Phosphodiesterase genes are associated with susceptibility to major depression and antidepressant treatment response.
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ABSTRACT:
SUBMITTER: Wong ML
PROVIDER: S-EPMC1581426 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:There are clinical parallels between the nature and course of depressive symptoms in major depressive disorder (MDD) and those of inflammatory disorders. However, the characterization of a possible immune system dysregulation in MDD has been challenging. Emerging data support the role of T-cell dysfunction. Here we report the association of MDD and antidepressant response to genes important in the modulation of the hypothalamic-pituitary-adrenal axis and immune functions in Mexican Americans with major depression. Specifically, single nucleotide polymorphisms (SNPs) in two genes critical for T-cell function are associated with susceptibility to MDD: PSMB4 (proteasome beta4 subunit), important for antigen processing, and TBX21 (T bet), critical for differentiation. Our analyses revealed a significant combined allele dose-effect: individuals who had one, two and three risk alleles were 2.3, 3.2 and 9.8 times more likely to have the diagnosis of MDD, respectively. We found associations of several SNPs and antidepressant response; those genes support the role of T cell (CD3E, PRKCH, PSMD9 and STAT3) and hypothalamic-pituitary-adrenal axis (UCN3) functions in treatment response. We also describe in MDD increased levels of CXCL10/IP-10, which decreased in response to antidepressants. This further suggests predominance of type 1 T-cell activity in MDD. T-cell function variations that we describe here may account for 47.8% of the attributable risk in Mexican Americans with moderate MDD. Immune function genes are highly variable; therefore, different genes might be implicated in distinct population groups.
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Project description:Major depressive disorder (MDD) is a complex and multifactorial psychiatric disorder that causes serious health, social, and economic concerns worldwide. The main treatment of the symptoms is through antidepressant (AD) drugs. However, not all patients respond properly to these drugs. Omic sciences are widely used to analyze not only biomarkers for the AD response but also their molecular mechanism. In this review, we aimed to focus on omics data to better understand the molecular mechanisms involving AD effects on MDD. We consistently found, from preclinical to clinical data, that glutamatergic transmission, immune/inflammatory processes, energy metabolism, oxidative stress, and lipid metabolism were associated with traditional and potential new ADs. Despite efforts of studies investigating biomarkers of response to ADs, which could contribute to personalized treatment, there is no biomarker panel available for clinical application. From clinical genomic studies, we found that the main findings contribute to the development of pharmacogenomic tests for AD efficacy for each patient. Several studies pointed at DRD2, PXDNL, CACNA1E, and CACNA2D1 genes as potential targets for MDD treatment and the efficacy and rapid-antidepressant effect of ketamine. Finally, more in-depth studies of the molecular targets pointed here are needed to determine the clinical relevance and provide further evidence for precision MDD treatment.
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Project description:The Sequenced Treatment Alternatives to Relieve Depression (STAR*D) Study revealed poorer antidepressant treatment response among black compared with white participants. This racial disparity persisted even after socioeconomic and baseline clinical factors were taken into account. Some studies have suggested genetic contributions to this disparity, but none have attempted to disentangle race and genetic ancestry. Here we used genome-wide single-nucleotide polymorphism (SNP) data to examine independent contributions of race and genetic ancestry to citalopram response. Secondary data analyses included 1877 STAR*D participants who completed an average of 10 weeks of citalopram treatment and provided DNA samples. Participants reported their race as White (n=1464), black (n=299) or other/mixed (n=114). Genetic ancestry was estimated by multidimensional scaling (MDS) analyses of about 500?000 SNPs. Ancestry proportions were estimated by STRUCTURE. Structural equation modeling was used to examine the direct and indirect effects of observed and latent predictors of response, defined as change in the Quick Inventory of Depressive Symptomatology (QIDS) score from baseline to exit. Socioeconomic and baseline clinical factors, race, and anxiety significantly predicted response, as previously reported. However, direct effects of race disappeared in all models that included genetic ancestry. Genetic African ancestry predicted lower treatment response in all models. Although socioeconomic and baseline clinical factors drive racial differences in antidepressant response, genetic ancestry, rather than self-reported race, explains a significant fraction of the residual differences. Larger samples would be needed to identify the specific genetic mechanisms that may be involved, but these findings underscore the importance of including more African-American patients in drug trials.
