BDNF and CREB1 genetic variants interact to affect antidepressant treatment outcomes in geriatric depression

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.

Polymorphisms of COMT and CREB1 are associated with treatment-resistant depression in a Chinese Han population

Genetic factors play a crucial role for the pathophysiology of treatment-resistant depression (TRD). It has been established that Catechol-O-methyltransferase (COMT) and cyclic amp-response element-binding protein (CREB) are associated with antidepressant response. The aim of this study was to explore the association between single nucleotide polymorphisms (SNPs) in COMT and CREB1 genes and TRD in a Chinese population. We recruited 181 patients with major depressive disorder (MDD) and 80 healthy controls, including 81 TRD patients. Depressive symptoms were assessed with the Hamilton Depression Rating Scale-17 (HDRS). Genotyping was performed using mass spectrometry. Genetic analyses were conducted by PLINK Software. The distribution of COMT SNP rs4818 allele and genotypes were significantly different between TRD and controls. Statistical differences in allele frequencies were observed between TRD and non-TRD groups, including rs11904814 and rs6740584 in CREB1 gene, rs4680 and rs4818 in COMT gene. There were differences in the distribution of HDRS total scores among different phenotypes of CREB1 rs11904814, CREB1 rs6740584, COMT rs4680 and rs4818. Gene-gene interaction effect of COMT-CREB1 (rs4680 × rs6740584) revealed significant epistasis in TRD. There findings indicate that COMT and CREB1 polymorphisms influence the risk of TRD and affect the severity of depressive symptoms of MDD.

Neurobiological effects of phospholipids in vitro: Relevance to stress-related disorders

Nutrition is a crucial component for maintenance of brain function and mental health. Accumulating evidence suggests that certain molecular compounds derived from diet can exert neuroprotective effects against chronic stress, and moreover improve important neuronal processes vulnerable to the stress response, such as plasticity and neurogenesis. Phospholipids are naturally occurring amphipathic molecules with promising potential to promote brain health. However, it is unclear whether phospholipids are able to modulate neuronal function directly under a stress-related context. In this study, we investigate the neuroprotective effects of phosphatidylcholine (PC), lysophosphatidylcholine (LPC), phosphatidylserine (PS), phosphatidylethanolamine (PE), phosphatidylinositol (PI), phosphatidylglycerol (PG), phosphatidic acid (PA), sphingomyelin (SM) and cardiolipin (CL) against corticosterone (CORT)-induced cytotoxicity in primary cultured rat cortical neurons. In addition, we examine their capacity to modulate proliferation and differentiation of hippocampal neural progenitor cells (NPCs).

We show that PS, PG and PE can reverse CORT-induced cytotoxicity and neuronal depletion in cortical cells. On the other hand, phospholipid exposure was unable to prevent the decrease of Bdnf expression produced by CORT. Interestingly, PS was able to increase hippocampal NPCs neurosphere size, and PE elicited a significant increase in astrocytic differentiation in hippocampal NPCs. Together, these results indicate that specific phospholipids protect cortical cells against CORT-induced cytotoxicity and improve proliferation and astrocytic differentiation in hippocampal NPCs, suggesting potential implications on neurodevelopmental and neuroprotective pathways relevant for stress-related disorders.

NRG1, PIP4K2A, and HTR2C as Potential Candidate Biomarker Genes for Several Clinical Subphenotypes of Depression and Bipolar Disorder

GSK3B, BDNF, NGF, NRG1, HTR2C, and PIP4K2A play important roles in molecular mechanisms of psychiatric disorders. GSK3B occupies a central position in these molecular mechanisms and is also modulated by psychotropic drugs. BDNF regulates a number of key aspects in neurodevelopment and synaptic plasticity. NGF exerts a trophic action and is implicated in cerebral alterations associated with psychiatric disorders. NRG1 is active in neural development, synaptic plasticity, and neurotransmission. HTR2C is another important psychopharmacological target. PIP4K2A catalyzes the phosphorylation of PI5P to form PIP2, the latter being implicated in various aspects of neuronal signal transduction. In the present study, the six genes were sequenced in a cohort of 19 patients with bipolar affective disorder, 41 patients with recurrent depressive disorder, and 55 patients with depressive episode. The study revealed a number of genetic variants associated with antidepressant treatment response, time to recurrence of episodes, and depression severity. Namely, alleles of rs35641374 and rs10508649 (NRG1 and PIP4K2A) may be prognostic biomarkers of time to recurrence of depressive and manic/mixed episodes among patients with bipolar affective disorder. Alleles of NC_000008.11:g.32614509_32614510del, rs61731109, and rs10508649 (also NRG1 and PIP4K2A) seem to be predictive biomarkers of response to pharmacological antidepressant treatment on the 28th day assessed by the HDRS-17 or CGI-I scale. In particular, the allele G of rs10508649 (PIP4K2A) may increase resistance to antidepressant treatment and be at the same time protective against recurrent manic/mixed episodes. These results support previous data indicating a biological link between resistance to antidepressant treatment and mania. Bioinformatic functional annotation of associated variants revealed possible impact for transcriptional regulation of PIP4K2A. In addition, the allele A of rs2248440 (HTR2C) may be a prognostic biomarker of depression severity. This allele decreases expression of the neighboring immune system gene IL13RA2 in the putamen according to the GTEx portal. The variant rs2248440 is near rs6318 (previously associated with depression and effects of psychotropic drugs) that is an eQTL for the same gene and tissue. Finally, the study points to several protein interactions relevant in the pathogenesis of mood disorders. Functional studies using cellular or animal models are warranted to support these results.

