Biomarkers in psychiatry: drawbacks and potential for misuse

A Machine Learning Analysis of Big Metabolomics Data for Classifying Depression: Model Development and Validation

BACKGROUND

Many metabolomics studies of depression have been performed, but these have been limited by their scale. A comprehensive in silico analysis of global metabolite levels in large populations could provide robust insights into the pathological mechanisms underlying depression and candidate clinical biomarkers.

METHODS

Depression-associated metabolomics was studied in 2 datasets from the UK Biobank database: participants with lifetime depression (N = 123,459) and participants with current depression (N = 94,921). The Whitehall II cohort (N = 4744) was used for external validation. CatBoost machine learning was used for modeling, and Shapley additive explanations were used to interpret the model. Fivefold cross-validation was used to validate model performance, training the model on 3 of the 5 sets with the remaining 2 sets for validation and testing, respectively. Diagnostic performance was assessed using the area under the receiver operating characteristic curve.

RESULTS

In the lifetime depression and current depression datasets and sex-specific analyses, 24 significantly associated metabolic biomarkers were identified, 12 of which overlapped in the 2 datasets. The addition of metabolic features slightly improved the performance of a diagnostic model using traditional (nonmetabolomics) risk factors alone (lifetime depression: area under the curve 0.655 vs. 0.658 with metabolomics; current depression: area under the curve 0.711 vs. 0.716 with metabolomics).

CONCLUSIONS

The machine learning model identified 24 metabolic biomarkers associated with depression. If validated, metabolic biomarkers may have future clinical applications as supplementary information to guide early and population-based depression detection.

Transdiagnostic Associations between Anger Hostility and Chemokine Interferon-gamma Inducible Protein 10

Objective

Many psychiatric disorders are linked to low grade systemic inflammation as measured by systemic cytokine levels. Exploration of cytokines and immune activity and their role in psychiatric symptoms may inform pathobiology and treatment opportunities. The aim of this study is to explore if there are associations between cytokines and psychiatric symptom clusters. Comparison between patients regularly using and those not using psychotropic medication is also conducted.

Methods

This was a cross sectional naturalistic study with 132 participants from a general open inpatient psychiatric ward at the Nordland Hospital Trust, Norway. Serum levels of 28 different cytokines were assessed. Psychiatric symptoms the last week were assessed by a self-rating scale (Symptom check list, SCL-90-R) and grouped in defined clusters. Multiple linear regression model was used for statistical analyses of associations between levels of cytokines and symptoms, adjusting for possible confounding factors.

Results

We found a positive association (p = 0.009) between the chemokine interferon-gamma inducible protein 10 (CXCL 10; IP-10) and the anger hostility cluster. No associations were found between the other symptom clusters and cytokines. IP-10 and the anger hostility cluster were positively associated (p = 0.002) in the subgroup of patients using psychotropic medication, not in the subgroup not using psychotropic medication.

Conclusion

Our analyses revealed a significant positive association between the symptom cluster anger hostility in SCL-90-R and the chemokine IP-10 in the subgroup of patients using psychotropic medications.

The Relationship between Depression Severity and Prefrontal Hemodynamic Changes in Adolescents with Major Depression Disorder: A Functional Near-infrared Spectroscopy Study

Objective

: Numerous studies have identified hemodynamic changes in adults with major depressive disorder (MDD) by using functional near-infrared spectroscopy (fNIRS). However, studies on adolescents with MDD are limited. As adolescence is a stage of rapid brain development, differences may occur depending on age. This study used fNIRS as an objective tool to investigate hemodynamic changes in the frontal lobe according to depression severity and age in adolescents with MDD.

Methods

: Thirty adolescents (12 aged 12-15 years and 18 aged 16-18 years) were retrospectively investigated. The Children's Depression Inventory was used as a psychiatric evaluation scale, fNIRS was used as an objective brain function evaluation tool, and the Verbal Fluency Test was performed.

Results

: During the Verbal Fluency Test, in the younger MDD group, oxygenated-hemoglobin concentration increased in the right dorsolateral prefrontal cortex region as the severity of depression increased. In the older MDD group, the oxygenated-hemoglobin concentration decreased in the right dorsolateral prefrontal cortex region as the severity of depression increased.

Conclusion

: These results suggest that fNIRS may be an objective tool for identifying age differences among adolescents with MDD. To generalize the results and verify fNIRS as a potential biomarker tool, follow-up studies with a larger sample group should be conducted.

Prediction and Validation of Hub Genes Related to Major Depressive Disorder Based on Co-expression Network Analysis

Major depressive disorder (MDD) is generally among the most prevalent psychiatric illnesses. Significant advances have occurred in comprehension of the MDD biology. However, it is still essential to recognize new biomarkers for potential targeted treatment of patients with MDD. The present work deals with in-depth comparative computational analyses to obtain new insights, such as gene ontology and pathway enrichment analyses and weighted gene co-expression network analysis (WGCNA) through gene expression dataset. The expression of selected hub-genes was validated in MDD patients using quantitative real-time PCR (RT-qPCR). We found that MDD progression includes the turquoise module genes (p-value = 1e-18, r = 0.97). According to gene enrichment analysis, the cytokine-mediated signaling pathway mostly involves genes in this module. By selection of four candidate hub-genes (IL6, NRG1, TNF, and BDNF), RT-qPCR validation was performed. A significant NRG1 downregulation was revealed by the RT-qPCR outcomes in MDD. In MDD patients, TNF and IL6 expression were considerably higher, and no considerable differences were found in the BDNF expression. Ultimately, based on ROC analyses, IL6, NRG1, and TNF had a higher MDD diagnostic performance. Therefore, our study presents information on the intricate association between MDD development and cytokine-mediated signaling, thus providing new rationales to develop new therapeutic approaches.

Dopamine D2 receptor antagonist modulates rTMS-induced pain experiences and corticospinal excitability dependent on stimulation targets

Both the primary motor cortex (M1) and dorsolateral prefrontal cortex (DLPFC) rTMS have the potential to reduce certain chronic pain conditions. However, the analgesic mechanisms remain unclear, in which M1- and DLPFC-rTMS may have different impact on the release of dopamine receptor D2 neurotransmissions (DRD2). Using a double-blind, randomised, sham- and placebo-controlled design, this study investigated the influence of DRD2 antagonist on rTMS-induced analgesia and corticospinal excitability across the M1 and DLPFC. Healthy participants in each group (M1, DLPFC, or Sham) received an oral dose of chlorpromazine or placebo before the delivery of rTMS in two separate sessions. Heat pain and cortical excitability were assessed before drug administration and after rTMS intervention. DRD2 antagonist selectively abolished the increased heat pain threshold induced by DLPFC stimulation and increased pain unpleasantness. The absence of analgesic effects in DLPFC stimulation was not accompanied by plastic changes in the corticospinal pathway. In contrast, DRD2 antagonist increased corticospinal excitability and rebalanced excitation-inhibition relationship following motor cortex stimulation, although there were no clear changes in pain experiences. These novel findings together highlight the influence of dopaminergic neurotransmission on rTMS-induced analgesia and corticospinal excitability dependent on stimulation targets.

