FIELD OF INVENTION

The present invention relates to peripheral measures of brain inflammation, markers therefor, and methods and uses thereof for diagnosis and/or treatment.

BACKGROUND

Psychiatric and neurological diseases are burdensome to society since they affect one in four people and are often treatment resistant (1). Greater microglial activation, an important process that is a key response to neuronal damage and participates in inflammatory responses; includes morphological changes in microglia of an enlarged cell body; and shortened thickened dendrites or amoeboid shape. This occurs across many neuropsychiatric illnesses including major depressive disorder, obsessive compulsive disorder, and neurodegenerative diseases (2-8). Increased density of activated microglia may be a promising target for immune modulating treatments to alter microglial function away from potentially harmful roles like producing reactive oxygen species, prostaglandins, and proteinases; and towards more curative roles like enhancing release of neurotrophic factors, promoting vascularization; and phagocytosing cellular debris (6, 9). However, a barrier for human clinical trials of investigational treatments targeting activated microglia is that there is heterogeneity in the density of activated microglia among individuals with neuropsychiatric diseases, which may be attributable to multiple factors including stage of illness, comorbid disease and, most likely, multiple etiological phenotypes (2, 3); thereby limiting optimal matching of cases to treatment.

No easily applicable, replicable, low cost measure indicative of microglial activation has been developed in the field. Although positron emission tomography (PET) imaging of the translocator protein (TSPO) replicates well in disease (2-8), and other radiotracers targeting P2X7, P2Y12 and CSF 1 receptors (10, 11) are being advanced, these methods are typically expensive, use scarce resources, and typically need arterial blood sampling for kinetic modeling because microglia are ubiquitous throughout the brain. Another direction is cerebrospinal fluid concentration of products consequent to greater indoleamine 2,3-dioxygenase activity and/or cytokines but the associated lumbar puncture is difficult for many patients (12, 13). In regards to magnetic resonance imaging (MRI) methods with paramagnetic probes like Cd-bis-5-HT-DTPA that measure myeloperoxidase activity across activated microglia, neutrophils and monocytes, their sensitivity to detect microglial activation in neuropsychiatric disease is not yet established and it is possible that their application may be restricted to disease states with substantial blood brain barrier breakdown (14).

PCT publication no. WO2016/112467 (47), entitled“Peripheral Measure of Central Brain Inflammation, Markers Therefor and Uses Thereof’, describes previously developed methods for determining the level of microglial activation in the brain of a subject, and is herein incorporated by reference in its entirety.

Alternative, additional, and/or improved markers, predictive measures, methods, and/or kits for determining microglial activation, diagnosing mental illness, and/or treating mental illness are desirable. SUMMARY OF INVENTION

Provided herein are methods for analyzing a sample, such as a blood, serum, or plasma sample, from a subject to determine a level of microglial activation in the brain of the subject, which may be used in the diagnosis, monitoring, and/or treatment of a neuropsychiatric illness, for example. A number of appealing markers and/or predictive measures are provided herein for evaluating levels of translocator protein distribution volume (TSPO VT), microglial activation levels, brain inflammation levels, and/or neuropsychiatric illness state of the subject. Among the markers and/or predictive measures described herein, -ln[CRP], [1.071*-ln(CRP) - 0.184*BMI], ln([TNFa]/[CRP]), ln([PGE2]/[CRP]), and ln([PGF2 _a ]/[CRP]) predictive measures are extensively studied in Examples provided herein. Results indicate that -ln[CRP], [1.071*- ln(CRP) - 0.184*BMI], ln([TNFa]/[CRP]), and ln([PGE2]/[CRP]) may be particularly appealing predictive measures, with -ln[CRP] and [1.071*-ln(CRP) - 0.184*BMI] predictive measures providing the best overall results in these studies.

In an embodiment, there is provided herein a method for determining a level of microglial activation in the brain of a subject, said method comprising: measuring a concentration of C-Reactive Protein (CRP) in a sample obtained from the subject; using the concentration of CRP to provide a predictive measure indicative of the level of microglial activation in the brain of the subject; determining the level of microglial activation in the brain of the subject from the predictive measure; and optionally, recommending a treatment option and/or administering a treatment to the subject based on the level of microglial activation in the brain on the subject. In another embodiment of the above method, the predictive measure may comprise a natural logarithm of the concentration of CRP.

In yet another embodiment of any of the above method or methods, the predictive measure may comprise:

-ln[CRP] In still another embodiment of any of the above method or methods, a threshold cut-off for -ln[CRP] of about 0, 0.4, 0.6, 0.8, or 1.2 may be used for identifying increased microglial activation in the brain of the subject.

In still another embodiment of any of the above method or methods, body mass index (BMI) or MCP-1 level of the subject may also be used to provide the predictive measure. In yet another embodiment of any of the above method or methods, the predictive measure may comprise a linear combination of-ln[CRP] and BMI.

In another embodiment of any of the above method or methods, the predictive measure may comprise: [1.071*-ln(CRP) - 0.184*BMI]

In another embodiment of any of the above method or methods, a threshold cut-off for [1.071*-ln(CRP) - 0.184*BMI] of about -3.5 may be used for identifying increased microglial activation in the brain of the subject. In still another embodiment of any of the above method or methods, the method may further comprise: measuring a concentration of tumor necrosis factor alpha (TNFa) in the sample obtained from the subject; and using the concentration of CRP and the concentration of TNFa to provide the predictive measure indicative of the level of microglial activation in the brain of the subject.

In yet another embodiment of any of the above method or methods, the predictive measure may comprise a ratio of the concentrations of TNFa and CRP.

In another embodiment of any of the above method or methods, the predictive measure may comprise a natural logarithm of a ratio of the concentrations of TNFa and CRP. In yet another embodiment of any of the above method or methods, the predictive measure may comprise: ln([TNFa]/[CRP]).

In still another embodiment of any of the above method or methods, a threshold cut-off for ln([TNFa]/[CRP]) of about 1 to 2.1 for example, but not limited to 1.9 to 2.1 may be used for identifying increased microglial activation in the brain of the subject.

In another embodiment of any of the above method or methods, the method may further comprise: measuring a concentration of prostaglandin E2 (PGE2) in the sample obtained from the subject; and using the concentration of CRP and the concentration of PGE2 to provide the predictive measure indicative of the level of microglial activation in the brain of the subject.

In still another embodiment of any of the above method or methods, the predictive measure may comprise a ratio of the concentrations of PGE2 and CRP. In yet another embodiment of any of the above method or methods, the predictive measure may comprise a natural logarithm of a ratio of the concentrations of PGE2 and CRP.

In another embodiment of any of the above method or methods, the predictive measure may comprise: ln([PGE ]/[CRP]). In still another embodiment of any of the above method or methods, a threshold cut-off for ln([PGE2]/[CRP]) of about 5.8 to 7.3, for example, but not limited to 6.9 to 7.3 may be used for identifying increased microglial activation in the brain of the subject.

In yet another embodiment of any of the above method or methods, the method may further comprise: measuring a concentration of prostaglandin F2 alpha (PGF2 _a ) in the sample obtained from the subject; and using the concentration of CRP and the concentration of PGF2« to provide the predictive measure indicative of the level of microglial activation in the brain of the subject.

In still another embodiment of any of the above method or methods, the predictive measure may comprise a ratio of the concentrations of PGF2 _« and CRP.

In another embodiment of any of the above method or methods, the predictive measure may comprise a natural logarithm of a ratio of the concentrations of PGF2 _« and CRP.

In another embodiment of any of the above method or methods, the predictive measure may comprise: ln([PGF _2a ]/[CRP]).

In still another embodiment of any of the above method or methods, the subject may be a subject having, or suspected of having, major depressive disorder (MDE) or obsessive compulsive disorder (OCD).

In another embodiment of any of the above method or methods, the predictive measure may be indicative of the level of microglial activation in the brain of the subject by predicting a translocator protein distribution volume (TSPO V _T ) of the subject.

In another embodiment of any of the above method or methods, the sample may comprise a blood sample, a serum sample, or a plasma sample obtained from the subject.

In yet another embodiment of any of the above method or methods, the subject may be a subject having, or suspected of having, or whom has exhibited one or more symptoms of, a neuropsychiatric illness.

In still another embodiment of any of the above method or methods, the neuropsychiatric illness may be characterized by an increased level of microglial activation in the brain.

In another embodiment of any of the above method or methods, the subject may be a subject having, or suspected of having, or whom has exhibited one or more symptoms of, depression, obsessive compulsive disorder, or both.

In still another embodiment of any of the above method or methods, the subject may be a subject having, or suspected of having, or has exhibited one or more symptoms of, major depressive disorder or obsessive compulsive disorder.

In yet another embodiment of any of the above method or methods, the subject may be a subject having, or suspected of having, or has exhibited one or more symptoms of, medication free major depressive episodes (MDE) secondary to major depressive disorder (MDD), treatment resistant major depressive episodes secondary to major depressive disorder, or medication free obsessive compulsive disorder (OCD). In another embodiment of any of the above method or methods, the CRP may be quantified by mass spectrometry, HPLC, immunoassay, radioimmunoassay, gas chromatography-mass spectrometry or other chromatographic or non-chromatographic procedure.

In yet another embodiment of any of the above method or methods, the microglial activation may be in the prefrontal cortex or dorsal caudate.

In still another embodiment of any of the above method or methods, the subject may be a subject having, or suspected of having, or has exhibited one or more symptoms of, medication free major depressive episodes (MDE) secondary to major depressive disorder (MDD) or treatment resistant major depressive episodes secondary to major depressive disorder, and the microglial activation may be in the prefrontal cortex.

In another embodiment of any of the above method or methods, the subject may be a subject having, or suspected of having, or has exhibited one or more symptoms of, OCD and the microglial activation may be in the dorsal caudate.

In still another embodiment of any of the above method or methods, the predictive measure, or the level of microglial activation, may be compared with that of one or more control subjects or groups.

In another embodiment of any of the above method or methods, the one or more control subjects or groups may comprise one or more healthy controls, one or more controls confirmed as having a neuropsychiatric illness, or both.

In still another embodiment of any of the above method or methods, the level of microglial activation may be an index of brain inflammation.

In yet another embodiment of any of the above method or methods, an increased level of microglial activation may identify or assist in identifying the subject as having depression, a major depressive episode (MDE), a major depressive disorder (MDD), obsessive compulsive disorder (OCD), or other neuropsychiatric illness, or as being prone to developing depression, MDE, MDD, OCD, or other neuropsychiatric illness, or brain inflammation associated therewith. In another embodiment of any of the above method or methods, the method may comprise recommending treatment, or treating, the subject with medication, non-medicinal therapy, or a combination thereof; monitoring the subject; counseling the subject; testing or screening the subject for clinical depression, major depressive episode, major depressive disorder, obsessive compulsive disorder (OCD) or any other neuropsychiatric illness; testing the sample for one or more additional genetic markers, nucleotide sequences, proteins, or metabolites; or any combination thereof.

In still another embodiment of any of the above method or methods, treating the subject with medication may comprise administering one or more anti-inflammatory agents, antidepressants, antipsychotics, mood stabilizers, anticonvulsants, antianxiolytics, steroids, or any combination thereof.

In still another embodiment of any of the above method or methods, the medication may comprise one or more glucocorticoids, phosphodiesterase inhibitors, cox-2 inhibitors, acetaminophen, non-steroidal anti-inflammatory agents, statins, neurokinin antagonists, thiazolidinediones, toll receptor antagonists/agonists, tetracycline antibiotics such as minocycline, cytokine antagonists such as infliximab, P2X7 receptor binding medications, riluzole, Janus kinase inhibitors, phospholipase inhibitors, antibody directed therapies for immune system targets, Monoamime Oxidase Inhibitor (MAOIs) such as tranylcypromine, phenelzine, isocarboxazid and the like, Tricyclic Antidepressants (TCAs) such as clomipramine, amitriptyline, desipramine, nortriptyline, doxepin, or trimipramine, Selective Serotonin Reuptake Inhibitors (SSRIs) such as citalopram, escitalopram, fluvoxamine, paroxetine, fluoxetine, sertraline or other common medications such as duloxetine, venlafaxine, mirtazapine, bupropion, trazodone, clozapine, lithium, ketamine, or any pharmaceutically acceptable salt or solvate thereof, of any combinations thereof. In still another embodiment of any of the above method or methods, the method may comprise treating the subject with, or identifying the subject as a candidate for treatment with, an anti inflammatory agent, a P2X7 antagonist, an indolamine 2,3 dioxygenase inhibitor, minocycline, simvastatin, or any combinations thereof. In another embodiment of any of the above method or methods, the method may comprise treating the subject with, or identifying the subject as a candidate for treatment with, celecoxib.

