Association between plasma levels of BDNF and GDNF and the diagnosis, treatment response in first-episode MDD

A systematic review of the biomarkers associated with cognition and mood state in bipolar disorder

BACKGROUND

Bipolar disorder (BD) is a severe psychiatric disorder characterized by changes in mood that alternate between (hypo) mania or depression and mixed states, often associated with functional impairment and cognitive dysfunction. But little is known about biomarkers that contribute to the development and sustainment of cognitive deficits. The aim of this study was to review the association between neurocognition and biomarkers across different mood states.

METHOD

Search databases were Web of Science, Scopus and PubMed. A systematic review was carried out following the PRISMA guidelines. Risk of bias was assessed with the Newcastle-Ottawa Scale. Studies were selected that focused on the correlation between neuroimaging, physiological, genetic or peripheral biomarkers and cognition in at least two phases of BD: depression, (hypo)mania, euthymia or mixed. PROSPERO Registration No.: CRD42023410782.

RESULTS

A total of 1824 references were screened, identifying 1023 published articles, of which 336 were considered eligible. Only 16 provided information on the association between biomarkers and cognition in the different affective states of BD. The included studies found: (i) Differences in levels of total cholesterol and C reactive protein depending on mood state; (ii) There is no association found between cognition and peripheral biomarkers; (iii) Neuroimaging biomarkers highlighted hypoactivation of frontal areas as distinctive of acute state of BD; (iv) A deactivation failure has been reported in the ventromedial prefrontal cortex (vmPFC), potentially serving as a trait marker of BD.

CONCLUSION

Only a few recent articles have investigated biomarker-cognition associations in BD mood phases. Our findings underline that there appear to be central regions involved in BD that are observed in all mood states. However, there appear to be underlying mechanisms of cognitive dysfunction that may vary across different mood states in BD. This review highlights the importance of standardizing the data and the assessment of cognition, as well as the need for biomarkers to help prevent acute symptomatic phases of the disease, and the associated functional and cognitive impairment.

Effect of Regular Aerobic Exercise on Cognitive Function, Depression Level and Regulative Role of Neurotrophic Factor: A Prospective Cohort Study in the Young and the Middle-Aged Sample

Purpose

Mild cognitive impairment (MCI) and depressive disorder (DD), which are associated with unhealthy lifestyles, are prevalent worldwide. This study aimed to investigate the effects of regular aerobic exercise on cognitive function, depression, and the regulatory role of neurotrophic growth factors for providing scientific basis in preventing MCI and DD in healthy individuals.

Patients and Methods

Eighty members of the fitness center and 80 community residents were recruited, who were administered by the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and the Patient Health Questionnaire (PHQ-9). Brain-derived neurotrophic factor (BDNF) and glial cell-line-derived neurotrophic factor (GDNF) in the peripheral blood were detected by enzyme-linked immunosorbent assay (ELISA).

Results

The RBANS and other factor scores, except for visuospatial abilities, were higher and PHQ-9 scores were lower in the study group than in the control group. The concentrations of BDNF and GDNF in the study group were higher than those in the control group. RBANS and its factor scores positively and PHQ-9 negatively correlated with BDNF and GDNF levels. Finally, multiple regression analysis showed that BDNF, as a predictor of RBANS, could explain 59.90% of its variance and that GDNF was a predictor of PHQ-9 could explain 12.30% of the variance.

Conclusion

Regular aerobic exercise can improve cognitive function and depressive symptoms by increasing the BDNF and GDNF levels.

Interactions between neurotrophins, mood, and physical activity under the conditions of sleep deprivation

Sleep deprivation (DS) is the forced elimination of sleep. While brain-derived neurotrophic factor (BDNF) has been extensively studied in the context of in mood changes following DS, the role of other neurotrophins remains elusive. This study explores the impact of DS on BDNF, glial cell line-derived neurotrophic factor (GDNF), neurotrophin-3 (NT3), and neurotrophin-4 (NT4) at mRNA and protein level, considering their potential links to mood disturbances. The study involved 81 participants subjected to polysomnography (PSG) and DS. Blood samples, mood assessments, and actigraphy data were collected twice, after PSG and DS. NT mRNA expression and serum protein concentrations of BDNF, GDNF, NT3, and NT4 were measured. Participants were divided into Responders and Non-Responders based on mood improvement after DS. DS reduced BDNF mRNA expression in all participants, with no change in serum BDNF protein. GDNF protein decreased in Non-Responders, while Responders exhibited reduced GDNF mRNA. NT3 protein increased in both groups, while NT3 mRNA decreased in Respondents. NT4 protein rose universally post-DS, but NT4 mRNA remained unchanged. Physical activity (PA) negatively correlated with mRNA expression of BDNF, GDNF, and NT3 post-DS. The study's short DS duration and exclusion of immature NT forms limit comprehensive insights. GDNF, together with NT3, might play an important role in mood response to DS. PA during DS seems to impair the mRNA expression of NTs in leukocytes. Future studies on the subject of sleep deprivation might consider investigating the relationship between BDNF and NT4 in the context of their apparent redundancy.

