Buccal swab biomarkers for schizophrenia

Abstract

Provided are methods for diagnosing and treating schizophrenia based on the presence of biomarkers for schizophrenia. The biomarkers can comprise specificity protein 4 (SP4) mRNA and heat shock protein 60 (HSP60) protein.

Description

[0001] Docket No. 070439.01926

[0002] BUCCAL SWAB BIOMARKERS FOR SCHIZOPHRENIA CROSS-REFERENCE TO RELATED APPLICATIONS This application is entitled to priority pursuant to 35 U.S.C. §119(e) to

[0003] U.S. Provisional Patent Application No. 63 / 745.562, filed on January 15. 2025. The content of the application is incorporated herein by reference in its entirety.

[0004] REFERENCE TO AN ELECTRONIC SEQUENCE LISTING

[0005] The contents of the electronic sequence listing (070439.01926SeqList.xml; Size: 28,391 bytes; and Date of Creation: December 18, 2025) is herein incorporated by reference in its entirety.

[0006] FIELD OF THE INVENTION

[0007] The present invention relates to methods for diagnosing and treating schizophrenia.

[0008] BACKGROUND

[0009] Schizophrenia (SCZ) is a debilitating and chronic psychiatric illness characterized by three clusters of symptoms: positive, negative, and cognitive. Positive symptoms describe experiences present in patients that are absent in healthy individuals, such as delusions and hallucinations. Negative symptoms describe behaviors and experiences absent in patients but present in healthy populations, including flat affect, avolition, and social withdrawal.

[0010] Cognitive

[0011] symptoms describe deficits in a range of cognitive functions, including attention, memory, abstraction, problem solving, and executive functioning. Negative and cognitive symptoms are

[0012] particularly difficult to ameliorate with current medications, yet they contribute substantially to

[0013] disability7.

[0014] SCZ has an estimated global age-standardized point prevalence of 0.28%. Despite this low prevalence, SCZ contributes substantially to the global burden of disease, resulting in 13.4 million years of life lived with disability. Moreover, only -13.5% of patients with SCZ recover, based on clinical and social recovery indices. Many do not respond well to current treatments, and common outcomes include poor quality of life, social disability, long-term hospitalization, suicide attempts, and premature mortality. Despite a two- to three-fold increased risk of death for individuals with SCZ, disease etiology is still poorly understood.

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[0017] This is predominately because SCZ is highly heterogeneous and polygenic, making it particularly challenging to identify the genetic causes of the disease.

[0018] Currently, psychiatrists rely on diagnostic frameworks described in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) to make categorical diagnoses based on behavioral phenotypes. Molecular and clinical neuroscience findings are not considered. Thus, it is likely that diagnostic categories for SCZ include individuals with multiple and different underlying pathophysiologies. Psychiatric medications are prescribed in a trial-and-error fashion, and identification of an effective medication regimen can take up to a year. Medications are

[0019] prescribed to treat SCZ symptoms, not the underlying biological mechanisms. Current treatments for SCZ only alleviate a subset of disease symptoms and have several undesirable side effects, resulting in low treatment compliance among patients.

[0020] To improve the diagnosis and treatment of SCZ, it is imperative to identify relevant biomarkers. Biomarkers are useful for diagnostic purposes, monitoring disease progression, increasing therapeutic efficacy, and understanding biological mechanisms. Genetic markers, blood and tissue-derived markers (e.g., protein levels), electroencephalographic signatures, and

[0021] neuroimaging and neuropsychological task-based markers, are essential for understanding the pathophysiology of psychiatric diseases. However, there are no standard biomarkers used to diagnose and aid in the treatment of patients with SCZ.

[0022] SUMMARY OF THE INVENTION

[0023] In one aspect, this disclosure provides methods for diagnosing, predicting the outcome or prognosis, and treating schizophrenia based on the presence of biomarkers for schizophrenia. In one aspect, provided is a method of diagnosing schizophrenia in a subject in need thereof, comprising:

[0024] a) collecting buccal cells from the subject;

[0025] b) extracting DNA, mRNA, and protein from the buccal cells; and

[0026] c) quantifying an amount of mRNA and protein of at least one biomarker of schizophrenia;

[0027] wherein an increase in the mRNA or protein of the biomarker compared to a subject who does not have schizophrenia correlates with symptoms of schizophrenia.

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[0030] In one embodiment, the biomarker is heat shock protein 60 (HSP60) protein or specificity protein 4 (SP4) mRNA. In one embodiment, the subject has an increase in both HSP60 protein and SP4 mRNA.

[0031] In some embodiments, the symptoms of schizophrenia comprise reduced short-term verbal memory, reduced response speed on a working memory task, depression, hallucinations, or anergia. In one embodiment, the symptoms of schizophrenia are measured by Positive and Negative Syndrome Scale (PANSS). In one embodiment, the subject is a human.

[0032] In one embodiment, step a) comprises swabbing the buccal cells from the subject’s mouth. In one embodiment, real-time quantitative PCR (RT-qPCR) quantifies the amount of mRNA and mass spectrometry, ELISA, or Western blot analysis quantifies the amount of protein in step c).

[0033] In one aspect, provided is a method of treating schizophrenia in a subject in need thereof, comprising administering to the subject a therapeutic agent, wherein the subject has increased mRNA or protein levels of at least one biomarker of schizophrenia. In one embodiment, the at least one biomarker is HSP60 protein or SP4 mRNA. In one embodiment, the subject exhibits symptoms of schizophrenia measured by PANSS. In one embodiment, the therapeutic agent is an antipsychotic agent. In some embodiments, the antipsychotic agent comprises haloperidol, aripiprazole, olanzapine, quetiapine, xanomeline, or trospium chloride.

[0034] BRIEF DESCRIPTION OF THE DRAWINGS FIGS. 1A-1C demonstrate that expression of SP4 (specificity protein 4, HF1B or SPR-7), but not NOS LAP (nitric oxide synthase 1 adaptor protein) or Dexr as 1 (ras related dexamethasone induced 1, RASD1, or AGS1), mRNA is increased in buccal cells of patients with SCZ. FIG. 1A is a graph of the results of RT-qPCR analysis of SP4 mRNA (normalized to GAPDPP) in buccal cell extracts from patients with schizophrenia (SCZ; n=23) or control subjects (CTRL; n=22). *** / ?=().0009 as determined by unpaired t-test with Welch's correction for unequal variances. FIG. IB is a graph of the results of RT-qPCR analysis of NOS1AP mRNA (normalized to GAPDPT) in buccal cell extracts from patients with SCZ (n=20) or CTRL subjects(n=23). No changes were observed ( ?=0.59) as determined by unpaired t-test. FIG. 1C is a graph of the results of RT-qPCR analysis of DexrasYmRNA (normalized to GAPDPP) in buccal cell extracts from patients with SCZ (n=20) or CTRL 3

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[0036] subjects (n=22). No changes were observed (p=0.43) as determined by an unpaired t-test with Welch’s correction for unequal variances. Error bars represent SD. For all analyses, outliers were removed (A=4, B=6, C=9) using the ROUT method (Q=l %), and samples with Ct values below detection levels or without an age-, race-, and gender-matched control were removed.

