Early growth response 1 (EGR1) is downregulated in peripheral blood from patients with major psychiatric disorders.

OBJECTIVES: To evaluate relative expression of genes with the potential to translate environmental stimuli into long-term alterations in the brain - namely Early Growth Response (EGR)1, EGR3, and Cryptochrome Circadian Regulator 2 (CRY2) - in peripheral blood from patients with Bipolar Disorder (BD), Schizophrenia (SZ), Major Depressive Disorder (MDD) and healthy controls (HC). METHODS: Thirty individuals ranging from 18 to 60 years were recruited for each group (BD, SZ, MDD or HC) from a Brazilian public hospital. Therefore, individuals' peripheral blood was collected and EGR1, EGR3 and CRY2 gene expression analyzed by PCR Real Time. RESULTS: EGR1 mRNA levels are significantly lower in psychiatric patients when compared to HC, but there is no difference for EGR3 and CRY2. Exploring the findings for each diagnosis, there is a significant difference between each diagnosis group only for EGR1, which was lower in BD, MDD and SZ as compared to HC. No significant correlations were found between gene expression and clinical features. CONCLUSIONS: EGR1 is downregulated in psychiatric patients, regardless of the diagnosis and may be a potential common target in major psychiatric disorders. EGR1, as a transcription factor, modulates many other genes and participates in crucial neuronal and synaptic processes, such as plasticity, neurotransmitters metabolism, vesicular transport and signaling pathways. The study of EGR1 and its upstream regulators in psychiatry might lead to potential new therapeutic targets.

Chronic pain predicts a worse response to depression treatment, regardless of thyroid function or psychotropics prescribed.

BACKGROUND: Chronic pain (CP) and thyroid hormones' (TH) abnormalities are associated with depression, but the impact of pain and TH fluctuation on the response to depression treatment is uncertain. METHODS: Eighty-eight patients with major depression were evaluated before and after 6 months of specific treatment, through scales of symptoms' severity (HAM-D-17), psychomotor disturbance (CORE), and quality of life (WHOQOL-Bref). We reviewed psychiatric medications and measured TSH, T3 and T4. We used Generalized Estimating Equations to assess the interaction effect between CP and treatment time on depression severity and TH levels, and Bonferroni to compare means. RESULTS: 47.7 % of the patients had CP. Patients with and without CP did not differ at baseline. At follow-up, those with CP experienced a more modest decrease in symptoms' severity and no improvement in any domain of psychomotor disturbance, contrasting with a decrease of over 40 % from the baseline values of CORE in patients without CP (non-CP). Initial and final scores were respectively: HAM-D CP 24.06 and 19.3, Δ = -4.75; HAM-D non-CP 22.92 and 14.7, Δ = -8.21; CORE CP 5.36 and 5.24, Δ = -0.12; CORE non-CP 5.8 and 3.22, Δ = -2.57. There was no interaction with TH or life quality. Model adjustments for psychotropic drugs received and sensitivity analysis excluding somatic symptoms from severity scales did not impact the results. LIMITATIONS: Findings may not replicate in mildly depressed patients from primary care. Pain scales were not applied. CONCLUSIONS: Individuals with chronic pain showed a suboptimal response to depression treatment, regardless of the medications used or TH levels.

Inflammation and damage-associated molecular patterns in major psychiatric disorders.

BACKGROUND: Emerging evidence indicates that inflammation plays an important role as a mechanism underlying mental disorders. However, most of the research on inflammatory mechanisms focuses on serum levels of interleukins and very few studies have investigated molecules that initiate and expand innate immune pathways such as damage-associated molecular patterns (DAMPs). OBJECTIVES: This study investigated the levels of DAMPs among patients diagnosed with major depressive disorder (MDD), bipolar disorder (BD) I and II, schizophrenia (SCZ), and generalized anxiety disorder (GAD). We quantified serum levels of heat shock proteins (HSPs) 70 and 60 and of S100 calcium-binding protein B (S100B). METHODS: Serum levels of HSP70, HSP60, and S100B were assessed in a sample of participants with psychiatric disorders (n = 191) and a control group (CT) (n = 59) using enzyme-linked immunosorbent assay (ELISA). RESULTS: Serum HSP70 concentrations were significantly higher in the MDD group compared to the CT, SCZ, and BD groups. The GAD group had higher concentrations of HSP70 than the SCZ group. Exploring associations with medications, lithium (p = 0.003) and clozapine (p = 0.028) were associated with lower HSP70 levels. Approximately 64% of the sample had DAMPs levels below the limits of detection indicated by the respective ELISA kit. CONCLUSION: This was the first study to assess DAMPs levels in a transdiagnostic sample. Our preliminary findings suggest that HSP70 may be associated with MDD pathophysiology. Medications such as lithium and clozapine were associated with lower HSP70 levels in BD and SCZ groups, respectively. Therefore, it is worth mentioning that all participants were medicated and many psychotropic drugs exert an anti-inflammatory effect, possibly reducing the signs of inflammation.

