Title: Neurochemical Correlates and Heterogeneous Clinical Response to Olanzapine in Schizophrenia: A Multidimensional Analysis of Central and Peripheral Biomarkers

Brief title: Biomarker-Based Stratification of Olanzapine Response in Schizophrenia

WirginiaKrzyściak1,7✉Emailwirginia.krzysciak@uj.edu.pl

MaciejPilecki2

BeataBystrowska3

MartaSzwajca2

NataliaŚmierciak2

AleksanderTurek2

PaulinaKarcz4

AmiraBryll5

PaulinaMazur1

EwaGomółka6

TadeuszPopiela5

1Department of Medical DiagnosticJagiellonian University Medical College30-688KrakowPoland

2Department of Child and Adolescent PsychiatryJagiellonian University Medical College31-501KrakowPoland

3Department of ToxicologyJagiellonian University Medical College30-688KrakowPoland

4Department of ElectroradiologyJagiellonian University Medical College31-126KrakowPoland

5Department of RadiologyJagiellonian University Medical College31-501KrakowPoland

6Toxicological Information Center, Department of Clinical Toxicology and Environmental DiseasesJagiellonian University Medical College31-503KrakowPoland

7Department of Medical DiagnosticJagiellonian University Medical College30-688KrakówPoland

Authors: Wirginia Krzyściak^1*, Maciej Pilecki², Beata Bystrowska³, Marta Szwajca², Natalia Śmierciak², Aleksander Turek², Paulina Karcz⁴, Amira Bryll⁵, Paulina Mazur¹, Ewa Gomółka⁶, Tadeusz Popiela⁵

¹ Department of Medical Diagnostic, Jagiellonian University Medical College, 30–688 Krakow, Poland

² Department of Child and Adolescent Psychiatry, Jagiellonian University Medical College, 31–501 Krakow, Poland

³Department of Toxicology, Jagiellonian University Medical College, 30–688 Krakow, Poland

⁴Department of Electroradiology, Jagiellonian University Medical College, 31–126 Krakow, Poland

⁵Department of Radiology, Jagiellonian University Medical College, 31–501 Krakow Poland

⁶Toxicological Information Center, Department of Clinical Toxicology and Environmental Diseases, Jagiellonian University Medical College, 31–503 Krakow, Poland

Corresponding author:

Wirginia Krzyściak

Department of Medical Diagnostic

Jagiellonian University Medical College

30–688 Kraków, Poland

E-mail: wirginia.krzysciak@uj.edu.pl

Abstract

This study aimed to identify neurochemical and clinical phenotypes among olanzapine-treated schizophrenia patients to inform biomarker-guided personalized therapy. We conducted a cross-sectional observational study of 51 adults with schizophrenia receiving chronic olanzapine treatment (mean duration = 5.6 years), integrating clinical assessments with peripheral neurochemical profiling and magnetic resonance spectroscopy (MRS) of the anterior and posterior cingulate cortices. Partial correlations controlling for age, sex, and treatment duration revealed significant associations: higher serum serotonin correlated with more severe negative symptoms (ρ = 0.32, p = 0.029), and increased cingulate Glx ratios were linked to greater depressive burden (ρ = 0.31, p = 0.031). Elevated serum glutamic acid was associated with overall psychopathology, whereas lower serum and cingulate glutamine levels were related to more severe symptoms and higher olanzapine exposure. Hierarchical clustering on principal components (HCPC) identified three phenotypic subgroups: (1) low-symptom, dose-efficient responders; (2) high-symptom, dose-resistant patients with cingulate hypoglutamatergia; and (3) younger individuals with elevated Glx ratios and moderate exposure, suggestive of a hyperglutamatergic, neurodevelopmental profile. These findings highlight the heterogeneity of olanzapine response in schizophrenia, shaped by neurochemical and demographic factors. Stratification based on glutamatergic markers and symptom profiles may advance precision psychiatry. This is the first study to integrate central and peripheral biomarkers with multivariate phenotyping in a naturalistic olanzapine-treated cohort.

Key words:

Schizophrenia

Olanzapine

Neurochemical biomarkers

Magnetic resonance spectroscopy

Personalized psychiatry

Multivariate analysis

Word count

3944

1. Introduction

Cognitive and affective dysfunctions are core features of schizophrenia and are often resistant to standard pharmacological interventions, particularly in chronic populations [1]. While second-generation antipsychotics (SGAs) such as olanzapine are widely used due to their favorable side-effect profiles compared to first-generation antipsychotics (FGAs) [2], their efficacy in addressing the broader neuropsychiatric burden—including negative symptoms, depressive comorbidity, and cognitive impairment—remains only partially understood [3–5]. Evidence from adult populations suggests that SGAs may modulate certain cognitive and affective domains, potentially through serotonergic and glutamatergic pathways, yet these effects are often subtle, heterogeneous, and difficult to generalize across patient subgroups [6–9].

Recent research has underscored the need for biomarker-guided personalization of antipsychotic therapy, especially in treatment-resistant or partially responsive cases [10]. Central neurochemical dysregulations, particularly within glutamatergic circuits of the anterior and posterior cingulate cortices, have been implicated in the persistence of negative and affective symptoms, while peripheral markers such as serum serotonin and glutamate-related metabolites may reflect systemic neurochemical imbalances associated with illness severity and pharmacodynamic variability [11–13]. However, the degree to which these central and peripheral neurochemical profiles co-vary with clinical outcomes during long-term olanzapine treatment remains insufficiently characterized.

The current study aims to elucidate the neurochemical underpinnings of clinical heterogeneity in a well-characterized cohort of schizophrenia patients undergoing chronic olanzapine therapy. Specifically, we investigate (1) the demographic, clinical, and neurochemical characteristics of the cohort; (2) partial correlations between peripheral and central neurochemical markers and symptom domains; and (3) data-driven phenotyping using hierarchical clustering of multimodal biomarkers. This multidimensional approach seeks to identify distinct neurobiological response profiles to olanzapine, with implications for treatment stratification and precision psychiatry in schizophrenia.

2. Results

2.1. Characteristics of the studied cohort

The baseline characteristics of a cohort of 51 patients with schizophrenia receiving olanzapine treatment were analyzed to elucidate demographic, clinical, and neurochemical profiles that may inform personalized therapeutic strategies. As summarized in Table 1, the cohort exhibited a balanced sex distribution, with 56.9% male (n = 29) and 43.1% female (n = 22), and a mean age of 27.7 years (SD = 9.4). Olanzapine serum concentrations displayed a median of 4.35 µg/L (interquartile range: 4.22–14.77 µg/L), with maximum values reaching 365 µg/L, indicating significant variability in drug exposure. The mean duration of olanzapine treatment was 5.6 years (SD = 5.9), reflecting a chronic treatment population.