Pharmacogenetic Implications for Antidepressant Pharmacotherapy in Late-Life Depression: A Systematic Review of the Literature for Response, Pharmacokinetics and Adverse Drug Reactions

Affecting up to 15% of older adults, late-life depression (LLD) is characterized by the occurrence of depressive symptoms after the age of 50-65 years and maybe pathophysiologically distinct from depression in younger adults. Therefore, LLD is challenging to treat, and predictive genetic testing might be essential to improve treatment in this vulnerable population. The current review aims to provide a summary of the literature exploring genetic associations with antidepressant treatment outcomes in late-life. We conducted a systematic search of three integrated electronic databases. We identified 29 articles investigating genetic associations with antidepressant treatment outcomes, pharmacokinetic parameters, and adverse drug reactions in older adults. Given the small number of investigations conducted in older adults, it is difficult to conclude the presence or absence of genetic associations with the outcomes of interest. In sum, the most substantial amount of evidence exists for the CYP2D6 metabolizer status, SLC6A4 5-HTTLPR, and BDNF rs6265. These findings are consistent in the literature when not restricting to older adults, suggesting that similar treatment recommendations may be provided for older adults regarding genetic variation, such as those outlined for CYP2D6 by the Clinical Pharmacogenetics Implementation Consortium. Nonetheless, further studies are required in well-characterized samples, including genome-wide data, to validate if similar treatment adjustments are appropriate in older adults, given that there appear to be significant effects of genetic variation on antidepressant treatment factors.

MicroRNA-382-5p Targets Nuclear Receptor Subfamily 3 Group C Member 1 to Regulate Depressive-Like Behaviors Induced by Chronic Unpredictable Mild Stress in Rats

BACKGROUND

Depression is an emotional disorder characterized by depression, lack of pleasure, and cognitive and sleep disorders. It is a systemic disease with a complex pathogenesis. In this study, we will be focused to investigate their associations and the exact functional mechanisms of miR-382-5p and NR3C1 in depression.

MATERIALS AND METHODS

We measured the expressions of microRNA-382-5p (miR-382-5p) and NR3C1 in the hippocampus by chronic unpredictable mild stress (CUMS). Depression behavior test including novelty-suppressed feeding test (NSFT), sucrose preference test (SPT), and forced swim test (FST) on rats have been conducted to examine the roles and functions of miR-382-5p and NR3C1 on depression-like behaviors by lentivirus vectors.

RESULTS

Up-regulation of miR-382-5p and down-regulation of NR3C1 were observed in rats' hippocampus induced by CUMS. miR-382-5p targeted NR3C1 and inhibited the expressions of NR3C1 in rats' hippocampus. miR-382-5p could significantly change the depression behaviors induced by CUMS. NR3C1 downstream BDNF and p-TrkB were also oppositely associated with miR-382-5p in rats' hippocampus.

CONCLUSION

Through our experiments and analysis, we found that the associations between miR-382-5p and NR3C1 could affect the depression-like behaviors.

Analysis of the Deleterious Single-Nucleotide Polymorphisms Associated With Antidepressant Efficacy in Major Depressive Disorder

Major depressive disorder (MDD) is a serious mental disease with negative effects on both mental and physical health of the patient. Currently, antidepressants are among the major ways to ease or treat MDD. However, the existing antidepressants have limited efficacy in treating MDD, with a large fraction of patients either responding inadequately or differently to antidepressants during the treatment. Pharmacogenetics studies have found that the genetic features of some genes are associated with the antidepressant efficacy. In order to obtain a better understanding on the relationship between the genetic factors and antidepressant treatment response, we compiled a list of 233 single-nucleotide polymorphisms (SNPs) significantly associated with the antidepressant efficacy in treating MDD. Of the 13 non-synonymous SNPs in the list, three (rs1065852, rs3810651, and rs117986340) may influence the structures and function of the corresponding proteins. Besides, the influence of rs1065852 on the structure of CYP2D6 was further investigated via molecular dynamics simulations. Our results showed that compared to the native CYP2D6 the flexibility of the F-G loop was reduced in the mutant. As a portion of the substrate access channel, the lower flexibility of F-G loop may reduce the ability of the substrates to enter the channel, which may be the reason for the lower enzyme activity of mutant. This study may help us to understand the impact of genetic variation on antidepressant efficacy and provide clues for developing new antidepressants.

