Novel Diagnostic Method For Diagnosing Depression

TITLE: Novel diagnostic method for diagnosing depression FIELD OF THE INVENTION

The invention relates to the field of diagnostics, more specifically diagnosis of affective disorders, more specifically diagnosis of depression, by assaying for an psychiatric disease-marker.


Mood disorders are often called affective disorders, since affect or emotion is the external display of mood which is, however, felt internally. Mood disorders are defined as a variety of symptoms fitted into syndromes. These syndromes are a consent statement of the committees assigned with the nosology of psychiatric disorders. The Diagnostic and Statistical Manual of Mental Disorders (DSM) of the American Psychiatric Association (Table 1) is worldwide approved by psychiatrists and co-workers in the field of mental health as a valid diagnostic system.

Diagnosis both in clinical practice and in clinical research studies is based on these sets of specific signs and symptoms called a syndrome which can be fitted in axis one or two of the DSM. These criteria have helped to distinguish various mood disorders that may have different causes and that may require different clinical management. The most common mood disorder is the major depressive disorder which occurs as a single episode or in recurrent episodes. The latter is very similar to the bipolar mood disorder which is characterised by the occurrence of manic episodes besides depression.

Less severe but an often longer-lasting form of depression, i.e. over two years in duration and often unremitting, is dysthymia.

Several theories have been postulated in time describing the neurobiologic mechanisms involved in the development of mood disorders. The monoamine theory, the HPA-axis disregulation theory, the immune system disregulation theory and the neuroplasticity theory have been postulated in the past. All these theories are probably true and interrelated. Also, there may be a genetic predisposition and a reaction to stressors. The latter may even alter the genetic material thus making people more vulnerable for mood disorders.

There are no pathognomonic markers of depression, although this is an area of active research (Duffy A., 2000, Can. J. Psychiatr., 45:340-348).

Depressive disorders are associated with poor work productivity, as indicated by a 3- fold increase in the number of sick days in the month preceding the illness for workers with a depressive illness compared to coworkers who did not have a history of such an illness (Parikh, S.V. et al., 1996, J. Affect. Disord. 38:57-65; Kessler, R.C. et al., 1999, Health Aff. 18: 163-171). Depressive illnesses also affect family members and caregivers (Denihan, A. et al., 1998, Int. J. Geriatr. Psychiatr. 13:691-694), and there is increasing evidence that children of women with depression have increased rates of problems in school and with behaviour, and have lower levels of social competence and self-esteem than their classmates with mothers who do not have depression (Goodman, S.H. and Gotlib, I.H., 1999, Psychol. Rev. 106:458-490). Depression is the leading cause of disability and premature death among people aged 18 to 44 years, and it is expected to be the second leading cause of disability for people of all ages by 2020 (Murray, CJ. and Lopez, A.D., 1997, The Lancet 349: 1498-1504; Gredon, J.F., 2001, J. Clin. Psychiatr. 62:26-31).

Depressive illnesses have also been shown to be associated with increased rates of death and disability from cardiovascular disease (e.g. Pratt, L.A. et al., 1996,

Circulation 94:3123-3129, Bush, D.E. et al., 2001, Am. J. Cardiol. 88:337-341). Among 1551 study subjects without a history of heart disease who were followed for 13 years, the odds ratio for acute myocardial infarction among the subjects who had a major depressive episode was 4.5 times higher than among those who did not have a depressive episode. Among consecutive patients admitted to hospital with an acute myocardial infarction who had their mood measured with a standard depression rating scale, even those with minimal symptoms of depression had evidence of higher subsequent risk of death following their infarction and over the next 4 months. This risk was independent of other major risk factors, including age, ventricular ejection fraction and the presence of diabetes mellitus.

Surprisingly, for such a common disease there is little agreement on the association between age and onset. This is due to the fact that research is hampered by the absence of an unambiguous and universally agreed on set of diagnostic criteria and the fact that many of the studies have included patients already in the medical care system. It is well known that many people who meet the diagnostic criteria for depression do not seek treatment.

