Association of Elevated Urinary Cadmium Levels with Schizophrenia and Treatment Response on Negative Symptom Remission

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Growing evidence suggests that environmental factors, including heavy metals, may contribute to its pathogenesis. This study investigated the dual role of urinary cadmium as both a risk factor for schizophrenia and a predictor of treatment response. In this case-control study of 34 schizophrenia patients and 33 healthy controls, we found that patients had significantly higher baseline urinary cadmium levels than controls (P < 0.0001). Firth’s logistic regression revealed a dramatically increased risk of schizophrenia in individuals with high cadmium levels, even after adjusting for age, BMI, and lifestyle factors (Adjusted OR = 569.65, 95% CI: 32.60–48771.81, P < 0.001). The diagnostic performance of urinary cadmium was robust, with an AUC of 0.79. Critically, in the longitudinal analysis of patients, baseline log-transformed cadmium levels were significantly and negatively correlated with the 8-week improvement in PANSS negative scores (r = -0.44, P = 0.01), indicating that higher cadmium exposure predicted poorer outcomes. This was confirmed by multiple linear regression, which showed that baseline cadmium was an independent predictor for diminished improvement in negative symptoms (Adjusted β = -5.60, P = 0.04) after controlling for initial symptom severity, chlorpromazine treatment and other covariates. In conclusion, elevated urinary cadmium appears to be a powerful risk factor for schizophrenia and, innovatively, a potential prognostic biomarker for poor response of negative symptoms to treatment. These findings underscore the importance of environmental neurotoxicants in the clinical course of schizophrenia and suggest that cadmium screening could aid in risk stratification and tailoring individualized therapies. Health sciences/Biomarkers Health sciences/Diseases Health sciences/Medical research Biological sciences/Neuroscience Health sciences/Risk factors Schizophrenia Negative symptom Cadmium Treatment response Figures Figure 1 Figure 2 Introduction Schizophrenia is a severe and debilitating chronic mental disorder that affects approximately 0.3 percent of the population 1 . Men have a higher risk of being diagnosed with schizophrenia with a relative risk of about 1.4 compared with women 2 . Characterized by a complex constellation of symptoms, it is typically categorized into three main domains: positive symptoms (e.g., hallucinations, delusions), negative symptoms (e.g., avolition, anhedonia, social withdrawal, blunted affect), and cognitive impairments (e.g., deficits in memory, attention, and executive function) 3 . While positive symptoms are the most conspicuous features of the illness, it is the persistent negative and cognitive symptoms that are most closely linked to long-term functional disability, poor quality of life, and substantial socioeconomic burden 4 , 5 . Current pharmacological treatment for schizophrenia primarily relies on antipsychotic medications, which are generally effective in managing positive symptoms by targeting dopamine D2 receptors 6 , 7 . However, their efficacy against primary negative and cognitive symptoms is disappointingly limited 8 , 9 . This significant unmet therapeutic need has driven a search for novel biological pathways and risk factors that may not only contribute to the etiology of schizophrenia but also influence its clinical presentation and treatment outcomes 10 . A deeper understanding of these factors is critical for developing more targeted and effective interventions, especially for the domains of illness that are refractory to current treatments. The etiology of schizophrenia is multifactorial, arising from a complex interplay between genetic predisposition and environmental exposures 11 , 12 . While the disorder has a high heritability, estimated to be around 80% 13 , genetic factors alone do not fully account for its incidence, concordance rates in monozygotic twins being approximately 50% 14 . This discrepancy highlights the critical role of environmental risk factors, particularly those occurring during critical neurodevelopmental periods 15 , 16 . Established environmental risk factors include prenatal infection, obstetric complications, urban upbringing, and migration 17 – 19 . In recent years, attention has increasingly turned towards the potential role of environmental chemical exposures, such as endocrine-disrupting chemicals (EDCs) and neurotoxic heavy metals 20 , 21 . Heavy metals are pervasive environmental pollutants known for their neurotoxic properties, capable of crossing the blood-brain barrier and inducing a cascade of detrimental effects on the central nervous system (CNS) 22 . These effects, including the induction of oxidative stress, promotion of neuroinflammation, and disruption of neurotransmitter systems, overlap significantly with the core pathophysiological mechanisms implicated in schizophrenia 23 – 25 . For instance, oxidative stress and mitochondrial dysfunction are well-documented features in patients with schizophrenia, leading to neuronal damage and synaptic dysfunction 25 . Therefore, exposure to heavy metals that exacerbate these processes represents a highly plausible, yet under-investigated, risk factor for the disorder. Among neurotoxic heavy metals, cadmium (Cd) is of particular concern due to its widespread presence and profound biological toxicity. Human exposure to cadmium occurs primarily through dietary intake (especially from contaminated crops like rice and vegetables), industrial emissions, and, most significantly, tobacco smoke 26 , 27 . With a long biological half-life of 10–30 years, cadmium accumulates in the body, particularly in the kidneys and liver, serving as a marker of long-term cumulative exposure 28 . Numerous studies have demonstrated that cadmium can inflict severe damage on the CNS. Its proposed neurotoxic mechanisms include: (i) potentiation of oxidative stress via the generation of reactive oxygen species (ROS) and depletion of endogenous antioxidants like glutathione 29 , 30 ; (ii) disruption of critical neurotransmitter systems, including the dopaminergic, glutamatergic, and serotonergic pathways 31 ; (iii) promotion of a pro-inflammatory state in the brain by activating microglia and astrocytes 32 ; and (iv) compromising the integrity of the blood-brain barrier 33 . Given these compelling biological mechanisms, a few pioneering studies have explored the link between cadmium and psychiatric disorders. Elevated blood or serum cadmium levels have been reported in patients with schizophrenia compared to healthy controls in some populations 34 , and associations have also been found with depression and cognitive impairment in the general population 35 , 36 . However, evidence remains scarce and sometimes inconsistent, and most studies have been limited by small sample sizes or failure to account for crucial confounders like smoking. Crucially, to our knowledge, no study has yet explored whether an individual’s cadmium body burden could act as a biological determinant of treatment response in schizophrenia. This is a critical research gap, as a neurotoxic agent like cadmium could plausibly contribute to the biological substrate of treatment-resistant symptoms, particularly the negative symptoms that are tied to deficits in brain regions vulnerable to oxidative stress and inflammation 37 . Therefore, this study was designed to address these gaps in the literature. Given that men not only have a higher incidence of schizophrenia, with a relative risk approximately 1.4 times that of women, but also tend to exhibit an earlier age of onset and a more severe course of illness, particularly with more prominent negative symptoms 2 , focusing on a male-only cohort allows for a reduction in heterogeneity related to sex-specific differences in disease presentation and hormonal influences. Concentrating on this higher-risk population, our study first aimed to confirm the association between urinary cadmium exposure and schizophrenia risk. More innovatively, we then sought to determine whether baseline cadmium burden could predict the longitudinal treatment response. Ultimately, this research seeks to establish urinary cadmium as a potential, accessible biomarker to stratify patient prognosis and guide personalized therapeutic strategies for the challenging domain of negative symptoms. Methods and Materials Study Design and Participants This case-control study was conducted at the Fourth People’s Hospital of Nantong City, China. All procedures were approved by the hospital’s Institutional Review Board (IRB)(Approved number: 2021-K025), and written informed consent was obtained from all participants or their legal guardians prior to enrollment. Patient participants were recruited from inpatient and outpatient services. Inclusion criteria for the schizophrenia group were: (1) a diagnosis of schizophrenia confirmed by two senior psychiatrists according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5); (2) age between 18 and 60 years; (3) ability