Psychotic disorders as a framework for precision psychiatry

People with psychotic disorders can show marked interindividual variations in the onset of illness, responses to treatment and relapse, but they receive broadly similar clinical care. Precision psychiatry is an approach that aims to stratify people with a given disorder according to different clinical outcomes and tailor treatment to their individual needs. At present, interindividual differences in outcomes of psychotic disorders are difficult to predict on the basis of clinical assessment alone. Therefore, current research in psychosis seeks to build models that predict outcomes by integrating clinical information with a range of biological measures. Here, we review recent progress in the application of precision psychiatry to psychotic disorders and consider the challenges associated with implementing this approach in clinical practice.

The various role of microRNAs in breast cancer angiogenesis, with a special focus on novel miRNA-based delivery strategies

After skin malignancy, breast cancer is the most widely recognized cancer detected in women in the United States. Breast cancer (BCa) can happen in all kinds of people, but it's much more common in women. One in four cases of cancer and one in six deaths due to cancer are related to breast cancer. Angiogenesis is an essential factor in the growth of tumors and metastases in various malignancies. An expanded level of angiogenesis is related to diminished endurance in BCa patients. This function assumes a fundamental part inside the human body, from the beginning phases of life to dangerous malignancy. Various factors, referred to as angiogenic factors, work to make a new capillary. Expanding proof demonstrates that angiogenesis is managed by microRNAs (miRNAs), which are small non-coding RNA with 19-25 nucleotides. MiRNA is a post-transcriptional regulator of gene expression that controls many critical biological processes. Endothelial miRNAs, referred to as angiomiRs, are probably concerned with tumor improvement and angiogenesis via regulation of pro-and anti-angiogenic factors. In this article, we reviewed therapeutic functions of miRNAs in BCa angiogenesis, several novel delivery carriers for miRNA-based therapeutics, as well as CRISPR/Cas9 as a targeted therapy in breast cancer.

The Role of Acupuncture in Treating a Patient with a Gambling Disorder

Background

Addiction is a chronic/relapsing disorder characterized by compulsive seeking and continuous involvement despite dangerous consequences. It causes long-term changes in the brain. Gambling disorder is a nonsubstance behavioral addiction. An important feature of gambling disorder is maladaptive gambling behavior that is persistent and repetitive, and interferes with patients' personal lives, families, and/or activities. Acupuncture is a nonpharmacologic therapeutic modality for managing addiction, with good results.

Case

A 32-year-old man with a gambling disorder was referred from a psychiatry department. The patient had a history of gambling since high school. He began to gamble in larger amounts in 2019. The patient got antiseizure, antidepressant, and antipsychotic medications, and cognitive behavioral therapy in the psychiatry department. Manual acupuncture therapy was performed at GV 20, Ex-HN 1, Ex-HN 3, PC 6, ST 40, and LR 3. Electroacupuncture was performed at LI 4, LI 11, ST 36, SP 6, and ST 25. Laser acupuncture was performed at NADA protocol bilateral ear points. The patient also received scalp acupuncture for extrapyramidal symptoms After this combination of acupuncture therapy for 8 sessions, with pharmacotherapy and psychotherapy, the patient's condition improved.

Conclusions

Acupuncture produces positive results in patient with gambling disorders. It helps regulate the reward system; stimulates release of neurotransmitters in the brain; produces neuroprotective effects; and activates certain brain areas to suppress impulsivity and craving and to balance emotions. Acupuncture is thought to be related to increased blood flow in the frontal lobe, thereby increasing nerve metabolism, as well as regulating dopamine in the basal ganglia. A combination of acupuncture, pharmacologic agents, and psychotherapy has a positive synergistic effect in patients with gambling disorder.

Among-individual differences in auditory and physical cognitive abilities in zebra finches

Among-individual variation in performance on cognitive tasks is ubiquitous across species that have been examined, and understanding the evolution of cognitive abilities requires investigating among-individual variation because natural selection acts on individual differences. However, relatively little is known about the extent to which individual differences in cognition are determined by domain-specific compared with domain-general cognitive abilities. We examined individual differences in learning speed of zebra finches across seven different tasks to determine the extent of domain-specific versus domain-general learning abilities, as well as the relationship between learning speed and learning generalization. Thirty-two zebra finches completed a foraging board experiment that included visual and structural discriminations, and then these same birds went through an acoustic operant discrimination experiment that required discriminating between different natural categories of acoustic stimuli. We found evidence of domain-general learning abilities as birds' relative performance on the seven learning tasks was weakly repeatable and a principal components analysis found a first principal component that explained 36% of the variance in performance across tasks with all tasks loading unidirectionally on this component. However, the few significant correlations between tasks and high repeatability within each experiment suggest the potential for domain-specific abilities. Learning speed did not influence an individual's ability to generalize learning. These results suggest that zebra finch performance across visual, structural, and auditory learning relies upon some common mechanism; some might call this evidence of "general intelligence"(g), but it is also possible that this finding is due to other noncognitive mechanisms such as motivation.

Association between brain-derived neurotropic factor (BDNF), high-sensitivity C-reactive protein (hs-CRP) and psychiatric symptoms in medicated and unmedicated patients

BACKGROUND

There is evidence that brain-derived neurotropic factor (BDNF) plays a protective role in the brain. Peripheral levels of BDNF correlate with its concentration in the brain. Previous studies have revealed lower serum BDNF levels in patients with mental illnesses. In most studies serum BDNF correlates negatively with psychiatric disorders and disease severity. Most studies in this field are on psychiatric diagnosis and personality traits. The aim of our study is to explore associations between general psychiatric symptoms, independent of diagnostic groups, and serum BDNF as well as the inflammatory biomarker high-sensitive CRP (hs-CRP). Comparison between the group regularly using psychotropic medication and those not using psychotropic medication is conducted.

METHODS

The study is a cross sectional study with 132 participants from a general open inpatient psychiatric ward at the Nordland Hospital Trust, Bodoe, Norway. Participants were assessed on serum levels of BDNF and hs-CRP. Psychiatric symptoms were assessed by a self-rating scale (Symptom check list, SCL-90- R). Multiple linear regression model was used for statistical analyses of associations between levels of BDNF, hs-CRP and symptoms.

RESULTS

We found a positive association (p < 0.05), for most SCL-90 symptom clusters with BDNF in the psychotropic medication-free group. No associations were found in the group of patients using psychotropic medication, except one, the paranoid ideation cluster (p 0.022). No associations were found between hs-CRP and symptom clusters.

CONCLUSION

We found no relation between symptom clusters and the inflammatory biomarker hs-CRP. Serum BDNF levels were positively associated with intensity of psychiatric symptoms in the group of patients not using psychotropic medication. Our findings are in conflict with several previous studies reporting increased hs-CRP as well as decreased rather than increased BDNF in mental suffering. Patients on psychotropic medication may not require the same upregulation because the medication is modulating the underlying biological pathology.

