Abstract:
Methods for diagnosing chronic stress in patients by first determining the level of one or more analytes in a patient sample and establishing the significance of the one or more analyte levels.

Description:
FIELD OF INVENTION  
     The present invention relates to the diagnosis of chronic stress and related disorders. 
     BACKGROUND OF THE INVENTION 
     Chronic stress is involved in the development of several different diseases in the nervous, endocrine and immune systems. Stressors of various types, e.g. psychological, physical and biological, abound. Sustained stress related to work appears to be an increasingly important factor for the development of both physical and mental illness (see Tennant, Journal of Psychosomatic Research, 2001, 51(5), 697-704; and Vahtera, Lancet, 1997, 350 (9085), 1124-1128). 
     In Sweden alone, public expenditure for sick-leave has more than doubled over a few years, and, in 2003, the number of persons on long-term sick leave (i.e. more than 30 days) had increased to an all-time high. Much of this dramatic increase appears to be due to stress-related affective illness. The question remains whether mild or moderate stress-induced depression should be seen as a purely psychological disorder, or whether the characteristic syndrome of fatigue, tension and dysphoria has physical connotations. 
     The physiological pathways that lead from prolonged stress to exhaustion and depression are likely to involve both the hypothalamus-pituitary-adrenal axis and other endocrine systems, as well as the immune system (see Folkow et al, Acta Physiologica Scandinavica, 1997, 161). The exact sequence of events in the brain-endocrine-immune, systems under chronic stress is not well known in humans, but recent progress in immunology has lead to increasing focus on the links between cytokines and depressive illnesses. 
     Cytokines are low molecular weight proteins or glycoproteins that were initially characterised as communication molecules of the immune system. They can be secreted by a number of different cell types and play a key role in the regulation of the immune system and the co-ordination of the host response to injury and infection. Cytokines produce their actions by binding to specific high-affinity cell surface receptors. The range of actions displayed by individual cytokines can be broad and diverse and is dependent on the receptor. Receptors can be soluble and can bind to the cytokine, in turn inhibiting the binding of the cytokine to the cell surface receptor, blocking its biological. Cytokines operate within a complex network and may act synergistically or antagonistically. They can influence the production of other cytokines from other cell types. Initially, it was thought that the cytokines were restricted to the immune system but it has since been demonstrated that they are also involved in signalling in the central nervous and endocrine systems. 
     In 1991, Smith formulated the macrophage theory of depression. This hypothesis proposed that excessive secretion of macrophage cytokines such as IL-1, TNFa and IFNg, were a cause of some cases of major depression. Both before and after the proposal of this theory, others have reported that when previously psychiatrically healthy individuals have been treated with exogenous cytokines they develop depressive-like symptoms. This has also been observed in patients being treated with cytokines such as IFNg, where 80% of patients reported fatigue from moderate to severe intensity. The same has been found with administration of certain cytokines to experimental animals. Many studies have measured the circulating levels of cytokines in relation to one or more specific stressors, but these studies have revealed conflicting results due to sample sizes being small and the use of different assays making results difficult to interpret. In vitro cytokine secretion by stimulation of the peripheral blood lymphocytes has also been studied in relation to stress and depression. These studies have almost exclusively focused on IL-6, IL-1, TNFa and IFNg. Again, the results have varied and no definite pattern has emerged. 
     Cytokines can be measured by either immunoassay or bioassay. Bioassays measure the functional activity of cytokines and require that some measure of biological activity be recorded. Bioassays can lack specificity as other cytokines present in the sample can give the same response in the assay or because the sample may contain inhibitors which block them. Also, if the cytokines have been proteolytically degraded they will not retain biological activity. Immunoassays are based on an antibody that recognises a small portion of the cytokine and therefore most are very specific for the cytokine being measured. It is possible for biologically inactive cytokines and proteolytically degraded cytokines to be measured. Until very recently most of the cytokine immunoassay measurements have been performed using individual ELISAs. 
     At present, no reliable markers of chronic stress and related disorders (e.g. stress-related depression) have been identified. 
     SUMMARY OF THE INVENTION 
     The present invention is based on the discovery of a number of potential markers of chronic stress, namely VEGF, IL-8, MCP1, EGF and TSH. 
     Accordingly, a first aspect of the invention is a method of diagnosis of chronic stress in a patient, which comprises:
         (a) determining the level of each of one or more analytes in the patient, wherein the one or more analytes are selected from VEGF, IL-8, MCP1, EGF and TSH; and   (b) establishing the significance of the or each level.       