Alterations in anthropometric, inflammatory and mental health parameters during Ramadan intermittent fasting in a group of healthy people: a prospective cohort study

Fasting has been practiced with different time span in different areas of the world and for various reasons. One of the types of fasting regimens is Ramadan intermittent fasting (RIF), which is described as intermittent dry fasting and known as the most commonly practiced form of religious fasting. Different studies have shown its effects on body composition parameters and mental health, fatigue and quality of life (QoL). Elucidating the relationship of RIF on biological parameters would also be of importance to show its mechanism. Therefore, we evaluated several biological mediators related to mental health, such as ß-nerve growth factor (ß-NGF), brain-derived neurotrophic factor (BDNF), glial cell line-derived neurotrophic factor (GDNF), and insulin-like growth factor-1 (IGF-1), interleukin-8 (IL-8), tumor necrosis factor-α (TNF-α), and matrix-metalloproteinase-9 (MMP-9). This study consisted of fasting (FG; n = 25) and non-fasting group (NFG; n = 25). Four different time points were assessed for FG: one week before (T1), mid (T2), last days (T3), and one week after (T4) RIF. T1 and T3 were the assessment time points for NFG. Biological mediators were determined from serum samples by using Human Magnetic Luminex and enzyme-linked immunosorbent assay. Furthermore, we then performed correlation analyses between biological mediators and our previously published clinical parameters including body composition and mental health parameters at all time points. Significant alterations were shown in FG for ß-NGF (T2vsT3, p < 0.05; T2vsT4, p < 0.05), GDNF (T1vsT4, p < 0.05; T2vsT4, p < 0.05), IL-8 (T2vsT3, p < 0.05; T3vsT4, p < 0.05), TNF-α (T1vsT3, p < 0.05; T1vsT4, p < 0.001; T2vsT4, p < 0.001), and MMP-9 (T1vsT4, p < 0.01). There were no statistically significant differences between FG and NFG in all biological mediators at T1 and T3. Correlation analysis showed that MMP-9 levels had negative correlation with body mass index (BMI) at T3. At T3 BDNF levels had negative correlation with Epworth Sleepiness Scale (ESS) as one of measured QoL parameters. ß-NGF, GDNF, TNF-α, and MMP-9 had positive correlation with some of body composition and mental health parameters. Findings demonstrate that RIF altered different biological mediators could give benefit to health. Its benefit is mediated by the alteration of biological mediators.

TCF4 and RBFOX1 as peripheral biomarkers for the differential diagnosis and treatment of major depressive disorder

BACKGROUND

Recent genome-wide association studies on major depressive disorder (MDD) have indicated the involvement of LRFN5 and OLFM4; however, the expression levels and roles of these molecules in MDD remain unclear. The present study aimed to determine the serum levels of TCF4 and RBFOX1 in patients with MDD and to investigate whether these molecules could be used as biomarkers for MDD diagnosis.

METHODS

The study included 99 drug-naïve MDD patients, 90 drug-treated MDD patients, and 81 healthy controls (HCs). Serum TCF4 and RBFOX1 levels were measured by ELISA. Pearson's correlation analysis was conducted to determine the association between TCF4/RBFOX1 and clinical variables. Linear support vector machine classifier was used to evaluate the diagnostic capabilities of TCF4 and RBFOX1.

RESULTS

Serum TCF4 and RBFOX1 levels were substantially higher in MDD patients than in HCs and significantly lower in drug-treated MDD patients than in drug-naïve MDD patients. Moreover, serum TCF4 and RBFOX1 levels were associated with the Hamilton Depression Scale score, duration of illness, serum lipids levels, and hepatic function. Thus, both these molecules showed potential as biomarkers for MDD. TCF4 and RBFOX1 combination exhibited a higher diagnostic performance, with the mean area under the curve values of 0.9861 and 0.9936 in the training and testing sets, respectively.

LIMITATIONS

Small sample size and investigation of only the peripheral nervous system.

CONCLUSIONS

TCF4 and RBFOX1 may be involved in the pathogenesis of MDD, and their combination may serve as a diagnostic biomarker panel for MDD.

