Discovery of blood transcriptomic markers for depression in animal models and pilot validation in subjects with early-onset major depression

Reduced default mode network suppression during a working memory task in remitted major depression

Insufficient default mode network (DMN) suppression was linked to increased rumination in symptomatic Major Depressive Disorder (MDD). Since rumination is known to predict relapse and a more severe course of MDD, we hypothesized that similar DMN alterations might also exist during full remission of MDD (rMDD), a condition known to be associated with increased relapse rates specifically in patients with adolescent onset. Within a cross-sectional functional magnetic resonance imaging study activation and functional connectivity (FC) were investigated in 120 adults comprising 78 drug-free rMDD patients with adolescent- (n = 42) and adult-onset (n = 36) as well as 42 healthy controls (HC), while performing the n-back task. Compared to HC, rMDD patients showed diminished DMN deactivation with strongest differences in the anterior-medial prefrontal cortex (amPFC), which was further linked to increased rumination response style. On a brain systems level, rMDD patients showed an increased FC between the amPFC and the dorsolateral prefrontal cortex, which constitutes a key region of the antagonistic working-memory network. Both whole-brain analyses revealed significant differences between adolescent-onset rMDD patients and HC, while adult-onset rMDD patients showed no significant effects. Results of this study demonstrate that reduced DMN suppression exists even after full recovery of depressive symptoms, which appears to be specifically pronounced in adolescent-onset MDD patients. Our results encourage the investigation of DMN suppression as a putative predictor of relapse in clinical trials, which might eventually lead to important implications for antidepressant maintenance treatment.

Genome-wide methylation study on depression: differential methylation and variable methylation in monozygotic twins

Depressive disorders have been shown to be highly influenced by environmental pathogenic factors, some of which are believed to exert stress on human brain functioning via epigenetic modifications. Previous genome-wide methylomic studies on depression have suggested that, along with differential DNA methylation, affected co-twins of monozygotic (MZ) pairs have increased DNA methylation variability, probably in line with theories of epigenetic stochasticity. Nevertheless, the potential biological roots of this variability remain largely unexplored. The current study aimed to evaluate whether DNA methylation differences within MZ twin pairs were related to differences in their psychopathological status. Data from the Illumina Infinium HumanMethylation450 Beadchip was used to evaluate peripheral blood DNA methylation of 34 twins (17 MZ pairs). Two analytical strategies were used to identify (a) differentially methylated probes (DMPs) and (b) variably methylated probes (VMPs). Most DMPs were located in genes previously related to neuropsychiatric phenotypes. Remarkably, one of these DMPs (cg01122889) was located in the WDR26 gene, the DNA sequence of which has been implicated in major depressive disorder from genome-wide association studies. Expression of WDR26 has also been proposed as a biomarker of depression in human blood. Complementarily, VMPs were located in genes such as CACNA1C, IGF2 and the p38 MAP kinase MAPK11, showing enrichment for biological processes such as glucocorticoid signaling. These results expand on previous research to indicate that both differential methylation and differential variability have a role in the etiology and clinical manifestation of depression, and provide clues on specific genomic loci of potential interest in the epigenetics of depression.

Blood transcriptomic markers for major depression: from animal models to clinical settings

Depression is a heterogeneous disorder and, similar to other spectrum disorders, its manifestation varies by age of onset, severity, comorbidity, treatment responsiveness, and other factors. A laboratory blood test based on specific biomarkers for major depressive disorder (MDD) and its subgroups could increase diagnostic accuracy and expedite the initiation of treatment. We identified candidate blood biomarkers by examining genome-wide expression differences in the blood of animal models representing both the genetic and environmental/stress etiologies of depression. Human orthologs of the resulting transcript panel were tested in pilot studies. Transcript abundance of 11 blood markers differentiated adolescent subjects with early-onset MDD from adolescents with no disorder (ND). A set of partly overlapping transcripts distinguished adolescent patients who had comorbid anxiety disorders from those with only MDD. In adults, blood levels of nine transcripts discerned subjects with MDD from ND controls. Even though cognitive behavioral therapy (CBT) resulted in remission of some patients, the levels of three transcripts consistently signaled prior MDD status. A coexpression network of transcripts seems to predict responsiveness to CBT. Thus, our approach can be developed into clinically valid diagnostic panels of blood transcripts for different manifestations of MDD, potentially reducing diagnostic heterogeneity and advancing individualized treatment strategies.