Plasma brain-derived neurotrophic factor (pBDNF) and executive dysfunctions in patients with major depressive disorder

Objectives: Executive dysfunctions are frequently seen in patients with major depressive disorder (MDD) and normalise in many cases during effective antidepressant therapy. This study investigated whether a normalisation of executive dysfunctions during antidepressant treatment correlates with or can be predicted by clinical parameters or levels of brain-derived neurotrophic factor (BDNF).Methods: In 110 MDD patients with executive dysfunctions (percentile <16), executive functions and plasma BDNF levels were analysed at baseline, and days 14 and 56 of an antidepressant treatment. BDNF exon IV and P11 methylation status was studied at baseline.Results: Eighty patients (73%) experienced a normalisation of executive dysfunctions, while 30 (27%) suffered from persistent dysfunctions until day 56. Patients with persistent dysfunctions had significantly higher HAMD scores at days 14 and 56, and lower plasma BDNF levels at each time point than patients with a normalisation of dysfunctions (F₁= 10.18; P = 0.002). This was seen for verbal fluency, but not processing speed. BDNF exon IV and p11 promoter methylation was not associated with test performance.Conclusions: Our results corroborate a concomitant amelioration of executive dysfunctions with successful antidepressant therapy and support a role of BDNF in the neural mechanisms underlying the normalisation of executive dysfunctions in MDD.ClinicalTrials.gov number: NCT00974155; EudraCT: 2008-008280-96.

Pharmacogenetics of Antidepressants: from Genetic Findings to Predictive Strategies

The constantly growing contribution of depressive disorders to the global disease statistics calls for a growth of treatment effectiveness and optimization. Antidepressants are the most frequently prescribed medicines for depressive disorders. However, development of a standardized pharmacotherapeutic approach is burdened by the genomic heterogeneity, lack of reliable predictive biomarkers and variability of the medicines metabolism aggravated by multiple side effects of antidepressants. According to modern assessments up to 20 % of the genes expressed in our brain are involved in the pathogenesis of depression. Large-scale genetic and genomic research has found a number of potentially prognostic genes. It has also been proven that the effectiveness and tolerability of antidepressants directly depend on the variable activity of the enzymes that metabolize medicines. Almost all modern antidepressants are metabolized by the cytochrome P450 family enzymes. The most promising direction of research today is the GWAS (Genome-Wide Association Study) method that is aimed to link genomic variations with phenotypical manifestations. In this type of research genomes of depressive patients with different phenotypes are compared to the genomes of the control group containing same age, sex and other parameters healthy people. Notably, regardless of the large cohorts of patients analyzed, none of the GWA studies conducted so far can reliably reproduce the results of other analogous studies. The explicit heterogeneity of the genes associated with the depression pathogenesis and their pleiotropic effects are strongly influenced by environmental factors. This may explain the difficulty of obtaining clear and reproducible results. However, despite any negative circumstances, the active multidirectional research conducted today, raises the hope of clinicians and their patients to get a whole number of schedules how to achieve remission faster and with guaranteed results

Link between depression and cardiovascular diseases due to epigenomics and proteomics: Focus on energy metabolism

Major depression is the most common mental disorder and a leading cause of years lived with disability. In addition to the burden attributed to depressive symptoms and reduced daily life functioning, people with major depression are at increased risk of premature mortality, particularly due to cardiovascular diseases. Several studies point to a bi-directional relation between major depression and cardiovascular diseases, thereby indicating that both diseases may share common pathophysiological pathways. These include lifestyle factors (e.g. physical activity, smoking behavior), dysfunctions of endocrine systems (e.g. hypothalamus-pituitary adrenal axis), and a dysbalance of pro- and anti-inflammatory factors. Furthermore, recent research point to the role of epigenomic and proteomic factors, that are reviewed here with a particular focus on the mitochondrial energy metabolism.

Psychobiological factors of resilience and depression in late life

In contrast to traditional perspectives of resilience as a stable, trait-like characteristic, resilience is now recognized as a multidimentional, dynamic capacity influenced by life-long interactions between internal and environmental resources. We review psychosocial and neurobiological factors associated with resilience to late-life depression (LLD). Recent research has identified both psychosocial characteristics associated with elevated LLD risk (e.g., insecure attachment, neuroticism) and psychosocial processes that may be useful intervention targets (e.g., self-efficacy, sense of purpose, coping behaviors, social support). Psychobiological factors include a variety of endocrine, genetic, inflammatory, metabolic, neural, and cardiovascular processes that bidirectionally interact to affect risk for LLD onset and course of illness. Several resilience-enhancing intervention modalities show promise for the prevention and treatment of LLD, including cognitive/psychological or mind-body (positive psychology; psychotherapy; heart rate variability biofeedback; meditation), movement-based (aerobic exercise; yoga; tai chi), and biological approaches (pharmacotherapy, electroconvulsive therapy). Additional research is needed to further elucidate psychosocial and biological factors that affect risk and course of LLD. In addition, research to identify psychobiological factors predicting differential treatment response to various interventions will be essential to the development of more individualized and effective approaches to the prevention and treatment of LLD.