Despite its high prevalence, only one-third of all patients with depression receive adequate treatment (Judd, L.L. et al., 1996, Am. J. Psychiatry 153:1411-1417). The following are 4 common clinical errors that lead to diagnostic or treatment failures associated with depressive disorders:

• Insufficient questioning. Diagnostic failures occur when the patient is not asked questions that may elicit the symptoms of a mood disorder despite what should be a high index of suspicion based on its prevalence. The mnemonic "SIGECAPS" (sleep, mterest, guilt, energy, concentration, appetite, psychomotor, suicide) (Table 1) may be a useful clinical adjunct (i.e., 4 or more SIGECAPS for major depression, 2 or 3

SIGECAPS for dysthymia). • Failure to consult a family member. Owing to the cognitive distortions associated with the disease, it is not unusual for patients to minimize or exaggerate their symptoms. Thus, inpatients who are relatively new to one's practice, it is risky at best to make (or exclude) a diagnosis of depression without collateral information from a relative, such as a spouse or parent.

• Acceptance of a diagnosis of a mood disorder despite lack of diagnostic criteria (e.g., starting treatment for depression when only a "depressed mood" is present without the concomitant mental and physical symptoms [i.e., SIGECAPS]).

• Exclusion of a diagnosis or failure to start treatment for depression despite the associated symptom complex (e.g., "Of course you're depressed. Who wouldn't be depressed if these events were occurring in their life?" In other words, "explaining" the diagnosis rather than considering treatment options).

These clinical errors, coupled with the stigma associated with psychiatric conditions (Sirey, J.A. et al., 2001, Psychiatr. Serv. 52: 1615-1620), result in the underdiagnosis of maj or mood disorders .

Another major hypothesis in the field of psychotherapy at present, is that recognition and treatment of both unipolar and bipolar depressions, causing all symptoms to remit for long periods of time, might prevent progression of the disease to more difficult states, emphasising that early recognition of mood disorder subtype is of great importance.

Taken all these data together, it is clear that there exists a major need for a reliable diagnosis of depression, or, alternatively, an assay that can confirm a diagnosis on basis of the SIGECAPS criteria. Current theories of depression are complex and Fig. 1 outlines some of these theories (Duman, R.S. et al., 1997, Arch. Gen. Psychiatry 54:597-608; Manji, H.K. et al., 2000, MoI. Psychiatry 5:578-593). We are now aware that "long-term" (i.e., 30 days) antidepressant treatment results in sustained activation of cyclic adenosine 3-5- monophosphate (cAMP) in specific brain regions. Protein kinase A, which is stimulated by cAMP, phosphorylates the cAMP regulatory element binding protein. This protein then regulates and activates specific target genes, including brain-derived neurotrophic factor (BDNF), a neuroprotective factor that results in hippocampal nerve growth (Fig. 1). Psychological stress, important in the pathogenesis of depression, can decrease the production of BDNF and result in hippocampal neuronal atrophy. Furthermore, a series of brain-imaging studies consistently showed reduced neuronal activity in the dorsolateral prefrontal cortex that covaried with the severity of the depression (i.e., the more severe the depression, the larger the prefrontal deficits) (Drevets, W.C., 1998, Ann. Rev. Med. 49:341-361). Thus, an updated hypothesis on the development of a depressive disorder might posit that stress-induced vulnerability in genetically susceptible people may induce a cascade of intracellular neuronal mechanisms that increase or decrease specific neurotrophic factors necessary for the survival and function of specific brain neurons. Furthermore, not only antidepressants but also electroconvulsive therapy (Vaidya V.A. et al., 1999, Neuroscience 89: 157- 166) and depression-focused psychotherapy (Thase, M. E., 2001, Arch. Gen.

Psychiatry 58:651-652) can affect neuronal growth and regional brain metabolism. In 1982, brain-derived neurotrophic factor (BDNF), the second member of the "neurotrophic" family of neurotrophic factors, was shown to promote survival of a subpopulation of dorsal root ganglion neurons, and subsequently purified from pig brain (Barde, Y.A. et al,, 1982, EMBO J. 1:549-533).

Brain-derived neurotrophic factor (BDNF), a 27-kDa noncovalently linked homodimer with subunits of ^ 13.5 kDa as viewed by SDS-PAGE, is thought to be primarily produced in the central nervous system. The level of BDNF in pooled human sera was estimated to be approximately 15 ng/ml as determined by an enzyme- linked immunosorbant assay. There is an approximately 200-fold increase in the levels of BDNF in serum relative to plasma. Results from experiments using differential centrifugation suggest that the source of this increase is due to release from platelets. (Rosenfeld RD et al., 1995, Protein Expr. Purif. 6:465-471). It is known that BDNF exerts various effects on the nervous system such as neuronal outgrowth, differentiation, synaptic connectivity and neuronal repair (Lindsay, R.M. et al., 1994, Trends Neurosci. 17:182-189; and Lewin, G.R. and Barde, Y.A., 1996, 19:289-317).