[0037] FIGS. 2A-2H illustrate that SP4 mRNA expression in buccal cells correlates with slower response times on the AX-CPT and poorer performance on the recognition portion of the HVLT-R. FIG. 2A is a schematic of the four trial types in the AX-CPT task, with AX being the target. Created with BioRender.com. FIG. 2B is a graph of the mean reaction time by trial type. Multiple unpaired t-tests with Welch’s correction were used to determine differences by trial type. Adjusted p-values were calculated using the Holm-Sldak method. Significant differences in reaction times were seen across all trial types (p<.001). FIG. 2C is a graph of the mean error rate by trial type. Multiple unpaired t-tests with Welch’s correction were used to determine differences by trial ty pe. Adjusted p-values were calculated using the Holm-Sldak method. No significant differences between patients with SCZ and CTRL (control) subjects were observed for the AY (p=0.33) and BY (p=.79) trials. However, patients with SCZ had significantly higher mean error rates in the AX (p= 0.02) and BX (p= 0.01) trials. FIGS.2D-2F are graphs that show increased SP4 mRNA expression significantly correlates with higher AY, BX, and BY reaction times in the AX-CPT task as determined by Pearson’s r. two-tailed (AX: r(45) = 0.393, p = 0.008; BX: r(45) = 0.329, p = 0.027; AY: r(45) = 0.379, p = 0.010; BY: r(45) = 0.323, p = 0.030; r(45) = 0.498, p < 0.001).

[0038] FIG. 2G is a schematic of trial progression in the HVLT-R. Adapted from “Timeline (Layout 5x1)’’, by BioRender.com (2024). Retrieved from app.biorender.com / biorendertemplates. Unpaired t-tests were used to determine p-values; Welch’s correction was used in cases of unequal variance. Outliers (recognition n=l) were removed using the ROUT method (Q=l %). Patients with SCZ scored lower in the categories of total recall (p=0.004), delayed recall (p=0.0005), retention (p=0.012), and recognition (p<0.0001). Error bars represent SD.

[0039] FIG. 2H is a graph that shows that increased SP4 mRNA expression significantly correlates with lower recognition determination scores in the HVLT-R task as determined by Pearson’s r, two-tailed (r(45) = -0.43, p = 0.003).

[0040] FIGS. 3A-3E demonstrate that SP4 mRNA expression in buccal cells significantly correlates with symptom severity' as measured by the PANSS. FIGS. 3A-3E are graphs that show that increased SP4 mRNA expression significantly correlates with an increased

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[0043] presence of positive (FIG.3A), negative (FIG. 3B) symptoms and excitement (FIG. 3C), thought disturbance (FIG.3D), and paranoia / belligerence (FIG. 3E) as determined by Pearson’s r, two-tailed (r(45) = 0.393, p = 0.008; r(45) = 0.329, p = 0.027; r(45) = 0.379, / ? = 0.010; r(45) = 0.323, / ? = 0.030; r(45) = 0.498, / ? < 0.001, respectively).

[0044] FIGS. 4A-4E illustrate that HSP60 protein abundance in buccal swabs correlates with poor AX-CPT performance, deficits in delayed recall and retention on HVLT-R, and higher PANSS scores. Label-free quantitation of buccal swab proteomics reveals differences in the abundance of mitochondrial, immune, and metabolism associated proteins in SCZ subjects versus CTRL subjects. FIG. 4A is a graph of the relevant canonical pathways with the greatest differences in buccal cells from patients with SCZ versus CTRL subjects. Orange indicates a positive z-score, predicted pathway activation; blue indicates a negative z-score, predicted pathway inhibition; gray indicates that Ingenuity Pathway Analysis was unable to predict a pattern of activity. Opacity indicates the degree of predicted activation or inhibition. Data were analyzed and the graph was created with the use of QIAGEN IP A (QIAGEN Inc., digitalinsights.qiagen.com / IPA). FIG.4B is a graph that shows that HSP60 protein is in greater abundance in buccal cells from patients with SCZ (protein abundance normalized to CTRL; fold change=1.77). Error bars represent SD. FIG.4C is a graph that shows that increased HSP60 protein abundance significantly correlates w ith AX and BX error rate on the AX-CPT as determined by Pearson's r, two-tailed (r(l 8) = 0.48, p = 0.044, and r(l 8) = 0.606, p = 0.008, respectively). HSP60 protein abundance significantly correlates with slower reaction time in all trial types of the AX-CPT using Pearson’s r, two-tailed (AX: r( 18) = 0.608, p = 0.007; AY: r(l 8) = 0.671, p = 0.002; BX: r(l 8) = 0.527, p = 0.025,; BY: r(18) = 0.717, p < 0.001). FIG. 4D is a graph that shows that HSP60 protein abundance correlates ith deficits in delayed recall and retention in the HVLT-R task. Higher HSP60 protein abundance significantly correlates with lower retention and delayed recall scores as determined by Pearson’s r, two-tailed (r(l 8) = -0.483, p = 0.043, and r(l 8) = -0.484, p = 0.04, respectively). FIG. 4E is a graph that shows that increased HSP60 protein abundance correlates with the severity of negative symptoms (r(l 8) = 0.579, p = 0.012), anergia (r(l 8) = 0.660, p =0.003), and paranoia and belligerence (r(l 8) = 0.539, p = 0.021) on the PANSS as determined by Pearson’s r, two-tailed.

[0045] DETAILED DESCRIPTION OF THE INVENTION

[0046] This disclosure relates to an unexpected discovery that increased levels of heat shock protein 60 (HSP60) protein and SP4 mRNA correlate with symptoms of schizophrenia.

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[0049] Schizophrenia pathogenesis is heterogenous and polygenic in nature, making it difficult to diagnose and treat. Thus, the present disclosure addresses a critical need for easy-to-collect biomarkers that aid in the treatment of patients with schizophrenia.

