Biomarkers Of Depression Research Articles

Does urinary metabolite signature act as a biomarker of post-stroke depression?

BackgroundIt is difficult to conduct the precise diagnosis of post-stroke depression (PSD) in clinical practice due to the complex psychopathology of depressive disorder. Several studies showed that gas chromatography–mass spectrometry (GC-MS)-identified urinary metabolite biomarkers could significantly discriminate PSD from stroke survivors.MethodsA systematic review was performed for the keywords of “urinary metabolite” and “PSD” using Medline, Cochrane Library, Embase, Web of Science, PsycINFO, Wanfang, CNKI, CBM, and VIP database from inception to 31 March 2022.ResultsFour related studies were included in the review. Differential urinary metabolites including lactic acid, palmitic acid, azelaic acid, and tyrosine were identified in all the included studies. As a significant deviation in the metabolite biomarker panel, glyceric acid, azelaic acid, phenylalanine, palmitic acid, pseudouridine, and tyrosine were found in at least 2 included studies, which indicated good potential for the differentiation of PSD.ConclusionThe systematic review provided evidence that differential urinary metabolites analyzed by the GC-MS-based approach might be used as a biomarker for the diagnosis and prognosis of PSD.

Serum brain-derived neurotrophic factor and glial cell-derived neurotrophic factor in patients with first-episode depression at different ages

Objectives We investigated the differences in serum brain-derived neurotrophic factor (BDNF) and glial cell line–derived neurotrophic factor (GDNF) levels and clinical symptoms with first-episode depression at different ages. Methods Ninety patients (15–60 years old) diagnosed with first-episode depression were enrolled as the study group, and they were divided into early-onset, adult and late-onset groups. The age-matched control groups were healthy volunteers. Serum BDNF and GDNF concentrations were determined by enzyme-linked immunosorbent assay (ELISA). GraphPad Prism 9 was used for t tests, one-way ANOVAs, chi-square tests, and correlation analyses. p < 0.05 indicated significant differences. Results Serum BDNF and GDNF levels were lower in the whole study group and the three subgroups than in the healthy groups. Illness severity, anxiety and education were higher in the early-onset than late-onset patients. Serum BDNF levels were lower in the adult than late-onset patients. Serum BDNF levels were negatively correlated with patient CGI-SI scores. After the LSD test for multiple comparisons, the results were also significant. Conclusions Low serum BDNF and GDNF levels may be involved in the pathophysiology of first-episode depression, and there were differences in serum BDNF levels at different ages, verifying that serum BDNF and GDNF could serve as potential biomarkers of depression. KEY POINTS Depression is often conceptualised as a systemic illness with different biological mechanisms, but satisfactory explanations have not been provided thus far. The aim of our study was to investigate differences in serum BDNF and GDNF levels and their relationships with clinical symptoms in patients with first-episode depression at different ages. The potential of the neurotrophic factor hypothesis to advance the diagnosis and treatment of depression will be a very exciting new strategy for future research.

Osteocalcin levels decrease during the treatment of an acute depressive episode.

ObjectivesOsteocalcin is a protein secreted by osteoblasts with a versatile endocrine role. Several domains in which it plays a role—stress response, monoamine synthesis, and cognitive functioning—are implicated also in the pathophysiology of major depressive disorder. In search of possible objective biomarkers of depression, the aim of the study was to assess the relationship between osteocalcin and depressive symptoms during the treatment of depressive episode.MethodsThe study included female inpatients with at least moderate depressive episode. In these patients, depression severity was measured using the Montgomery-Åsberg Depression Rating Scale (MADRS), and osteocalcin levels were assessed before the stabilization of antidepressive treatment and after 6 weeks. Relationships between osteocalcin levels and symptoms were analyzed with mixed-effect and linear models, taking into account age, menopausal status, and body mass index.ResultsIn 11 out of 13 enrolled inpatients, osteocalcin levels decreased during the first 6 weeks of treatment; this decrease was significant according to the mixed-effects model (t = −2.345, p = 0.019). According to the linear model, this decrease was significantly associated with reduction in depressive symptom severity (t = 2.673, p = 0.028). Osteocalcin was not associated with initial depressive symptom severity, and initial osteocalcin levels did not predict response to treatment. Limitations of the study include low sample size and inclusion of both pre- and postmenopausal women of various ages.ConclusionsThis preliminary study suggests that osteocalcin may be a candidate biomarker of antidepressive treatment response and that this topic warrants further investigation.