Table 1
Summary of demographic, clinical, and neurochemical characteristics in olanzapine-treated patients.
Clinical outcome	Biomarker candidate	Partial correlation	p	95% CI Lower	95% CI Upper
PANSS Negative Symptoms Score	Serotonin	0.25	0.086	-0.03	0.49
PANSS Negative Subscale Items N1-N7 Sum	Serotonin	0.32	0.029	0.04	0.54
PANSS Negative Subscale Items N1-N7 Sum	Glutamine	-0.27	0.066	-0.51	0.01
PANSS Negative Subscale Items N1-N7 Sum	Glutamate ACC	-0.26	0.075	-0.50	0.02
PANSS Total Score	Serotonin	0.26	0.070	-0.01	0.50
PANSS Total Score	Glutamic Acid	0.29	0.049	0.01	0.52
PANSS Total Score	Glutamine	-0.29	0.045	-0.52	-0.02
BDI-II Total Score	Glutamate ACC	0.28	0.053	-0.01	0.52
BDI-II Total Score	Glx ACC	0.31	0.031	0.04	0.54
Proportion of Patients with Serum Olanzapine Concentration > 4.35 µg/L	Serotonin	0.26	0.079	-0.02	0.50
Proportion of Patients with Serum Olanzapine Concentration > 4.35 µg/L	Glutamine ACC	-0.30	0.037	-0.53	-0.03

Clinical symptom severity, assessed via the Positive and Negative Syndrome Scale (PANSS), Calgary Depression Scale for Schizophrenia (CDSS), and the Beck Depression Inventory-II (BDI-II), revealed substantial heterogeneity. The mean PANSS negative symptoms score was 21.2 (SD = 6.6, range: 2.0–33.0), with a similar negative subscale sum (mean = 21.4, SD = 6.6, range: 8.0–34.0), indicating moderate to severe negative symptomatology. The total PANSS score averaged 79.9 (SD = 20.9, range: 37.0–126.0), reflecting a broad spectrum of overall psychopathology. Depressive symptoms were moderate, with mean CDSS and BDI-II scores of 8.5 (SD = 6.2, range: 0.0–22.0) and 18.7 (SD = 13.5, range: 0.0–51.0), respectively, revealing variable affective burden.

Peripheral neurochemical markers further highlighted cohort diversity. Mean serum serotonin concentration was 130.1 ng/mL (SD = 21.7, range: 4.0–176.5), while glutamic acid and glutamine concentrations averaged 2,711.4 µg/mL (SD = 1,733.9, range: 537.9–8,871.9) and 342.6 µg/mL (SD = 66.6, range: 87.6–476.8), respectively, indicating significant variability in excitatory neurotransmitter levels. Magnetic Resonance Spectroscopy (MRS) ratios in the anterior cingulate cortex (ACC) and posterior cingulate cortex (PCC) at echo time (TE) = 30 ms provided insights into central neurochemical profiles. In the ACC, mean ratios included glutamine/(Cr + PCr) at 0.6 (SD = 0.1, range: 0.3–1.0), glutamate/(Cr + PCr) at 1.6 (SD = 0.2, range: 1.2–2.4), myo-inositol/(Cr + PCr) at 0.9 (SD = 0.1, range: 0.7–1.1), and composite glutamate + glutamine (Glx)/(Cr + PCr) at 2.2 (SD = 0.3, range: 1.8–3.0). Similar patterns were observed in the PCC, with glutamine/(Cr + PCr) at 0.6 (SD = 0.1, range: 0.4–1.0), glutamate/(Cr + PCr) at 1.6 (SD = 0.2, range: 1.1–1.8), myo-inositol/(Cr + PCr) at 0.9 (SD = 0.1, range: 0.7–1.1), and glutamate + glutamine (Glx)/(Cr + PCr) at 2.2 (SD = 0.2, range: 1.8–2.7). These findings indicate relatively stable central neurochemical ratios despite wide peripheral variability.

2.2. Partial correlation analysis of clinical and neurochemical associations in olanzapine-treated schizophrenia

The partial correlation analysis, conducted to elucidate potential associations between clinical outcomes and neurochemical biomarkers in a cohort of 51 patients with schizophrenia treated with olanzapine, revealed several significant and near-significant relationships, as detailed in Table 2.

Among the findings, a significant positive correlation was observed between the PANSS Negative Subscale Items N1-N7 Sum and serum serotonin concentration (partial correlation = 0.32, p = 0.029), with a 95% CI ranging from 0.04 to 0.54. This indicates that higher serotonin levels are associated with increased severity of negative symptoms, a finding that aligns with the potential role of serotonergic dysregulation in treatment response. Similarly, the BDI-II Total Score exhibited a significant positive correlation with Glx ratio in the ACC (partial correlation = 0.31, p = 0.031, 95% CI: 0.04 to 0.54), indicating that elevated ACC Glx levels may be linked to greater depressive symptom burden, consistent with glutamatergic hyperactivity in mood dysregulation.

The PANSS Total Score were positively correlated with serum glutamic acid (partial r = 0.29, p = 0.049, 95% CI: 0.01–0.52) and negatively correlated with serum glutamine (partial r = − 0.29, p = 0.045, 95% CI: − 0.52 to − 0.02). These findings suggest that higher glutamic acid levels may worsen psychopathology, while lower glutamine levels may indicate impaired glutamate–glutamine cycling, both potentially affecting olanzapine’s efficacy. Moreover, higher serum olanzapine levels correlated negatively with the ACC glutamine / (Cr + PCr) ratio (partial r = − 0.30, p = 0.037, 95% CI: − 0.53 to − 0.03), implying a dose-dependent reduction in ACC glutamine.

Near-significant associations included a positive trend between PANSS Negative Symptoms Score and serotonin (partial correlation = 0.25, p = 0.086, 95% CI: -0.03 to 0.49), PANSS Negative Subscale Items N1-N7 Sum with glutamine (partial correlation = -0.27, p = 0.066, 95% CI: -0.51 to 0.01) and glutamate in ACC (partial correlation = -0.26, p = 0.075, 95% CI: -0.50 to 0.02), PANSS Total Score with serotonin (partial correlation = 0.26, p = 0.070, 95% CI: -0.01 to 0.50), BDI-II Total Score with glutamate in ACC (partial correlation = 0.28, p = 0.053, 95% CI: -0.01 to 0.52), and the proportion of patients with elevated olanzapine concentration with serotonin (partial correlation = 0.26, p = 0.079, 95% CI: -0.02 to 0.50).