Although BDNF has mostly been studied in the nervous system, large quantities have also been found in non-neuronal cells and particularly in the human platelet

(Yamamoto and Gurney, 1990, J. Neurosci. 10:3469-3478), a blood cell often used as a serotonin (5HT) neuronal model. The source and the function of platelet BDNF remains unknown, but it has been demonstrated that platelet BDNF is massively released in serum upon platelet activation in a similar manner to that of platelet 5HT (Radka et al., 1996, Brain Res. 709:122-130). Furthermore, a complete passage of intact BDNF across the blood-brain barrier by a high-capacity and saturable transport system, as well as its efflux from brain to blood, has been reported (Pan, W. et al., 1998, Neuropharmacol. 37:1553-1561). Finally, a positive correlation between cortical and serum BDNF levels has been observed in rats (Karege, F. et al., 2002, Neurosci. Lett. 328:261-264).

Studies in animals on depression and stress revealed lower BDNF mRNA levels (Russo-Neustadt et al., 2001, Behav. Brain Res. 120:87-95; and Smith, M.A. et al., 1995, J. Neurosci. 15:1768-1777). Similarly low levels of BDNF were demonstrated in patients with major depressive disorder who were antidepressant-free (Karege F. et al., 2002, Psychiatry Res. 109: 143-148 and Karege F. et al., 2002, Neurosci. Lett. 328:261-264) or naϊve (Shimuzu et al., 2003, Biol. Psychiatry 54:70-75). Further, BDNF levels increased with chronic antidepressant treatment (Gonul et al., 2005, Eur. Arch. Psychiatry Clin. Neurosci. 255:267-268; and Aydemir et al., 2005, Prog.

Neuropsychopharmacol. Biol. Psychiatry 29:261-265). Also supporting its possible involvement with major depressive disorder, in a post-mortem study, Chen et al.

(2001, Biol. Psychiatry 50:260-265) observed an increase in the hippocampal BDNF immunoreactivity in subjects who had been under antidepressant medication. In addition, Shimuzu et al. (2003) detected a negative correlation between the severity of depression and the serum BDNF levels. Further, in the same study, the response to the treatment was correlated with the increase in BDNF level as well. The findings of Aydemir et al. (2006, Biol. Psychiatry 30:1256-1260) have indicated that the BDNF levels were lower in antidepressant naϊve patients than in healthy controls and that they increased during the treatment with S-citalopram. These results are indicative of the effect of S-citalopram on neuroplasticity and depression, suggesting that BDNF might have an important role in depression.

Recent studies (Matrisciano, 2009, 43:247-254) have implicated brain-derived neurotrophic factor (BDNF) in the pathophysiology of depression and the activity of antidepressant drugs. Serum BDNF levels are lower in depressed patients, and increase in response to antidepressant medication. However, how BDNF responds to different classes of antidepressant drugs is unknown. Serum BDNF levels in 21 patients with major depressive episode treated with sertraline, escitalopram, or venlafaxine and 20 healthy controls were assessed. Serum samples were collected between 10 a.m. and 12 p.m. at baseline, 5 weeks, and 6 months of treatment. BDNF levels were measured via immunoassay. The severity of symptoms and response to treatment were assessed by the Hamilton rating scales for depression (HRSD).

Baseline serum BDNF levels were significantly lower in depressed patients compared to controls. Sertraline increased BDNF levels after 5 weeks and 6 months of treatment. Venlafaxine increased BDNF levels only after 6 months. Escitalopram did not affect BDNF levels at either time point. A significant negative association was found between percentage increase in BDNF levels and percentage decreased in HRSD scores after 6 months of treatment. These results suggest that different antidepressant drugs have variable effects on serum BDNF levels. This is true even though the three different drugs were equally effective in relieving symptoms of depression and anxiety (Matrisciano, 2009).

Lee and Kim (2008, Neuropsychobiol. 57:194-199) tested the hypothesis that BDNF might be a peripheral marker for the mechanism of action of antidepressant agents in humans. Thirty-two patients meeting the DSM-IV criteria for major depressive disorder and 50 normal control subjects were recruited for this study. Plasma BDNF levels and Hamilton Depression Rating Scales were measured at baseline and 6 weeks after antidepressant administration. At baseline, the mean plasma BDNF level was lower in the depressed patients (698.1 +/- 537.7 pg/ml) than in the control subjects (830.7 +/- 624.8 pg/ml), although the difference was not statistically significant (p = 0.33). The plasma BDNF levels in depressed patients significantly increased from 698.1 +/- 537.7 to 1,028.9 +/- 744.5 after 6 weeks of antidepressant treatment (p = 0.01). Moreover, plasma BDNF levels were significantly increased after 6 weeks of treatment in the responder group, while there was no statistically significant change in the unresponsive group. These results suggest that the therapeutic response after antidepressant administration might be attributable to the increase in BDNF levels. BDNF may play a critical role in the action mechanism of antidepressant drugs.