to provide informed consent. Exclusion criteria were: (1) a history of other major psychiatric disorders, including substance use disorders; (2) neurological diseases or a history of significant head trauma; (3) severe or unstable physical illnesses (e.g., renal, hepatic, or cardiovascular disease). A group of age- and sex-matched healthy controls was recruited from individuals undergoing routine health examinations at the same hospital. Controls were screened to exclude any personal or family history of major psychiatric disorders. Patients in the schizophrenia group received a standardized 8-week treatment protocol. Treatment was initiated with an appropriate antipsychotic medication (quetiapine, olanzapine, aripiprazole, or risperidone) based on the patient’s clinical condition. The initial dose was administered for one week to assess tolerability, after which it was gradually titrated to a therapeutic level. Doses were adjusted as needed throughout the 8-week period based on clinical response and side effects. To standardize the medication dosage for statistical analysis, all antipsychotic doses were converted to chlorpromazine equivalents. Data and Sample Collection Demographic information, including age, Body Mass Index (BMI), education level, smoking status, and alcohol consumption history, was collected from all participants through a structured questionnaire and clinical interview. First-morning midstream urine samples were collected from all participants at baseline (prior to the initiation of the 8-week treatment for patients). Samples were collected in sterile, polypropylene tubes, immediately placed on ice, and then centrifuged to remove sediment. The supernatant was aliquoted and stored at -80°C until analysis. Clinical Symptom Assessment The severity of psychiatric symptoms in the patient group was assessed using the Positive and Negative Syndrome Scale (PANSS). Assessments were conducted by two trained and experienced raters at three time points: baseline (0w), week 4 (4w), and week 8 (8w) of the treatment period. The change in symptom severity over the 4 and 8-week course was calculated as a delta score (Δ Score), defined as the 4 or 8-week score minus the baseline score. A negative value for this score indicates an improvement in symptoms. Urinary Cadmium Measurement Urinary cadmium concentrations were determined using an Inductively Coupled Plasma-Mass Spectrometer (ICP-MS), specifically an Agilent 7700x instrument (Agilent Technologies, Santa Clara, CA, USA), following established analytical protocols for trace metal analysis in biological fluids. Prior to analysis, frozen urine samples were thawed completely at room temperature, vortexed for 30 seconds to ensure homogeneity, and then centrifuged at 3000 g for 10 minutes using a Model 5424 R centrifuge (Eppendorf, Hamburg, Germany) to pellet any precipitates or cellular debris. A 0.5 mL aliquot of the clear supernatant was carefully transferred to a clean, metal-free 1.5 mL polypropylene tube (Eppendorf, Hamburg, Germany). The aliquot was then diluted 10-fold with a diluent consisting of 2% (v/v) nitric acid (Sigma-Aldrich, St. Louis, MO, USA) and 0.01% (v/v) Triton X-100 (Sigma-Aldrich, St. Louis, MO, USA) in deionized, ultrapure water (18.2 MΩ·cm), which was generated by a Milli-Q® system (MilliporeSigma, Burlington, MA, USA). The instrument was optimized daily for sensitivity and stability. Quantification was performed using an external calibration curve (0, 0.5, 1.0, 5.0, 10.0 µg/L) prepared by serially diluting a certified cadmium standard stock solution (1000 mg/L, Sigma-Aldrich, St. Louis, MO, USA) in the same diluent used for the samples. Statistical Analysis All statistical analyses were performed using R (version 4.2.0) and SPSS (version 26.0). A two-tailed P-value < 0.05 was considered statistically significant. Descriptive statistics were used to summarize participant characteristics. Non-normally distributed data were expressed as median (interquartile range, IQR), with group comparisons performed using the Mann-Whitney U test, respectively. Categorical variables were presented as frequencies (percentages) and compared between groups using the Chi-square (χ²) test. To assess the association between urinary cadmium and schizophrenia risk, urinary cadmium concentrations were log-transformed to better approximate a normal distribution. We then dichotomized the urinary cadmium levels into low/medium and high groups based on the median value of the entire cohort. Due to the presence of quasi-complete separation in the data, Firth’s penalized logistic regression was employed. Both a crude model and an adjusted model were constructed. The adjusted model controlled for age, BMI, education level, smoking status, and alcohol consumption. The diagnostic performance of urinary cadmium in distinguishing patients from controls was evaluated using Receiver Operating Characteristic (ROC) curve analysis. The Area Under the Curve (AUC) with its 95% confidence interval (CI) was calculated. The relationship between baseline cadmium levels and clinical symptoms was explored using Pearson’s correlation analysis. Correlations were calculated between log-transformed cadmium and baseline PANSS scores, as well as their 4 and 8-week change scores. To validate cadmium as an independent predictor of treatment response, multiple linear regression analysis was conducted. The 4 and 8-week change in PANSS negative symptoms (Δ in negative) was set as the dependent variable, with log-transformed urinary cadmium as the primary independent variable. Both a crude model and an adjusted model were developed. The adjusted model included age, BMI, education level, smoking status, alcohol consumption, chlorpromazine equivalent dose, and, critically, the baseline PANSS negative score to control for its potential influence on the magnitude of change. Results Participant Demographics and Baseline Cadmium Levels A total of 34 male patients with schizophrenia and 33 healthy male controls were included in this study. As detailed in Table 1 , there were no significant differences between the schizophrenia and control groups in terms of age, body mass index (BMI), height, or weight. Similarly, the distribution of smoking status, alcohol consumption, and education level did not differ significantly between the two groups. Table 1 The demographics for cases and control Control (n = 33) Schizophrenia (n = 34) Z/χ² P 25th 50th 75th 25th 50th 75th Age 24.50 33.00 48.00 27.50 35.50 41.75 -0.09 0.93 Height 1.63 1.73 1.77 1.68 1.75 1.78 -1.24 0.22 Weight 63.00 68.00 77.00 65.00 73.50 80.50 -1.43 0.15 BMI 22.59 24.39 25.85 22.72 24.68 25.99 -0.41 0.68 Cadmium 1.37 1.62 2.65 2.28 2.98 4.03 -4.10 12y 12(36.36%) 6(17.64%) 3.66 0.16 12y 13(39.39%) 14(41.18%) < 12y 8(24.25%) 14(41.18%) In stark contrast, the median urinary cadmium level in the schizophrenia group (2.98 ng/ml) was significantly higher than that in the control group (1.62 ng/ml; Z = -4.10, P < 0.0001). This difference is visually represented in a boxplot (Fig. 1 A), illustrating the elevated cadmium exposure in the patient cohort. Association between Urinary Cadmium and Schizophrenia Risk To investigate the association between cadmium exposure and schizophrenia, we performed Firth’s logistic regression, which is robust for data with separation. As shown in Table 2 , after dichotomizing participants into low/medium (Q1 + Q2) and high (Q3 + Q4) cadmium exposure groups, the high exposure group showed a significantly increased risk of schizophrenia in the crude model (OR = 6.92, 95% CI: 2.49–20.90, P < 0.001). Table 2 Association between urinary cadmium levels and schizophrenia risk using Firth’s logistic regression Beta OR (95% CI) P Crude Model (Log-transformed urinary cadmium) Low/Medium (Q1 + Q2) 1 High (Q3 + Q4) 1.94 6.92 (2.49–20.90) < 0.001 Adjusted Model* (Log-transformed urinary cadmium) Low/Medium (Q1 + Q2) 1 High (Q3 + Q4) 6.35 569.65 (32.60–48771.81) < 0.001 *Adjusted for age, BMI, education level, smoking status, and alcohol consumption. This association was substantially strengthened after adjusting for potential confounders including age, BMI, education level, smoking status, and alcohol consumption. In the adjusted model, individuals with high urinary cadmium levels had a dramatically increased risk of schizophrenia (Adjusted OR = 569.65, 95% CI: 32.60–48771.81, P < 0.001), indicating a powerful independent association. Furthermore, to evaluate the diagnostic potential of urinary cadmium, a Receiver Operating Characteristic (ROC) curve analysis was performed (Fig. 1 B). Urinary cadmium demonstrated strong performance in distinguishing patients with schizophrenia from healthy controls, with an Area Under the Curve (AUC) of 0.79. Correlation between Cadmium Levels and Clinical Symptom Changes We next explored the relationship between baseline log-transformed urinary cadmium levels and the changes in PANSS scores over the 8-week treatment period within the patient group (Table 3 ). Pearson’s correlation analysis revealed no significant association between baseline cadmium and baseline symptom severity for total, positive, or