Biological Diagnosis of Depression: A Biomarker Panel from Several Nonspecial Indicators Instead of the Specific Biomarker(s)

It is a consensus that the diagnosis efficiency of depression is rather low in clinic. The traditional way of diagnosing depression by symptomatology is flawed. Recent years, a growing body of evidence has underlined the importance of physiological indicators in the diagnosis of depression. However, the diagnosis of depression is difficult to be like some common clinical diseases, which have clear physiological indicators. A single physiological index provides limited information to clinicians and is of little help in the diagnosis of depression. Thus, it is more rational and practical to diagnose depression with a biomarker panel, which covers a few non-specific indicators, such as hormones, cytokines, and neurotrophins. This open review suggested that biomarker panel had a bright future in creating a new model of depression diagnosis or at least providing a reference to the existing depression criteria. The viewpoint is also the future of other psychiatric diagnosis.

The applicability of the Beck Depression Inventory and Hamilton Depression Scale in the automatic recognition of depression based on speech signal processing

Depression is a growing problem worldwide, impacting on an increasing number of patients, and also affecting health systems and the global economy. The most common diagnostical rating scales of depression are self-reported or clinician-administered, which differ in the symptoms that they are sampling. Speech is a promising biomarker in the diagnostical assessment of depression, due to non-invasiveness and cost and time efficiency. In our study, we try to achieve a more accurate, sensitive model for determining depression based on speech processing. Regression and classification models were also developed using a machine learning method. During the research, we had access to a large speech database that includes speech samples from depressed and healthy subjects. The database contains the Beck Depression Inventory (BDI) score of each subject and the Hamilton Rating Scale for Depression (HAMD) score of 20% of the subjects. This fact provided an opportunity to compare the usefulness of BDI and HAMD for training models of automatic recognition of depression based on speech signal processing. We found that the estimated values of the acoustic model trained on BDI scores are closer to HAMD assessment than to the BDI scores, and the partial application of HAMD scores instead of BDI scores in training improves the accuracy of automatic recognition of depression.

Potential biomarkers of major depression diagnosis and chronicity

BACKGROUND

Molecular biomarkers are promising tools to be routinely used in clinical psychiatry. Among psychiatric diseases, major depression disorder (MDD) has gotten attention due to its growing prevalence and morbidity.

METHODS

We tested some peripheral molecular parameters such as serum mature Brain-Derived Neurotrophic Factor (mBDNF), plasma C-Reactive Protein (CRP), serum cortisol (SC), and the salivary Cortisol Awakening Response (CAR), as well as the Pittsburgh sleep quality inventory (PSQI), as part of a multibiomarker panel for potential use in MDD diagnosis and evaluation of disease's chronicity using regression models, and ROC curve.

RESULTS

For diagnosis model, two groups were analyzed: patients in the first episode of major depression (MD: n = 30) and a healthy control (CG: n = 32). None of those diagnosis models tested had greater power than Hamilton Depression Rating Scale-6. For MDD chronicity, a group of patients with treatment-resistant major depression (TRD: n = 28) was tested across the MD group. The best chronicity model (p < 0.05) that discriminated between MD and TRD included four parameters, namely PSQI, CAR, SC, and mBDNF (AUC ROC = 0.99), with 96% of sensitivity and 93% of specificity.

CONCLUSION

These results indicate that changes in specific biomarkers (CAR, SC, mBDNF and PSQI) have potential on the evaluation of MDD chronicity, but not for its diagnosis. Therefore, these findings can contribute for further studies aiming the development of a stronger model to be commercially available and used in psychiatry clinical practice.

Screening approaches for identifying fetal alcohol spectrum disorder in children, adolescents, and adults: A systematic review

BACKGROUND

Fetal alcohol spectrum disorder (FASD) is a prevalent neurodevelopmental disorder that is caused by prenatal alcohol exposure (PAE) and associated with a range of cognitive, affective, and health concerns. Although the identification of FASD can facilitate the provision of interventions and support, and plays a protective role against adverse outcomes, there are high rates of missed detection. The identification of FASD via screening may improve its recognition across settings. The current systematic review examined the available evidence on FASD screening tools and approaches across age groups and settings.

METHODS

A systematic search was carried out for both peer-reviewed studies and gray literature sources published between January 1990 and May 2020 and was preregistered with PROSPERO (#CRD42019122077). Studies included in the review focused on human applications of FASD screening in children, adolescents, and adults. The quality of the studies was assessed using the QUADAS-2 and GRADE frameworks.

RESULTS

The search yielded 20 screening tools and approaches across 45 studies, broadly characterized in 2 groups. The first group included approaches currently in use that aim to identify individuals at risk of FASD using a range of markers (n = 19) or associated sentinel dysmorphic facial features (n = 6). Another group of studies, characterized as emerging, focused on identifying promising biomarkers of PAE/FASD (n = 20). Overall, we identified limited research supporting the psychometric properties of most screening approaches. The quality review provided evidence of bias due to the common use of case-control designs and lack of adequate reference standards.

CONCLUSIONS

Although several FASD screening tools and approaches are available for use across a range of age groups and settings, the overall evidence base supporting their psychometric properties is weak, with most studies demonstrating significant risk of bias. Service providers should exercise caution in selecting and implementing FASD screening tools given these limitations. It is critically important to accurately identify individuals with FASD across ages and settings to support healthy outcomes. Thus, there is a pressing need for additional research in this area, particularly validation studies in large and representative samples using robust methodological approaches.

Biomarkers of Major Depressive Disorder: Knowing is Half the Battle

Major depressive disorder (MDD) is a heterogeneous disease which is why there are currently no specific methods to accurately test the severity, endophenotype or therapy response. This lack of progress is partly attributed to the com-plexity and variability of depression, in association with analytical variability of clinical literature and the wide number of theoretically complex biomarkers. The literature accessible, indicates that markers involved in inflammatory, neuro-trophic and metabolic processes and components of neurotransmitters and neuroendocrine systems are rather strong indicators to be considered clinically and can be measured through genetic and epigenetic, transcriptomic and proteomic, metabolomics and neuroimaging assessments. Promising biologic systems/markers found were i.e., growth biomarkers, endocrine markers, oxidant stress markers, proteomic and chronic inflammatory markers, are discussed in this review. Several lines of evidence suggest that a portion of MDD is a dopamine agonist-responsive subtype. This review analyzes concise reports on the pathophysiological biomarkers of MDD and therapeutic reactions via peripheral developmental factors, inflammative cytokines, endocrine factors and metabolic markers. Various literatures also support that endocrine and metabolism changes are associated with MDD. Accumulating evidence suggests that at least a portion of MDD patients show characteristics pathological changes regarding different clinical pathological biomarkers. By this review we sum up all the different biomarkers playing an important role in the detection or treatment of the different patients suffering from MDD. The review also gives an overview of different biomarker's playing a potential role in modulating effect of MDD.