Further studies with a larger number of subjects are needed to verify these findings. Yet, until now it has seemed impossible to build a reliable detection method of mood disorders using a BDNF assay. SUMMARY OF THE INVENTION

Surprisingly, the present inventors have discovered that BDNF is detectable in urine and that BDNF levels in urine indicates the presence of mood disorders. Even more surprising is that the BDNF levels in urine are increased in patients suffering from a mood disorder in respect of the BDNF levels of healthy controls. This is even more surprising because the serum levels of BDNF show the opposite effect.

Thus, the invention relates to a method for the diagnosis of a mood disorder comprising:

a. taking a urine sample of a subject;

b. measuring the content of brain derived neurotrophic factor (BDNF) in said sample; and

c. diagnose the mood disorder if the concentration of BDNF is higher than in control healthy subjects.

More specifically, in such a method said mood disorder is diagnosed if the urine level of BDNF is higher than about 80 pg/ml, preferably higher than about 90 pg/ml, more preferably higher than about 100 pg/ml, even more preferably higher than about 100 pg/ml and most preferably higher than about 120 pg/ml.. Preferably the mood disorder is depression, chosen from dysthymia, endogenous depression, reactive depression, minor depression, major depression, psychotic depression, neurotic depression, unipolar depression and bipolar depression, most preferably major depression.

Further, the invention comprises a method to determine the influence of

antidepressant therapy in a subject comprising:

a. Performing an assay method according to the invention;

b. Providing the subject with antidepressant therapy;

c. Repeat step a) with regular intervals during said treatment; and d. Register any difference in the concentration of the measured compound in the urine.

Also the invention comprises a method to monitor the progress of a mood disorder in a subject comprising performing a method according to the invention. Further, the invention also relates to the use of BDNF in the diagnosis and monitoring of progression of a mood disorder. LEGENDS TO THE HGURES

Fig. 1. A molecular and cellular model for the action of antidepressant treatments and the pathophysiology of stress-related disorders. This model of the hippocampus shows the major cell types in the hippocampus and how stress and antidepressant treatments may influence CA3 pyramidal cells. The 3 major subfields of the hippocampus (CA3 and CAl pyramidal cells and dentate gyrus granule cells) are connected by the mossy fibre and Schaffer collateral pathways. Recent studies demonstrate that chronic stress decreases the expression of brain-derived neurotrophic factor (BDNF) in the hippocampus. This may contribute to the atrophy or death of neurons in the CA3 pyramidal cell layer of the hippocampus. Long-term elevation of glucocorticoid levels is also known to decrease the survival of these neurons. Other types of neuronal insult, such as hypoxia-ischemia, hypoglycemia, neurotoxins and viral infections, may also cause atrophy or damage of neurons and thereby make a person vulnerable to subsequent insults. These types of interaction may underlie the observations of decreased function and volume of hippocampus in patients with affective disorders and may explain the selective vulnerability of certain people to become depressed. Long-term antidepressant treatments increase the expression of BDNF as well as tyrosine kinase receptor B (trkB) and prevent the down-regulation of BDNF elicited by stress. This may increase the growth or survival of neurons, or help repair or protect neurons from further damage. Increased expression of BDNF and trkB seems to be mediated by the sustained elevation of the serotonin and norepinephrine (NE) systems and the cyclic adenosine monophosphate cascade. Normalization of glucocorticoid levels by long-term antidepressant treatments may also contribute to the recovery of C A3 neurons. (Adapted from Duman et al., supra).


The most surprising finding of this invention is the fact that the concentration of BDNF in urine is increased in patients with a mood disorder, while the serum concentration of BDNF is decreased in those patients, with respect to the

concentration levels in control patients. The reason for this paradoxical inconsistency is currently unknown, and only speculative guesses can be made. One of the possible explanations is that recent research has indicated that there are several isoforms of BDNF (Liu, Q.-R. et al., 2005, Am. J. Med. Genet. 134B:93-103; Pruunsild, P. et al., 2007, Genomics 90:397-406). It could be speculated that different isoforms have been measured in the various studies, or that the isoform in serum is existent in di- or trimerized form, whereas the isoform found in urine exists only as monomer.