negative scores. Similarly, cadmium levels were not significantly correlated with the 8-week changes in total PANSS scores (r = -0.29, P = 0.10) or positive symptoms (r = -0.28, P = 0.11). Table 3 Correlation Analysis between Log-transformed Baseline Urinary Cadmium Levels and Changes in PANSS Scores. Pearson’s r P Total 0w 0.02 0.92 4w 0.21 0.23 8w 0.40 0.02* Positive 0w 0.15 0.39 4w 0.32 0.07 8w 0.45 0.01** Negative 0w -0.07 0.69 4w 0.08 0.66 8w 0.28 0.11 Δ in total 4w -0.15 0.39 8w -0.29 0.10 Δ in positive 4w -0.25 0.16 8w -0.28 0.11 Δ in negative 4w -0.27 0.12 8w -0.44 0.01* However, a significant and moderately strong negative correlation was found between baseline log-transformed cadmium levels and the 8-week improvement in negative symptoms (Δ in negative, 8w; r = -0.44, P = 0.01). This indicates that higher baseline cadmium levels were associated with less improvement in negative symptoms over the treatment course. This key relationship is visualized in the scatter plot presented in Fig. 2 . Cadmium as an Independent Predictor of Negative Symptom Improvement To determine if the association between cadmium and negative symptom improvement was independent of other potential confounders, we conducted a multiple linear regression analysis (Table 4 ). In the crude model, log-transformed urinary cadmium was a significant predictor of the 8-week change in negative symptoms (β = -4.69, 95% CI: -8.20 to -1.18, P = 0.01). Table 4 Association of Log-transformed Baseline Urinary Cadmium with the 8-Week Change in Negative Symptoms: A Multiple Linear Regression Analysis Log-transformed urinary cadmium Beta P Crude model -4.69(-8.20–1.18) 0.01 Adjusted model* -5.60(-10.88–0.31) 0.04 *Adjusted for age, BMI, education level, smoking status, alcohol consumption and chlorpromazine treatment. Crucially, after adjusting for age, BMI, education level, smoking status, alcohol consumption, and chlorpromazine equivalent dose of antipsychotic treatment, baseline urinary cadmium remained a significant independent predictor (Adjusted β = -5.60, 95% CI: -10.88 to -0.31, P = 0.04). This result suggests that for every one-unit increase in log-transformed urinary cadmium, the improvement in negative symptoms was predicted to decrease by 5.60 points, independent of the effects of other covariates. Discussion In this study, we investigated the dual role of urinary cadmium as both a risk factor and a prognostic marker in a male cohort with schizophrenia. Our findings provide two major insights. Firstly, we identified a powerful association between elevated urinary cadmium levels and the risk of schizophrenia, even after rigorous adjustment for key confounders. Secondly, and more innovatively, we demonstrated for the first time that baseline cadmium burden is a significant and independent predictor of the treatment response of negative symptoms over an 8-week period, with higher cadmium levels forecasting a poorer therapeutic outcome. Our first finding, that patients with schizophrenia exhibit significantly higher urinary cadmium levels, corroborates and extends previous research linking heavy metal exposure to psychiatric disorders 34 . The magnitude of the association observed in our study is striking and underscores the potential importance of this environmental toxicant in the disorder’s pathophysiology. The biological plausibility for this association is strong. Cadmium is a potent neurotoxin known to breach the blood-brain barrier and accumulate in the CNS 33 , 38 . Its neurotoxicity is mediated through multiple pathways that are highly relevant to the established neurobiology of schizophrenia. These include the induction of profound oxidative stress and the depletion of endogenous antioxidants like glutathione in critical brain regions such as the hippocampus and prefrontal cortex 39 , 40 , mechanisms that mirror the well-documented oxidative stress and neuroinflammation hypotheses of schizophrenia. Furthermore, cadmium has been shown to disrupt the delicate balance of key neurotransmitter systems, including dopaminergic and glutamatergic pathways, which are central to the current understanding of the disorder 41 . Thus, chronic cadmium exposure could act as a persistent environmental “hit,” exacerbating genetic vulnerabilities and contributing to the neurodevelopmental and neurodegenerative processes implicated in schizophrenia. The most significant contribution of our study lies in the second finding: the predictive value of baseline cadmium for the longitudinal treatment response of negative symptoms. This moves beyond a simple cross-sectional association to suggest a role for cadmium in shaping the clinical course of the illness. While positive symptoms often respond well to antipsychotic medication, negative symptoms frequently persist and are the primary drivers of long-term functional impairment 9 . Our results show a clear, negative correlation where higher cadmium levels were linked to diminished improvement in these refractory symptoms. We hypothesize that this effect may be due to cadmium-induced damage that undermines the neurobiological substrate for therapeutic response. For instance, negative symptoms are strongly associated with dysfunction in the prefrontal cortex 42 . Cadmium’s propensity to induce inflammation and oxidative stress in this very region could compromise neuronal plasticity and integrity, thereby rendering it less responsive to the therapeutic effects of antipsychotics. Essentially, cadmium may create a state of “biological resistance” that limits the potential for symptomatic recovery, particularly in the domain of negative symptoms. The clinical implications of these findings, if validated, could be substantial. Urinary cadmium is a readily accessible, non-invasive, and relatively inexpensive measurement. Our results suggest it could serve as a valuable biomarker with a dual purpose. Firstly, it could be used as an adjunct screening tool to identify individuals at higher risk for schizophrenia, particularly in populations with known environmental exposure. More importantly, within a clinical setting, baseline cadmium screening could help stratify patients according to their predicted treatment trajectory. Identifying patients with high cadmium burden at the outset could alert clinicians to a higher risk of poor response in negative symptoms. This would allow for the proactive consideration of more intensive or alternative treatment strategies, such as the early introduction of psychosocial interventions, targeted augmentation therapies, or novel treatments aimed at mitigating oxidative stress, thus paving the way for more personalized medicine in schizophrenia care 43 . This study possesses several strengths, including its prospective design for the treatment response component and its specific focus on the clinically crucial dimension of negative symptoms. However, certain limitations must be acknowledged. The sample size is relatively modest, which may affect the generalizability of our findings and the precision of our estimates, as reflected in the wide confidence interval of the adjusted OR. As a case-control study, it cannot definitively establish causality between cadmium exposure and schizophrenia risk. Furthermore, while we controlled for major confounders like smoking, there may be unmeasured variables, such as detailed dietary habits or specific occupational exposures, that could have influenced the results. Finally, as a single-center study, our findings require replication in larger, more diverse populations. Future research should be directed towards validating these findings in larger, multi-center, prospective cohort studies. Such studies would be better positioned to establish causality and provide more precise risk estimates. Additionally, preclinical research using animal models is warranted to elucidate the precise molecular mechanisms by which cadmium impairs the therapeutic response of negative symptoms. Investigating whether interventions aimed at reducing cadmium body burden, such as chelation therapy or antioxidant supplementation, could improve clinical outcomes in patients with high exposure would be a logical and clinically relevant next step. Conclusion In conclusion, this study provides compelling evidence for the dual role of cadmium in schizophrenia. Elevated urinary cadmium is not only a potent risk factor for the disorder, but also more critically, an independent predictor of poor therapeutic response for negative symptoms. These findings highlight urinary cadmium as a promising, non-invasive biomarker to aid in risk stratification and, importantly, to identify patients who may require more targeted therapeutic strategies to address one of the most persistent and debilitating aspects of the illness. Declarations Ethical approval This study was conducted in accordance with the principles of the Declaration of Helsinki (as revised in 2013). The study protocol was formally approved by the Institutional Review Board of the Nantong 4th People’s Hospital (No. 2021-K025). All participants were provided with a comprehensive explanation of the study’s objectives and procedures, and written