     Preferably, the or each level is determined using a sample (e.g. a blood sample) taken from the patient. 
    
    
     DESCRIPTION OF THE INVENTION 
     The term “chronic stress” as used herein refers to chronic stress as diagnosed according to the Hospital Anxiety and Depression Scale of Snaith and Zigmond, Br. Med. J, Clin. Res. Ed., 1986, 292, 6516, 344. 
     Elevated levels of VEGF, MCP1, IL-8 and EGF, or reduced levels of TSH are believed to be indicative of chronic stress. Without wishing to be bound by theory, it is believed that one or more of the following are indicative of chronic stress: VEGF levels of at least about 25 pg/ml, EGF levels of at least about 70 pg/ml, IL-8 levels of at least about 3 pg/ml (particularly in men) and MCP1 levels of at least about 220 pg/ml. It will be appreciated that the benchmark levels may vary somewhat between patients and depend on factors such as the age, general health, weight, sex and diet of the patient in question. In particular, the sex of the patient may be a crucial factor since analyte levels generally differ in men and women. A method of the invention preferably comprises determining a plurality of analytes, the analytes preferably including VEGF, MCP1 and EGF. 
     It is envisaged that a method of the invention may also be used for the diagnosis of disorders related to chronic stress, for example stress-related depression. In this case, the control may be a person not suffering from a major depressive disorder. The term “major depressive disorder” as defined herein refers to a major depressive disorder as diagnosed according to the Diagnostic and Statistical Manual of the American Psychiatric Association, 4 th  Edition. 
     The levels of the or each analyte may be determined using any suitable method known in the art. A preferred system is the “Evidence” immunoassay analyser (Randox Laboratories Ltd). The Evidence system is a fully automated immunoassay analyser based on a protein biochip array technology and allows for the simultaneous quantification of a plurality of analytes. For example, the Evidence cytokine and growth factor panel can determine the presence of up to twelve analytes in a single sample. 
     The invention will now be illustrated by way of example only. 
     Subjects 
     Patients on Long Term Sick Leave for Affective Disorder 
     287 patients (77 men and 210 women) on sick-leave (for more than three months) for any affective or stress-related mental disorder (depression, anxiety disorder, stress disorder, burnout, exhaustion), were recruited. All patients were ambulatory and none had received in-patient care for their current illness. They were diagnosed by specially trained physicians for chronic stress according to the Hospital Anxiety and Depression scale of Snaith and Zigmond. They were also diagnosed for stress-related depression according to the Diagnostic and Statistical Manual of the American Psychiatric Association, 4th Edition (“DSM-IV”, 1994), using the Structured Clinical Interview for DSM-IV (“SCID-I,”, 1997). 82% of patients fulfilled DSM-IV criteria for Major Depressive Disorder at some time during their current illness episode. Likely eliciting factors could be identified for all subjects. 
     Health Care Personnel with Occupational Stress 
     A group of women experiencing work stress. Of the employees who replied to the and who scored above the 75th percentile on the Oldenburg Burnout Inventory (“OLBI”, which measures the degree of professional burnout; see Demerouti et al, Journal of Applied Psychology, 2001, 86(3), 499-512) were invited to participate in a randomised controlled study of the possible beneficial effect of a series of structured group discussions with colleagues. Those who were randomised to active treatment were asked to leave blood samples. The resulting group consisted of 45 women, ranging in age from 39 to 62 years, the mean age being 52.8±52 years. 
     Healthy Control Workers 
     The reference group comprised 187 individuals (104 men and 83 women, having a mean age of 36±7.5 yrs, and a range of 22-61 years), recruited. The subjects were all full-time workers, 34% were managers and 54% project leaders. Two women were pregnant at the time of the physiological examination. 
     Methods 
     Venous blood was drawn and immediately centrifuged, plasma was separated and stored in aliquots at −20° C. or below until analysed. 
     Among the various cytokines and growth factors analysed were: interleukin 8 (IL8), monocyte chemotactic protein-1 (MCP1), epidermal growth factor (EGF) and vascular endothelial growth factor (VEGF). Furthermore, thyroid stimulating hormone (TSH) and testosterone were included in the panel analysed using the “Evidence” immunoassay system (Randox Laboratories Ltd). The assays were done on coded plasma samples by investigators who were unaware of subject category. 
     Results 
     Means and standard deviations of the 17 markers in men and women, on sick leave for stress-induced depression, still working but experiencing high levels of occupational stress, and apparently healthy controls, are shown in Tables 1 and 2. 
     In the women, there were very large differences between the three subject groups for MCP1, EGF and VEGF. MCP1 levels were more than twice as high in the sick leave group compared to the healthy controls, with the occupational stress group in between. VEGF levels were three times as high in the sick leave group, and EGF levels were more than twice as high, compared to the healthy group, once more with the occupational stress group in between. The sick leave group also had significantly lower levels of prolactin and TSH. 
     In the men, it was not possible to gain access to an occupational stress group, and the comparisons are therefore between men on sick leave and apparently healthy controls. Among the men, IL-8 levels were significantly increased in the sick leave group, while testosterone levels were decreased. As in the women, the greatest differences were shown for MCP1, EGF and VEGF, which were two to three times as high in the sick leave group. 
     Since there were weak but significant correlations between some of the markers and age, and the mean age differed significantly between the groups (women one-way ANOVA F=59.09 df=2, 338 P=0.000; men T=8.87 df=174 p=0.000), the data was controlled for age in an analysis of covariance. This resulted in one additional significant difference for the women, namely in testosterone, which was higher in the sick leave group. Among men, when controlling for age, the significant effects of testosterone found by using a T-test disappeared in the analysis of covariance. Thus, four markers, IL8, MCP1, VEGF and EGF, remained significant in the men. 
     In order to examine the usefulness of these markers for screening and diagnostic purposes, a receiver operating characteristic (ROC) curve analysis (according to Metz, Semin Nucl Med, 1978, 8(4), 283-98) was performed. As Table 3 shows, the best sensitivity and specificity was obtained for MCP1, VEGF, and EGF. 
     The relative value of MCP1, EGF, and VEGF, as risk factors for classification as ill or healthy was tested for women and men. The results are shown in Table 4, and indicate that each of these markers independently associates with a significantly increased risk for being classified as ill. 
     