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Project description:Background:Recent emergence of long noncoding RNAs in regulating gene expression and thereby modulating physiological functions in brain has manifested their possible role in psychiatric disorders. In this study, the roles of long noncoding RNAs in susceptibility and resiliency to develop stress-induced depression and their response to antidepressant treatment were examined. Methods:Microarray-based transcriptome-wide changes in long noncoding RNAs were determined in hippocampus of male Holtzman rats who showed susceptibility (learned helplessness) or resiliency (nonlearned helplessness) to develop depression. Changes in long noncoding RNA expression were also ascertained after subchronic administration of fluoxetine to learned helplessness rats. Bioinformatic and target prediction analyses (cis- and trans-acting) and qPCR-based assays were performed to decipher the functional role of altered long noncoding RNAs. Results:Group-wise comparison showed an overrepresented class of long noncoding RNAs that were uniquely associated with nonlearned helplessness or learned helplessness behavior. Chromosomal mapping within the 5-kbp flank region of the top 20 dysregulated long noncoding RNAs in the learned helplessness group showed several target genes that were regulated through cis- or trans-actions, including Zbtb20 and Zfp385b from zinc finger binding protein family. Genomic context of differentially expressed long noncoding RNAs showed an overall blunted response in the learned helplessness group regardless of the long noncoding RNA classes analyzed. Gene ontology exhibited the functional clustering for anatomical structure development, cellular architecture modulation, protein metabolism, and cellular communications. Fluoxetine treatment reversed learned helplessness-induced changes in many long noncoding RNAs and target genes. Conclusions:The involvement of specific classes of long noncoding RNAs with distinctive roles in modulating target gene expression could confer the role of long noncoding RNAs in resiliency or susceptibility to develop depression with a reciprocal response to antidepressant treatment.
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Project description:The N-methyl-D-aspartate (NMDA) glutamate receptor antagonist ketamine has demonstrated rapid antidepressant effects in patients with treatment-resistant depression (TRD). Despite the promise of a novel and urgently needed treatment for refractory depression, concerns regarding potential adverse neurocognitive effects of ketamine remain.Although extensive research has been conducted in healthy volunteers, there is a paucity of studies examining the neurocognitive effects of ketamine in depressed patients. Therefore, the aims of the current study were to characterize the relationship between baseline neurocognition and antidepressant response to ketamine, measure the acute impact of ketamine on neurocognition, and investigate the relationship between acute neurocognitive effects of ketamine and antidepressant response.Neurocognitive functioning was assessed in 25 patients with TRD using a comprehensive battery: estimated premorbid intelligence quotient (IQ), current IQ, and tests from the MATRICS Consensus Cognitive Battery (MCCB). A subset of the MCCB was repeated immediately following a 40-min intravenous infusion of ketamine (0.5 mg/kg).Patients who responded to ketamine 24 h following treatment had poorer baseline neurocognitive performance relative to nonresponders and, in particular, slower processing speed (F?=?8.42; df?=?23; p?=?0.008). Ketamine was associated with selective impairments in memory recall, and the degree of cognitive change carried negative prognostic significance (e.g., negative cognitive effects immediately after ketamine predicted lower response rate at 24 h; Fisher's exact test two-sided p?=?0.027).Taken together, our findings suggest a potential baseline neurocognitive predictor of ketamine response and an inverse relationship between the cognitive effects of ketamine and antidepressant efficacy.
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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.
