Depression patient-derived cortical neurons reveal potential biomarkers for antidepressant response.
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ABSTRACT:
SUBMITTER: Avior Y
PROVIDER: S-EPMC8016835 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Accumulating evidence suggests that neuroinflammation is involved in bipolar disorder (BD) pathogenesis. The tumor necrosis factor-alpha (TNF-?) antagonist infliximab was recently reported to improve depressive symptoms in a subpopulation of individuals with BD and history of childhood maltreatment. To explore the mechanistic mediators of infliximab's effects, we investigated its engagement with biomarkers of cellular response to inflammation derived from plasma extracellular vesicles enriched for neuronal origin (NEVs). We hypothesized that infliximab, compared to placebo, would decrease TNF-? receptors (TNFRs) and nuclear factor-kappa B (NF-?B) pathway signaling biomarkers, and that history of childhood abuse would moderate infliximab's effects. We immunocaptured NEVs from plasma samples collected at baseline and at weeks 2, 6, and 12 (endpoint) from 55 participants of this clinical trial and measured NEV biomarkers using immunoassays. A subset of participants (n = 27) also underwent whole-brain magnetic resonance imaging at baseline and endpoint. Childhood physical abuse moderated treatment by time interactions for TNFR1 (?2 = 9.275, p = 0.026), NF-?B (?2 = 13.825, p = 0.003), and inhibitor of NF-?B (I?B?)? (?2 = 7.990, p = 0.046), indicating that higher levels of physical abuse were associated with larger biomarker decreases over time. Moreover, the antidepressant response to infliximab was moderated by TNFR1 (?2 = 7.997, p = 0.046). In infliximab-treated participants, reductions in TNFR1 levels were associated with improvement of depressive symptoms, an effect not detected in the placebo group. Conversely, reductions in TNFR1 levels were associated with increased global cortical thickness in infliximab- (r = -0.581, p = 0.029), but not placebo-treated, patients (r = 0.196, p = 0.501). In conclusion, we report that NEVs revealed that infliximab engaged the TNFR/NF-?B neuro-inflammatory pathway in individuals with BD, in a childhood trauma-dependent manner, which was associated with clinical response and brain structural changes.
| S-EPMC7226726 | biostudies-literature
Project description:This SuperSeries is composed of the following subset Series: GSE35751: Comparative analysis of S100a10-expressing cortical pyramidal cells and whole cortex GSE35758: Comparative analysis of S100a10 and Glt25d2 cortical pyramidal cells GSE35761: Effect of fluoxetine treatment on translational profiles of S100a10 cortical pyramidal cells GSE35763: Effect of fluoxetine treatment on translational profiles of Glt25d2 cortical pyramidal cells GSE35765: Effect of fluoxetine treatment on translational profiles of S100a10 cortical pyramidal cells in p11 KOs Refer to individual Series
2012-05-31 | E-GEOD-35766 | biostudies-arrayexpress
Project description:BACKGROUND:In recent years, we have accomplished a deeper understanding about the pathophysiology of major depressive disorder (MDD). Nevertheless, this improved comprehension has not translated to improved treatment outcome, as identification of specific biologic markers of disease may still be crucial to facilitate a more rapid, successful treatment. Ongoing research explores the importance of screening biomarkers using neuroimaging, neurophysiology, genomics, proteomics, and metabolomics measures. RESULTS:In the present review, we highlight the biomarkers that are differentially expressed in MDD and treatment response and place a particular emphasis on the most recent progress in advancing technology which will continue the search for blood-based biomarkers. LIMITATIONS:Due to space constraints, we are unable to detail all biomarker platforms, such as neurophysiological and neuroimaging markers, although their contributions are certainly applicable to a biomarker review and valuable to the field. CONCLUSIONS:Although the search for reliable biomarkers of depression and/or treatment outcome is ongoing, the rapidly-expanding field of research along with promising new technologies may provide the foundation for identifying key factors which will ultimately help direct patients toward a quicker and more effective treatment for MDD.