A cohort study of adolescents with depression in China: tracking multidimensional outcomes and early biomarkers for intervention

BackgroundDepression in adolescents is recognised as a global public health concern, but little is known about the trajectory of its clinical symptoms and pathogenesis. Understanding the nature of adolescents with...

Prognostic Significance of Blood-Based Baseline Biomarkers in Treatment-Resistant Depression: A Literature Review of Available Studies on Treatment Response.

Major depressive disorder is a leading cause of disability worldwide and a major contributor to the overall global burden of disease. While there are several options for antidepressant treatment, only about 40–60% of patients respond to initial monotherapy, while 30–40% of patients may even show resistance to treatment. This article offers a narrative review of those studies evaluating the predictive properties of various blood-based baseline biomarkers regarding treatment responses to the pharmacological, stimulation, or behavioral treatment of patients with treatment-resistant depression (TRD). Our results show that overall, there is only a very limited number of studies assessing baseline peripheral biomarkers regarding treatment response in TRD. Although there is some evidence for the predictive significance of particular biomarkers (e.g., IL-6, CRP, BDNF), the majority of the results are either single-study reports or studies with conflicting results. This may contribute to the wide variety of treatment protocols and different TRD definition criteria, the small number of patients included, and the existence of different biological phenotypes of the disorder used within the various studies. Taken together, there does not yet appear to be any specific baseline peripheral biomarker with sufficient discriminative predictive validity that can be used in the routine clinical practice of TRD. The discovery of new biomarkers and the better clinical characterization of known biomarkers could support the better classification and staging of TRD, the development of personalized treatment algorithms with higher rates of remission and fewer side effects, and the development of new precision drugs for specific subgroups of patients.

Correlation of Ionized Magnesium with the Parameters of Oxidative Stress as Potential Biomarkers in Patients with Anxiety and Depression: A Pilot Study.

BackgroundMagnesium (Mg) is the second most abundant intracellular cation. Ionized Mg is the only active form of Mg. The concentration of ionized Mg could be a potentially novel biomarker for anxiety and depression.AimThe aim of this study was to assess the serum concentration of ionized Mg and its correlation with biomarkers of oxidative stress and inflammation in patients with anxiety and depression.MethodsIn this study included 93 respondents were divided into 3 groups: C (control group—18 respondents); A (patients with anxiety disorder, dissociative/conversion disorders and somatoform disorders—36 patients); D (patients with depression—39 patients). Clinical diagnosis was based on ICD-10 criteria. Blood samples were used for standard laboratory analysis, ionized Mg analysis, oxidative stress, and inflammatory parameters.ResultsStatistical significance was recorded between healthy volunteers and patients (anxiety/depression) in ionized Mg values. In anxious patients, malondialdehyde (MDA) had a positive correlation between the parameters of oxidative stress with ionized Mg. In depressive patients, MDA had a positive correlation, and glutathione peroxidase 1 (GPX1) a negative correlation with the concentration of ionized Mg.ConclusionIonized Mg and its correlation with parameters of oxidative stress could be potential biomarkers in anxious and depressive patients.

Voltammetric Approach for Characterizing the Biophysical and Chemical Functionality of Human Induced Pluripotent Stem Cell-Derived Serotonin Neurons.