[0050] HSP60 is a chaperone that belongs to class I chaperons. Specifically, HSP60 binds unfolded proteins and catalyzes their folding in an ATP-dependent manner. HSP60 is a nuclear-encoded protein synthesized in the cytoplasm and transported into the sub-cellular organelles.

[0051] SP4 is a transcription factor that binds to the to the GC promoter region of a variety of genes, including those of the photoreceptor signal transduction system. SP4 single nucleotide polymorphisms (SNPs) have been found to be associated with schizophrenia, major depressive disorder (MDD), and bipolar disorder.

[0052] In one aspect, provided is a method of diagnosing schizophrenia in a subject in need thereof, comprising:

[0053] a) collecting buccal cells from the subject;

[0054] b) extracting DNA, mRNA, and protein from the buccal cells; and

[0055] c) quantifying an amount of mRNA and protein of at least one biomarker of schizophrenia;

[0056] wherein an increase in the mRNA or protein of the biomarker compared to a subject who does not have schizophrenia correlates with symptoms of schizophrenia.

[0057] Buccal cells are cells that line the cheeks and lips. Buccal swabs can be collected as a non-invasive method to collet DNA samples. Buccal swabs generally use a collection device such as a cotton swab or a small brush to collect a sample of cells from the inside surface of the cheek. In one embodiment, the inside surface of the cheek is swabbed for one minute. In one embodiment, protein and DNA are extracted from the buccal cells using methods as known in the art.

[0058] In one embodiment, the biomarker is HSP60 protein or SP4 mRNA. In one embodiment, the subject has an increase in HSP60 protein and / or SP4 mRNA. In some embodiments, the subject has at least a 10% increase in HSP60 protein and / or SP4 mRNA, such as at least 10%. 20%. 30%. 40%. 50%. 60%. 70%. 80%. 90%. or 100% increase, or any amount therebetween.

[0059] In one embodiment, the biomarker is any one of the genes shown in Table 3. In one embodiment, the subject has an increase in any one of the proteins shown in Table 3. In some 6

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[0061] embodiments, the subject has at least a 10% increase in the protein or mRNA levels of any one of the biomarkers shown in Table 3, such as at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100% increase, or any amount therebetween.

[0062] In some embodiments, the symptoms of schizophrenia include, but are not limited to, reduced short-term verbal memory, reduced response speed on a working memory task, depression, hallucinations, or anergia. In one embodiment, the symptoms of schizophrenia are measured by Positive and Negative Syndrome Scale (PANSS). PANSS is known in the art as the gold standard or assessment of antipsychotic treatment efficacy (Kay SR, Fiszbein A, Opfer LA. The Positive and Negative Syndrome Scale (PANSS) for Schizophrenia.

[0063] Schizophrenia Bulletin 1987; 13(2): 261-276).

[0064] In one embodiment, step a) comprises swabbing the buccal cells from the subject's mouth. In one embodiment, real-time quantitative PCR (RT-qPCR) quantifies the amount of mRNA and mass spectrometry, ELISA, or Western blot analysis quantifies the amount of protein in step c).

[0065] In one aspect, provided is a method of treating schizophrenia in a subject in need thereof, comprising administering to the subject a therapeutic agent, wherein the subject has increased mRNA or protein levels of at least one biomarker of schizophrenia. In one aspect, the at least one biomarker is HSP60 protein or SP4 mRNA. In one embodiment, the subject exhibits symptoms of schizophrenia measured by PANSS.

[0066] In one embodiment, the therapeutic agent is an antipsychotic agent. In some embodiments, the antipsychotic agent comprises haloperidol, aripiprazole, olanzapine, quetiapine, xanomeline, or trospium chloride. Additional therapeutic agents can be found in U.S. Patent No. 11,129,807, which is herein incorporated by reference in its entirety.

[0067] In one embodiment, the therapeutic agent is administered to the subject at least once every day. In some embodiments, the therapeutic agent is administered to the subject at least once every week for one month, two months, three months, four months, five months, six months, seven months, eight months, nine months, ten months, eleven months, one year, or longer. A medical professional determines the duration of time for which the therapeutic agent is needed.

[0068] In one aspect, provided is a method of predicting the outcome or prognosis of a subject who has schizophrenia, wherein the subject has increased mRNA or protein levels of at least one biomarker of schizophrenia.

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[0071] As used herein and in the appended claims, the singular forms “a,” “and"’ and “the” include plural references unless the context clearly dictates otherwise.

[0072] As used herein, the term “diagnosed” or “diagnosing” refers to the identification of schizophrenia in a subject via symptoms and / or the presence of schizophrenia biomarkers.

[0073] As used herein, the term “treating” or “treatment” of any disease or disorder refers in one embodiment, to ameliorating schizophrenia (z.e., arresting or reducing the development of schizophrenia or at least one of the clinical symptoms thereof). In another embodiment, “treating” or “treatment” refers to ameliorating at least one physical parameter, which may not be discernible by the subject. In yet another embodiment, “treating” or “treatment” refers to modulating the disease or disorder, either physically, (e.g., stabilization of a discernible symptom), physiologically, (e g., stabilization of a physical parameter), or both. In yet another embodiment, “treating” or “treatment” refers to preventing or delaying the onset or development or progression of schizophrenia.

[0074] As used herein, the term “subject” refers to a mammal. The term “mammal” as used herein is intended to include, but is not limited to, humans, laboratory’ animals, domestic pets, and farm animals. Mammals, include, but are not limited to, a human or non-human mammal, such as a canine, bovine, equine, ovine, or feline, etc. Individuals and patients are also subjects herein.

[0075] As used herein, the terms “including,” “comprising,” “containing,” or “having” and variations thereof are meant to encompass the items listed thereafter and equivalents thereof as well as additional subject matter unless otherwise noted.

[0076] As used herein, the phrases “in one embodiment,” “in various embodiments,” “in some embodiments,” and the like are used repeatedly. Such phrases do not necessarily refer to the same embodiment, but they may unless the context dictates otherwise.

[0077] As used herein, the terms “and / or” or “ / ” means any one of the items, any combination of the items, or all of the items with which this term is associated.

[0078] As used herein, the term “each,” when used in reference to a collection of items, is intended to identify an individual item in the collection but does not necessarily refer to every item in the collection. Exceptions can occur if explicit disclosure or context clearly dictates otherwise. All publications mentioned herein are incorporated herein by reference in their entireties.

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[0081] EXAMPLES

[0082] Example 1. Materials and Methods

[0083] This Example details the materials and methods used in Examples 2-8.