informed consent was obtained from each individual prior to their enrollment. Competing interests The authors declare no competing interests. Funding This work was supported by the Chinese National Science Foundation (81700710), the Medical Research Project of Jiangsu Commission of Health (Z2021055), the Jiangsu Provincial Medical Association Special Research Fund Project (SYH-32034-0079(20230026)), Jiangsu Provincial Geriatric Health Research Project (LKM2024041), Medical Research Project of Nantong Commission of Health (MS2024075, MS2024073 and MS2023085). Author Contribution Gujun Cong, Zhenhua Ge, Xuming Wu and Qi Yan contributed equally to this work. They were responsible for the study’s conceptualization and design, development of the methodology, and overall project supervision, including quality assurance and control. Peijuan Wang and Jiancheng Qiu managed the on-site field activities and participant recruitment. Zhangjian Biao coordinated and executed the sample collection and processing. Yaqin Ding, Chao Liu, Yalin Jin conducted the literature search and drafted the initial versions of the Materials and Methods and Discussion sections. Ning Shen and Ningwei Zhao designed the statistical analysis plan, performed the formal data analysis, and interpreted the results. All authors read and approved the final manuscript. Data Availability The data that support the findings of this study are available within the manuscript. References Same, K. et al. A global, regional, and national burden and quality of care index for schizophrenia: Global burden of disease systematic analysis 1990–2019. Schizophr. Bull. 50 , 1083–1093 (2024). Janoutová, J. et al. Epidemiology and risk factors of schizophrenia. Neuroendocrinol. Lett. 37 , 1–8 (2016). 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G. et al. Reduction of plasma glutathione in psychosis associated with schizophrenia and bipolar disorder in translational psychiatry. Translational psychiatry . 7 , e1215–e1215 (2017). Chaves, C., Dursun, S. M., Tusconi, M. & Hallak, J. E. C. Neuroinflammation and schizophrenia–is there a link? Front. Psychiatry . 15 , 1356975 (2024). Pyatha, S., Kim, H., Lee, D. & Kim, K. Co-exposure to lead, mercury, and cadmium induces neurobehavioral impairments in mice by interfering with dopaminergic and serotonergic neurotransmission in the striatum. Front. Public. Health . 11 , 1265864 (2023). Zhao, Y. et al. Cortical thickness abnormalities at different stages of the illness course in schizophrenia: a systematic review and meta-analysis. JAMA psychiatry . 79 , 560–570 (2022). Kishi, T., Sakuma, K. & Hatano, M. & Iwata, N. N-acetylcysteine for schizophrenia: A systematic review and meta‐analysis. Psychiatry & Clin. Neurosciences 77 (2023). 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8104089","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":593074027,"identity":"3e1fc2c2-c47c-4ffc-84d5-b3ed0855e766","order_by":0,"name":"Jianbiao Zhang","email":"","orcid":"","institution":"Nantong 4th People’s Hospital, Affiliated to Kangda College of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jianbiao","middleName":"","lastName":"Zhang","suffix":""},{"id":593074028,"identity":"42ff8340-364e-427a-9cc0-1a93d4a9ad01","order_by":1,"name":"Ning Shen","email":"","orcid":"","institution":"Nantong 4th People’s Hospital, Affiliated to Kangda College of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ning","middleName":"","lastName":"Shen","suffix":""},{"id":593074031,"identity":"eb10e802-cf97-41b8-af5c-3840bb9588f7","order_by":2,"name":"Peijuan Wang","email":"","orcid":"","institution":"Nantong 4th People’s Hospital, Affiliated to Kangda College of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Peijuan","middleName":"","lastName":"Wang","suffix":""},{"id":593074032,"identity":"8ce37203-8f28-49cc-838c-b69fa1824d84","order_by":3,"name":"Jiancheng Qiu","email":"","orcid":"","institution":"Nantong 4th People’s Hospital, Affiliated to Kangda College of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jiancheng","middleName":"","lastName":"Qiu","suffix":""},{"id":593074033,"identity":"5c9d7ede-9905-4c4a-a04a-28aa0b14cd41","order_by":4,"name":"Yonghua Luo","email":"","orcid":"","institution":"Nantong 4th People’s Hospital, Affiliated to Kangda College of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yonghua","middleName":"","lastName":"Luo","suffix":""},{"id":593074034,"identity":"c045ed06-8ac6-4baf-bcfd-193e357d3f73","order_by":5,"name":"Yaqin Ding","email":"","orcid":"","institution":"Nantong 4th People’s Hospital, Affiliated to Kangda College of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yaqin","middleName":"","lastName":"Ding","suffix":""},{"id":593074039,"identity":"5aab81d6-42f3-4d3d-b798-9ed2da58ffad","order_by":6,"name":"Chao Liu","email":"","orcid":"","institution":"Nantong 4th People’s Hospital, Affiliated to Kangda College of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chao","middleName":"","lastName":"Liu","suffix":""},{"id":593074040,"identity":"88b934e1-0e19-49fa-872a-322ac535f268","order_by":7,"name":"Yalin Jin","email":"","orcid":"","institution":"Nantong 4th People’s Hospital, Affiliated to Kangda College of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yalin","middleName":"","lastName":"Jin","suffix":""},{"id":593074041,"identity":"37a1c6f2-f6ad-4c59-bc06-0a0254e8d6f7","order_by":8,"name":"Ningwei Zhao","email":"","orcid":"","institution":"China Exposomics Institute (CEI) Precision Medicine Co. Ltd","correspondingAuthor":false,"prefix":"","firstName":"Ningwei","middleName":"","lastName":"Zhao","suffix":""},{"id":593074043,"identity":"d94661d8-406f-496f-ae4e-555c52072d1c","order_by":9,"name":"Gujun Cong","email":"","orcid":"","institution":"Nantong 4th People’s Hospital, Affiliated to Kangda College of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Gujun","middleName":"","lastName":"Cong","suffix":""},{"id":593074044,"identity":"7c2cfc5c-67a6-4100-9fde-e0b6ba132b52","order_by":10,"name":"Zhenhua Ge","email":"","orcid":"","institution":"Nantong 4th People’s Hospital, Affiliated to Kangda College of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhenhua","middleName":"","lastName":"Ge","suffix":""},{"id":593074045,"identity":"79776bf7-096c-480d-81c1-905c2a83334e","order_by":11,"name":"Xuming Wu","email":"","orcid":"","institution":"Nantong 4th People’s Hospital, Affiliated to Kangda College of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xuming","middleName":"","lastName":"Wu","suffix":""},{"id":593074049,"identity":"255ef644-cef7-47b9-9f55-7355ece66a9a","order_by":12,"name":"Qi Yan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIie3PsUrDQBzH8QsHl6VYuv2LkPgIFw5CBh/m/hQyhSxdbhA5KMTFB6hQfAYn5yuFupxkjdghUXDq4tZJbEcVLhkd7jv++X2GPyE+339Nqq+IxfVnKxVE8TBijRgDEby1mUj0EBJUBqdLkk66SiExPWv+9LxuWruT/FXnBO9BBpp2b42L2HKWSfVR8p3ZtvgIZUiYEIWLmCIFaemcG7zhRzIP9IidO0m9TwErig9mxgBXgNr0kaY4kQ3eLfMj0QPItNmLTNpcjEeWcrkFkSx6fjmri+TloC4jFt4G3eHqOorDRffuIheGEPh5oo75qVj/IT6fz+f71TcPVlXDF456ZgAAAABJRU5ErkJggg==","orcid":"","institution":"Nantong 4th People’s Hospital, Affiliated to Kangda College of Nanjing Medical University","correspondingAuthor":true,"prefix":"","firstName":"Qi","middleName":"","lastName":"Yan","suffix":""}],"badges":[],"createdAt":"2025-11-13 09:38:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8104089/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8104089/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103177569,"identity":"03207fd1-fb12-46db-a9e0-7a1b64fc17ab","added_by":"auto","created_at":"2026-02-22 16:52:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":738255,"visible":true,"origin":"","legend":"\u003cp\u003eUrinary Cadmium Levels and Diagnostic Performance\u003c/p\u003e\n\u003cp\u003e(A) Boxplot comparison of urinary cadmium concentrations between patients with schizophrenia (n=34) and healthy controls (n=33). (B) ROC curve analysis assessing the diagnostic ability of urinary cadmium to differentiate patients with schizophrenia from healthy controls.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8104089/v1/47ca8efdd0501e3d4015aed1.png"},{"id":103177570,"identity":"cb21b640-a2aa-459d-a567-0f9258187620","added_by":"auto","created_at":"2026-02-22 16:52:26","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1019717,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plot of the association between log-transformed baseline urinary cadmium levels and the change in PANSS scores.\u003c/p\u003e\n\u003cp\u003eThe scatter plot illustrates the correlation between log-transformed baseline urinary cadmium levels (x-axis) and the 4 and 8-week change in PANSS total (A,B), positive (C, D) and negative (E,F) symptoms scores (y-axis). Each point represents an individual patient. The solid line represents the linear regression best-fit line. The Pearson correlation coefficient (r) and the corresponding P-value are displayed.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8104089/v1/d67bf715913773d2f8f42bbb.png"},{"id":104780790,"identity":"83817f6e-c62e-4089-a8d8-73e9c7577bda","added_by":"auto","created_at":"2026-03-17 07:53:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2447225,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8104089/v1/d26b7cbd-fadd-4344-801e-fdef15806818.