist. Changes in hippocampal MR expression in mice influence expression of the serotonin receptor 1A (5-HT1A) (Rozeboom et al., 2007). Moreover, the MR, GR and 5-HT1A receptors are co-expressed in specific cells of the hippocampus, while the level of MR occupation by cortisol affects the 5HT1A-receptor mediated hyperpolarization response (Joels and Van Riel, 2004). On the other hand, serotonin but also SSRIs increase MR and/or GR expression in vivo and in vitro (Seckl and Fink, 1991; Seckl and Fink, 1992; Robertson et al., 2005). Possibly, SSRIs affect MR expression directly or indirectly through 5-HT in a genotype-dependent manner, eventually leading to differential cortisol regulation.
[0478] Several lines of evidence suggest a role for the MR in the CAR. Highest MR mRNA expression levels have been measured in the human hippocampus, while much lower levels were detectable in other areas such as the amygdala, prefrontal cortex and anterior cingulate cortex (M. D. Klok et al., unpublished observations). A putative role for the hippocampus in the regulation of the CAR was previously demonstrated (Buchanan et al., 2004). In addition, the CAR was recently postulated to enable individuals to anticipate upcoming daily events, a process in which the hippocampus is central and in which the MR is involved (de Kloet et al., 2005; Fries et al., 2009). Moreover, the hippocampus is important for tonic inhibition of the HPA axis, which is MR mediated. Taken together, the data fit with a role of the MR, predominantly located in the hippocampus, in the control of the CAR.
[0479] The function and importance of the CAR for health and disease is still unclear. However, data indicate that small differences in the CAR can be of clinical relevance as they are associated with physiological and psychological disturbances (Fries et al., 2009; Vreeburg et al., 2009a). It was demonstrated that the CAR was elevated not only in current depressed patients but also in remitted depressed patients and in unaffected subjects with a parental history of depression or anxiety disorder, as assessed with the DSM-IV Composite International Diagnostic Interview (CIDI) (Vreeburg et al., 2009a); Vreeburg et al., unpublished observations). This suggests that an increased CAR in MDD patients is not only a state marker but represents in part a trait. Here, we identified a biological determinant of inter-individual variability in the CAR, possibly representing a vulnerability/protective factor for the pathophysiology or course of depressed mood. Moreover, the MR gene variants may underlie in part the development of particular symptoms of depression, not only problems with mood but also for example cognitive problems (Kuningas et al., 2007). Indeed, multiple studies have shown that MR activity influences cognitive flexibility in healthy individuals (Otte et al., 2007; Schwabe et al., 2009).
[0480] Normalization of the HPA axis, either by alleviation of hypercortisolism or a decrease of reactivity as measured by the Dex-CRH test, is predictive for clinical benefit (Barden et al., 1995; Zobel et al., 2004). In the present study, the SSRIs by themselves had no effect on the CAR. However, the MR-by-SSRI interaction effect on the CAR was remarkably distinct; depending on MR genotype, 25 percent of the women and men using SSRIs showed a small or even flattened CAR (-2 C-allele carriers), while another 25 percent of the patients (-2G/G carriers) frequently using SSRIs displayed a high CAR compared to the other genotype groups. This effect could indicate that some patients benefit from SSRI treatment when it comes to neuroendocrine normalization, while others experience deterioration depending on their MR genotype. The groups are too small to properly evaluate the course of the disorder in these subjects, although the present association found with Cortisol also seemed to correlate with differences in depressive and anxiety symptoms (data not shown). A role of the MR in pharmacological treatment of depression was recently demonstrated in a study by (Otte et al., 2009) in which administration of a MR agonist accelerated the response of MDD patients to the SSRI escitalopram. The results complement the results of earlier studies showing that the MR antagonist spironolactone hampers the response to the TCA amithptyline (Holsboer, 1999). It is plausible that these effects are also depending on MR genetic makeup.