2.3. Cluster-based phenotyping of olanzapine response profiles in schizophrenia

The conducted hierarchical clustering on principal components (HCPC) procedure yielded three clusters: Cluster 1 (n = 11, 21.6% of the cohort), Cluster 2 (n = 22, 43.1%), and Cluster 3 (n = 18, 35.3%). These clusters were characterized by differential patterns across clinical, demographic, and neurochemical domains, revealing heterogeneous responses to olanzapine that may inform biomarker-guided personalization of antipsychotic therapy (see Fig. 1).

Fig. 1

Hierarchical clustering dendrogram (Panel A) and principal component analysis of the first two dimensions (Panel B) depicting patient phenotypes in olanzapine-treated schizophrenia.

As shown in Supplementary Table S1, PANSS negative symptoms and total scores exhibited the strongest associations (η² >0.53, p < 0.001), followed by composite MRS Glx ratios in the PCC and ACC (η² = 0.41–0.50, p < 0.001). Weaker but significant associations were observed for individual MRS glutamate and glutamine ratios, age, CDSS depression scores, and the binary olanzapine exposure indicator (η² = 0.12–0.34, p < 0.05). These findings underscore the multidimensional nature of olanzapine response profiles, with clinical symptom severity and cingulate Glx dysregulation emerging as primary discriminants.

Cluster-specific profiles are presented in Supplementary Tables S2–S4, summarizing metrics for Clusters 1–3 to support interpretation of phenotype–clinical associations. The clusters delineate heterogeneous patient profiles and highlight distinct links between serum olanzapine levels (above vs. below the median of 4.35 µg/L) and key clinical, demographic, and neurochemical variables. These patterns suggest differing pharmacodynamic efficiencies and potential mechanisms underlying variability in olanzapine response, informing dose optimization in schizophrenia treatment.

2.3.1. Cluster 1: Low-symptom, dose-efficient responders (n = 11)

This subgroup exemplifies therapeutic efficiency at submedian olanzapine exposure, with only 18% of patients surpassing the 4.35 µg/L threshold (versus 51% overall, v-test = -2.43, p = 0.007), correlating strongly with attenuated clinical symptomatology. Notably, PANSS negative symptoms (mean 11.91 versus overall 21.22, v-test = -5.26, p < 0.001) and total scores (50.91 versus 79.88, v-test = -5.19, p < 0.001) are markedly reduced, alongside diminished depressive indices (CDSS: 3.55 versus 8.54, v-test = -3.01, p = 0.001; BDI-II: 10.09 versus 18.74, v-test = -2.39, p = 0.008). Demographically, these patients skew older (mean age 33.18 years versus 27.71, v-test = 2.19, p = 0.014) and female-predominant (27% male versus 57% overall, v-test = -2.22, p = 0.013), patterns that may enhance olanzapine's affinity for D2 receptors or mitigate catabolic metabolism via CYP enzymes. Parameters such as peripheral neurochemical concentrations (e.g., serotonin, glutamic acid, glutamine) and individual MRS ratios not listed with significant deviations did not differ from cohort means, indicating that the phenotype's distinctiveness arises primarily from clinical remission and demographic factors rather than peripheral or neurochemical perturbations.

2.3.2. Cluster 2: High-symptom, dose-resistant profile with hypoglutamatergic dysregulation (n = 22)

Representing the modal phenotype, Cluster 2 reveals a paradoxical association wherein supra-median olanzapine exposure predominates (68% above 4.35 µg/L versus 51% overall, v-test = 2.12, p = 0.017), yet fails to ameliorate severe psychopathology, highlighting potential pharmacoresistance. Elevated PANSS negative symptoms (24.73 versus 21.22, v-test = 3.30, p < 0.001) and total scores (91.45 versus 79.88, v-test = 3.45, p < 0.001), coupled with heightened depression (CDSS: 11.30 versus 8.54, v-test = 2.76, p = 0.003), coexist with male predominance (77% versus 57% overall, v-test = 2.54, p = 0.006) – a demographic factor linked to slower olanzapine clearance and amplified negative symptom burden. Critically, this high-exposure subgroup exhibits cingulate hypoglutamatergia, with reduced composite Glx ratios (ACC: 2.07 versus 2.21, v-test = -3.33, p < 0.001; PCC: 2.07 versus 2.20, v-test = -4.13, p < 0.001) and constituent deficits in glutamate (ACC: 1.53 versus 1.62, v-test = -3.02, p = 0.001; PCC: 1.49 versus 1.56, v-test = -2.70, p = 0.003) and glutamine (p ≤ 0.001). Parameters including duration of olanzapine treatment, serotonin serum levels, and other unlisted neurochemical markers showed no significant deviations from cohort means, emphasizing that the resistance profile is driven by central glutamatergic alterations and symptom persistence rather than treatment duration or peripheral factors. Such neurochemical attenuation, potentially exacerbated by chronic olanzapine blockade of NMDA-glutamate interactions, may perpetuate negative and affective symptoms despite adequate dosing, aligning with eta-squared values indicating moderate cluster discrimination by Glx metrics (η² = 0.41–0.50).

2.3.3. Cluster 3: Youthful hyperglutamatergic subgroup with neutral dose dynamics (n = 18)

In contrast to the dose-extremes of other clusters, Cluster 3 demonstrates neutral olanzapine exposure, with no significant deviation from the cohort mean proportion exceeding 4.35 µg/L (η² = 0.14 overall, p = 0.024, but non-discriminative within this cluster), yet is defined by pronounced cingulate glutamatergic hyperactivity that may modulate early olanzapine responsiveness. Elevated Glx ratios prevail (ACC: 2.44 versus 2.21, v-test = 4.49, p < 0.001; PCC: 2.37 versus 2.20, v-test = 4.79, p < 0.001), propelled by glutamate surges (ACC: 1.78 versus 1.62, v-test = 4.11, p < 0.001; PCC: 1.64 versus 1.56, v-test = 2.86, p = 0.002) and glutamine elevations (ACC: 0.66 versus 0.59, v-test = 2.75, p = 0.003; PCC: 0.74 versus 0.64, v-test = 3.78, p < 0.001), in the context of younger age (21.17 years versus 27.71, v-test = -3.69, p < 0.001). Notably, clinical symptom scores (e.g., PANSS, CDSS, BDI-II), treatment duration, and peripheral neurochemical concentrations not reported with significant p-values did not differ from cohort means, indicating that this phenotype reflects a neurodevelopmental glutamatergic imbalance independent of overt psychopathology or dosing variations at the cohort median. Absent overt symptom exacerbation, this hyperglutamatergic state – potentially unmitigated by standard olanzapine doses due to immature receptor downregulation – reveals a developmental window where excitatory overflow in frontocingulate networks precedes full syndromal expression, with olanzapine concentrations at median levels insufficient to normalize glutamate efflux.