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of Elevated Urinary Cadmium Levels with Schizophrenia and Treatment Response on Negative Symptom Remission","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSchizophrenia is a severe and debilitating chronic mental disorder that affects approximately 0.3 percent of the population\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Men have a higher risk of being diagnosed with schizophrenia with a relative risk of about 1.4 compared with women\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Characterized by a complex constellation of symptoms, it is typically categorized into three main domains: positive symptoms (e.g., hallucinations, delusions), negative symptoms (e.g., avolition, anhedonia, social withdrawal, blunted affect), and cognitive impairments (e.g., deficits in memory, attention, and executive function)\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. While positive symptoms are the most conspicuous features of the illness, it is the persistent negative and cognitive symptoms that are most closely linked to long-term functional disability, poor quality of life, and substantial socioeconomic burden\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCurrent pharmacological treatment for schizophrenia primarily relies on antipsychotic medications, which are generally effective in managing positive symptoms by targeting dopamine D2 receptors\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. However, their efficacy against primary negative and cognitive symptoms is disappointingly limited\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. This significant unmet therapeutic need has driven a search for novel biological pathways and risk factors that may not only contribute to the etiology of schizophrenia but also influence its clinical presentation and treatment outcomes\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. A deeper understanding of these factors is critical for developing more targeted and effective interventions, especially for the domains of illness that are refractory to current treatments.\u003c/p\u003e \u003cp\u003eThe etiology of schizophrenia is multifactorial, arising from a complex interplay between genetic predisposition and environmental exposures\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. While the disorder has a high heritability, estimated to be around 80%\u003csup\u003e13\u003c/sup\u003e, genetic factors alone do not fully account for its incidence, concordance rates in monozygotic twins being approximately 50%\u003csup\u003e14\u003c/sup\u003e. This discrepancy highlights the critical role of environmental risk factors, particularly those occurring during critical neurodevelopmental periods\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Established environmental risk factors include prenatal infection, obstetric complications, urban upbringing, and migration\u003csup\u003e\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. In recent years, attention has increasingly turned towards the potential role of environmental chemical exposures, such as endocrine-disrupting chemicals (EDCs) and neurotoxic heavy metals\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHeavy metals are pervasive environmental pollutants known for their neurotoxic properties, capable of crossing the blood-brain barrier and inducing a cascade of detrimental effects on the central nervous system (CNS)\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. These effects, including the induction of oxidative stress, promotion of neuroinflammation, and disruption of neurotransmitter systems, overlap significantly with the core pathophysiological mechanisms implicated in schizophrenia\u003csup\u003e\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. For instance, oxidative stress and mitochondrial dysfunction are well-documented features in patients with schizophrenia, leading to neuronal damage and synaptic dysfunction\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Therefore, exposure to heavy metals that exacerbate these processes represents a highly plausible, yet under-investigated, risk factor for the disorder.\u003c/p\u003e \u003cp\u003eAmong neurotoxic heavy metals, cadmium (Cd) is of particular concern due to its widespread presence and profound biological toxicity. Human exposure to cadmium occurs primarily through dietary intake (especially from contaminated crops like rice and vegetables), industrial emissions, and, most significantly, tobacco smoke\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. With a long biological half-life of 10\u0026ndash;30 years, cadmium accumulates in the body, particularly in the kidneys and liver, serving as a marker of long-term cumulative exposure\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Numerous studies have demonstrated that cadmium can inflict severe damage on the CNS. Its proposed neurotoxic mechanisms include: (i) potentiation of oxidative stress via the generation of reactive oxygen species (ROS) and depletion of endogenous antioxidants like glutathione\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e; (ii) disruption of critical neurotransmitter systems, including the dopaminergic, glutamatergic, and serotonergic pathways\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e; (iii) promotion of a pro-inflammatory state in the brain by activating microglia and astrocytes\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e; and (iv) compromising the integrity of the blood-brain barrier\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGiven these compelling biological mechanisms, a few pioneering studies have explored the link between cadmium and psychiatric disorders. Elevated blood or serum cadmium levels have been reported in patients with schizophrenia compared to healthy controls in some populations\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e, and associations have also been found with depression and cognitive impairment in the general population\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. However, evidence remains scarce and sometimes inconsistent, and most studies have been limited by small sample sizes or failure to account for crucial confounders like smoking. Crucially, to our knowledge, no study has yet explored whether an individual\u0026rsquo;s cadmium body burden could act as a biological determinant of treatment response in schizophrenia. This is a critical research gap, as a neurotoxic agent like cadmium could plausibly contribute to the biological substrate of treatment-resistant symptoms, particularly the negative symptoms that are tied to deficits in brain regions vulnerable to oxidative stress and inflammation\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTherefore, this study was designed to address these gaps in the literature. Given that men not only have a higher incidence of schizophrenia, with a relative risk approximately 1.4 times that of women, but also tend to exhibit an earlier age of onset and a more severe course of illness, particularly with more prominent negative symptoms\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, focusing on a male-only cohort allows for a reduction in heterogeneity related to sex-specific differences in disease presentation and hormonal influences. Concentrating on this higher-risk population, our study first aimed to confirm the association between urinary cadmium exposure and schizophrenia risk. More innovatively, we then sought to determine whether baseline cadmium burden could predict the longitudinal treatment response. Ultimately, this research seeks to establish urinary cadmium as a potential, accessible biomarker to stratify patient prognosis and guide personalized therapeutic strategies for the challenging domain of negative symptoms.\u003c/p\u003e"},{"header":"Methods and Materials","content":"\u003cp\u003eStudy Design and Participants\u003c/p\u003e \u003cp\u003eThis case-control study was conducted at the Fourth People\u0026rsquo;s Hospital of Nantong City, China. All procedures were approved by the hospital\u0026rsquo;s Institutional Review Board (IRB)(Approved number: 2021-K025), and written informed consent was obtained from all participants or their legal guardians prior to enrollment.\u003c/p\u003e \u003cp\u003ePatient participants were recruited from inpatient and outpatient services. Inclusion criteria for the schizophrenia group were: (1) a diagnosis of schizophrenia confirmed by two senior psychiatrists according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5); (2) age between 18 and 60 years; (3) ability to provide informed consent. Exclusion criteria were: (1) a history of other major psychiatric disorders, including substance use disorders; (2) neurological diseases or a history of significant head trauma; (3) severe or unstable physical illnesses (e.g., renal, hepatic, or cardiovascular disease).