Targeting dynamic interplay among disordered domains or endophenotypes to understand complex neuropsychiatric disorders: Translational lessons from preclinical models

Contemporary biological psychiatry uses clinical and experimental (animal) models to increase our understanding of brain pathogenesis. Modeling psychiatric disorders is currently performed by targeting various key neurobehavioral clusters of phenotypic traits (domains), including affective, cognitive, social, motor and reward. Analyses of such domains and their 'smaller units' - individual endophenotypes - are critical for the study of complex brain disorders and their neural underpinnings. The spectrum nature of brain disorders and the importance of pathogenetic linkage among various disordered domains or endophenotypes have also been recognized as an important strategic direction of translational research. Here, we discuss cross-domain analyses of animal models, and focus on their value for mimicking the clinical overlap between disordered neurobehavioral domains in humans. Based on recent experimental evidence, we argue that understanding of brain pathogenesis requires modeling the clinically relevant inter-relationships between various individual endophenotypes (or their domains).

Testing the predictive value of peripheral gene expression for nonremission following citalopram treatment for major depression

Major depressive disorder (MDD) in general, and anxious-depression in particular, are characterized by poor rates of remission with first-line treatments, contributing to the chronic illness burden suffered by many patients. Prospective research is needed to identify the biomarkers predicting nonremission prior to treatment initiation. We collected blood samples from a discovery cohort of 34 adult MDD patients with co-occurring anxiety and 33 matched, nondepressed controls at baseline and after 12 weeks (of citalopram plus psychotherapy treatment for the depressed cohort). Samples were processed on gene arrays and group differences in gene expression were investigated. Exploratory analyses suggest that at pretreatment baseline, nonremitting patients differ from controls with gene function and transcription factor analyses potentially related to elevated inflammation and immune activation. In a second phase, we applied an unbiased machine learning prediction model and corrected for model-selection bias. Results show that baseline gene expression predicted nonremission with 79.4% corrected accuracy with a 13-gene model. The same gene-only model predicted nonremission after 8 weeks of citalopram treatment with 76% corrected accuracy in an independent validation cohort of 63 MDD patients treated with citalopram at another institution. Together, these results demonstrate the potential, but also the limitations, of baseline peripheral blood-based gene expression to predict nonremission after citalopram treatment. These results not only support their use in future prediction tools but also suggest that increased accuracy may be obtained with the inclusion of additional predictors (eg, genetics and clinical scales).

A Review of Biomarkers in Mood and Psychotic Disorders: A Dissection of Clinical vs. Preclinical Correlates

Despite significant research efforts aimed at understanding the neurobiological underpinnings of mood (depression, bipolar disorder) and psychotic disorders, the diagnosis and evaluation of treatment of these disorders are still based solely on relatively subjective assessment of symptoms as well as psychometric evaluations. Therefore, biological markers aimed at improving the current classification of psychotic and mood-related disorders, and that will enable patients to be stratified on a biological basis into more homogeneous clinically distinct subgroups, are urgently needed. The attainment of this goal can be facilitated by identifying biomarkers that accurately reflect pathophysiologic processes in these disorders. This review postulates that the field of psychotic and mood disorder research has advanced sufficiently to develop biochemical hypotheses of the etiopathology of the particular illness and to target the same for more effective disease modifying therapy. This implies that a "one-size fits all" paradigm in the treatment of psychotic and mood disorders is not a viable approach, but that a customized regime based on individual biological abnormalities would pave the way forward to more effective treatment. In reviewing the clinical and preclinical literature, this paper discusses the most highly regarded pathophysiologic processes in mood and psychotic disorders, thereby providing a scaffold for the selection of suitable biomarkers for future studies in this field, to develope biomarker panels, as well as to improve diagnosis and to customize treatment regimens for better therapeutic outcomes.

Blood transcriptomic biomarkers in adult primary care patients with major depressive disorder undergoing cognitive behavioral therapy