3. Discussion

Partial correlation analysis of clinical and neurochemical associations in olanzapine-treated schizophrenia

The significant positive correlation between serum serotonin levels and the severity of negative symptoms (PANSS N1–N7) in olanzapine-treated patients suggests that higher peripheral serotonin is associated with more pronounced negative symptoms. This counterintuitive finding may reflect impaired central serotonin processing, such that reduced serotonin transporter (SERT) availability or altered monoamine oxidase A (MAO-A) expression leads to elevated peripheral serotonin without effective central neurotransmission [14].

Olanzapine, known for its high affinity antagonism at 5-HT₂A and 5-HT₆ receptors, may further modulate serotonergic tone. Positron Emission Tomography (PET) studies have demonstrated that even low doses of olanzapine (e.g., 5 mg/day) achieve substantial 5-HT₂A receptor occupancy in vivo [15], which could interfere with serotonin-mediated cortical excitation. Moreover, olanzapine has been shown to enhance extracellular serotonin levels when co-administered with selective serotonin reuptake inhibitors (SSRIs) such as fluoxetine or citalopram, possibly via disinhibition of serotonergic neurons through 5-HT₆ receptor antagonism in the dorsal raphe nucleus [16]. These interactions underscore the complexity of serotonergic modulation under antipsychotic treatment and may explain why higher peripheral serotonin is paradoxically associated with negative symptom severity - an effect potentially driven by central serotonergic dysregulation rather than hyperfunction.

Similarly, the positive correlation between depressive symptom severity (BDI-II total score) and Glx levels in the anterior cingulate cortex (ACC) supports a growing body of evidence linking glutamatergic hyperactivity with affective symptoms in schizophrenia. Elevated Glx - representing the combined signal of glutamate and glutamine in Proton magnetic resonance spectroscopy (¹H-MRS) - has been consistently reported in patients with major depressive disorder, particularly in treatment-resistant subgroups [17]. The increased Glx levels observed in the present study may reflect either excessive synaptic glutamate or a compensatory increase in glutamine synthesis by astrocytes, aimed at buffering excitotoxicity [18]. Persistent elevations of both glutamate and glutamine may indicate disruption in the glutamate–glutamine cycle or prolonged activation of the hypothalamic–pituitary–adrenal (HPA) axis, both of which have been implicated in the pathophysiology of mood dysregulation.

Collectively, the associations of increased peripheral serotonin with negative symptoms and elevated central Glx with depressive symptoms suggest a shared disruption of monoaminergic and glutamatergic pathways in schizophrenia, particularly under chronic olanzapine treatment. These findings emphasize the relevance of biomarker-informed phenotyping, and support further research into neurochemical stratification of patients to optimize treatment approaches.

Multicenter studies using proton magnetic resonance spectroscopy (¹H-MRS) have demonstrated that patients with schizophrenia - particularly in the early stages of the illness or during acute psychotic episodes - exhibit elevated glutamate levels in brain regions such as the anterior cingulate cortex (ACC) and the hippocampus [19].

An increased concentration of glutamate in serum may also reflect excessive glutamatergic activity in the brain, potentially leading to excitotoxicity, oxidative stress, and worsening of psychopathological symptoms. The observed positive correlation between serum glutamate levels and the PANSS total score suggests that glutamate excess may contribute to the severity of both positive and negative symptoms.

In our previous studies, we observed that patients with acute psychotic decompensation showed reduced glutamate and glutamine levels in the anterior cingulate cortex, likely reflecting a downstream consequence of earlier excitotoxic and oxidative processes. These neurochemical alterations, correlated with markers of oxidative stress and mitochondrial dysfunction, supported a model of progressive glutamatergic imbalance in schizophrenia. The current finding of elevated serum glutamate and its association with PANSS total score extends this pattern, suggesting that peripheral glutamate excess may mirror central glutamatergic dysregulation contributing to symptom severity [20].

Consistent with this interpretation, glutamine plays a buffering role in the glutamate–glutamine cycle, mediating glutamate transport and recycling between neurons and astrocytes. Reduced serum glutamine levels may therefore reflect impaired astrocytic glutamine synthetase activity, leading to disrupted glutamate clearance, enhanced excitatory transmission, and worsening of clinical symptoms [21].

Olanzapine-Induced Glutamatergic Modulation and Clinical Response Clusters in Schizophrenia

The critical involvement of glutamatergic pathways in the pathophysiology of schizophrenia, as well as their potential role in mediating the therapeutic effects of antipsychotic treatment, has been increasingly recognized. Although olanzapine primarily acts as an antagonist of dopaminergic and serotonergic receptors, it also exerts modulatory effects on the glutamatergic system. Preclinical studies suggest that olanzapine can alter glutamate and glutamine concentrations in the brain [22].

Therefore, the observed correlations may reflect not only underlying pathophysiological mechanisms in schizophrenia but also potential biomarkers of treatment response to olanzapine, which has important implications for precision psychiatry. The findings of a positive correlation between serum glutamate and PANSS total score, alongside a negative correlation with serum glutamine, align with current scientific understanding.

Cluster 1: Low-symptom, dose-efficient responders (n = 11)

This cluster comprised predominantly older female patients who achieved clinical remission at submedian olanzapine exposure. The inverse relationship between low drug levels and symptom remission suggests a “dose-sparing” phenotype, in which peripheral monitoring could support individualized dose reduction to minimize metabolic and sedative side effects without compromising efficacy. Similar findings by Zabala et al. (2017) also described patients maintaining stability at low olanzapine concentrations, reinforcing this low-exposure efficacy profile [23]. In contrast, Hiemke et al. (2018) emphasized that concentrations below approximately 20 ng/mL are generally associated with diminished therapeutic response, underscoring the importance of individualized interpretation of therapeutic reference ranges [24].

This phenotype is further supported by several case reports and large-scale studies highlighting the potential for clinical efficacy at subtherapeutic or low-dose olanzapine exposure, particularly in older adults and women. Kurozumi et al. described a case of a 70-year-old woman with very-late-onset schizophrenia-like psychosis (VLOSLP), who achieved sustained remission for over two years on only 2.5 mg/day of olanzapine, despite an initial relapse following treatment discontinuation [25]. The authors emphasized that age-related pharmacokinetic changes, such as reduced clearance and slower metabolism, may result in higher drug exposure at lower doses in elderly patients, especially females.

Real-world data from Kang et al. (2025), analyzing 9,565 olanzapine-treated patients, showed that 17% received doses ≤ 1.25 mg/day, which were associated with a significantly lower risk of metabolic side effects (e.g., diabetes, dyslipidemia) without compromising clinical efficacy in older patients, predominantly women [26]. These findings support the emerging need for personalized, low-dose strategies and the availability of lower-dose formulations.

