Parental rearing and personality traits as predictors for adolescents with obsessive-compulsive disorder (OCD).

We aim to determine the correlation between parental rearing, personality traits, and obsessive-compulsive disorder (OCD) in different quantiles. In particular, we created an intermediary effect model in which parental rearing affects OCD through personality traits. All predictors were measured at the time of the survey, comprising parental rearing (paternal rearing and maternal rearing), demographics (grade and gender), and personality traits (neuroticism, extroversion, and psychoticism). These results suggest that (a) paternal emotional warmth was negatively correlated with OCD at the 0.40-0.80 quantile, while maternal emotional warmth was positively correlated with the OCD at the 0.45-0.69 quantile. (b) The correlation between negative parental rearing and OCD ranged from the 0.67 to 0.95 quantile for paternal punishment, 0.14-0.82 quantile for paternal overprotection, 0.05-0.36 and >0.50 quantile for maternal over-intervention and overprotection, and 0.08-0.88 quantile for maternal rejection. (c) Extroversion, neuroticism, and psychoticism were not only associated with OCD in a particular quantile but also mediated between parental rearing (namely parental emotional warmth, paternal punishment, paternal overprotection, maternal rejection, maternal over-intervention, and overprotection) and OCD. These findings provide targets for early interventions of OCD to improve the form of family education and personality traits and warrant validation.

Quantile regression analysis of the association between parental rearing and interpersonal sensitivity in Chinese adolescents.

BACKGROUND: Parental rearing is well documented as an important influencing factor of interpersonal sensitivity (IS). However, little research has focused on the extent by which various aspects of parental rearing in fluence IS. This study aimed to analyze the effects of parental rearing on IS, using quantile regression. We analyzed the extent of the influence of parental rearing on IS by quantile regression to provide definitive evidence on the family education of adolescents with IS problems. METHODS: The multiple cross-sectional studies were conducted among 3345 adolescents from Harbin, China, in 1999, 2006, 2009 and 2016. Furthermore, a multistage sampling method (stratified random cluster) was used to select participants. IS was assessed using a subscale of the Symptom Checklist-90-Revision. Perceived parental rearing was assessed using the Egna Minnen av. Barndoms Uppfostran. The ordinary least squares (OLS) linear regression was used to determine the average effect of parental rearing on IS. The quantile regression was conducted to examine the established associations and to further explain the association. RESULTS: Paternal emotional warmth was found to be associated with IS across the quantile, especially after the 0.6 quantiles; however, this association was not found for maternal emotional warmth. Paternal punishment was associated with IS at the 0.22-0.27 and 0.60 quantile; however, maternal punishment had no significant effect on IS. QR method found that paternal overinvolvement was associated with IS at the 0.48-0.65 quantiles, but paternal overprotection was associated with IS across the quantile; however, maternal overinvolvement and overprotection was positively correlated with IS at the 0.07-0.95 quantiles. The correlation between paternal rejection and IS was found at the 0.40-0.75 and > 0.90 quantiles; maternal rejection was associated with IS within the 0.05-0.92 quantiles. CONCLUSIONS: Parental rearing practices predict different magnitudes of IS at varying levels. This study provides suggestions for parents to assess purposefully and systematically, intervene, and ameliorate adolescent IS problems. We also highlight the role of paternal rearing in children's IS problems, providing new ideas for family education.

Assessing the depression risk in the U.S. adults using nomogram.