Genetic variants in major depressive disorder: From pathophysiology to therapy

In spite of promising preclinical results there is a decreasing number of new registered medications in major depression. The main reason behind this fact is the lack of confirmation in clinical studies for the assumed, and in animals confirmed, therapeutic results. This suggests low predictive value of animal studies for central nervous system disorders. One solution for identifying new possible targets is the application of genetics and genomics, which may pinpoint new targets based on the effect of genetic variants in humans. The present review summarizes such research focusing on depression and its therapy. The inconsistency between most genetic studies in depression suggests, first of all, a significant role of environmental stress. Furthermore, effect of individual genes and polymorphisms is weak, therefore gene x gene interactions or complete biochemical pathways should be analyzed. Even genes encoding target proteins of currently used antidepressants remain non-significant in genome-wide case control investigations suggesting no main effect in depression, but rather an interaction with stress. The few significant genes in GWASs are related to neurogenesis, neuronal synapse, cell contact and DNA transcription and as being nonspecific for depression are difficult to harvest pharmacologically. Most candidate genes in replicable gene x environment interactions, on the other hand, are connected to the regulation of stress and the HPA axis and thus could serve as drug targets for depression subgroups characterized by stress-sensitivity and anxiety while other risk polymorphisms such as those related to prominent cognitive symptoms in depression may help to identify additional subgroups and their distinct treatment. Until these new targets find their way into therapy, the optimization of current medications can be approached by pharmacogenomics, where metabolizing enzyme polymorphisms remain prominent determinants of therapeutic success.

Effects of CREB1 gene silencing on cognitive dysfunction by mediating PKA-CREB signaling pathway in mice with vascular dementia

Background

As a form of dementia primarily affecting the elderly, vascular dementia (VD) is characterized by changes in the supply of blood to the brain, resulting in cognitive impairment. The aim of the present study was to explore the effects involved with cyclic adenosine monophosphate (cAMP) response element-binding (CREB)1 gene silencing on cognitive dysfunction through meditation of the protein kinase A (PKA)-CREB signaling pathway in mice with VD.

Methods

Both the Morris water maze test and the step down test were applied to assess the cognitive function of the mice with VD. Immunohistochemical and TUNEL staining techniques were employed to evaluate the positive expression rates of the protein CREB1 and Cleaved Caspase-3, as well as neuronal apoptosis among hippocampal tissues in a respective manner. Flow cytometry was applied to determine the proliferation index and apoptosis rate of the hippocampal cells among each group. Reverse transcription quantitative polymerase chain reaction and Western blot analysis methods were applied to detect the expressions of cAMP, PKA and CREB in hippocampal cells.

Results

Compared with the normal group, all the other groups exhibited impaired cognitive function, reduced cell numbers in the CAI area, positive expressions of CREB1 as well as positive optical density (OD) values. Furthermore, increased Cleaved Caspase-3 positive expression, OD value, proliferation index, apoptosis rate of hippocampal cells and neurons, were observed in the other groups when compared with the normal group, as well as lower expressions of cAMP, PKA and CREB1 and p-CREB1 (the shCREB1–1, H89 and shCREB1–1 + H89 groups < the VD group).

Conclusion

The key findings of the present study demonstrated that CREB1 gene silencing results in aggravated VD that occurs as a result of inhibiting the PKA-CREB signaling pathway, thus exasperating cognitive dysfunction.

Predictors of treatment outcome in depression in later life: A systematic review and meta-analysis

BACKGROUND

Predictor analyses of late-life depression can be used to identify variables associated with outcomes of treatments, and hence ways of tailoring specific treatments to patients. The aim of this review was to systematically identify, review and meta-analyse predictors of outcomes of any type of treatment for late-life depression.

METHODS

Pubmed, Embase, CINAHL, Web of Science and PsycINFO were searched for studies published up to December 2016. Primary and secondary studies reported treatment predictors from randomised controlled trials of any treatment for patients with major depressive disorder aged over 60 were included. Treatment outcomes included response, remission and change in depression score.

RESULTS

Sixty-seven studies met the inclusion criteria. Of 65 identified statistically significant predictors, only 7 were reported in at least 3 studies. Of these, 5 were included in meta-analyses, and only 3 were statistically significant. Most studies were rated as being of moderate to strong quality and satisfied key quality criteria for predictor analyses.

LIMITATIONS

The searches were limited to randomised controlled trials and most of the included studies were secondary analyses.

CONCLUSIONS

Baseline depression severity, co-morbid anxiety, executive dysfunction, current episode duration, early improvement, physical illnesses and age were reported as statistically significant predictors of treatment outcomes. Only the first three were significant in meta-analyses. Subgroup analyses showed differences in predictor effect between biological and psychosocial treatment. However, high heterogeneity and small study numbers suggest a cautious interpretation of results. These predictors were associated with various mechanisms including brain pathophysiology, perceived social support and proposed distinct types of depressive disorder. Further investigation of the clinical utility of these predictors is suggested.

Blood-based biomarkers predicting response to antidepressants

Major depressive disorder is a common, serious and in some cases, life-threatening condition and affects approximately 350 million people globally. Although there is effective treatment available for it, more than 50% of the patients fail to respond to the first antidepressant they receive. The selection of a distinct treatment is still exclusively based on clinical judgment without incorporating lab-derived objective measures. However, there is growing evidence of biomarkers that it helps to improve diagnostic processes and treatment algorithms. Here genetic markers and blood-based biomarkers of the monoamine pathways, inflammatory pathways and the hypothalamic-pituitary-adrenal (HPA) axis are reviewed. Promising findings arise from studies investigating inflammatory pathways and immune markers that may identify patients suitable for anti-inflammatory based treatment regimes. Next, an early normalization of a disturbed HPA axis or depleted neurotrophic factors may predict stable treatment response. Genetic markers within the serotonergic system may identify patients who are vulnerable because of stressful life events, but evidence for guiding treatment regimes still is inconsistent. Therefore, there is still a great need for studies investigating and validating biomarkers for the prediction of treatment response to facilitate the treatment selection and shorten the time to remission and thus provide personalized medicine in psychiatry.