[0084] Participants

[0085] All subjects were between 18-65 years of age. Healthy control subjects (n=27) were recruited from Rutgers University and the surrounding community and met the following criteria: 1) no diagnosis of a neurological or psychiatric disorder, 2) no history of psychotic episodes, 3) not currently taking antipsychotics, antidepressants, orNMDA receptor agonists / antagonists, and 4) no history of epilepsy or seizes. Patients with SCZ (n=27) were recruited from the Rutgers University Behavioral Health Care (UBHC) acute, extended partial, and inpatient hospitalization programs. All subjects with SCZ who participated in the study met the following criteria: 1) had a SCZ or schizoaffective diagnosis confirmed with the Structural Clinical Interview for the DSM-5 (SCID-5), 2) no diagnosis of another neurological or psychiatric disorder (such as bipolar disorder or Parkinson’s disease), and 3) no history of seizures or epilepsy. This study was approved by the Rutgers University Institutional Approval Board (IRB), Pro2020001322.

[0086] Control subjects were recruited who were age- (+ / - 6 years), race-, and gender-matched to each patient. In one pair, matched ethnicity, gender, and age were prioritized over race. Overall, only age-, race-, and gender-matched pairs, with no dropouts, were included in the analysis (SCZ n= 27, CTRL n=27). Demographic characteristics are shown in Table 1.

[0087] Table 1. Participant demographics. Demographic data for patients, age-, race-, and gender-matched control subjects, and aggregated samples.

[0088]

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[0091]

[0092] Structured interviews and cognitive tasks

[0093] Structured clinical interviews were performed at The Rutgers-Princeton Center for Computational Cognitive Neuropsychiatry' (CCNP) on Rutgers University' Busch campus in person or virtually over Zoom, based on the participant's preference. All computerized cognitive

[0094] tasks and neuropsychological measures were administered in-person at the CCNP.

[0095] Structured Clinical Interview for the DSM-5 (SCID-5)

[0096] This 1 to 2 hour semi-structured interview was used to determine any major DSM-5 diagnoses as described (First MB WJ. Karg RS. Spitzer RL. Structured Clinical Interview for DSM-5 — Research Version (SCID-5 for DSM-5, Research Version; SCID-5-RV). American Psychiatric Association: Arlington, V A, 2015).

[0097] Structured Clinical Interview for The Positive and Negative Syndrome Scale (SCI-PANSS) A 30-item structured interview was used to rate the intensity' of psychotic symptoms, as well as general psychopathology (e.g, depression, anxiety, mental status changes) in patients (Kay SR, Fiszbein A, Opfer LA. The Positive and Negative Syndrome Scale (PANSS) for

[0098] Schizophrenia. Schizophrenia Bulletin 1987; 13(2): 261-276). Specifically, 5-factor and cluster scoring were used to examine positive symptoms, negative symptoms, cognitive symptoms, excitement, depression, disorganization, anergia, thought disturbance, activation, and paranoia / belligerence.

[0099] AX continuous performance task (AX-CPT)

[0100] This task was acquired from The Cognitive Neuroscience Test Reliability7and Clinical applications for Schizophrenia (CNTRaCS) website by filling out the request form (Barch DM et al. Cognitive [Computational] Neuroscience Test Reliability and Clinical Applications for Serious Mental Illness (CNTRaCS) Consortium: Progress and Future Directions. In: Barch DM, Young JW (eds). Cognitive Functioning in Schizophrenia: Leveraging the RDoC Framework. Springer International Publishing: Cham, 2023, pp 19-60; Cognitive Neuroscience Test Reliability' and Clinical applications for Schizophrenia (CNTRaCS) Consortium, cntracs.ucdavis.edu / dpx). This computerized cognitive task took 20 minutes to 10

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[0102] complete and made use of two buttons. Participants were instructed to press one button when the target stimulus (i.e. the letter X’) was presented on the screen and the other button when any other stimulus was presented (i.e. the letter 'A’). The order in which the stimuli were presented is important; the letter ‘X’ is only a target when one specific letter precedes it (i.e. A >X is a target, but B >X is not). This task consisted of 4 blocks of 36 trials (144 total trials) (Cognitive Neuroscience Test Reliability and Clinical applications for Schizophrenia (CNTRaCS) Consortium, cntracs.ucdavis.edu / dpx). Specifically, this task consists of 104 AX trials, 16 AY trials, 16 BX trials, and 8 BY trials. (Id.). Each trial consists of a cue, interstimulus

[0103] interval, and target; each trial is separated by 1200 ms. (Id.). The cue (i.e. A or B) is displayed for 1000 ms. the interstimulus interval lasts for 2000 ms, and the target (i.e. X or Y) is displayed for 500 ms with a 1500 ms response period. (Id.).

[0104] Jittered-orientation visual integration task (JOVI)

[0105] This task was acquired from The Cognitive Neuroscience Test Reliability and Clinical Applications for Schizophrenia (CNTRaCS) website by filling out the request form (Barch DM, Boudewyn MA et al. Cognitive [Computational] Neuroscience Test Reliability and Clinical Applications for Serious Mental Illness (CNTRaCS) Consortium: Progress and Future Directions. In: Barch DM, Young JW (eds). Cognitive Functioning in Schizophrenia: Leveraging the RDoC Framework. Springer International Publishing: Cham, 2023. pp 19-60; Cognitive Neuroscience Test Reliability and Clinical applications for Schizophrenia (CNTRaCS) Consortium, cntracs.ucdavis.edu / dpx). This 15 minute assessment of visual integration was conducted on a computer and made use of two buttons. Participants were asked to look at a series of images composed of Gabor elements in which a closed egg shape, embedded within randomly oriented Gabors, either pointed to the left or to the right (Silverstein SM et al. Optimization

[0106] and Validation of a Visual Integration Test for Schizophrenia Research. Schizophrenia Bulletin 2012; 38(1): 125-134). This task included 6 conditions in which the degree of orientational jitter of the egg’s contour elements was varied (0°, 7°-8°, 9°-10°, 11°-12°, 13°- 14°, 15°-16°) (Cognitive Neuroscience Test Reliability and Clinical applications for Schizophrenia (CNTRaCS) Consortium, cntracs.ucdavis.edu / dpx). In addition, the task included trials containing no background elements and others in which a curved line was drawn that connected the contour elements. These ‘catch’ trials were included to identify subjects who responded randomly or were inattentive. In total, the task consisted of 24 blocks 11

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[0108] (4 blocks per condition), each containing 12 trials. (Id.). Each image was presented for 2 seconds with a 1 second interstimulus interval separating each trial (Silverstein SM et al. Optimization and Validation of a Visual Integration Test for Schizophrenia Research.