\u003c/p\u003e \u003cp\u003eA group of age- and sex-matched healthy controls was recruited from individuals undergoing routine health examinations at the same hospital. Controls were screened to exclude any personal or family history of major psychiatric disorders.\u003c/p\u003e \u003cp\u003ePatients in the schizophrenia group received a standardized 8-week treatment protocol. Treatment was initiated with an appropriate antipsychotic medication (quetiapine, olanzapine, aripiprazole, or risperidone) based on the patient\u0026rsquo;s clinical condition. The initial dose was administered for one week to assess tolerability, after which it was gradually titrated to a therapeutic level. Doses were adjusted as needed throughout the 8-week period based on clinical response and side effects. To standardize the medication dosage for statistical analysis, all antipsychotic doses were converted to chlorpromazine equivalents.\u003c/p\u003e \u003cp\u003eData and Sample Collection\u003c/p\u003e \u003cp\u003eDemographic information, including age, Body Mass Index (BMI), education level, smoking status, and alcohol consumption history, was collected from all participants through a structured questionnaire and clinical interview.\u003c/p\u003e \u003cp\u003e First-morning midstream urine samples were collected from all participants at baseline (prior to the initiation of the 8-week treatment for patients). Samples were collected in sterile, polypropylene tubes, immediately placed on ice, and then centrifuged to remove sediment. The supernatant was aliquoted and stored at -80\u0026deg;C until analysis.\u003c/p\u003e \u003cp\u003eClinical Symptom Assessment\u003c/p\u003e \u003cp\u003eThe severity of psychiatric symptoms in the patient group was assessed using the Positive and Negative Syndrome Scale (PANSS). Assessments were conducted by two trained and experienced raters at three time points: baseline (0w), week 4 (4w), and week 8 (8w) of the treatment period. The change in symptom severity over the 4 and 8-week course was calculated as a delta score (Δ Score), defined as the 4 or 8-week score minus the baseline score. A negative value for this score indicates an improvement in symptoms.\u003c/p\u003e \u003cp\u003eUrinary Cadmium Measurement\u003c/p\u003e \u003cp\u003eUrinary cadmium concentrations were determined using an Inductively Coupled Plasma-Mass Spectrometer (ICP-MS), specifically an Agilent 7700x instrument (Agilent Technologies, Santa Clara, CA, USA), following established analytical protocols for trace metal analysis in biological fluids.\u003c/p\u003e \u003cp\u003ePrior to analysis, frozen urine samples were thawed completely at room temperature, vortexed for 30 seconds to ensure homogeneity, and then centrifuged at 3000 g for 10 minutes using a Model 5424 R centrifuge (Eppendorf, Hamburg, Germany) to pellet any precipitates or cellular debris. A 0.5 mL aliquot of the clear supernatant was carefully transferred to a clean, metal-free 1.5 mL polypropylene tube (Eppendorf, Hamburg, Germany). The aliquot was then diluted 10-fold with a diluent consisting of 2% (v/v) nitric acid (Sigma-Aldrich, St. Louis, MO, USA) and 0.01% (v/v) Triton X-100 (Sigma-Aldrich, St. Louis, MO, USA) in deionized, ultrapure water (18.2 MΩ\u0026middot;cm), which was generated by a Milli-Q\u0026reg; system (MilliporeSigma, Burlington, MA, USA).\u003c/p\u003e \u003cp\u003eThe instrument was optimized daily for sensitivity and stability. Quantification was performed using an external calibration curve (0, 0.5, 1.0, 5.0, 10.0 \u0026micro;g/L) prepared by serially diluting a certified cadmium standard stock solution (1000 mg/L, Sigma-Aldrich, St. Louis, MO, USA) in the same diluent used for the samples.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using R (version 4.2.0) and SPSS (version 26.0). A two-tailed P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003cp\u003eDescriptive statistics were used to summarize participant characteristics. Non-normally distributed data were expressed as median (interquartile range, IQR), with group comparisons performed using the Mann-Whitney U test, respectively. Categorical variables were presented as frequencies (percentages) and compared between groups using the Chi-square (χ\u0026sup2;) test.\u003c/p\u003e \u003cp\u003eTo assess the association between urinary cadmium and schizophrenia risk, urinary cadmium concentrations were log-transformed to better approximate a normal distribution. We then dichotomized the urinary cadmium levels into low/medium and high groups based on the median value of the entire cohort. Due to the presence of quasi-complete separation in the data, Firth\u0026rsquo;s penalized logistic regression was employed. Both a crude model and an adjusted model were constructed. The adjusted model controlled for age, BMI, education level, smoking status, and alcohol consumption.\u003c/p\u003e \u003cp\u003eThe diagnostic performance of urinary cadmium in distinguishing patients from controls was evaluated using Receiver Operating Characteristic (ROC) curve analysis. The Area Under the Curve (AUC) with its 95% confidence interval (CI) was calculated.\u003c/p\u003e \u003cp\u003eThe relationship between baseline cadmium levels and clinical symptoms was explored using Pearson\u0026rsquo;s correlation analysis. Correlations were calculated between log-transformed cadmium and baseline PANSS scores, as well as their 4 and 8-week change scores.\u003c/p\u003e \u003cp\u003eTo validate cadmium as an independent predictor of treatment response, multiple linear regression analysis was conducted. The 4 and 8-week change in PANSS negative symptoms (Δ in negative) was set as the dependent variable, with log-transformed urinary cadmium as the primary independent variable. Both a crude model and an adjusted model were developed. The adjusted model included age, BMI, education level, smoking status, alcohol consumption, chlorpromazine equivalent dose, and, critically, the baseline PANSS negative score to control for its potential influence on the magnitude of change.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eParticipant Demographics and Baseline Cadmium Levels\u003c/p\u003e \u003cp\u003eA total of 34 male patients with schizophrenia and 33 healthy male controls were included in this study. As detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, there were no significant differences between the schizophrenia and control groups in terms of age, body mass index (BMI), height, or weight. Similarly, the distribution of smoking status, alcohol consumption, and education level did not differ significantly between the two groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe demographics for cases and control\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;33)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eSchizophrenia (n\u0026thinsp;=\u0026thinsp;34)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eZ/χ\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25th\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50th\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75th\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25th\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50th\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75th\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e73.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e80.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCadmium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-4.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eSmoke Status\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e26(78.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e32(94.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e7(21.20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e2(5.90%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eAlcoholic status\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e28(84.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e31(91.18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e5(15.15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e3(8.82%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;12y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e12(36.36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e6(17.64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e3.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e13(39.39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e14(41.18%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;12y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e8(24.25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e14(41.18%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn stark contrast, the median urinary cadmium level in the schizophrenia group (2.98 ng/ml) was significantly higher than that in the control group (1.62 ng/ml; Z = -4.10, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). This difference is visually represented in a boxplot (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), illustrating the elevated cadmium exposure in the patient cohort.