| S-EPMC5815949 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2012-06-01 | GSE35766 | GEO
Project description:Our understanding of current treatments for depression, and the development of more specific therapies, is limited by the complexity of the circuits controlling mood and the distributed actions of antidepressants. Although the therapeutic efficacy of serotonin-specific reuptake inhibitors (SSRIs) is correlated with increases in cortical activity, the cell types crucial for their action remain unknown. Here we employ bacTRAP translational profiling to show that layer 5 corticostriatal pyramidal cells expressing p11 (S100a10) are strongly and specifically responsive to chronic antidepressant treatment. This response requires p11 and includes the specific induction of Htr4 expression. Cortex-specific deletion of p11 abolishes behavioral responses to SSRIs, but does not lead to increased depression-like behaviors. Our data identify corticostriatal projection neurons as critical for the response to antidepressants, and suggest that the regulation of serotonergic tone in this single cell type plays a pivotal role in antidepressant therapy.
| S-EPMC3397430 | biostudies-literature
Project description:Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD.CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response.From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research.ClinicalTrials.gov identifier NCT01655706 . Registered July 27, 2012.
| S-EPMC4833905 | biostudies-literature
Project description:In the wake of recent advances in scientific research, personalized medicine using deep learning techniques represents a new paradigm. In this work, our goal was to establish deep learning models which distinguish responders from non-responders, and also to predict possible antidepressant treatment outcomes in major depressive disorder (MDD). To uncover relationships between the responsiveness of antidepressant treatment and biomarkers, we developed a deep learning prediction approach resulting from the analysis of genetic and clinical factors such as single nucleotide polymorphisms (SNPs), age, sex, baseline Hamilton Rating Scale for Depression score, depressive episodes, marital status, and suicide attempt status of MDD patients. The cohort consisted of 455 patients who were treated with selective serotonin reuptake inhibitors (treatment-response rate = 61.0%; remission rate = 33.0%). By using the SNP dataset that was original to a genome-wide association study, we selected 10 SNPs (including ABCA13 rs4917029, BNIP3 rs9419139, CACNA1E rs704329, EXOC4 rs6978272, GRIN2B rs7954376, LHFPL3 rs4352778, NELL1 rs2139423, NUAK1 rs2956406, PREX1 rs4810894, and SLIT3 rs139863958) which were associated with antidepressant treatment response. Furthermore, we pinpointed 10 SNPs (including ARNTL rs11022778, CAMK1D rs2724812, GABRB3 rs12904459, GRM8 rs35864549, NAALADL2 rs9878985, NCALD rs483986, PLA2G4A rs12046378, PROK2 rs73103153, RBFOX1 rs17134927, and ZNF536 rs77554113) in relation to remission. Then, we employed multilayer feedforward neural networks (MFNNs) containing 1-3 hidden layers and compared MFNN models with logistic regression models. Our analysis results revealed that the MFNN model with 2 hidden layers (area under the receiver operating characteristic curve (AUC) = 0.8228 ± 0.0571; sensitivity = 0.7546 ± 0.0619; specificity = 0.6922 ± 0.0765) performed maximally among predictive models to infer the complex relationship between antidepressant treatment response and biomarkers. In addition, the MFNN model with 3 hidden layers (AUC = 0.8060 ± 0.0722; sensitivity = 0.7732 ± 0.0583; specificity = 0.6623 ± 0.0853) achieved best among predictive models to predict remission. Our study indicates that the deep MFNN framework may provide a suitable method to establish a tool for distinguishing treatment responders from non-responders prior to antidepressant therapy.