In another embodiment, there is provided herein a kit comprising any one or more of:

C-Reactive Protein (CRP); tumor necrosis factor alpha (TNF a); prostaglandin E2 (PGE2); prostaglandin F ₂ alpha (PGF _2a ); one or more diagnostic agents or reagents for quantifying or assisting in quantifying CRP, TNF a, PGE2, PGF2 _a , or any combination thereof; a container; instructions for performing any of the method or methods described herein; or any combinations thereof.

In another embodiment of the above kit, the one or more diagnostic agents or reagents may comprise one or more antibodies or antibody derivatives or an agent, component, diluent or buffer which can be employed in mass spectrometry, HPLC, immunoassay, radioimmunoassay, gas chromatography-mass spectrometry or other chromatographic or non-chromatographic procedure to quantify CRP, TNFa, PGE2, PGF2a, or any combination thereof.

In another embodiment, there is provided herein a method for treating a subject having major depressive episode (MDE) and/or major depressive disorder (MDD), said method comprising: determining a level of microglial activation in the brain of the subject using a method as defined herein; and identifying the subject as a candidate for treatment with an anti-inflammatory agent where an elevated level of microglial activation is determined and treating the subject with the anti-inflammatory agent.

In another embodiment, there is provided herein a use of an anti-inflammatory agent for treating major depressive episode (MDE) and/or major depressive disorder (MDD), wherein the anti inflammatory agent is for administration to a subject in need thereof, the subject having an elevated level of microglial activation. In certain embodiments, the subject may be a subject determined as having an elevated level of microglial activation by any of the method or methods as described herein.

In another embodiment, there is provided herein a use of an anti-inflammatory agent in the manufacture of a medicament for treating major depressive episode (MDE) and/or major depressive disorder (MDD), wherein the medicament is for administration to a subject in need thereof, the subject having an elevated level of microglial activation. In certain embodiments, the subject may be a subject determined as having an elevated level of microglial activation by any of the method or methods as described herein.

In another embodiment, there is provided herein an anti-inflammatory agent for use in treating major depressive episode (MDE) and/or major depressive disorder (MDD), wherein the anti inflammatory agent is for administration to a subject in need thereof, the subject having an elevated level of microglial activation. In certain embodiments, the subject may be a subject determined as having an elevated level of microglial activation by any of the method or methods as described herein.

In another embodiment of any of the above method or methods, the anti-inflammatory agent may comprise celecoxib.

In another embodiment of the above method or methods, the subject may be identified as a candidate for treatment with the anti-inflammatory agent when the level of microglial activation, or level of TSPO V _T , is determined to be elevated by at least about 30% versus a healthy control.

In another embodiment, there is provided herein a method for treating a subject having major depressive episode (MDE) and/or major depressive disorder (MDD), or obsessive compulsive disorder (OCD), or any combination thereof, said method comprising: treating the subject with an anti-inflammatory agent; wherein the subject is a subject having an elevated level of microglial activation in the brain according to a method as described herein.

In another embodiment, there is provided herein a use of an anti-inflammatory agent for treating major depressive episode (MDE) and/or major depressive disorder (MDD), or obsessive compulsive disorder (OCD), or any combination thereof, wherein the anti-inflammatory agent is for administration to a subject in need thereof, the subject having an elevated level of microglial activation in the brain. In certain embodiments, the subject may be a subject determined as having an elevated level of microglial activation by any of the method or methods as described herein.

In another embodiment, there is provided herein a use of an anti-inflammatory agent in the manufacture of a medicament for treating major depressive episode (MDE) and/or major depressive disorder (MDD), or obsessive compulsive disorder (OCD), or any combination thereof, wherein the medicament is for administration to a subject in need thereof, the subject having an elevated level of microglial activation in the brain. In certain embodiments, the subject may be a subject determined as having an elevated level of microglial activation by any of the method or methods as described herein.

In another embodiment, there is provided herein an anti-inflammatory agent for use in treating major depressive episode (MDE) and/or major depressive disorder (MDD), obsessive compulsive disorder (OCD), or any combination thereof, wherein the anti-inflammatory agent is for administration to a subject in need thereof, the subject having an elevated level of microglial activation in the brain. In certain embodiments, the subject may be a subject determined as having an elevated level of microglial activation by any of the method or methods as described herein. In another embodiment of any of the above method or methods, the anti-inflammatory agent may comprise celecoxib.

In another embodiment of any of the above method or methods, -ln[CRP] may be a predictive measure used for identifying the subject as having an elevated level of microglial activation in the brain.

In still another embodiment of any of the above method or methods, the method may be for improving the subject’s Hamilton Depression Rating Scale (HDRS) score.

In another embodiment, there is provided herein a method of treatment, comprising: determining a level of microglial activation in the brain of a subject by measuring a concentration of C-Reactive Protein (CRP) in a sample obtained from the subject and using the concentration of CRP to provide a predictive measure indicative of the level of microglial activation in the brain of the subject; and treating the subject with an anti-inflammatory and/or an antidepressant when the level of microglial activation in the brain of the subject is determined as being elevated.

In another embodiment, there is provided herein a use of an anti-inflammatory and/or or an antidepressant for treating a disease, disorder, or condition associated with microglial activation in the brain, wherein the anti-inflammatory and/or the antidepressant is for administration to a subject in need thereof, the subject having an elevated level of microglial activation in the brain. In certain embodiments, the subject may be a subject identified as having an elevated level of microglial activation in the brain by measuring a concentration of C-Reactive Protein (CRP) in a sample obtained from the subject and using the concentration of CRP to provide a predictive measure indicative of the level of microglial activation in the brain of the subject. In certain embodiments, the subject may be a subject determined as having an elevated level of microglial activation by any of the method or methods as described herein.

In another embodiment, there is provided herein a use of an anti-inflammatory and/or or an antidepressant in the manufacture of a medicament for treating a disease, disorder, or condition associated with microglial activation in the brain, wherein the medicament is for administration to a subject in need thereof, the subject having an elevated level of microglial activation in the brain. In certain embodiments, the subject may be a subject identified as having an elevated level of microglial activation in the brain by measuring a concentration of C-Reactive Protein (CRP) in a sample obtained from the subject and using the concentration of CRP to provide a predictive measure indicative of the level of microglial activation in the brain of the subject. In certain embodiments, the subject may be a subject determined as having an elevated level of microglial activation by any of the method or methods as described herein.

In another embodiment, there is provided herein an anti-inflammatory and/or or an antidepressant, for use in treating a disease, disorder, or condition associated with microglial activation in the brain, wherein the anti-inflammatory and/or the antidepressant is for administration to a subject in need thereof, the subject having an elevated level of microglial activation in the brain. In certain embodiments, the subject may be a subject identified as having an elevated level of microglial activation in the brain by measuring a concentration of C- Reactive Protein (CRP) in a sample obtained from the subject and using the concentration of CRP to provide a predictive measure indicative of the level of microglial activation in the brain of the subject. In certain embodiments, the subject may be a subject determined as having an elevated level of microglial activation by any of the method or methods as described herein.

In another embodiment of any of the above method or methods, the predictive measure may comprise a natural logarithm of the concentration of CRP.

In another embodiment of the above method or methods, the predictive measure may comprise: -ln[CRP]

In yet another embodiment of the above method or methods, a threshold cut-off for -ln[CRP] of about 0.6 may be used for identifying elevated microglial activation in the brain of the subject.

In still another embodiment of any of the above method or methods, body mass index (BMI) of the subject, or MCP-1 level of the subject, may also be used to provide the predictive measure.

In still another embodiment of any of the above method or methods, the predictive measure may comprise a linear combination of-ln[CRP] and BMI.

In another embodiment of any of the above method or methods, the predictive measure may comprise: [1.071*-ln(CRP) - 0.184*BMI]

In yet another embodiment of any of the above method or methods, a threshold cut-off for [1.071*-ln(CRP) - 0.184*BMI] of about -3.5 may be used for identifying elevated microglial activation in the brain of the subject. In still another embodiment of any of the above method or methods, the method may further comprise: measuring a concentration of tumor necrosis factor alpha (TNFa) in the sample obtained from the subject; and using the concentration of CRP and the concentration of TNFa to provide the predictive measure indicative of the level of microglial activation in the brain of the subject.

In still another embodiment of any of the above method or methods, the predictive measure may comprise a ratio of the concentrations of TNFa and CRP.

In another embodiment of any of the above method or methods, the predictive measure may comrpise a natural logarithm of a ratio of the concentrations of TNFa and CRP. In still another embodiment of any of the above method or methods, the predictive measure may comrpise: ln([TNFa]/[CRP]).

In another embodiment of any of the above method or methods, a threshold cut-off for ln([TNFa]/[CRP]) of about 1.0 to 2.1 may be used for identifying elevated microglial activation in the brain of the subject.

In still another embodiment of any of the above method or methods, the method may further comprise: measuring a concentration of prostaglandin E2 (PGE2) in the sample obtained from the subject; and using the concentration of CRP and the concentration of PGE2 to provide the predictive measure indicative of the level of microglial activation in the brain of the subject.

In yet another embodiment of any of the above method or methods, the predictive measure may comprise a ratio of the concentrations of PGE2 and CRP. In still another embodiment of any of the above method or methods, the predictive measure may comprise a natural logarithm of a ratio of the concentrations of PGE2 and CRP.

In another embodiment of any of the above method or methods, the predictive measure may comprise: ln([PGE ]/[CRP]). In another embodiment of any of the above method or methods, a threshold cut-off for ln([PGE2]/[CRP]) of about 5.8 to 7.3, for example 6.9 to 7.3 may be used for identifying increased microglial activation in the brain of the subject.

In still another embodiment of any of the above method or methods, the method may further comprise: measuring a concentration of prostaglandin F2 alpha (PGF2 _a ) in the sample obtained from the subject; and using the concentration of CRP and the concentration of PGF2« to provide the predictive measure indicative of the level of microglial activation in the brain of the subject.

In another embodiment of any of the above method or methods, the predictive measure may comrpise a ratio of the concentrations of PGF2 _« and CRP.

In yet another embodiment of any of the above method or methods, the predictive measure may comprise a natural logarithm of a ratio of the concentrations of PGF2 _« and CRP.

In still another embodiment of any of the above method or methods, the predictive measure may comprise: ln([PGF _2a ]/[CRP])..

BRIEF DESCRIPTION OF DRAWINGS

These and other features will become better understood with regard to the following description and accompanying drawings, wherein: FIGURE 1 shows results in which blood serum markers significantly correlated with translocator protein distribution volume in all three cohorts. Ln(PGE2/CRP) and ln(TNFa/CRP) were highly significant correlates of prefrontal cortex TSPO V _T in MDE and TRD cohorts, and dorsal caudate TSPO V _T in OCD cohort. To address the effect of the rs6971 genotype on TSPO V _T , the differential effect of genotype in a linear regression was found for TSPO V _T . Then, the MAB TSPO V _T values were adjusted by adding the differential effect of genotype to the TSPO V _T values. (Adjusted prefrontal cortex TSPO Vr=unadjusted TSPO Vr+bl *genotype, where b 1=4.939 in MDE cohort and b 1=4.678 in TRD cohort. Adjusted dorsal caudate TSPO Vr=unadjusted TSPO Vr+bl * genotype, where b 1=4.230 in OCD cohort). Abbreviations: CRP, c-reactive protein; HAB, high-affinity binders; MAB, mixed-affinity binders; MDE, medication free major depressive episodes secondary to major depressive disorder; OCD, obsessive compulsive disorder; PGE ₂ , prostaglandin E ₂ ; TNFa, tumor necrosis factor alpha; TRD, treatment resistant major depressive episodes secondary to major depressive disorder; TSPO VT, translocator protein distribution volume;

FIGURE 2 shows receiver operating characteristic curve analyses in collective depressed (MDE and TRD) cohorts. Receiver operating characteristic (ROC) curve analyses in the collective depressed sample (MDE and TRD n=76) for A) ln(PGE ₂ /CRP) and B) ln(TNFa/CRP). ROC curve analyses revealed accuracies of 74.9% and 78.1% in the ability of ln(PGE ₂ /CRP) and ln(TNFa/CRP) biomarkers to correctly classify those with and without elevated prefrontal cortex TSPO VT, respectively. To address the effect of the rs6971 genotype on TSPO V _T , the differential effect of genotype in a linear regression was found for TSPO VT. Then, the MAB TSPO V _T values were first adjusted by adding the differential effect of genotype to the TSPO V _T values. (Adjusted prefrontal cortex TSPO Vr=unadjusted TSPO Vr+bl *genotype, where b 1=4.939 in MDE cohort and b 1=4.678 in TRD cohort). Abbreviations: CRP, c-reactive protein; MDE, medication free major depressive episodes secondary to major depressive disorder; PGE2, prostaglandin E2; TNFa, tumor necrosis factor alpha; TRD, treatment resistant major depressive episodes secondary to major depressive disorder; TSPO V _T , translocator protein distribution volume;