A further surprising finding of this invention is that the concentration of BDNF in urine can serve as an assay for mood disorders. This is surprising because it has been established that the serum level of BDNF, although it is correlated with the presence or the severity of a mood disorder, is not a reliable marker that can be used for diagnosis of a mood disorder.

A special advantage of an assay wherein BDNF is detected in the urine is that no invasive techniques are necessary to obtain a sample from the patient. In principle, it would even be possible to perform the assay outside a clinical setting, i.e. at the subject's own premises. Detection of BDNF can take place in any manner that would be known to a person of skill in the art. Several assay kits (for detection of BDNF in serum or brain) are commercially available (e.g. from Antigenix America Inc, Promega), and these can easily be adapted for detection of BDNF in urine. In principle most of these assays rely on an immunochemical reaction between the BDNF in the sample and a BDNF-antibody (e.g. detectable through an ELISA assay). However, the invention is not limited to such an embodiment: detection of BDNF can also take place by other analytical methods, such as chemical analytical methods (like mass spectrometry, MALDI-TOF, etc.), receptor-based assays, using the BDNF receptor as analytical tool, etc. The assays that are useful in the present invention are preferably quantitative assays, in which the concentration of BDNF in the sample can be determined. This can - in principle - be achieved with all of the above mentioned detection methods.

Most preferred is an assay based on an immunochemical reaction between the

BDNF in the sample and a BDNF-antibody which is made detectable and quantifiable through an ELISA assay.

Preferably, the assay also includes a simultaneous assay for creatinine.

Creatinine is one of the byproducts of protein metabolism. Under normal conditions it is present in the blood and is excreted as a final metabolite in the urine. Urine creatinine levels are routinely used as part of kidney function diagnosis. In particular, altered creatinine levels in urine are indicative of kidney diseases such as acute or chronic nephritis, nephrosis, and the like. Because normative values for creatinine excretion have been established, urine creatinine levels are also useful for correction of assays for other compounds, as they document the adequacy of the urine collection for such assays. In particular, the creatinine correction can be used to correct for urine dilution, thus giving a possibility to standardize measured concentrations irrespective of the water content of the urine and/or the time of the day when the urine was produced. Further, changes in renal function which influence rates of excretion, can be corrected by measurement of creatinine in urine.

As will be clear from the experimental results, there is a clear difference between urine BDNF levels in control (healthy) patients and in subjects suffering a mood disorder, especially subjects suffering from depression, more preferably major depression. Patients suffering from a mood disorder generally have a BDNF concentration in the urine that is higher than about 80 pg/ml, preferably higher than about 90 pg/ml, more preferably higher than about 100 pg/ml, even more preferably higher than about 100 pg/ml and most preferably higher than about 120 pg/ml., whereas healthy persons have a BDNF urine concentration below 50 pg/ml. It is envisaged that subjects that have a BDNF urine concentration between 50 and 100 pg/ml are at risk of developing a mood disorder. Generally it can be said, that the urinary BDNF concentration pairs with the Hamilton score of a patient: the higher the Hamilton score, the higher the urinary BDNF concentration. A Hamilton score of less or equal to 7 is scored by healthy persons, a score of 7-17 indicates mild depression, a score of 18-24 medium depression and a score of more than 24 indicates severe depression. Thus, by measuring the BDNF concentration in the urine, it can easily be established if a person is suffering from a mood disorder. From preliminary tests that have been performed, it can even be learnt that subjects that do not have clear clinical symptoms, i.e. subjects that do not know or do not realise that they suffer from a mood disorder, already have high urinary BDNF levels. Indeed one of the subjects with such high levels was clinically diagnosed as being depressive a few weeks after the assay proved positive. Further, it has appeared that subjects which have a familial history of mood disorders (e.g. depressive parents or other relatives) have a relatively high urinary BDNF level, indicating that they are at risk of also developing a mood disorder.