Similarly, Graff-Guerrero et al. (2015), using PET imaging, demonstrated that gradual dose reduction in stable patients aged ≥ 50 years lowered D2/3 receptor occupancy to approximately 64%, improving tolerability (e.g., EPS, hyperprolactinemia) without loss of clinical stability [27]. The authors proposed a lower therapeutic window (50–60%) for D2/3 occupancy in late-life schizophrenia (LLS), reinforcing the rationale for individualized dose optimization.

Pharmacokinetic studies also confirm these trends. Solhaug et al. (2025), in a TDM analysis of 19,926 patients, reported a significant age-related increase in the olanzapine concentration-to-dose (C:D) ratio, most pronounced in elderly women [28]. Castberg et al. (2017), analyzing over 43,000 TDM samples, showed an exponential rise in C:D with age, with women over 80 reaching plasma levels two to three times higher than younger adults at equivalent doses. Women also exhibited 25–30% higher concentrations than men at the same dose, highlighting increased sensitivity in this group [29].

Taken together, these findings strengthen the concept of a "low-exposure efficacy phenotype" and suggest that therapeutic targets for older adults, especially women, may be achieved at substantially lower doses. This underscores the clinical utility of TDM and age- and sex-informed dosing strategies to optimize efficacy while minimizing adverse effects.

This phenotype further underscores olanzapine’s ability to promote neuroplasticity at lower plasma thresholds, potentially through enhanced 5-HT₂A receptor antagonism. It supports the need for prospective studies to validate submedian concentrations as reliable predictors of sustained remission. In clinical practice, identifying such low-exposure responders through baseline PANSS assessments combined with therapeutic drug monitoring (TDM) could enable early dose de-escalation. This approach not only fosters long-term adherence by minimizing adverse effects but also reduces the clinical and economic burdens associated with polypharmacy, particularly in vulnerable populations such as elderly women.

Cluster 2: High-symptom, dose-resistant profile with hypoglutamatergic dysregulation (n = 22)

Cluster 2 comprised high-symptom, dose-resistant individuals with cingulate hypoglutamatergia despite high olanzapine levels, indicating potential pharmacoresistance and the need for adjunctive glutamatergic modulation or alternative treatment strategies. This pattern is consistent with the conceptual framework proposed by Kantrowitz and Javitt (2010), who highlighted NMDA receptor hypofunction as a potential final common pathway underlying persistent symptoms and treatment resistance in schizophrenia [30]. The current profile advocates for therapeutic drug monitoring to confirm supra-median levels (e.g., targeting 20–40 µg/L troughs) before adjunctive interventions, such as glutamatergic modulators (e.g., sarcosine) or switches to clozapine, thereby addressing resistance rooted in olanzapine-glutamate decoupling and improving functional outcomes. Routine integration of MRS assessments in this subgroup could refine risk stratification, enabling proactive management to mitigate chronic disability and enhance psychosocial rehabilitation.

Cluster 3: Youthful hyperglutamatergic subgroup with neutral dose dynamics (n = 18)

Cluster 3 included younger patients with hyperglutamatergic profiles and neutral olanzapine exposure, possibly reflecting a neurodevelopmental imbalance preceding full symptom manifestation. The modest overall η² for olanzapine (0.14) implies indirect modulation, perhaps via dose-dependent GABA-glutamate balance, warranting escalation in youth to harness olanzapine's potential effects on metabotropic glutamate receptors. Consistent with this notion, Marsman et al. (2013) demonstrated that antipsychotic treatment can normalize cortical Glx concentrations, supporting an indirect glutamatergic modulation underlying clinical improvement [31]. Similarly, Egerton et al. (2012) emphasized that changes in glutamatergic tone may reflect downstream effects of dopamine–serotonin receptor interactions, aligning with olanzapine’s receptor profile and its putative impact on neuroplasticity [32]. As a biomarker ensemble, these Glx elevations, decoupled from dose extremes and clinical severity, signal prodromal risk amenable to preventive dosing, integrating MRS surveillance with pharmacokinetic assays to tailor interventions and forestall progression in adolescent cohorts. In this context, Berk et al. (2008) provided evidence that adjunctive N-acetylcysteine may enhance glutamatergic homeostasis and improve functional outcomes, highlighting the translational potential of early metabolic modulation strategies [33]. This neutral dose profile further highlights the need for age-specific TDM thresholds, potentially incorporating serial MRS to track glutamatergic normalization and guide adjunctive therapies like N-acetylcysteine for early stabilization.

Summary

This study underscores the urgent need to bridge the gap between laboratory research and clinical practice in schizophrenia treatment. Current psychiatric care often relies on observable symptoms and standardized clinical scales, yet growing evidence shows that such approaches may overlook key biological underpinnings of treatment response. Our findings reveal distinct neurochemical profiles among patients treated with olanzapine, highlighting that similar drug exposure can result in widely divergent clinical outcomes. Particularly striking is the observation that some individuals, especially younger patients, exhibit significant alterations in brain glutamatergic activity without corresponding changes in symptom severity — suggesting that traditional symptom-based monitoring may miss early neurobiological signs of treatment failure or progression.

While therapeutic drug monitoring (TDM) for antipsychotics remains largely absent from routine psychiatric practice, several countries — including Germany, Switzerland, and Austria — have already implemented TDM as part of clinical decision-making in psychiatry, acknowledging its value in optimizing efficacy and minimizing side effects. However, even in these systems, TDM typically focuses on serum drug levels without considering parallel changes occurring in the brain.

This research highlights the necessity of expanding psychiatric monitoring beyond the bloodstream. Neuroimaging tools, such as magnetic resonance spectroscopy (MRS), offer a window into real-time neurochemical dynamics, providing insight into mechanisms that influence both drug response and resistance. Integrating central biomarkers with clinical observation and peripheral measures could transform treatment strategies — particularly for patients under 40, where early neurochemical dysregulation may shape long-term outcomes.

The message is clear: psychiatry must move toward precision medicine. By combining clinical, peripheral, and neuroimaging data, clinicians can better tailor interventions, avoid ineffective treatments, and identify at-risk patients before symptoms escalate. Translating these findings into practice is not merely an innovation — it is a clinical imperative.

4. Materials and Methods

4.1. Study Design and Objectives

This cross-sectional observational study was conducted in a naturalistic sample of adult patients with schizophrenia treated with olanzapine. The primary objective was to identify clinical and neurochemical profiles associated with treatment response by integrating symptom ratings, peripheral blood biomarkers, and brain metabolites measured via proton magnetic resonance spectroscopy (¹H-MRS). A secondary objective was to examine the relationship between serum olanzapine concentrations and clinical or neurochemical measures to inform personalized treatment strategies.