FIGURE 3 shows relationship of positive predictive value and proportion of participants retained in collective depressed (MDE and TRD) cohorts. Relationship of positive predictive value and proportion of participants retained with varying thresholds of ln(PGE2/CRP) and ln(TNFa/CRP) in the collective depressed sample (MDE and TRD n=76). Cut-offs of ln(PGE ₂ /CRP)=6.9 and ln(TNFa/CRP)=2.1 reveal positive predictive values of approximately 80% for prefrontal cortex TSPO VT >13.5 while retaining 40% of cases. To address the effect of the rs6971 genotype on TSPO VT, the differential effect of genotype in a linear regression was found for TSPO VT. Then, the MAB TSPO VT values were first adjusted by adding the differential effect of genotype to the TSPO VT values. (Adjusted prefrontal cortex TSPO Vr=unadjusted TSPO Vr+bl*genotype, where b 1=4.939 in MDE cohort and b 1=4.678 in TRD cohort). Abbreviations: CRP, c-reactive protein; PGE2, prostaglandin E ₂ ; TNFa, tumor necrosis factor alpha; TSPO VT, translocator protein distribution volume;

FIGURE 4 shows correlation of Ln(PGF2 _a /CRP) with dorsal caudate translocator protein distribution volume in obsessive compulsive disorder. Linear regression assessing predictiveness found ln(PGF2 _a /CRP) was a significant predictor of dorsal caudate TSPO VT in the OCD cohort (Fi _{, 19} =25.5, R ² =0.56, p<0.0001), where it accounted for 56.3% of the variance. To address the effect of the rs6971 genotype on TSPO VT, the differential effect of genotype in a linear regression was found for TSPO VT. Then, the MAB TSPO VT values were first adjusted by adding the differential effect of genotype to the TSPO VT values. (Adjusted dorsal caudate TSPO Vr=unadjusted TSPO Vr+bl* genotype, where b 1=4.230 in OCD cohort). Abbreviations: CRP, c-reactive protein; HAB, high-affinity binders; MAB, mixed-affinity binders; OCD, obsessive compulsive disorder; PGF2 _a , prostaglandin F ₂ alpha, TSPO VT, translocator protein distribution volume;

FIGURE 5 shows negative Ln(CRP) serum marker significantly correlated with translocator protein distribution volume in collective depressed (MDE and TRD) cohorts. Post-hoc linear regression assessing predictiveness found -ln(CRP) was a significant predictor of prefrontal cortex TSPO V _T in collective depressed sample (MDE and TRD n=76) (Fi _{, 75} =26.9, R ² =0.26, p<0.0001), accounting for 25.7% of the variance. To address the effect of the rs6971 genotype on TSPO V _T , the differential effect of genotype in a linear regression was found for TSPO V _T . Then, the MAB TSPO V _T values were first adjusted by adding the differential effect of genotype to the TSPO V _T values. (Adjusted prefrontal cortex TSPO Vr=unadjusted TSPO Vr+bl*genotype, where b 1=4.939 in MDE cohort and b 1=4.678 in TRD cohort). Abbreviations: CRP, c-reactive protein; ELAB, high-affinity binders; MAB, mixed-affinity binders; MDE, medication free major depressive episodes secondary to major depressive disorder; TRD, treatment resistant major depressive episodes secondary to major depressive disorder; TSPO V _T , translocator protein distribution volume;

FIGURE 6 shows receiver operating characteristic curve analysis of Ln(CRP) serum marker in collective depressed (MDE and TRD) cohorts. Post-hoc receiver operating characteristic curve analysis was applied in the collected depressed sample (MDE and TRD n=76) for -ln(CRP). Assessing revealed an accuracy of 81.8% (p<0.0001, 95% Cl [72.5, 91.1]) in the ability of the blood marker to correctly classify those with and without elevated prefrontal cortex TSPO V _T . To address the effect of the rs6971 genotype on TSPO V _T , the differential effect of genotype in a linear regression was found for TSPO V _T . Then, the MAB TSPO V _T values were first adjusted by adding the differential effect of genotype to the TSPO V _T values. (Adjusted prefrontal cortex TSPO Vr=unadjusted TSPO Vr+bl*genotype, where b 1=4.939 in MDE cohort and b 1=4.678 in TRD cohort). Abbreviations: Cl, confidence interval; CRP, c-reactive protein; HAB, high- affinity binders; MAB, mixed-affinity binders; MDE, medication free major depressive episodes secondary to major depressive disorder; TRD, treatment resistant major depressive episodes secondary to major depressive disorder; TSPO V _T , translocator protein distribution volume; FIGURE 7 shows relationship of positive predictive value of Ln(CRP) serum marker and proportion of participants retained in collective depressed (MDE and TRD) cohorts. In the collective depressed sample (MDE and TRD n=76), varying thresholds of -ln(CRP) were assessed in relation to the positive predictive value and proportion of participants retained. With a cut-off of -ln(CRP)=1.0, positive predictive values for elevated prefrontal cortex TSPO V _T exceeding 85% were possible while retaining 40% of the participants. To address the effect of the rs6971 genotype on TSPO VT, the differential effect of genotype in a linear regression was found for TSPO VT. Then, the MAB TSPO VT values were first adjusted by adding the differential effect of genotype to the TSPO VT values. (Adjusted prefrontal cortex TSPO Vr=unadjusted TSPO V _T +bl*genotype, where b 1=4.939 in MDE cohort and b 1=4.678 in TRD cohort). Abbreviations: CRP, c-reactive protein; HAB, high-affmity binders; MAB, mixed- affinity binders; MDE, medication free major depressive episodes secondary to major depressive disorder; TRD, treatment resistant major depressive episodes secondary to major depressive disorder; TSPO VT, translocator protein distribution volume; FIGURE 8 shows linear combination of Ln(CRP) and body mass index significantly predictive of translocator protein distribution volume in collective depressed (MDE and TRD) cohorts. Post-hoc linear regression assessing predictiveness found [1.071*-ln(CRP) - 0.184*BMI] was a significant predictor of prefrontal cortex TSPO VT in collective depressed sample (MDE and TRD n=76) (Fi _{, 75} =36.0, R ² =0.32, p<0.0001), accounting for 32.0% of the variance. To address the effect of the rs6971 genotype on TSPO VT, the differential effect of genotype in a linear regression was found for TSPO VT. Then, the MAB TSPO VT values were first adjusted by adding the differential effect of genotype to the TSPO VT values. (Adjusted prefrontal cortex TSPO Vr=unadjusted TSPO Vr+bl*genotype, where b 1=4.939 in MDE cohort and b 1=4.678 in TRD cohort). Abbreviations: BMI, body mass index; CRP, c-reactive protein; HAB, high- affinity binders; MAB, mixed-affinity binders; MDE, medication free major depressive episodes secondary to major depressive disorder; TRD, treatment resistant major depressive episodes secondary to major depressive disorder; TSPO VT, translocator protein distribution volume;

FIGURE 9 shows receiver operating characteristic curve analysis of linear combination of Ln(CRP) and body mass index in collective depressed (MDE and TRD) cohorts. Post-hoc receiver operating characteristic curve analysis was applied in the collected depressed sample (MDE and TRD n=76) for [1.071*-ln(CRP) - 0.184*BMI], the combination of the linear regressors -ln(CRP) and BMI that significantly predicted TSPO VT. Assessing revealed an accuracy of 85.3% (p<0.0001, 95% Cl [76.7, 93.8]) in the ability of the blood marker to correctly classify those with and without elevated prefrontal cortex TSPO VT. TO address the effect of the rs6971 genotype on TSPO VT, the differential effect of genotype in a linear regression was found for TSPO VT. Then, the MAB TSPO VT values were first adjusted by adding the differential effect of genotype to the TSPO VT values. (Adjusted prefrontal cortex TSPO Vr=unadjusted TSPO Vr+bl*genotype, where b 1=4.939 in MDE cohort and b 1=4.678 in TRD cohort). Abbreviations: BMI, body mass index; Cl, confidence interval; CRP, c-reactive protein; HAB, high-affinity binders; MAB, mixed-affinity binders; MDE, medication free major depressive episodes secondary to major depressive disorder; TRD, treatment resistant major depressive episodes secondary to major depressive disorder; TSPO VT, translocator protein distribution volume; FIGURE 10 shows relationship of positive predictive value of linear combination of Ln(CRP) and body mass index and proportion of participants retained in collective depressed (MDE and TRD) cohorts. In the collective depressed sample (MDE and TRD n=76), varying thresholds of the combination of -ln(CRP) and BMI predictors determined in the linear regression for TSPO VT [1.071*-ln(CRP) - 0.184*BMI] were assessed in relation to the positive predictive value and proportion of participants retained. With a cut-off of [1.071*-ln(CRP) - 0.184*BMI]=-3.5 positive predictive values for elevated prefrontal cortex TSPO VT exceeding 80% while retaining 65% of the participants. To address the effect of the rs6971 genotype on TSPO VT, the differential effect of genotype in a linear regression was found for TSPO VT. Then, the MAB TSPO VT values were first adjusted by adding the differential effect of genotype to the TSPO VT values. (Adjusted prefrontal cortex TSPO Vr=unadjusted TSPO Vr+bl*genotype, where b 1=4.939 in MDE cohort and b 1=4.678 in TRD cohort). Abbreviations: BMI, body mass index; CRP, c-reactive protein; HAB, high-affinity binders; MAB, mixed-affinity binders; MDE, medication free major depressive episodes secondary to major depressive disorder; TRD, treatment resistant major depressive episodes secondary to major depressive disorder; TSPO VT, translocator protein distribution volume;

FIGURE 11 shows reduction in symptom severity versus serum biomarker. Fitting the plot of the -In transformation of baseline C-reactive protein was related to the cumulative mean change in severity of depression with a fitting of a four parameter sigmoidal curve y=-3.08+ 5.43/(l+exp(- (x+1.0159)/(-0.82))). The adjusted Rsquare was 0.79, suggesting that 79% of the variance was accounted for by -ln(CRP). CRP was in units of mg/L. The change in Hamilton Depression Rating Scale (HDRS) was the difference between the first HDRS measure and the last HDRS measure after open label administration of celecoxib titrated within 2 weeks to an intervention dose of 200mg twice per day which was, after titration, given for 6 weeks to cases of major depressive disorder non responsive to their current medication treatment. N=40 subjects; and

FIGURE 12 shows receiver operating characteristic curve analyses in entire sample. Post-hoc receiver operating characteristic curve analysis was applied in the whole sample (n=96) for A) ln(PGE2/CRP) and B) ln(TNF _o /CRP). Assessing revealed an accuracy of 72.9% (P=0.00013, 95% Cl [62.5, 83.2]) and 76.6 (p<0.0001, 95% Cl [66.7, 86.4]) in the abilities for ln(PGE /CRP) and ln(TNF _a /CRP), respectively, to correctly classify those with and without elevated PFC TSPO VT. TO address the effect of the rs6971 genotype on TSPO VT, the differential effect of genotype in a linear regression was found for TSPO VT. Then, the MAB TSPO VT values were first adjusted by adding the differential effect of genotype to the TSPO VT values. (Adjusted prefrontal cortex TSPO Vr=unadjusted TSPO Vr+bl*genotype, where b 1=4.939 in MDE cohort, bl=6.217 in the OCD cohort, and bl=4.678 in TRD cohort). Abbreviations: Cl, confidence interval; CRP, c-reactive protein; HAB, high-affinity binders; MAB, mixed-affinity binders; MDE, medication free major depressive episodes secondary to major depressive disorder; OCD, obsessive-compulsive disorder; TRD, treatment resistant major depressive episodes secondary to major depressive disorder; TSPO VT, translocator protein distribution volume.

DETAILED DESCRIPTION

Described herein are peripheral measures of brain inflammation, markers therefor, and methods and uses thereof for diagnosis and/or treatment. It will be appreciated that embodiments and examples are provided for illustrative purposes intended for those skilled in the art, and are not meant to be limiting in any way.

In certain embodiments, methods are provided herein for analyzing a sample, such as a blood, serum, or plasma sample, from a subject to determine a level of microglial activation in the brain of the subject, which may be used in the diagnosis, monitoring, and/or treatment of a neuropsychiatric illness, for example. A number of appealing markers and/or predictive measures are identified and described herein for use in evaluating levels of translocator protein distribution volume (TSPO VT), microglial activation levels, brain inflammation levels, and/or neuropsychiatric illness state of the subject. Among the markers and/or predictive measures described herein, -ln[CRP], [1.071*-ln(CRP) - 0.184*BMI], ln([TNFa]/[CRP]), ln([PGE2]/[CRP]), and ln([PGF2 _a ]/[CRP]) predictive measures are extensively studied in Examples sections below. Results indicate that -ln[CRP], [1.071*-ln(CRP) - 0.184*BMI], ln([TNFa]/[CRP]), and ln([PGE2]/[CRP]) may be particularly appealing predictive measures, with -ln[CRP] and [1.071*-ln(CRP) - 0.184*BMI] predictive measures providing the best overall diagnostic results in these studies.