Neuroplasticity and second messenger pathways in antidepressant efficacy: pharmacogenetic results from a prospective trial investigating treatment resistance

Genes belonging to neuroplasticity, monoamine, circadian rhythm, and transcription factor pathways were investigated as modulators of antidepressant efficacy. The present study aimed (1) to replicate previous findings in an independent sample with treatment-resistant depression (TRD), and (2) to perform a pathway analysis to investigate the possible molecular mechanisms involved. 220 patients with major depressive disorder who were non-responders to a previous antidepressant were treated with venlafaxine for 4-6 weeks and in case of non-response with escitalopram for 4-6 weeks. Symptoms were assessed using the Montgomery Asberg Depression Rating Scale. The phenotypes were response and remission to venlafaxine, non-response (TRDA) and non-remission (TRDB) to neither venlafaxine nor escitalopram. 50 tag SNPs in 14 genes belonging to the pathways of interest were tested for association with phenotypes. Molecular pathways (KEGG database) that included one or more of the genes associated with the phenotypes were investigated also in the STAR*D sample. The associations between ZNF804A rs7603001 and response, CREB1 rs2254137 and remission were replicated, as well as CHL1 rs2133402 and lower risk of TRD. Other CHL1 SNPs were potential predictors of TRD (rs1516340, rs2272522, rs1516338, rs2133402). The MAPK1 rs6928 SNP was consistently associated with all the phenotypes. The protein processing in endoplasmic reticulum pathway (hsa04141) was the best pathway that may explain the mechanisms of MAPK1 involvement in antidepressant response. Signals in genes previously associated with antidepressant efficacy were confirmed for CREB1, ZNF804A and CHL1. These genes play pivotal roles in synaptic plasticity, neural activity and connectivity.

Molecular network-selected pharmacogenomics in a case of bipolar spectrum disorder

Personal genomic analysis was used for molecular diagnosis and pharmacogenomics in a 53-year-old female suffering from alternating depressive and dysphoric episodes. A total of 52 genes and 108 SNPs were analyzed in the whole genome. Results from the pharmacogenomic analysis were consistent with the pharmacological history and indicate mutations associated with low monoaminergic tone, but also a hyperactive 5HT2A receptor, a feature that associates to a high probability of developing a bipolar condition, especially under 5-hydroxytryptamine potentiating pharmacology. This aligns with the patient developing dysphoria with high clomipramine. The pharmacokinetic genomics pointed out to some absorption, distribution, metabolism, and excretion (ADME) alterations that can lower or nullify drug's activity. A personalized regimen was proposed, with a positive outcome after 1 year.

Alleviative effects of fluoxetine on depressive-like behaviors by epigenetic regulation of BDNF gene transcription in mouse model of post-stroke depression

Fluoxetine, one of the selective serotonin reuptake inhibitor (SSRI) antidepressants, has been thought to be effective for treating post-stroke depression (PSD). Recent work has shown that fluoxetine may exert an antidepressive effect through increasing the level of brain-derived neurotrophic factor (BDNF), but the underlying mechanism still remains unclear. In the present study, we successfully established the PSD model using male C57BL/6 J mice by photothrombosis of the left anterior cortex combined with isolatied-housing conditions. In the process, we confirmed that fluoxetine could improve the depression-like behaviors of PSD mice and upregulate the expression of BDNF in the hippocampus. However, depletion of BDNF by transfecting lentivirus-derived shBDNF in hippocampus suppressed the effect of fluoxetine. Furthermore, we demonstrated the epigenetic mechanisms involved in regulation of BDNF expression induced by fluoxetine. We found a statistically significant increase in DNA methylation at specific CpG sites (loci 2) of Bdnf promoter IV in the hippocampus of PSD mice. We also found that fluoxetine treatment could disassociate the MeCP2-CREB-Bdnf promoter IV complex via phosphorylation of MeCP2 at Ser421 by Protein Kinase A (PKA). Our research highlighted the importance of fluoxetine in regulating BDNF expression which could represent a potential strategy for preventing PSD.

New insights into the genetics of fibromyalgia

Although debate on the concept of fibromyalgia (FM) has been vigorous ever since the classification criteria were first published, FM is now better understood and has become recognized as a disorder. Recently, FM has come to be considered a major health problem, affecting 1% to 5% of the general population. As familial aggregations have been observed among some FM patients, genetic research on FM is logical. In fact, genome-wide association studies and linkage analysis, and studies on candidate genes, have uncovered associations between certain genetic factors and FM. Genetic susceptibility is now considered to influence the etiology of FM. At the same time, novel genetic techniques, such as microRNA analysis, have been used in attempts to improve our understanding of the genetic predisposition to FM. In this article, we review recent advances in, and continuing challenges to, the identification of genes contributing to the development of, and symptom severity in, FM.