One of the main advantages of the present invention is that it provides an easy and reliable way to monitor progress of the disease and/or effectiveness of a therapy. To this end, the BDNF values for a subject are determined at a certain moment (null- value) and after an amount of time this procedure is repeated. Over the time, several repeat measurements can be performed. In the mean time therapy can e.g. be started or changed. Change(s) in the levels of BDNF will then indicate the effectiveness of the therapy or the progress of the disease. For instance, as is shown in the Examples, an intial high concentration of BDNF in the urine, which after therapy has lowered, will mean that the therapy is - at least partially - effective. No change in the urine BDNF level, or even an increase, indicates that the disease is progressing and that a therapy does not provide improvement in the disease state.

Thus, in this way, in a non- invasive and easy manner, the progress of the disease can be monitored.

In the below examples specific embodiments of performing the invention will be explained in more detail. However, a person of skill in the art will easily find other ways of performing the assays within the scope the invention.


Example 1

Identification of major depression (MD) marker BDNF (MD patients either on medication or not and healthy control individuals).

Experimental Procedures Subjects

Urine samples were collected from both MD patients and healthy individuals. All subjects provided informed consent prior to participation. The urine samples were stored at 4°C.

For quantifying BDNF in the urine samples, an ELISA test (BDNF EMax®

Immunoassay System Kit, Promega Corp.) was used: flat-bottom 96-well plates were coated with Anti-BDNF monoclonal antibody to bind soluble BDNF present in the urine samples. The captured BDNF was bound to a second, specific, BDNF polyclonal antibody (pAb). After washing, the amount of specifically bound pAb was then detected using a species-specific anti-IgY antibody conjugated to horseradish peroxidase (HRP) as tertiary reactant. Unbound conjugate was removed by washing, and following an incubation with a chromogenic substrate, the color change was measured. The amount of BDNF in the test solution was proportional to the color generated in the HRP oxidation-reduction reaction. According to this technique total free BDNF was measured.

In total, 18 MD patients and 25 healthy individuals were recruited. The BDNF levels in their urine samples were measured. The mean BDNF concentration in MD urine samples was 244,5 ± 140,8 pg/ml (range 93,1 pg/ml - 980,0 pg/ml) whereas in healthy urine samples this was 48,3 ± 24,1 pg/ml (range 16,0 pg/ml - 92,0 pg/ml). Some of the MD patients were on antidepressant treatment. It appeared that for those patients the BDNF values were generally lower than for patients that did not receive treatment (or the levels of those persons for whom not yet the diagnosis depression was confirmed). Example 2

Monitoring urinary BDNF levels over time. From several of the above patients multiple assays were performed at various time intervals. From the data of patient 2, it can be derived that the Hamilton score follows the trend of the urine levels of BDNF. Thus, the BDNF assay according to the invention can replace the Hamilton score for following effects of treatment. In some cases also the serum BDNF levels were measured, and it turns out that these gave no consistent picture. This again illustrates the usefulness of urinary BDNF assays over serum BDNF assays.

For patient 1 no objective (Hamilton) depression scale score data are available. However, this patient was already on antidepressant medication for more than 6 months at the beginning of the BDNF measurements and medication continued at least until the last measurement. It is clear that during therapy BDNF levels in the urine lowered and the BDNF values correlated well with the subjective well being of the patient. At the end of the measuring period, the patient did not show any clinical symptoms anymore.


1 A method for the diagnosis of a mood disorder comprising:

a.taking a urine sample of a subject;

b.measuring the content of brain derived neurotrophic factor (BDNF) in said sample; and

c.diagnose the mood disorder if the concentration of BDNF is higher than in control healthy subjects.

2 Method according to claim 1, wherein the said mood disorder is diagnosed if the urine level of BDNF is higher than about 80 pg/ml, preferably higher than about 90 pg/ml, more preferably higher than about 100 pg/ml, even more preferably higher than about 100 pg/ml and most preferably higher than about 120 pg/ml..

3 Method according to claim 1 or claim 2, wherein the mood disorder is depression, chosen from dysthymia, endogenous depression, reactive depression, minor depression, major depression, psychotic depression, neurotic depression, postnatal depression, burn out, overstrain, unipolar depression and bipolar depression, most preferably major depression.

4 Method according to any of the previous claims wherein the concentration of BDNF is calculated using a creatinine correction. 5 Method to determine the influence of antidepressant therapy in a subject comprising: a. performing a method according to any of claims 1-4;

b.treating the subject with antidepressant(s) therapy;

c.repeat step a) with regular intervals during said treatment; and

d.register any difference in the concentration of the measured BDNF in the urine. 6 Method to monitor the progress of a mood disorder in a subject comprising performing a method according to any of claims 1-4.

7 Use of BDNF in the diagnosis and monitoring of progression of a mood disorder.

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