In an embodiment, there is provided herein a method for determining a level of microglial activation in the brain of a subject, said method comprising: measuring a concentration or level of C-Reactive Protein (CRP) in a sample obtained from the subject; using the concentration of CRP to provide a predictive measure indicative of the level of microglial activation in the brain of the subject; determining the level of microglial activation in the brain of the subject from the predictive measure; and optionally, recommending a treatment option and/or administering a treatment to the subject based on the level of microglial activation in the brain on the subject.

As will be understood, in certain embodiments, determining a level of microglial activation in the brain may comprise determining a qualitative assessment of microglial activation levels, such as identifying whether microglial activation levels are decreased, increased, or similar to a control or reference level such as that of a healthy control group, a reference group having a neuropsychiatric illness, an activation level of the subject from a previous time point (i.e. monitoring changes over time and/or monitoring changes in response to a treatment), or any other suitable control or reference level(s) appropriate for the particular application. In certain other embodiments, determining a level of microglial activation in the brain may comprise determining a quantitative assessment of microglial activation levels, such as identifying an approximate or precise amount (for example, a % change) by which microglial activation levels are decreased, increased, or similar to a control or reference level such as that of a healthy control group, a reference group having a neuropsychiatric illness, an activation level of the subject from a previous time point (i.e. monitoring changes over time and/or monitoring changes in response to a treatment), or any other suitable control or reference level(s) appropriate for the particular application. In certain embodiments, both qualitative and quantitative assessment may be performed.

In certain embodiments, the predictive measure, or the level of microglial activation, may be compared with that of one or more control subjects or groups. In certain embodiments, the one or more control subjects or groups may comprise one or more healthy controls, one or more controls confirmed as having a neuropsychiatric illness, or both. In certain embodiments, the level of microglial activation may provide an index of brain inflammation in the subject.

In certain embodiments, the sample obtained from the subject may comprise a blood sample, a serum sample, or a plasma sample obtained from the subject. In certain embodiments, the concentration of C-Reactive Protein (CRP) in the sample may be measured or quantified using any suitable procedure known to the person of skill in the art having regard to the teachings herein. In certain embodiments, the concentration of CRP may be measured or quantified using mass spectrometry, HPLC, immunoassay, radioimmunoassay, gas chromatography-mass spectrometry or other chromatographic or non-chromatographic procedures. In certain embodiments, CRP may be measured or quantified by immunoturbidimetric assay. By way of example, in the Examples section below CRP was measured by CRPHS assay (Cobas C, Roche Diagnostics).

In certain embodiments, the measured the concentration of CRP may be used to provide a predictive measure indicative of the level of microglial activation in the brain of the subject. The relationship between [CRP] and microglial activation is described and investigated in detail herein. In certain embodiments, the CRP concentration itself may be used as the predictive measure, or the CRP concentration may be a factor of the predictive measure. In certain embodiments, the predictive measure may include one or more additional factors in addition to CRP concentration. As will be understood, predictive measures may be expressed in a variety of different ways, may or may not be transformed, and may or may not include one or more additional factors which may be in addition to CRP concentration or may modify the CRP concentration factor. The person of skill in the art having regard to the teachings herein will be aware of a variety of suitable predictive measures including CRP concentration as a factor, which may be selected or tailored for the particular application and/or the particular manner in which the predictive measure is to be related to the level of microglial activation in the brain. By way of example, in the studies described herein, -ln[CRP], [1.071*-ln(CRP) - 0.184*BMI], ln([TNFa]/[CRP]), ln([PGE2]/[CRP]), and ln([PGF2 _a ]/[CRP]) were identified as predictive measures of particular interest.

In certain embodiments, the level of microglial activation in the brain of the subject may be determined from the predictive measure in a qualitative manner, a quantitative manner, or both, as described above. In certain embodiments, the concentration of the CRP, or the predictive measure, may be compared (directly or indirectly) to a control or reference level such as that of a healthy control group, a reference group having a neuropsychiatric illness, an activation level of the subject from a previous time point (i.e. monitoring changes over time and/or monitoring changes in response to a treatment), or any other suitable control or reference level(s) appropriate for the particular application. In certain embodiments, the concentration of the CRP, or the predictive measure, may be compared (directly or indirectly) to a predetermined calibration curve, threshold value, threshold range, or other suitable comparator or criteria relating the concentration of the CRP or the predictive measure to the level of microglial activation in the brain. In certain embodiments, the concentration of CRP or the predictive measure may be related to the level of microglial activation via providing an indication of a translocator protein distribution volume (TSPO V _T ) of the subject.

In certain embodiments, the method may further comprise recommending a treatment option and/or administering a treatment to the subject based on the determined level of microglial activation in the brain on the subject. As described in detail herein, microglial activation levels may be reflective of a neuropsychiatric illness or disorder, such as depression, obsessive compulsive disorder, or both. In certain embodiments, where increased microglial activation is detected, methods described herein may comprise a step of recommending treatment, or treating, the subject with medication, non-medicinal therapy, or a combination thereof; monitoring the subject; counseling the subject; testing or screening the subject for clinical depression, major depressive episode, major depressive disorder, obsessive compulsive disorder (OCD) or another neuropsychiatric illness; testing the sample for one or more additional genetic markers, nucleotide sequences, proteins, or metabolites; or any combinations thereof. In certain embodiments, the method may comprise treating the subject with medication by administering one or more anti-inflammatory agents, antidepressants, antipsychotics, mood stabilizers, anticonvulsants, antianxiolytics, steroids, or any combination thereof. In certain embodiments, the medication may comprise one or more glucocorticoids, phosphodiesterase inhibitors, cox -2 inhibitors, acetaminophen, non-steroidal anti-inflammatory agents, statins, neurokinin antagonists, thiazolidinediones, toll receptor antagonists/agonists, tetracycline antibiotics such as minocycline, cytokine antagonists such as infliximab, P2X7 receptor binding medications, riluzole, Janus kinase inhibitors, phospholipase inhibitors, antibody directed therapies for immune system targets, Monoamime Oxidase Inhibitor (MAOIs) such as tranylcypromine, phenelzine, isocarboxazid and the like, Tricyclic Antidepressants (TCAs) such as clomipramine, amitriptyline, desipramine, nortriptyline, doxepin, or trimipramine, Selective Serotonin Reuptake Inhibitors (SSRIs) such as citalopram, escitalopram, fluvoxamine, paroxetine, fluoxetine, sertraline or other common medications such as duloxetine, venlafaxine, mirtazapine, bupropion, trazodone, clozapine, lithium, ketamine, or any pharmaceutically acceptable salt or solvate thereof, of any combinations thereof. In certain embodiments, detection of increased microglial activation may identify the subject as a candidate for treatment with an anti-inflammatory agent, a P2X7 antagonist, an indolamine 2,3 dioxygenase inhibitor, minocycline, simvastatin, or any combinations thereof. In certain embodiments, the method may comprise a step of treating the subject with, or identifying the subject as a candidate for treatment with, an anti-inflammatory agent, a P2X7 antagonist, an indolamine 2,3 dioxygenase inhibitor, minocycline, simvastatin, or any combinations thereof where an increased level of microglial activation is determined. In certain embodiments, the method may comprise a step of treating the subject with, or identifying the subject as a candidate for treatment with, celecoxib where an increased level of microglial activation is detected.

In certain embodiments, treatment may comprise an inflammatory modulating treatment which may reduce inflammation and/or change inflammation profile and/or behaviour in the subject so as to provide a therapeutic benefit to the subject in need thereof.

In certain embodiments, the predictive measure indicative of the level of microglial activation in the brain of the subject may comprise a natural logarithm of the concentration of CRP. In certain embodiments, the predictive measure may comprise: -ln[CRP] In certain embodiments, a threshold cut-off for -ln[CRP] of about 0.6 may be used for identifying increased microglial activation in the brain of the subject. In certain embodiments, a -ln[CRP] greater than about 0.6 may indicate a subject as having a high TSPO V _T . With reference to the examples below, values of -ln[CRP] of 0, 0.4, 0.6, 0.8, and 1.2 may have increasingly positive predictive value to detect an elevated level of TSPO V _T , an index mainly reflecting microglial activation (TSPO is found in a few different types of cells in the brain, but when inflammation occurs in diseases, it is mainly overexpressed in activated microglia), from approximately 58% to over 85%. Elevated TSPO V _T was exemplified as a value of greater than 13.5 in the prefrontal cortex, which is approximately 30% greater than the mean of healthy individuals.

In certain embodiments, use of the term about in connection with a value recited herein may encompass values within ± 20%, ± 15%, ± 10%, or ± 5% of the recited value, for example.

In certain embodiments, the predictive measure indicative of the level of microglial activation in the brain of the subject may consider one or more additional factors in addition to CRP concentration. For example, in certain embodiments, the predictive measure may include body mass index (BMI) of the subject as an additional factor. In certain embodiments, the predictive measure may comprise a linear combination of -ln[CRP] and BMI. In certain embodiments, the predictive measure may comprise: [1.071*-ln(CRP) - 0.184*BMI] In certain embodiments, a threshold cut-off for [1.071*-ln(CRP) - 0.184*BMI] of about -5 or higher, for example, but not limited to -3.5 may be used for identifying increased microglial activation in the brain of the subject. In certain embodiments, a [1.071*-ln(CRP) - 0.184*BMI] of greater than -3.5 may indicate a subject as having a high TSPO V _T . With reference to the examples below, values of [1.071*-ln(CRP) - 0.184*BMI] of -5, -4.9, -4.4, -4.1, and -3.3 or any value therein between may have increasingly positive predictive value to detect an elevated level of TSPO VT, an index mainly reflecting microglial activation (TSPO is found in a few different types of cells in the brain, but when inflammation occurs in diseases, it is mainly overexpressed in activated microglia), from approximately 60% to approximately 80%. Elevated TSPO VT was exemplified as a value of greater than 13.5 in the prefrontal cortex, which is approximately 30% greater than the mean of healthy individuals.

In certain embodiments, the predictive measure indicative of the level of microglial activation in the brain of the subject may consider one or more additional factors in addition to CRP concentration. For example, in certain embodiments, the predictive measure may comprise or include MCP-1 level of the subject. It is found that is certain embodiments, ln(MCP-l) may additionally predict about 5% of the variance in TSPO VT values over -ln(CRP), which in certain embodiments may also be expressed as ln(MCP-l/CRP).

In certain embodiments, the method may further comprise: measuring a concentration of tumor necrosis factor alpha (TNFa) in the sample obtained from the subject; and using the concentration of CRP and the concentration of TNFa to provide the predictive measure indicative of the level of microglial activation in the brain of the subject.

Accordingly, in certain embodiments, the predictive measure may comprise a ratio of the concentrations of TNFa and CRP. In certain embodiments, the predictive measure may comprise a natural logarithm of a ratio of the concentrations of TNFa and CRP. In certain embodiments, the predictive measure may comprise: ln([TNFa]/[CRP]). In certain embodiments, a threshold cut-off for ln([TNFa]/[CRP]) of about 1.9 to 2.1 may be used for identifying increased microglial activation in the brain of the subject. In certain embodiments, a ln([TNFa]/[CRP]) of greater than 2.1 may indicate a subject as having a high TSPO VT. With reference to the examples below, values of ln([TNFa]/[CRP]) of 1, 1.3, 1.6, 1.9, 2.5, 2.8, and 3.1 may have increasingly positive predictive value to detect an elevated level of TSPO VT, an index mainly reflecting microglial activation (TSPO is found in a few different types of cells in the brain, but when inflammation occurs in diseases, it is mainly overexpressed in activated microglia), from approximately 60% to approximately 90%. Elevated TSPO V _T was exemplified as a value of greater than 13.5 in the prefrontal cortex, which is approximately 30% greater than the mean of healthy individuals.

In another embodiment, the method may further comprise: measuring a concentration of prostaglandin E ₂ (PGE ₂ ) in the sample obtained from the subject; and using the concentration of CRP and the concentration of PGE ₂ to provide the predictive measure indicative of the level of microglial activation in the brain of the subject.