An objective, laboratory-based diagnostic tool could increase the diagnostic accuracy of major depressive disorders (MDDs), identify factors that characterize patients and promote individualized therapy. The goal of this study was to assess a blood-based biomarker panel, which showed promise in adolescents with MDD, in adult primary care patients with MDD and age-, gender- and race-matched nondepressed (ND) controls. Patients with MDD received cognitive behavioral therapy (CBT) and clinical assessment using self-reported depression with the Patient Health Questionnaire-9 (PHQ-9). The measures, including blood RNA collection, were obtained before and after 18 weeks of CBT. Blood transcript levels of nine markers of ADCY3, DGKA, FAM46A, IGSF4A/CADM1, KIAA1539, MARCKS, PSME1, RAPH1 and TLR7, differed significantly between participants with MDD (N=32) and ND controls (N=32) at baseline (q< 0.05). Abundance of the DGKA, KIAA1539 and RAPH1 transcripts remained significantly different between subjects with MDD and ND controls even after post-CBT remission (defined as PHQ-9 <5). The ROC area under the curve for these transcripts demonstrated high discriminative ability between MDD and ND participants, regardless of their current clinical status. Before CBT, significant co-expression network of specific transcripts existed in MDD subjects who subsequently remitted in response to CBT, but not in those who remained depressed. Thus, blood levels of different transcript panels may identify the depressed from the nondepressed among primary care patients, during a depressive episode or in remission, or follow and predict response to CBT in depressed individuals.

Investigation of manic and euthymic episodes identifies state- and trait-specific gene expression and STAB1 as a new candidate gene for bipolar disorder

Bipolar disorder (BD) is a highly heritable psychiatric disease characterized by recurrent episodes of mania and depression. To identify new BD genes and pathways, the present study employed a three-step approach. First, gene-expression profiles of BD patients were assessed during both a manic and an euthymic phase. These profiles were compared intra-individually and with the gene-expression profiles of controls. Second, those differentially expressed genes that were considered potential trait markers of BD were validated using data from the Psychiatric Genomics Consortiums' genome-wide association study (GWAS) of BD. Third, the implicated molecular mechanisms were investigated using pathway analytical methods. In the present patients, this novel approach identified: (i) sets of differentially expressed genes specific to mania and euthymia; and (ii) a set of differentially expressed genes that were common to both mood states. In the GWAS data integration analysis, one gene (STAB1) remained significant (P=1.9 × 10(-4)) after adjustment for multiple testing. STAB1 is located in close proximity to PBMR1 and the NEK4-ITIH1-ITIH3-ITIH4 region, which are the top findings from GWAS meta-analyses of mood disorder, and a combined BD and schizophrenia data set. Pathway analyses in the mania versus control comparison revealed three distinct clusters of pathways tagging molecular mechanisms implicated in BD, for example, energy metabolism, inflammation and the ubiquitin proteasome system. The present findings suggest that STAB1 is a new and highly promising candidate gene in this region. The combining of gene expression and GWAS data may provide valuable insights into the biological mechanisms of BD.

Attenuated inhibition of medium spiny neurons participates in the pathogenesis of childhood depression

Accumulating evidence suggests that the nucleus accumbens, which is involved in mechanisms of reward and addiction, plays a role in the pathogenesis of depression and in the action of antidepressants. In the current study, intraperitoneal injection of nomifensine, a dopamine reuptake inhibitor, decreased depression-like behaviors in the Wistar Kyoto rat model of depression in the sucrose-preference and forced swim tests. Nomifensine also reduced membrane excitability in medium spiny neurons in the core of the nucleus accumbens in the childhood Wistar Kyoto rats as evaluated by electrophysiological recording. In addition, the expression of dopamine D2-like receptor mRNA was downregulated in the nucleus accumbens, striatum and hippocampus of nomifensine-treated childhood Wistar Kyoto rats. These experimental findings indicate that impaired inhibition of medium spiny neurons, mediated by dopamine D2-like receptors, may be involved in the formation of depression-like behavior in childhood Wistar Kyoto rats, and that nomifensine can alleviate depressive behaviors by reducing medium spiny neuron membrane excitability.

Aberrant resting-state functional connectivity in a genetic rat model of depression

Abnormal intrinsic functional connectivity, measured by resting-state functional MRI, has been reported in major depressive disorder (MDD). Our study is the first to demonstrate hypo- and hyperconnectivity between the hippocampus and cortical, subcortical regions in a genetic animal model of depression, similar to connectivity anomalies found in MDD.

The search for peripheral biomarkers for major depression: benefiting from successes in the biology of smoking

The search for robust, clinically useful markers for major depression (MD) has been relatively unproductive. This is unfortunate because MD is one of the largest socio-economic challenges for much of the world and the development of reliable biomarkers for MD could aid in the prevention or treatment of this common syndrome. In this editorial, we compare the approaches taken in the search for biomarkers for MD to that of the more successful searches for biomarkers for tobacco use, and identify several substantive barriers. We suggest that many of the existing clinical repositories used in these biomarkers searches for MD may be of limited value. We conclude that in the future greater attention should be given to the clinical definitions, characterization of confounding environmental factors and age of subjects included in studies. © 2014 Wiley Periodicals, Inc.