Depression is quickly becoming one of the world's most pressing public health crises, and there is an urgent need for better diagnostics and therapeutics. Behavioral models in animals and humans have not adequately addressed the diagnosis and treatment of depression, and biomarkers of mental illnesses remain ill-defined. It has been very difficult to identify biomarkers of depression because of in vivo measurement challenges. While our group has made important strides in developing in vivo tools to measure such biomarkers (e.g., serotonin) in mice using voltammetry, these tools cannot be easily applied for depression diagnosis and drug screening in humans due to the inaccessibility of the human brain. In this work, we take a chemical approach, ex vivo, to introduce a human-derived system to investigate brain serotonin. We utilize human induced pluripotent stem cells differentiated into serotonin neurons and establish a new ex vivo model of real-time serotonin neurotransmission measurements. We show that evoked serotonin release responds to stimulation intensity and tryptophan preloading, and that serotonin release and reuptake kinetics resemble those found in vivo in rodents. Finally, after selective serotonin reuptake inhibitor (SSRI) exposure, we find dose-dependent internalization of the serotonin reuptake transporters (a signature of the in vivo response to SSRI). Our new human-derived chemical model has great potential to provide an ex vivo chemical platform as a translational tool for in vivo neuropsychopharmacology.

Blood Inflammatory Cytokines as Predictors of Depression in Patients With Glioma.

BackgroundDepression commonly develops as a comorbid disorder related to glioma, which affects the patients’ physical function and prognosis. Circulating inflammatory cytokines are potential predictors of depression in disparate cancers. However, less research has specifically investigated this aspect within the context of glioma.Study objectivesThe objective of this study was to investigate the occurrence of depression in patients with glioma and draw a comparison of the ability to predict it through diverse inflammatory cytokines.MethodsA total of 203 patients with stage I–IV glioma were enrolled in this study. Depression was evaluated according to the Hamilton Depression Scale, and the plasma inflammatory cytokines levels were simultaneously measured. We performed the receiver operating characteristic (ROC) analysis to confirm the abilities of identified inflammatory cytokines to predict depression.ResultsAmong the 203 patients with glioma, 135 (66.5%) showed obvious depressive symptoms. Proinflammatory cytokines, including interleukin (IL)-6 (area under the curve (AUC) = 0.76) and tumor necrosis factor (TNF)-α (AUC = 0.75), showed good performance in accurately predicting depression in patients with glioma. These inflammatory cytokines indicated great potential to be depression biomarkers regardless of the patients’ disparate treatment experience.ConclusionWith their relatively simple and time-saving measurement procedures, inflammatory cytokines should be seriously considered effective clinical screening and diagnostic tools, as well as potential biomarkers for depression in patients with glioma.

Association of FKBP5 gene methylation and adolescents’ sex with depressive symptoms outcomes: a nested case-control study among Chinese adolescents

IntroductionAltered DNA methylation in the FK506 binding protein 5 (FKBP5) gene has been shown to regulate stress response, which may serve as a biomarker of depression and a promising candidate for explaining sexual differences. However, there is no consistent conclusion so far.ObjectivesThe present study aimed to test the associations of FKBP5 DNA methylation with depressive symptoms and whether these associations were influenced by sex.MethodsA nested case-control study comprising 87 cases and 151 controls was conducted in South China from January 2019 and December 2019. Peripheral blood for DNA extraction and DNA methylation analysis of FKBP5 gene promoter was collected, and severity of depressive symptoms was assessed at baseline and after one year follow-up.ResultsCompared to healthy controls, lower methylation percentage of FKBP5-12 CpG 1 was observed in adolescents with depressive symptoms after adjusting covariates (case: 0.94 ± 2.00, control: 0.47 ± 0.92; F = 5.41, P = 0.021). In addition, hypomethylation of FKBP5 CpG sites was not an independent risk factor for depressive symptoms after adjustment for environmental stress factors (P &gt; 0.05). No significant sex differences were found in the association of FKBP5 gene methylation with depressive symptoms.ConclusionsLower levels of FKBP5 methylation were found in adolescents with depressive symptoms. Our study supported that the epigenetic factors did not act alone in the development of depressive symptoms. Taken together, these findings contribute to a better understanding of complex mechanisms of gene-environment interactions involved in depression.DisclosureNo significant relationships.