Accordingly, in certain embodiments the predictive measure may comprise a ratio of the concentrations of PGE ₂ and CRP. In certain embodiments, the predictive measure may comprise a natural logarithm of a ratio of the concentrations of PGE ₂ and CRP. In certain embodiments, the predictive measure may comprise: ln([PGE ₂ ]/[CRP]). In certain embodiments, a threshold cut-off for ln([PGE ₂ ]/[CRP]) of about 6.9 to 7.3 may be used for identifying increased microglial activation in the brain of the subject. In certain embodiments, a ln([PGE ₂ ]/[CRP]) of greater than 7.3 may indicate a subject as having a high TSPO V _T . With reference to the examples below, values of ln([PGE2]/[CRP]) of 5.4, 5.7, 6.0, 6.3, 6.6, 6.9, and 7.2 may have increasingly positive predictive value to detect an elevated TSPO V _T , an index mainly reflecting microglial activation (TSPO is found in a few different types of cells in the brain, but when inflammation occurs in diseases, it is mainly overexpressed in activated microglia), from approximately 55% to approximately 90%. Elevated TSPO V _T was exemplified as a value of greater than 13.5 in the prefrontal cortex, which is approximately 30% greater than the mean of healthy individuals.

In yet another embodiment, the method may further comprise: measuring a concentration of prostaglandin F ₂ alpha (PGF _2a ) in the sample obtained from the subject; and using the concentration of CRP and the concentration of PGF _2a to provide the predictive measure indicative of the level of microglial activation in the brain of the subject.

Accordingly, in certain embodiments, the predictive measure may comprise a ratio of the concentrations of PGF _2« and CRP. In certain embodiments, the predictive measure may comprise a natural logarithm of a ratio of the concentrations of PGF _2« and CRP. In certain embodiments, the predictive measure may comprise: ln([PGF _2a ]/[CRP]). In certain embodiments, a threshold cut-off for ln([PGF _2a ]/[CRP]) of about 2 to 4.5 may be used for identifying increased microglial activation in the brain of the subject. With reference to the examples below, values of ln([PGF _2a ]/[CRP]) of 2, 2.5, 3, 3.5, 4, and 4.5 may have increasingly positive predictive value to detect an elevated level of TSPO V _T , an index mainly reflecting microglial activation, from approximately 80% to approximately 100% in OCD, for example. Elevated TSPO V _T may be exemplified in OCD as a value of greater than 9.4 in the caudate, which is approximately 30% greater than the mean of healthy individuals. In certain embodiments, the subject may be a subject having, or suspected of having, major depressive disorder (MDE) or obsessive compulsive disorder (OCD). In certain embodiments, the subject may be a subject having, or suspected of having, medication free depression. In certain embodiments, the subject may be a subject having, or suspected of having, OCD.

In still another embodiment, the method may further comprising performing additional suitable conventional diagnosis steps, such as those described in DSM-V (herein incorporated by reference in its entirety).

[0076] In still another embodiment, the method may comprise a step of recommending a treatment option for the subject based on the level of microglial activation in the brain. For example, a subject determined as having an elevated level of microglial activation may be recommended a treatment program involving treatment to reduce brain inflammation using, for example, treatments described in further detail herein. Where a subject is afflicted with a neuropsychiatric illness related to elevated brain inflammation, the subject may be recommended a treatment program involving a conventional treatment for the neuropsychiatric illness alone, or in combination with a treatment for reducing or controlling brain inflammation.

In certain embodiments, the sample obtained from the subject may comprise a blood sample, a serum sample, or a plasma sample obtained from the subject. In certain embodiments, the concentration of TNFa, PGE ₂ , and/or PGF _2a in the sample may be measured or quantified using any suitable procedure known to the person of skill in the art having regard to the teachings herein. In certain embodiments, the concentration of TNFa, PGE ₂ , and/or PGF _2a may be measured or quantified using mass spectrometry, HPLC, immunoassay, radioimmunoassay, gas chromatography-mass spectrometry or other chromatographic or non-chromatographic procedures. In certain embodiments, TNFa, PGE ₂ , and/or PGF _2a may be measured or quantified by competitive immunoassay or bead panel. By way of example, in the Examples section below PGE ₂ and PGF _2a were measured by competitive immunoassay (Parameter, R&D Systems Inc; and ELISA Kit, MyBioSource, respectively), and TNFa was measured by Human Adipokine Magnetic Bead Panel 2 (Milliplex, MAP, EMD Millipore Corp).

In certain embodiments, any of [CRP], [TNFa], [PGE ₂ ], and/or [PGF ₂ J may be measured in a blood sample obtained from the subject, or in a plasma or serum or other processed product obtained therefrom. In certain embodiments, any of [CRP], [TNFa], [PGE ₂ ], and/or [PGF _2a ] may be measured in a peripheral blood sample such as a serum sample.

The person of skill in the art having regard to the teachings herein will understand that brain inflammation levels may be correlated with any one or more predictive measures as described herein. Determining a threshold level for a particular predictive measure, beyond which brain inflammation levels in a subject may be considered as being elevated, may vary between different subject populations or different applications. In certain embodiments, comparisons may be made with level(s) of a healthy subject, or the same subject at a prior time point, determined in the same manner, for assessing changes or increases.

It will be understood by the person of skill in the art having regard to the teachings herein that brain inflammation levels may be correlated with one or more predictive measures as described herein. Thus, it is contemplated herein that any of the method or methods described herein may involve monitoring or determining on or more of the predictive measures described herein over time to determine whether a subject’s level of microglial activation, or brain inflammation, has increased or decreased over the period of time. By way of example, determination of a change from an initial time point to a subsequent time point may suggest that an increase or decrease in microglial activation, or brain inflammation, has occurred over the intervening time period (depending on the nature of the change), or that microglial activation and/or brain inflammation is higher/lower at the subsequent time point than it was at the initial time point. Monitoring or determining one or more predictive measures as described herein of a subject, such as a subject having MDD, MDE, depression, or OCD, over time may assist in determining whether microglial activation and/or brain inflammation is improving or worsening either naturally or in response to a treatment program, for example.

In certain embodiments of the methods described herein, the predictive measure may be indicative of the level of microglial activation in the brain of the subject by predicting a translocator protein distribution volume (TSPO V _T ) of the subject.

In certain embodiments of the methods described herein, the subject may be a subject having, or suspected of having, or whom has exhibited one or more symptoms of, a neuropsychiatric illness. In certain embodiments, the neuropsychiatric illness may be characterized by an increased level of microglial activation in the brain. By way of example, in certain embodiments, the subject may be a subject having, or suspected of having, or whom has exhibited one or more symptoms of, depression, obsessive compulsive disorder, or both. In certain embodiments, the subject may be a subject having, or suspected of having, or whom has exhibited one or more symptoms of, major depressive disorder or obsessive compulsive disorder. In certain embodiments, the subject is a subject having, or suspected of having, or has exhibited one or more symptoms of, medication free major depressive episodes (MDE) secondary to major depressive disorder (MDD), treatment resistant major depressive episodes secondary to major depressive disorder, or medication free obsessive compulsive disorder (OCD). In certain embodiments, said subject may exhibit MDE, MDD or depression as determined by the Structures Clinical Interview for DSM-V, Hamilton Depression rating Scale or another psychiatric rating scale.

In certain embodiments, it is contemplated that a subject may be clinically depressed, suspected of being clinically depressed or has exhibited one or more symptoms of depression, or one or more other neuropsychiatric illnesses. For example, but not wishing to be considered limiting in any manner, the subject may be diagnosed or suspected of having major depressive episode (MDE) or major depressive disorder (MDD). MDD can be further subcategorized as being atypical depression, melancholic depression, psychotic major depression, catatonic depression, postpartum depression and seasonal affective disorder. Depressive disorders may further comprise dysthymia and depressive disorder not otherwise specified and bipolar disorder (or manic-depression). Depressive disorders not otherwise specified include recurrent brief depression and minor depressive disorder. Bipolar disorder is a neuropsychiatric illness that can also be subcategorized into bipolar I, bipolar II, cyclothymia and bipolar disorder not otherwise specified. In a further embodiment, the subject may exhibit major depressive episode (MDE) secondary to major depressive disorder (MDD). Preferably, depression, MDE, MDD or one or more neuropsychiatric illnesses is diagnosed in a subject or patient according to the Structures Clinical Interview for DSM-V, Hamilton Depression rating Scale or another psychiatric rating scale. However, it is also contemplated that the methods as described herein may be practiced in subjects or patients who are suspected of having depression or a depressive disorder without a formal diagnosis. In still a further embodiment, the subject may have no symptoms of any illness.

In certain embodiments, the microglial activation may be in the prefrontal cortex or dorsal caudate, for example. In certain embodiments, the subject may be a subject having, or suspected of having, or whom has exhibited one or more symptoms of, medication free major depressive episodes (MDE) secondary to major depressive disorder (MDD) or treatment resistant major depressive episodes secondary to major depressive disorder, and the microglial activation may be in the prefrontal cortex. In certain embodiments, the subject may be a subject having, or suspected of having, or whom has exhibited one or more symptoms of, OCD and the microglial activation may be in the dorsal caudate.

In certain embodiments, an increased level of microglial activation may identify or assist in identifying the subject as having or being at risk of developing depression, a major depressive episode (MDE), a major depressive disorder (MDD), obsessive compulsive disorder (OCD), or other neuropsychiatric illness, or as being prone to developing depression, MDE, MDD, OCD, or other neuropsychiatric illness, or brain inflammation associated therewith. In certain embodiments, a subject identified as having elevated microglial activation may be recommended treatment, or may be treated, with medication, non-medicinal therapy, or a combination thereof; may be monitored; may be counseled; may be tested or screened for clinical depression, major depressive episode, major depressive disorder, obsessive compulsive disorder (OCD) or any other neuropsychiatric illness; may be further tested for one or more additional genetic markers, nucleotide sequences, proteins, or metabolites; or any combination thereof. In certain embodiments, the subject may be treated with medication, and may comprise administering one or more anti-inflammatory agents, antidepressants, antipsychotics, mood stabilizers, anticonvulsants, antianxiolytics, steroids, or any combination thereof. In certain embodiments, the medication may comprise one or more glucocorticoids, phosphodiesterase inhibitors, cox-2 inhibitors, acetaminophen, non-steroidal anti-inflammatory agents, statins, neurokinin antagonists, thiazolidinediones, toll receptor antagonists/agonists, tetracycline antibiotics such as minocycline, cytokine antagonists such as infliximab, P2X7 receptor binding medications, riluzole, Janus kinase inhibitors, phospholipase inhibitors, antibody directed therapies for immune system targets, Monoamime Oxidase Inhibitor (MAOIs) such as tranylcypromine, phenelzine, isocarboxazid and the like, Tricyclic Antidepressants (TCAs) such as clomipramine, amitriptyline, desipramine, nortriptyline, doxepin, or trimipramine, Selective Serotonin Reuptake Inhibitors (SSRIs) such as citalopram, escitalopram, fluvoxamine, paroxetine, fluoxetine, sertraline or other common medications such as duloxetine, venlafaxine, mirtazapine, bupropion, trazodone, clozapine, lithium, ketamine, or any pharmaceutically acceptable salt or solvate thereof, of any combinations thereof. In certain embodiments, the subject may be treated with, or may be identified as a candidate likely to benefit from treatment with, an anti-inflammatory agent, a P2X7 antagonist, an indolamine 2,3 dioxygenase inhibitor, minocycline, simvastatin, or any combinations thereof. In certain embodiments, the subject may be treated with, or identified as a candidate likely to benefit from treatment with, celecoxib when an increased level of microglial activation is detected. In certain embodiments, the subject may be treated with, or identified as a candidate likely to benefit from treatment with, pioglitazone, aspirin, statin medication (such as simvastatin), or any combination thereof, when an increased level of microglial activation is detected.

In certain embodiments, subjects having OCD may be treated with a suitable conventional OCD treatment including a behavioral treatment, pharmaceutical treatment, or a combination thereof.

Also contemplated herein is a method of reducing microglial activation in the brain of a subject by administering to said subject an anti-inflammatory agent to reduce microglial activation in the subject. In certain embodiments, it is contemplated that an anti-inflammatory agent that can reduce microglial activation in the brain may in turn reduce brain inflammation and/or improve depressive disorders or symptoms associated therewith.

It is also contemplated that methods as described herein may further comprise a further step of brain imaging. In certain embodiments, the brain imaging may PET imaging. It is also contemplated that brain imaging may comprise TSPO analysis of one or more regions of the brain, for example, but not limited to as described herein.

In another embodiment, there is provided herein a kit for determining a level of microglial activation in the brain of a subject, for diagnosing or treating a neuropsychiatric illness, or both, said kit comprising any one or more of:

C-Reactive Protein (CRP); tumor necrosis factor alpha (TNFa); prostaglandin E2 (PGE2); prostaglandin F2 alpha (PGF2a); one or more diagnostic agents or reagents for quantifying or assisting in quantifying CRP, TNFa, PGE2, PGF2 _a , or any combination thereof; a container; instructions for performing any of the method or methods described herein; or any combinations thereof.