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Project description:Antidepressants are widely prescribed, but their efficacy relative to placebo is modest, in part because the clinical diagnosis of major depression encompasses biologically heterogeneous conditions. Here, we sought to identify a neurobiological signature of response to antidepressant treatment as compared to placebo. We designed a latent-space machine-learning algorithm tailored for resting-state electroencephalography (EEG) and applied it to data from the largest imaging-coupled, placebo-controlled antidepressant study (n?=?309). Symptom improvement was robustly predicted in a manner both specific for the antidepressant sertraline (versus placebo) and generalizable across different study sites and EEG equipment. This sertraline-predictive EEG signature generalized to two depression samples, wherein it reflected general antidepressant medication responsivity and related differentially to a repetitive transcranial magnetic stimulation treatment outcome. Furthermore, we found that the sertraline resting-state EEG signature indexed prefrontal neural responsivity, as measured by concurrent transcranial magnetic stimulation and EEG. Our findings advance the neurobiological understanding of antidepressant treatment through an EEG-tailored computational model and provide a clinical avenue for personalized treatment of depression.
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Project description:BackgroundClinical evidence that ketamine, a nonselective N-methyl-D-aspartate receptor (NMDAR) antagonist, has therapeutic effects within hours in people suffering from depression suggests that modulating glutamatergic neurotransmission is a fundamental step in alleviating the debilitating symptoms of mood disorders. Acutely, ketamine increases extracellular glutamate levels, neuronal excitability, and spontaneous γ oscillations, but it is unknown whether these effects are key to the mechanism of antidepressant action of ketamine.MethodsTwenty drug-free major depressive disorder patients received a single, open-label intravenous infusion of ketamine hydrochloride (.5 mg/kg). Magnetoencephalographic recordings were made approximately 3 days before and approximately 6.5 hours after the infusion, whereas patients passively received tactile stimulation to the right and left index fingers and also while they rested (eyes-closed). Antidepressant response was assessed by percentage change in Montgomery-Åsberg Depression Rating Scale scores.ResultsPatients with robust improvements in depressive symptoms 230 min after infusion (responders) exhibited increased cortical excitability within this antidepressant response window. Specifically, we found that stimulus-evoked somatosensory cortical responses increase after infusion, relative to pretreatment responses in responders but not in treatment nonresponders. Spontaneous somatosensory cortical γ-band activity during rest did not change within the same timeframe after ketamine in either responders or nonresponders.ConclusionsThese findings suggest NMDAR antagonism does not lead directly to increased cortical excitability hours later and thus might not be sufficient for therapeutic effects of ketamine to take hold. Rather, increased cortical excitability as depressive symptoms improve is consistent with the hypothesis that enhanced non-NMDAR-mediated glutamatergic neurotransmission via synaptic potentiation is central to the antidepressant effect of ketamine.
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Project description:Selective serotonin reuptake inhibitor (SSRI) use during pregnancy incurs a low absolute risk for major malformations; however, other adverse outcomes have been reported. Major depression also affects reproductive outcomes. This study examined whether 1) minor physical anomalies, 2) maternal weight gain and infant birth weight, 3) preterm birth, and 4) neonatal adaptation are affected by SSRI or depression exposure.This prospective observational investigation included maternal assessments at 20, 30, and 36 weeks of gestation. Neonatal outcomes were obtained by blinded review of delivery records and infant examinations. Pregnant women (N=238) were categorized into three mutually exclusive exposure groups: 1) no SSRI, no depression (N=131); 2) SSRI exposure (N=71), either continuous (N=48) or partial (N=23); and 3) major depressive disorder (N=36), either continuous (N=14) or partial (N=22). The mean depressive symptom level of the group with continuous depression and no SSRI exposure was significantly greater than for all other groups, demonstrating the expected treatment effect of SSRIs. Main outcomes were minor physical anomalies, maternal weight gain, infant birth weight, pregnancy duration, and neonatal characteristics.Infants exposed to either SSRIs or depression continuously across gestation were more likely to be born preterm than infants with partial or no exposure. Neither SSRI nor depression exposure increased risk for minor physical anomalies or reduced maternal weight gain. Mean infant birth weights were equivalent. Other neonatal outcomes were similar, except 5-minute Apgar scores.For depressed pregnant women, both continuous SSRI exposure and continuous untreated depression were associated with preterm birth rates exceeding 20%.
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