[0481] To conclude, we have identified the MR as a possible modulator of the CAR in depressed patients. A clear effect of the functional MR-2G/C SNP on the CAR was found in the lifetime MDD patients frequently using SSRIs, with prolonged heightened early morning Cortisol levels observed in MR-2G/G carriers and lower levels in -2 C-allele carriers. No effect was found in patients not using SSRIs. The finding of a MR genotype-by-SSRI interaction effect on the dynamics of the CAR could be of importance for future therapy selection and for development of novel pharmacological treatments.
REFERENCES FOR EXAMPLE 4
[0482] Atkinson, H. C., Wood, S. A., Castrique, E. S., Kershaw, Y. M., Wiles, C. C., Lightman, S. L., 2008. Corticosteroids mediate fast feedback of the rat hypothalamic-pituitary-adrenal axis via the mineralocorticoid receptor. Am J Physiol Endocrinol Metab 294, E1011-1022. [0483] Barden, N., Reul, J. M., Holsboer, F., 1995. Do antidepressants stabilize mood through actions on the hypothalamic-pituitary-adrenocortical system? Trends Neurosci. 18, 6-11. [0484] Barrett, J. C., Fry, B., Mailer, J., Daly, M. J., 2005. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21, 263-265. [0485] Bet, P. M., Penninx, B. W., Bochdanovits, Z., Uitterlinden, A. G., Beekman, A. T., van Schoor, N. M., Deeg, D. J., Hoogendijk, W. J., 2009. Glucocorticoid receptor gene polymorphisms and childhood adversity are associated with depression: New evidence for a gene-environment interaction. Am J Med Genet B Neuropsychiatr Genet 150B, 660-669. [0486] Bjartmar, L, Johansson, I. M., Marcusson, J., Ross, S. B., Seckl, J. R., Olsson, T., 2000. Selective effects on NGFI-A, MR, GR and NGFI-B hippocampal mRNA expression after chronic treatment with different subclasses of antidepressants in the rat. Psychopharmacology (Berl). 151, 7-12. [0487] Boomsma, D. I., Willemsen, G., Sullivan, P. F., Heutink, P., Meijer, P., Sondervan, D., Kluft, C, Smit, G., Nolen, W. A., Zitman, F. G., Smit, J. H., Hoogendijk, W. J., van Dyck, R., de Geus, E. J., Penninx, B. W., 2008. Genome-wide association of major depression: description of samples for the GAIN Major Depressive Disorder Study: NTR and NESDA biobank projects. Eur. J. Hum. Genet. 16, 335-342. [0488] Buchanan, T. W., Kern, S., Allen, J. S., Tranel, D., Kirschbaum, C, 2004. Circadian regulation of Cortisol after hippocampal damage in humans. Biol. Psychiatry 56, 651-656. Carey, M. P., Deterd, C. H., de Koning, J., Helmerhorst, F., de Kloet, E. R., 1995. The influence of ovarian steroids on hypothaiamic-pituitary-adrenal regulation in the female rat. J. Endocrinol. 144, 311-321. [0489] Chang, Y. T., Chen, Y. C., Wu, C. W., Yu, L, Chen, H. I., Jen, C. J., Kuo, Y. M., 2008. Glucocorticoid signaling and exercise-induced downregulation of the mineralocorticoid receptor in the induction of adult mouse dentate neurogenesis by treadmill running. Psychoneuroendocrinology 33, 1173-1182. [0490] Clow, A., Thorn, L, Evans, P., Hucklebridge, F., 2004. The awakening Cortisol response: methodological issues and significance. Stress 7, 29-37. [0491] de Graaf, R., Bijl, R. V., Ten Have, M., Beekman, AT., Vollebergh, W. A., 2004. Pathways to comorbidity: the transition of pure mood, anxiety and substance use disorders into comorbid conditions in a longitudinal population-based study. J. Affect. Disord. 82, 461-467. [0492] de Kloet, E. R., Joels, M., Holsboer, F., 2005. Stress and the brain: from adaptation to disease. Nat Rev Neurosci 6, 463-475. 