Monitoring candidate gene expression variations before, during and after a first major depressive episode in a 51-year-old man

BACKGROUND

Although psychiatric disorders are frequently characterized by clinical heterogeneity, high recurrence, and unpredictable prognosis, studies of mRNA expression variations in blood cells from psychiatric patients constitute a promising avenue to establish clinical biomarkers. We report here, to our knowledge, the first genetic monitoring of a major depressive episode (MDE).

CASE PRESENTATION

The subject is a 51-year-old male, who was healthy at baseline and whose blood mRNA was monitored over 67 weeks for expression variations of 9 candidate genes. At week 20 the subject experienced a mild to moderate unexpected MDE, and oral antidepressant treatment was initiated at week 29. At week 36, the patient recovered from his MDE. After 6 months, antidepressant treatment was discontinued and the subject remained free of depressive symptoms. Genetic monitoring revealed that mRNA expression of SLC6A4/5HTT increased with the emergence of a depressive state, which later returned to basal levels after antidepressant treatment and during MDE recovery. PDLIM5, S100A10 and TNF mRNA showed also an interesting pattern of expression with regards to MDE evolution.

CONCLUSION

This case demonstrated the applicability of peripheral mRNA expression as a way to monitor the natural history of MDE.

Correlative gene expression pattern linking RNF123 to cellular stress-senescence genes in patients with depressive disorder: implication of DRD1 in the cerebral cortex

BACKGROUND

The expression level of the RNF1213 gene in blood cells has been identified as a disease risk marker, more than ten years before the diagnosis of depression (Glahn et al., 2012). To explore the status of this gene in the acute depressive state we have quantified the expression of RNF123 in the blood leukocytes (N=17), dorsolateral prefrontal and cingulate cortex (N=24) of patients with diagnosed depression and of matched controls. We have measured the expression of the DRD1 gene as a "neuronal probe". We have also quantified the mRNA of six genes previously identified as markers of the biopsychological stress associated with major depression: FOS, DUSP1, OGG1, STMN1, p16(INK4a) and TERT.

METHODS

The steady state of mRNA has been quantified by the real-time quantitative PCR technique.

RESULTS

RNF123 was overexpressed by 45% in the cingulate cortex of patients with psychotic depression. There were distinct co-expression patterns of RNF123 and stress-related genes in the blood cells and brain cortex of patients, demonstrating a transcriptional regulatory shift. In both the prefrontal and cingulate cortex of these patients a strong correlation interlinked STMN1, TERT and DRD1 pointing to a role of these genes in dopamine signaling.

LIMITATIONS

The two groups of patients were clinically heterogeneous. All the patients had received antidepressant treatment, details of which were not available.

CONCLUSION

We did not identify RNF123 as a clinically relevant, peripheral state marker of depression, but our study probably lacked statistical power to detect small effect size. It is likely to be involved in distinct pleiotropic molecular pathways at peripheral (blood) and central (brain) level.

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.

Core modular blood and brain biomarkers in social defeat mouse model for post traumatic stress disorder

Background

Post-traumatic stress disorder (PTSD) is a severe anxiety disorder that affects a substantial portion of combat veterans and poses serious consequences to long-term health. Consequently, the identification of diagnostic and prognostic blood biomarkers for PTSD is of great interest. Previously, we assessed genome-wide gene expression of seven brain regions and whole blood in a social defeat mouse model subjected to various stress conditions.

Results

To extract biological insights from these data, we have applied a new computational framework for identifying gene modules that are activated in common across blood and various brain regions. Our results, in the form of modular gene networks that highlight spatial and temporal biological functions, provide a systems-level molecular description of response to social stress. Specifically, the common modules discovered between the brain and blood emphasizes molecular transporters in the blood-brain barrier, and the associated genes have significant overlaps with known blood signatures for PTSD, major depression, and bipolar disease. Similarly, the common modules specific to the brain highlight the components of the social defeat stress response (e.g., fear conditioning pathways) in each brain sub-region.

Conclusions

Many of the brain-specific genes discovered are consistent with previous independent studies of PTSD or other mental illnesses. The results from this study further our understanding of the mechanism of stress response and contribute to a growing list of diagnostic biomarkers for PTSD.