The genetic overlap between mood disorders and cardiometabolic diseases: a systematic review of genome wide and candidate gene studies

Meta-analyses of genome-wide association studies (meta-GWASs) and candidate gene studies have identified genetic variants associated with cardiovascular diseases, metabolic diseases and mood disorders. Although previous efforts were successful for individual disease conditions (single disease), limited information exists on shared genetic risk between these disorders. This article presents a detailed review and analysis of cardiometabolic diseases risk (CMD-R) genes that are also associated with mood disorders. First, we reviewed meta-GWASs published until January 2016, for the diseases 'type 2 diabetes, coronary artery disease, hypertension' and/or for the risk factors 'blood pressure, obesity, plasma lipid levels, insulin and glucose related traits'. We then searched the literature for published associations of these CMD-R genes with mood disorders. We considered studies that reported a significant association of at least one of the CMD-R genes and 'depression' or 'depressive disorder' or 'depressive symptoms' or 'bipolar disorder' or 'lithium treatment response in bipolar disorder', or 'serotonin reuptake inhibitors treatment response in major depression'. Our review revealed 24 potential pleiotropic genes that are likely to be shared between mood disorders and CMD-Rs. These genes include MTHFR, CACNA1D, CACNB2, GNAS, ADRB1, NCAN, REST, FTO, POMC, BDNF, CREB, ITIH4, LEP, GSK3B, SLC18A1, TLR4, PPP1R1B, APOE, CRY2, HTR1A, ADRA2A, TCF7L2, MTNR1B and IGF1. A pathway analysis of these genes revealed significant pathways: corticotrophin-releasing hormone signaling, AMPK signaling, cAMP-mediated or G-protein coupled receptor signaling, axonal guidance signaling, serotonin or dopamine receptors signaling, dopamine-DARPP32 feedback in cAMP signaling, circadian rhythm signaling and leptin signaling. Our review provides insights into the shared biological mechanisms of mood disorders and cardiometabolic diseases.

Pharmacogenetics and Imaging-Pharmacogenetics of Antidepressant Response: Towards Translational Strategies

Genetic variation underlies both the response to antidepressant treatment and the occurrence of side effects. Over the past two decades, a number of pharmacogenetic variants, among these the SCL6A4, BDNF, FKBP5, GNB3, GRIK4, and ABCB1 genes, have come to the forefront in this regard. However, small effects sizes, mixed results in independent samples, and conflicting meta-analyses results led to inherent difficulties in the field of pharmacogenetics translating these findings into clinical practice. Nearly all antidepressant pharmacogenetic variants have potentially pleiotropic effects in which they are associated with major depressive disorder, intermediate phenotypes involved in emotional processes, and brain areas affected by antidepressant treatment. The purpose of this article is to provide a comprehensive review of the advances made in the field of pharmacogenetics of antidepressant efficacy and side effects, imaging findings of antidepressant response, and the latest results in the expanding field of imaging-pharmacogenetics studies. We suggest there is mounting evidence that genetic factors exert their impact on treatment response by influencing brain structural and functional changes during antidepressant treatment, and combining neuroimaging and genetic methods may be a more powerful way to detect biological mechanisms of response than either method alone. The most promising imaging-pharmacogenetics findings exist for the SCL6A4 gene, with converging associations with antidepressant response, frontolimbic predictors of affective symptoms, and normalization of frontolimbic activity following antidepressant treatment. More research is required before imaging-pharmacogenetics informed personalized medicine can be applied to antidepressant treatment; nevertheless, inroads have been made towards assessing genetic and neuroanatomical liability and potential clinical application.

Influence of Genetic Polymorphisms and Concomitant Anxiolytic Doses on Antidepressant Maintenance Doses in Japanese Patients with Depression

To prevent recurrent depression, patients should ideally continue treatment for >6 months with the antidepressant dose that effectively suppressed acute depressive symptoms. However, there are inter-individual differences in the antidepressant doses required to achieve response and maintenance. Therefore, this study was conducted to examine the role of clinical features, including genetic polymorphisms, on the antidepressant dose required for maintenance therapy in 82 Japanese patients with depression. We calculated the antidepressant dose using the imipramine equivalent scale and the dose of concomitant anxiolytics and hypnotics using the diazepam equivalent scale. The 82 participants were classified into two groups based on the median imipramine equivalent dose, and we examined the influence of patient characteristics and the presence of genetic polymorphisms of brain-derived neurotropic factor (BDNF; rs6265) and cyclic adenosine monophosphate responsive element-binding protein 1 (CREB1; rs2253306, rs4675690, rs769963) on the antidepressant maintenance dose. Using a multivariate logistic regression analysis, we found that the concomitant diazepam equivalent dose and presence of the CREB1 rs4675690 polymorphism were significantly associated with the antidepressant maintenance dose. We concluded that these factors influenced the antidepressant dose in maintenance therapy among Japanese patients with depression. However, further research is required in large cohorts.

Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network

Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE‐PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of “precision medicine.” The February 2015 eMERGE‐PGx data release includes sequence‐derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation‐Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.

Cyr NM, Siddarth P, Baune BT, Lavretsky H. Genomic predictors of remission to antidepressant treatment in geriatric depression using genome-wide expression analyses: a pilot study

OBJECTIVE

This first pilot study of genome-wide expression as predictor of antidepressant response in late-life depression examined genome-wide transcriptional profiles in a randomized placebo-controlled trial of combined methylphenidate and citalopram.