General Transcription Factor IIF Polypeptide 2: A Novel Therapeutic Target for Depression Identified Using an Integrated Bioinformatic Analysis.

Depression currently affects 4% of the world’s population; it is associated with disability in 11% of the global population. Moreover, there are limited resources to treat depression effectively. Therefore, we aimed to identify a promising novel therapeutic target for depression using bioinformatic analysis. The GSE54568, GSE54570, GSE87610, and GSE92538 gene expression data profiles were retrieved from the Gene Expression Omnibus (GEO) database. We prepared the four GEO profiles for differential analysis, protein–protein interaction (PPI) network construction, and weighted gene co-expression network analysis (WGCNA). Gene Ontology functional enrichment and Kyoto Encyclopedia of Genes and Genomes metabolic pathway analyses were conducted to determine the key functions of the corresponding genes. Additionally, we performed correlation analyses of the hub genes with transcription factors, immune genes, and N6-methyladenosine (m6A) genes to reveal the functional landscape of the core genes associated with depression. Compared with the control samples, the depression samples contained 110 differentially expressed genes (DEGs), which comprised 56 downregulated and 54 upregulated DEGs. Moreover, using the WGCNA and PPI clustering analysis, the blue module and cluster 1 were found to be significantly correlated with depression. GTF2F2 was the only common gene identified using the differential analysis and WGCNA; thus, it was used as the hub gene. According to the enrichment analyses, GTF2F2 was predominantly involved in the cell cycle and JAK-STAT, PI3K-Akt, and p53 signaling pathways. Furthermore, differential and correlation analyses revealed that 9 transcription factors, 12 immune genes, and 2 m6A genes were associated with GTF2F2 in depression samples. GTF2F2 may serve as a promising diagnostic biomarker and treatment target of depression, and this study provides a novel perspective and valuable information to explore the molecular mechanism of depression.

Functional MRI in major depressive disorder: A review of findings, limitations, and future prospects.

Objective diagnosis and prognosis in major depressive disorder (MDD) remains a challenge due to the absence of biomarkers based on physiological parameters or medical tests. Numerous studies have been conducted to identify functional magnetic resonance imaging‐based biomarkers of depression that either objectively differentiate patients with depression from healthy subjects, predict personalized treatment outcome, or characterize biological subtypes of depression. While there are some findings of consistent functional biomarkers, there is still lack of robust data acquisition and analysis methodology. According to current findings, primarily, the anterior cingulate cortex, prefrontal cortex, and default mode network play a crucial role in MDD. Yet, there are also less consistent results and the involvement of other regions or networks remains ambiguous. We further discuss image acquisition, processing, and analysis limitations that might underlie these inconsistencies. Finally, the current review aims to address and discuss possible remedies and future opportunities that could improve the search for consistent functional imaging biomarkers of depression. Novel acquisition techniques, such as multiband and multiecho imaging, and neural network‐based cleaning approaches can enhance the signal quality in limbic and frontal regions. More comprehensive analyses, such as directed or dynamic functional features or the identification of biological depression subtypes, can improve objective diagnosis or treatment outcome prediction and mitigate the heterogeneity of MDD. Overall, these improvements in functional MRI imaging techniques, processing, and analysis could advance the search for biomarkers and ultimately aid patients with MDD and their treatment course.

Differential malondialdehyde (MDA) detection in plasma samples of patients with major depressive disorder (MDD): A potential biomarker.

ObjectiveTo measure plasma levels of malondialdehyde (MDA), a marker of oxidative stress (OS), in patients with major depressive disorder (MDD) compared with healthy control (HC) subjects in order to determine if it is a possible biomarker of depression.MethodsThis prospective cross-sectional study enrolled patients with MDD and HC subjects. The plasma levels of MDA were measured using a commercially-available colorimetric assay.ResultsA total of 30 patients with MDD and 20 HC subjects with similar sex, age and body mass index distribution were enrolled in the study. Patients with MDD had significantly higher plasma levels of MDA than the HC subjects. Receiver operating characteristic curve analysis for plasma MDA levels in patients with MDD demonstrated an area under the curve of 0.9767.ConclusionThe findings of this current study provide further evidence of the role pathophysiological relevance of OS and MDA in MDD. This study provides the basis for the use of MDA as a biomarker for MDD.