Brain-Derived Neurotrophic Factor (BDNF) as a Predictor of Treatment Response in Major Depressive Disorder (MDD): A Systematic Review

Brain-derived neurotrophic factor (BDNF) has been studied as a biomarker of major depressive disorder (MDD). Besides diagnostic biomarkers, clinically useful biomarkers can inform response to treatment. We aimed to review all studies that sought to relate BDNF baseline levels, or BDNF polymorphisms, with response to treatment in MDD. In order to achieve this, we performed a systematic review of studies that explored the relation of BDNF with both pharmacological and non-pharmacological treatment. Finally, we reviewed the evidence that relates peripheral levels of BDNF and BDNF polymorphisms with the development and management of treatment-resistant depression.

Plasma Brain-Derived Neurotrophic Factor Levels in First-Episode and Recurrent Major Depression and before and after Bright Light Therapy in Treatment-Resistant Depression

Brain-derived neurotrophic factor (BDNF) is implicated in the etiology and treatment response in major depressive disorder (MDD). However, peripheral BDNF concentrations have not been compared across different MDD stages. Bright light therapy (BLT) offers some potential in treatment-resistant depression (TRD), but its effects on BDNF levels are unknown. This study included a cross-sectional analysis of plasma BDNF concentration in females with TRD, unmedicated MDD patients, and healthy controls (HC), and measurements of longitudinal BLT effects on plasma BDNF levels in TRD patients. The present study included 55 drug-naïve, first-episode patients, 25 drug-free recurrent-episode MDD patients, 71 HC participants, and 54 TRD patients. Patients were rated by Hamilton Depression Rating Scale (HAMD)-17 and the Montgomery-Åsberg Depression Rating Scale (MADRS). Patients with TRD received BLT during 4 weeks. The total HAMD-17 and MADRS scores decreased following BLT. All patient groups had lower plasma BDNF than HC, but BDNF levels did not differ between first- and recurrent-episode BDNF patients and TRD patients before or after BLT. However, responders and remitters to BLT had higher post-treatment plasma BDNF concentrations than patients who did not achieve response or remission. The changes in plasma BDNF levels may be candidates for biomarkers of treatment response to BLT in TRD patients.

Changes in Plasma TPH2, GDNF, Trk-b, BDNF, and proBDNF in People Who Died by Suicide

Recent studies have shown that neuropeptides and neurotrophic factors may be involved in the pathophysiological mechanisms of suicide. However, the current research on this aspect is still insufficient. Our study aimed to explore the biological patterns of suicide deaths, including levels of BDNF, proBDNF, BDNF/proBDNF, Trk-b, GDNF, and TPH2. The researchers selected 25 normal control patients matched by age with 30 suicide deaths. We used enzyme-linked immunosorbent assays to detect the levels of BDNF, proBDNF, BDNF/proBDNF, Trk-b, GDNF, and TPH2 in the plasma of suicide and control subjects. proBDNF, BDNF/proBDNF, Trk-b, GDNF, and TPH2 levels are shown as the median (25th-75th percentile). BDNF levels are shown as the mean (standard error of the mean). (1) The levels of plasma TPH2 and proBDNF in people who died by suicide were significantly higher than those in the control group. (2) The plasma levels of GDNF and BDNF/proBDNF in the suicide group were obviously lower than those in the control group. (3) There was no significant difference in plasma BDNF or Trk-b concentrations between the suicide group and the control group.Plasma TPH2, GDNF, and proBDNF levels are related to suicide. Plasma neurotrophic factor markers may predict suicide risk.

Serum BDNF levels and state anxiety are associated with somatic symptoms in patients with panic disorder

Background

We aimed to explore the predictive role of serum BDNF and anxiety-related variables in changes in somatic symptoms post-escitalopram treatment in panic disorder (PD) patients.

Methods

Ninety PD patients and 99 healthy controls (HCs) were enrolled. PD patients received an 8-week escitalopram treatment. All patients were administered the Panic Disorder Severity Scale-Chinese Version (PDSS-CV) and State-Trait Anxiety Inventory (STAI) to assess panic and anxiety-related symptoms, respectively. Patient Health Questionnaire 15-item scale (PHQ-15) was performed to measure somatic symptoms, and the blood sample was collected to detect serum BDNF levels in all participants. We performed partial correlation analysis and multiple linear regression to explore correlates of PHQ-15 and predictors of PHQ-15 changes post-escitalopram treatment after controlling for age, gender, education levels (set as a dummy variable), the current duration, comorbid AP, and/or GAD.