Default mode network activity in depression subtypes

Depression continues to carry a major disease burden worldwide, with limitations on the success of traditional pharmacological or psychological treatments. Recent approaches have therefore focused upon the neurobiological underpinnings of depression, and on the "individualization" of depression symptom profiles. One such model of depression has divided the standard diagnostic criteria into four "depression subtypes", with neurological and behavioral pathways. At the same time, attention has been focused upon the region of the brain known as the "default mode network" (DMN) and its role in attention and problem-solving. However, to date, no review has been published of the links between the DMN and the four subtypes of depression. By searching the literature studies from the last 20 years, 62 relevant papers were identified, and their findings are described for the association they demonstrate between aspects of the DMN and the four depression subtypes. It is apparent from this review that there are potential positive clinical and therapeutic outcomes from focusing upon DMN activation and connectivity, via psychological therapies, transcranial magnetic stimulation, and some emerging pharmacological models.

Biomarkers in psychiatry: a clinician's viewpoint

INTRODUCTION

The dearth of biomarkers limits the precision of our research into pathogenesis of psychiatric disorders and has slowed down the development of new drugs. In clinical practice, it undermines the validity of psychiatric diagnoses and hampers the delivery of personalized treatment.

SOURCES OF DATA

The data quoted in this paper are gathered from a range of sources encompassing scientific and journalistic both in print and electronic.

AREAS OF AGREEMENT

Availability of clinically useful biomarkers will improve the prognosis and outcome of psychiatric patients by helping in early diagnosis and delivery of individualized treatment.

AREAS OF CONTROVERSY

The cross-sectional and longitudinal observation of psychopathology is the bedrock of current clinical practice. Are psychiatric biomarkers advanced enough to supplant it?

GROWING POINTS

The need for biomarkers of psychiatric disorders has become more acute with the advent of new treatments which require precision and an individualized approach.

AREAS TIMELY FOR DEVELOPING RESEARCH

Identification and deployment of intermediate phenotypes in classification, research and clinical practice of psychiatry.

Cannabis use influence on peripheral brain-derived neurotrophic factor levels in antipsychotic-naïve first-episode psychosis

The objective of this study is to determine whether cannabis influences BDNF levels in patients with psychosis (FEP) and healthy volunteers (HV) to help understand the role of BDNF in psychosis. We assessed the association between BDNF and cannabis in a cohort of FEP antipsychotic-naïve patients and HV, whilst controlling for other potential confounding factors. 70 FEP drug-naive patients and 57 HV were recruited. A sociodemographic variable collection, structured clinical interview, weight and height measurement, substance use determination, and blood collection to determine BDNF levels by ELISA analysis were done. In FEP patients, cannabis use was associated with BDNF levels (high cannabis use was associated with lower BDNF levels). Moreover, cannabis use was statistically significantly associated with age (high use of cannabis was associated with younger age). In HV, no relationship between cannabis use and BDNF levels was observed. Otherwise, cannabis use was significantly associated with tobacco use, so that high cannabis users were also high tobacco users. This study showed a different association between cannabis use and BDNF levels in FEP patients compared with HV, particularly, with high doses of cannabis. These findings may help understand the deleterious effects of cannabis in some vulnerable individuals, as well as discrepancies in the literature.

Thiol/Disulfide Homeostasis in Bipolar and Unipolar Depression

Objective

Bipolar disorder and unipolar depressive disorder are complex phenotypes. There appear to be phenotypical, mechanistic, and therapeutic differences between bipolar depression (BD) and unipolar depression (UD). There is a need for understanding the underlying biological variation between these clinical entities. The role of oxidative processes underlying bipolar disorder and depression has been demonstrated. Thiol-disulfide homeostasis (TDH) is a recent oxidative stress marker. In this study, we aimed to inspect patients with bipolar depression and unipolar depression in terms of thiol-disulfide balance and to compare them with healthy controls.

Methods

Patients admitted to the outpatient clinic of Ankara Numune Training and Research Hospital and diagnosed either as a depressive episode with bipolar disorder (n = 37) or unipolar depression (n = 24) according to DSM-5 criteria, along with healthy controls (HC) (n = 50), were included in the study. Native thiol, total thiol, and disulfide levels were compared across the groups.

Results

In comparison to HC, both BD and UD groups had higher disulfide levels, disulfide/native thiol ratio, and disulfide/total thiol ratio. No significant differences between BD and UD were detected in terms of disulfide level, disulfide/native thiol ratio, and disulfide/total thiol ratio.

Conclusion

Increased levels of disulfide, native thiol, and disulfide/total thiol ratios compared to healthy controls in both UD and BD groups may be indicative of the presence of oxidative damage in these two clinical conditions. To clarify the role of oxidative stress in the pathophysiology of depressive disorders and investigate TDH, longitudinal studies in patients with medication-free UD and BD are required.

Platelet Serotonin Concentration Is Associated with Illness Duration in Schizophrenia and Chronological Age in Depression

OBJECTIVE

Impaired serotonergic neurotransmission has been implicated in the pathogenesis of depression and schizophrenia. Blood platelets have been used for years as a peripheral model of neuronal serotonin dynamics. The objective was to investigate platelet count and serotonin concentration in patients with depression and schizophrenia, in an attempt to ascertain their clinical usefulness.

METHODS

953 participants were included in the study, 329 patients with depression, 339 patients with schizophrenia and 285 healthy controls. ELISA was used to assess platelet serotonin concentrations.

RESULTS

There were no statistically significant differences among groups regarding age, total platelet count and serotonin concentration. Linear regression analyses revealed inverse correlations between platelet serotonin concentration and age of patients with depression and healthy individuals, as well as between platelet serotonin concentration and illness duration in patients with schizophrenia. In other words, longer illness duration in patients with schizophrenia, and higher age in patients with depression and healthy individuals was associated with lower platelet serotonin concentrations.

CONCLUSION

Platelet count and serotonin concentration did not prove to be of diagnostic value in differentiating patients and healthy individuals. However, illness duration in patients with schizophrenia may be associated with reduced concentrations of platelet serotonin.

Preventing discrimination based on psychiatric risk biomarkers

Recent studies have identified genomic and nongenomic psychiatric risk biomarkers (PRBs; e.g., genomic variants, blood analytes, gray matter volume). PRBs may soon become a powerful tool for improving psychiatric care and prevention. PRB research and its translation to clinical care, however, may prove to be a double-edged sword. Mental health stigma and discrimination are already widespread, and data caution that biological explanations of psychiatric disorders can exacerbate these stigmatizing attitudes, increasing the desire for social distance and heightening the perceived dangerousness of the patient. As a reaction to the Human Genome Project and historical concerns about eugenics, the international community mobilized to establish legislation to prevent genomic discrimination. But in most countries, these laws are limited to few contexts (e.g., employment, health insurance), and very few countries protect against discrimination based on nongenomic risk biomarkers. Like genomic PRBs, nongenomic PRBs provide information regarding risk for stigmatized psychiatric disorders and have similar-and in some cases greater-predictive value. Numerous large-scale neuroscience and neurogenomics projects are advancing the identification and translation of PRBs. The prospect of PRB-based stigma however, threatens to undermine the potential benefits of this research. Unbridaled by nonexistent or limited PRB anti-discrimination protections, the threat of PRB-based stigma and discrimination may lead many to forego PRB testing, even if shown to have clinical utility. To maximize the clinical and social benefits of PRB-based technologies, educational campaigns should address mental health and PRB stigma, and lawmakers should carefully consider expanding legislation that prohibits PRB-based discrimination.