Using digital health tools for the Remote Assessment of Treatment Prognosis in Depression (RAPID): a study protocol for a feasibility study

IntroductionDigital health tools such as smartphones and wearable devices could improve psychological treatment outcomes in depression through more accurate and comprehensive measures of patient behaviour. However, in this emerging field,...

Biomolecular Assessment and Assay of Kisspeptin, Oxytocin and Melatonin in Female Depressed Patients on Antidepressant Therapy: A Comparative Study

Depression, a common psychiatric disorder with a prevalence of 4.4%, a leading cause of disability and the fourth highest contributor to the global burden of diseases remains underdiagnosed. Biomarkers have been suggested to enable a better understanding of the variable responses to therapy observed in depression. Kisspeptin, oxytocin and melatonin have been implicated in the etiology of anxiety and neuropsychiatric disorders such as seasonal affective depression. This study aimed to compare the differences in the serum levels of oxytocin, melatonin, kisspeptin and their messenger RNAs between antidepressant naïve females (control group) and those who had received at least a four‐week course of antidepressant therapy (test group). The mean serum levels of oxytocin, melatonin and kisspeptin among the test subjects was were 3.18 ±.77 pg/mL, 41.8 ± 2.53 pg/mL, and 291.56 ±106.11 nmol/L, respectively; and 3.14 ±.8.1 pg/mL, 42.06 ±3.18 pg/mL, and 268.89 ± 98.92 nmol/L, respectively for the control group. The total mRNA with the test group was an average of 17.5 ± 18.64), while for the control group it was 11.5 ± 18.41). There were slight correlations between the clinical symptoms of the patients and their mRNA levels but no significant changes in the total mRNA levels of oxytocin and kisspeptin in individuals on antidepressant therapy. There was also no significant relationships in the mRNAs and the serum levels of oxytocin, melatonin and kisspeptin between the test and control groups. Results from this study suggest that kisspeptin, oxytocin and melatonin may not be suitable biomarker for depression but provides a platform for further research.

P256. ABCB1 Gene Variants and Antidepressant Response and Tolerability: A Systematic Review and Meta-Analysis Including Results From the CAN-BIND-1 Cohort

The p-glycoprotein efflux pump, encoded by the ABCB1 gene, has been shown to alter concentrations of various antidepressants in the brain. In this study, we investigated the association between selected ABCB1 single nucleotide polymorphisms (SNPs) and antidepressant treatment outcomes, including new and unpublished data from the Canadian Biomarker and Integration Network for Depression (CAN-BIND-1) cohort.

Vocal Acoustic Features as Potential Biomarkers for Identifying/Diagnosing Depression: A Cross-Sectional Study.