[0109] Schizophrenia Bulletin 2012; 38(1): 125-134).

[0110] Hopkins Verbal Learning Test-Revised (HVLT-R)

[0111] This 30 minute assessment of verbal learning and memory is composed of three learning trials, a delayed recall trial, and a recognition trial (Benedict RHB et al. Hopkins Verbal Learning Test -Revised: Normative Data and Analysis of Inter-Form and Test-Retest Reliability. The Clinical Neuropsychologist 1998; 12(1): 43-55). In each learning trial, participants were read a list of 12 nouns (each word belongs to one of three semantic categories, such as “vegetables”) and asked to repeat the words out loud after the experimenter finished reading the list. (Id. . The delayed recall trial was administered 20-25 minutes after the learning trials. (Id.).

[0112] During this portion of the task, participants were asked to verbally recall any words they remembered from the learning trials. (Id.). The recognition trial was then administered.

[0113] During the recognition trial, participants were read a list of words and indicated whether or not the word was included in the learning trials by responding "yes” or “no.” (Id.).

[0114] Buccal Swabs

[0115] Two buccal swabs were collected from each participant during the third session after completion of the cognitive tasks. Subjects were instructed to not eat or drink for two hours before swabbing. Buccal swabbing was performed by rotating a Cytobrush GT® (Cooper surgical, Trumbull, CT, USA) for protein and mRNA collection, on the inside of the subject’s cheek. Each cheek was swabbed for one minute. The Cytobrush GT® was inserted into a 15 ml conical tube containing ~4 ml of RNAlater (Thermo Fisher, Waltham, MA, USA; cat. no. AM7020). Both samples were stored at 4 °C for 2-4 days after which samples were stored at -80 °C until further processing.

[0116] Trizol extraction of RNA and protein from buccal cell samples

[0117] Samples were thawed on ice for an hour and then at room temperature for 15 minutes. RNAlater was removed via centrifugation at 5 000 x g for 10 minutes at 4 °C. Supernatant was

[0118] removed and then samples were spun down for an additional 5 minutes at 5 000 x g at 4 °C. Next, RNA and protein were extracted from the samples using Trizol (Thermo Fisher, cat. no.

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[0121] 15596026) following the manufacturer’s protocol.

[0122] Real-time ive PCR

[0123]

[0124] Buccal cell mRNA was extracted as described herein. cDNA was synthesized using the High-Capacity RNA-to-cDNA Kit (Applied Biosystems, Waltham. MA, USA; cat. no.

[0125] 4387406)

[0126] following the manufacturer’s protocol. RT-qPRC was performed using PowerUp SYBR Green

[0127] Master Mix (Thermo Fisher, cat. no. A25780) and gene-specific primers (Table 2). Samples were run in triplicate or quadruplicate in a 96 well plate (Thermo Fisher, cat. No.

[0128] 4481190). Human brain cDNA (Zyagen, San Diego, CA, USA; cat. no. HD-201) was used as a

[0129] positive control. QuantStudio 3 (Applied Biosystems) was used to determine Threshold cycle (Ct) values for SP4, Dexrasl, NOS1 AP, and GAPDH expression. Relative gene expression was determined by normalizing to GAPDH and performing 2'

[0130]

[0131] calculations following the methodology outlined in Schmittgen and Livak (Schmittgen TD et al. Analyzing real-time PCR data by the comparative CT method. Nature Protocols 2008; 3(6): 1101-1108).

[0132] Table 2. Primers used for RT-qPCR reactions.

[0133]

[0134] Proteomic analysis

[0135] Label-free quantitative (LFQ) proteomics was performed on extracts from a subset (males, ages 22-51) of patients with SCZ (n=9) and age- and gender-matched control subjects (n=9). Mass spectrometry analysis was performed by The Integrated Mass Spectrometry Unit at Michigan State University (Soliman AS et al. EFhd2 brain interactome reveals its association with different cellular and molecular processes. Journal of Neurochemistry 2021;

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[0138] 159(6): 992-1007). Five pg protein was buffer exchanged with 25 rnM ammonium bicarbonate. Detergents were removed via ethyl acetate extraction. Proteins were digested with lys-C / trypsin. 500 ng of digest was loaded for nanoLC-MS / MS analysis. Peptides were separated via revered-phase liquid chromatography (UltiMate™ 3000 RSLCnano) using a C18 Easy-Spray™ column and

[0139] a 2 hr, 4-95% ACN gradient. MSI and MS2 mass spectra (Q Exactive™ HF-X) were collected in top20 data-dependent mode, resolution 120k / 30k. Proteome Discoverer 2.5.0 with SEQUEST

[0140] HT was used for protein identification against the reviewed Uniprot Homo sapiens database (UP000005460), including L0R552 and contaminant sequences. The Percolator node was used

[0141] for FDR analysis. Abundances values were normalized to the total peptide amount of Homo sapiens sequences. For pathway analysis, proteins were uploaded into Ingenuity Pathway Analysis (IP A; QIAGEN Inc., Hilden, Germany) and filtered by removing proteins with Log2 < -0.3 and Log2 > 0.3. Data were analyzed with the use of QIAGEN IPA (QIAGEN Inc.,

[0142] digitalinsights.qiagen.com / IPA) 22. For biomarker identification, LFQ was run on a subset (males, ages 24-41) of patients (n=4) and matched controls (n=4) and filtered by removing proteins with fewer than 4 peptide spectral matches across all samples, common contaminant proteins, and proteins with less than a 20% difference between groups. This list of proteins was

[0143] then compared to a list of potential SP4 target genes (Silverstein SM et al. Optimization and Validation of a Visual Integration Test for Schizophrenia Research. Schizophrenia Bulletin 2012; 38(1): 125-134). Fourteen possible protein biomarkers were identified (Table 3), and HSP60 protein was chosen for targeted quantitation (tMS) in a larger subset of gender- and age-matched samples (males, ages 22-51, n=18). tMS analysis collected fragment spectra of the peptides reported in (Table 4). Skyline v. 23.1.0 was used for fragment ion quantitation.

[0144] Table 3. Representative SP4 targets that are SCZ risk genes.

[0145]

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[0148]

[0149] Table 4. Representative HSP60 tMS peptides.

[0150]

[0151] Statistical analysis

[0152] GraphPad Prism 10 and IBM SPSS Statistics (Version 29.0.2.0) software were used to analyze all data. Correlations or differences between groups were considered significant when p<0.05. Only patients with an age-, race-, and gender-matched controls were included in analysis.

[0153] Example 2. SCZ patients have significantly higher levels of SP4 mRNA in buccal cell swabs compared to that of controls.