4.2. Participants

The study included 51 patients with schizophrenia diagnosed according to ICD-10 criteria (F20), confirmed by a structured clinical interview conducted by a trained psychiatrist. Participants were consecutively recruited from inpatient and outpatient psychiatric services to ensure a clinically representative cohort. Inclusion criteria were: (1) treatment with olanzapine monotherapy for ≥ 6 months, (2) maintenance of a stable dose for ≥ 4 weeks prior to enrollment, and (3) capacity to provide informed consent. Exclusion criteria included: (1) comorbid neurological or major medical illness, (2) substance use disorder within the past 6 months (excluding nicotine), and (3) contraindications to magnetic resonance imaging (MRI).

All participants provided written informed consent.

The study protocol was approved by the local ethics committee (reference number 1072.6120.87.2024) and conducted in accordance with the Declaration of Helsinki.

4.3. Clinical Assessments

Psychopathology was assessed using the Positive and Negative Syndrome Scale (PANSS) [34], the Calgary Depression Scale for Schizophrenia (CDSS) [35], and the Beck Depression Inventory-II (BDI-II) [36]. The PANSS was administered to capture overall symptom severity, with the Negative Subscale (items N1–N7) summed to provide a focused index of negative symptoms. The CDSS was employed as a schizophrenia-specific measure of depression designed to minimize overlap with negative symptoms, whereas the BDI-II, a general self-report scale, was included to facilitate comparability with studies outside the schizophrenia field. All clinician-rated assessments (PANSS, CDSS) were conducted by a board-certified psychiatrist trained in the use of these instruments.

4.4. Peripheral Biomarker Measurements

Peripheral blood samples were collected between 8:00 and 10:00 a.m. after an overnight fast. Serum was separated by centrifugation and stored at − 80°C until analysis. Serum concentrations of serotonin, glutamic acid (glutamate), and glutamine were determined using validated chromatographic methods, as described in our previous papers [37, 38].

The Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS), a reference method known for its superior sensitivity, specificity, and minimal susceptibility to matrix effects [39]. To 100 µL of serum, 4 µL of a deuterated serotonin, glutamate and glutamine internal standard (serotonin-d4, 500 µg/mL in water, glutamate acid-13C5 and glutamine-13C5, both 500ug/ml in water) was added, followed by vortex mixing for 10 seconds. Samples were deproteinized by adding 100 µL of acetonitrile (1:1, v/v), mixed for 30 seconds, and centrifuged at 8,000 rpm for 10 minutes at 4°C. The resulting supernatant (100 µL) was transferred into chromatographic vials for analysis.

Chromatographic separation was performed using a Waters ACQUITY UPLC® H-Class system (Waters Corporation, Milford, MA, USA) with a ZIC®-HILIC column (5 µm, 200 Å, 150 × 2.1 mm; Merck, Darmstadt, Germany), maintained at 40°C. The mobile phases consisted of 0.1% formic acid in water (phase A) and 0.1% formic acid in acetonitrile (phase B), delivered at a flow rate of 0.6 mL/min under a gradient program. The injection volume was 4 µL, and the total run time was 6 minutes. The retention time for serotonin (and its internal standard) was 2.35 minutes.

Mass spectrometric detection was conducted on a Xevo TQ-S® triple quadrupole mass spectrometer (Waters Corporation, Milford, MA, USA) equipped with an electrospray ionization (ESI) source operating in positive ionization mode. Ion source parameters were as follows: ion spray voltage 5500 V, nebulizer gas at 30 psi, turbo gas at 20 psi, source temperature at 550°C, and curtain gas at 30 psi. Data were acquired in multiple reaction monitoring (MRM) mode, monitoring the transitions m/z 177.0 → 119.0 for serotonin and m/z 182.83 → 119.76 for serotonin-d4; m/z = 148/84 for Glut and 153/89 for Glut-13C5; m/z = 147/84 for GLN and 152/88 for GLN-13C5. Quantification was based on calibration curves constructed by linear regression analysis of peak area versus concentration.

Intra- and inter-assay coefficients of variation for serotonin, glutamate, and glutamine determinations were consistently below 10%.

4.5. Quantification of olanzapine in serum using LC–MS/MS

Serum olanzapine concentrations were quantified using a fully automated high-performance liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) system, designed to support high-throughput and high-precision therapeutic drug monitoring in a clinical laboratory setting. Serum samples were obtained by standard centrifugation at 4000 × g for 4 minutes at 4°C and stored at − 80°C until analysis.

Sample preparation followed the manufacturer’s instructions included with the commercial LC-MS/MS assay kit (MassTox®, Chromsystems). After equilibrating all reagents to room temperature and gentle mixing, 50 µL of each serum sample was pipetted into 1.5 mL reaction tubes. Next, 25 µL of extraction buffer was added; samples were vortexed briefly and allowed to stand for 2 minutes at room temperature. Subsequently, 250 µL of internal standard solution (containing isotopically labeled olanzapine) was added, and tubes were vortexed for 30 seconds. Samples were then centrifuged for 5 minutes at 15,000 × g. The resulting supernatant was diluted 1:4 using a 1:1 (v/v) mixture of two dilution buffers provided in the kit.

Chromatographic separation was performed on a reverse-phase MassTox® TDM MasterColumn Series A (REF 92110, LOT 2024, SN 259) under gradient elution conditions. The LC-MS/MS system included a cooled autosampler and a triple quadrupole mass spectrometer operating in positive electrospray ionization mode (ESI+). The injection volume was 8 µL, with a flow rate of 0.6 mL/min and a total run time of 3.2 minutes. Autosampler needle rinsing was performed after each injection using a dedicated rinsing solution. The column temperature was maintained between 20 and 25°C, and the system was stabilized for at least 10 minutes before analysis.

Multiple reaction monitoring (MRM) was used to detect olanzapine, with two transitions monitored: m/z 313 → 256 and m/z 313 → 213. The method was calibrated using certified reference standards, and validation against an external LC-MS/MS method (MassTox®) demonstrated excellent agreement across the therapeutic range (R² >0.98). Assay performance was monitored using quality control samples, with coefficients of variation consistently below 5%.

Analytical sensitivity was established during method optimization. The lower limit of detection (LOD) was calculated as 0.31 µg/L, and the lower limit of quantification (LLOQ) as 1.03 µg/L. The analytical bias was calculated as − 2.7%, indicating high accuracy across the measured range. Hemolyzed samples were excluded due to potential interference.