BACKGROUND: Depression has received a lot of attention as a common and serious illness. However, people are rarely aware of their current depression risk probabilities. We aimed to develop and validate a predictive model applicable to the risk of depression in US adults. METHODS: This study was conducted using the database of the National Health and Nutrition Examination Survey (NHANES, 2017-2012). In particular, NHANES (2007-2010) was used as the training cohort (n = 6015) for prediction model construction and NHANES (2011-2012) was used as the validation cohort (n = 2812) to test the model. Depression was assessed (defined as a binary variable) by the Patient Health Questionnaire (PHQ-9). Socio-demographic characteristics, sleep time, illicit drug use and anxious days were assessed using a self-report questionnaire. Logistic regression analysis was used to evaluate independent risk factors for depression. The nomogram has the advantage of being able to visualize complex statistical prediction models as risk estimates of individualized disease probabilities. Then, we developed two depression risk nomograms based on the results of logistic regression. Finally, several validation methods were used to evaluate the prediction performance of nomograms. RESULTS: The predictors of model 1 included gender, age, income, education, marital status, sleep time and illicit drug use, and model 2, furthermore, included anxious days. Both model 1 and model 2 showed good discrimination ability, with a bootstrap-corrected C index of 0.71 (95% CI, 0.69-0.73) and 0.85 (95% CI, 0.83-0.86), and an externally validated C index of 0.71 (95% CI, 0.68-0.74) and 0.83 (95% CI, 0.81-0.86), respectively, and had well-fitted calibration curves. The area under the receiver operating characteristic curve (AUC) values of the models with 1000 different weighted random sampling and depression scores of 10-17 threshold range were higher than 0.7 and 0.8, respectively. Calculated net reclassification improvement (NRI) and integrated discrimination improvement (IDI) showed the discrimination or accuracy of the prediction models. Decision curve analysis (DCA) demonstrated that the depression models were practically useful. The network calculators work for participants to make personalized predictions. CONCLUSIONS: This study presents two prediction models of depression, which can effectively and accurately predict the probability of depression as well as helping the U.S. civilian non-institutionalized population to make optimal treatment decisions.

Global, regional, and national temporal trend in burden of major depressive disorder from 1990 to 2019: An analysis of the global burden of disease study.

Major depressive disorder (MDD) is one of the leading causes of disability worldwide. Comprehensive description of the global burden of MDD and its attributable risk factors is essential for policymaking but currently lacking. In this study, we aim to estimate the burden of MDD in terms of incidence, prevalence, and years lived with disability (YLDs), along with its attributable risk factors at global, regional, and rational level between 1990 and 2019, using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019. Data analysis was completed on July 1, 2023. In 2019, 274.80 million (95 % uncertainty interval [UI], 241.28 to 312.77) new cases of MDD were identified globally, with an increase of 59 % from 1990. A total of 37.20 million (25.65 to 51.22) YLDs were attributable to MDD, accounting for the largest proportion of mental disorder YLDs (29.7 %). Countries in the low sociodemographic index quantile exhibited the highest age-standardized incidence rate of MDD, with Uganda (7836.2, per 100,000 person-years, 6713.7 to 9181.1) and Palestine (7687.7, 6546.1 to 9023.9) reporting the highest rates among them. The United States had the highest increase in age-standardized rates, with an average annual percent change of 0.99. Females had 1.6 times higher age-standardised rates than males, ranging from 1.2 (Oceania) to 2.2 (tropical Latin America) times across 21 regions. Globally, the proportions of YLDs due to MDD attributable to bullying victimization, childhood sexual abuse, and intimate partner violence were 4.86 %, 5.46 %, and 8.43 % in 2019, respectively. The heavy burden of MDD serves as a stark reminder that a coordinated response from governments and health communities is urgently needed to scale up mental health services and implement effective interventions, particularly in low-income countries.

Trends in the prevalence and treatment of comorbid depression among US adults with and without cancer, 2005-2020.

BACKGROUND: Understanding trend characteristics of depression among cancer survivors is essential for healthcare policies and planning. This study estimates longitudinal trends in the prevalence and treatment of depression among adults in the United States with and without cancer. METHODS: This cross-sectional study focused on adults aged 20 years or older based on nationally representative data from the National Health and Nutrition Examination Surveys 2005-2020. Weighted logistic regression model was established to assess association between depression and cancer status after adjusting various covariates potentially related to depression. RESULTS: Among the 37,283 participants (weighted mean age, 47.5; women, 50.9 %), 3648 (9.8 %) were diagnosed with cancer and 3343 (9.0 %) were screened positive for depression. The age-standardized prevalence of depression showed a U-shaped trend in cancer survivors, decreasing from 11.8 % (95 % confidence interval, 8.4 %-15.2 %) in 2005-2008 to 8.3 % (5.6 %-11.0 %) in 2013-2016, then increasing to 11.7 % (6.3 %-17.2 %) in 2017-2020. These trends varied by population subgroup. Among depressive patients with cancer, antidepressant use increased from 38.6 % (28.7 %-48.5 %) in 2005-2008 to 62.9 % (40.6 %-85.2 %) in 2017-2020, whereas mental health consultation increased slightly. LIMITATIONS: Using a screening questionnaire instead of diagnostic criteria to identify depression; small sample size of patients with cancer; and cross-sectional analysis without prospective outcomes. CONCLUSIONS: From 2005 to 2020, the depression disease burden in patients with cancer eased in 2009-2015, but deteriorated recently. A healthy lifestyle and reasonable treatment for depression, based on an objective examination of depression characteristics, would improve long-term cancer outcomes and quality of life.