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Psychological stress increases hippocampal mineralocorticoid receptor levels: involvement of corticotropin-releasing hormone. J. Neurosci. 21, 4822-4829. [0499] Gueorguieva, R., Krystal, J. H., 2004. Move over ANOVA: progress in analyzing repeated-measures data and its reflection in papers published in the Archives of General Psychiatry. Arch. Gen. Psychiatry 61, 310-317. [0500] Hellhammer, J., Fries, E., Schweisthal, O. W., Schlotz, W., Stone, A. A., Hagemann, D., 2007. Several daily measurements are necessary to reliably assess the Cortisol rise after awakening: state- and trait components. Psychoneuroendocrinology 32, 80-86. [0501] Heuser, I., Deuschle, M., Weber, B., Stalla, G. K., Holsboer, F., 2000. Increased activity of the hypothalamus-pituitary-adrenal system after treatment with the mineralocorticoid receptor antagonist spironolactone. Psychoneuroendocrinology 25, 513-518. [0502] Holsboer, F., 1999. The rationale for corticotropin-releasing hormone receptor (CRH-R) antagonists to treat depression and anxiety. J. Psychiatr. Res. 33, 181-214. [0503] Holsboer, F., Barden, N., 1996. Antidepressants and hypothalamic-pituitary-adrenocortical regulation. Endocr. Rev. 17, 187-205. [0504] Joels, M., Karst, H., DeRijk, R., de Kloet, E. R., 2008. The coming out of the brain mineralocorticoid receptor. Trends Neurosci. 31, 1-7. [0505] Joels, M., Van Riel, E., 2004. Mineralocorticoid and glucocorticoid receptor-mediated effects on serotonergic transmission in health and disease. Ann. N. Y. Acad. Sci. 1032, 301-303. [0506] Kirschbaum, C, Hellhammer, D. H., 1994. Salivary Cortisol in psychoneuroendocrine research: recent developments and applications. Psychoneuroendocrinology 19, 313-333. [0507] Kuehner, C, Holzhauer, S., Huffziger, S., 2007. Decreased Cortisol response to awakening is associated with cognitive vulnerability to depression in a nonclinical sample of young adults. Psychoneuroendocrinology 32, 199-209. [0508] Kumsta, R., Entringer, S., Koper, J. W., van Rossum, E. F., Hellhammer, D. H., Wust, S., 2007. Sex specific associations between common glucocorticoid receptor gene variants and hypothalamus-pituitary-adrenal axis responses to psychosocial stress. Biol. Psychiatry 62, 863-869. [0509] Kuningas, M., de Rijk, R. H., Westendorp, R. G., Jolles, J., Slagboom, P. E., van Heemst, D., 2007. Mental performance in old age dependent on Cortisol and genetic variance in the mineralocorticoid and glucocorticoid receptors. Neuropsychopharmacology 32, 1295-1301. [0510] Nestler, E. J., Barrot, M., DiLeone, R. J., Eisch, A. J., Gold, S. J., Monteggia, L. M., 2002. Neurobiology of depression. Neuron 34, 13-25. [0511] Otte, C, Hinkelmann, K., Moritz, S., Yassouridis, A., Jahn, H., Wiedemann, K., Kellner, M., 2009. Modulation of the mineralocorticoid receptor as add-on treatment in depression: A randomized, double-blind, placebo-controlled proof-of-concept study. J. Psychiatr. Res. [0512] Otte, C, Moritz, S., Yassouridis, A., Koop, M., Madrischewski, A. M., Wiedemann, K., Kellner, M., 2007. Blockade of the mineralocorticoid receptor in healthy men: effects on experimentally induced panic symptoms, stress hormones, and cognition. Neuropsychopharmacology 32, 232-238. [0513] Penninx, B. W., Beekman, AT., Smit, J. H., Zitman, F. G., Nolen, W. A., Spinhoven, P., Cuijpers, P., De Jong, P. J., Van Marwijk, H. W., Assendelft, W. J., Van Der Meer, K., [0514] Verhaak, P., Wensing, M., De Graaf, R., Hoogendijk, W. J., Ormel, J., Van Dyck, R., 2008. The Netherlands Study of Depression and Anxiety (NESDA): rationale, objectives and methods. Int J Methods Psychiatr Res 17, 121-140. [0515] Pruessner, J. C., Kirschbaum, C, Meinlschmid, G., Hellhammer, D. H., 2003. Two formulas for computation of the area under the curve represent measures of total hormone concentration versus time-dependent change. Psychoneuroendocrinology 28, 916-931. [0516] Pruessner, J. C., Wolf, O. T., Hellhammer, D. H., Buske-Kirschbaum, A., von Auer, K., Jobst, S., Kaspers, F., Kirschbaum, C, 1997. Free Cortisol levels after awakening: a reliable biological marker for the assessment of adrenocortical activity. Life Sci. 61, 2539-2549. [0517] Robertson, D. A., Beattie, J. E., Reid, I. C., Balfour, D. J., 2005. Regulation of corticosteroid receptors in the rat brain: the role of serotonin and stress. Eur. J. Neurosci. 21, 1511-1520. [0518] Rozeboom, A. M., Akil, H., Seasholtz, A. F., 2007. Mineralocorticoid receptor overexpression in forebrain decreases anxiety-like behavior and alters the stress response in mice. Proc. Natl. Acad. Sci. U.S.A 104, 4688-4693. [0519] Schwabe, L, Oitzl, M. S., Richter, S., Schachinger, H., 2009. Modulation of spatial and stimulus-response learning strategies by exogenous Cortisol in healthy young women. Psychoneuroendocrinology 34, 358-366. [0520] Seckl, J. R., Fink, G., 1991. Use of in situ hybridization to investigate the regulation of hippocampal corticosteroid receptors by monoamines. J. Steroid Biochem. Mol. Biol. 40, 685-688. [0521] Seckl, J. R., Fink, G., 1992. Antidepressants increase glucocorticoid and mineralocorticoid receptor mRNA expression in rat hippocampus in vivo. Neuroendocrinology 55, 621-626. [0522] Sullivan, P. F., de Geus, E. J., Willemsen, G., James, M. R., Smit, J. H., Zandbelt, T., Arolt, V., Baune, B. T., Blackwood, D., Cichon, S., Coventry, W. L., Domschke, K., Farmer, A., Fava, M., Gordon, S. D., He, Q., Heath, A. C., Heutink, P., Holsboer, F., Hoogendijk, W. J., Hottenga, J. J., Hu, Y., Kohli, M., Lin, D., Lucae, S., Macintyre, D. J., Maier, W., McGhee, K. A., McGuffin, P., Montgomery, G. W., Muir, W. J., Nolen, W. A., Nothen, M. M., Perlis, R. H., Pirlo, K., Posthuma, D., Rietschel, M., Rizzu, P., Schosser, A., Smit, A. B., Smoller, J. W., Tzeng, J. Y., van Dyck, R., Verhage, M., Zitman, F. G., Martin, N. G., Wray, N. R., Boomsma, D. I., Penninx, B. W., 2009. Genome-wide association for major depressive disorder, a possible role for the presynaptic protein piccolo. Mol. Psychiatry 14, 359-375. [0523] Turner, B. B., 1997. Influence of gonadal steroids on brain corticosteroid receptors: a minireview. Neurochem. Res. 22, 1375-1385. [0524] van Eekelen, J. A., Rots, N. Y., Sutanto, W., Oitzl, M. S., de Kloet, E. R., 1991. Brain corticosteroid receptor gene expression and neuroendocrine dynamics during aging. J. Steroid Biochem. Mol. Biol. 40, 679-683. [0525] van Leeuwen, N., Kumsta, R., Entringer, S., de Kloet, E. R., Zitman, F. G., Derijk, R. H., Wust, S., 2009. Functional mineralocorticoid receptor (MR) gene variation influences the Cortisol awakening response after dexamethasone. Psychoneuroendocrinology. [0526] Vreeburg, S. A., Hoogendijk, W. J., van Pelt, J., Derijk, R. H., Verhagen, J. C., van Dyck, R., Smit, J. H., Zitman, F. G., Penninx, B. W., 2009a. Major depressive disorder and hypothalamic-pituitary-adrenal axis activity: results from a large cohort study. Arch. Gen. Psychiatry 66, 617-626. [0527] Vreeburg, S. A., Kruijtzer, B. P., van Pelt, J., van Dyck, R., DeRijk, R. H., Hoogendijk, W. J., Smit, J. H., Zitman, F. G., Penninx, B. W., 