Could a blood test for PTSD and depression be on the horizon?

INTRODUCTION

Depression and posttraumatic stress disorder (PTSD) are two complex and debilitating psychiatric disorders that result in poor life and destructive behaviors against self and others. Currently, diagnosis is based on subjective rather than objective determinations leading to misdiagnose and ineffective treatments. Advances in novel neurobiological methods have allowed assessment of promising biomarkers to diagnose depression and PTSD, which offers a new means of appropriately treating patients. Areas covered: Biomarkers discovery in blood represents a fundamental tool to predict, diagnose, and monitor treatment efficacy in depression and PTSD. The potential role of altered HPA axis, epigenetics, NPY, BDNF, neurosteroid biosynthesis, the endocannabinoid system, and their function as biomarkers for mood disorders is discussed. Insofar, we propose the identification of a biomarker axis to univocally identify and discriminate disorders with large comorbidity and symptoms overlap, so as to provide a base of support for development of targeted treatments. We also weigh in on the feasibility of a future blood test for early diagnosis. Expert commentary: Potential biomarkers have already been assessed in patients' blood and need to be further validated through multisite large clinical trial stratification. Another challenge is to assess the relation among several interdependent biomarkers to form an axis that identifies a specific disorder and secures the best-individualized treatment. The future of blood-based tests for PTSD and depression is not only on the horizon but, possibly, already around the corner.

Suggested Biomarkers for Major Depressive Disorder

Currently, the diagnosis of major depressive disorder (MDD) mainly relies on clinical examination and subjective evaluation of depressive symptoms. There is no non-invasive, quantitative test available today for the diagnosis of MDD. In MDD, exploration of biomarkers will be helpful in diagnosing the disorder as well as in choosing a treatment, and predicting the treatment response. In this article, it is aimed to review the findings of suggested biomarkers such as growth factors, cytokines and other inflammatory markers, oxidative stress markers, endocrine markers, energy balance hormones, genetic and epigenetic features, and neuroimaging in MDD and to evaluate how these findings contribute to the pathophysiology of MDD, the prediction of treatment response, severity of the disorder, and identification of subtypes. Among these, the findings related to the brain-derived neurotrophic factor, the hypothalamo-pituitary-adrenal axis, cytokines, and neuroimaging may be strong candidates for being biomarkers MDD, and may provide critical information in understanding biological etiology of depression. Although the findings are not sufficient yet, we think that the results of epigenetic studies will also provide very important contributions to the biomarker research in MDD. The availability of biomarkers in MDD will be an advancement that will facilitate the diagnosis of the disorder, treatment choices in the early stages, and prediction of the course of the disorder.

Using Cognitive Neuroscience to Improve Mental Health Treatment: A Comprehensive Review

Mental health interventions do not yet offer complete, client-defined functional recovery, and novel directions in treatment research are needed to improve the efficacy of available interventions. One promising direction is the integration of social work and cognitive neuroscience methods, which provides new opportunities for clinical intervention research that will guide development of more effective mental health treatments that holistically attend to the biological, social, and environmental contributors to disability and recovery. This article reviews emerging trends in cognitive neuroscience and provides examples of how these advances can be used by social workers and allied professions to improve mental health treatment. We discuss neuroplasticity, which is the dynamic and malleable nature of the brain. We also review the use of risk and resiliency biomarkers and novel treatment targets based on neuroimaging findings to prevent disability, personalize treatment, and make interventions more targeted and effective. The potential of treatment research to contribute to neuroscience discoveries regarding brain change is considered from the experimental-medicine approach adopted by the National Institute of Mental Health. Finally, we provide resources and recommendations to facilitate the integration of cognitive neuroscience into mental health research in social work.

Event-Related Potentials as Biomarkers of Behavior Change Mechanisms in Substance Use Disorder Treatment

Substance use disorders (SUDs) are one of the most prevalent psychiatric conditions and represent a significant public health concern. Substantial research has identified key processes related to reinforcement and cognition for the development and maintenance of SUDs, and these processes represent viable treatment targets for psychosocial and pharmacological interventions. Research on SUD treatments has suggested that most approaches are comparable in effectiveness. As a result, recent work has focused on delineating the underlying mechanisms of behavior change that drive SUD treatment outcome. Given the rapid fluctuations associated with the key neurocognitive processes associated with SUDs, high-temporal-resolution measures of human brain processing, namely event-related potentials (ERPs), are uniquely suited to expand our understanding of the underlying neural mechanisms of change during and after SUD treatment. The value of ERPs in the context of SUD treatment are discussed along with work demonstrating the predictive validity of ERPs as biomarkers of SUD treatment response. Example associations between multiple ERP components and psychosocial and/or pharmacological treatment outcome include the P3a and P3b (in response to neutral and substance-related cues), the attention-related negativities (e.g., N170, N200), the late positive potential, and the error-related negativity. Also addressed are limitations of the biomarker approach to underscore the need for research programs evaluating mechanisms of change. Finally, we emphasize the advantages of ERPs as indices of behavior change in SUD treatment and outline issues relevant for future directions in this context.

The Utility of EEG in Attention Deficit Hyperactivity Disorder: A Replication Study

The routine use of stimulants in pediatrics has increased dramatically over the past 3 decades and the long-term consequences have yet to be fully studied. Since 1978 there have been 7 articles identifying electroencephalogram (EEG) abnormalities, particularly epileptiform discharges in children with attention deficit hyperactivity disorder (ADHD). Many have studied the prevalence of these discharges in this population with varying results. An article published in 2011 suggests that EEG technology should be considered prior to prescribing stimulants to children diagnosed with ADHD due to a high prevalence of epileptiform discharges. The 2011 study found a higher prevalence (26%) of epileptiform discharges when using 23-hour and sleep-deprived EEGs in comparison with other methods of activation (hyperventilation or photostimulation) and conventional EEG. We sought to replicate the 2011 results using conventional EEG with the added qEEG technologies of automatic spike detection and low-resolution electromagnetic tomography analysis (LORETA) brain mapping. Our results showed 32% prevalence of epileptiform discharges, which suggests that an EEG should be considered prior to prescribing stimulant medications.

Is there Progress? An Overview of Selecting Biomarker Candidates for Major Depressive Disorder

Major depressive disorder (MDD) contributes to a significant worldwide disease burden, expected to be second only to heart disease by 2050. However, accurate diagnosis has been a historical weakness in clinical psychiatry. As a result, there is a demand for diagnostic modalities with greater objectivity that could improve on current psychiatric practice that relies mainly on self-reporting of symptoms and clinical interviews. Over the past two decades, literature on a growing number of putative biomarkers for MDD increasingly suggests that MDD patients have significantly different biological profiles compared to healthy controls. However, difficulty in elucidating their exact relationships within depression pathology renders individual markers inconsistent diagnostic tools. Consequently, further biomarker research could potentially improve our understanding of MDD pathophysiology as well as aid in interpreting response to treatment, narrow differential diagnoses, and help refine current MDD criteria. Representative of this, multiplex assays using multiple sources of biomarkers are reported to be more accurate options in comparison to individual markers that exhibit lower specificity and sensitivity, and are more prone to confounding factors. In the future, more sophisticated multiplex assays may hold promise for use in screening and diagnosing depression and determining clinical severity as an advance over relying solely on current subjective diagnostic criteria. A pervasive limitation in existing research is heterogeneity inherent in MDD studies, which impacts the validity of biomarker data. Additionally, small sample sizes of most studies limit statistical power. Yet, as the RDoC project evolves to decrease these limitations, and stronger studies with more generalizable data are developed, significant advances in the next decade are expected to yield important information in the development of MDD biomarkers for use in clinical settings.