[0154] Proteins encoded by two SCZ risk genes were selected - SP4 (specificity protein 4, Sp4) (Zhou X. Over-representation of potential SP4 target genes within schizophrenia-risk 15

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[0156] genes. Molecular Psychiatry 2022; 27(2): 849-854; Shmakova AA et al. Analysis of the Relationship between Genetic Factors and the Risk of Schizophrenia. Neuroscience and Behavioral Physiology 2023; 53(7): 1128-1138; Ripke S et al. Mapping genomic loci prioritises genes and

[0157] implicates synaptic biology' in schizophrenia. Cold Spring Harbor Laboratory 2020; and Singh T et al. Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia. Cold Spring Harbor Laboratory' 2020). NOS1AP (Nitric Oxide Synthase 1 Adaptor Protein) (Freudenberg F et al. Neuronal nitric oxide synthase (NOS1) and its

[0158] adaptor, NOS1AP, as a genetic risk factors for psychiatric disorders. Genes, Brain and Behavior 2015; 14(1): 46-63; Brzustowicz LM. NOS1AP in schizophrenia. Current Psychiatry Reports 2008; 10(2): 158-163; and Weber H et al. The genetic contribution of the NO system at the glutamatergic post-synapse to schizophrenia: Further evidence and metaanalysis. European

[0159] Neuropsychopharmacology 2014; 24(1): 65-85) - and a binding partner of NOS1AP.

[0160] RASD1 (encodes dexamethasone-induced ras-related protein 1; Dexrasl 29-31) as possible buccal cell biomarkers. RT-qPCR was performed to determine mRNA expression levels of the genes of interest in both patients and matched controls. Patients with SCZ had significantly higher buccal cell SP4 mRNA expression than CTRL subjects (p<0.001) (FIG.

[0161] 1A)

[0162] However, no such differences were observed for NOS1AP or RASD1 (FIGS. IB and 1C) These data suggest that SP4 mRNA is a buccal cell biomarker for SCZ.

[0163] Example 3. Higher SP4 mRNA expression in buccal cell swabs is associated with slower response times in the AX-CPT.

[0164] To determine whether changes to SP4 mRNA levels correlate with cognitive impairment,

[0165] clinical structured interviews and a battery of tasks were administered that are sensitive to the cognitive deficits characteristic of patients with SCZ. The subjects were tested using the AX-CPT and JOVI tasks, which measure goal maintenance and cognitive control (Paxton JL et al. Cognitive control, goal maintenance, and prefrontal function in healthy aging. Cereb Cortex 2008; 18(5): 1010-1028) and visual perception (Silverstein SM et al. Optimization and Validation of a Visual Integration Test for Schizophrenia Research. Schizophrenia 16

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[0167] Bulletin 2012; 38(1): 125-134), respectively. In all trial types of the AX-CPT (FIG. 2A), CTRL subjects demonstrated significantly faster performance than their SCZ counterparts ( / ?<0.001 ) (FIG. 2B). Similarly, on the AX and BX trials, patients with SCZ were significantly less accurate in their responses ( / ?<0.05) (FIG. 2C). On the JOVI task, CTRL subjects had significantly faster performance on the 0° jitter condition and both catch conditions ( / ?<0.05) when compared to SCZ patients. Moreover, in the 7°, 9°, and 11° conditions of the JOVI, SCZ patients made significantly more errors than CTRL groups ( / ?<0.05). There was a statistically

[0168] significant, moderate positive correlation between SP4 rnRNA expression and BY reaction time

[0169] in the AX-CPT task, (r(43) = .352, p = .021) (FIG. 2D). Additionally, a statistically significant, moderate positive correlation was observed between SP4 rnRNA expression and BX reaction time in the AX-CPT task, (r(43) = .400, p = .008) (FIG. 2E) and a statistically significant, moderate positive correlation between SP4 rnRNA expression and AY reaction time in the AX-CPT task, (r(43) = .316, / ? = .039) (FIG. 2F). No relationship was observed between SP4 mRNA expression in buccal swabs and JOVI reaction times. While SP4 rnRNA expression was significantly correlated with accuracy on the 15° jitter trial of the JOVI task (r(45) = 0.367, / ? = 0.013), overall, SP4 mRNA expression in buccal swabs was not correlated with accuracy on the JOVI. These data support the idea that higher SP4 rnRNA expression in buccal cells correlates with cognitive slowing on a working memory task.

[0170] Example 4. Higher buccal cell SP4 mRNA expression correlates with poorer performance on the recognition portion of the HVLT-R

[0171] To determine whether buccal cell SP4 rnRNA expression sen es as a biomarker for memory dysfunction in SCZ, the HVLT-R performance task was used. Overall, it was determined that SCZ patients demonstrate deficits in HVLT-R task performance.

[0172] Specifically, patients scored lower in the categories of total recall, delayed recall, retention, and recognition ( / ?<0.05) (FIG. 2G). The relationship between HVLT-R performance and SP4 mRNA expression w as then explored and a statistically significant, moderate negative correlation between SP4 mRNA expression and recognition determination in the HVLT-R task (r(45) = -.43, p = .003) was identified (FIG. 2H). Thus, higher SP4 mRNA expression predicts lower recognition, but not recall, performance supporting the hypothesis of a relationship between this biological variable and information encoding and / or storage impairments.

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[0175] Example 5. Higher SP4 mRNA expression in buccal cell swabs correlates with increased severity of symptoms

[0176] Since patients with SCZ experience defined symptoms, it was evaluated whether buccal SP4 mRNA expression levels correlate with the presence of these different symptoms using the SCIPANSS. Based on a 5-factor and cluster scoring solution, the SCZ cohort ranged from

[0177] moderately to markedly ill across factors (Table 5) (Wallwork RS etal. Searching for a consensus five-factor model of the Positive and Negative Syndrome Scale for schizophrenia. Schizophr Res 2012; 137(1-3): 246-250; Leucht S et al. What does the PANSS mean? Schizophrenia Research 2005; 79(2): 231-238; and Daneluzzo E et al. PANSS factors and scores in schizophrenic and bipolar disorders during an index acute episode: a further analysis of the cognitive component. Schizophrenia Research 2002:56(1): 129-136). A statistically significant,

[0178] moderate positive correlation between SP4 mRNA expression and the severity of positive (r(45)

[0179] = 0.393, p = 0.008) and negative (r(45) = 0.329, p = 0.027) symptoms was identified (FIGS.