2009b. Associations between sociodemographic, sampling and health factors and various salivary Cortisol indicators in a large sample without psychopathology. Psychoneuroendocrinology 34, 1109-1 20. [0528] Wilhelm, I., Born, J., Kudielka, B. M., Schlotz, W., Wust, S., 2007. Is the Cortisol awakening rise a response to awakening? Psychoneuroendocrinology 32, 358-366. [0529] Wust, S., Federenko, I., Hellhammer, D. H., Kirschbaum, C, 2000a. Genetic factors, perceived chronic stress, and the free Cortisol response to awakening. Psychoneuroendocrinology 25, 707-720. [0530] Wust, S., Wolf, J., Hellhammer, D. H., Federenko, I., Schommer, N., Kirschbaum, C, 2000b. The Cortisol awakening responsenormal values and confounds. Noise Health 2, 79-88. [0531] Zobel, A. W., Schulze-Rauschenbach, S., von Widdern, O. C., Metten, M., Freymann, N., Grasmader, K., Pfeiffer, U., Schnell, S., Wagner, M., Maier, W., 2004. Improvement of working but not declarative memory is correlated with HPA normalization during antidepressant treatment. J. Psychiatr. Res. 38, 377-383.
EMBODIMENTS OF INVENTION
[0532] 1. A method of assessing the susceptibility of a subject to, or aiding the diagnosis of, an anxiety disorder or depression, the method comprising genotyping any one or more single nucleotide polymorphisms (SNPs) selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, and/or one or more polymorphic sites which are in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, wherein reduced susceptibility is indicated when the allele of the one or more SNPs is respectively one or more of +CT, C, T, C and C, and/or when the allele of the one or more polymorphic sites is one that is in linkage disequilibrium with the respective one or more +CT, C, T, C and C alleles of the one or more SNPs.
[0533] 2. A method according to Embodiment 1, wherein genotyping any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, and/or one or more polymorphic sites which are in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, comprises contacting a sample of nucleic acid from the subject with one or more nucleic acid molecules that hybridise selectively to a genomic region encompassing any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, and/or a genomic region encompassing one or more polymorphic sites which are in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951.
[0534] 3. A method according to Embodiment 1 or 2, wherein the subject is a female human.
[0535] 4. A method according to any of Embodiments 1-3, wherein the one or more polymorphic sites which are in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, are within the mineralocorticoid receptor (MR) gene.
[0536] 5. A method according to any of Embodiments 1-4, wherein the one or more polymorphic sites which are in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, are SNPs selected from the group consisting of rs5522, rs5525 and rs7671250, wherein reduced susceptibility is indicated when the allele of one or more of rs5522, rs5525 and rs7671250 is respectively A, C and T.
[0537] 6. A method according to any of Embodiments 1-5, wherein the one or more polymorphic sites are SNPs selected from the group consisting of rs767 250, rs5522, rs5525, rs4835519, rs2172002, rs11929719, rs11099695, rs11730626, rs2070949, rs2248038, rs9992256, rs5520 and SNP x at position 149585620 in the MR gene as numbered in
[0538] 7. A method according to any of Embodiments 1-6, wherein a further genetic locus associated with an anxiety disorder or depression is analysed in the subject.