Development and validation of a predictive model for depression risk in the U.S. adult population: Evidence from the 2007-2014 NHANES.

BACKGROUND: Depression is a prevalent mental health disorder with a complex etiology and substantial public health implications. Early identification of individuals at risk for depression is crucial for effective intervention and prevention efforts. This study aimed to develop a predictive model for depression by integrating demographic factors (age, race, marital status, income), lifestyle factors (sleep duration, physical activity), and physiological measures (hypertension, blood lead levels). A key objective was to explore the role of physical activity and blood lead levels as predictors of current depression risk. METHODS: Data were extracted from the 2007-2014 National Health and Nutrition Examination Survey (NHANES). We applied a logistic regression analysis to these data to assess the predictive value of the above eight factors for depression to create the predictive model. RESULTS: The predictive model had bootstrap-corrected c-indexes of 0.68 (95% CI, 0.67-0.70) and 0.66 (95% CI, 0.64-0.68) for the training and validation cohorts, respectively, and well-calibrated curves. As the risk of depression increased, the proportion of participants with 1.76 ~ 68.90 µg/L blood lead gradually increased, and the proportion of participants with 0.05 ~ 0.66 µg/L blood lead gradually decreased. In addition, the proportion of sedentary participants increased as the risk of depression increased. CONCLUSIONS: This study developed a depression risk assessment model that incorporates physical activity and blood lead factors. This model is a promising tool for screening, assessing, and treating depression in the general population. However, because the corrected c-indices of the predictive model have not yet reached an acceptable threshold of 0.70, caution should be exercised when drawing conclusions. Further research is required to improve the performance of this model.

Cardiac-targeted delivery of nuclear receptor RORα via ultrasound targeted microbubble destruction optimizes the benefits of regular dose of melatonin on sepsis-induced cardiomyopathy.

BACKGROUND: Large-dose melatonin treatment in animal experiments was hardly translated into humans, which may explain the dilemma that the protective effects against myocardial injury in animal have been challenged by clinical trials. Ultrasound-targeted microbubble destruction (UTMD) has been considered a promising drug and gene delivery system to the target tissue. We aim to investigate whether cardiac gene delivery of melatonin receptor mediated by UTMD technology optimizes the efficacy of clinically equivalent dose of melatonin in sepsis-induced cardiomyopathy. METHODS: Melatonin and cardiac melatonin receptors in patients and rat models with lipopolysaccharide (LPS)- or cecal ligation and puncture (CLP)-induced sepsis were assessed. Rats received UTMD-mediated cardiac delivery of RORα/cationic microbubbles (CMBs) at 1, 3 and 5 days before CLP surgery. Echocardiography, histopathology and oxylipin metabolomics were assessed at 16-20 h after inducing fatal sepsis. RESULTS: We observed that patients with sepsis have lower serum melatonin than healthy controls, which was observed in the blood and hearts of Sprague-Dawley rat models with LPS- or CLP-induced sepsis. Notably, a mild dose (2.5 mg/kg) of intravenous melatonin did not substantially improve septic cardiomyopathy. We found decreased nuclear receptors RORα, not melatonin receptors MT1/2, under lethal sepsis that may weaken the potential benefits of a mild dose of melatonin treatment. In vivo, repeated UTMD-mediated cardiac delivery of RORα/CMBs exhibited favorable biosafety, efficiency and specificity, significantly strengthening the effects of a safe dose of melatonin on heart dysfunction and myocardial injury in septic rats. The cardiac delivery of RORα by UTMD technology and melatonin treatment improved mitochondrial dysfunction and oxylipin profiles, although there was no significant influence on systemic inflammation. CONCLUSIONS: These findings provide new insights to explain the suboptimal effect of melatonin use in clinic and potential solutions to overcome the challenges. UTMD technology may be a promisingly interdisciplinary pattern against sepsis-induced cardiomyopathy.