A method for reproducible measurements of serum BDNF: comparison of the performance of six commercial assays

Brain-Derived Neurotrophic Factor (BDNF) has attracted increasing interest as potential biomarker to support the diagnosis or monitor the efficacy of therapies in brain disorders. Circulating BDNF can be measured in serum, plasma or whole blood. However, the use of BDNF as biomarker is limited by the poor reproducibility of results, likely due to the variety of methods used for sample collection and BDNF analysis. To overcome these limitations, using sera from 40 healthy adults, we compared the performance of five ELISA kits (Aviscera-Bioscience, Biosensis, Millipore-ChemiKine^TM, Promega-Emax^®, R&D-System-Quantikine^®) and one multiplexing assay (Millipore-Milliplex^®). All kits showed 100% sample recovery and comparable range. However, they exhibited very different inter-assay variations from 5% to 20%. Inter-assay variations were higher than those declared by the manufacturers with only one exception which also had the best overall performance. Dot-blot analysis revealed that two kits selectively recognize mature BDNF, while the others reacted with both pro-BDNF and mature BDNF. In conclusion, we identified two assays to obtain reliable measurements of human serum BDNF, suitable for future clinical applications.

Pharmaco-EEG: A Study of Individualized Medicine in Clinical Practice

Pharmaco-electroencephalography (Pharmaco-EEG) studies using clinical EEG and quantitative EEG (qEEG) technologies have existed for more than 4 decades. This is a promising area that could improve psychotropic intervention using neurological data. One of the objectives in our clinical practice has been to collect EEG and quantitative EEG (qEEG) data. In the past 5 years, we have identified a subset of refractory cases (n = 386) found to contain commonalities of a small number of electrophysiological features in the following diagnostic categories: mood, anxiety, autistic spectrum, and attention deficit disorders, Four abnormalities were noted in the majority of medication failure cases and these abnormalities did not appear to significantly align with their diagnoses. Those were the following: encephalopathy, focal slowing, beta spindles, and transient discharges. To analyze the relationship noted, they were tested for association with the assigned diagnoses. Fisher's exact test and binary logistics regression found very little (6%) association between particular EEG/qEEG abnormalities and diagnoses. Findings from studies of this type suggest that EEG/qEEG provides individualized understanding of pharmacotherapy failures and has the potential to improve medication selection.

Differential expression of microRNA in peripheral blood mononuclear cells as specific biomarker for major depressive disorder patients

Currently, diagnosis and treatment of major depressive disorder (MDD) are based on the patients' description of symptoms, mental status examinations, and clinical behavioral observations, which increases the chance of misdiagnosis. There is a serious need to find a practical biomarker for the proper diagnosis of MDD. This study aimed to explore the possibility of microRNA (miRNA) in peripheral blood mononuclear cells (PBMCs) as specific blood-based biomarker for MDD patients. By using an Affymetrix array that covers 723 human miRNAs, we identified 26 miRNAs with significant changes in expression in PBMCs of MDD patients. Real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis in a larger cohort of 81 MDD patients and 46 healthy controls confirmed that the expression levels of 5 miRNAs (miRNA-26b, miRNA-1972, miRNA-4485, miRNA-4498, and miRNA-4743) were up-regulated. By receiver operating characteristic (ROC) curve analysis, the combining area under the ROC curve (AUC) of these five miRNAs was 0.636 [95% confidence interval (CI): 0.58-0.90]. MiRNA target gene prediction and functional annotation analysis showed that there was a significant enrichment in several pathways associated with nervous system and brain functions, supporting the hypothesis that differentially-regulated miRNAs may be involved in mechanism underlying development of MDD. We conclude that altered expression of miRNAs in PMBCs might be involved in multiple stages of MDD pathogenesis, and thus might be able to serve as specific biomarker for diagnosis of MDD.

Biomarkers in the diagnosis of ADHD--promising directions

The etiology and pathogenesis of attention-deficit/hyperactivity disorder (ADHD) are unclear and a more valid diagnosis would certainly be welcomed. Starting from the literature, we built an hypothetical pyramid representing a putative set of biomarkers where, at the top, variants in DAT1 and DRD4 genes are the best candidates for their associations to neuropsychological tasks, activation in specific brain areas, methylphenidate response and gene expression levels. Interesting data come from the noradrenergic system (norepinephrine transporter, norepinephrine, 3-methoxy-4-hydroxyphenylglycol, monoamine oxidase, neuropeptide Y) for their altered peripheral levels, their association with neuropsychological tasks, symptomatology, drugs effect and brain function. Other minor putative genetic biomarkers could be dopamine beta hydroxylase and catechol-O-methyltransferase. In the bottom, we placed endophenotype biomarkers. A more deep integration of "omics" sciences along with more accurate clinical profiles and new high-throughput computational methods will allow us to identify a better list of biomarkers useful for diagnosis and therapies.

Altered plasma glutathione levels in bipolar disorder indicates higher oxidative stress; a possible risk factor for illness onset despite normal brain-derived neurotrophic factor (BDNF) levels

BACKGROUND

Oxidative stress and neurotrophic factors have been implicated in the pathophysiology of bipolar disorder. Our objective was to determine whether plasma glutathione or brain-derived neurotrophic factor (BDNF) levels were abnormal in bipolar disorder and therefore useful as possible biomarkers.

METHOD

Blood samples were collected from subsyndromal, medicated bipolar I patients (n = 50), recruited from OXTEXT, University of Oxford, and from 50 matched healthy controls. Total and oxidized glutathione levels were measured using an enzymatic recycling method and used to calculate reduced, percentage oxidized, ratio of reduced:oxidized and redox state. BDNF was measured using an enzyme-linked immunoassay. Self-monitored mood scores for the bipolar group were available (Quick Inventory of Depressive Symptomatology and the Altman Self-Rating Mania Scale) over an 8-week period.

RESULTS

Compared with controls, bipolar patients had significantly lower levels of total glutathione and it was more oxidized. BDNF levels were not different. Age of illness onset but not current mood state correlated with total glutathione levels and its oxidation status, so that lower levels of total and reduced glutathione were associated with later onset of disease, not length of illness.

CONCLUSIONS

Plasma glutathione levels and redox state detect oxidative stress even in subsyndromal patients with normal BDNF. It may relate to the onset and development of bipolar disorder. Plasma glutathione appears to be a suitable biomarker for detecting underlying oxidative stress and for evaluating the efficacy of antioxidant intervention studies.