Gene expression profiles in relation to tension and dissociation in borderline personality disorder

The biological underpinnings of borderline personality disorder (BPD) and its psychopathology including states of aversive tension and dissociation is poorly understood. Our goal was to examine transcriptional changes associated with states of tension or dissociation within individual patients in a pilot study. Dissociation is not only a critical symptom of BPD but has also been associated with higher risk for self-mutilation and depression. We conducted a whole blood gene expression profile analysis using quantitative PCR in 31 female inpatients with BPD. For each individual, two samples were drawn during a state of high tension and dissociation, while two samples were drawn at non-tension states. There was no association between gene expression and tension states. However, we could show that Interleukin-6 was positively correlated to dissociation scores, whereas Guanine nucleotide-binding protein G(s) subunit alpha isoforms, Mitogen-activated protein kinase 3 and 8, Guanine nucleotide-binding protein G(i) subunit alpha-2, Beta-arrestin-1 and 2, and Cyclic AMP-responsive element-binding protein were negatively correlated to dissociation. Our data point to a potential association of dissociation levels with the expression of genes involved in immune system regulation as well as cellular signalling/second-messenger systems. Major limitations of the study are the the possibly heterogeneous cell proportions in whole blood and the heterogeneous medication.

Peripheral biomarkers in animal models of major depressive disorder

Investigations of preclinical biomarkers for major depressive disorder (MDD) encompass the quantification of proteins, peptides, mRNAs, or small molecules in blood or urine of animal models. Most studies aim at characterising the animal model by including the assessment of analytes or hormones affected in depressive patients. The ultimate objective is to validate the model to better understand the neurobiological basis of MDD. Stress hormones or inflammation-related analytes associated with MDD are frequently measured. In contrast, other investigators evaluate peripheral analytes in preclinical models to translate the results in clinical settings afterwards. Large-scale, hypothesis-free studies are performed in MDD models to identify candidate biomarkers. Other studies wish to propose new targets for drug discovery. Animal models endowed with predictive validity are investigated, and the assessment of peripheral analytes, such as stress hormones or immune molecules, is comprised to increase the confidence in the target. Finally, since the mechanism of action of antidepressants is incompletely understood, studies investigating molecular alterations associated with antidepressant treatment may include peripheral analyte levels. In conclusion, preclinical biomarker studies aid the identification of new candidate analytes to be tested in clinical trials. They also increase our understanding of MDD pathophysiology and help to identify new pharmacological targets.

Mass spectrometry for the detection of potential psychiatric biomarkers

The search for molecules that can act as potential biomarkers is increasing in the scientific community, including in the field of psychiatry. The field of proteomics is evolving and its indispensability for identifying biomarkers is clear. Among proteomic tools, mass spectrometry is the core technique for qualitative and quantitative identification of protein markers. While significant progress has been made in the understanding of biomarkers for neurodegenerative diseases such as Alzheimer's disease, multiple sclerosis and Parkinson's disease, psychiatric disorders have not been as extensively investigated. Recent and successful applications of mass spectrometry-based proteomics in fields such as cardiovascular disease, cancer, infectious diseases and neurodegenerative disorders suggest a similar path for psychiatric disorders. In this brief review, we describe mass spectrometry and its use in psychiatric biomarker research and highlight some of the possible challenges of undertaking this type of work. Further, specific examples of candidate biomarkers are highlighted. A short comparison of proteomic with genomic methods for biomarker discovery research is presented. In summary, mass spectrometry-based techniques may greatly facilitate ongoing efforts to understand molecular mechanisms of psychiatric disorders.

The epigenetics of maternal cigarette smoking during pregnancy and effects on child development

The period of in utero development is one of the most critical windows during which adverse intrauterine conditions and exposures can influence the growth and development of the fetus as well as the child's future postnatal health and behavior. Maternal cigarette smoking during pregnancy remains a relatively common but nonetheless hazardous in utero exposure. Previous studies have associated prenatal smoke exposure with reduced birth weight, poor developmental and psychological outcomes, and increased risk for diseases and behavioral disorders later in life. Researchers are now learning that many of the mechanisms whereby maternal smoke exposure may affect key pathways crucial for proper fetal growth and development are epigenetic in nature. Maternal cigarette smoking during pregnancy has been associated with altered DNA methylation and dysregulated expression of microRNA, but a deeper understanding of the epigenetics of maternal cigarette smoking during pregnancy as well as how these epigenetic changes may affect later health and behavior remain to be elucidated. This article seeks to explore many of the previously described epigenetic alterations associated with maternal cigarette smoking during pregnancy and assess how such changes may have consequences for both fetal growth and development, as well as later child health, behavior, and well-being. We also outline future directions for this new and exciting field of research.