       
         
               
               
               
               
               
               
             
               
               
               
               
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
               
               
               
               
             
           
               
                   
                 TABLE 1 
               
             
             
               
                   
                   
               
               
                   
                   
                 Occupational 
                   
                   
                 Significant 
               
               
                   
                 Sick leave 
                 stress 
                 Healthy 
                 ANOVA 
                 pairwise 
               
             
          
           
               
                 Marker 
                 M 
                 SD 
                 M 
                 SD 
                 M 
                 SD 
                 F 
                 Df 
                 P 
                 comparisons 
               
               
                   
               
             
          
           
               
                 IL8 
                 5.4 
                 10.8 
                 3.3 
                 2.9 
                 3.1 
                 1.3 
                 2.98 
                 2,338 
                 .052  
                   
               
               
                 MCP1 
                 348.4 
                 126.7 
                 217.8 
                 92.6 
                 160.2 
                 85.7 
                 97.82 
                 2,338 
                 .000* 
                 1-2, 1-3, 2-3 
               
               
                 EGF 
                 117.0 
                 77.2 
                 70.6 
                 53.0 
                 29.4 
                 47.5 
                 56.16 
                 2,338 
                 .000* 
                 1-2, 1-3, 2-3 
               
               
                 VEGF 
                 30.9 
                 22.7 
                 18.4 
                 15.4 
                 10.3 
                 7.1 
                 41.24 
                 2,338 
                 .000* 
                 1-2, 1-3 
               
               
                 TSH 
                 1.8 
                 1.0 
                 2.4 
                 1.6 
                 2.4 
                 1.2 
                 11.11 
                 2,342 
                 .000* 
                 1-3 
               
               
                 Testosterone 
                 4.1 
                 1.5 
                 4.0 
                 1.8 
                 3.5 
                 1.4 
                 5.39 
                 2,330 
                 .005  
               
               
                   
               
               
                 *Significant at the .05 level 
               
               
                 Table 1: Biochemical markers in women experiencing different levels of stress, patients on long term sick leave for affective disorders (Sick leave; 1), health care personnel at risk for professional burnout (Burnout; 2) and healthy controls (Healthy; 3) employed in an IT company. Means (M),standard deviations (SD), and one-way ANOVA:s: F-ratios (F), degrees of freedom (Df) and P-value (P), (significance corrected according to Bonferroni&#39;s method), and post-hoc analysis according to Scheffe&#39;s method. 
               