Inflammation and damage-associated molecular patterns in major psychiatric disorders

Abstract Background Emerging evidence indicates that inflammation plays an important role as a mechanism underlying mental disorders. However, most of the research on inflammatory mechanisms focuses on serum levels of interleukins and very few studies have investigated molecules that initiate and expand innate immune pathways such as damage-associated molecular patterns (DAMPs). Objectives This study investigated the levels of DAMPs among patients diagnosed with major depressive disorder (MDD), bipolar disorder (BD) I and II, schizophrenia (SCZ), and generalized anxiety disorder (GAD). We quantified serum levels of heat shock proteins (HSPs) 70 and 60 and of S100 calcium-binding protein B (S100B). Methods Serum levels of HSP70, HSP60, and S100B were assessed in a sample of participants with psychiatric disorders (n = 191) and a control group (CT) (n = 59) using enzyme-linked immunosorbent assay (ELISA). Results Serum HSP70 concentrations were significantly higher in the MDD group compared to the CT, SCZ, and BD groups. The GAD group had higher concentrations of HSP70 than the SCZ group. Exploring associations with medications, lithium (p = 0.003) and clozapine (p = 0.028) were associated with lower HSP70 levels. Approximately 64% of the sample had DAMPs levels below the limits of detection indicated by the respective ELISA kit. Conclusion This was the first study to assess DAMPs levels in a transdiagnostic sample. Our preliminary findings suggest that HSP70 may be associated with MDD pathophysiology. Medications such as lithium and clozapine were associated with lower HSP70 levels in BD and SCZ groups, respectively. Therefore, it is worth mentioning that all participants were medicated and many psychotropic drugs exert an anti-inflammatory effect, possibly reducing the signs of inflammation.

Earlier age of onset is associated with a pro-inflammatory state in major depressive disorder.

Major depressive disorder (MDD) is a common condition that affects the general population over a wide range of ages, regardless of gender and social background. Early-onset of MDD in adulthood, between ages of 18 and 30 years, is associated with worse outcomes and increased years of disability. Stress load and physical health have been associated with age of onset in MDD. We aim to investigate whether early onset MDD might be associated with changes in systemic inflammatory markers. We examined levels of following cytokines: IL-1ß, IL-6, IL-10 and TNFα in 234 patients with MDD. Higher serum levels of TNFα and IL-1ß are associated with the early onset of the disorder in patients with MDD. IL-6 levels were also higher in the early onset group and IL-10 levels were higher in the late onset group, but with no significant difference. Changes in the anti-inflammatory/pro-inflammatory balance have been described in mood disorders and may be implicated in its severity and pattern of progression. Our findings reinforce that higher serum levels of IL-1ß and TNFα may be associated with the earlier onset subgroup of MDD patients. Future research that target inflammatory markers of immune modulation may be, key in the search for novel preventative therapeutics.

Potential Candidates for Biomarkers in Bipolar Disorder: A Proteomic Approach through Systems Biology.

Bipolar disorder (BD) is one of the most disabling diseases characterized by severe humor fluctuation. It is accompanied by cognitive and functional impairment in addiction to high suicide rates. BD is often underdiagnosed and treated incorrectly because many of the reported symptoms are not exclusive to the disorder. Once the diagnosis is exclusively clinical, it is not possible to state precisely. From that, proteomic approaches were used to identify, in a large scale, all proteins involved in cellular or tissue processes. This review aggregate data from blood proteomes, by using protein association network, of subjects with BD and healthy controls to suggest dysfunctional molecular pathways involved in disease. Original articles containing proteomic analysis were searched in PubMed. Seven studies were selected and data were extracted for posterior analysis. A protein-protein interaction network was created by STRING database. A final set of proteins in this network were employed as input in ClueGO and, the main biological process was visualized using R package pathview. The analysis revealed proteins associated with many biological processes, including growth and endocrine regulation, iron transportation, protease inhibition, protection against pathogens and cholesterol transport. Moreover, pathway analysis indicated the association of uncovered proteins with two main metabolic pathways: complement system and coagulation cascade. Thus, a better understanding on the pathophysiology of psychiatric disorders and the identification of potential biomarker candidates are essential to improve diagnostic, prognostic and design pharmacological strategies.