Results

Compared to HCs, PD patients had lower serum BDNF levels and higher PHQ-15 scores that could be improved post-escitalopram treatment. Lower baseline STAI state (b = -0.07, p = 0.004), and PDSS-CV scores (b = -0.25, p = 0.007), but higher baseline serum BDNF levels (b = 0.35, p = 0.007) contributed to the prediction of PHQ-15 changes post-escitalopram treatment.

Conclusion

State anxiety, serum BDNF levels, and panic severity could predict changes in somatic symptoms post-escitalopram treatment, our results highlighted that serum BDNF could serve as a biological indicator for improving somatic symptoms in PD patients.

Serum BDNF levels are involved in the diagnosis and treatment response in patients with PD

BACKGROUND

The study aimed to explore whether brain-derived neurotrophic factor (BDNF) could be predictive for the diagnosis of panic disorder (PD) and to explore the association between serum BDNF levels and the treatment response to escitalopram in PD patients.

METHODS

Ninety PD patients and 99 healthy controls (HCs) were finally recruited. PD patients were treated only by escitalopram for 8 weeks. All patients were administered the Short-Form Health Survey-36 (SF-36), Hamilton Anxiety Rating Scale (HAMA-14), and State-Trait Anxiety Inventory (STAI) to assess life quality, anxiety symptoms and trait, respectively. Neuropsychological tests were assessed at baseline in all participants. Besides, peripheral venous blood was drawn from all participants for BDNF serum levels detection both at baseline and after 8 weeks of treatment.

RESULTS

In PD patients, the baseline serum BDNF levels were lower than HCs. The area under the ROC curve (AUC) of baseline serum BDNF levels predicting PD from HCs was 0.947 (94.9 % for sensitivity, 77.8 % for specificity). The baseline serum BDNF levels (beta = 0.276, p = 0.007), the current duration (beta = -0.301, p = 0.004), and trait anxiety (TAI) (beta = 0.201, p = 0.045) were predictors for reduction rates of HAMA-14 after 8 weeks' escitalopram treatment.

LIMITATIONS

A long-term observation and high homogeneity of sample may make the results more convincing.

CONCLUSION

This preliminary finding highlighted the value of serum BDNF levels for the diagnosis of PD. In addition, the higher baseline serum BDNF levels may predict the better escitalopram treatment response in PD patients.

The roles of extracellular vesicles in major depressive disorder

Major depressive disorder (MDD) is a serious mental disease characterized by depressed mood, loss of interest and suicidal ideation. Its rising prevalence has rendered MDD one of the largest contributors to the global disease burden. However, its pathophysiological mechanism is still unclear, and reliable biomarkers are lacking. Extracellular vesicles (EVs) are widely considered important mediators of intercellular communication, playing an important role in many physiological and pathological processes. Most preclinical studies focus on the related proteins and microRNAs in EVs, which can regulate energy metabolism, neurogenesis, neuro-inflammation and other pathophysiological processes in the development of MDD. The purpose of this review is to describe the current research progress of EVs in MDD and highlight their potential roles as biomarkers, therapeutic indicators and drug delivery carriers for the treatment of MDD.

Association between impaired glucose metabolism and long-term prognosis at the time of diagnosis of depression: Impaired glucose metabolism as a promising biomarker proposed through a machine-learning approach

BACKGROUND

Predicting the course of depression is necessary for personalized treatment. Impaired glucose metabolism (IGM) was introduced as a promising depression biomarker, but no consensus was made. This study aimed to predict IGM at the time of depression diagnosis and examine the relationship between long-term prognosis and predicted results.

METHODS

Clinical data were extracted from four electronic health records in South Korea. The study population included patients with depression, and the outcome was IGM within 1 year. One database was used to develop the model using three algorithms. External validation was performed using the best algorithm across the three databases. The area under the curve (AUC) was calculated to determine the model's performance. Kaplan-Meier and Cox survival analyses of the risk of hospitalization for depression as the long-term outcome were performed. A meta-analysis of the long-term outcome was performed across the four databases.

RESULTS

A prediction model was developed using the data of 3,668 people, with an AUC of 0.781 with least absolute shrinkage and selection operator (LASSO) logistic regression. In the external validation, the AUCs were 0.643, 0.610, and 0.515. Through the predicted results, survival analysis and meta-analysis were performed; the hazard ratios of risk of hospitalization for depression in patients predicted to have IGM was 1.20 (95% confidence interval [CI] 1.02-1.41, p = 0.027) at a 3-year follow-up.

CONCLUSIONS

We developed prediction models for IGM occurrence within a year. The predicted results were related to the long-term prognosis of depression, presenting as a promising IGM biomarker related to the prognosis of depression.