The long-term impact of early adversity on late-life psychiatric disorders

Early adversity is a strong and enduring predictor of psychiatric disorders including mood disorders, anxiety disorders, substance abuse or dependence, and posttraumatic stress disorder. However, the mechanisms of this effect are not well understood. The purpose of this review is to summarize and integrate the current research knowledge pertaining to the long-term effects of early adversity on psychiatric disorders, particularly in late life. We explore definitional considerations including key dimensions of the experience such as type, severity, and timing of adversity relative to development. We then review the potential biological and environmental mediators and moderators of the relationships between early adversity and psychiatric disorders. We conclude with clinical implications, methodological challenges and suggestions for future research.

[Endophenotypes: the molecular biology point of view]

Endophenotypes are proposed for a better understanding of the molecular substrate underlying psychiatric disorders vulnerability. In this review, we discuss key points of the definition of endophenotypes from the molecular biology point of view. First, we examine the concept of heritability of endophenotype, which does not directly explain the molecular mechanisms responsible for the studied disorder Indeed, we discuss the necessity to better decipher the functional role of polymorphisms associated to endophenotypes, especially if those endophenotypes would be assigned a clinical and biological value. The complexity of endophenotypes definition and use in psychiatric research is also illustrated by the complexity of the human genome organization and gene networks as well as by the gene x environment interactions and also the possible existence of phenocopies.

Responder and nonresponder patients exhibit different peripheral transcriptional signatures during major depressive episode

To date, it remains impossible to guarantee that short-term treatment given to a patient suffering from a major depressive episode (MDE) will improve long-term efficacy. Objective biological measurements and biomarkers that could help in predicting the clinical evolution of MDE are still warranted. To better understand the reason nearly half of MDE patients respond poorly to current antidepressive treatments, we examined the gene expression profile of peripheral blood samples collected from 16 severe MDE patients and 13 matched controls. Using a naturalistic and longitudinal design, we ascertained mRNA and microRNA (miRNA) expression at baseline, 2 and 8 weeks later. On a genome-wide scale, we detected transcripts with roles in various biological processes as significantly dysregulated between MDE patients and controls, notably those involved in nucleotide binding and chromatin assembly. We also established putative interactions between dysregulated mRNAs and miRNAs that may contribute to MDE physiopathology. We selected a set of mRNA candidates for quantitative reverse transcriptase PCR (RT-qPCR) to validate that the transcriptional signatures observed in responders is different from nonresponders. Furthermore, we identified a combination of four mRNAs (PPT1, TNF, IL1B and HIST1H1E) that could be predictive of treatment response. Altogether, these results highlight the importance of studies investigating the tight relationship between peripheral transcriptional changes and the dynamic clinical progression of MDE patients to provide biomarkers of MDE evolution and prognosis.

The genetics of alcohol dependence: advancing towards systems-based approaches

BACKGROUND

Personalized treatment for psychopathologies, in particular alcoholism, is highly dependent upon our ability to identify patterns of genetic and environmental effects that influence a person's risk. Unfortunately, array-based whole genome investigations into heritable factors that explain why one person becomes dependent upon alcohol and another does not, have indicated that alcohol's genetic architecture is highly complex. That said, uncovering and interpreting the missing heritability in alcohol genetics research has become all the more important, especially since the problem may extend to our inability to model the cumulative and combinatorial relationships between common and rare genetic variants. As numerous studies begin to illustrate the dependency of alcohol pharmacotherapies on an individual's genotype, the field is further challenged to identify new ways to transcend agnostic genomewide association approaches. We discuss insights from genetic studies of alcohol related diseases, as well as issues surrounding alcohol's genetic complexity and etiological heterogeneity. Finally, we describe the need for innovative systems-based approaches (systems genetics) that can provide additional statistical power that can enhance future gene-finding strategies and help to identify heretofore-unrealized mechanisms that may provide new targets for prevention/treatments efforts. Emerging evidence from early studies suggest that systems genetics has the potential to organize our neurological, pharmacological, and genetic understanding of alcohol dependence into a biologically plausible framework that represents how perturbations across evolutionarily robust biological systems determine susceptibility to alcohol dependence.