The Predictive Value of Monocyte/High-Density Lipoprotein Ratio (MHR) and Positive Symptom Scores for Aggression in Patients with Schizophrenia

Monitoring of mental health in occupational populations: a study on the role and application of HDL-related inflammatory index

Background

Mental disorders in occupational populations pose significant health and economic burdens, but there exists a lack of practical and objective biomarkers for occupational mental health monitoring. Our study aims to explore the correlation between high-density lipoprotein (HDL)-related inflammatory markers and negative psychological symptoms in occupational populations. We also seek to evaluate the potential application effectiveness of these indicators as biomarkers for identifying the impact of mental health on occupational populations. Moreover, the indicators found in this study can be used as indicators for identifying high-risk groups prone to inflammatory responses caused by negative psychological symptoms.

Methods

Our study adopted a cross-sectional design with a combination of questionnaires and biochemical index tests for 1920 eligible occupational populations. The Depression Anxiety Stress Scales-21 (DASS-21) was used to measure participants' levels of anxiety, depression, and stress. Collect individual and occupational characteristics of survey respondents through self-administered questionnaires. Blood samples are also collected to measure high-density lipoprotein cholesterol levels and peripheral blood cell counts. We employed statistical analyses including correlation analysis, Receiver Operating Characteristic (ROC) curve analysis, and univariate and multivariate regression.

Results

The final sample size included in the analysis was 1,434. The results showed that stress, anxiety, and depressive symptoms were significantly correlated with all four HDL-related inflammatory indices (p < 0.05). Especially for MHR, compared to those without symptoms, individuals experiencing stress, anxiety, or depression had an OR of 2.75 (95% CI: 1.90, 3.99), 3.27 (95% CI: 2.25, 4.78), and 3.02 (95% CI: 2.08, 4.40) for abnormally high levels, respectively. In addition, subgroup analyses showed that lower monthly incomes, longer working hours and frequent night shifts might be promoting factors for elevated HDL-related inflammatory levels. Receiver Operating Characteristic (ROC) analysis further demonstrated that PHR and MHR exhibit good predictive ability for all three psychological symptoms, with AUC values exceeding 0.6. Notably, for individuals with over 30 years of work experience, the predictive performance AUC is even higher, reaching above 0.7.

Conclusion

The results of this study suggest that PHR and MHR are expected to be potential biomarkers for identifying health problems caused by negative psychological symptoms in occupational groups, providing valuable information for occupational mental health assessment. Preventive measures should be implemented for high-risk groups, including those with low income, long working hours, and frequent night shifts, to mitigate potential health impacts.

Markers of inflammation in patients with generalized anxiety disorder

Purpose: The aim of this study was to analyze the systemic immune response index, systemic immune inflammation index, neutrophil/HDL, lymphocyte/HDL, platelet/HDL, and monocyte/HDL ratio, used as inflammatory markers in patients with generalized anxiety disorder (GAD). Materials and Methods: A total of 864 participants, including 432 healthy controls and 432 patients diagnosed with GAD, were included in this study. High-density lipoprotein (HDL-c) levels, neutrophil, monocyte, lymphocyte, and platelet counts; systemic inflammatory response index (SIRI), systemic immune-inflammatory index (SII), neutrophil/high-density lipoprotein ratio (NHR), lymphocyte/high-density lipoprotein ratio (LHR), monocyte/high-density lipoprotein ratio (MHR), and platelet/high-density lipoprotein ratio (PHR) were calculated. Results: The median age of the case group was 35.50 (interquartile range: 28.00-44.00), while the median age of the control group was 35.00 (interquartile range: 28.00-44.00). In the GAD group, neutrophils, monocytes, SII, SIRI, NHR, LHR, MHR, and PHR were significantly higher, while platelets and HDL were significantly lower. Conclusions: This study highlights that elevated systemic inflammation markers, such as SII and SIRI, along with altered HDL ratios, may be associated with GAD. The findings support the hypothesis that inflammation plays a role in the etiopathogenesis of GAD, potentially contributing to both diagnosis and management.

Clinical and Diagnostic Value of High-Density Lipoprotein-Based Inflammatory Indices and Lipid Ratios in Young Adults with Schizophrenia

Purpose

This study aimed to assess High-density Lipoprotein (HDL)-based Inflammatory Indices and lipid profile changes in antipsychotic-naive first-episode schizophrenia (AN-FES) patients, chronic schizophrenia (CS) patients, and explore the clinical and predictive value of these parameters for schizophrenia.

Patients and Methods

The study cohort included 52 AN-FES patients, 46 CS patients, and 52 healthy controls (HCs), with an average age of 24 years. Upon admission, patients underwent complete blood count and lipid profile analyses. Various ratios were calculated, including neutrophil-to-HDL (NHR), monocyte-to-HDL (MHR), lymphocyte-to-HDL (LHR), and platelet-to-HDL (PHR), as well as lipid ratios like triglycerides/HDL, non-HDL/HDL, total cholesterol/HDL, and low-density lipoprotein/HDL. For the AN-FES group, these evaluations were repeated after two months of treatment with atypical antipsychotics. Statistical analyses included correlation analysis, Receiver Operating Characteristic (ROC) curve analysis, and univariate and multivariate regression.