[0180] 3A and 3B). Moreover, it was also observed significant relationships between SP4 mRNA expression and the severity of excitement (r(45) = 0.379, p = 0.010), thought disturbance (r(45) = 0.323, p = 0.030), and paranoia / belligerence (r(45) = 0.498, p < 0.001) symptoms (FIGS.3C and 3D). These data give additional support for the use of buccal cell SP4 mRNA as a useful biomarker related to the clinical expression of SCZ.

[0181] Table 5. PANSS scores. PANSS scores for both groups using 5-factor and cluster scoring. P-values determined using unpaired t-test with Welch’s correction for unequal variances.

[0182] <

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[0189]

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[0194]

[0195] Example 6. Mitochondrial and immune pathways are altered in buccal cells in patients Since SP4 is a transcription factor, it was determined whether any of its downstream targets could also be used as a biomarker for SCZ. Label-free quantitative (LFQ) proteomics was used to compare the profiles between patients with SCZ and control subjects. Data from a subset of age-matched and gender-uniform participants (n=18) were analyzed. Biological pathway analysis revealed significant abundance differences in a number of pathways, most notably mitochondrial and immune system proteins and protein metabolism (FIG.4A). Upon further analysis, it was determined that mitochondrial function is decreased, and immune activity is increased in patients with SCZ (FIG. 4A), in line with reports that these two processes are dysregulated in SCZ.

[0196] Example 7. HSP60, a heat shock protein involved in mitochondrial function and inflammatory responses, protein is increased in buccal swabs from SCZ patients

[0197] Proteins were searched for with genes that are known targets of SP4 (Zhou X. Overrepresentation of potential SP4 target genes within schizophrenia-risk genes. Molecular Psychiatry 2022; 27(2): 849-854) and exhibited at least a 20% change in abundance, as detected by label-free quantitative proteomics (n=8). Fourteen proteins were identified from the GWASTop357 list of the over-represented SCZ -risk genes with potential SP4 target sites Id.), including three heat shock proteins (HSP) (Table 3). Of these targets, this study focused on the chaperonin, HSP60. HSP60 plays a crucial role in mitochondrial function and immune signaling, both of which have been implicated in SCZ pathology. To further investigate whether HSP60 protein is a potential biomarker for SCZ, lysates were analyzed from a larger subset of gender and age matched samples (n=18) by targeted quantitation (tMS). While there was variation in protein abundance between samples, likely due to the heterogeneous pathology of SCZ, on average, HSP60 protein was more abundant in SCZ patients (abundance fold change=1.77) (FIG. 4B).

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[0199] Example 8. Higher buccal swab HSP60 protein abundance correlates with poorer performance on the AX-CPT, impaired delayed recall and retention, and increased severity of symptoms To determine whether HSP60 protein abundance correlates with aberrant cognitive control and goal maintenance commonly seen in SCZ (reviewed in Lesh TA et al. Cognitive control deficits in schizophrenia: mechanisms and meaning. Neuropsychopharmacology 2011; 36(1): 316-338). normalized HSP60 protein abundance values were compared with AX-CPT performance. A statistically significant, moderate positive correlation was observed between HSP60 protein abundance and AX error rate, (r(18) = 0.48, p = 0.044) and a significant, strong, positive correlation with BX error rate (r(18) = 0.606, / ? = 0.008) (FIG.

[0200] 4C). Additionally, moderate-strong positive correlations were observed between HSP60 protein abundance and reaction time in all trial types (AX: r(l 8) = 0.608. p = 0.007, AY : r(l 8) = 0.671, p = 0.002, BX: r(l 8) = 0.527, p = 0.025, BY: r(l 8) = 0.717, / ? < 0.001) (FIG.

[0201] 4C). HSP60 protein abundance significantly, moderately, and negatively correlated with retention (r(18) = -0.483, p = 0.043) and delayed recall (r(l 8) = -0.484, p = 0.042) on the HVLT-R (FIG. 4D). In addition, HSP60 protein abundance was significantly correlated with increased reaction time on the no background catch trials of the JOVI task (r( 18) = 0.652, p = 0.003). However, in the 15° jitter trials, HSP60 protein abundance was significantly correlated with decreased reaction time (r(l 8) = -0.524, ? = 0.26). HSP60 protein abundance also correlates with symptom severity (negative: r(l 8) = 0.579, / ? = 0.012, anergia: r(l 8) = 0.660, / ? = 0.003. and paranoia and belligerence: r(l 8) = 0.539, p = 0.021) (FIG. 4E).

[0202] Together, these data add additional support for the use of HSP60 protein abundance in buccal swabs as an indicator of processes involved in SCZ.

[0203] In view of the above-discussed data, these studies identified two novel, biomarker candidates for SCZ in buccal cells. Patients with SCZ have significantly higher levels otSP4 mRNA and HSP60 protein in buccal swabs than do control subjects. Importantly, higher SP4 expression positively correlates with reaction time on the AX-CPT, deficits in recognition discrimination, and symptom severity. Specifically, a relationship was observed between SP4 mRNA expression and the presence of positive and negative symptoms, excitement, thought disturbance, and paranoia / belligerence. Similarly, HSP60 protein abundance correlates with slowed responses on tests of working memory (AX-CPT), impairments of delayed recall and recognition memory, and increased severity of symptoms. However, the results from the JOVI task do not indicate a consistent relationship between STNmRNA expression or HSP60 protein abundance and contour integration. Taken together, these results provide a rationale 20

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[0205] for larger-scale studies of buccal cell SP4 mRNA and HSP60 protein in buccal swabs in SCZ, including studies of their specificity to diagnosis and / or alternative classification types (e.g, B / SNIP biotypes), cognitive impairment, functional impairment, and trait vs. state sensitivity (Clementz BA et al. Psychosis Biotypes: Replication and Validation from the B-SNIP Consortium. Schizophrenia Bulletin 2022; 48(1): 56-68).

[0206] The AX-CPT reaction time data suggest that SP4 mRNA expression correlates with cognitive slowing.

[0207] SP4 is a particularly compelling biomarker candidate for SCZ. In 2020, The Schizophrenia Working Group of the Psychiatric Genomics Consortium conducted the largest genome-wide association study (GWAS) to date, and the Schizophrenia Exome MetaAnalysis (SCHEMA) Consortium released the largest exome sequencing project to date (Ripke S et al. Mapping genomic loci prioritises genes and implicates synaptic biology in schizophrenia. Cold Spring Harbor Laboratory 2020; Singh T et al. Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia. Cold Spring Harbor Laboratory 2020; and Trubetskoy V et al. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature 2022; 604(7906): 502-508). Notably, only two genes, SP4 and GRIN2A, were identified as top ten risk genes by both the GWAS and the SCHEMA (Zhou X. Over-representation of potential SP4 target genes within schizophrenia-risk genes. Molecular Psychiatry 2022; 27(2): 849-854).