To facilitate stratified analysis, a binary exposure variable was created by dichotomizing olanzapine serum concentrations at the sample median (4.35 µg/L), distinguishing low- and high-exposure groups.

4.6. Magnetic Resonance Spectroscopy (MRS) Acquisition and Processing

Brain metabolite levels were acquired using a 3T MRI scanner (Siemens Prisma, Germany) with a 64-channel head coil. Single-voxel proton MRS (¹H-MRS) spectra were obtained from the anterior cingulate cortex (ACC) and posterior cingulate cortex (PCC) using the Point RESolved Spectroscopy (PRESS) sequence with TE = 30 ms, TR = 2000 ms, and 128 averages. Voxel sizes were 20×20×20 mm³. Metabolite quantification was performed using LCModel (version 6.3-1L) with water scaling, and metabolite concentrations were expressed as ratios to total creatine (Cr + PCr). Quantified ratios included: glutamine/(Cr + PCr), glutamate/(Cr + PCr), (glutamate + glutamine)/(Cr + PCr), and myo-inositol/(Cr + PCr). Only spectra with a full width at half maximum (FWHM) < 0.08 ppm and a signal-to-noise ratio (SNR) > 15 were included in the analysis; spectra not meeting these quality criteria were excluded from subsequent statistical analyses.

4.7. Statistical Analysis

4.7.1. Partial correlation analysis of clinical and neurochemical variables in olanzapine-treated schizophrenia

Partial correlation analysis was performed to examine the associations between clinical outcomes and biomarker candidates, controlling for confounding factors to isolate direct relationships relevant to olanzapine response. This approach was justified by the need to account for demographic and treatment-related influences that could bias the observed correlations, thereby providing a more accurate assessment of potential biomarkers for personalized therapeutic strategies in schizophrenia. Clinical outcomes were selected as variables directly reflective of symptom severity and treatment exposure, including the Positive and Negative Syndrome Scale (PANSS) Negative Symptoms Score, PANSS Negative Subscale Items N1-N7 Sum, PANSS Total Score, Calgary Depression Scale for Schizophrenia (CDSS) Total Score, Beck Depression Inventory-II (BDI-II) Total Score, and a binary indicator of serum olanzapine concentration exceeding the cohort median. These measures were chosen due to their established clinical relevance in evaluating negative, depressive, and overall psychotic symptoms, as well as drug exposure status, which are central to assessing olanzapine efficacy.

Biomarker candidates encompassed peripheral and central neurochemical markers potentially indicative of biological response mechanisms, including Serum Serotonin Concentration, Glutamic Acid Serum Concentration, Glutamine Serum Concentration, Glutamine / (Cr + PCr) Ratio (MRS, ACC, TE = 30 ms), Glutamate / (Cr + PCr) Ratio (MRS, ACC, TE = 30 ms), myo-Inositol / (Cr + PCr) Ratio (MRS, ACC, TE = 30 ms), (Glutamate + Glutamine) / (Cr + PCr) Ratio (MRS, ACC, TE = 30 ms), Glutamine / (Cr + PCr) Ratio (MRS, PCC, TE = 30 ms), Glutamate / (Cr + PCr) Ratio (MRS, PCC, TE = 30 ms), myo-Inositol / (Cr + PCr) Ratio (MRS, PCC, TE = 30 ms), and (Glutamate + Glutamine) / (Cr + PCr) Ratio (MRS, PCC, TE = 30 ms). These parameters were justified by their role in neurotransmitter systems modulated by olanzapine, such as serotonergic and glutamatergic pathways, and their potential to serve as objective indicators of treatment response.

Covariates were included to adjust for factors known to influence both clinical outcomes and neurochemical profiles, comprising age (years), sex (male), and duration of olanzapine treatment (years). Age and sex were selected as standard demographic confounders due to their established impact on symptom presentation and pharmacokinetics in schizophrenia. Treatment duration was incorporated to control for chronicity-related effects, such as cumulative drug exposure or disease progression, which could confound the associations.

The Spearman rank correlation method was employed overall to compute partial correlation coefficients, accounting for potential non-linear relationships in the data. This non-parametric approach was appropriate given the variability in clinical and neurochemical measures observed in the cohort. Partial correlations were calculated for each pair of a clinical outcome and a biomarker candidate, adjusting for the three covariates.

P-values were approximated using a t-distribution based on the partial correlation coefficient and degrees of freedom adjusted for the number of covariates and sample size, with a significance threshold of α = 0.05. The 95% confidence interval (CI) for the Spearman rank correlation coefficient (Rho) was estimated via Fisher's z-transformation, converting the correlation to a z-score, calculating the interval in z-space, and transforming back to the correlation scale, ensuring robust interval estimation for the non-parametric method [40, 41]. Due to the exploratory nature of the correlation analysis, all correlation p-values were reported without additional adjustment for multiple comparisons to facilitate the identification of potential associations for further investigation.

4.7.2. Hierarchical clustering on principal components for patient profiling in olanzapine treatment

To characterize distinct patient profiles among 51 individuals with schizophrenia treated with olanzapine, hierarchical clustering on principal components (HCPC) was employed. The analysis integrated a binary indicator of serum olanzapine concentration above the cohort median (4.35 µg/L) with demographic variables (age, sex), clinical symptom measures (Positive and Negative Syndrome Scale [PANSS] negative symptoms, CDSS, BDI-II), peripheral neurochemical markers (serum serotonin, glutamate, glutamine concentrations), and MRS ratios from ACC and PCC (glutamate/glutamine and myo-inositol ratios relative to creatine plus phosphocreatine, measured at TE = 30 ms).

Principal component analysis (PCA) was first conducted to reduce dimensionality and capture variance within this heterogeneous dataset. Subsequently, HCPC was applied to the PCA results using the HCPC function, with a maximum of four clusters to identify distinct patient subgroups [42]. This approach is well-suited for uncovering complex, multidimensional relationships in clinical and neurochemical data, enabling unsupervised identification of patient profiles associated with olanzapine exposure [43].

The overall link between the cluster assignment and each variable using analysis of variance (ANOVA). For each variable, the eta-squared (η²) statistic is reported, which quantifies the proportion of variance in the quantitative variable explained by the clusters, analogous to R² in regression models. The associated p-value is derived from the F-test in the ANOVA framework, indicating the statistical significance of the cluster effect on the variable, with a significance threshold set at α = 0.05. Variables are ranked by descending η² to highlight those most discriminative across clusters.