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAssociation between Urinary Cadmium and Schizophrenia Risk\u003c/p\u003e \u003cp\u003eTo investigate the association between cadmium exposure and schizophrenia, we performed Firth\u0026rsquo;s logistic regression, which is robust for data with separation. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, after dichotomizing participants into low/medium (Q1\u0026thinsp;+\u0026thinsp;Q2) and high (Q3\u0026thinsp;+\u0026thinsp;Q4) cadmium exposure groups, the high exposure group showed a significantly increased risk of schizophrenia in the crude model (OR\u0026thinsp;=\u0026thinsp;6.92, 95% CI: 2.49\u0026ndash;20.90, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between urinary cadmium levels and schizophrenia risk using Firth\u0026rsquo;s logistic regression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCrude Model (Log-transformed urinary cadmium)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow/Medium (Q1\u0026thinsp;+\u0026thinsp;Q2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh (Q3\u0026thinsp;+\u0026thinsp;Q4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.92 (2.49\u0026ndash;20.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eAdjusted Model* (Log-transformed urinary cadmium)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow/Medium (Q1\u0026thinsp;+\u0026thinsp;Q2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh (Q3\u0026thinsp;+\u0026thinsp;Q4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e569.65 (32.60\u0026ndash;48771.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*Adjusted for age, BMI, education level, smoking status, and alcohol consumption.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThis association was substantially strengthened after adjusting for potential confounders including age, BMI, education level, smoking status, and alcohol consumption. In the adjusted model, individuals with high urinary cadmium levels had a dramatically increased risk of schizophrenia (Adjusted OR\u0026thinsp;=\u0026thinsp;569.65, 95% CI: 32.60\u0026ndash;48771.81, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating a powerful independent association.\u003c/p\u003e \u003cp\u003eFurthermore, to evaluate the diagnostic potential of urinary cadmium, a Receiver Operating Characteristic (ROC) curve analysis was performed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Urinary cadmium demonstrated strong performance in distinguishing patients with schizophrenia from healthy controls, with an Area Under the Curve (AUC) of 0.79.\u003c/p\u003e \u003cp\u003eCorrelation between Cadmium Levels and Clinical Symptom Changes\u003c/p\u003e \u003cp\u003eWe next explored the relationship between baseline log-transformed urinary cadmium levels and the changes in PANSS scores over the 8-week treatment period within the patient group (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Pearson\u0026rsquo;s correlation analysis revealed no significant association between baseline cadmium and baseline symptom severity for total, positive, or negative scores. Similarly, cadmium levels were not significantly correlated with the 8-week changes in total PANSS scores (r = -0.29, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.10) or positive symptoms (r = -0.28, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.11).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation Analysis between Log-transformed Baseline Urinary Cadmium Levels and Changes in PANSS Scores.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePearson\u0026rsquo;s r\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eΔ in total\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eΔ in positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eΔ in negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eHowever, a significant and moderately strong negative correlation was found between baseline log-transformed cadmium levels and the 8-week improvement in negative symptoms (Δ in negative, 8w; r = -0.44, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01). This indicates that higher baseline cadmium levels were associated with less improvement in negative symptoms over the treatment course. This key relationship is visualized in the scatter plot presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCadmium as an Independent Predictor of Negative Symptom Improvement\u003c/p\u003e \u003cp\u003eTo determine if the association between cadmium and negative symptom improvement was independent of other potential confounders, we conducted a multiple linear regression analysis (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In the crude model, log-transformed urinary cadmium was a significant predictor of the 8-week change in negative symptoms (β = -4.69, 95% CI: -8.20 to -1.18, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of Log-transformed Baseline Urinary Cadmium with the 8-Week Change in Negative Symptoms: A Multiple Linear Regression Analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLog-transformed urinary cadmium\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrude model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.69(-8.20\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdjusted model*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-5.60(-10.88\u0026ndash;0.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e*Adjusted for age, BMI, education level, smoking status, alcohol consumption and chlorpromazine treatment.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCrucially, after adjusting for age, BMI, education level, smoking status, alcohol consumption, and chlorpromazine equivalent dose of antipsychotic treatment, baseline urinary cadmium remained a significant independent predictor (Adjusted β = -5.60, 95% CI: -10.88 to -0.31, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04). This result suggests that for every one-unit increase in log-transformed urinary cadmium, the improvement in negative symptoms was predicted to decrease by 5.60 points, independent of the effects of other covariates.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we investigated the dual role of urinary cadmium as both a risk factor and a prognostic marker in a male cohort with schizophrenia. Our findings provide two major insights. Firstly, we identified a powerful association between elevated urinary cadmium levels and the risk of schizophrenia, even after rigorous adjustment for key confounders. Secondly, and more innovatively, we demonstrated for the first time that baseline cadmium burden is a significant and independent predictor of the treatment response of negative symptoms over an 8-week period, with higher cadmium levels forecasting a poorer therapeutic outcome.\u003c/p\u003e \u003cp\u003eOur first finding, that patients with schizophrenia exhibit significantly higher urinary cadmium levels, corroborates and extends previous research linking heavy metal exposure to psychiatric disorders\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. The magnitude of the association observed in our study is striking and underscores the potential importance of this environmental toxicant in the disorder\u0026rsquo;s pathophysiology. The biological plausibility for this association is strong. Cadmium is a potent neurotoxin known to breach the blood-brain barrier and accumulate in the CNS\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Its neurotoxicity is mediated through multiple pathways that are highly relevant to the established neurobiology of schizophrenia. These include the induction of profound oxidative stress and the depletion of endogenous antioxidants like glutathione in critical brain regions such as the hippocampus and prefrontal cortex\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, mechanisms that mirror the well-documented oxidative stress and neuroinflammation hypotheses of schizophrenia. Furthermore, cadmium has been shown to disrupt the delicate balance of key neurotransmitter systems, including dopaminergic and glutamatergic pathways, which are central to the current understanding of the disorder\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Thus, chronic cadmium exposure could act as a persistent environmental \u0026ldquo;hit,\u0026rdquo; exacerbating genetic vulnerabilities and contributing to the neurodevelopmental and neurodegenerative processes implicated in schizophrenia.\u003c/p\u003e \u003cp\u003eThe most significant contribution of our study lies in the second finding: the predictive value of baseline cadmium for the longitudinal treatment response of negative symptoms. This moves beyond a simple cross-sectional association to suggest a role for cadmium in shaping the clinical course of the illness. While positive symptoms often respond well to antipsychotic medication, negative symptoms frequently persist and are the primary drivers of long-term functional impairment\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Our results show a clear, negative correlation where higher cadmium levels were linked to diminished improvement in these refractory symptoms. We hypothesize that this effect may be due to cadmium-induced damage that undermines the neurobiological substrate for therapeutic response. For instance, negative symptoms are strongly associated with dysfunction in the prefrontal cortex\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Cadmium\u0026rsquo;s propensity to induce inflammation and oxidative stress in this very region could compromise neuronal plasticity and integrity, thereby rendering it less responsive to the therapeutic effects of antipsychotics. Essentially, cadmium may create a state of \u0026ldquo;biological resistance\u0026rdquo; that limits the potential for symptomatic recovery, particularly in the domain of negative symptoms.