METHODS

Genome-wide transcriptional profiles were examined in peripheral blood leukocytes sampled at baseline and 16 weeks from 35 older adults with major depression, who were randomized to methylphenidate + citalopram, citalopram + placebo, or methylphenidate + placebo. Methylphenidate doses ranged between 10 and 40 mg/day, and citalopram doses ranged between 20 and 60 mg/day. Remission was defined as Hamilton Depression Rating Scale score of 6 or below. Early remission was achieved in the first 4 weeks of treatment. We hypothesized that differential gene expression at baseline can predict antidepressant response.

RESULTS

We analyzed gene expression in 24 remitters and 11 non-remitters. At baseline, we found three genes showing higher expression in all remitters versus non-remitters that satisfied the established level of significance: a fold change of 2 and p-value of 0.05 that included HLA-DRB5, SELENBP1, and LOC388588. Two gene transcripts showed higher expression in early remitters at baseline compared with non-remitters. The first gene was CA1 carbonic anhydrase gene, on chromosome 8 involved in respiratory function (fold change 2.54; p = 0.03). The second gene was the SNCA-α-synuclein gene, implicated, which binds to dopamine transporter (fold change 2.1; p = 0.03).

CONCLUSIONS

Remission to antidepressants in geriatric depression may be associated with a particular gene expression profile in monoaminergic and metabolic pathways and needs to be replicated in a larger sample.

Targeting drug sensitivity predictors: New potential strategies to improve pharmacotherapy of human brain disorders

One of the main challenges in medicine is the lack of efficient drug therapies for common human disorders. For example, although depressed patients receive powerful antidepressants, many often remain resistant to psychopharmacotherapy. The growing recognition of complex interplay between the drug targets and the predictors of drug sensitivity requires an improved understanding of these two key aspects of drug action and their potentially shared molecular networks. Here, we apply the concept of endophenotypes and their interplay to drug action and sensitivity. Based on these analyses, we postulate that novel drugs may be developed by targeting specific molecular pathways that integrate drug targets with drug sensitivity predictors.

Depression in Older Adults: A Palliative Medicine Perspective

This article aims to discuss the rapidly growing field of palliative medicine and its unique approach to treating depression in older adults.

Pharmacogenetics of major depressive disorder: top genes and pathways toward clinical applications

The pharmacogenetics of antidepressants has been not only a challenging but also frustrating research field since its birth in the 1990s. Indeed, great expectations followed the first evidence of familiar aggregation of antidepressant response. Despite the progress from candidate gene studies to genome-wide association studies (GWAS), results fell out the expectations and they were often inconsistent. Anyway, the cumulative evidence supports the involvement of some genes and molecular pathways in antidepressant efficacy. The best single genes are SLC6A4, HTR2A, BDNF, GNB3, FKBP5, ABCB1, and cytochrome P450 genes (CYP2D6 and CYP2C19). Molecular pathways involved in inflammation and neuroplasticity show the greatest support. The first studies evaluating benefits of genotype-guided antidepressant treatments provided encouraging results and confirmed the relevance of SLC6A4, HTR2A, ABCB1, and cytochrome P450 genes. Further progress in genotyping and data analysis would allow to move forward and complete the understanding of antidepressant pharmacogenetics and its translation into clinical applications.

Epigenetic alterations in depression and antidepressant treatment

Epigenetic modifications control chromatin structure and function, and thus mediate changes in gene expression, ultimately influencing protein levels. Recent research indicates that environmental events can induce epigenetic changes and, by this, contribute to long-term changes in neural circuits and endocrine systems associated with altered risk for stress-related psychiatric disorders such as major depression. In this review, we describe recent approaches investigating epigenetic modifications associated with altered risk for major depression or response to antidepressant drugs, both on the candidate gene levels as well as the genome-wide level. In this review we focus on DNA methylation, as this is the most investigated epigenetic change in depression research.

Serotonin transporter gene: a new polymorphism may affect response to antidepressant treatments in major depressive disorder

BACKGROUND AND OBJECTIVES

Several gene variants have been related to major depressive disorder (MDD) treatment outcomes; however, few studies have investigated a possible different effect on pharmacotherapy and brief psychotherapy response.

METHODS

A total of 137 MDD patients were randomized to either interpersonal counseling (IPC; n = 40) or antidepressant pharmacological treatment (n = 97). Outcomes were remission, response, and symptom improvement at week 8. Five genetic variants were investigated (5HTR2A rs6314, BDNF rs6265, SLC6A4 rs8076005, CREB1 rs2253206, and TPH2 rs11179023) as possible modulators of outcomes.

RESULTS

The LC6A4 rs8076005 AA genotype and A allele were associated with response rate in the antidepressant group (p = 0.015 and 0.005, respectively) and in the whole sample (p = 0.03 and 0.02, respectively). In the IPC group a non-significant trend in the same direction was observed. The TPH2 rs11179023 A allele showed a marginal association with symptom improvement in the IPC group only. Other gene variants did not impact on outcomes in any treatment group.