Risk of neutropenia among clozapine users and non-users: results from 5,847 patients

Objective: Clozapine is underprescribed due to neutropenia risk. Blood tests every 3 months in those on continuous treatment for > 1 year who have never had an absolute neutrophil count (ANC) < 2,000/µL has been proposed as a monitoring strategy; however, there are no South American data to support this recommendation. This study sought to investigate whether clozapine use and other variables could explain the occurrence of ANC < 1,000/µL in patients with severe mental disorders. Methods: A total of 5,847 subjects were included, 1,038 on clozapine. We performed a Cox regression considering the outcome as ANC < 1,000/µL at any time point. Predictors were sex, age, ethnicity, clozapine use, ANC > 2,000/µL during the first year of blood monitoring, and presence of a severe medical condition. Results: In the Cox regression model, ethnicity (white) (hazard ratio [HR] 0.53; 95%CI 0.29-0.99, p < 0.05) and ANC > 2,000/µL (HR 0.04; 95%CI 0.01-0.10, p < 0.001) were protective factors, while presence of a severe medical condition (HR 69.35; 95%CI 37.45-128.44, p < 0.001) was a risk factor for ANC < 1,000/µL. Other variables were not significant, including clozapine use (HR 1.33; 95%CI 0.74-2.39, p > 0.05). Conclusions: These findings suggest that clozapine does not increase the risk of neutropenia in subjects with ANC > 2,000/µL during the first year of use and in the absence of a severe medical condition. These results could help guide clinical and public-health decisions regarding clozapine blood monitoring guidelines.

Risk of neutropenia among clozapine users and non-users: results from 5,847 patients.

OBJECTIVE: Clozapine is underprescribed due to neutropenia risk. Blood tests every 3 months in those on continuous treatment for > 1 year who have never had an absolute neutrophil count (ANC) < 2,000/µL has been proposed as a monitoring strategy; however, there are no South American data to support this recommendation. This study sought to investigate whether clozapine use and other variables could explain the occurrence of ANC < 1,000/µL in patients with severe mental disorders. METHODS: A total of 5,847 subjects were included, 1,038 on clozapine. We performed a Cox regression considering the outcome as ANC < 1,000/µL at any time point. Predictors were sex, age, ethnicity, clozapine use, ANC > 2,000/µL during the first year of blood monitoring, and presence of a severe medical condition. RESULTS: In the Cox regression model, ethnicity (white) (hazard ratio [HR] 0.53; 95%CI 0.29-0.99, p < 0.05) and ANC > 2,000/µL (HR 0.04; 95%CI 0.01-0.10, p < 0.001) were protective factors, while presence of a severe medical condition (HR 69.35; 95%CI 37.45-128.44, p < 0.001) was a risk factor for ANC < 1,000/µL. Other variables were not significant, including clozapine use (HR 1.33; 95%CI 0.74-2.39, p > 0.05). CONCLUSIONS: These findings suggest that clozapine does not increase the risk of neutropenia in subjects with ANC > 2,000/µL during the first year of use and in the absence of a severe medical condition. These results could help guide clinical and public-health decisions regarding clozapine blood monitoring guidelines.

Bipolar disorder: an association between body mass index and cingulate gyrus fractional anisotropy not mediated by systemic inflammation.

OBJECTIVE: To investigate associations between body mass index (BMI), white matter fractional anisotropy (FA), and C-reactive protein (CRP) in a group of individuals with bipolar disorder (BD) during euthymia and compare them with a control group of healthy subjects (CTR). METHODS: The sample consisted of 101 individuals (BD n = 35 and CTR n = 66). Regions of interest (ROI) were defined using a machine learning approach. For each ROI, a regression model tested the association between FA and BMI, controlling for covariates. Peripheral CRP levels were assayed, correlated with BMI, and included in a mediation analysis. RESULTS: BMI predicted the FA of the right cingulate gyrus in BD (AdjR2 = 0.312 F(3) = 5.537 p = 0.004; ß = -0.340 p = 0.034), while there was no association in CTR. There was an interaction effect between BMI and BD diagnosis (F(5) = 3.5857 p = 0.012; Fchange = 0.227 AdjR2 = 0.093; ß = -1.093, p = 0.048). Furthermore, there was a positive correlation between BMI and CRP in both groups (AdjR2 = 0.170 F(3) = 7.337 p < 0.001; ß = 0.364 p = 0.001), but it did not act as a mediator of the effect on FA. CONCLUSION: Higher BMI is associated with right cingulate microstructure in BD, but not in CTR, and this effect could not be explained by inflammatory mediation alone.