In certain embodiments, the one or more diagnostic agents or reagents may comprise one or more antibodies or antibody derivatives or an agent, component, diluent or buffer which can be employed in mass spectrometry, HPLC, immunoassay, radioimmunoassay, gas chromatography- mass spectrometry or other chromatographic or non-chromatographic procedure to quantify CRP, TNFa, PGE ₂ , PGF _2a , or any combination thereof.

In another embodiment, there is provided herein a kit comprising one or more markers of microglial activation, one or more markers of brain inflammation, one or more markers of peripheral body inflammation, one or more diagnostic agents capable of quantifying or assisting in quantifying one or more markers of microglial activation, one or more markers of brain inflammation, one or more markers of peripheral body inflammation or any combination thereof.

In another embodiment, the one or more diagnostic agents may comprise one or more antibodies or antibody derivatives or an agent, component, diluent, or buffer which may be employed in mass spectrometry, HPLC, immunoassay, radioimmunoassay, gas chromatography-mass spectrometry or other chromatographic or non-chromatographic procedure to quantify the one or more markers. In yet another embodiment, the kit may comprise an antibody or other agent specific for detecting or quantifying one or more of CRP, TNFa, PGE ₂ , PGF _2a , or any combination thereof. The one or more diagnostic agents may comprise one or more antibodies or antibody derivatives such as, but not limited to FAB, FAB’ or single chain antibodies or alternatively the agent may be any component, diluent or buffer which can be employed in mass spectrometry, HPLC, immunoassay, radioimmunoassay, gas chromatography-mass spectrometry or other chromatographic or non-chromatographic procedure to quantify the marker.

In another embodiment, there is provided herein a kit comprising one or more components, such as one or more primary antibodies that are capable of binding to CRP, TNFa, PGE ₂ , and/or PGF _2a , one or more secondary antibodies that are capable of binding the primary antibody, one or more solutions or reagents for immunological analysis, for example, blocking or binding solution or the like, a dish, multi-well plate or the like, purification media for example, but not limited to remove abundant plasma proteins from samples that are collected, centrifugation media, immunoabsorption columns, resin, buffers, enzymes, one or more supports, multiwell plates, instructions for using any component or practicing any method as described herein, or any combination thereof. In still another embodiment, there is provided herein a method for treating a subject having major depressive episode (MDE) and/or major depressive disorder (MDD), said method comprising: determining a level of microglial activation in the brain of the subject using any of the method or methods as described herein; and identifying the subject as a candidate for treatment with an anti-inflammatory agent where an elevated level of microglial activation is determined, and treating the subject with the anti-inflammatory agent.

In certain embodiments, the anti-inflammatory agent may comprise celecoxib, minocycline, pioglitazone, aspirin, statin medication (such as simvastatin, for example), or any combinations thereof. In certain embodiments, the subject may be identified as a candidate for treatment with the anti-inflammatory agent when the level of microglial activation is determined to be elevated by at least about 30% versus a healthy control.

In another embodiment, there is provided herein a method for treating a subject having major depressive episode (MDE) and/or major depressive disorder (MDD), or obsessive compulsive disorder (OCD), or any combination thereof, said method comprising: treating the subject with an anti-inflammatory agent; wherein the subject is a subject having an elevated level of microglial activation in the brain according to any of the method or methods as described herein.

In another embodiment, there is provided herein a use of an anti-inflammatory agent for treating a subject having major depressive episode (MDE) and/or major depressive disorder (MDD), or obsessive compulsive disorder (OCD), or any combination thereof, wherein the subject is a subject having an elevated level of microglial activation in the brain according to any of the method or methods as described herein.

In yet another embodiment, the anti-inflammatory agent may comprise celecoxib. In certain embodiments, -ln[CRP] may be a predictive measure used for identifying the subject as having an elevated level of microglial activation in the brain. In certain embodiments, the method or use may be for improving the subject’s Hamilton Depression Rating Scale (HDRS) score.

In another embodiment, there is provided herein a method for identifying candidates for treating brain inflammation in a subject having a neuropsychiatric illness, said method comprising: (a) determining a level of microglial activation in the brain of the subject using a method as described herein prior to administration of a potential agent for treating brain inflammation; (b) administering the potential agent for treating brain inflammation; and (c) determining a level of microglial activation in the brain of the subject using a method as described herein following administration of the potential agent for treating brain inflammation; wherein a reduction in microglial activation post-treatment indicates that the potential agent is a candidate for treating brain inflammation in a subject having a neuropsychiatric illness.

EXAMPLE 1 - Replicating Predictive Serum Correlates of Greater Translocator Protein Distribution Volume in Brain

Greater microglial activation, a key component of neuroinflammation, is an appealing process to target in neuropsychiatric illnesses. However, the magnitude of microglial activation varies across cases so low-cost predictors are desirable to stratify subjects for clinical trials. In this example, several such blood serum measures were assessed in relation to TSPO VT, an index of translocator protein density, measured with positron emission tomography that is primarily a brain marker of microglial activation during illness.

Blood serum concentration of several products synthesized by activated microglia [prostaglandin E ₂ (PGE ₂ ), prostaglandin F ₂ alpha (PGF _2a ), and tumor necrosis factor alpha (TNFa)], controlled by an index of peripheral inflammation [C-reactive protein (CRP)] and TSPO VT were measured in 3 cohorts: prefrontal cortex TSPO VT of 20 subjects with major depressive episodes from major depressive disorder; and 56 subjects with treatment resistant major depressive episodes from major depressive disorder; and dorsal caudate TSPO VT of 20 subjects with obsessive compulsive disorder. Ln(PGE2/CRP) and ln(TNFa/CRP) consistently correlated with TSPO VT (R ² =0.36 to 0.11, p=0.0030 to p=0.0076). Assessment of threshold serum values to predict highly elevated TSPO VT, demonstrated that a positive predictive value (PPV) of 80% was possible while retaining 40% of participant samples and that receiver operating curves (ROC) ranged from 75 to 81%. Post-hoc selection of ln(CRP) was more predictive (R ² =0.23 to 0.39, p=0.0058 to p=0.00013; ROC>80%). Systematic assessment of selected peripheral inflammatory markers supports development of low cost predictors of TSPO V _T . Marker thresholds with high PPV may improve subject stratification for clinical trials of microglial targeting therapeutics, for example.

For the present study, to design relatively low cost blood markers, composite measures were created. Activated microglia in brain were considered an important source of inflammatory markers, and several such products that are also actively transported out of the central nervous system into blood were measured, including serum prostaglandin E2 (PGE2), prostaglandin F2 alpha (PGF _2a ), and tumor necrosis factor alpha (TNFa) (15-19). PGE ₂ was given the highest priority since it may arguably be the most commonly measured product of activated microglia among in vitro studies (15). Since PGE2, PGF2 _a , and TNFa are also produced by the immune response of peripheral tissues (20) and microglial activation in brain is influenced by peripheral inflammation (9), a controlling measure of a well-accepted index of peripheral inflammation, serum C-reactive protein (CRP) concentration was applied. Hence, the primary hypothesis was that PGE2/CRP may predict TSPO total distribution volume (V _T ) in brain and PGF2 _« /CRP and TNFa/CRP were secondary candidates.

In the present study, the relationship of these serum markers to brain TSPO V _T was assessed in three groups: medication free major depressive disorder; antidepressant treated, treatment resistant major depressive disorder; and medication free obsessive compulsive disorder (OCD) subjects, illnesses for which TSPO V _T is elevated yet there is also substantial variability across subjects (2-8). In medication free major depressive disorder and treatment resistant major depressive disorder the prefrontal cortex (PFC) was prioritized because subregions of the PFC are often adversely affected in these illnesses (21-23), and it is a large portion of brain tissue. In OCD, the caudate nucleus was prioritized because it is the region with the most abnormally elevated TSPO V _T (2), and is strongly implicated in the pathophysiology of OCD, having the greatest convergence of neurochemical abnormalities across investigations in OCD (24-26).

Methods: Participants:

Three cohorts were recruited: 20 with medication free major depressive episodes secondary to major depressive disorder (MDE) (7); 56 treatment resistant major depressive episodes secondary to major depressive disorder (TRD) (31 previously described (3)); and 20 medication free obsessive compulsive disorder (OCD) (19 previously described (2)) were recruited from the Greater Toronto Area and the Centre for Addiction and Mental Health between July 2010 and October 2018 (Table 1). To assess the diagnosis, all participants underwent the Structured Clinical Interview for DSM-IV with confirmation by a consultation with a psychiatrist (JHM). All were currently experiencing significant symptoms: For MDE and TRD, a minimum of 17 on the 17-item Hamilton Depressive Rating Scale (17-item HDRS) (27) was required and for OCD participants, scores on the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) (28), reflected moderate to severe illness. All were aged 18 to 72 years, non-cigarette smoking, and otherwise in good physical health (see demographic characteristics in Table 1; for additional criteria see below). The study, protocol, etc., were approved by the Research Ethics Board at the Centre for Addiction and Mental Health.

Image Acquisition and Analysis:

As previously described (2, 3, 7), each participant underwent one [ ¹⁸ F]FEPPA PET (HRRT; CPS/Siemens, Knoxville, TN, USA) and one MRI scan at the Research Imaging Centre at the Centre for Addiction and Mental Health (see below for additional detail). [ ¹⁸ F]FEPPA was administered intravenously as a bolus (mean 184.6 MBq [SD 13.0]). [ ¹⁸ F]FEPPA was of high radiochemical purity (>96%) and high specific activity (mean 83.1 TBq/mmol [SD 73.0]). Manual and automatic blood samplings (ABSS, Model #PBS-101; Veenstra Instuments, Joure, The Netherlands) were obtained to determine the unmetabolised parent radioligand in plasma which was the input function for the kinetic analysis. A brain MRI was acquired for each participant for the anatomical delineation of regions of interest (ROIs) generated using the semi- automated software (ROMI, Toronto, Ontario) (29). A two-tissue compartment model was applied to the time-activity curves from regions of interest to measure TSPO VT, which is the optimal model for [ ^l8 F]FEPPA PET (30) (see below for additional detail).

Peripheral Inflammatory Marker Measurements:

PGE2 and PGF2 _a concentrations were determined using the competitive immunoassay, Prostaglandin E2 Assay (Parameter, R&D Systems Inc) and Prostaglandin F2 _a ELISA Kit (MyBioSource) respectively. TNFa level was analyzed using the Human Adipokine Magnetic Bead Panel 2 (Milliplex MAP, EMD Millipore Corp) and CRP was analyzed with the CRPHS Assay (Cobas C, Roche Diagnostics). PGE2 and TNFa levels were measured twice in the same sample and the mean value was applied, and all other markers were measured in singleton. Further details regarding sample collection are described below. Statistical Analyses:

For the main analyses, TSPO VT was the dependent variable and the natural logarithm of the blood markers (PGE ₂ /CRP, PGF _2a /CRP, and TNFa/CRP) were each assessed separately as predictor variables in a linear regression in each cohort. The natural logarithm was applied to produce a normal distribution of the predictor variables. To address for the effect of the rs6971 genotype on TSPO VT, a corrective adjustment was applied to the mixed-affinity binder (MAB) TSPO VT values based on a linear regression assessing the effect of genotype with regional TSPO VT as the dependent variable such that the differential effect of genotype was added to the TSPO VT of the MAB subjects (see below for further description). Since PGE2/CRP was the primary hypothesized predictor, the threshold for significance for the linear regression was set at 0.05 for each cohort. For the other two main predictor markers being assessed (PGF2 _« /CRP and

TNFa/CRP), the threshold for significance of the linear regression was set at p<0.017 since inclusion of these two measures resulted in a total of three high priority measures. For statistical analysis, the adjusted R ² was assessed and reported.

Also, receiver operator characteristic (ROC) curves were generated to evaluate the performance of consistently predictive biomarkers. For this, TSPO V _T values from all subjects were treated as dichotomous variables with PFC TSPO VT >13.5 for MDE and TRD, and dorsal caudate TSPO

VT >9.4 for OCD (after adjusting MAB TSPO VT as described in the preceding paragraph).

These thresholds correspond to -30% greater than healthy controls representing approximately a 2 standard deviation difference. All analyses were performed using IBM SPSS Statistics (version 21).