\u003c/p\u003e \u003cp\u003eThe clinical implications of these findings, if validated, could be substantial. Urinary cadmium is a readily accessible, non-invasive, and relatively inexpensive measurement. Our results suggest it could serve as a valuable biomarker with a dual purpose. Firstly, it could be used as an adjunct screening tool to identify individuals at higher risk for schizophrenia, particularly in populations with known environmental exposure. More importantly, within a clinical setting, baseline cadmium screening could help stratify patients according to their predicted treatment trajectory. Identifying patients with high cadmium burden at the outset could alert clinicians to a higher risk of poor response in negative symptoms. This would allow for the proactive consideration of more intensive or alternative treatment strategies, such as the early introduction of psychosocial interventions, targeted augmentation therapies, or novel treatments aimed at mitigating oxidative stress, thus paving the way for more personalized medicine in schizophrenia care\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis study possesses several strengths, including its prospective design for the treatment response component and its specific focus on the clinically crucial dimension of negative symptoms. However, certain limitations must be acknowledged. The sample size is relatively modest, which may affect the generalizability of our findings and the precision of our estimates, as reflected in the wide confidence interval of the adjusted OR. As a case-control study, it cannot definitively establish causality between cadmium exposure and schizophrenia risk. Furthermore, while we controlled for major confounders like smoking, there may be unmeasured variables, such as detailed dietary habits or specific occupational exposures, that could have influenced the results. Finally, as a single-center study, our findings require replication in larger, more diverse populations.\u003c/p\u003e \u003cp\u003eFuture research should be directed towards validating these findings in larger, multi-center, prospective cohort studies. Such studies would be better positioned to establish causality and provide more precise risk estimates. Additionally, preclinical research using animal models is warranted to elucidate the precise molecular mechanisms by which cadmium impairs the therapeutic response of negative symptoms. Investigating whether interventions aimed at reducing cadmium body burden, such as chelation therapy or antioxidant supplementation, could improve clinical outcomes in patients with high exposure would be a logical and clinically relevant next step.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study provides compelling evidence for the dual role of cadmium in schizophrenia. Elevated urinary cadmium is not only a potent risk factor for the disorder, but also more critically, an independent predictor of poor therapeutic response for negative symptoms. These findings highlight urinary cadmium as a promising, non-invasive biomarker to aid in risk stratification and, importantly, to identify patients who may require more targeted therapeutic strategies to address one of the most persistent and debilitating aspects of the illness.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthical approval\u003c/h2\u003e \u003cp\u003e This study was conducted in accordance with the principles of the Declaration of Helsinki (as revised in 2013). The study protocol was formally approved by the Institutional Review Board of the Nantong 4th People\u0026rsquo;s Hospital (No. 2021-K025). All participants were provided with a comprehensive explanation of the study\u0026rsquo;s objectives and procedures, and written informed consent was obtained from each individual prior to their enrollment.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the Chinese National Science Foundation (81700710), the Medical Research Project of Jiangsu Commission of Health (Z2021055), the Jiangsu Provincial Medical Association Special Research Fund Project (SYH-32034-0079(20230026)), Jiangsu Provincial Geriatric Health Research Project (LKM2024041), Medical Research Project of Nantong Commission of Health (MS2024075, MS2024073 and MS2023085).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eGujun Cong, Zhenhua Ge, Xuming Wu and Qi Yan contributed equally to this work. They were responsible for the study\u0026rsquo;s conceptualization and design, development of the methodology, and overall project supervision, including quality assurance and control. Peijuan Wang and Jiancheng Qiu managed the on-site field activities and participant recruitment. Zhangjian Biao coordinated and executed the sample collection and processing. Yaqin Ding, Chao Liu, Yalin Jin conducted the literature search and drafted the initial versions of the Materials and Methods and Discussion sections. Ning Shen and Ningwei Zhao designed the statistical analysis plan, performed the formal data analysis, and interpreted the results. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available within the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSame, K. et al. 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Neurosciences\u003c/em\u003e \u003cb\u003e77\u003c/b\u003e (2023).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Schizophrenia, Negative symptom, Cadmium, Treatment response","lastPublishedDoi":"10.21203/rs.3.rs-8104089/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8104089/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSchizophrenia is a severe mental disorder where negative symptoms remain a major therapeutic challenge. Growing evidence suggests that environmental factors, including heavy metals, may contribute to its pathogenesis. This study investigated the dual role of urinary cadmium as both a risk factor for schizophrenia and a predictor of treatment response. In this case-control study of 34 schizophrenia patients and 33 healthy controls, we found that patients had significantly higher baseline urinary cadmium levels than controls (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Firth\u0026rsquo;s logistic regression revealed a dramatically increased risk of schizophrenia in individuals with high cadmium levels, even after adjusting for age, BMI, and lifestyle factors (Adjusted OR\u0026thinsp;=\u0026thinsp;569.65, 95% CI: 32.60\u0026ndash;48771.81, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The diagnostic performance of urinary cadmium was robust, with an AUC of 0.79. Critically, in the longitudinal analysis of patients, baseline log-transformed cadmium levels were significantly and negatively correlated with the 8-week improvement in PANSS negative scores (r = -0.44, P\u0026thinsp;=\u0026thinsp;0.01), indicating that higher cadmium exposure predicted poorer outcomes. This was confirmed by multiple linear regression, which showed that baseline cadmium was an independent predictor for diminished improvement in negative symptoms (Adjusted β = -5.60, P\u0026thinsp;=\u0026thinsp;0.04) after controlling for initial symptom severity, chlorpromazine treatment and other covariates. In conclusion, elevated urinary cadmium appears to be a powerful risk factor for schizophrenia and, innovatively, a potential prognostic biomarker for poor response of negative symptoms to treatment. These findings underscore the importance of environmental neurotoxicants in the clinical course of schizophrenia and suggest that cadmium screening could aid in risk stratification and tailoring individualized therapies.\u003c/p\u003e","manuscriptTitle":"Association of Elevated Urinary Cadmium Levels with Schizophrenia and Treatment Response on Negative Symptom Remission","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-22 16:52:21","doi":"10.21203/rs.3.rs-8104089/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ef8c1f03-0382-4731-a463-bebda1112eba","owner":[],"postedDate":"February 22nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":63106250,"name":"Health sciences/Biomarkers"},{"id":63106251,"name":"Health sciences/Diseases"},{"id":63106252,"name":"Health sciences/Medical research"},{"id":63106253,"name":"Biological sciences/Neuroscience"},{"id":63106254,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-03-12T04:09:40+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-22 16:52:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8104089","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8104089","identity":"rs-8104089","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}