Bipolar disorder: an association between body mass index and cingulate gyrus fractional anisotropy not mediated by systemic inflammation

Abstract Objective To investigate associations between body mass index (BMI), white matter fractional anisotropy (FA), and C-reactive protein (CRP) in a group of individuals with bipolar disorder (BD) during euthymia and compare them with a control group of healthy subjects (CTR). Methods The sample consisted of 101 individuals (BD n = 35 and CTR n = 66). Regions of interest (ROI) were defined using a machine learning approach. For each ROI, a regression model tested the association between FA and BMI, controlling for covariates. Peripheral CRP levels were assayed, correlated with BMI, and included in a mediation analysis. Results BMI predicted the FA of the right cingulate gyrus in BD (AdjR2 = 0.312 F(3) = 5.537 p = 0.004; β = -0.340 p = 0.034), while there was no association in CTR. There was an interaction effect between BMI and BD diagnosis (F(5) = 3.5857 p = 0.012; Fchange = 0.227 AdjR2 = 0.093; β = -1.093, p = 0.048). Furthermore, there was a positive correlation between BMI and CRP in both groups (AdjR2 = 0.170 F(3) = 7.337 p < 0.001; β = 0.364 p = 0.001), but it did not act as a mediator of the effect on FA. Conclusion Higher BMI is associated with right cingulate microstructure in BD, but not in CTR, and this effect could not be explained by inflammatory mediation alone.

Association between childhood trauma, parental bonding and antisocial personality disorder in adulthood: A machine learning approach.

Childhood trauma (CT) and parental bonding (PB) have been correlated with later antisocial personality disorder (ASPD). Aiming to better understand this complex interaction we analyzed the data from a cross-sectional study that evaluated 346 male inpatient cocaine users, using both traditional statistical analysis and machine learning (ML) approaches. Childhood Trauma Questionnaire (CTQ), Parental Bonding Instrument (PBI), and Mini International Neuropsychiatric Interview (MINI) were applied. We found a markedly higher prevalence of mental illness in the ASPD group. The ML method and the traditional analysis showed that emotional and physical abuse were the factors with the strongest relationship with ASPD. Also, there were discrepancies between the findings of both methods regarding physical neglect and paternal care. Although this study does not allow definitive answers in this matter, we do propose that these two methods can aid in better comprehending how multiple variables interact with each other in the development of psychological disorders.

Evaluation of major depression symptom networks using clinician-rated and patient-rated data.

BACKGROUND: Major depressive disorder (MDD) is heterogeneous, but official diagnostic classifications and widely used rating scales are based on the premise that MDD is a single disorder and that symptoms are equally important to assess severity. Also, patients and clinicians frequently diverge in how they evaluate MDD severity. In order to better understand the differences between MDD scales used by clinicians and patients in the context of MDD heterogeneity, we performed a network analysis from an approach that focuses on the interaction of symptoms rather than total score. METHODS: The Hamilton Depression Rating Scale (HDRS) and the Beck Depression Inventory with 21 items (BDI) scored by the clinician or patient, respectively, were used to estimate the networks based on 794 MDD patients. The networks were estimated using software R 4.0.2 and Graphical Lasso, identifying communities of symptoms by the clique percolation method, and the mixed graphical models were used to evaluate the explained variance of each symptom. RESULTS: The networks presented different communities of symptoms and connection structure (M = 0.177, p = 0.0028). The guilt connection strength and its association with suicidal ideation was greater in the BDI network. LIMITATIONS: Transversal data from severe, chronic, or treatment resistant depression patients. CONCLUSIONS: The present study suggests that the self-rated scale may perform better when assessing association between guilt and other symptoms, especially suicidal ideation. Communities of symptoms and edges between symptoms suggest that insomnia may be an independent symptom, thus requiring specific interventions. Some similar items are strongly connected and could be collapsed.

Prediction of depression cases, incidence, and chronicity in a large occupational cohort using machine learning techniques: an analysis of the ELSA-Brasil study.

Abstract. BACKGROUND: Depression is highly prevalent and marked by a chronic and recurrent course. Despite being a major cause of disability worldwide, little is known regarding the determinants of its heterogeneous course. Machine learning techniques present an opportunity to develop tools to predict diagnosis and prognosis at an individual level. METHODS: We examined baseline (2008-2010) and follow-up (2012-2014) data of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), a large occupational cohort study. We implemented an elastic net regularization analysis with a 10-fold cross-validation procedure using socioeconomic and clinical factors as predictors to distinguish at follow-up: (1) depressed from non-depressed participants, (2) participants with incident depression from those who did not develop depression, and (3) participants with chronic (persistent or recurrent) depression from those without depression. RESULTS: We assessed 15 105 and 13 922 participants at waves 1 and 2, respectively. The elastic net regularization model distinguished outcome levels in the test dataset with an area under the curve of 0.79 (95% CI 0.76-0.82), 0.71 (95% CI 0.66-0.77), 0.90 (95% CI 0.86-0.95) for analyses 1, 2, and 3, respectively. CONCLUSIONS: Diagnosis and prognosis related to depression can be predicted at an individual subject level by integrating low-cost variables, such as demographic and clinical data. Future studies should assess longer follow-up periods and combine biological predictors, such as genetics and blood biomarkers, to build more accurate tools to predict depression course.