             
          
         
       
     
     
       
         
               
               
               
               
             
               
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
               
             
           
               
                   
                 TABLE 2 
               
             
             
               
                   
                   
               
               
                   
                 Sick 
                   
                   
               
               
                   
                 leave 
                 Healthy 
               
             
          
           
               
                 Marker 
                 M 
                 SD 
                 M 
                 SD 
                 T 
                 Df 
                 P 
               
               
                   
               
             
          
           
               
                 IL8 
                 4.9 
                 5.0 
                 2.8 
                 0.9 
                 4.10 
                 178 
                 .000* 
               
               
                 MCP1 
                 404.9 
                 148.6 
                 176.3 
                 61.4 
                 14.10 
                 178 
                 .000* 
               
               
                 EGF 
                 119.5 
                 76.5 
                 26.0 
                 41.5 
                 10.51 
                 178 
                 .000* 
               
               
                 VEGF 
                 38.7 
                 29.5 
                 11.2 
                 8.5 
                 8.98 
                 178 
                 .000* 
               
               
                 TSH 
                 1.8 
                 1.3 
                 2.2 
                 0.9 
                 2.62 
                 174 
                 .010 
               
               
                 Testosterone 
                 19.6 
                 7.8 
                 23.3 
                 6.2 
                 3.44 
                 167 
                 .001* 
               
               
                   
               
               
                 *Significant at the .05 level 
               
               
                 Table 2: Biochemical markers in men experiencing different levels of stress, patients on long term sick leave for affective disorders (Sick leave), and healthy controls (Healthy) employed in an IT company. Means (M), standard deviations (SD), and independent T-tests) (significance corrected according to Bonferroni&#39;s method). 
               
             
          
         
       
     
     
       
         
               
               
               
               
               
               
             
               
               
               
               
               
               
             
           
               
                 TABLE 3 
               
               
                   
               
               
                 Gender 
                 Marker 
                 Area 
                 Cut-off 
                 Sensitivity 
                 Specificity 
               
               
                   
               
             
             
               
                   
               
             
          
           
               
                 Women 
                 MCP1 
                 0.886 
                 243.00 
                 0.85 
                 0.92 
               
               
                   
                 VEGF 
                 0.805 
                 7.80 
                 0.78 
                 0.85 
               
               
                   
                 EGF 
                 0.798 
                 68.00 
                 0.69 
                 1.00 
               
               
                   
                 TSH 
                 0.624 
                 1.80 
                 0.58 
                 0.69 
               
               
                   
                 Testosterone 
                 0.618 
                 3.73 
                 0.63 
                 0.65 
               
               
                 Men 
                 MCP1 
                 0.869 
                 226.00 
                 0.92 
                 0.82 
               
               
                   
                 EGF 
                 0.859 
                 30.00 
                 0.92 
                 0.80 
               
               
                   
                 VEGF 
                 0.817 
                 7.80 
                 0.78 
                 0.85 
               
               
                   
                 IL8 
                 0.801 
                 3.00 
                 0.87 
                 0.72 
               
               
                   
               
               
                 Table 3: Optimal cut-off, area under the ROC-curve (Area), and diagnostic sensitivity and specificity of statistically significant biochemical markers in women and men. 
               
             
          
         
       
     
     
       
         
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
             
           
               
                 TABLE 4 
               
               
                   
               
               
                 Gender 
                 Marker 
                 Beta 
                 Wald 
                 P 
                 OR 
                 95% CI 
               
               
                   
               
             
             
               
                   
               
             
          
           
               
                 Women 
                 MCP1 
                 3.55 
                 52.17 
                 0.000 
                 34.85 
                 13.30-91.35  
               
               
                   
                 EGF 
                 2.12 
                 18.02 
                 0.000 
                 8.35 
                 3.13-22.25  
               
               
                   
                 VEGF 
                 2.08 
                 18.99 
                 0.000 
                 8.02 
                 3.14-20.44  
               
               
                 Men 
                 MCP1 
                 3.64 
                 26.96 
                 0.000 
                 37.97 
                 9.62-149.83 
               
               
                   
                 EGF 
                 3.56 
                 25.39 
                 0.000 
                 35.09 
                 8.79-140.05 
               
               
                   
                 VEGF 
                 2.18 
                 11.64 
                 0.001 
                 8.85 
                 2.53-30.95  
               
               
                   
               
               
                 Table 4: Relative risks of being classified as ill, using the established cut-off points of MCP1, EGF and VEGF (Table 3). Multiple logistic regression analyses in men and women. OR signifies Observed risk, with 95 per cent confidence interval (95% CI)