| S-EPMC6043864 | biostudies-literature
Project description:The tumor necrosis factor (TNF) antagonist infliximab was previously found to reduce depressive symptoms in patients with treatment-resistant major depression (TRD) who exhibited high baseline inflammation, as reflected by plasma C-reactive protein (CRP) >5?mg/L. Further predictors of antidepressant response to infliximab included differential expression of peripheral blood gene transcripts that were related not only to inflammation but also to glucose and lipid metabolism. To determine whether plasma biomarkers of glucose and lipid metabolism were similarly associated with antidepressant response to infliximab and with relevant gene transcripts, we measured concentrations of glucose, insulin, and protein hormones that regulate glucose homeostasis and metabolism (leptin, resistin, and adiponectin), as well as cholesterols, triglycerides, and non-esterified fatty acids (NEFA), in medically-stable TRD outpatients at baseline and 2 weeks after the first infusion of infliximab (n?=?26) or placebo (n?=?26). Treatment response was defined as 50% reduction in depressive symptoms at any point during the 12-week trial. We found that baseline cholesterol (total, low-density lipoprotein [LDL], and non-high-density lipoprotein [non-HDL]), triglycerides and NEFA were elevated in patients who exhibited an antidepressant response to infliximab (all p?<?0.05) but not placebo (all p?>?0.299). HDL and non-HDL cholesterol concentrations also correlated with two lipid-related gene transcripts that were predictive of antidepressant response (r?=?0.33 to 0.39, p?<?0.05). Although not associated with response to infliximab, resistin correlated with numerous glucose-related transcripts (r?=?-0.32 to 0.37, p?<?0.05) and was higher at 2 weeks post-infusion in patients treated with infliximab compared to placebo (p?=?0.028). Concentrations of cholesterol (total, LDL, HDL, non-HDL) were also lower at 2 weeks in patients treated with infliximab compared to placebo, but only in those patients with CRP?>5?mg/L at baseline (all p?<?0.05). These results are consistent with previous work showing that high inflammation in patients with depression is associated with metabolic alterations, which together predict response to both traditional and experimental antidepressant therapies. Additionally, our findings suggest a causal relationship between increased inflammation and high cholesterol in depression, as a single infusion of infliximab reduced cholesterol in TRD patients with high CRP compared to placebo.
| S-EPMC6214671 | biostudies-literature
Project description:Genetic variation at the FKBP5 locus has been reported to affect clinical outcomes in patients treated with antidepressant medications in several studies. However, other reports have not confirmed this association. FKBP5 may regulate the sensitivity of the hypothalamic-pituitary-adrenal axis. We tested two FKBP5 single nucleotide polymorphisms (rs1360780 and rs3800373) in a sample of 246 geriatric patients treated for 8 weeks in a double-blind randomized comparison trial of paroxetine and mirtazapine. These two polymorphisms had previously been reported to predict efficacy in depressed patients treated with selective serotonin reuptake inhibitors such as paroxetine, and those treated with mirtazapine, an agent with both serotonergic and noradrenergic actions. However, we found no significant associations between these FKBP5 genetic variants and clinical outcomes. Neither mean Hamilton Depression Rating Scale scores nor time to remission or response were predicted by FKBP5 genetic variation. These results suggest that FKBP5 is unlikely to play a major role in determining antidepressant treatment outcomes in geriatric patients.
| S-EPMC2897151 | biostudies-literature
Project description:Familial Alzheimer's disease (fAD) mutations alter amyloid precursor protein (APP) cleavage by γ-secretase, increasing the proportion of longer amyloidogenic amyloid-β (Aβ) peptides. Using five control induced pluripotent stem cell (iPSC) lines and seven iPSC lines generated from fAD patients, we investigated the effects of mutations on the Aβ secretome in human neurons generated in 2D and 3D. We also analysed matched CSF, post-mortem brain tissue, and iPSCs from the same participant with the APP V717I mutation. All fAD mutation lines demonstrated an increased Aβ42:40 ratio relative to controls, yet displayed varied signatures for Aβ43, Aβ38, and short Aβ fragments. We propose four qualitatively distinct mechanisms behind raised Aβ42:40. (1) APP V717I mutations alter γ-secretase cleavage site preference. Whereas, distinct presenilin 1 (PSEN1) mutations lead to either (2) reduced γ-secretase activity, (3) altered protein stability or (4) reduced PSEN1 maturation, all culminating in reduced γ-secretase carboxypeptidase-like activity. These data support Aβ mechanistic tenets in a human physiological model and substantiate iPSC-neurons for modelling fAD.
| S-EPMC7577860 | biostudies-literature