BackgroundAt present, there is no established biomarker for the diagnosis of depression. Meanwhile, studies show that acoustic features convey emotional information. Therefore, this study explored differences in acoustic characteristics between depressed patients and healthy individuals to investigate whether these characteristics can identify depression.MethodsParticipants included 71 patients diagnosed with depression from a regional hospital in Beijing, China, and 62 normal controls from within the greater community. We assessed the clinical symptoms of depression of all participants using the Hamilton Depression Scale (HAMD), Hamilton Anxiety Scale (HAMA), and Patient Health Questionnaire (PHQ-9), and recorded the voice of each participant as they read positive, neutral, and negative texts. OpenSMILE was used to analyze their voice acoustics and extract acoustic characteristics from the recordings.ResultsThere were significant differences between the depression and control groups in all acoustic characteristics (p < 0.05). Several mel-frequency cepstral coefficients (MFCCs), including MFCC2, MFCC3, MFCC8, and MFCC9, differed significantly between different emotion tasks; MFCC4 and MFCC7 correlated positively with PHQ-9 scores, and correlations were stable in all emotion tasks. The zero-crossing rate in positive emotion correlated positively with HAMA total score and HAMA somatic anxiety score (r = 0.31, r = 0.34, respectively), and MFCC9 of neutral emotion correlated negatively with HAMD anxiety/somatization scores (r = −0.34). Linear regression showed that the MFCC7-negative was predictive on the PHQ-9 score (β = 0.90, p = 0.01) and MFCC9-neutral was predictive on HAMD anxiety/somatization score (β = −0.45, p = 0.049). Logistic regression showed a superior discriminant effect, with a discrimination accuracy of 89.66%.ConclusionThe acoustic expression of emotion among patients with depression differs from that of normal controls. Some acoustic characteristics are related to the severity of depressive symptoms and may be objective biomarkers of depression. A systematic method of assessing vocal acoustic characteristics could provide an accurate and discreet means of screening for depression; this method may be used instead of—or in conjunction with—traditional screening methods, as it is not subject to the limitations associated with self-reported assessments wherein subjects may be inclined to provide socially acceptable responses rather than being truthful.

Effect of aerobic exercise as a treatment on type 2 diabetes mellitus with depression-like behavior zebrafish

BackgroundDepression is the most known complication of type 2 diabetes mellitus (T2DM). Aerobic exercise improves glycemic control in T2DM, although the underlying mechanisms of comorbid depression-like behaviors in T2DM have not yet been fully elucidated. Methods120 zebrafish were randomly assigned to four groups: Control, T2DM, T2DM + metformin, and T2DM + aerobic exercise. Then, all animals except the control group were fed with high glucose fairy shrimp (~40 g/kg/day) and exposed reserpine (40 μg/ml for 20 min) for 10 days. Here, behavioral tests were used for model verification. Following the verification, all groups were treated as before. Additionally, the T2DM + metformin group received metformin (~10.6 mg/kg/day) at the same time, while the T2DM + aerobic exercise group received aerobic exercise 30 min/day. Finally, blood glucose and behavioral tests, as well as protein and molecular levels were determined at Day 11 and 12. ResultsAerobic exercise alleviated depressive-like behavior and enhanced the levels of antidepressant biomarkers (NE, 5-HIAA) in zebrafish after 10 consecutive days of exercise. Additionally, 10 consecutive days of aerobic exercise decreased the levels of inflammatory biomarkers (IFN-γ, IL-1, IL-4) and depressive biomarkers (cortisol). Meanwhile, it also aided in the reduction of CD11b, IL-6, IL-6R, and caspase-3 expression to combat the neuroinflammation induced by T2DM, mediated the BDNF-TrkB pathway, and increased Bcl-2/Bax levels. ConclusionGiven the remarkable similarity in neurochemistry between humans and zebrafish, this study supports the effectiveness of aerobic exercise as clinical guidance in preventing and treating T2DM complicated with depression.

Characteristics of single-channel electroencephalogram in depression during conversation with noise reduction technology

BackgroundPrevious studies have attempted to characterize depression using electroencephalography (EEG), but results have been inconsistent. New noise reduction technology allows EEG acquisition during conversation.MethodsWe recorded EEG from 40 patients with depression as they engaged in conversation using a single-channel EEG device while conducting real-time noise reduction and compared them to those of 40 healthy subjects. Differences in EEG between patients and controls, as well as differences in patients’ depression severity, were examined using the ratio of the power spectrum at each frequency. In addition, the effects of medications were examined in a similar way.ResultsIn comparing healthy controls and depression patients, significant power spectrum differences were observed at 3 Hz, 4 Hz, and 10 Hz and higher frequencies. In the patient group, differences in the power spectrum were observed between asymptomatic patients and healthy individuals, and between patients of each respective severity level and healthy individuals. In addition, significant differences were observed at multiple frequencies when comparing patients who did and did not take antidepressants, antipsychotics, and/or benzodiazepines. However, the power spectra still remained significantly different between non-medicated patients and healthy individuals.LimitationsThe small sample size may have caused Type II error. Patients’ demographic characteristics varied. Moreover, most patients were taking various medications, and cannot be compared to the non-medicated control group.ConclusionA study with a larger sample size should be conducted to gauge reproducibility, but the methods used in this study could be useful in clinical practice as a biomarker of depression.