Results:

Linear Regression Assessing Relationship of Blood Markers to TSPO V _T :

Ln(PGE2/CRP) and ln(TNFa/CRP) were consistent, highly significant correlates of TSPO V _T for all three cohorts (Figure 1, Table 2; ln(PGE2/CRP): MDE, Fi _{, 19} =10.3 to 11.8, p=0.0030 to 0.0048; TRD F ₅ =7.7 to 10.0, p=0.0026 to 0.0076; OCD, F ₉ =7.0 to 11.3, p=0.0035 to 0.016), especially in the MDE and OCD cohorts in which they accounted for 24.1 to 36.2% of the variance. Ln(PGF2 _a /CRP) was only significantly predictive in the MDE and OCD cohorts (Table 2; MDE, Fi _{, 19} =9.1, p=0.0093; OCD, F _W9 =25.5, pO.OOOl); accounting for 35.0% and 56.3% of the variance respectively (Figure 4). Since TSPO V _T tended to be highly correlated across regions, the predictors tended to also be correlated with TSPO V _T values in other brain regions (Table 3).

Receiver Operating Characteristic (ROC) Curve Analysis with A Priori Hypothesized Blood Markers:

ROC curve analyses were applied for the collective depressed sample (MDE and TRD n=76) for ln(PGE2/CRP) and ln(TNFa/CRP), assessing revealed an accuracy of 74.9% (p=0.00021, 95% confidence interval [63.5, 86.4]) and 78.1% (p<0.0001, 95% confidence interval [67.5, 88.7]) in the ability of the blood marker to correctly classify those with and without elevated PFC TSPO V _T (Figure 2). ROC curve analyses were applied for the OCD cohort for ln(PGE2/CRP), ln(PGF2 _a /CRP), and ln(TNFa/CRP), assessing revealed an accuracy of 80.2% (p=0.029, 95% confidence interval [58.4, 100.0]), 79.1% (p=0.036, 95% confidence interval [57.5, 100.0]), and 81.3% (p=0.024, 95% confidence interval [60.0, 100.0]), respectively, in the ability of the blood marker to correctly classify those with and without elevated dorsal caudate TSPO V _T (Table 4).

Relationship of Positive Predictive Value and Sample Retention:

In the collective MDE and TRD sample, varying thresholds of ln(PGE2/CRP) and ln(TNFa/CRP) were assessed in relation to the positive predictive value and proportion of participants retained as these are key practical values for practical use of blood markers in clinical trials, for example. With cut-offs of ln(PGE ₂ /CRP)=6.9 and ln(TNFa/CRP)=2.1 respectively in the depressed sample, positive predictive values greater than 80% for elevated prefrontal cortex TSPO VT were possible while retaining 40% of the participants (Figure 3). Similarly, a threshold serum value of 7.3 for ln(PGE2/CRP) or 1.9 for ln(TNFa/CRP) in OCD subjects selects approximately 50% of cases of which 85% have dorsal caudate TSPO VT values more than 9.4.

Post-Hoc Analyses:

Since the ln(PGE2/CRP) or ln(TNFa/CRP) may be equivalently expressed as ln(PGE2) minus ln(CRP) or ln(TNFa) minus ln(CRP) respectively, it was contemplated to test different linear combinations of ln(PGE2) and ln(TNFa) with ln(CRP) with linear regression (see below). The most optimal predictor was ln(CRP) alone which resulted in higher levels of significance in predicting PFC TSPO VT in MDE and TRD participants and dorsal caudate TSPO VT in OCD participants (MDE: F ₉ =13.0, R ² =0.39, p=0.0020; TRD: F ₅ =17.0, R ² =0.23, p=0.00013; OCD: Fi _,i9 =9.8, R ² =0.32, p=0.00058). The ROC curve analysis of ln(CRP) in the OCD cohort revealed an accuracy of 81.3% (p=0.024, 95% confidence interval [61.5, 100.0]) (Table 4). Interestingly, predictiveness increased further in the collective depressed sample (MDE and TRD n=76) when body mass index (BMI) was included, leading to a ROC curve accuracy of 85.3% (see below for more detail and Figures 5-10).

Additional Information on Methods and Results:

Participants:

Exclusion criteria for all participants included pregnancy; history of substance abuse disorder; electroconvulsive therapy or mechanical brain stimulation treatments within the previous six months; use of anti-inflammatory drugs lasting at least one week within the past month; and current hormone replacement therapy. All participants underwent urine drug screening and all women under age 65 years underwent a urine pregnancy test on both enrollment and positron emission tomography (PET) scan days. Exclusion criteria for medication free subjects included no use of herbal, drug or medication, except oral contraceptives, for at least six weeks. All participants reported no recent infections of at least four weeks prior to PET scanning. Participants taking medication reported receiving a stable dose for least four weeks. Treatment resistant major depressive disorder subjects were currently taking an antidepressant and had a history of non-response to two antidepressants and a history of non-response to at least one antidepressant whose mechanism of action raises extracellular serotonin level and one antidepressant whose mechanism of action raises extracellular norepinephrine level. The binding affinity of all newer radioligands for translocator protein (TSPO), including [ ¹⁸ F]FEPPA, are affected by a single-nucleotide polymorphism (rs6971) of the TSPO gene (40) and 90 to 95% of the population in the Greater Toronto Area have either the high-affinity binding (Alal47/Alal47) or mixed-affinity binding (MAB) (Alal47/Thrl47) genotypes (41-43). Subjects with homozygote low-affinity binding (Thrl47/Thrl47) were excluded from data analysis.

Fifty-six treatment resistant depressed (TRD) participants were taking medication at a stable clinical dose for at least 4 weeks prior to PET scanning. Table 6 provides the current medication and dose of each TRD participant. 48 (85.7%) of TRD participants were taking either a selective serotonin reuptake inhibitor or a selective serotonin and norepinephrine reuptake inhibitor.

Image Acquisition and Analysis:

Biexponential and Hill functions were used to fit the blood-to-plasma ratios and the percentage of unmetabolized tracer, respectively (44). The PET scan duration was 125 minutes following [ ¹⁸ F]FEPPA administration. The PET scans were obtained using a three-dimensional brain scanner (HRRT; CPS/Siemens, Knoxville, TN, USA); were corrected for attenuation using a single photon point source, cesium 137 (half-life, 30.2 years; energy, 662 keV); and were reconstructed using a filtered back-projection algorithm, with a Hann filter at Nyquist cut off frequency (44).

20 medication free major depressive episodes secondary to major depressive disorder (MDE) and 8 medication free obsessive compulsive disorder (OCD) participants underwent two-dimensional axial proton density magnetic resonance imaging (MRI) acquired with a General Electric (Milwaukee, WI, USA) Signa 1.5 T MRI scanner (section thickness, 2 mm; repetition time, >5300 ms; echo time, 13 ms; flip angle, 90°; number of excitations, 2; acquisition matrix, 256 x 256; and field of view, 22 cm). The remaining 12 OCD and 56 treatment resistant major depressive episodes secondary to major depressive disorder (TRD) participants underwent two- dimensional axial proton density MRI acquired with a General Electric (Milwaukee, WI, USA) Signa 3-T MRI scanner (section thickness, 2 mm; repetition time, 6000 ms; echo time, 8 ms; flip angle, 90°; number of excitations, 1; acquisition matrix, 256 x 192; and field of view, 16.5 cm). A subset of participants were scanned with both MRI machines. The differences in MRI acquisitions resulted in near identical TSPO VT values and regional volumes as previously described (n=12; r>0.97; P0.001) (42).

Peripheral Inflammatory Marker Measurements:

18 mL of blood was collected on the PET scan day intravenously and allowed to clot for 30 minutes at room temperature in a serum separator tube (BD Life Sciences, BD 367815 Tube Vacutainer) before centrifugation for 15 minutes at 4° Celsius and 1000 x g (Thermo Scientific, Heraeus Megafuge 16R Centrifuge). Serum was pipetted into 0.5 mL aliquots (Axygen, MaxyClear Snaplock Microtubes 1.5 mL) and samples were then immediately stored in a -80° Celsius freezer until assaying.

Statistical Analyses:

To address the effect of the rs6971 genotype on TSPO VT, a corrective adjustment to the MAB TSPO VT values was applied based on a linear regression assessing the effect of genotype. The differential effect of genotype in a linear regression was found for TSPO VT in each region. Then, for analyses assessing the effect of low-cost predictors on TSPO VT values, the MAB TSPO VT values were first adjusted by adding the differential effect of genotype to the TSPO VT values. An alternative method sometimes applied in the literature (43, 45) of multiplying by a factor of 1.4 was also evaluated and yielded similar adjustments (correlation of TSPO VT in MAB between methods, MDE: r=0.97, p<0.0001, n=20; TRD: r=0.97, p<0.0001, n=56; and OCD: r=0.93, p<0.0001, n=20).

Post-Hoc Analyses:

Assessing A*ln(PGE2) + B*ln(TNFa) - ln(CRP) where A equals 0 to 1 in steps of 0.1 and B equals 0 to 1 in steps of 0.1 led to 121 different sets of predictors. The resultant adjusted R ² values as predictors of the combined MDD and TRD groups, for which PFC TSPO VT could be evaluated as the dependent variable were determined (Table 5). Review of the combinations indicated the predictors that accounted for higher levels of variance were associated with low values for A and B, including zero for each. Subsequently, a stepwise regression was applied to assess the predictors of ln(PGE2), ln(TNFa), and ln(CRP) on PFC TSPO VT in the collective depressed sample (MDE and TRD n=76). Only ln(CRP) was significant [ln(CRP): Fi _{, 75} =26.9, R ² =0.26, pO.OOOl]

Subsequently ln(CRP) was assessed as a predictor of TSPO VT across the three cohorts and it consistently showed highly significant correlations (Figure 5; ln(CRP): MDE, Fu9= 13.0,

p=0.00058). ROC curve analyses were applied for the collective depressed sample (n=76) for - ln(CRP). Analysis revealed an accuracy of 81.8% (pO.OOOl, 95% confidence interval [72.5, 91.1]) in the ability to correctly classify those with and without elevated PFC TSPO VT (Figure 6)·

In the collective MDE and TRD sample (n=76), varying thresholds of -ln(CRP) were assessed in relation to the positive predictive value and proportion of participants retained as these are key practical values for practical use of biomarkers in clinical trials, for example. With cut-offs of - ln(CRP)=0.6 in the depressed sample, positive predictive values for elevated prefrontal cortex TSPO VT exceeding 80% were possible while retaining 65% of the sample (Figure 7).

Also, since body mass index (BMI) is predictive of TSPO VT in MDE (41, 46) it was evaluated as an additional predictor to -ln(CRP). In the collective depressed sample (MDE and TRD n=76), it was additionally predictive of PFC TSPO VT (F2 _{, 75} =17.8, R ² =0.31, pO.OOOl), but not dorsal caudate TSPO VT in the OCD sample. A set of predictor values was constructed from the linear combination of -ln(CRP) and BMI values [1.071*-ln(CRP) - 0.184*BMI] [-ln(CRP) standard error: 0.29; BMI standard error: 0.071] that optimally accounted for variance in PFC TSPO VT in the collective depressed sample. This set of values was significantly predictive of PFC TSPO VT (MDE: Fi _{, 19} =14.7, R ² =0.42, p=0.0012; TRD: Fi _{, 55} =22.7, R ² =0.28, pO.OOOl ; collective depressed sample: Fi _{, 75} =36.0, R ² =0.32, pO.OOOl; Figure 8) and was then applied in ROC analyses, revealing an accuracy of 85.3% (p<0.0001, 95% confidence interval [76.7, 93.8]) in the ability to correctly classify those with and without elevated PFC TSPO VT (Figure 9). Also, the same set of predictor variables was assessed in relation to the positive predictive value and proportion of subjects retained. With cut-offs of [1.071*-ln(CRP) - 0.184*BMI]=-3.5 in the collective depressed sample, positive predictive values for elevated prefrontal cortex TSPO VT exceeding 80% were possible while retaining 65% of the sample (Figure 10). In addition, there was no significant correlation between BMI and CRP (Pearson Correlation, 2-tailed: r=0.14, P=0.19; n=96).

Although the a priori region is different in OCD, ROC curve analyses were applied for the whole sample (n=96) for ln(PGE2/CRP) and ln(TNF _o /CRP) to assess the ability of the blood markers to correctly classify those with and without elevated PFC TSPO VT (see Figure 12). Assessing revealed an accuracy of 72.9% (P=0.00013, 95% confidence interval [62.5, 83.2]) and 76.6 (P<0.0001, 95% confidence interval [66.7, 86.4]) in the abilities for the blood markers to correctly classify those with and without elevated PFC TSPO VT (Figure 12). These results are similar to those for the collected depressed sample (MDE and TRD n=76) as described.