CONCLUSION

Our study suggests that rs8076005 in the SLC6A4 gene may be a modulator of antidepressant response, especially when pharmacological treatment is used.

Advances in biomarkers of major depressive disorder

Major depressive disorder (MDD) is characterized by mood, vegetative, cognitive, and even psychotic symptoms and signs that can cause substantial impairments in quality of life and functioning. Biomarkers are measurable indicators that could help diagnosing MDD or predicting treatment response. In this chapter, lipid profiles, immune/inflammation, and neurotrophic factor pathways that have long been implicated in the pathogenesis of MDD are discussed. Then, pharmacogenetics and epigenetics of serotonin transport and its metabolism pathway, brain-derived neurotrophic factor, and abnormality of hypothalamo-pituitary-adrenocortical axis also revealed new biomarkers. Lastly, new techniques, such as proteomics and metabolomics, which allow researchers to approach the studying of MDD with new directions and make new discoveries are addressed. In the future, more data are needed regarding pathophysiology of MDD, including protein levels, single nucleotide polymorphism, epigenetic regulation, and clinical data in order to better identify reliable and consistent biomarkers for diagnosis, treatment choice, and outcome prediction.

Understanding the pharmacogenetics of selective serotonin reuptake inhibitors

INTRODUCTION

The genetic background of antidepressant response represents a unique opportunity to identify biological markers of treatment outcome. Encouraging results alternating with inconsistent findings made antidepressant pharmacogenetics a stimulating but often discouraging field that requires careful discussion about cumulative evidence and methodological issues.

AREAS COVERED

The present review discusses both known and less replicated genes that have been implicated in selective serotonin reuptake inhibitors (SSRIs) efficacy and side effects. Candidate genes studies and genome-wide association studies (GWAS) were collected through MEDLINE database search (articles published till January 2014). Further, GWAS signals localized in promising genetic regions according to candidate gene studies are reported in order to assess the general comparability of results obtained through these two types of pharmacogenetic studies. Finally, a pathway enrichment approach is applied to the top genes (those harboring SNPs with p < 0.0001) outlined by previous GWAS in order to identify possible molecular mechanisms involved in SSRI effect.

EXPERT OPINION

In order to improve the understanding of SSRI pharmacogenetics, the present review discusses the proposal of moving from the analysis of individual polymorphisms to genes and molecular pathways, and from the separation across different methodological approaches to their combination. Efforts in this direction are justified by the recent evidence of a favorable cost-utility of gene-guided antidepressant treatment.

Are there meaningful biomarkers of treatment response for depression?

During the past decades, the prevalence of affective disorders has been on the rise globally, with only one out of three patients achieving remission in acute treatment with antidepressants. The identification of physiological markers that predict treatment course proves useful in increasing therapeutic success. On the basis of well-documented, recent findings in depression research, we highlight and discuss the most promising biomarkers for antidepressant therapy response. These include genetic variants and gene expression profiles, proteomic and metabolomic markers, neuroendocrine function tests, electrophysiology and imaging techniques. Ultimately, this review proposes an integrative use of biomarkers for antidepressant treatment outcome.

Antidepressant pharmacogenetics

PURPOSE OF REVIEW

This article reviews recent literature published over the period March 2012-August 2013 on antidepressant pharmacogenetics, with a focus on clinical translation and methodological challenges.

RECENT FINDINGS

Recently, various polymorphisms associated with differential antidepressant efficacy, tolerability, and safety have emerged in association studies, but mixed findings, limited effect sizes, and poor control of confounders have prevented findings translating to practice. Although promising steps have been made, empirically robust clinically translatable pharmacogenetic tests are not yet established. The complex neurobiology of major depressive disorder (MDD) together with the evolving understanding of genetic processes present research challenges for clinical translation.

SUMMARY

Early reports of clinical utility are published. The current evidence base for antidepressant pharmacogenetics is, however, not yet empirically robust enough to inform routine prescribing guidelines. Over the coming years, genetically guided versus unguided trials will help determine if antidepressant pharmacogenetics merits more widespread application.

Gene expression: biomarker of antidepressant therapy?

While antidepressant therapy is an essential treatment of major depression, a substantial group of treated patients do not respond to therapy, or suffer from severe side effects. Moreover, the time of onset of the clinical improvement is often delayed. Antidepressants as currently available usually enhance serotonergic, noradrenergic and dopaminergic neurotransmission and may contribute to the inadequate remission rates for major depression. Therefore biomarkers enabling the identification of subgroups of patients and also finding unprecedented targets would provide the basis for personalized medication and thus improve treatment efficacy and reduce side effects. Several pharmacogenetic studies on antidepressant treatment response using single nucleotide polymorphism (SNPs) mapping have been performed but provided only modest findings. Therefore the analysis of gene expression to integrate genomic activity and environmental effects promises a new approach to cope with the complexity of factors influencing antidepressant treatment. Here gene expression studies focusing on candidate genes and genome-wide approaches using RNA derived from peripheral blood cells are reviewed. The most promising findings exist for hypothalamic-pituitary-adrenal (HPA) axis, inflammation and neuroplasticity related genes. However, straightforward translation into tailored treatment is still unlikely. Contradictory results limit the clinical use of the findings. Future studies are necessary, which could include functional analysis and consider gene-environment interactions.