Development and Validation of a Novel Prognostic Model for Lower-Grade Glioma Based on Enhancer RNA-Regulated Prognostic Genes.

Enhancer RNAs (eRNAs) are present specifically in tumors, where they affect the expression of eRNA-regulated genes (ERGs). Owing to this characteristic, ERGs were hypothesized to improve prognosis of overall survival in heterogeneous low-grade and intermediate-grade gliomas. This study aimed to construct and validate an ERG prognostic tool to facilitate clinical management, and offer more effective diagnostic and therapeutic biomarkers for glioma. Survival-related eRNAs were identified, and their ERGs were selected based on eRNA and target gene information. The ERG prognostic model was constructed and validated using internal and external validation cohorts. Finally, biological differences related to the ERG signature were analysed to explore the potential mechanisms influencing survival outcomes. Thirteen ERGs were identified and used to build an ERG risk signature, which included five super-enhancer RNA (seRNA)-regulated genes and five LGG-specific eRNA-regulated genes. The prognostic nomogram established based on combining the ERG score, age, and sex was evaluated by calibration curves, clinical utility, Harrell's concordance index (0.86; 95% CI: 0.83-0.90), and time-dependent receiver operator characteristic curves. We also explored potential immune-related mechanisms that might cause variation in survival. The established prognostic model displayed high validity and robustness. Several immune-related genes regulated by seRNAs or specific eRNAs were identified, indicating that these transcripts or their genes were potential targets for improving immunotherapeutic/therapeutic outcomes. The functions of an important specific eRNA-regulated gene (USP28) were validated in robust vitro experiments. In addition, the ERG risk signature was significantly associated with the immune microenvironment and other immune-related features.

A Novel Prognostic Tool for Glioma Based on Enhancer RNA-Regulated Immune Genes.

Background: Gliomas are the most malignant tumors of the nervous system. Even though their survival outcome is closely affected by immune-related genes (IRGs) in the tumor microenvironment (TME), the corresponding regulatory mechanism remains poorly characterized. Methods: Specific enhancer RNAs (eRNAs) can be found in tumors, where they control downstream genes. The present study aimed to identify eRNA-regulated IRGs, evaluate their influence on the TME, and use them to construct a novel prognostic model for gliomas. Results: Thirteen target genes (ADCYAP1R1, BMP2, BMPR1A, CD4, DDX17, ELN, FGF13, MAPT, PDIA2, PSMB8, PTPN6, SEMA6C, and SSTR5) were identified and integrated into a comprehensive risk signature, which distinguished two risk subclasses. Discrepancies between these subclasses were compared to explore potential mechanisms attributed to eRNA-regulated genes, including immune cell infiltration, clinicopathological features, survival outcomes, and chemotherapeutic drug sensitivity. Furthermore, the risk signature was used to construct a prognostic tool that was evaluated by calibration curve, clinical utility, Harrell's concordance index (0.87; 95% CI: 0.84-0.90), and time-dependent receiver operator characteristic curves (AUCs: 0.93 and 0.89 at 3 and 5 years, respectively). The strong reliability and robustness of the established prognostic tool were validated in another independent cohort. Finally, potential subtypes were explored in patients with grade III tumors. Conclusion: Overall, eRNAs were associated with immune-related dysfunctions in the TME. Targeting of IRGs regulated by eRNAs could improve immunotherapeutic/therapeutic outcomes.

Temporal trend of circulating trans-fatty acids and risk of long-term mortality in general population.