Elevated systemic expression of ER stress related genes is associated with stress-related mental disorders in the Detroit Neighborhood Health Study

BACKGROUND

The role of endoplasmic reticulum (ER) stress response in mental illness is not well understood. Human studies and animal models of depression show elevated brain ER stress response. In addition, some ER stress associated disorders (e.g. cardiovascular disease) show higher rates of depression compared to the general population, raising the possibility that ER stress response contributes to depression risk. It remains unknown, however, if ER stress response is present among individuals suffering from other stress-related mental illness, and whether such a response would be evident in a non-clinical sample. This study tests for systemic changes in ER stress response associated with Major Depressive Disorder (MDD) or post-traumatic stress disorder (PTSD) among community-dwelling individuals.

METHODS

We analyzed expression of BiP, EDEM1, CHOP, and XBP1, the major indicators of ER stress response, with real-time PCR in leukocyte-derived RNA samples from 86 participants of the Detroit Neighborhood Health Study. Participants were selected based on the presence of either past year MDD or past year PTSD; controls were age and sex matched.

RESULTS

Relative to controls, MDD is associated with a 1.34-fold increase in BiP (P=0.004), 1.35-fold increase in EDEM1 (P=0.001), 1.68-fold increase in CHOP (P=0.002), and 1.60-fold increase in XBP1 (P=0.004). These results remained significant after correction for multiple testing. In contrast, PTSD is associated with a 1.27-fold increase in EDEM1 expression only (P=0.027), a result that is attenuated to non-significance following adjustment for multiple testing; however, a subsample of participants with past month PTSD showed elevated expression of BiP and EDEM1 (uncorrected P value 0.049 and 0.017, respectively).

CONCLUSIONS

These data indicate systemic and persistent activation of the ER stress response pathway in MDD among community-dwelling individuals. Systemic activation of the ER stress response may also occur in PTSD among persons with more recent symptoms.

Ownership and technical efficiency of hospitals: evidence from Ghana using data envelopment analysis

Background

In order to measure and analyse the technical efficiency of district hospitals in Ghana, the specific objectives of this study were to (a) estimate the relative technical and scale efficiency of government, mission, private and quasi-government district hospitals in Ghana in 2005; (b) estimate the magnitudes of output increases and/or input reductions that would have been required to make relatively inefficient hospitals more efficient; and (c) use Tobit regression analysis to estimate the impact of ownership on hospital efficiency.

Methods

In the first stage, we used data envelopment analysis (DEA) to estimate the efficiency of 128 hospitals comprising of 73 government hospitals, 42 mission hospitals, 7 quasi-government hospitals and 6 private hospitals. In the second stage, the estimated DEA efficiency scores are regressed against hospital ownership variable using a Tobit model. This was a retrospective study.

Results

In our DEA analysis, using the variable returns to scale model, out of 128 district hospitals, 31 (24.0%) were 100% efficient, 25 (19.5%) were very close to being efficient with efficiency scores ranging from 70% to 99.9% and 71 (56.2%) had efficiency scores below 50%. The lowest-performing hospitals had efficiency scores ranging from 21% to 30%.

Quasi-government hospitals had the highest mean efficiency score (83.9%) followed by public hospitals (70.4%), mission hospitals (68.6%) and private hospitals (55.8%). However, public hospitals also got the lowest mean technical efficiency scores (27.4%), implying they have some of the most inefficient hospitals.

Regarding regional performance, Northern region hospitals had the highest mean efficiency score (83.0%) and Volta Region hospitals had the lowest mean score (43.0%).

From our Tobit regression, we found out that while quasi-government ownership is positively associated with hospital technical efficiency, private ownership negatively affects hospital efficiency.

Conclusions

It would be prudent for policy-makers to examine the least efficient hospitals to correct widespread inefficiency. This would include reconsidering the number of hospitals and their distribution, improving efficiency and reducing duplication by closing or scaling down hospitals with efficiency scores below a certain threshold. For private hospitals with inefficiency related to large size, there is a need to break down such hospitals into manageable sizes.

Biomarkers of PTSD: military applications and considerations

BACKGROUND

Although there are no established biomarkers for posttraumatic stress disorder (PTSD) as yet, biological investigations of PTSD have made progress identifying the pathophysiology of PTSD. Given the biological and clinical complexity of PTSD, it is increasingly unlikely that a single biomarker of disease will be identified. Rather, investigations will more likely identify different biomarkers that indicate the presence of clinically significant PTSD symptoms, associate with risk for PTSD following trauma exposure, and predict or identify recovery. While there has been much interest in PTSD biomarkers, there has been less discussion of their potential clinical applications, and of the social, legal, and ethical implications of such biomarkers.

OBJECTIVE

This article will discuss possible applications of PTSD biomarkers, including the social, legal, and ethical implications of such biomarkers, with an emphasis on military applications.

METHOD

Literature on applications of PTSD biomarkers and on potential ethical and legal implications will be reviewed.

RESULTS

Biologically informed research findings hold promise for prevention, assessment, treatment planning, and the development of prophylactic and treatment interventions. As with any biological indicator of disorder, there are potentially positive and negative clinical, social, legal, and ethical consequences of using such biomarkers.

CONCLUSIONS

Potential clinical applications of PTSD biomarkers hold promise for clinicians, patients, and employers. The search for biomarkers of PTSD should occur in tandem with an interdisciplinary discussion regarding the potential implications of applying biological findings in clinical and employment settings.

Biomarkers in major depressive disorder: the role of mass spectrometry

Major depressive disorder (MDD) is common. Despite numerous available treatments, many individuals fail to improve clinically. MDD continues to be diagnosed exclusively via behavioral rather than biological methods. Biomarkers-which include measurements of genes, proteins, and patterns of brain activity-may provide an important objective tool for the diagnosis of MDD or in the rational selection of treatments. Proteomic analysis and validation of its results as biomarkers is less explored than other areas of biomarker research in MDD. Mass spectrometry (MS) is a comprehensive, unbiased means of proteomic analysis, which can be complemented by directed protein measurements, such as Western Blotting. Prior studies have focused on MS analysis of several human biomaterials in MDD, including human post-mortem brain, cerebrospinal fluid (CSF), blood components, and urine. Further studies utilizing MS and proteomic analysis in MDD may help solidify and establish biomarkers for use in diagnosis, identification of new treatment targets, and understanding of the disorder. The ultimate goal is the validation of a biomarker or a biomarker signature that facilitates a convenient and inexpensive predictive test for depression treatment response and helps clinicians in the rational selection of next-step treatments.