Comparison of cognitive impairments with lipid profiles and inflammatory biomarkers in unipolar and bipolar depression

Cognitive impairments is one of important accompanied symptom in Unipolar depressive disorder (UD) and bipolar disorder (BD) that was hard to distinguish, as their diagnosis is based on behavioural observations and subjective symptoms. In this study, we could highlight the difference of cognitive ability in UD and BD by testing lipid profiles and inflammatory biomarkers in major depressive episodes (MDE). 207 subjects (96 unipolar and 111 bipolar depressed patients) were included in this study. We applied Montreal Cognitive Assessment (MoCA) to test cognitive ability. The 24-item Hamilton Depression Rating Scale was used for assessment at the beginning of treatment. A series of clinical variables and lipid profiles were collected from clinic record. We detected pro-inflammatory biomarkers Interleukin-1β (IL-1β), Interleukin-6 (IL-6), C-reaction protein (CRP) levels and brain-derived neurotrophic factor (BDNF) by enzyme linked immunosorbent assay. From the results, cognitive impairments were more popular in BD than UD, most obviously in severe cognitive impairments (MoCA score<23). And UD showed better cognitive ability than BD in MoCA, particularly in language domain. Compared lipid profiles like total cholesterol (TC), triglycerides (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), Apolipoprotein B (ApoB) and lipoprotein α (Lpα), we found that ApoB was higher in BD than UD that maybe a risk factor in cognition. There was no obviously difference in TC, TG, HDL-C, LDL-C, ApoA1, or Lpα. Also, we found CRP level in BD was higher than UD, and showed no significant difference in IL-1β and IL-6 levels. Furthermore, BDNF level which was neurotrophic biomarker for cognition and mood was significantly declined in BD compared with UD. Correlation analysis showed that ApoB and CRP was negative closed associated with MoCA scores. And BDNF level was positive related with cognitive ability in MDE patients. From our results mentioned that quantitative lipid profiles and inflammatory biomarkers analysis might help to objectively identify between these disorders and up our understanding of their pathophysiology. And ApoB, CRP and BDNF could be as potential peripheral candidates in cognitive evaluation to distinguish UD and BD.

Altered levels of neurobiological biomarkers at the interface of depression and gestational diabetes mellitus in Asian Indian women

AimGestational diabetes mellitus (GDM) might predispose the mothers to depression. Studies have reported the role of biomarkers either in GDM or depression, but very few have examined them in GDM with depression. The present study profiled the circulating levels of brain-derived neurotrophic factor (BDNF), Beta Endorphin (BE) and nesfatin-1 in women with GDM (with and without depression). Methods160 pregnant women at 24–28 weeks of pregnancy (NGT/GDM with & without depression, n = 40 each) were randomly selected from the ongoing STRiDE (STratification of Risk of Diabetes in Early pregnancy) study. Depression score was derived using PHQ-9 questionnaire and ELISA was used to quantify the biomarkers. ResultsCirculatory levels of BDNF, BE and nesfatin-1 were lower in GDM women with or without depression compared to NGT without depression, however, nesfatin-1 levels were higher in NGT with depression. Notably, GDM with depression had the lowest levels of BDNF and BE. Both BDNF and BE levels were negatively correlated with depression, 1 h and 2 h plasma glucose. Regression analysis confirmed that each standard deviation decreases in BDNF and BE were independently associated with higher odds of GDM with or without depression even after adjusting for potential confounders. ConclusionOur study has identified altered levels of a panel of neurobiological biomarkers (BDNF/BE/nesfatin-1) in those with combined GDM and depression. BDNF/BE could be potential biomarkers to assess the higher risk of coexisting depression and GDM.