[0208] SP4 is a member of the specificity protein 1 (SP1) transcription factor family, and it binds to GC-boxes in the promoter region of target genes. (Id). Previous studies reported that a reduction in SP4 expression results in learning and memory deficits and other brain and behavior abnormalities associated with SCZ. ( ). Remarkably, there is an abundance of SCZ risk genes that contain a GC-box in their promoter region, suggesting that SP4 may act as an upstream regulator of several other SCZ risk genes. While most high-risk genes for SCZ are brain-specific, the fact that SP4 is also expressed in epithelial cells. Moreover, interleukin 6 (IL-6), a proinfl ammatory cytokine, and soluble interleukin-6 receptor (sIL-6R) signaling cascade can epigenetically activate SP4 expression in peritoneal tissue comprised of endothelial cells.

[0209] An altered abundance of proteins associated with mitochondrial and immune pathways were identified. Recently, reports have emerged demonstrating mitochondrial

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[0212] dysfunction and chronic immune activation in patients with SCZ. These results are consistent with evidence of dysfunction in multiple cell types and neural pathways in SCZ.

[0213] Mitochondrial dysfunction can lead to immune activation in the following manner; deficits in mitochondrial proteins lead to dysfunction of the electron transport chain and the production of oxidative and nitrosative stress responses. In turn, immune-inflammatory pathways are activated, resulting in chronic low-grade inflammation and neuroprogressive changes characteristic of SCZ.

[0214] HSP60 was also identified as a candidate buccal cell biomarker of SCZ. HSP60 is encoded by a SCZ risk gene, and it is a predicted target of SP4 as its proximal promoter contains two GC-boxes. Furthermore, since HSP60 bridges the gap between mitochondrial function and immune response, both of which have been well documented in SCZ pathology, there is support for HSP60 as a biomarker for SCZ. HSP60, a multifaceted chaperonin, plays an important role in maintaining proteostasis in the mitochondria, and its elevated abundance is indicative of mitochondrial stress.

[0215] Moreover, HSP60 can be secreted from cells, interact with immune cells via membrane-bound receptors, and travel through the bloodstream, and affect distant sites. HSP60 plays an important role in several inflammatory and autoimmune diseases of the nervous system, including multiple sclerosis and myasthenia gravis. It also contributes to the pathogenesis of several neurological diseases, such as hereditary spastic paraplegias, MitCHAP-60, Alzheimer’s Disease. Parkinson’s Disease, and Huntington’s Disease. Since HSP60 is ubiquitously expressed throughout the body, it is easy to collect and detect, as demonstrated in buccal cell extracts.

[0216] These studies are the first to identify biomarker candidates in buccal cells. Buccal cells were selected as tissue for peripheral biomarkers of SCZ for the following reasons. First, the CNS and buccal epithelium both develop from ectodermal tissue. The buccal epithelium is cellularly more homogenous than blood, making it a better source of material. Second, buccal epithelial cells contain a greater amount of disease-associated single-nucleotide polymorphism (SNPs) and larger interindividual epigenetic variation than blood cells. Third, and most importantly, buccal swabs are far less invasive than methods used to acquire other commonly collected tissues, such as blood or cerebrospinal fluid. Thus, cheek swabs are particularly appealing for the identification and exploration of biomarkers, and potentially, for clinical decision making. It should be noted that any of these methods may show variation as SCZ is a heterogeneous disease and it is not uncommon to identify changes in only a 22

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[0218] subset of samples in any ty pe of markers of SCZ. Indeed, in the tMS experiments, HSP60 varied in protein abundance between SCZ samples.

[0219] Together, the data described herein suggest that SP4 mRNA expression and its downstream target HSP60 protein are novel biomarkers of SCZ. These studies are the first to report buccal cell biomarkers that correlate with cognitive deficits observed in SCZ patients. These findings can provide insight into disease pathophysiology’ and aid in the development of novel therapeutics.

[0220] The foregoing examples and description of the preferred embodiments should be taken as illustrating, rather than as limiting the present disclosure as defined by the claims. As will be readily appreciated, numerous variations and combinations of the features set forth above can be utilized without departing from the present disclosure as set forth in the claims. Such variations are not regarded as a departure from the scope of the disclosure, and all such variations are intended to be included within the scope of the following claims. All references cited herein are incorporated by reference in their entireties.

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Claims

Docket No. 070439.01926CLAIMSWhat is claimed is:

1. A method of diagnosing schizophrenia in a subject in need thereof, comprising:a) collecting buccal cells from the subject;b) extracting DNA, mRNA, and protein from the buccal cells; andc) quantifying an amount of mRNA and protein of at least one biomarker of schizophrenia;wherein an increase in the mRNA or protein of the biomarker compared to a subject who does not have schizophrenia correlates with symptoms of schizophrenia.

2. The method of claim 1, wherein the biomarker is heat shock protein 60 (HSP60) protein or specificity protein 4 (SP4) mRNA.

3. The method of claim 1, wherein the symptoms of schizophrenia comprise reduced shortterm verbal memory, reduced response speed on a working memory task, depression, hallucinations, or anergia.

4. The method of claim 1, wherein step a) comprises swabbing the buccal cells from the subject’s mouth.

5. The method of claim 1, wherein real-time quantitative PCR (RT-qPCR) quantifies the amount of mRNA and mass spectrometry, ELISA, or Western blot analysis quantifies the amount of protein in step c).

6. The method of claim 1, wherein the symptoms of schizophrenia are measured by Positive and Negative Syndrome Scale (PANSS).

7. The method of claim 1, wherein the subject is a human.

8. The method of claim 1, wherein the subject has an increase in HSP60 protein and / or SP4 mRNA.

9. A method of treating schizophrenia in a subject in need thereof, comprising administering to the subject a therapeutic agent, wherein the subject has increased mRNA or protein levels of at least one biomarker of schizophrenia.

10. The method of claim 9, wherein the at least one biomarker is HSP60 protein or SP4 mRNA.

11. The method of claim 9, wherein the subject exhibits symptoms of schizophrenia measured by PANSS.24180404115.1Docket No. 070439.0192612. The method of claim 9, wherein the subject is a human.

13. The method of claim 9, wherein the therapeutic agent is an antipsychotic agent.

14. The method of claim 13, wherein the antipsychotic agent comprises haloperidol, aripiprazole, olanzapine, quetiapine, xanomeline, or trospium chloride.25180404115.1

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