BACKGROUND & AIMS: There has been controversial evidence regarding the relationship between isomers of circulating trans-fatty acids (TFAs) and mortality. This study aimed to ascertain the relationships between plasma TFAs and overall or cause-specific mortality of the general population in two independent subsets from the US National Health and Nutrition Examination Survey (1999-2000 and 2009-2010 cycles). METHODS AND RESULTS: Plasma TFA isomers (C16:1n-7t, C18:1n-7t, C18:1n-9t and C18:2n-6,9t) in 3439 adults free of cancer or severe cardiovascular disease were analyzed by gas chromatography/mass spectrometry. Overall, 259 died among 1376 individuals over a median follow-up of 15.6 years in the 1999-2000 cycle, and 105 died in the latter subset of 2063 subjects during a median of 5.9 years. Cox proportional hazards regression was conducted to estimate the hazard ratios of mortality. The main isomer of industrially derived TFAs, elaidic acid (C18:1n-9t) was considerably associated with long-term total mortality in the 1999-2000 cycle after adjusting for confounders, with a 54% increase in the top tertile compared with the bottom one. However, the association disappeared with halving C18:1n-9t by 2009-2010. In contrast, neither of the ruminant-derived TFAs (C16:1n-7t and C18:1n-7t) suggested any inverse correlations with all-cause death, mortality due to heart disease, cancer or other causes. CONCLUSION: The major isomer of industrial TFAs, the higher circulating C18:1n-9t might be associated with increased long-term mortality. The associations with death risk turned slight with the reduction of TFAs consumption by half. However, dietary guidelines should rigorously identify the healthy effect of animal TFAs consumption.

Fecal g. Streptococcus and g. Eubacterium_coprostanoligenes_group combined with sphingosine to modulate the serum dyslipidemia in high-fat diet mice.

BACKGROUND & AIMS: Although high-fat diet (HFD) could impact the composition of fecal microbiome and their metabolites, it is still largely unknown which fecal bacteria and metabolites are relatively important in responding to the HFD. This study aimed to identify the crucial fecal bacteria and metabolites in the HFD mice using a microbial-metabolite network, and to investigate the synergistic mediation effect of the crucial fecal bacteria and metabolites on serum dyslipidemia induced by the HFD. METHODS: The 16srDNA sequencing and the ultra-performance liquid chromatography (UPLC/TOF MSMS) platform were performed to characterize the composition and function of fecal microbiome, and metabolites in the HFD. The microbial-metabolite network, correlation and mediation analyses were performed to examine the relationships among fecal microbiome, metabolites, and serum dyslipidemia indicators. Mice models were conducted to evaluate the effect of fecal metabolite on dyslipidemia. RESULTS: Compared to the control, 32 genera were altered in the HFD, including 26 up-regulated and 6 down-regulated. A total of 42 altered pathways were observed between the control and HFD, and the "Glycosphingolipid biosynthesis" was identified as the most significant pathway (fold change = 0.64; p < 0.001). Meanwhile, 49 fecal metabolites were altered in the HFD, and the fecal microbiome was associated with the fecal metabolism (M2 = 0.776, p = 0.008). Based on the microbial-metabolite network, two major hub genera were screened (HUB1: g. Streptococcus, HUB2: g. Eubacterium_coprostanoligenes_group), and one bacterial metabolite, sphingosine, was found in this study. Further, the HUB2 was positively associated with fecal sphingosine (r = 0.646, p = 0.001), and its downstream metabolic pathway, "Glycosphingolipid biosynthesis" pathway (r = 0.544, p = 0.009). The regulatory relationship between the HUB2 and sphingosine synergistically mediated the effect of HFD on TCHO (33.7%), HDL-C (37.3%), and bodyweight (36.7%). Besides, compared to the HFD, the HFD with sphingosine supplementation had lower bodyweight (35.12 ± 1.23 vs. 39.42 ± 1.25, p < 0.001), TG (0.44 ± 0.08 vs. 0.52 ± 0.05, p = 0.002), TCHO (3.81 ± 0.34 vs. 4.51 ± 0.38, p = 0.002), and LDL-c (0.82 ± 0.09 vs. 0.97 ± 0.15, p = 0.016). CONCLUSIONS: The g. Streptococcus and g. Eubacterium_coprostanoligenes are two hub genera in the fecal micro-ecosystem of the HFD, and the g. Eubacterium_coprostanoligenes mediates the effect of HFD on dyslipidemia through sphingosine. Sphingosine supplementation can improve dyslipidemia induced by HFD.