[0539] 8. A method according to Embodiment 7, wherein the further genetic locus is any one or more of the glucocorticoid receptor (GR) gene, a heat shock protein gene, the P-glycoprotein gene and the corticotropin releasing hormone receptor-1 (CRHR-1) gene.
[0540] 9. A method according to any of Embodiments 1-8, wherein one or more of the age, sex, body mass index (BMI), smoking status, childhood trauma status, or stress status of the subject is considered.
[0541] 10. A method according to Embodiment 2, wherein the sample of nucleic acid from the subject is subjected to a nucleic acid amplification before contacting with one or more nucleic acid molecules that hybridise selectively to the any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, and/or to one or more polymorphic sites which are in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951.
[0542] 11. Use of one or more nucleic acid molecules that hybridise selectively to a genomic region encompassing any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, and/or to a genomic region encompassing one or more polymorphic sites which are in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951 for assessing the susceptibility of a subject to, or aiding the diagnosis of, an anxiety disorder or depression, wherein reduced susceptibility is indicated when the allele of the one or more SNPs is respectively one or more of +CT, C, T, C and C, and/or when the allele of the one or more polymorphic sites is one that is in linkage disequilibrium with the respective one or more +CT, C, T, C and C alleles of the one or more SNPs 12. One or more nucleic acid molecules that hybridise selectively to a genomic region encompassing any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, and/or to a genomic region encompassing one or more polymorphic sites which are in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951 for use in assessing the susceptibility of a subject to, or aiding the diagnosis of, an anxiety disorder or depression, wherein reduced susceptibility is indicated when the allele of the one or more SNPs is respectively one or more of +CT, C, T, C and C and/or when the allele of the one or more polymorphic sites is one that is in linkage disequilibrium with the respective one or more +CT, C, T, C and C alleles of the one or more SNPs.
[0543] 13. Use of one or more nucleic acid molecules that hybridise selectively to a genomic region encompassing any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, and/or to a genomic region encompassing one or more polymorphic sites which are in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs32 6799, rs6814934, rs7658048, rs2070950 and rs2070951 in the manufacture of a reagent for assessing the susceptibility of a subject to, or aiding the diagnosis of, an anxiety disorder or depression, wherein reduced susceptibility is indicated when the allele of the one or more SNPs is respectively one or more of +CT, C, T, C and C and/or when the allele of the one or more polymorphic sites is one that is in linkage disequilibrium with the respective one or more +CT, C, T, C and C alleles of the one or more SNPs.
[0544] 14. A kit of parts for use in assessing the susceptibility of a subject to, or aiding the diagnosis of, an anxiety disorder or depression, the kit comprising one or more nucleic acid molecules that hybridise selectively to a genomic region encompassing any two or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, and/or that hybridise selectively to a genomic region encompassing two or more polymorphic sites in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951.
[0545] 15. A kit of parts for use in assessing the susceptibility of a subject to, or aiding the diagnosis of, an anxiety disorder or depression, the kit comprising one or more nucleic acid molecules that hybridise selectively to a genomic region encompassing any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, and that hybridise selectively to a genomic region encompassing one or more polymorphic sites in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951.
[0546] 16. A solid substrate for use in assessing the susceptibility of a subject to, or aiding the diagnosis of, an anxiety disorder or depression, the solid substrate having attached thereto one or more nucleic acid molecules that hybridise selectively to a genomic region encompassing any two or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, and/or that hybridise selectively to a genomic region encompassing two or more polymorphic sites in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951.
[0547] 17. A solid substrate for use in assessing the susceptibility of a subject to, or aiding the diagnosis of, an anxiety disorder or depression, the solid substrate having attached thereto one or more nucleic acid molecules that hybridise selectively to a genomic region encompassing any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, and that hybridise selectively to a genomic region encompassing one or more polymorphic sites in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs3216799, rs68 4934, rs7658048, rs2070950 and rs2070951.