Results

Compared to HCs, CS patients exhibited significantly higher MHR and NHR values, while AN-FES patients showed elevated levels of PHR, MHR, and NHR. No significant differences were observed in LHR or lipid ratios across the three groups. In the AN-FES cohort, MHR correlated positively with neutrophil counts, and NHR with monocyte counts. Additionally, white blood cell counts were positively associated with both MHR and NHR. Following treatment, NHR levels decreased, whereas TG/HDL ratios increased, with MHR and PHR remaining elevated. ROC analysis highlighted NHR as the most diagnostically valuable parameter (AUC = 0.799), with 86.5% specificity at an optimal cutoff of 3.534, outperforming MHR and PHR. Regression analyses recognized NHR (OR=2.225) as an independent risk factor for schizophrenia, even after adjusting for confounders.

Conclusion

HDL-based inflammatory indices, particularly NHR, may serve as valuable diagnostic and prognostic markers in young adults with schizophrenia, even though significant alterations in lipid ratios were not observed in this demographic.

Construction and verification of aggressive behavior risk prediction model in stable patients with schizophrenia

BACKGROUND

Among all types of mental disorders, individuals with schizophrenia exhibit the highest frequency of aggressive behavior. This disrupts the healthcare environment and poses threats to family life and social harmony. Present approaches fail to identify individuals with schizophrenia who are predisposed to aggressive behavior. In this study, we aimed to construct a risk prediction model for aggressive behavior in stable patients with schizophrenia, which may facilitate early identification of patients who are predisposed to aggression by assessing relevant factors, enabling the management of high-risk groups to mitigate and prevent aggressive behavior.

METHODS

A convenience sample of stable inpatients with schizophrenia were selected from Daqing Municipal Third Hospital and Chifeng Municipal Anding Hospital from March 2021 to July 2023. A total of 429 patients with stable schizophrenia who met the inclusion criteria were included. A survey was conducted with them using a questionnaire consisting of general information questionnaire, Positive and Negative Symptom Scale, Childhood Trauma Questionnaire-Short Form, Connor-Davidson Resilience Scale and Self-esteem Scale. Patients enrolled in this study were divided into aggressive and non-aggressive groups based on whether there was at least one obvious and recorded personal attack episode (including obvious wounding and self-injurious behavior) following diagnosis. Binary Logistic regression was used to determine the influencing factors, and R software was used to establish a nomogram model for predicting the risk of aggressive behavior. Bootstrap method was used for internal validation of the model, and the validation group was used for external validation. C statistic and calibration curve were used to evaluate the prediction performance of the model.

RESULTS

The model variables included Age, Duration of disease, Positive symptom, Childhood Trauma, Self-esteem and Resilience. The AUROC of the model was 0.790 (95% CI:0.729-0.851), the best cutoff value was 0.308; the sensitivity was 70.0%; the specificity was 81.4%; The C statistics of internal and external validation were 0.759 (95%CI:0.725-0.814) and 0.819 (95%CI:0.733-0.904), respectively; calibration curve and Brier score showed good fit.

CONCLUSIONS

The prediction model has a good degree of discrimination and calibration, which can intuitively and easily screen the high risk of aggressive behavior in stable patients with schizophrenia, and provide references for early screening and intervention.

Neutrophil/high-density lipoprotein cholesterol (HDL), monocyte/HDL and platelet/HDL ratios are increased in acute mania as markers of inflammation, even after controlling for confounding factors

OBJECTIVE

Recent studies show that inflammation is related to the pathogenesis of acute mania of bipolar disorder. Neutrophil/high-density lipoprotein (HDL) ratio (NHR), lymphocyte/HDL ratio (LHR), monocyte/HDL ratio (MHR) and platelet/HDL ratio (PHR) have recently been investigated as novel markers of inflammation. In addition, the atherogenic index of plasma (AIP) and atherogenic coefficient (AC) are the leading atherogenic indices. The study aimed to investigate these inflammation and atherogenic index markers in acute mania of bipolar disorder. Another aim was to determine whether there is a relationship between these markers and disease severity and psychotic symptoms.

METHODS

A total of 109 BD-M and 101 (HC) were enrolled in the study. The differences in NHR, LHR, MHR, PHR, AIP and AC and their association with illness severity and psychotic symptoms were analyzed after adjusting for age, sex, total cholesterol level, body-mass index and smoking status. Then, a receiver operating characteristic (ROC) curve and linear discriminant analysis (LDA) were used to analyze these parameters' diagnostic potential. Moreover, the Young Mania Rating Scale (YMRS) and Clinical Global Impression Scale for use in bipolar illness-Severity subscale (CGI-BP-S) were used to assess the severity of clinical symptoms.

RESULTS

We found higher levels of NHR, MHR, PHR and AIP, but not LHR and AC, after adjusting confounding factors in patients with BD-M compared to HCs. In logistic regression analysis, higher levels of MHR and NHR were associated with BD-M. MHR, NHR and PHR were predictors for differentiating the BD-M group from the HC group. However, the severity of the illness or the psychotic feature of the manic episode did not significantly affect the parameters. In the ROC curve analysis of BD-M, the indicators with an area under the curve (AUC) higher than 0.6 were the MHR, NHR, PHR and LHR.

CONCLUSIONS

These results provide information about the role of inflammation in the pathophysiology of BD-M. Even after controlling for confounding factors, MHR, NHR, PHR and AIP are potential biomarkers for BD-M. Moreover, the increase in AIP may explain the co-morbidity between BD and cardiovascular diseases. However, the severity of the illness or the psychotic feature of the manic episode did not significantly affect the levels of inflammation ratios used in our study. Due to the low cost and widespread use of lipid metabolism and related inflammation rates, it may be beneficial to know the MHR, NHR, PHR and AIP levels in BD-M patients.