A method for biomarker measurements in peripheral blood mononuclear cells isolated from anxious and depressed mice: β-arrestin 1 protein levels in depression and treatment

A limited number of biomarkers in the central and peripheral systems which are known may be useful for diagnosing major depressive disorders and predicting the effectiveness of antidepressant (AD) treatments. Since 60% of depressed patients do not respond adequately to medication or are resistant to ADs, it is imperative to delineate more accurate biomarkers. Recent clinical studies suggest that β-arrestin 1 levels in human mononuclear leukocytes may be an efficient biomarker. If potential biomarkers such as β-arrestin 1 could be assessed from a source such as peripheral blood cells, then they could be easily monitored and used to predict therapeutic responses. However, no previous studies have measured β-arrestin 1 levels in peripheral blood mononuclear cells (PBMCs) in anxious/depressive rodents. This study aimed to develop a method to detect β-arrestin protein levels through immunoblot analyses of mouse PBMCs isolated from whole blood. In order to validate the approach, β-arrestin levels were then compared in na\"{\i}ve, anxious/depressed mice, and anxious/depressed mice treated with a selective serotonin reuptake inhibitor (fluoxetine, 18~mg/kg/day in the drinking water). The results demonstrated that mouse whole blood collected by submandibular bleeding permitted isolation of enough PBMCs to assess circulating proteins such as β-arrestin 1. β-Arrestin 1 levels were successfully measured in healthy human subject and na\"{\i}ve mouse PBMCs. Interestingly, PBMCs from anxious/depressed mice showed significantly reduced β-arrestin 1 levels. These decreased β-arrestin 1 expression levels were restored to normal levels with chronic fluoxetine treatment. The results suggest that isolation of PBMCs from mice by submandibular bleeding is a useful technique to screen putative biomarkers of the pathophysiology of mood disorders and the response to ADs. In addition, these results confirm that β-arrestin 1 is a potential biomarker for depression.

Diagnostic accuracy of serum brain derived neurotrophic factor concentration in antidepressant naïve patients with first major depression episode

Diagnosing major depressive disorder (MDD) continues to be based on meeting phenomenological and descriptive criteria. As of yet, there is still no non-invasive, peripheral biomarker that would allow for a certain diagnosis of MDD. The objective of this paper is to use the receiver operating characteristic (ROC) analysis to test the diagnostic value of serum concentrations of brain derived neurotrophic factor (BDNF) in diagnosing the first episode of MDD. Among 1014 patients admitted for an initial psychiatric evaluation, antidepressant naïve patients diagnosed with first episode MDD were separated into the test group. Only patients signing an informed consent form were included in the study. Using DSM-IV-TR diagnostic criteria, those patients meeting the MDD criteria (N = 122) and patients not meeting MDD or other psychiatric disorder criteria (N = 142) were differentiated. Subjects with repeated episode MDD (N = 121) and other psychiatric comorbid illnesses (N = 138) in the MDD group were excluded from the study. In the group without MDD or other psychiatric illnesses, patients with physical comorbidities (N = 59) were excluded. The serum concentration of BDNF was determined in all patients using the ELISA assay. Subjects with first episode MDD showed differences in serum BDNF concentrations (ng/mL) in comparison to the control group of patients not meeting the criteria for first episode MDD (mean ± SD; 37.5 ± 13.3 vs. 56.8 ± 6.3; t = 1.372; df = 262; p < 0.01). The ROC analysis established a discriminant diagnostic value of serum BDNF in diagnosing MDD. The area under the curve (AUC) was 0.892 with a 95% confidence level (0.826-0.939), which was statistically significant at p < 0.01. The serum BDNF had a high diagnostic sensitivity of 83.9% and a specificity of 93%. Serum BDNF concentrations appear to be a promising tool in discriminating subjects with MDD from those without MDD.

Potential biomarkers in psychiatry: focus on the cholesterol system

Measuring biomarkers to identify and assess illness is a strategy growing in popularity and relevance. Although already in clinical use for treating and predicting cancer, no biological measurement is used clinically for any psychiatric disorder. Biomarkers could predict the course of a medical problem, and aid in determining how and when to treat. Several studies have indicated that of candidate psychiatric biomarkers detected using proteomic techniques, cholesterol and associated proteins, specifically apolipoproteins (Apos), may be of interest. Cholesterol is necessary for brain development and its synthesis continues at a lower rate in the adult brain. Apos are the protein component of lipoproteins responsible for lipid transport. There is extensive evidence that the levels of cholesterol and Apos may be disturbed in psychiatric disorders, including autistic spectrum disorders (ASD). Here, we describe putative serum biomarkers for psychiatric disorders, and the role of cholesterol and Apos in central nervous system (CNS) disorders.

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

Early-onset major depressive disorder (MDD) is a serious and prevalent psychiatric illness in adolescents and young adults. Current treatments are not optimally effective. Biological markers of early-onset MDD could increase diagnostic specificity, but no such biomarker exists. Our innovative approach to biomarker discovery for early-onset MDD combined results from genome-wide transcriptomic profiles in the blood of two animal models of depression, representing the genetic and the environmental, stress-related, etiology of MDD. We carried out unbiased analyses of this combined set of 26 candidate blood transcriptomic markers in a sample of 15-19-year-old subjects with MDD (N=14) and subjects with no disorder (ND, N=14). A panel of 11 blood markers differentiated participants with early-onset MDD from the ND group. Additionally, a separate but partially overlapping panel of 18 transcripts distinguished subjects with MDD with or without comorbid anxiety. Four transcripts, discovered from the chronic stress animal model, correlated with maltreatment scores in youths. These pilot data suggest that our approach can lead to clinically valid diagnostic panels of blood transcripts for early-onset MDD, which could reduce diagnostic heterogeneity in this population and has the potential to advance individualized treatment strategies.

Functional neuroimaging studies in addiction: multisensory drug stimuli and neural cue reactivity

Neuroimaging studies on cue reactivity have substantially contributed to the understanding of addiction. In the majority of studies drug cues were presented in the visual modality. However, exposure to conditioned cues in real life occurs often simultaneously in more than one sensory modality. Therefore, multisensory cues should elicit cue reactivity more consistently than unisensory stimuli and increase the ecological validity and the reliability of brain activation measurements. This review includes the data from 44 whole-brain functional neuroimaging studies with a total of 1168 subjects (812 patients and 356 controls). Correlations between neural cue reactivity and clinical covariates such as craving have been reported significantly more often for multisensory than unisensory cues in the motor cortex, insula and posterior cingulate cortex. Thus, multisensory drug cues are particularly effective in revealing brain-behavior relationships in neurocircuits of addiction responsible for motivation, craving awareness and self-related processing.

Functional biomarkers of depression: diagnosis, treatment, and pathophysiology

Major depressive disorder (MDD) is a heterogeneous illness for which there are currently no effective methods to objectively assess severity, endophenotypes, or response to treatment. Increasing evidence suggests that circulating levels of peripheral/serum growth factors and cytokines are altered in patients with MDD, and that antidepressant treatments reverse or normalize these effects. Furthermore, there is a large body of literature demonstrating that MDD is associated with changes in endocrine and metabolic factors. Here we provide a brief overview of the evidence that peripheral growth factors, pro-inflammatory cytokines, endocrine factors, and metabolic markers contribute to the pathophysiology of MDD and antidepressant response. Recent preclinical studies demonstrating that peripheral growth factors and cytokines influence brain function and behavior are also discussed along with their implications for diagnosing and treating patients with MDD. Together, these studies highlight the need to develop a biomarker panel for depression that aims to profile diverse peripheral factors that together provide a biological signature of MDD subtypes as well as treatment response.