[0548] 18. A kit of parts according to Embodiment 14 or 15, or solid substrate according to Embodiment 16 or 17, wherein the polymorphic sites in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, are SNPs selected from the group consisting of rs5522, rs5525 and rs7671250.
[0549] 19. A kit of parts according to Embodiment 14 or 15, or solid substrate according to Embodiment 16 or 17, wherein the polymorphic sites in linkage disequilibrium with any one or more SNPs selected from the group consisting of rs3216799, rs6814934, rs7658048, rs2070950 and rs2070951, are SNPs selected from the group consisting of rs7671250, rs5522, rs5525, rs4835519, rs2172002, rs11929719, rs11099695, rs11730626, rs2070949, rs2248038, rs9992256, rs5520 and SNP x at position 149585620 in the MR gene as numbered in
[0550] 20. A kit of parts according to any of Embodiments 14, 15, 18 and 19, or a solid substrate according to any of Embodiments 16-19, further comprising a nucleic acid molecule that hybridises selectively to a further genetic locus associated with an anxiety disorder or depression.
[0551] 21. A kit of parts or solid substrate according to Embodiment 20, wherein the further genetic locus is any one or more of the glucocorticoid receptor (GR) gene, a heat shock protein gene, the P-glycoprotein gene and the corticotropin releasing hormone receptor-1 (CRHR-1) gene.
[0552] 22. A method of recording data on the susceptibility of a subject to an anxiety disorder or depression, the method comprising carrying out the method of any of Embodiments 1-10 and recording the results on a data carrier.
[0553] 23. A method of preparing a data carrier containing data on the susceptibility of a subject to an anxiety disorder or depression, the method comprising carrying out the method of Embodiment 22.
[0554] 24. A method according to Embodiment 22 or 23 wherein the data is recorded in electronic form.
[0555] 25. A method of combating an anxiety disorder or depression in a subject, the method comprising assessing the susceptibility of a subject to, or aiding the diagnosis of, an anxiety disorder or depression according to any of Embodiments 1-10 and depending upon the outcome of the assessment treating the subject.
[0556] 26. A method according to Embodiment 25, wherein treating the subject comprises administering any one or more of an anti-depressant, an anti-convulsant, a beta-blocker, cortisol, a cortisol agonist, a cortisol antagonist, an MR agonist, an MR antagonist or an agent that modulates MR-expression to the subject.
[0557] 27. A compound for use in combating an anxiety disorder or depression in a subject who has been assessed as having, or having an increased likelihood of developing, an anxiety disorder or depression according to any of Embodiments 1-10, the compound being selected from an anti-depressant, an anti-convulsant, a beta-blocker, cortisol, a cortisol agonist, a cortisol antagonist, an MR agonist, an MR antagonist or an agent that modulates MR-expression.
[0558] 28. Use of a compound in the manufacture of a medicament for combating an anxiety disorder or depression in a subject who has been assessed as having, or having an increased likelihood of developing, an anxiety disorder or depression according to any of Embodiments 1-10, the compound being selected from an anti-depressant, an anti-convulsant, a beta-blocker, cortisol, a cortisol agonist, a cortisol antagonist, an MR agonist, an MR antagonist, or an agent that modulates MR-expression.
[0559] 29. A method according to any of Embodiments 1-10 and 22-26, a use according to any of Embodiments 11, 13 and 28, a nucleic acid according to Embodiment 12, a kit of parts according to any of Embodiments 14, 15 and 18-21, a solid substrate according to any of Embodiments 16-21, and a compound according to Embodiment 27, wherein the anxiety disorder is any of substance-induced anxiety disorder, generalised anxiety, panic disorder, acute stress disorder, posttraumatic stress disorder, adjustment disorder with anxious features, social phobia, obsessive-compulsive disorder or specific phobias.
[0560] 30. Any novel method of assessing susceptibility to, or aiding diagnosis of, an anxiety disorder or depression in a subject as herein disclosed.
[0561] 31. Any novel kit of parts as herein disclosed.