To rule out a potential bias from a relationship between free fraction in plasma (fp) and individual serum biomarkers, we evaluated these relationships and found no significant correlation between fp and the serum biomarkers in any group:

MDE group, Pearson Correlations, 2-tailed

Variables: fp and ln(PGE2/CRP) (n=20): r=-0.19, P=0.41

Variables: fp and ln(PGF _o /CRP) (n=16): r=0.082, P=0.76

Variables: fp and ln(TNF„/CRP) (n=20): r=-0.37, P=0.11

OCD group, Pearson Correlations, 2-tailed

Variables: fp and ln(PGE2/CRP) (n=19): r=0.44, P=0.059

Variables: fp and ln(PGF _2o /CRP) (n=19): r=0.25, P=0.30

Variables: fp and ln(TNF„/CRP) (n=19): r=0.34, P=0.16

TRD group, Pearson Correlations, 2-tailed

Variables: fp and ln(PGE2/CRP) (n=52): r=-0.11, P=0.44 Variables: fp and ln(PGF _2o /CRP) (n=52): r=-0.023, P=0.87

Variables: fp and ln(TNF„/CRP) (n=52): r=0.11, P=0.46

Table 1. Demographic Characteristics

¹ Single nucleotide polymorphism rs6971 of the TSPO gene known to influence [ ¹⁸ F]FEPPA binding: HAB, high affinity binders; MAB, mixed affinity binders.

² 17-item Hamilton Depression Rating Scale (HDRS); scores derived on the day of scanning.

³ Missing data in one medication free MDE subject.

⁴ Pearson chi-squared test.

⁵ Analysis of variance. 6 MDE for MDD; or first episode of OCD symptoms for OCD cases. Abbreviations: BMI, body mass index; MDD, major depressive disorder; MDE, major depressive episode; NA, not applicable; No., number; OCD, obsessive compulsive disorder; SD, standard deviation; TSPO, translocator protein; Y-BOCS, Yale-Brown Obsessive-Compulsive Scale.

Table 2. Relationship of Serum Predictor Markers to TSPO VT

1 Linear regression with genotyped adjusted TSPO V _T as dependent variable with predictor listed as independent.

² PGF ₂₀₁ data missing from 4 medication free MDE subjects.

Abbreviations: CRP, c-reactive protein; MDE, major depressive episode; n, number; OCD, obsessive compulsive disorder; PGE ₂ , prostaglandin E ₂ ; PGF _2a , prostaglandin F ₂ alpha; TNFa, tumor necrosis factor alpha; TRD, treatment resistant depression; and TSPO VT, translocator protein distribution volume.

Table 3. Correlations of Blood Serum Markers with TSPO VT Across All Brain Regions

¹ Linear regression with genotype adjusted TSPO V _T as as independent.

² PGFz _a data missing from 4 medication free MDE subjects.

³ Poor fit such that the sum of squares is higher than use of the mean value.

Abbreviations: CRP, c-reactive protein; MDE, medication free major depressive episodes secondary to major depressive disorder; OCD, obsessive compulsive disorder; PGE ₂ , prostaglandin E ₂ ; PGF _2a , prostaglandin F ₂ alpha; TNFa, tumor necrosis factor alpha; TRD, treatment resistant major depressive episodes secondary to major depressive disorder; TSPO V _T , translocator protein distribution volume.

Table 4. Receiver Operating Characteristics of Serum Markers for TSPO VT Elevation of 30 %

1 Under the nonparametric assumption

² Null hypothesis: true area=0.50

Abbreviations: CRP, c-reactive protein; OCD, obsessive compulsive disorder; PGE ₂ , prostaglandin E ₂ ; PGF _2a , prostaglandin F ₂ alpha; TNFa, tumor necrosis factor alpha.

Table 5. Contribution to Variance Assessed by Varying Weightings of Serum Markers

Adjusted R ² values were evaluated post-hoc in the collective depressed sample (MDE and TRD, n=76). Independent predictor variables were constructed by varying weightings of ln(PGE ₂ ) and ln(TNFa) using a model of A*ln(PGE ₂ ) + B*ln(TNFa) - ln(CRP). Contribution to variance was obtained using linear regression with the prefrontal cortex TSPO VT adjusted for genotype as dependent variable. Abbreviations: CRP, c-reactive protein; MDE, medication free major depressive episodes secondary to major depressive disorder; PGE ₂ , prostaglandin E ₂ ; TNFa, tumor necrosis factor alpha; TRD, treatment resistant major depressive episodes secondary to major depressive disorder; TSPO VT, translocator protein distribution volume.

Table 6. List of Medications for Treatment Resistant Depressed Participants

Abbreviations: PRN, pro re nata (as needed).

Discussion:

In this example, it is found that composite blood serum measures of products synthesized by activated microglia that also have strong efflux from the central nervous system, controlled for by peripheral inflammation are consistently significantly correlated with TSPO V _T . The predictiveness of two such measures created a priori, ln(PGE2/CRP) and ln(TNFa/CRP), replicate across three cohorts. However, it was also noted that ln(PGF2 _« /CRP) was accounted for a high proportion of variance of TSPO V _T in the OCD sample and that in post-hoc analyses that the ln(CRP) was, on average, a stronger predictor of TSPO V _T across the three cohorts. Relatively low cost predictive markers of TSPO V _T may have major implications for subject stratification for clinical trials of therapeutics targeting activated microglia, for example.

The present studies demonstrate that either serum ln(PGE2/CRP) or ln(TNFa/CRP) consistently identifies a subsample with a high TSPO V _T phenotype. Figure 3, indicates that a threshold serum value of 6.9 for ln(PGE2/CRP) or 2.1 for ln(TNFa/CRP) in the combined MDE and TRD samples selects a subsample of approximately 40% of cases of which 80% have prefrontal cortex TSPO V _T values more than 13.5, which corresponds to 2 standard deviations above the mean of health. Similarly, a threshold serum value of 7.3 for ln(PGE2/CRP) or 1.9 for ln(TNFa/CRP) in OCD subjects (n=20) selects approximately 50% of cases of which 85% have dorsal caudate TSPO V _T values more than 9.4. Since the heterogeneity of TSPO V _T elevation ranges from 0% to over 100% in primary regions of interest for MDE and OCD (2-4), these serum thresholds may represent a practical low-cost option to stratify subjects, for example. Moreover, it is contemplated that these thresholds may be assessed in clinical trials, particularly for MDD and TRD for which therapeutic development to target microglial activation is actively occurring with, for example, P2X7 antagonists for microglial proliferation, indolamine 2,3 dioxygenase inhibitors to promote conversion of tryptophan towards serotonin rather than the kyurenine pathway; as well as repurposed medications like minocycline and the simvastatin that influence major histocompatibility protein II to reduce adverse functions of microglial activation (31, 32), for example.

A consistent, positive relationship between blood markers of inflammation and TSPO V _T in brain is desirable in the field. In a sample of 30 subjects (14 cases with schizophrenia and 16 healthy), no significant relationships were found between TSPO V _T and plasma IL-6, TNFa, plasma interferon gamma (IFNy), plasma IL-10, or cerebrospinal fluid IL-6 levels (33). In a sample of 8 healthy subjects exposed to lipopolysaccharide, Sandiego et al. demonstrated elevations in TSPO V _T as well as TNFa, plasma IFNy, IL-6, IL-8, and IL-10, but there was no correlation between change among brain and peripheral blood measures (34). Similarly reported no relationship between blood CRP level and TSPO V _T was reported in a sample of 10 MDD subjects some of whom were currently in a MDE, nor in a previous sample of 20 MDE subjects (7, 35). In a sample of 48 MDD subjects with concurrent TSPO imaging and plasma samples, among 8 plasma measures including CRP, Richards et al. reported one positive correlation of plasma adiponectin, at an exploratory uncorrected significance (4).

There were several additional predictors of interest, due to the high level of variance in TSPO V _T accounted for by the markers. Although all cohorts included those with neuropsychiatric disease, the diseases were not identical, hence, ln(PGF2 _a /CRP), accounting for 56% of the variance in TSPO V _T in the dorsal caudate in medication free OCD but not predictive in the TRD sample, may be reassessed in medication free OCD and/or for OCD specificity, for example. Similarly, since In CRP and BMI collectively, albeit with most of the impact from ln(CRP), accounted for 32% of the variance and 85.3% of the area under the ROC to predict elevated TSPO VT in the collective MDE and TRD cohorts; and that the relationship between BMI and TSPO V _T was also reported in a separate sample (4) suggest that this combination may be of particular interest in MDE and TRD samples.

Elevated TSPO V _T is associated with a morphological change in microglia to an activated state but does not indicate how the microglia are functioning. TSPO imaging may not be fully selective for microglial activation since TSPO may be detectable in other cells such as astroglia and endothelial cells, however, the elevation in TSPO level from most paradigms that activate microglia, such as stroke, toxins, or lipopolysaccharide is strongly associated with concurrent markers of microglial and not astroglial activation (36, 37). PGE2 and TNFa, while synthesized by activated microglia may not be specific to such, for example, they may also be produced by activated astrocytes (38, 39). The relationship of the prioritized blood markers to elevated brain TSPO VT in healthy subjects was not specifically assessed because in health, TSPO VT has a limited range and is not commonly elevated. Also, since activated microglia function differently during disease it was not assumed that the relationships of TSPO VT to PGE2 and TNFa in illness are similar in health. To apply these blood measures in clinical trials, in particular, it is contemplated that a highly similar protocol may be used for blood preparation in order to avoid potentially rapid degradation of PGE2 and TNFa since the blood samples taken were converted into serum over 30 minutes, placed in a chilled centrifuge and stored quickly at -80° Celsius (see Additional Information above). The subject sample also reported no recent infections in the four weeks prior to scanning which may have lowered variability in the TSPO VT measure. Results are empirically based on the relationship of several predictor values with TSPO VT and after assessing a number of these in a post-hoc manner it was noted that there are several combinations and/or selections of such parameters, such as ln(CRP), which in some examples both alone and in combination with BMI value yields even greater levels of predictiveness for TSPO V _T (see Figures 8-10).

In summary, the studies in this example assessed a general strategy of testing the serum ratio of products synthesized by activated microglia that are also actively removed from the central nervous system, controlled for by markers of peripheral inflammation, and identified the natural logarithm of serum PGE2/CRP and TNFa/CRP, as highly significant correlates of TSPO VT in brain in three separate samples. It was also noted in post-hoc analyses several linear combinations of markers that were also highly predictive including ln(CRP) itself as well as in combination with BMI. These measures may be applied at thresholds with high positive predictive value to select subjects with elevated TSPO VT thereby addressing the heterogeneity of the TSPO VT marker when recruiting subjects for clinical trials of therapeutics targeting microglial activation, for example. Moreover, in certain embodiments it is contemplated that systematically assessing collective predictor(s) in relation to TSPO V _T may provide more individualized clinical care of neuropsychiatric illnesses with elevated microglial activation, for example. EXAMPLE 2 - Investigation of -ln[CRP] as a Predictor of Cumulative Change in Severity in MDE following Treatment with Celecoxib

In this example, a study was performed to investigate particular markers (and, in particular, -ln[CRP]) as a predictor of cumulative change in severity of MDE in an open label trial of celecoxib. In these studies, there was no significant correlation between PGE2, TNFa, PGF2 _a , or the In transform of these variables with regional TSPO VT. Since -ln[CRP] is predictive of prefrontal cortex TSPO VT (see above), and since prefrontal cortex TSPO VT is a predictor of the cumulative change in severity of MDE in the dataset of an open label clinical trial of celecoxib, this example assessed -InCRP as a predictor of cumulative change in severity of MDE. The underlying principle was that subjects with low severity of brain inflammation may have little or no drop in severity of symptoms with celecoxib addition, and that those subjects with greater severity of brain inflammation may be more likely to have a decline in severity of depression. Forty subjects completed all procedures.

Results are shown in Figure 11, which shows reduction in symptom severity versus serum biomarker. Fitting the plot of the -In transformation of baseline C-reactive protein was related to the cumulative mean change in severity of depression with a fitting of a four parameter sigmoidal curve y=-3.08+ 5.43/(l+exp(-(x+1.0159)/(-0.82))). The adjusted Rsquare was 0.79, suggesting that 79% of the variance was accounted for by -ln(CRP). CRP was in units of mg/L. The change in Hamilton Depression Rating Scale (HDRS) was the difference between the first HDRS measure and the last HDRS measure after open label administration of celecoxib titrated within 2 weeks to an intervention dose of 200mg twice per day which was, after titration, given for 6 weeks to cases of major depressive disorder non responsive to their current medication treatment (N=40 subjects). These results indicate -ln(CRP) as an indicator for identifying a subpopulation of subjects having depression which may be more likely to benefit from treatment with an anti-inflammatory agent such as celecoxib.

One or more illustrative embodiments have been described by way of example. It will be understood to persons skilled in the art that a number of variations and modifications can be made without departing from the scope of the invention as defined in the claims.

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