Subsequently, each cluster is described by comparing its mean on each quantitative variable to the overall sample mean. This involves a standardized test statistic (v.test), calculated as Eq. (1):

$\:v=\:\frac{{Mean}_{cluster}-\:{Mean}_{overall}}{\sqrt{\frac{{SD}_{cluster}^{2}}{{n}_{cluster}}+\frac{{SD}_{overall}^{2}}{{n}_{overall}}\:}}$

where

$\:{n}_{cluster}$

and

$\:{n}_{overall}\:$

iare the sample sizes of the cluster and cohort, respectively. Under the assumption of normality, the v.test follows a standard normal distribution, enabling the computation of a one-sided p-value (P(Z > v.test), where Z ~ N(0,1)) to assess whether the cluster mean deviates significantly from the overall mean (positive v.test indicates higher-than-average values; negative indicates lower). For each variable in each cluster, the following metrics are reported: v.test, mean in the cluster, overall mean, standard deviation (SD) in the cluster, overall SD, and the corresponding p-value. Only variables with significant deviations (p < 0.05) are highlighted for interpretation.

4.7.3. Characteristics of the statistical tool

Analyses were conducted using the R Statistical language (version 4.3.3)[44] on Windows 11x64 (build 26100), using the packages rio (version 1.2.1)[45] factoextra (version 1.0.7) [46], ppcor (version 1.1) [47], FactoMineR (version 2.11) [48], report (version 0.5.8) [49], patchwork (version 1.2.0) [50], gtsummary (version 2.2.0) [51], MASS (version 7.3.60.0.1) [52], ggplot2 (version 3.5.0) [53], dplyr (version 1.1.4)[54] and tidyr (version 1.3.1) [55].

Electronic Supplementary Material

Below is the link to the electronic supplementary material

Supplementary Material 1

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Acknowledgments:

None

Author Contribution

WK conceptualized the study, developed the methodology, ensured quality control of brain imaging data, conducted the experiments, constructed the statistical model, performed data analysis, and created all visual materials. She also managed the overall project, secured funding, and served as the primary supervisor of the study. WK interpreted the data. WK, MS, and PM drafted the manuscript. PK performed magnetic resonance spectroscopy. AB performed the MRI radiological examination, prepared the radiological description for the patients. WK, AT, MP, NŚ, and MS were responsible for patient recruitment and the collection of clinical data and biological samples. WK critically revised the manuscript for important intellectual content. WK supervised the research process. TP was responsible for leding the team of radiologists and the medical physicist involved in the study. WK made the most substantial contribution to all stages of the study and manuscript preparation. In recognition of her leading role, she is designated as the first and corresponding author.All authors have read and approved the final version of the manuscript.

All authors have read and approved the final version of the manuscript.

Data Availability

The data obtained through the experimental research conducted in this study are available from the corresponding author upon reasonable request. All data were acquired as part of the experimental work coordinated and supervised by the corresponding author, who was responsible for the overall design and execution of the study.

Competing interests

The authors declare no competing interests.

Ethics Declarations

The research was approved by the Bioethics Committee of the Jagiellonian University, under reference number 1072.6120.87.2024.

Consent for Publication

All authors have reviewed and approved the final manuscript.

Funding

This study was supported by the Priority Research Area BioS under the Excellence Initiative—Research University program at the Jagiellonian University in Krakow, Poland (grant no. U1C/P03/NO/03.36, awarded to WK as the principal investigator), and by the Jagiellonian University Medical College, Poland (grant no. N42/DBS/000452, awarded to WK as the principal investigator). The project was also funded by the National Science Centre, Poland (grant no. 2024/08/X/NZ7/00479, awarded to WK as the principal investigator).

Tables

Category	Characteristic	N	Value
Demographic Characteristics, n (%)	Sex	51
	Male		29 (56.9%)
	Female		22 (43.1%)
	Age (years)	51	27.7 (9.4)
Treatment Characteristics, n (%)	Olanzapine Serum Concentration (µg/L)	51
	≤ 4.35 µg/L		25 (49.0%)
	> 4.35 µg/L		26 (51.0%)
	Duration of Olanzapine Treatment (years), Mean (SD)	51	5.6 (5.9)
Clinical Scores, Mean (SD), [min – max]	PANSS Negative Symptoms Score	51	21.2 (6.6) [2.0–33.0]
	PANSS Negative Subscale Items N1–N7 Sum	51	21.4 (6.6) [8.0–34.0]
	PANSS Total Score	51	79.9 (20.9) [37.0–126.0]
	CDSS Total Score	51	8.5 (6.2) [0.0–22.0]
	BDI-II Total Score	51	18.7 (13.5) [0.0–51.0]
Serum Neurochemical Concentrations, Mean (SD), [min – max]	Serotonin Serum Concentration (ng/mL)	51	130.1 (21.7) [4.0–176.5]
	Glutamic Acid Serum Concentration (µg/mL)	51	2,711.4 (1,733.9) [537.9–8,871.9]
	Glutamine Serum Concentration (µg/mL)	51	342.6 (66.6) [87.6–476.8]
MRS Neurochemical Ratios (ACC, TE = 30 ms), Mean (SD), [min – max]	Glutamine / (Cr + PCr) Ratio	51	0.6 (0.1) [0.3–1.0]
	Glutamate / (Cr + PCr) Ratio	51	1.6 (0.2) [1.2–2.4]
	myo-Inositol / (Cr + PCr) Ratio	51	0.9 (0.1) [0.7–1.1]
	(Glutamate + Glutamine) / (Cr + PCr) Ratio	51	2.2 (0.3) [1.8–3.0]
MRS Neurochemical Ratios (PCC, TE = 30 ms), Mean (SD), [min – max]	Glutamine / (Cr + PCr) Ratio	51	0.6 (0.1) [0.4–1.0]
	Glutamate / (Cr + PCr) Ratio	51	1.6 (0.2) [1.1–1.8]
	myo-Inositol / (Cr + PCr) Ratio	51	0.9 (0.1) [0.7–1.1]
	(Glutamate + Glutamine) / (Cr + PCr) Ratio	51	2.2 (0.2) [1.8–2.7]

Notes: PANSS: Positive and Negative Syndrome Scale; CDSS: Calgary Depression Scale for Schizophrenia; BDI-II: Beck Depression Inventory-II. MRS: Magnetic Resonance Spectroscopy; ACC: Anterior Cingulate Cortex; PCC: Posterior Cingulate Cortex; Cr: Creatine; PCr: Phosphocreatine; TE: Echo Time.

Note

Partial correlation coefficients were calculated using the Spearman method, controlling for age, sex, and treatment duration. Only significant (p < 0.05) or near-significant (p < 0.10) results are reported. 95% CIs were estimated using Fisher’s z-transformation, adjusted for three covariates and a sample size of 51.

Table 2. Partial correlation coefficients and 95% confidence intervals for significant and near-significant associations.

Yes